690 results for ""PhD+2001"+"Professor+of+Bioinformatics"+2012+18000+citations+profile"

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• Transcriptomic analysis of liver CD8+ T cells

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS The liver is bathed in bacterial products including LPS transported from the intestinal portal vasculature, but maintains a state of tolerance exploited by persistent pathogens and tumours1,2,3,4. The cellular basis mediating this tolerance, yet allowing a switch to immunity or immunopathology, needs to be better understood for successful immunotherapy of liver diseases. Here we show that a variable proportion of CD8+T-cells compartmentalised in the human liver co-stain for CD14 and other prototypic myeloid membrane proteins; CD14+CD8+T-cells preferentially accumulate within the donor pool in liver allografts, amongst hepatic virus-specific and tumour-infiltrating responses, and in cirrhotic ascites. CD14+CD8+T-cells exhibit increased turnover, activation and constitutive immunomodulatory features with high homeostatic IL-10/IL-2 production directly ex vivo, and an enhanced capacity to rapidly produce antiviral/anti-tumour cytokines upon TCR engagement. This CD14+CD8+T-cell profile can be recapitulated by acquisition of membrane proteins, including the LPS receptor complex, from mononuclear phagocytes, resulting in augmented tumour killing by TCR-redirected T-cells in vitro. CD14+CD8+T-cells express integrins and chemokine receptors favouring interactions with the local stroma, which can promote their induction through CXCL12. LPS can also increase the frequency of CD14+CD8+T-cells in vitro and in vivo, and skew their function towards the production of chemotactic and regenerative cytokines. Thus, bacterial products in the gut-liver axis and tissue stromal factors can tune liver immunity by driving myeloid instruction of CD8+T-cells with immunomodulatory capacity. For the analysis of the single cell transcriptome two intrahepatic perfusate samples were isolated and frozen at -80 'C for storage prior to transportation to Newcastle, UK. Once thawed in pre-warmed HBSS containing 0.001% DNaseI, intrahepatic leukocytes were sorted by FACS to index classical mononuclear phagocytes (MNP) defined as Singlets, CD3-CD56-CD19-CD14hiHLA-DR+ or CD14± CD8+T-cells as follows: Singlets, CD3+CD56-CD19-CD4-CD8+V7.2- and split in to CD14± based on an isotype control. Single cells were sorted into 96-well skirted LoBind plates (Eppendorf) containing 5 µL lysis buffer (TCL buffer [Qiagen], supplemented with 1% b-mercaptoethanol [Sigma Aldrich; Merck]) on a BD Bioscience FACSFusion. The sorted plates were subsequently immediately sealed, centrifuged, and placed on dry ice to flash-freeze the cell lysate and stored at -80 'C. A modified SMART-seq2 protocol57 was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Study EGAS00001006885

• Genomic and Phenotypic Profile of Sickle Cell Disease in Human Population in Cameroon

  Sickle cell disease (SCD) is caused by a biallelic single nucleotide substitution in the beta-globin gene (HBB), resulting in an amino acid substitution, Glu7Val, formerly known as Glu6Val. An estimated 300,000 babies with SCD are born worldwide each year, with nearly 75% of these births being in sub-Saharan Africa. In Africa, at least 30-50% of children with untreated SCD die before the age of 5 years. Therefore, accelerating the path for novel therapies for SCD through genomics research on fetal hemoglobin (HbF) is critical. Variants in the currently known HbF‐modulating genes/loci, i.e., BCL11A, HBS1L-MYB, and XmnI-HBG2, explain only 10-20% of the variation of HbF levels in African individuals with SCD, compared with nearly 50% of the variation in HbF levels among Europeans. Expanding genomic research in populations of African ancestry could uncover the missing heritability of HbF-promoting loci. This study used the Human Heredity and Health (H3Africa) consortium SNP genotyping array developed from whole genome enriched for common variants in sub-Saharan Africans to investigate genomic variations associated with HbF levels in individuals with sickle cell anemia of the HbSS genotype from Cameroon. Two of the previously described loci, BCL11A and HBS1L-MYB were replicated, while a novel locus on chromosome 13 mapping to FLT1 was uncovered. The study therefore opens up a novel avenue for exploring SCD gene therapy.

  Study phs003748

• Hydroxyurea to Prevent Organ Damage in Children with Sickle Cell Anemia (BABY HUG) Phase III Clinical Trial and Follow-Up Observational Studies I and II

  Sickle cell anemia is associated with substantial morbidity from acute complications and organ dysfunction beginning in the first year of life. In 1995, the Multicenter Study of Hydroxyurea (MSH) (dbGaP phs002348) demonstrated that, in adults, hydroxyurea is effective in decreasing the frequency of painful crises, hospitalizations for crises, acute chest syndrome, and blood transfusions by 50%. The phase I/II study of hydroxyurea in children (HUG KIDS) demonstrated that children have a response to hydroxyurea similar to that seen in adults in terms of increasing fetal hemoglobin levels and total hemoglobin, and decreasing complications associated with sickle cell anemia. In addition, this study demonstrated that the drug does not adversely affect growth and development between the ages of 5 and 15. A pilot study of hydroxyurea (HUSOFT) given to children between the ages of 6 months and 24 months demonstrated that the drug was well tolerated and that the fetal hemoglobin levels rose and remained elevated compared to baseline with continued hydroxyurea administration. A Special Emphasis Panel (SEP) met on April 12, 1996 to review the results of the MSH trial and the progress to date of the HUG KIDS study. The SEP recommended that NHLBI undertake the BABY HUG trial. The BABY HUG Randomized Controlled Trial concluded that hydroxyurea treatment in very young children seemed to have an acceptable safety profile and to reduce complications of sickle cell anemia. However, more data were needed on the long-term safety of hydroxyurea use in very young children. As a result, follow-up studies were initiated. The Follow-Up Study II provided longer follow-up than Follow-Up Study I, and included more assessment types than Follow-Up Study I.The BABY HUG program consisted of three related studies, each of which has associated datasets and bio-specimens. A randomized controlled trial comparing hydroxyurea to placebo in very young children with sickle cell anemia (BABY HUG Randomized Controlled Trial) The first observational follow-up study of children from the randomized controlled trial (BABY HUG Follow-Up Study I). All children in Follow-Up Study I were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child. The second observational follow-up study of children from BABY HUG Follow-Up Study I. All children in Follow-Up Study II were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The purpose of the Randomized Controlled Trial was to determine if hydroxyurea can safely prevent early end organ damage in very young children with sickle cell anemia. The purpose of the BABY HUG Follow-up Study I was to provide structured follow-up of the children enrolled in the BABY HUG Randomized Controlled Trial, in order to characterize the long-term toxicities and unexpected risks (if any) associated with treatment with hydroxyurea at an early age. The objective of Follow-Up Study II was to obtain additional data about the long-term safety and efficacy of hydroxyurea use in children with Sickle Cell Anemia through at least the first decade of life.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002415

• Genome-Wide Analysis of Diffuse Large B-Cell Lymphoma (De Novo and Derived from the High Grade Transformation of Follicular Lymphoma)

  Version 1. Diffuse Large B-cell Lymphoma (DLBCL) represents the most common form of B-cell non-Hodgkin Lymphoma (B-NHL), accounting for ~30% of the de novo diagnoses and also arising as a frequent clinical evolution of Follicular Lymphoma (FL). The molecular pathogenesis of DLBCL is associated with multiple genetic lesions that in part distinctly segregate with individual phenotypic subtypes, suggesting the involvement of distinct oncogenic pathways. However, the lesions identified so far likely represent only a fraction of those necessary for malignant transformation. In order to characterize the entire set of structural alterations present in the DLBCL genome, we have integrated next generation whole exome sequencing analysis of 6 DLBCL cases and genome-wide high-density SNP array analysis of 72 DLBCL cases. We report here that FL and DLBCL harbor frequent structural alterations inactivating CREBBP and, more rarely, EP300, two highly related histone and non-histone acetyltransferases (HATs) that act as transcriptional co-activators in multiple signaling pathways. Overall, ~37% of DLBCL and 36% of FL cases display genomic deletions and/or somatic point mutations that remove or inactivate the HAT coding domain of these two genes. These lesions commonly affect a single allele, suggesting that reduction in HAT dosage is important for lymphomagenesis. We demonstrate specific defects in the acetylation-mediated inactivation of the BCL6 oncoprotein and activation of the p53 tumor suppressor. These results identify CREBBP/EP300 mutations as a major pathogenic mechanism shared by common forms of B-NHL, and have direct implications for the use of drugs targeting acetylation/deacetylation mechanisms. Version 2. Follicular lymphoma (FL) is an indolent, but incurable disease that, in 30-40% of cases, undergoes transformation to an aggressive diffuse large B cell lymphoma (DLBCL). The history of clonal evolution and the mechanisms that underlie transformation to DLBCL (tFL) remain largely unknown. Using whole exome sequencing and copy number analysis of 39 tFL patients, including 12 with paired sequential FL/tFL biopsies, we show that, in most cases, FL and tFL arise by divergent evolution from a common mutated precursor cell through the acquisition of distinct genetic lesions. Mutations in epigenetic modifiers (e.g., MLL2, CREBBP, EZH2, ARID1A) and anti-apoptotic genes (BCL2, FAS) were observed in 93% (36/39) and 78% (30/39) of cases, respectively, and were invariably shared between the two disease phases, suggesting an early acquisition in the common mutated precursor. Conversely, the development of tFL is associated with deregulation of genes involved in the control of cell proliferation, cell cycle progression and DNA damage responses (CDKN2A/2B, MYC, TP53), as well as with an aberrant activity of the somatic hypermutation mechanism. Finally, we show that the genomic profile of tFL shares significant similarities with that of germinal center B-cell type de novo DLBCL, but also displays unique combinations of altered genes that may explain the dismal clinical course of tFL.Version 3. This version includes thirty-five additional de novo DLBCL samples, newly diagnosed, and their paired normal DNA from previously untreated patients, which were analyzed by whole exome sequencing (n=27T and 25N), whole genome sequencing (8T and 10N), and/or targeted HLA-next generation sequencing (n=26T/N pairs) in order to identify genetic alterations associated with loss of surface MHC-II expression.

  Study phs000328

• NHLBI Family Heart Study (FamHS-Visit1 and FamHS-Visit2)

  The Family Heart Study (FamHS) was funded by the National Heart, Lung, and Blood Institute (NHLBI). It was begun in 1992 with the ascertainment of 1,200 families, half randomly sampled, and half selected because of an excess of coronary heart disease (CHD) or risk factor abnormalities as compared with age- and sex-specific population rates (Higgins et al. 1996). The families, with approximately 6,000 individuals, were sampled on the basis of information on probands from four population-based parent studies: the Framingham Heart Study, the Utah Family Tree Study, and two Atherosclerosis Risk in Communities (ARIC) centers (Minneapolis, and Forsyth County, NC). A broad range of phenotypes were assessed at a clinic examination in broad domains of CHD, atherosclerosis, cardiac and vascular function, inflammation and hemostasis, lipids and lipoproteins, blood pressure, diabetes and insulin resistance, pulmonary function, and anthropometry (FamHS Visit 1). Approximately 8 years later, study participants belonging to the largest pedigrees were invited for a second clinical exam (FamHS Visit 2). A total of 2,756 Caucasian subjects in 508 extended families were examined. A two-phase design was adopted for the genome wide association (GWA) study. In phase-1, 1007 subjects were chosen, equally distributed between the upper and lower quartile of age- and sex-adjusted values for coronary artery calcification, assessed by CT scan in Visit 2. These subjects were chosen to be largely unrelated; 34% of the subjects were from unique families, while 200 other subjects had 1 or more siblings selected into the sample, yielding a sample of 465 unrelated subjects. The remaining family members (N=1749) were genotyped in the phase-2 for replication of the top hits from the phase-1. The results presented here represent those for the analysis of the phase-1 case-control sample for variables assessed in FamHS Visit 1 (from 1992 to 1995) and for the variables assessed in FamHS Visit 2 (from 2002 to 2003). All subjects were typed on the Illumina HumMap 550 chip (Phase 1 genotype). Of these, 33 (3.3%) were excluded due to technical errors, call rates below 98%, and discrepancies between reported sex and sex-diagnostic markers. The final sample of 974 subjects have Visit 2 phenotypes, approximately 100 of these do not have Visit 1 phenotypes. There was no significant plate-to-plate variation in allele frequencies. The covariate adjustments were performed separately by sex using cubic polynomial age and clinical centers, and retaining the terms in the stepwise regression analysis that were significant at the 5% level. Extreme outliers (>4 SD from the mean) were set aside, temporarily, for the adjustments. The final phenotypes were computed for all individuals using the best mean regression models and standardizing to 0 mean and unit variance. The FamHS has contributed GWA results in many phenotype domains (antropometric and adiposity, atherosclerosis and coronary heart disease, lipid profile, diabetes and glicemic traits, metabolic syndrome etc) to meta-analyses and various consortia, including Heard-Costa et al. 2009, Köttgen et al. 2010, Teslovich et al. 2010, Nettleton et al. 2010, Lango et al. 2010, Heid et al. 2010, Speliotes et al. 2010, Dupuis et al. 2010, Kraja et al. 2011.

