Search Results - EGA European Genome-Phenome Archive

Whole-Exome Sequencing and Targeted DNA Sequencing of Matched Ocular Melanocytosis and Uveal Melanoma

Ocular melanocytosis is the most important predisposing condition for the eye cancer uveal melanoma (UM). Here we used whole-exome and deep targeted sequencing to identify for the first time a clonal Gq pathway mutation in ocular melanocytosis, which gave rise to UM. Additionally, we elucidated the order in which canonical genetic aberrations were acquired during tumor evolution. These findings provide a mechanistic explanation for the well-known clinical association of ocular melanocytosis with UM, and they provide new insights into UM tumor evolution. Reprinted from: Durante MA, Field MG, Sanchez MI, Covington KR, Decatur CL, Dubovy SR, Harbour JW. Genomic evolution of uveal melanoma arising in ocular melanocytosis, with permission from Cold Spring Harbor Molecular Case Studies.

Study phs001835

VCRC Genetic Repository One Time DNA Protocol

The purpose of this study is to identify genes that increase the risk of developing vasculitis, a group of severe diseases that feature inflammation of blood vessels. Better methods are needed to recruit patients with these rare diseases into cohorts of adequate size for high-quality genetics studies, and the existing infrastructure of the Vasculitis Clinical Research Consortium (VCRC) provides the means for such recruitment. Results of these studies will provide vasculitis researchers with insight into the causes of these diseases and generate new ideas for diagnostic tests and therapies, and will be of great interest to the larger communities of researchers investigating vasculitis and other autoimmune, inflammatory, and vascular diseases. This study will enhance the VCRC Data and Specimen Repository.

Study phs001712

Multi-Modal Single-Cell and Whole-Genome Sequencing of Small, Frozen Clinical Specimens

Clinical application of single-cell sequencing technologies has been hampered by their need for quick processing of relatively large, fresh specimens. Here, we benchmarked the performance of a new technique for single-cell sequencing from snap-frozen clinical samples, vs. sequencing from fresh samples, on 5 samples from cutaneous melanoma brain metastasis, 6 samples from NSCLC brain metastasis, and 3 from uveal melanoma primary tumor. Additionally, we performed frozen sample sequencing of 20 uveal melanoma liver metastasis samples, and 3 cutaneous melanoma extracranial metastasis samples. Finally, for selected groups of the above-mentioned samples, we also performed TCR sequencing, SlideSeqV2 spatial transcriptomics, ultra-shallow whole-genome sequencing, and whole-exome sequencing, to present a comprehensive multi-modal profiling of all datasets.

Study phs003097

Autism Genome Project (AGP) Consortium - Whole Genome Association Study of over 1,500 Parent-Offspring Trios - Stage I and II

Autism spectrum disorders (ASDs) are highly heritable (~90%), yet the underlying genetic determinants are largely unknown. To understand the genetic and phenotypic heterogeneity in ASDs, we analyzed 2,611 strictly defined ASD families with over 1,000,000 single nucleotide polymorphisms (SNPs), and applied multiple analytical strategies to examine these families for SNPs and Copy Number Variation (CNVs) affecting risk for ASDs. Secondary analyses examined associations in more homogenous subgroups. Furthermore, the use of large control datasets permitted contrasting case and control samples and addressed the potential increased burden of rare CNVs in ASD. Our data have allowed us to discern key features of the ASD genomic architecture, find new susceptibility loci, and chart a course for future studies in ASDs.

Study phs000267

Cergentis FFPE-TLC

In this study, formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing is used as a novel technology for targeted detection of tumor-specific genomic structural variants (SVs) in the primary tumor of 29 colorectal cancer patients with metastatic disease. The tumor region was macrodissected and sequenced for 29 patients, and the "normal" region of the same slide was macrodissected and sequenced for 8 of these patients. SVs were found in the common fragile site (CFS)-associated genes MACROD2, PRKN, FHIT and WWOX as well as SVs caused by three LINE transposable elements. Tumor-specificity of selected SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated.

Study EGAS50000000427

Gene-Specific RNA Sequencing in PLCG2-Associated Immune Dysregulation with Cold Urticaria

This study utilized gene-specific RNA-sequencing of PLCG2 to screen for disease causing in-frame exon-skipping transcripts of PLCG2 in a collection of 9 subjects with cold urticaria, 2 subjects with known PLCG2-associated antibody deficiency and immune dysregulation (PLAID)-causing deletions of PLCG2 (positive controls) and 3 healthy subjects (negative controls). Full length cDNA of PLCG2 was generated using gene specific reverse transcription of peripheral blood mononuclear cell RNA. The full length PLCG2 cDNA was used as the template to create Illumina sequencing libraries. To identify the underlying genetic basis for the exon-skipping transcripts, trio-based whole genome sequencing was performed for probands in whom in-frame exon-skipping transcripts of PLCG2 were identified.