  Study phs000221

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• Idiopathic Pulmonary Fibrosis Network AntiCoagulant Effectiveness in Idiopathic Pulmonary Fibrosis (IPFNet-ACE-IPF-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The ACE-IPF trial tested the hypothesis that treatment with warfarin at recognized therapeutic doses would reduce rates of mortality, hospitalization, and declines in Forced Vital Capacity (FVC) in subjects with Idiopathic pulmonary fibrosis (IPF).Background: IPF is a chronic, progressive lung disease of unknown cause characterized by the histopathologic pattern of usual interstitial pneumonia. The median survival of patients with IPF after the onset of symptoms is 2 to 5 years. Prior animal and human studies in pulmonary fibrosis provide a compelling rationale to examine anticoagulation as a therapeutic approach in IPF. Large epidemiologic studies link IPF with thrombosis-related clinical events, such as an increased risk of acute coronary syndrome and deep vein thrombosis. The suspected causal relationship may extend beyond simple coagulation cascade-induced thrombus formation, as procoagulant enzymes may directly stimulate fibrosis via cell surface receptor - mediated responses.Participants: Patients aged 35 to 80 years with progressive IPF were potentially eligible. Progressive IPF was defined as a history of (1) worsening of dyspnea, or (2) physiologic deterioration defined as an absolute decline of either FVC greater than or equal to 10% or DlCO greater than or equal to 15%, a reduction in arterial oxygen saturation of greater than or equal to 5%, or progression of radiographic findings. Between December 14, 2009 and April 1, 2011, 145 subjects were enrolled: 72 in the warfarin group and 73 in the placebo group. The mean age for the population was 67 years. 27% of the subjects were women and 92% were white.Participants were excluded if they met any of the following criteria: current indication for, or treatment with, warfarin, prasugrel, or clopidogrel combined with aspirin; the presence of an increased risk of bleeding; a recent cerebral vascular accident or gastrointestinal bleeding; any current signs or symptoms of severe, progressive, or uncontrolled comorbid illness; and their presence on the active list for lung transplantation. Design: ACE-IPF was a double-blind, randomized, placebo-controlled trial of warfarin targeting an international normalized ratio (INR) of 2.0 to 3.0 in patients with IPF. Subjects were randomized in a 1:1 ratio to warfarin or matching placebo for a planned treatment period of 48 weeks. Study subjects were provided two strengths of warfarin tablets (1 mg and 2.5 mg) or matching placebos. Subjects measured their INR with encrypted meters at least weekly. Participants were seen at screening, baseline, and at 16, 32, and 48 weeks after enrollment. Home monitoring was validated by plasma INR measurement at the week 1 and 16 visits.The primary outcome was a composite endpoint based on the time to all-cause mortality; nonelective, nonbleeding hospitalization; or a decrease in the absolute FVC greater than or equal to 10% from baseline value. Secondary outcome measures included rates of mortality, hospitalization, respiratory-related hospitalization, acute exacerbation, bleeding, cardiovascular events, and changes over time in FVC, 6-minute walk test distance, DlCO, plasma fibrin D-dimer levels, and quality of life (QOL).Conclusions: The study did not show a benefit for warfarin in the treatment of patients with progressive IPF and was terminated due to excess mortality in the warfarin treatment group. Treatment with warfarin was associated with an increased risk of mortality in an IPF population who lacked other indications for anticoagulation.Reported causes of death indicated 11 of the 14 were respiratory-related in the warfarin group versus three of the three in the placebo group. There were also three cardiovascular deaths in the warfarin group versus none in the placebo group. No deaths were attributed to bleeding. The warfarin group also demonstrated an increased rate of combined all-cause hospitalization and all-cause mortality. (Am J Respir Crit Care Med. 2012 Jul 1;186(1):88-95.)

  Study phs004070

• A Multifactorial Tumor and Immune Cell Profile Determines Response to Immune Checkpoint blockade in Melanoma

  The complex crosstalk between tumor and immune cells during immune checkpoint blockade mandates the development of integrated models that interpret the anti-tumor immune response and predict clinical outcome. We have integrated genome-wide sequence and structural alterations with pre and on-therapy transcriptomic and T cell repertoire features for a cohort of 64 immunotherapy-naïve melanomas treated with anti-PD1 monotherapy or combined anti-PD1 and anti-CTLA4 therapy. While tumor mutation burden (TMB) was associated with improved response to therapy, expressed mutation burden was superior to TMB in predicting outcome. An increased pre-existing T cell density differentiated responding from non-responding tumors independent of therapy. Importantly, T cell repertoire reshaping determined by T cell receptor (TCR) clonotypic regressions and expansions reflected response to therapy such that a more dynamic repertoire predicted improved clinical outcome. Through whole-transcriptome analyses, we discovered differential abundance of B cell subsets in responding tumors, which highlights the importance of the interplay between pre-existing T and B cell immunity in shaping therapeutic response. Tumor temporal trajectories during therapy revealed distinct patterns of molecular response related to expressed mutation elimination or retention that accurately interpreted clinical response. High-dimensional genomic, transcriptomic and immune repertoire data were integrated by both a machine learning and a censored regression approach, resulting in a harmonized multi-modal predictor of response to immune checkpoint blockade. B cell abundance, expressed mutation load and tumor aneuploidy were combined to identify patients at high risk for recurrence, such that high risk patients had a significantly shorter progression-free survival (HR=9.18, 95% CI: 3.14-26.85, p=3.4e-06) especially in the anti-PD1/anti-CTLA4 group (HR=20.34, 95% CI: 4.08-101.32, p=1.68e-06).

  Study EGAS00001004548

• National Eye Institute (NEI) Age-Related Eye Disease Study (AREDS)

  The Age-Related Eye Disease Study (AREDS) was initially designed as a long-term multi-center, prospective study of the clinical course of age-related macular degeneration (AMD) and age-related cataract. In addition to collecting natural history data, AREDS included a clinical trial of high-dose vitamin and mineral supplements for AMD and a clinical trial of high-dose vitamin supplements for cataract. AREDS participants were 55 to 80 years of age at enrollment and had to be free of any illness or condition that would make long-term follow-up or compliance with study medications unlikely or difficult. On the basis of fundus photographs graded by a central reading center, best-corrected visual acuity and ophthalmologic evaluations, 4,757 participants were enrolled in one of several AMD categories, including persons with no AMD. The clinical trials for AMD and cataract were conducted concurrently. AREDS participants were followed on the clinical trials for a median time of 6.5 years. Subsequent to the conclusion of the clinical trials, participants were followed for an additional 5 years and natural history data were collected. The AREDS research design is detailed in AREDS Report 1. AREDS Report 8 contains the mainline results from the AMD trial; AREDS Report 9 contains the results of the cataract trial. Blood samples were also collected from 3,700+ AREDS participants for genetic research. Genetic samples from 600 AREDS participants (200 controls, 200 Neovascular AMD cases, and 200 Geographic Atrophy cases) were selected using data available in March 2005 and then were evaluated with a genome-wide scan. These data, as well as selected phenotypic data, were made available in the dbGaP. DNA from AREDS participants, which is currently being stored in the AREDS Genetic Repository, is available for research purposes. However, not all of the 3,700+ AREDS participants who submitted a blood sample currently have DNA available. In addition to including the data from the genome-wide scan on the 600 original samples, this second version of the AREDS dbGaP database provides a comprehensive set of data tables with extensive clinical information collected for the 4,757 participants who participated in AREDS. The tables include information collected at enrollment/baseline, during study follow-up, fundus and lens pathology, nutritional estimates, quality of life measures and measures of morbidity and mortality. In November 2010, over 72,000 high quality fundus and lens photographs of 595 AREDS participants (of the original 600 selected for the genome-wide scan) were made available in the AREDS dbGaP. In addition to the genome-wide scan data, the fundus and lens grading data for these participants are also available through the AREDS dbGaP. Details about the ocular photographs that are available may be found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs". In January 2012, a measure of daily sunlight exposure was added in a separate "sunlight" table. Furthermore, the "followup" table has been revised. The visual acuity for the right eye was inadvertently missing at odd-numbered visits (01, 03, 05, etc.). This data is now part of the table. In February 2014 over 134,500 high-quality fundus photographs (macular field F2) of 4613 AREDS participants were added to the existing AREDS dbGaP resource. The AREDS dbGaP image archive already contains over 72,000 high quality fundus and lens photographs of 595 AREDS participants for whom dbGaP-accessible genotype data exist. Information about the available ocular photographs found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs" has been updated with an addendum. It is hoped that this resource will better help researchers understand two important diseases that affect an aging population. These data may be applied to examination and inference on genetic and genetic-environmental bases for age-related diseases of public health significance and may also help elucidate the clinical course of both conditions, generate hypotheses, and aid in the design of clinical trials of preventive interventions. Definitions of Final AMD Phenotype Categories Please see phd001138.1 for a detailed description of how AREDS participants' final AMD phenotype was categorized. User's Guide for AREDS Phenotype Data A detailed User's Guide for the AREDS phenotype data is available. This User's Guide is meant to be a comprehensive document which explains the complexities of the AREDS data. It is recommended that all researchers using AREDS phenotype data make use of this User's Guide.

  Study phs000001

• National Cancer Institute (NCI) TARGET: Therapeutically Applicable Research to Generate Effective Treatments

  The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative seeks to accelerate research in novel marker and drug development, along with understanding the molecular basis of pediatric malignancy, through identification of genomic changes associated with the following childhood cancers: Acute Lymphoblastic Leukemia (ALL) - A fast-growing type of blood cancer in which too many immature white blood cells are found in the blood and bone marrow. Acute Myeloid Leukemia (AML), including AML Induction Failure cases (AML-IF) - Another type of blood cancer marked by too many myeloblasts, an alternate type of immature white blood cell, are found in the blood and bone marrow. Upon diagnosis, AML patients without high-risk genetic markers undergo standard chemotherapy regimen, called the primary induction phase, to eliminate most cancer cells and induce a remission state. Clear Cell Sarcoma of the Kidney (CCSK) - A rare type of kidney cancer, in which the inside of the cells looks clear when viewed under a microscope. Clear cell sarcoma can spread from the kidney to other organs, most commonly the bone, but also including the lungs, brain, and soft tissues of the body. Neuroblastoma (NBL) - Cancer of cells of the sympathetic nervous system. Cancer Model Systems (MDLS), including PPTP - MDLS includes acute leukemia cell lines and xenografts with matched primary and/or relapsed tumor information, NBL cell lines and xenografts with matched controls, kidney tumor cell lines, normal brain tissues, and embryonic stem cell lines that were sequenced for some TARGET disease projects. Osteosarcoma (OS) - A cancer of the bone that primarily affects children and adolescents. Rhabdoid Tumor (RT) - A rare, fast-growing cancer that usually forms in the kidney or central nervous system (the brain and spinal cord) but can also form in soft tissues in other areas of the body. Rhabdoid tumors tend to spread quickly, are hard to treat, and have a poor prognosis. Wilms' Tumor (WT) - A cancer of cells in the kidney that can spread to the liver, lung and lymph nodes. More information can be found about each TARGET subproject by following the links on the top of this page. Together these cancers account for the majority of the more than 10,000 childhood cancer cases diagnosed in the United States each year. TARGET has employed a set of advanced and complementary genome analysis technologies, including large scale 2nd and 3rd generation genome sequencing, to strategically characterize alterations in both gene expression and in genomic structure (such as deletions and amplification) that are involved in childhood cancers. The goal of this coordinated effort has been to create a comprehensive genomic and transcriptomic profile of each cancer. Integrated analysis of the TARGET data has identified those genes that are either altered in their expression level or mapped to the chromosome regions of deletion/amplification/translocation, as these genes represent strong candidates for therapeutic targeting. To learn more about the TARGET project, which is now completed, visit the website at https://www.cancer.gov/ccg/research/genome-sequencing/target. TARGET data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the TARGET Publication Pages at the GDC (Please see the "Supplemental Links" section of any TARGET publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original TARGET research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data - gene expression, copy number variation, epigenetics, targeted sequencing), as well as higher level data generated by the GDC. Please see the TARGET Use and Publication Guidelines for updated details on the sharing of any TARGET substudy data, including how to cite TARGET.

  Study phs000218

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Pomalidomide for the Treatment of Bleeding in HHT (PATH-HHT)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine efficacy (reduction in severity of epistaxis), tolerability, and improvement in quality of life of pomalidomide compared to placebo after 24 weeks of treatment.Background: This study addresses the efficacy of pomalidomide in the treatment of epistaxis in patients with Hereditary Hemorrhagic Telangiectasia (HHT) who have anemia and/or require blood transfusion or iron infusion for treatment of bleeding-induced anemia and iron deficiency. HHT (also known as Osler-Weber-Rendu disease) is an inherited bleeding disorder. Over 95% of patients develop recurrent epistaxis, which may be severe and result in chronic anemia, need for iron infusions and blood transfusions, substantial psychiatric comorbidity (including depression and post-traumatic stress disorder) and reduction in health-related quality of life (HRQoL). HHT is clinically diagnosed using the Curacao criteria, which consists of 1) spontaneous and recurrent epistaxis, 2) telangiectasias at characteristic sites, 3) visceral arteriovenous malformations (AVMs) or telangiectasias, and 4) a first degree relative with HHT (inheritance is usually autosomal dominant). Patients with three criteria are considered to have definite HHT, and those with 2 criteria probable HHT. HHT affects approximately 1 in 3,800 individuals. Significant manifestations of HHT often do not appear until the third or fourth decades, sometimes later.Participants: 144 patients from 11 clinical centers were enrolled.Design: This is a multi-center, double blind, randomized placebo-controlled trial that investigated the efficacy and safety of pomalidomide in patients with HHT and chronic epistaxis leading to iron-deficiency anemia or requiring intravenous iron infusions or blood transfusion.Screening evaluation included the Epistaxis Severity Score (ESS) with three-month recall, which reflected the patient's history of epistaxis and bleeding over the prior three months, as well as detailed review of iron infusion and red cell transfusion over the preceding six months. Eligible patients were provided a diary to record the duration of each epistaxis event that occurred during the 4 weeks prior to the baseline visit, and then returned for the baseline randomization visit, at which time patients underwent genetic testing, if this had not been previously performed, and completed an ESS with 4-week recall and quality of life assessments. Patients were randomized 2:1, stratified by study site, to either pomalidomide 4 mg/day or matching placebo during each of six 28 day cycles (24 weeks). Patients were seen every four weeks during treatment, and at a 4-week post-treatment follow-up visit to measure the ESS (with 4-week recall), laboratory assessments including iron stores and need for iron infusion, CBC, and metabolic profile. Patients were assessed for adverse events (AE) throughout the study. Treatment dosage could be reduced, or temporarily or permanently discontinued following AE-specific guidelines related to fatigue, cytopenias or other toxicities.Quality of life assessments were completed at baseline, and the 12- and 24-week visits, and the 4-week post-treatment follow-up visit using validated NIH instruments of 1) Neuro-QOL satisfaction with social roles and activities, 2) PROMIS emotional distress – depression, and 3) PROMIS fatigue, and the HHT-specific quality of life instrument developed specifically for this study. The effect of pomalidomide on duration of epistaxis was assessed via diary between weeks 8-12, 20-24 and the 4-week post-treatment period.Conclusions: Among patients with HHT, pomalidomide treatment resulted in a significant, clinically relevant reduction in epistaxis severity. No unexpected safety signals were identified (Al-Samkari et al., 2024; PMID: 39292928)

  Study phs003948

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606

• All you need to know about our new DAC Portal

  With the DAC Portal, it is possible to streamline the process of managing access to sensitive data, ensuring that researchers have the necessary resources to advance scientific discovery while maintaining the highest standards of data protection and privacy. We know that, as a new tool, its first use can be complex. For this reason, in this article we will try to show all the elements of interest. Enjoy! Credentials: who needs to create a new user to access the DAC Portal and who doesn't? Only new users (since September the 12th) need to create an EGA account to access the DAC Portal. The EGA team went one step ahead by creating EGA accounts for former DAC members to login to the DAC Portal. These accounts are linked to the personal email used in the DAC structure: To check the linked email, DAC members can paste the DAC ID right after this link: https://metadata.ega-archive.org/dacs/ (e.g. https://metadata.ega-archive.org/dacs/EGAC00001002543) In case of password oblivion, it is possible to set a new one. All the process is channelled through the personal email. Some DAC members may be interested in updating the DAC email. This action can be done contacting our Helpdesk team. For the correct functioning of the DAC Portal, users must add the missing information of the DAC Profile. For a deeper dive, check out our documentation. The first step: knowing your workspace on the Portal Once logged in to the platform using the EGA User credentials, note the sections available: DACs and Policies. In the first one it is possible to check all user's registered DACs by default. It provides a comprehensive overview of each DAC, including its EGA accessions (EGAC), title, status, and the number of data access requests associated with each DAC. Whereas the Policies section is where users can manage and view all their registered policies, along with their associated EGA accessions, links, and titles. A drop-down menu is available with shortcuts to the most useful pages in the top right corner. It is possible to check DACs and policies, as well as creating new ones. In this menu, users can also contact the Helpdesk team using the “Need Help?” section to make inquiries about DACs and policies. Comprehending the DACs list & making the most of all the features Colours are crucial in the DAC's section as they will indicate the user role and the status in every committee, namely: Yellow: you are the administrator of the DAC and have full control to add other contacts, modify the content, and manage data access requests. Orange: you are a member of the DAC and have the authority to manage data access requests but cannot make any changes to the content. Blue: you have been invited to join the DAC and need to either accept or decline the invitation. Grey: the DAC is currently pending validation by the EGA Helpdesk team. Red: the DAC has been declined by the EGA Helpdesk team. Discover more information on how to view the message from Helpdesk containing the declination reason or how to validate or reject a DAC invitation by taking the tour of the DAC Portal. How to create, register and edit a DAC Creating a DAC is an easy process that only requires users to complete the necessary information. After that, the EGA Helpdesk team will review the proposal and validate the proposal. Once the DAC is validated it is possible for authorised users with admin role to edit it at any time, ensuring that all information and contacts associated with the committee is accurate and up to date. Membership management is controlled by searching for the EGA user looking for their username, email, or organisation. Please, note that for a person's details to appear in this search engine, they must have registered as a EGA user. Data Access Committee administrators manage two types of permissions that apply to contacts: Main contact and Role. Both can be modified at any time: Main contact refers to the primary person we firstly contact for any inquiry about the DAC (please, note that we can contact all DAC members, and this refers to the person we will contact first). Role defines the actions that can be taken by each contact. There are two possible status, admin and member, details of which can be found in the Take the Tour. Keep in mind that, to save the modifications, it is always necessary to click on “Update”. Moreover, it is also possible to delete any contact in a DAC whenever it is needed. The data request process: how to manage access requests The data request process is now channelled through the EGA website. Once a user sends a request access, the petition will go directly to the DAC Portal profile of the DAC members liked to the requested dataset. Whenever a request is received, a sand clock symbol will be displayed next to the DAC responsible for the dataset involved. By clicking on the DAC, it is possible to discover more information about requester(s). In this section, DAC Portal users will also be able to modify the display of the data access requests. It is possible to group requests by dataset accession or username, depending on the user preferences. Additionally, it is possible to isolate specific requests by user or dataset. To accept a request, users must slide the button to the right. Once the button turns green, it signifies that the request is accepted; the requester will be granted access to the requested dataset. To make lives easier, we have implemented a “Select all” button to easily accept or revoke multiple requests at once. To decline requests, it is necessary to slide the button to the left. A red button means the requester will not be granted access to the dataset. The DAC Portal will always ask to submit the reason why the data access was denied. Please, note that any decision, grant or denial, must be confirmed clicking the "Apply" button. This will update the status of the request and notify the requester accordingly. Taking control of the activity in the DAC Portal: checking the requests history The History button is a useful feature that allows users to access a list of all the requests that have been granted. This is especially useful for auditing purposes, as it enables to keep track of who has been granted access to the data and when. To facilitate control for those users with several requests we have included a filtering option. It allows to filter requests by user, mail, dataset, EGA ID, and date (these are combinable to boost the search). Don't forget about policies: creation, management, and update Similarly to the DACs section, in the Policies one users can manage and view all their registered policies. By clicking on any policy, it is possible to view its details as well as making any necessary updates or modifications. The sheets symbol and its adjacent number indicate the quantity of objects using a policy. By clicking in the location symbol users will go directly to the DAC page on the DAC Portal to see more information about that DAC. DAC Portal users can create new policies. The first step requires to link the policy to a registered DAC. After defining the title, users can either add a link to an external URL containing terms & conditions or write the policy content directly on the DAC Portal. Keep in mind that both options can be included. Data Use Ontology (DUO) codes can be added to new policies. These codes are used to specify the permitted and prohibited uses of the data. Please, note that some of them require a modifier to provide additional specificity. Find out more by checking out this specific content on the DAC Portal Tour. Policies can be modified at any given time by clicking on one registered policy, which will display the current information.

  Blog new-dac-portal

• National Cancer Institute (NCI) Biospecimen Pre-analytical Variables (BPV) Analysis

  The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the "Substudies" box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80°C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors. Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors. Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80°C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80°C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors. Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors. Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors. Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80°C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors. mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors. The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001304 Biospecimen PV cohort. phs001634 CIT mRNA phs001635 CNV aCGH phs001636 Fixation Delay phs001637 Global Metabolite Profiling phs001638 mRNA TaqMan phs001639 NGS phs001640 Tumor Storage

  Study phs001304

• Gene Expression and Regulatory Networks in Human Leukocytes - Immunological Variation Consortium

  Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified naive CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal data group, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, NanoString technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies. Additionally, over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, in a second study we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (ATAC-QTLs). ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression. In another study we analyzed RNA-seq profiles from primary CD4+ T cells of two healthy donors at six time points from 0 to 72 hours after stimulation with bead-bound antibodies against CD3 and CD28.

  Study phs000815

• Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

  Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

  Blog safe-access-to-sensitive-human-data-federated-ega

• Better Outcomes for Children: GWAS from Cincinnati Children's Hospital Medical Center (CCHMC) - eMERGE Phase II data - (dbGaP Deposit 1)

  This submission includes genotyping data from 6 separate cohorts (named A-E here), each is described in separate paragraphs below. Cohort A) Autism is a neurodevelopmental disorder that affects 1.5 million people in the United States, at an estimated lifetime cost of $4 million. It is part of Pervasive Developmental Disorder characterized by impairments in communication, language and reciprocal social interaction, and by unusual patterns of restricted and repetitive interests or behaviors. Autism, or autistic disorder, is the most severe form of the disease which has a wide range of symptom severity encompassed by the more inclusive term, Autism Spectrum Disorder (ASD). The prevalence of Autistic Disorder is currently estimated to be 4 per 1000, affecting 4 times more boys than girls. Susceptibility to autism is clearly attributable to genetic factors but the extensive clinical and genetic heterogeneity within the disorder have hindered efforts at genetic dissection. Identifying the genetic variants that contribute to this highly heritable disease is crucial to advancing research on autism. Reported concordance rates among monozygotic twins range from 60% − 90% and heritability of autism has been estimated to be 90% or greater. Identifying genetic variants that contribute to this highly heritable disease is crucial to advancing research on autism. Cohort B) The long-term objective of this research is to determine the molecular genetic basis of Cardiovascular (CV) disease in the young; this study seeks to identify gene mutations that cause "structural heart defects". Every year in the USA, 32,000 individuals are born with CV malformations; approximately 20% die during the first year of life. Another 30,000 young people develop a disturbance of cardiac rhythm or conduction. In addition, the life expectancy of another 40,000 young people is shortened by other forms of CV disease. It is becoming more apparent that in spite of the success in diagnosis and treatment, very little is known about the causes of CV disease in the young; understanding the causes will permit insight into the pathophysiologic basis of disease and allow definition of disease risk - two critical elements for disease prevention. Disease prevention and/or risk modification promises to be the new frontier in the management of CV disease in the young. Cohort C) Eosinophilic Esophagitis (EE) is one of the manifestations of eosinophilic gastrointestinal inflammation which have profound effects on a patient's health and development. Results of epidemiologic studies performed through our center demonstrate that eosinophil-associated gastrointestinal disease is not an uncommon entity. While the epidemiology of eosinophilic esophagitis has not been thoroughly studied until recently, there appears to be a significant increase in the diagnosis of EE in the last decade. Based on our research, this mainly reflects increased disease recognition, but there is also a bona-fide increase in disease incidence which coincides with the increasing incidence of asthma and allergic diseases in the industrialized world. In addition, many patients with intractable symptoms thought in the past to represent atypical GERD or other disorders are now being recognized as having EE. Diagnosis of EE requires endoscopy and biopsies to document the characteristic histologic findings of esophageal eosinophilia. In general, this study proposed to elucidate the mechanisms underlying eosinophil growth, survival, migration, and function, and to investigate and further characterize the pathophysiology of, clinical manifestations of, and spectrum of disease severity of eosinophilic esophagitis in humans. Cohort D) Juvenile idiopathic arthritis (JIA) is a debilitating complex genetic disorder characterized by inflammation of the joints and other tissues and shares histopathological features with other autoimmune diseases. It is considered a complex genetic disorder. There are more than 50,000 children with JIA in the USA, approximately 1 per 1000 births, which is about the same incidence as juvenile diabetes. It is believed that genes in the major histocompatibility complex (MHC) play a role in defining genetic risk, and it can be hypothesized that loci in other chromosomal regions are involved in conferring risk in JIA. These candidate chromosomal regions can be identified using genome wide association analyses. The long-term goal is a comprehensive understanding of the genetic basis of these disabling arthropathies for which the molecular basis is not presently understood. The results of recent GWAS for Caucasian JIA were recently published in Arthritis Rheum. 2012 Feb 21 (Published online, PMID=22354554). Cohort E) Childhood Absence Epilepsy (CAE) is characterized by very frequent (several to many per day) absence seizures in an otherwise normal child with an EEG usually demonstrating 3 Hz bilateral, synchronous, symmetrical spikewaves pattern with normal background activity. CAE occurs in 10% to 15% of all children with epilepsy with an annual incidence of 6.3 to 8/100,000 in children <15 years of age. Females are more affected than males. Epilepsy onset is typically between the ages of 4 to 8 years with a peak incidence of 6 to 7 years. CAE does not start after age 13 years. The primary objective of this study is: To identify the optimal anticonvulsant (i.e. the antiepileptic drug (AED) with highest rate of seizure control and lowest incidence of treatment limiting toxicity) used for the initial treatment of children with Childhood Absence Epilepsy (CAE). The secondary objectives are: To determine the pharmacogenetic and other non-heritable factors underlying the interindividual variation in anticonvulsant response efficacy and toxicity. To define and contrast the effects of ethosuximide, lamotrigine, and valproic acid monotherapy on cognition (attention), behavior and quality of life in children with Childhood Absence Epilepsy. Cohort F) Cincinnati Controls. These are local healthy children selected to be representative of the population of Cincinnati with respect to gender and ancestry. Cohort G) Cytogenetics cases are ascertained by the clinical request to obtain cytogenetic analysis. The platform used included genotyping data which are then available for genome wide association analysis

  Study phs000494

• Transcriptomic Profile of Whole Blood Cells from Elderly Subjects fed Probiotic Bacteria Lactobacillus rhamnosus GG ATCC 53103 (LGG) in a Phase I Open Label Study

  Open label study to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) in elderly subjects. Fifteen healthy elderly volunteers, ages 65-80 were enrolled in a study in which they received LGG capsules containing 1 x 1010 CFU, twice daily for 28 days and were followed through day 56. The study subjects completed a daily diary, a telephone call on study days 3, 7 and 14 and study visits at the Massachusetts General Hospital Clinical Research Center at baseline, day 28 and day 56. During each visit, the subject diary, interim history, potential adverse effects and concomitant medications were reviewed and vital signs and a physical examination were performed. Routine blood tests were obtained to monitor for safety during visits and nasopharyngeal and stool samples were collected for microbiome analysis. Volunteers interested in participating in the effect of LGG probiotic on the Human whole Blood Transcriptome substudy also had blood drawn for DNA and RNA extraction, after signing the substudy consent form. The main objective of the study was to assess the safety and tolerability of 2 x 1010 CFU LGG administered orally to elderly subjects for 28 days. Secondary objectives were to evaluate the richness and microbial diversity in nasopharyngeal and stool specimens using pyrosequencing, and to compare cytokine production in response to bacterial stimulation by following the kinetics of mRNA expression of pro and anti-inflammatory genes and different signaling pathways, in relation to changes in stool Bifidobacterium and Lactobacillus spp. The study was reviewed and approved by the Partners Human Research Committee (IRB # 2010P001695) and was registered at ClinicalTrials.gov (NCT01274598). The main results regarding the clinical signs and safety of intervention is published in PLoS One. 2014 Dec 1;9(12):e113456. doi: 10.1371/journal.pone.0113456. eCollection 2014. PMID: 25438151. RNA sequencing for transcriptome analysis was only done in 11 of the 15 subjects as RNA integrity and quantity had to be optimal for the three times where blood was collected in order for a subject to be included in the study. The information regarding the microbiome data associated with this study is presented in a separate paper, which can be found at dbGaP study accession, phs000896, and PMID: 25873374.

  Study phs000928

• OncoArray: Prostate Cancer

  Original description of the study: From ELLIPSE (linked to the PRACTICAL consortium), we contributed ~78,000 SNPs to the OncoArray. A large fraction of the content was derived from the GWAS meta-analyses in European ancestry populations (overall and aggressive disease; ~27K SNPs). We also selected just over 10,000 SNPs from the meta-analyses in the non-European populations, with a majority of these SNPs coming from the analysis of overall prostate cancer in African ancestry populations as well as from the multiethnic meta-analysis. A substantial fraction of SNPs (~28,000) were also selected for fine-mapping of 53 loci not included in the common fine-mapping regions (tagging at r2>0.9 across ±500kb regions). We also selected a few thousand SNPs related with PSA levels and/or disease survival as well as SNPs from candidate lists provided by study collaborators, as well as from meta-analyses of exome SNP chip data from the Multiethnic Cohort and UK studies. The Contributing Studies: Aarhus: Hospital-based, Retrospective, Observational. Source of cases: Patients treated for prostate adenocarcinoma at Department of Urology, Aarhus University Hospital, Skejby (Aarhus, Denmark). Source of controls: Age-matched males treated for myocardial infarction or undergoing coronary angioplasty, but with no prostate cancer diagnosis based on information retrieved from the Danish Cancer Register and the Danish Cause of Death Register. AHS: Nested case-control study within prospective cohort. Source of cases: linkage to cancer registries in study states. Source of controls: matched controls from cohort ATBC: Prospective, nested case-control. Source of cases: Finnish male smokers aged 50-69 years at baseline. Source of controls: Finnish male smokers aged 50-69 years at baseline BioVu: Cases identified in a biobank linked to electronic health records. Source of cases: A total of 214 cases were identified in the VUMC de-identified electronic health records database (the Synthetic Derivative) and shipped to USC for genotyping in April 2014. The following criteria were used to identify cases: Age 18 or greater; male; African Americans (Black) only. Note that African ancestry is not self-identified, it is administratively or third-party assigned (which has been shown to be highly correlated with genetic ancestry for African Americans in BioVU; see references). Source of controls: Controls were identified in the de-identified electronic health record. Unfortunately, they were not age matched to the cases, and therefore cannot be used for this study. Canary PASS: Prospective, Multi-site, Observational Active Surveillance Study. Source of cases: clinic based from Beth Israel Deaconness Medical Center, Eastern Virginia Medical School, University of California at San Francisco, University of Texas Health Sciences Center San Antonio, University of Washington, VA Puget Sound. Source of controls: N/A CCI: Case series, Hospital-based. Source of cases: Cases identified through clinics at the Cross Cancer Institute. Source of controls: N/A CerePP French Prostate Cancer Case-Control Study (ProGene): Case-Control, Prospective, Observational, Hospital-based. Source of cases: Patients, treated in French departments of Urology, who had histologically confirmed prostate cancer. Source of controls: Controls were recruited as participating in a systematic health screening program and found unaffected (normal digital rectal examination and total PSA < 4 ng/ml, or negative biopsy if PSA > 4 ng/ml). COH: hospital-based cases and controls from outside. Source of cases: Consented prostate cancer cases at City of Hope. Source of controls: Consented unaffected males that were part of other studies where they consented to have their DNA used for other research studies. COSM: Population-based cohort. Source of cases: General population. Source of controls: General population CPCS1: Case-control - Denmark. Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPCS2: Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPDR: Retrospective cohort. Source of cases: Walter Reed National Military Medical Center. Source of controls: Walter Reed National Military Medical Center ACS_CPS-II: Nested case-control derived from a prospective cohort study. Source of cases: Identified through self-report on follow-up questionnaires and verified through medical records or cancer registries, identified through cancer registries or the National Death Index (with prostate cancer as the primary cause of death). Source of controls: Cohort participants who were cancer-free at the time of diagnosis of the matched case, also matched on age (±6 mo) and date of biospecimen donation (±6 mo). EPIC: Case-control - Germany, Greece, Italy, Netherlands, Spain, Sweden, UK. Source of cases: Identified through record linkage with population-based cancer registries in Italy, the Netherlands, Spain, Sweden and UK. In Germany and Greece, follow-up is active and achieved through checks of insurance records and cancer and pathology registries as well as via self-reported questionnaires; self-reported incident cancers are verified through medical records. Source of controls: Cohort participants without a diagnosis of cancer EPICAP: Case-control, Population-based, ages less than 75 years at diagnosis, Hérault, France. Source of cases: Prostate cancer cases in all public hospitals and private urology clinics of département of Hérault in France. Cases validation by the Hérault Cancer Registry. Source of controls: Population-based controls, frequency age matched (5-year groups). Quotas by socio-economic status (SES) in order to obtain a distribution by SES among controls identical to the SES distribution among general population men, conditionally to age. ERSPC: Population-based randomized trial. Source of cases: Men with PrCa from screening arm ERSPC Rotterdam. Source of controls: Men without PrCa from screening arm ERSPC Rotterdam ESTHER: Case-control, Prospective, Observational, Population-based. Source of cases: Prostate cancer cases in all hospitals in the state of Saarland, from 2001-2003. Source of controls: Random sample of participants from routine health check-up in Saarland, in 2000-2002 FHCRC: Population-based, case-control, ages 35-74 years at diagnosis, King County, WA, USA. Source of cases: Identified through the Seattle-Puget Sound SEER cancer registry. Source of controls: Randomly selected, age-frequency matched residents from the same county as cases Gene-PARE: Hospital-based. Source of cases: Patients that received radiotherapy for treatment of prostate cancer. Source of controls: n/a Hamburg-Zagreb: Hospital-based, Prospective. Source of cases: Prostate cancer cases seen at the Department of Oncology, University Hospital Center Zagreb, Croatia. Source of controls: Population-based (Croatia), healthy men, older than 50, with no medical record of cancer, and no family history of cancer (1st & 2nd degree relatives) HPFS: Nested case-control. Source of cases: Participants of the HPFS cohort. Source of controls: Participants of the HPFS cohort IMPACT: Observational. Source of cases: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has been diagnosed with prostate cancer during the study. Source of controls: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has not been diagnosed with prostate cancer during the study. IPO-Porto: Hospital-based. Source of cases: Early onset and/or familial prostate cancer. Source of controls: Blood donors Karuprostate: Case-control, Retrospective, Population-based. Source of cases: From FWI (Guadeloupe): 237 consecutive incident patients with histologically confirmed prostate cancer attending public and private urology clinics; From Democratic Republic of Congo: 148 consecutive incident patients with histologically confirmed prostate cancer attending the University Clinic of Kinshasa. Source of controls: From FWI (Guadeloupe): 277 controls recruited from men participating in a free systematic health screening program open to the general population; From Democratic Republic of Congo: 134 controls recruited from subjects attending the University Clinic of Kinshasa KULEUVEN: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases recruited at the University Hospital Leuven. Source of controls: Healthy males with no history of prostate cancer recruited at the University Hospitals, Leuven. LAAPC: Subjects were participants in a population-based case-control study of aggressive prostate cancer conducted in Los Angeles County. Cases were identified through the Los Angeles County Cancer Surveillance Program rapid case ascertainment system. Eligible cases included African American, Hispanic, and non-Hispanic White men diagnosed with a first primary prostate cancer between January 1, 1999 and December 31, 2003. Eligible cases also had (a) prostatectomy with documented tumor extension outside the prostate, (b) metastatic prostate cancer in sites other than prostate, (c) needle biopsy of the prostate with Gleason grade ≥8, or (d) needle biopsy with Gleason grade 7 and tumor in more than two thirds of the biopsy cores. Eligible controls were men never diagnosed with prostate cancer, living in the same neighborhood as a case, and were frequency matched to cases on age (± 5 y) and race/ethnicity. Controls were identified by a neighborhood walk algorithm, which proceeds through an obligatory sequence of adjacent houses or residential units beginning at a specific residence that has a specific geographic relationship to the residence where the case lived at diagnosis. Malaysia: Case-control. Source of cases: Patients attended the outpatient urology or uro-onco clinic at University Malaya Medical Center. Source of controls: Population-based, age matched (5-year groups), ascertained through electoral register, Subang Jaya, Selangor, Malaysia MCC-Spain: Case-control. Source of cases: Identified through the urology departments of the participating hospitals. Source of controls: Population-based, frequency age and region matched, ascertained through the rosters of the primary health care centers MCCS: Nested case-control, Melbourne, Victoria. Source of cases: Identified by linkage to the Victorian Cancer Registry. Source of controls: Cohort participants without a diagnosis of cancer MD Anderson: Participants in this study were identified from epidemiological prostate cancer studies conducted at the University of Texas MD Anderson Cancer Center in the Houston Metropolitan area. Cases were accrued in the Houston Medical Center and were not restricted with respect to Gleason score, stage or PSA. Controls were identified via random-digit-dialing or among hospital visitors and they were frequency matched to cases on age and race. Lifestyle, demographic, and family history data were collected using a standardized questionnaire. MDACC_AS: A prospective cohort study. Source of cases: Men with clinically organ-confined prostate cancer meeting eligibility criteria for a prospective cohort study of active surveillance at MD Anderson Cancer Center. Source of controls: N/A MEC: The Multiethnic Cohort (MEC) is comprised of over 215,000 men and women recruited from Hawaii and the Los Angeles area between 1993 and 1996. Between 1995 and 2006, over 65,000 blood samples were collected from participants for genetic analyses. To identify incident cancer cases, the MEC was cross-linked with the population-based Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii, and unaffected cohort participants with blood samples were selected as controls MIAMI (WFPCS): Prostate cancer cases and controls were recruited from the Departments of Urology and Internal Medicine of the Wake Forest University School of Medicine using sequential patient populations as described previously (PMID:15342424). All study subjects received a detailed description of the study protocol and signed their informed consent, as approved by the medical center's Institutional Review Board. The general eligibility criteria were (i) able to comprehend informed consent and (ii) without previously diagnosed cancer. The exclusion criteria were (i) clinical diagnosis of autoimmune diseases; (ii) chronic inflammatory conditions; and (iii) infections within the past 6 weeks. Blood samples were collected from all subjects. MOFFITT: Hospital-based. Source of cases: clinic based from Moffitt Cancer Center. Source of controls: Moffitt Cancer Center affiliated Lifetime cancer screening center NMHS: Case-control, clinic based, Nashville TN. Source of cases: All urology clinics in Nashville, TN. Source of controls: Men without prostate cancer at prostate biopsy. PCaP: The North Carolina-Louisiana Prostate Cancer Project (PCaP) is a multidisciplinary population-based case-only study designed to address racial differences in prostate cancer through a comprehensive evaluation of social, individual and tumor level influences on prostate cancer aggressiveness. PCaP enrolled approximately equal numbers of African Americans and Caucasian Americans with newly-diagnosed prostate cancer from North Carolina (42 counties) and Louisiana (30 parishes) identified through state tumor registries. African American PCaP subjects with DNA, who agreed to future use of specimens for research, participated in OncoArray analysis. PCMUS: Case-control - Sofia, Bulgaria. Source of cases: Patients of Clinic of Urology, Alexandrovska University Hospital, Sofia, Bulgaria, PrCa histopathologically confirmed. Source of controls: 72 patients with verified BPH and PSA<3,5; 78 healthy controls from the MMC Biobank, no history of PrCa PHS: Nested case-control. Source of cases: Participants of the PHS1 trial/cohort. Source of controls: Participants of the PHS1 trial/cohort PLCO: Nested case-control. Source of cases: Men with a confirmed diagnosis of prostate cancer from the PLCO Cancer Screening Trial. Source of controls: Controls were men enrolled in the PLCO Cancer Screening Trial without a diagnosis of cancer at the time of case ascertainment. Poland: Case-control. Source of cases: men with unselected prostate cancer, diagnosed in north-western Poland at the University Hospital in Szczecin. Source of controls: cancer-free men from the same population, taken from the healthy adult patients of family doctors in the Szczecin region PROCAP: Population-based, Retrospective, Observational. Source of cases: Cases were ascertained from the National Prostate Cancer Register of Sweden Follow-Up Study, a retrospective nationwide cohort study of patients with localized prostate cancer. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PROGReSS: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases from the Hospital Clínico Universitario de Santiago de Compostela, Galicia, Spain. Source of controls: Cancer-free men from the same population ProMPT: A study to collect samples and data from subjects with and without prostate cancer. Retrospective, Experimental. Source of cases: Subjects attending outpatient clinics in hospitals. Source of controls: Subjects attending outpatient clinics in hospitals ProtecT: Trial of treatment. Samples taken from subjects invited for PSA testing from the community at nine centers across United Kingdom. Source of cases: Subjects who have a proven diagnosis of prostate cancer following testing. Source of controls: Identified through invitation of subjects in the community. PROtEuS: Case-control, population-based. Source of cases: All new histologically-confirmed cases, aged less or equal to 75 years, diagnosed between 2005 and 2009, actively ascertained across Montreal French hospitals. Source of controls: Randomly selected from the Provincial electoral list of French-speaking men between 2005 and 2009, from the same area of residence as cases and frequency-matched on age. QLD: Case-control. Source of cases: A longitudinal cohort study (Prostate Cancer Supportive Care and Patient Outcomes Project: ProsCan) conducted in Queensland, through which men newly diagnosed with prostate cancer from 26 private practices and 10 public hospitals were directly referred to ProsCan at the time of diagnosis by their treating clinician (age range 43-88 years). All cases had histopathologically confirmed prostate cancer, following presentation with an abnormal serum PSA and/or lower urinary tract symptoms. Source of controls: Controls comprised healthy male blood donors with no personal history of prostate cancer, recruited through (i) the Australian Red Cross Blood Services in Brisbane (age range 19-76 years) and (ii) the Australian Electoral Commission (AEC) (age and post-code/ area matched to ProsCan, age range 54-90 years). RAPPER: Multi-centre, hospital based blood sample collection study in patients enrolled in clinical trials with prospective collection of radiotherapy toxicity data. Source of cases: Prostate cancer patients enrolled in radiotherapy trials: CHHiP, RT01, Dose Escalation, RADICALS, Pelvic IMRT, PIVOTAL. Source of controls: N/A SABOR: Prostate Cancer Screening Cohort. Source of cases: Men >45 yrs of age participating in annual PSA screening. Source of controls: Males participating in annual PSA prostate cancer risk evaluations (funded by NCI biomarkers discovery and validation grant), recruited through University of Texas Health Science Center at San Antonio and affiliated sites or through study advertisements, enrolment open to the community SCCS: Case-control in cohort, Southeastern USA. Prospective, Observational, Population-based. Source of cases: SCCS entry population. Source of controls: SCCS entry population SCPCS: Population-based, Retrospective, Observational. Source of cases: South Carolina Central Cancer Registry. Source of controls: Health Care Financing Administration beneficiary file SEARCH: Case-control - East Anglia, UK. Source of cases: Men < 70 years of age registered with prostate cancer at the population-based cancer registry, Eastern Cancer Registration and Information Centre, East Anglia, UK. Source of controls: Men attending general practice in East Anglia with no known prostate cancer diagnosis, frequency matched to cases by age and geographic region SNP_Prostate_Ghent: Hospital-based, Retrospective, Observational. Source of cases: Men treated with IMRT as primary or postoperative treatment for prostate cancer at the Ghent University Hospital between 2000 and 2010. Source of controls: Employees of the University hospital and members of social activity clubs, without a history of any cancer. SPAG: Hospital-based, Retrospective, Observational. Source of cases: Guernsey. Source of controls: Guernsey STHM2: Population-based, Retrospective, Observational. Source of cases: Cases were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PCPT: Case-control from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial SELECT: Case-cohort from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial TAMPERE: Case-control - Finland, Retrospective, Observational, Population-based. Source of cases: Identified through linkage to the Finnish Cancer Registry and patient records; and the Finnish arm of the ERSPC study. Source of controls: Cohort participants without a diagnosis of cancer UGANDA: Uganda Prostate Cancer Study: Uganda is a case-control study of prostate cancer in Kampala Uganda that was initiated in 2011. Men with prostate cancer were enrolled from the Urology unit at Mulago Hospital and men without prostate cancer (i.e. controls) were enrolled from other clinics (i.e. surgery) at the hospital. UKGPCS: ICR, UK. Source of cases: Cases identified through clinics at the Royal Marsden hospital and nationwide NCRN hospitals. Source of controls: Ken Muir's control- 2000 ULM: Case-control - Germany. Source of cases: familial cases (n=162): identified through questionnaires for family history by collaborating urologists all over Germany; sporadic cases (n=308): prostatectomy series performed in the Clinic of Urology Ulm between 2012 and 2014. Source of controls: age-matched controls (n=188): age-matched men without prostate cancer and negative family history collected in hospitals of Ulm WUGS/WUPCS: Cases Series, USA. Source of cases: Identified through clinics at Washington University in St. Louis. Source of controls: Men diagnosed and managed with prostate cancer in University based clinic. Acknowledgement Statements: Aarhus: This study was supported by the Danish Strategic Research Council (now Innovation Fund Denmark) and the Danish Cancer Society. The Danish Cancer Biobank (DCB) is acknowledged for biological material. AHS: This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119). ATBC: This research was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C, and HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services. BioVu: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding and by the National Center for Research Resources, Grant UL1 RR024975-01 (which is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). Canary PASS: PASS was supported by Canary Foundation and the National Cancer Institute's Early Detection Research Network (U01 CA086402) CCI: This work was awarded by Prostate Cancer Canada and is proudly funded by the Movember Foundation - Grant # D2013-36.The CCI group would like to thank David Murray, Razmik Mirzayans, and April Scott for their contribution to this work. CerePP French Prostate Cancer Case-Control Study (ProGene): None reported COH: SLN is partially supported by the Morris and Horowitz Families Endowed Professorship COSM: The Swedish Research Council, the Swedish Cancer Foundation CPCS1 & CPCS2: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, DenmarkCPCS1 would like to thank the participants and staff of the Copenhagen General Population Study for their important contributions. CPDR: Uniformed Services University for the Health Sciences HU0001-10-2-0002 (PI: David G. McLeod, MD) CPS-II: The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. CPS-II thanks the participants and Study Management Group for their invaluable contributions to this research. We would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. EPIC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); the Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation, Greek Ministry of Health; Greek Ministry of Education (Greece); the Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); the Statistics Netherlands (The Netherlands); the Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, Spanish Ministry of Health ISCIII RETIC (RD06/0020), Red de Centros RCESP, C03/09 (Spain); the Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and Västerbotten, Fundacion Federico SA (Sweden); the Cancer Research UK, Medical Research Council (United Kingdom). EPICAP: The EPICAP study was supported by grants from Ligue Nationale Contre le Cancer, Ligue départementale du Val de Marne; Fondation de France; Agence Nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES). The EPICAP study group would like to thank all urologists, Antoinette Anger and Hasina Randrianasolo (study monitors), Anne-Laure Astolfi, Coline Bernard, Oriane Noyer, Marie-Hélène De Campo, Sandrine Margaroline, Louise N'Diaye, and Sabine Perrier-Bonnet (Clinical Research nurses). ERSPC: This study was supported by the DutchCancerSociety (KWF94-869,98-1657,2002-277,2006-3518, 2010-4800), The Netherlands Organisation for Health Research and Development (ZonMW-002822820, 22000106, 50-50110-98-311, 62300035), The Dutch Cancer Research Foundation (SWOP), and an unconditional grant from Beckman-Coulter-HybritechInc. ESTHER: The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. The ESTHER group would like to thank Hartwig Ziegler, Sonja Wolf, Volker Hermann, Heiko Müller, Karina Dieffenbach, Katja Butterbach for valuable contributions to the study. FHCRC: The FHCRC studies were supported by grants R01-CA056678, R01-CA082664, and R01-CA092579 from the US National Cancer Institute, National Institutes of Health, with additional support from the Fred Hutchinson Cancer Research Center. FHCRC would like to thank all the men who participated in these studies. Gene-PARE: The Gene-PARE study was supported by grants 1R01CA134444 from the U.S. National Institutes of Health, PC074201 and W81XWH-15-1-0680 from the Prostate Cancer Research Program of the Department of Defense and RSGT-05-200-01-CCE from the American Cancer Society. Hamburg-Zagreb: None reported HPFS: The Health Professionals Follow-up Study was supported by grants UM1CA167552, CA133891, CA141298, and P01CA055075. HPFS are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. IMPACT: The IMPACT study was funded by The Ronald and Rita McAulay Foundation, CR-UK Project grant (C5047/A1232), Cancer Australia, AICR Netherlands A10-0227, Cancer Australia and Cancer Council Tasmania, NIHR, EU Framework 6, Cancer Councils of Victoria and South Australia, and Philanthropic donation to Northshore University Health System. We acknowledge support from the National Institute for Health Research (NIHR) to the Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden Foundation NHS Trust. IMPACT acknowledges the IMPACT study steering committee, collaborating centres, and participants. IPO-Porto: The IPO-Porto study was funded by Fundaçäo para a Ciência e a Tecnologia (FCT; UID/DTP/00776/2013 and PTDC/DTP-PIC/1308/2014) and by IPO-Porto Research Center (CI-IPOP-16-2012 and CI-IPOP-24-2015). MC and MPS are research fellows from Liga Portuguesa Contra o Cancro, Núcleo Regional do Norte. SM is a research fellow from FCT (SFRH/BD/71397/2010). IPO-Porto would like to express our gratitude to all patients and families who have participated in this study. Karuprostate: The Karuprostate study was supported by the the Frech National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la ProstateKarusprostate thanks Séverine Ferdinand. KULEUVEN: F.C. and S.J. are holders of grants from FWO Vlaanderen (G.0684.12N and G.0830.13N), the Belgian federal government (National Cancer Plan KPC_29_023), and a Concerted Research Action of the KU Leuven (GOA/15/017). TVDB is holder of a doctoral fellowship of the FWO. LAAPC: This study was funded by grant R01CA84979 (to S.A. Ingles) from the National Cancer Institute, National Institutes of Health. Malaysia: The study was funded by the University Malaya High Impact Research Grant (HIR/MOHE/MED/35). Malaysia thanks all associates in the Urology Unit, University of Malaya, Cancer Research Initiatives Foundation (CARIF) and the Malaysian Men's Health Initiative (MMHI). MCCS: MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MCC-Spain: The study was partially funded by the Accion Transversal del Cancer, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI09/00773-Cantabria, PI11/01889-FEDER, PI12/00265, PI12/01270, and PI12/00715), by the Fundación Marqués de Valdecilla (API 10/09), by the Spanish Association Against Cancer (AECC) Scientific Foundation and by the Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Also sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d'Oncologia de Catalunya (XBTC). MCC-Spain acknowledges the contribution from Esther Gracia-Lavedan in preparing the data. We thank all the subjects who participated in the study and all MCC-Spain collaborators. MD Anderson: Prostate Cancer Case-Control Studies at MD Anderson (MDA) supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388. MDACC_AS: None reported MEC: Funding provided by NIH grant U19CA148537 and grant U01CA164973. MIAMI (WFPCS): ACS MOFFITT: The Moffitt group was supported by the US National Cancer Institute (R01CA128813, PI: J.Y. Park). NMHS: Funding for the Nashville Men's Health Study (NMHS) was provided by the National Institutes of Health Grant numbers: RO1CA121060. PCaP only data: The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. For HCaP-NC follow-up data: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. For studies using both PCaP and HCaP-NC follow-up data please use: The North Carolina - Louisiana Prostate Cancer Project (PCaP) and the Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study are carried out as collaborative studies supported by the Department of Defense contract DAMD 17-03-2-0052 and the American Cancer Society award RSGT-08-008-01-CPHPS, respectively. For any PCaP data, please include: The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. For studies using PCaP DNA/genotyping data, please include: We would like to acknowledge the UNC BioSpecimen Facility and LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). For studies using PCaP tissue, please include: We would like to acknowledge the RPCI Department of Urology Tissue Microarray and Immunoanalysis Core for our tissue processing, storage and sample disbursement. For studies using HCaP-NC follow-up data, please use: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. The authors thank the staff, advisory committees and research subjects participating in the HCaP-NC study for their important contributions. For studies that use both PCaP and HCaP-NC, please use: The authors thank the staff, advisory committees and research subjects participating in the PCaP and HCaP-NC studies for their important contributions. PCMUS: The PCMUS study was supported by the Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2-2009; DFNI-B01/28/2012) with additional support from the Science Fund of Medical University - Sofia (contract 51/2009; 8I/2009; 28/2010). PHS: The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490, and HL34595. PHS members are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. PLCO: This PLCO study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHPLCO thanks Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention at the National Cancer Institute, the screening center investigators and staff of the PLCO Cancer Screening Trial for their contributions to the PLCO Cancer Screening Trial. We thank Mr. Thomas Riley, Mr. Craig Williams, Mr. Matthew Moore, and Ms. Shannon Merkle at Information Management Services, Inc., for their management of the data and Ms. Barbara O'Brien and staff at Westat, Inc. for their contributions to the PLCO Cancer Screening Trial. We also thank the PLCO study participants for their contributions to making this study possible. Poland: None reported PROCAP: PROCAP was supported by the Swedish Cancer Foundation (08-708, 09-0677). PROCAP thanks and acknowledges all of the participants in the PROCAP study. We thank Carin Cavalli-Björkman and Ami Rönnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skilful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. We acknowledge The NPCR steering group: Pär Stattin (chair), Anders Widmark, Stefan Karlsson, Magnus Törnblom, Jan Adolfsson, Anna Bill-Axelson, Ove Andrén, David Robinson, Bill Pettersson, Jonas Hugosson, Jan-Erik Damber, Ola Bratt, Göran Ahlgren, Lars Egevad, and Roy Ehrnström. PROGReSS: The PROGReSS study is founded by grants from the Spanish Ministry of Health (INT15/00070; INT16/00154; FIS PI10/00164, FIS PI13/02030; FIS PI16/00046); the Spanish Ministry of Economy and Competitiveness (PTA2014-10228-I), and Fondo Europeo de Desarrollo Regional (FEDER 2007-2013). ProMPT: Founded by CRUK, NIHR, MRC, Cambride Biomedical Research Centre ProtecT: Founded by NIHR. ProtecT and ProMPT would like to acknowledge the support of The University of Cambridge, Cancer Research UK. Cancer Research UK grants (C8197/A10123) and (C8197/A10865) supported the genotyping team. We would also like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge, UK. We would also like to acknowledge the support of the National Cancer Research Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT) collaborative (grant code G0500966/75466) which has funded tissue and urine collections in Cambridge. We are grateful to staff at the Welcome Trust Clinical Research Facility, Addenbrooke's Clinical Research Centre, Cambridge, UK for their help in conducting the ProtecT study. We also acknowledge the support of the NIHR Cambridge Biomedical Research Centre, the DOH HTA (ProtecT grant), and the NCRI/MRC (ProMPT grant) for help with the bio-repository. The UK Department of Health funded the ProtecT study through the NIHR Health Technology Assessment Programme (projects 96/20/06, 96/20/99). The ProtecT trial and its linked ProMPT and CAP (Comparison Arm for ProtecT) studies are supported by Department of Health, England; Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466, and The NCRI, UK. The epidemiological data for ProtecT were generated though funding from the Southwest National Health Service Research and Development. DNA extraction in ProtecT was supported by USA Dept of Defense award W81XWH-04-1-0280, Yorkshire Cancer Research and Cancer Research UK. The authors would like to acknowledge the contribution of all members of the ProtecT study research group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health of England. The bio-repository from ProtecT is supported by the NCRI (ProMPT) Prostate Cancer Collaborative and the Cambridge BMRC grant from NIHR. We thank the National Institute for Health Research, Hutchison Whampoa Limited, the Human Research Tissue Bank (Addenbrooke's Hospital), and Cancer Research UK. PROtEuS: PROtEuS was supported financially through grants from the Canadian Cancer Society (13149, 19500, 19864, 19865) and the Cancer Research Society, in partnership with the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec, and the Fonds de la recherche du Québec - Santé.PROtEuS would like to thank its collaborators and research personnel, and the urologists involved in subjects recruitment. We also wish to acknowledge the special contribution made by Ann Hsing and Anand Chokkalingam to the conception of the genetic component of PROtEuS. QLD: The QLD research is supported by The National Health and Medical Research Council (NHMRC) Australia Project Grants (390130, 1009458) and NHMRC Career Development Fellowship and Cancer Australia PdCCRS funding to J Batra. The QLD team would like to acknowledge and sincerely thank the urologists, pathologists, data managers and patient participants who have generously and altruistically supported the QLD cohort. RAPPER: RAPPER is funded by Cancer Research UK (C1094/A11728; C1094/A18504) and Experimental Cancer Medicine Centre funding (C1467/A7286). The RAPPER group thank Rebecca Elliott for project management. SABOR: The SABOR research is supported by NIH/NCI Early Detection Research Network, grant U01 CA0866402-12. Also supported by the Cancer Center Support Grant to the Cancer Therapy and Research Center from the National Cancer Institute (US) P30 CA054174. SCCS: SCCS is funded by NIH grant R01 CA092447, and SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SCPCS: SCPCS is funded by CDC grant S1135-19/19, and SCPCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). SEARCH: SEARCH is funded by a program grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SNP_Prostate_Ghent: The study was supported by the National Cancer Plan, financed by the Federal Office of Health and Social Affairs, Belgium. SPAG: Wessex Medical ResearchHope for Guernsey, MUG, HSSD, MSG, Roger Allsopp STHM2: STHM2 was supported by grants from The Strategic Research Programme on Cancer (StratCan), Karolinska Institutet; the Linné Centre for Breast and Prostate Cancer (CRISP, number 70867901), Karolinska Institutet; The Swedish Research Council (number K2010-70X-20430-04-3) and The Swedish Cancer Society (numbers 11-0287 and 11-0624); Stiftelsen Johanna Hagstrand och Sigfrid Linnérs minne; Swedish Council for Working Life and Social Research (FAS), number 2012-0073STHM2 acknowledges the Karolinska University Laboratory, Aleris Medilab, Unilabs and the Regional Prostate Cancer Registry for performing analyses and help to retrieve data. Carin Cavalli-Björkman and Britt-Marie Hune for their enthusiastic work as research nurses. Astrid Björklund for skilful data management. We wish to thank the BBMRI.se biobank facility at Karolinska Institutet for biobank services. PCPT & SELECT are funded by Public Health Service grants U10CA37429 and 5UM1CA182883 from the National Cancer Institute. SWOG and SELECT thank the site investigators and staff and, most importantly, the participants who donated their time to this trial. TAMPERE: The Tampere (Finland) study was supported by the Academy of Finland (251074), The Finnish Cancer Organisations, Sigrid Juselius Foundation, and the Competitive Research Funding of the Tampere University Hospital (X51003). The PSA screening samples were collected by the Finnish part of ERSPC (European Study of Screening for Prostate Cancer). TAMPERE would like to thank Riina Liikanen, Liisa Maeaettaenen and Kirsi Talala for their work on samples and databases. UGANDA: None reported UKGPCS: UKGPCS would also like to thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. UKGPCS should also like to acknowledge the NCRN nurses, data managers, and consultants for their work in the UKGPCS study. UKGPCS would like to thank all urologists and other persons involved in the planning, coordination, and data collection of the study. ULM: The Ulm group received funds from the German Cancer Aid (Deutsche Krebshilfe). WUGS/WUPCS: WUGS would like to thank the following for funding support: The Anthony DeNovi Fund, the Donald C. McGraw Foundation, and the St. Louis Men's Group Against Cancer.

  Study phs001391

• Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS)

  This pharmacogenomic study focused on the response of patients with MDD to an 8-week course of treatment with citalopram or escitalopram. Briefly, clinical assessments and research assessments were performed at each study visit as summarized in Table 1. Many patients continued on antidepressant medication after the 8 week study. Table 1: Study timeline and patient contacts. Week Consent/Med Hx Write Rx SI Qx SCID HRS-D17 QIDSC16 CGI-I 0 SC RC RC SC SC SC 4 RC RC SC SC RC 8 RC RC SC SC RC HRS-D17=Hamilton Rating Scale for Depression, QIDS-C16=Quick Inventory of Depressive Symptomatology, CGI-I=Clinical Global Impression-Improvement, SCID=Structured Clinical Interview for DSM-IV, SC=Study Coordinator, RC=Research Clinician. Enrollment and baseline assessment. Upon initial intake, the Study Coordinator (SC) obtained informed consent as well as clinical and demographic information, including history of bone marrow or liver transplant or blood transfusion within the previous 6 weeks, and prior history of treatment during the current major depressive episode. The SC completed the Structured Clinical Interview for DSM-IV (SCID), the HRS-D17 (17-item Hamilton Rating Scale for Depression) and the QIDS-C16 (Quick Inventory of Depressive Symptomatology) and reviewed the inclusion/exclusion criteria. After review with the Research Clinician (RC) and when appropriate, after a negative pregnancy test, the SC invited the subject to participate in the study if entry criteria were met. If the subject agreed, he/she received treatment according to the study protocol. Treatment schedule. Participants selected for inclusion in the study were seen at weeks 0, 4, and 8. The appropriate treatment antidepressant (citalopram or escitalopram) was determined following discussion between the patient and RC concerning medical, financial, and insurance considerations. The study medication citalopram was given in tablet or liquid form, depending on the patient's need. A fixed-flexible dose schedule was employed with the possibility of a dose escalation. In particular, the initial dose of citalopram was 20 mg and escitalopram was 10 mg. This dose was increased to 40 mg and 20 mg, respectively, after 4 weeks if the subject had a score of >/= 6 on the QIDS-C16 and the RC concluded that the subject could tolerate the increase. If necessary, dose was reduced at the discretion of the RC. The importance of medication compliance was discussed with the subject, and subjects were asked to bring in the medication at each visit for the purpose of counting remaining pills to assess compliance. Participants may have had an abbreviated course of therapy if they were clearly intolerant of the drug or failed to respond to a 40 mg dose of citalopram or a 20 mg dose of escitalopram. They then received standard treatment from a primary physician or psychiatrist with different medications and/or therapeutic modalities (e.g. psychotherapy). Special attention was given to subjects with suicidal ideation. Those subjects were offered additional appointments as needed to ensure their safety. Participants were also contacted by telephone at week 1 and week 2 by the Clinical Nurse Specialist (CNS) or other study personnel to ensure medication compliance and patient safety. The CNS was supervised by the study psychiatrist and principal investigator and deferred to the physician's judgment as needed. The SC was trained to notify the RC at the time of the clinical visits or the phone interviews if the subject endorsed any suicidal ideation or plans. For those subjects who were unable to attend the follow-up visits as scheduled, the patient was contacted by phone to complete the HRS-D17/QIDS-C16. The participant was also asked to return to the clinic to complete a final blood draw for the study. Adjunctive and concurrent medications. Adjunctive treatments were those used to manage transient associated symptoms (e.g., insomnia) or transient or longer-term medication side effects (e.g., sexual dysfunction). Adjunctive treatments that were not used to treat depression were allowed during the study. However, drugs in the exclusion criteria for this study were not used as adjunctive therapies. Subjects were allowed to participate in the study while receiving concurrent medications for general medical conditions as long as there was no contraindication to use while taking citalopram or escitalopram. Drug efficacy phenotype evaluation. The change in QIDS-C16 score and change in HRS-D17 score were used as the major research outcome measures to assess drug response. At each clinical research visit, the RC also completed the Clinician Global Impression of Improvement (CGI-I) scale. For the primary genome-wide association analyses, dichotomous outcome variables, remission and response, were defined based on the QIDS-C16 last visit score. Remission was defined as a QIDS-C16 score of 5 or less, while response was defined as at least a 50% reduction in the QIDS-C16 score from baseline. Specimen collection. Specimen collections were obtained by the General Clinical Research Center (GCRC) at St. Mary's Hospital (SMH). Subjects had blood drawn on an outpatient basis at GCRC-SMH on three separate occasions - baseline (0), week 4 and week 8 visits. Prior to sample collection, date and time of last dose of study medication was gathered at the 4 and 8 week visits. For those patients who were unable to complete the regularly scheduled visits, a dismissal blood draw was requested. GCRC then shipped samples to Mayo Clinic's Biospecimens Accessioning and Processing Lab. Genotyping and biomarker assays. DNA from 529 patients was genotyped by the RIKEN Center for Genomic Medicine (Yokohama, Japan) using Illumina Human610-Quad BeadChips (Illumina, San Diego, CA). The study also included the determination of plasma drug levels at weeks 4 and 8, and metabolite levels at baseline and weeks 4 and 8 for a subset of subjects. The primary genome-wide association study based on these data, which includes a summary of the protocol, subject description, selection of subjects for genetic analyses, and definitions of clinical outcomes, was published in the Pharmacogenomics Journal (Ji et al., 2012).

  Study phs000670

• Oncoarray Consortium - Lung Cancer Studies

  The study was conducted under the auspices of the Transdisciplinary Research In Cancer of the Lung (TRICL) Research Team, which is a part of the Genetic Associations and MEchanisms in ONcology (GAME-ON) consortium, and associated with the International Lung Cancer Consortium (ILCCO). Ethics: All participants provided written informed consent. All studies were reviewed and approved by institutional ethics review committees at the involved institutions. Sequencing data are derived from four substudies. The substudies that contributed include Harvard, Liverpool, Toronto, and IARC. The Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study is a randomized primary prevention trial including 29,133 male smokers enrolled in Finland between 1985 and 1993. Participants ranged between ages of 50 to 69 at enrollment and were randomized in a factorial design to take either 50 milligrams of d-alpha tocopheryl acetate (Vitamin E), 20 mg of all-trans-beta-carotene, both or placebo. The study continued to monitor cancer incidence through 2012 and total mortality through December 2013. The CAncer de PUlmon en Asturias Study (CAPUA) is a hospital-based case-control study conducted in Asturias, Spain by the University of Oviedo. Lung cancer cases were recruited in three main hospitals of Asturias, following an identical protocol from 2002 to 2012. Eligible cases were incident cases of histologically confirmed lung cancer between 30 and 85 years of age and residents in the geographical area of each participating hospital. Controls were selected from patients admitted to those hospitals with diagnoses unrelated to the exposures of interest and individually matched by ethnicity, gender, age (± 5 years) and hospital. Epidemiologic data were collected personally through computer-assisted questionnaires by trained interviewers during the first hospital admission. Structured questionnaires collected information on sociodemographic characteristics, recent and prior tobacco use, environmental exposure (air pollution and passive smoking), diet, personal and family history of cancer, and occupational history from each participant. Peripheral blood samples (or mouthwash samples when they refused to donate blood) were collected from all participants. Coding of histology was based on 2001 WHO/IASLC. Genomic DNA was extracted based on standard protocol. The Canadian Screening Study includes the nested case-control samples from 3 screening programs: IELCAP-Toronto: Ever smokers of more than 10 pack-years age 50 and above were eligible for the I-ELCAP screening program since 2003, and a total of 4782 individuals have been enrolled in the Greater Toronto Area. Participants were administered a LDCT scan along with a standard study questionnaire at baseline. Blood samples were systematically collected at baseline since 2006. Participants who had an abnormality in a CT scan were followed up every 1 to 2 years. The screening program was organized by the Princess Margaret Hospital. PanCan: Ever smokers between the ages of 50-75 with no previous history of invasive cancer are eligible to participate in the study. The study was carried out across Canada in Vancouver, Calgary, Hamilton, Toronto, Ottawa, Quebec, Halifax, and St. John's. A total of 2537 smokers have been screened from 2008 to 2011. All study participants completed a detailed questionnaire, spirometry, collection of blood specimens for biomarker measurement and LDCT at baseline. All participants are followed for a minimum of 3 years. On yearly follow up, an updated shorter questionnaire is administered, blood is collected and CT scans are performed. Blood samples are available from all 2537 individuals. BCCA Screening Program: From 1990 to 2007, 4274 smokers above 40 years old who had smoked 20 pack-years or more were enrolled at BCCA. Upon enrollment, subjects completed a questionnaire for their lifestyle and medical history. Baseline spirometry was conducted using a flow-sensitive spirometer in accordance with the American Thoracic Society recommendations. Since 2000, a LDCT was obtained in 2440 individuals. The participants were followed prospectively to determine whether they developed lung cancer. A total of 9759 individuals participated in the CT screening program in Canada from these 3 programs. The samples included in this project is based on a subset of nested lung cancer case-control pairs based on 1:2 ratio. The Carotene and Retinol Efficacy Trial (CARET) was a randomized, double-blind, placebo-controlled trial of the cancer prevention efficacy and safety of a daily combination of 30 mg of beta-carotene and 25,000 IU of retinyl palmitate in 18,314 persons at high risk for lung cancer. CARET began in 1985, and the intervention was halted in January 1996, 21 months ahead of schedule, with the twin conclusions for definitive evidence of no benefit and substantial evidence of a harmful effect of the intervention on both lung cancer incidence and total mortality. CARET continued to follow and collect endpoints on their participants through 2005. Pathology reports and medical records were reviewed to confirm cancer endpoints, and death certificates obtained to capture cause of death. During the active intervention phase of CARET, serum, plasma, whole blood, and lung tissue specimens were collected on participants. These biospecimens make up the CARET Biorepository. For the OncoArray Project, CARET provided DNA extracted from whole blood of lung cancer cases and controls matched on age at baseline (± 4 years), sex, race, baseline smoking status, history of occupational asbestos exposure (asbestos vs heavy smoker), and year of enrollment (2-year intervals). The European Prospective Investigation into Cancer and Nutrition (EPIC) study is a multi-center cohort study involving 521,000 study participants from 10 European countries. The current study involved EPIC participants from 7 countries (Greece, Netherlands, UK, France, Germany, Spain, and Italy), including 1223 incident lung cancer cases and 1249 smoking matched controls. The Kentucky Lung Cancer Research Initiative is a study conducted by the Markey Cancer Center Cancer Center and the University of Kentucky using a population-based, case-control framework to study the extraordinarily high rates of lung cancer in Southeastern, Appalachian Kentucky. Cancer cases were recruited from the Kentucky Cancer Registry at the time of diagnosis and controls were recruited from a random digit dialing process from the same region. Study accrual began in January 5, 2012 and completed on September 5, 2014 and 520 subjects were recruited in a 4:1 ratio of controls: cases from Appalachian Kentucky. Of the 520 subjects recruited, 231 are included in the OncoArray analysis, including all 93 cancer cases, and 123 controls. Newly diagnosed lung cancer cases and controls underwent blood, toenail (for trace element analysis), urine, buffy coat, water, soil, and radon collection, residence GPS mapping, as well as an extensive epidemiologic, occupational, and health history questionnaire (Clinical Trials.gov Identifier: NCT01648166). The Harvard Lung Cancer Study (HLCS) is a case-control study based at Mass General Hospital (MGH) in Boston, Massachusetts from 1992 to 2004. Details of the study were described previously. Briefly, eligible cases included any person over the age of 18 years with a diagnosis of primary lung cancer that was further confirmed by an MGH lung pathologist. Controls were recruited from the friends or spouses of cancer patients or the friends or spouses of other surgery patients in the same hospital. Potential controls were excluded from participation if they had a diagnosis of any cancer (other than non-melanoma skin cancer). Interviewer-administered questionnaires, a modified version of the standardized American Thoracic Society respiratory questionnaire, collected information on demographics, medical history, family history of cancer, smoking history, and a detailed work history, including job titles and tasks. Genome-wide genotype data were first generated using Illumina Human 610-Quad BeadChips and then imputed by MACH against the 1000 Genome Project dataset (http://browser.1000genomes.org/index.html). The Institutional Review Board of MGH and the Human Subjects Committee of the Harvard School of Public Health approved the study. The Israel study (NICCC-LCA) is an ongoing case-control study of newly diagnosed lung cancer cases of any histology and population age/sex/ethnicity-matched "healthy" controls. All participants undergo face-to-face interviews, provide a venous blood sample (separated into DNA, Sera, lymphocytes) after signing an IRB-approved form. Histology reports, FFPE blocks and clinical follow-up are available for most cancer cases. The MD Anderson Cancer Center (MDACC) Study. Lung cancer cases and frequency-matched controls were ascertained from a large ongoing case-control study at the University of Texas MD Anderson Cancer Center (UTMDACC) since 1991. Detailed study description was provided previously (Spitz et al 2007). In brief, cases were newly-diagnosed and histologically confirmed lung cancer patients recruited from UTMDACC. Controls were healthy individuals without a history of cancer (except for nonmelanoma skin cancer) and recruited from the Kelsey-Seybold Clinics, the largest private multispecialty physician group in the Houston metropolitan area. Controls were frequency-matched to cases on age (±5 years), sex, and race/ethnicity. After providing written informed consent, each study participants completed an in-person interview by staff interviewers to collect information on demographics, smoking status, etc. Blood samples were also drawn from all the study participants. This study was approved by institutional review boards of UTMDACC and Kelsey-Seybold Clinics. The Malmö Diet and Cancer Study (MDCS) is a population-based prospective cohort study that recruited men and women aged at 44 to 74 years old of living in Malmö, Sweden between 1991 and 1996. The main goal of the MDCS is to study the impact of diet on cancer incidence and mortality. It consists of a baseline examination including dietary assessment, a self-administered questionnaire, anthropometric measurements and collection of blood samples. A total of 165 incident lung cancer cases and 174 individually smoking-matched controls were available for this analysis. The Multiethnic Cohort (MEC) Study includes 215,251 men and women aged 45-74 years at recruitment, primarily from five ethnic/racial groups - African Americans and Latinos mostly recruited from CA (mainly from Los Angeles County) and Japanese Americans, Native Hawaiians and whites (mostly recruited from HI). The cohort was assembled in 1993-1996 by mailing a self-administered questionnaire to persons identified primarily through driver's license files. The baseline questionnaire obtained information on demographics, anthropometry, smoking history, medical and reproductive histories, family history of cancer, diet and physical activity. Incident cancer cases are identified by regular linkage with the State of California Cancer Registry and the Hawaii Tumor Registry, both members of the SEER Program of the NCI. In 2001-2006, a prospective biorepository was assembled by collecting a pre-diagnostic blood specimen from 67,594 surviving MEC members. At the time of blood collection a short questionnaire was administered that included information on smoking during the previous 15 days. For this study, cases were all lung cancer cases incident to blood draw and diagnosed before December 2012. For each case, a control was selected among unaffected MEC participants who were alive at time of the case's diagnosis and matched on study site, sex, race/ethnicity, age (age at diagnosis for cases; age at blood collection for controls), and date of blood collection. The Mount-Sinai Hospital-Princess Margaret Study (MSH-PMH) was conducted in the greater Toronto area from 2008 to 2013. Lung cancer cases were recruited at the hospitals in the network of the University of Toronto. Controls were selected randomly from individuals registered in the family medicine clinics databases and were frequency matched with cases on age and sex. All subjects were interviewed, and information on lifestyle risk factors, occupational history and medical and family history was collected using a standard questionnaire. Tumors were centrally reviewed by the reference pathologist, a member of the International Association for the Study of Lung Cancer (IASLC) committee, and a second pathologist in the University Health Network. If the reviews conflicted, a consensus was arrived at after discussion. Coding of histology was based on 2001 WHO/IASLC. Genomic DNA was extracted based on standard protocol. The New England Lung Cancer Study (NELCS) is a population-based case-control study of lung cancer among residents of Northern and Central New Hampshire counties and the bordering region of Vermont. Cases with histologically confirmed primary incident lung cancer were identified from 2005 to 2007 using the New Hampshire State Cancer Registry and the Dartmouth-Hitchcock Medical Center (DHMC) Tumor Registry. Control participants were identified using a commercial database and matched to lung cancer cases within 5-year age groups, sex and county. Genomic DNA was isolated from blood or buccal specimens provided by consenting participants. The study complied with requirements of the Dartmouth College's Committee for Protection of Human Subjects. The Nijmegen Lung Cancer Study. The Netherlands patients with lung cancer were identified through the population-based cancer registry of the Netherlands Comprehensive Cancer Organisation in Nijmegen, the Netherlands. Patients who were diagnosed in one of three hospitals (Radboud University Medical Center, Canisius Wilhelmina Hospital in Nijmegen, and Rijnstate Hospital in Arnhem) since 1989 and who were still alive at April 15th, 2008 were recruited for a study on gene-environment interactions in lung cancer. 458 patients gave informed consent and donated a blood sample. This case series was expanded with 94 patients to a total of 552 by linking three other studies to the population-based cancer registry in order to identify new occurrences of lung cancer among the participants of these other studies. All three other studies (i.e., POLYGENE, the Nijmegen Biomedical Study, and the Radboudumc Urology Outpatient Clinic Epidemiology Study) were initiated to study genetic risk factors for disease and participants to these studies gave general informed consent for DNA-related research and linkage with disease registries. Information on histology, stage of disease, and age at diagnoses was obtained through the cancer registry. Lifestyle information was collected through a structured questionnaire and whole blood for DNA isolation was collected by the regional thrombosis services. The cancer-free controls (46% males) were selected from participants of the "Nijmegen Biomedical Study" (NBS), an age- and sex-stratified random sample of the general population of the municipality of Nijmegen, The Netherlands. All participants provided extensive lifestyle information by structured questionnaires and blood samples for DNA isolation, serum and plasma. All controls are of self-reported European descent. The study protocols of the NBS were approved by the Institutional Review Board of the Radboudumc and all study subjects signed a written informed consent form. The Northern Sweden Health and Disease Study (NSHDS) encompasses several prospective cohorts. The current study involves participants from the Västerbotten Intervention Project (VIP), a sub-cohort within NSHDS. VIP is an ongoing prospective cohort and intervention study intended for health promotion of the general population of the Västerbotten County in northern Sweden. VIP was initiated in 1985 and all residents in the Västerbotten County were invited to participate by attending a health check-up at 40, 50 and 60 years of age. Participants were asked to complete a self-administered questionnaire including various demographic factors such as education, smoking habits, physical activity and diet. In addition, height and weight were measured and participants were asked to donate a fasting blood sample for future research. A total of 243 incident lung cancer cases and 266 individually smoking-matched controls were available for this analysis. Norway National Institute of Occupational Health Study. Early-stage NSCLC cases and healthy controls at the time of enrollment were Caucasians of Norwegian origin and were recruited from the same geographical region (Western Norway). The patients were enrolled in the study, whenever practically feasible among patients admitted for lung cancer at the Haukeland University Hospital in Bergen, Norway. The informed written consents covering analysis of molecular and genetic markers was signed by the patients prior to surgery. Only patients with histologically confirmed early-stage NSCLC were included in our study. The subjects included in this project are a subgroup recruited into the project "lung cancer genetics" at NIOH. The controls were recruited from the same geographical region of Western Norway and frequency-matched with cases on cumulative smoking dose (pack-years). Pack-years smoked [( 20 cigarettes per day) x years smoked] were calculated to indicate the cumulative smoking dose. The Cases and controls were interviewed using similar questionnaires and were categorized as never smokers, ex-smokers or current smokers. Never smokers are subjects indicating having smoked less than 100 cigarettes in their life time. Ex-smokers were defined as those having quitted at least 1 year before sampling, and current smokers were those indicating that they were smokers at the time of sampling. The project has been approved by the Regional Committee for Medical and Health Research Ethics in Southern Norway in accordance with the WMA Declaration of Helsinki. The ethical approval covered access to the NSCLC databank. The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) Study, a randomized trial aimed at evaluating the efficacy of screening in reducing cancer mortality, recruited approximately 155,000 men and women age 55 to 74 years from 1992 to 20014. Screening for lung cancer among participants in the intervention arm included a chest x-ray at baseline followed by either three annual x-rays (for current or former smokers at enrollment) or two annual x-rays (for never smokers); participants in the control arm received routine health care. Screening-arm participants provided data on sociodemographic factors, smoking behavior, anthropometric characteristics, medical history, and family history of cancer, as well as blood samples annually for the first 6 years of the study (baseline T0 and T1 through T5). Lung cancers were ascertained through annual questionnaires mailed to the participants, and positive reports were followed up by abstracting medical records or death certificates. Follow-up in the trial as of July 2009 was 96.7%. Patients were excluded because of missing baseline questionnaire, previous history of any cancer, diagnosis of multiple cancers during follow-up, missing smoking information at baseline, missing consent for utilization of biologic specimens for etiologic studies, or unavailability/insufficient quantity of serum or DNA specimens. The Resource for the Study of Lung Cancer Epidemiology in North Trent (ReSoLuCENT) is an ongoing study conducted in Sheffield from 2006 and due to complete recruitment in 2016. The study recruited pathologically confirmed lung cancer cases diagnosed at age 60 years or younger and family matched controls. Lung cancer cases diagnosed at ages older than 60 years were recruited if they reported a family history of lung cancer. The cases and matched controls were recruited through several major cancer treatment centers, however, the majority were recruited in North Trent. All participants completed a detailed lifestyle questionnaire which included questions about occupational exposures, education, medical history and family history of cancer and lung disease. Participants also donated blood samples for DNA extraction. The ReSoLuCENT study has been funded by the Sheffield Hospitals Charity, Sheffield ECMC and Weston Park Hospital Cancer Charity. First degree relatives were removed from the sample deposited to dbGaP. The Roy Castle Lung Study of Liverpool Lung Project (LLP) is a case-control and cohort study which has recruited over 11,500 individuals since 1996 from the Liverpool region in the UK. Detailed epidemiological and clinical data is collected with associated specimens (i.e. tumor tissue, blood, plasma, sputum, bronchial lavage and oral brushings). The participants have completed a detailed lifestyle questionnaire at recruitment, with repeat questionnaires at intervals; updated data on clinical outcome and hospital events are collected through the Health and Social Care Information Center (including Office of National Statistics mortality data, Cancer Registry and Health Episode Statistics). The project is registered on the UK National Institute for Health Research (NIHR) lung cancer portfolio and has all the required ethical approvals and sponsorship arrangements in place. The lung tumors were reviewed by the reference pathologist. The Seoul Bundang Lung Cancer Study was conducted between 2005 and 2010 to discover genetic and environmental factors related with lung cancer development. Lung cancer cases were recruited at the Seoul National University Hospital in Bundang. Controls were selected randomly from individuals participated in health check-up program and were frequency matched with cases on age and sex. All subjects were interviewed, and information on lifestyle risk factors, occupational history and medical and family history was collected using a standard questionnaire. Tumors were reviewed by the pathologists in the hospital. If the reviews conflicted, a consensus was arrived at after discussion. Coding of histology was based on 2001 WHO/IASLC. Genomic DNA was extracted based on standard protocol. The Shanghai Cohort Study (SCS) consisted of 18,244 men in Shanghai, China, who were 45-64 years old at the time of enrollment during 1986-1989. Approximately 80% of eligible men participated in the study. At the time of recruitment, each cohort subject was interviewed in-person by a trained nurse interviewer using a structured questionnaire that included background information, history of tobacco and alcohol use, current diet, and medical history. At the completion of the interview, the nurse collected a 10 ml blood and a single void urine specimen from the study participant. The buccal cell samples were collected from all surviving cohort members (~15,000) in the 2001-2002 follow-up interviews. The cohort has been followed for the occurrence of cancer and death through routine ascertainment of new cases from the population-based Shanghai Cancer Registry and Shanghai Vital Statistics Units. To maximize the cancer findings and minimize the loss of follow-up, we contacted each surviving cohort member annually. Retired nurses visit the last known address of each living cohort member and record details of the interim health history of the cohort member. As of December 31, 2014, cumulatively 612 (3.4%) original subjects were lost to follow-up, and 574 (3.1%) refused to our continued follow-up interview. A nested case-control study of incident lung cancer cases within the Shanghai Cohort Study was used to examine the association between serum levels of vitamin B6 and other compounds in the one-carbon metabolism pathway and risk of lung cancer. Briefly, 516 lung cancer cases were identified among cohort participants with available serum samples as of 12/31/2006. For each case, we randomly selected one control subject from all cohort members who were free of cancer and alive at the time of cancer diagnosis of the index case. Controls were matched to the index case by age at enrollment (±2 years), date of biospecimen collection (±1 month) and neighborhood of residence at recruitment, and smoking status (current, former and never smokers) as established previously for other studies. For former smokers, cases and controls were further matched by years since quitting smoking (<10 vs ≥10 years). One serum vial per subject was retrieved from biorepository and all serum samples were sent to the laboratory (B-vital) for measurements. DNA samples of 250 lung cancer cases and 250 matched controls were available for the present study. The Singapore Chinese Health Study (SCHS) cohort consisted of 63,257 Chinese men and women in Singapore when they were 45-74 years old at the time of enrollment between April 1993 and December 1998. At recruitment, each study subject was interviewed in person by a trained interviewer using a structured questionnaire that emphasized current diet assessed via a validated, 165-item food frequency questionnaire. The questionnaire also requested information on demographics, lifetime use of tobacco, incense use, current physical activity, usual sleep duration, reproductive history (women only), occupational exposure, medical history, and family history of cancer. Blood or buccal cell, and spot urine samples were collected first from a random 3% sample of cohort participants in April 1994, and extended to all surviving cohort participants starting in January 2000. Overall approximately 60% of eligible cohort participants donated biospecimens. The cohort has been passively followed for death and cancer occurrence through regular record linkage with the population-based Singapore Cancer Registry and the Singapore Registry of Births and Deaths. Migration out of Singapore, especially among housing estate residents, was negligible. As of latest update, only 55 individuals from this cohort were known to be lost to follow-up due to migration and other reason. A nested case-control study of incident lung cancer cases within the Singapore Chinese Health Study was used to examine the association between serum levels of vitamin B6 and other compounds in the one-carbon metabolism pathway and risk of lung cancer. As of 12/31/2011, 422 lung cancer cases were identified among cohort participants with available prediagnostic plasma samples. For each case, one control subject was randomly selected from all eligible cohort members who were alive and free of cancer on the date of cancer diagnosis of the index case. The control subject was individually matched to the index case by gender, dialect group (Hokkien, Cantonese), age at enrollment (±3 years), date of baseline interview (±2 year), date of biospecimen collection (±6 months), and smoking status (current, former, and never smokers). For current smokers, cases and controls were further matched by number of cigarettes per day (<15, ≥15 cigarettes/day). For former smokers, cases and controls were further matched by years since quitting smoking (<10, ≥10 years). One plasma aliquot per subject was retrieved from the biorepository and all plasma samples were sent to the laboratory (B-vital) for measurements, and one aliquot of DNA per subject for the present study. The International Agency for Research on Cancer (IARC) L2 Study. Lung cancer cases and controls were recruited through a multicentric case-control study coordinated by the IARC in Russia, Poland, Serbia, Czech Republic, and Romania from 2005 to 2013. Cases were incident cancer patients collected from general hospitals. Controls were recruited from individuals visiting general hospitals and out-patient clinics for disorders unrelated to lung cancer and/or its associated risk factors, or from the general population. Information on lifestyle risk factors, medical and family history was collected from subjects by interview using a standard questionnaire. All study participants provided written informed consent. The current study included 1,133 lung cancer cases and 1,117 controls genotyped on the Oncoarray. The Washington State University Lung Cancer Study is a hospital case-control study of 511 subjects with newly-diagnosed (within 1 year of diagnosis) lung cancer and 820 race-, sex- and age-matched controls. Lung cancer cases were recruited from lung cancer clinics within the H. Lee Moffitt Cancer Center while controls were recruited from the Lifetime Cancer Screening Center, a H. Lee Moffitt Cancer Center affiliate. None of the controls were diagnosed with any form of cancer at the time of screening. Detailed questionnaire data and oral buccal cells were collected for all subjects. The Total Lung Cancer (TLC) Study is a hospital-based study that included 458 lung cancer patients recruited for Moffitt Cancer Center's Total Cancer Care™ protocol between April 2006 and August 2010. Total Cancer Care™ is a multi-institutional observational study of cancer patients that prospectively collects self-reported demographic and clinical data, medical record information and blood samples for research purposes. All patients used in this cohort were recruited from the Thoracic Oncology Clinic at the Moffitt Cancer Center. The Vanderbilt Lung Cancer Study (BioVU) is a case-control study nested within the Vanderbilt University Medical Center biobank, BioVU. BioVU is a biorepository of DNA extracted from blood drawn from patients seeking routine clinical care at Vanderbilt University Medical Center and linked to de-identified electronic health records for research purposes. Lung cancer cases and controls were identified from BioVU participants in February 2014. Lung cancer cases were identified from the Vanderbilt tumor registry. All specimens undergo pathologic review for determination of morphology. Coding of histology was based on SEER Program Coding Guidelines. Controls were randomly selected from BioVU participants, excluding cancer patients, and were matched to cases on age (± 5 years), sex, and race. Relevant covariates were identified from electronic health records using natural language processing. Genomic DNA was extracted based on a standard protocol.

  Study phs001273

• Genetic Causes of Growth Disorders

  Description of the disorder: A very common disorder presenting to pediatricians/pediatric endocrinologists is childhood growth failure. Sometimes the cause is evident, for example, growth hormone deficiency. In other children, the etiology remains unknown despite extensive evaluation, resulting in the unhelpful diagnosis of severe idiopathic short stature (SISS). These conditions are quite heterogeneous, including children with isolated growth failure and others who also have other abnormalities such as developmental delay or a constellation of congenital anomalies (syndromic short stature). Sometimes, the disorder appears to primarily affect the growth plate, which drives skeletal growth and thereby determines overall body proportions, whereas in other children, the disorder affects skeletal and non-skeletal tissues equally. Some cases of SISS have a polygenic inheritance while others appear to follow a Mendelian inheritance model, recessive, dominant or X-linked. Very recently, genome-wide analysis for copy number variants (CNVs) and whole-exome sequencing have begun to identify some of the molecular etiologies of these disorders.1 Identifying the molecular etiology of growth disorders has clinical and scientific value. Clinically, identifying a molecular cause prevents extensive further testing and may direct anticipatory care for associated medical problems. For example, we recently studied aggrecan (ACAN) gene mutations in families with autosomal dominant short stature and accelerated skeletal maturation. These mutations affect both growth plate cartilage, causing linear growth failure, and also articular cartilage, causing osteochondritis dissecans and early-onset osteoarthritis.1 Etiological classification of idiopathic growth failure allows more precise characterization of prognosis and response to treatment, which are currently highly imprecise because of the locus heterogeneity. In some cases, finding the genetic etiology points to a novel treatment approach that targets the specific molecular pathway involved. The proposed project is central to the main focus of our group, the Section on Growth and Development, NICHD. Our primary goal is to investigate cellular and molecular mechanisms governing childhood growth and to gain insight into the many human genetic disorders causing childhood growth failure. The proposed project is well suited for the intramural program because it takes advantage of Clinical Center expertise to phenotype subjects with SISS. Study subjects: We will study subjects with SISS and nuclear family members. SISS will be defined by height SDS < -2.5 for age without evident cause after routine evaluation including: growth hormone axis evaluation; thyroid function testing; celiac disease screening; urinalysis; CBC; chemistry; karyotype (girls, for Turner syndrome); and testing for single gene defects based on the clinical evaluation (for example, SHOX or Noonan-associated genes). Candidate families will include isolated growth disorders and growth disorders that are accompanied by congenital anomalies, developmental delay, or other syndromic short stature. Strong preference will be given to subjects with a severe phenotype and a pedigree that indicates a Mendelian inheritance. Multiple independent families with the same phenotype will have priority. The pool of applicants for recruitment is large, and we receive many inquiries by emails and phone consultations from pediatric endocrinologists for advice regarding diagnosis and management of unusual growth disorders, including familial disease. Often these families are seeking further evaluation and are willing to participate in a research study. From this pool, we will be selecting pedigrees with very favorable Mendelian characteristics, for example de novo dominant occurrences where two normal parents have a child with SISS, and the child grows up to be an adult who passes this phenotype on to multiple grandchildren in the next generation. Subjects and family members will be brought to the NIH Clinical Center (NIHCC) for outpatient evaluation. Participants will be evaluated by pediatric endocrinology fellows (as part of our training program) and by senior staff to establish the clinical findings and construct a pedigree. Subjects will receive additional biochemical and imaging studies at the Clinical Center to complete the phenotyping and assign affected status. The growth abnormality will be evaluated by assessing body proportions, relative organ size, and skeletal imaging as indicated. Associated clinical abnormalities beyond altered growth will be characterized with the help of other Clinical Center subspecialists. Subjects and family members will be evaluated by SNP microarray and whole-exome sequencing. We anticipate 4-5 persons for each of 16-20 families, for a total of 72-90 whole-exome sequences. Half of the families will be recruited and studied within the first year and half in the second year. We will use freshly collected peripheral blood as the DNA source for SNP array and NextGen Sequencing. Analytic approach: The candidate genes will be chosen based on 1) inheritance state consistency, 2) population frequency in the ESP and UDP databases, and 3) predictions of deleteriousness. We will use VarSifter and the B road Institute Integrated Genome Viewer to filter and visualize these data. The genetic model will be dependent on the family's pedigree. For a simple trio, we will explore variants using genetic models including autosomal recessive, de novo (dominant), compound heterozygous, deletion/point mutation recessive, and X-linked (male only). The candidate variants will be identified using Boolean logic sets in VarSifter following intramural NHGRI/UDP methods. We will also use SNP microarray data to identify copy number variations, complete/single copy deletions, duplications, non-paternity, consanguinity for homozygosity mapping, uniparental isodisomy, mosaicism, and segregation patterns (bed file generation for use in VarSifter filter work). After a list of candidate sequence variants has been generated, annotation will include using the Exome Variant Server, Polyphen-2, MutationTaster, Sift, and CADD predictions of deleteriousness. Biological laboratory data will be included to prioritize candidate variants. Our group has expertise in the molecular mechanisms regulating both skeletal growth2,3 and growth of other tissues4,5, which may be helpful in this phase of the analysis. The most promising candidate mutations will be confirmed by Sanger sequencing and studied functionally, in vitro and/or in vivo. For mutations that affect skeletal growth, we will use experimental systems related to growth plate cartilage. For in vitro studies, we have experience transfecting chondrocyte cell lines, such as ATDC5, and primary chondrocytes. We will determine whether the mutation alters protein and/or cell function. In vivo studies can be used to explore pathophysiology. We have recently successfully used a new approach, the CAS9/CRISPR system to knockout multiple loci in mice (unpublished), which can be used again in the future to create mouse models efficiently. 1J Clin Endocrinol Metab, 2014 (PMID: 24762113) 2J Mol Endocrinol, 2014 (PMID: 24740736) 3Hum Mol Genet, 2012 (PMID: 22914739) 4Proc Natl Acad Sci U S A, 2013 (PMID: 23530192) 5Endocr Rev, 2011 (PMID: 21441345)

  Study phs001617

• Covid19 Gene expression

  The dataset contains the gene expression profile of each individual along with gene fusion events.

  Dataset EGAD00001010185