Study phs003807

Single-Cell ATAC and RNA Sequencing of Human Breast Cancer Reveals Salient Cancer-Specific Enhancers

Matched single-cell chromatin accessibility sequencing (scATAC-seq) and single-cell transcriptomic sequencing (scRNA-seq) were performed for 12 human breast tumor samples, 4 normal human mammary reduction samples, and 4 human breast cancer cell lines (HCC1143, SUM149PT, MCF7, and T47D). Both scATAC-seq and scRNA-seq assays resolved the underlying cellular heterogeneity in chromatin accessibility and transcriptional output for each patient sample. In this work, we quantitatively linked variation in chromatin accessibility to gene expression across malignant and non-malignant cell types from patient samples. We then showed that our findings were recapitulated in the breast cancer cell line samples. These data will serve as an important resource for the single-cell genomics and breast cancer research communities.

Study phs003253

Establishment and genomic analysis of mixed phenotypic acute leukemia cell lines

Among acute leukemias, mixed phenotype acute leukemias (MAPL; mixed phenotype acute leukemiae), which have both acute myeloid and acute lymphocytic leukemia traits, are generally considered resistant to chemotherapy, especially those with t(9;22) MPAL has a poorer prognosis than other forms of MPAL and is a challenge to overcome. MPAL accounts for less than 1% of all acute leukemias, and the rarity of this disease makes it difficult to conduct clinical studies to develop treatments for the disease. Therefore, we planned to establish cell lines based on acute leukemia cells (JMPAL-1) obtained from MPAL patients, and to analyze information such as gene mutations related to disease development based on these cell lines for therapeutic purposes.

Study JGAS000721

Investigation of a method for generating cells for regenerative medicine using comprehensive nucleic acid analysis of iPS cell-derived cardiomyocytes.

Regenerative medicine for heart failure is expected to restore cardiac function by using human iPS cells (hiPSCs). In our laboratory, it was shown that transplantation of cardiomyocytes (CMs) derived from hiPSCs into a pig model of myocardial infarction improves the disease condition. However, the instability of differentiation efficiency and tumorigenicity after transplantation are still issues to be resolved. We attempt to identify and analyze the genes and DNA methylation associated with the induction of differentiation of hiPSCs into CMs with the aim of achieving stable induction of CMs differentiation. Furthermore, we aim to analyze genes involved in tumorigenesis in CMs, and to develop a predictive marker for tumorigenesis to ensure the safety of cells before transplantation.

Study JGAS000665

TRAIP promotes DNA damage response during genome replication and is mutated in primordial dwarfism

DNA lesions encountered by replicative polymerases threaten genome stability and cell cycle progression. Here we report the identification of mutations in TRAIP, encoding an E3 RING ubiquitin ligase, in patients with microcephalic primordial dwarfism/Seckel syndrome. We establish that TRAIP relocalizes to sites of DNA damage where it is required for optimal phosphorylation of H2AX and RPA2 during S-phase in response to UV irradiation, as well as fork progression through UV-induced DNA lesions. TRAIP is necessary for efficient cell cycle progression and mutations in TRAIP therefore limit cellular proliferation, providing a potential mechanism for microcephaly and dwarfism phenotypes. Human genetics thus identifies TRAIP as a novel component of the DNA damage response to replication-blocking DNA lesions.

Study EGAS00001001501

GCT WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

For GCT cohorts, OvCaRe cases were reviewed, including frozen material, by at least two expert gynecopathologists prior to inclusion in the sequencing cohort who provided the confirmation on final selected cohort. Frozen H&E from Tokyo were also used for evaluation along with representative H&E photos and review done at the Jikei School of Medicine. All GCT tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

Dataset EGAD00001003267

CCOC WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

For CCOC cohorts, OvCaRe cases were reviewed, including frozen material, by at least two expert gynecopathologists prior to inclusion in the sequencing cohort who provided the confirmation on final selected cohort. Frozen H&E from Tokyo were also used for evaluation along with representative H&E photos and review done at the Jikei School of Medicine. All CCOC tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

Dataset EGAD00001003265

Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

Dataset EGAD00001005035

Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA)

The Resource for Genetic Epidemiology Research on Aging (GERA) Cohort was created by a RC2 "Grand Opportunity" grant that was awarded to the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) and the UCSF Institute for Human Genetics (AG036607; Schaefer/Risch, PIs). The RC2 project enabled genome-wide SNP genotyping (GWAS) to be conducted on a cohort of over 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its RPGEH. The purpose of the RPGEH is to facilitate research on the genetic and environmental factors that affect health and disease by linking together clinical data from electronic health records, survey data on demographic and behavioral factors, and environmental data from various sources, with genetic data derived from biospecimens collected from participants. At the time of the award of the RC2 project in late 2009, the RPGEH had established a cohort of about 140,000 individuals who had answered a detailed survey, provided saliva samples for extraction of DNA, and given broad consent for the use of their data in studies of health and disease. To maximize the diversity of the resulting sample, the GERA cohort was formed by including all racial and ethnic minority participants with saliva samples (N = 20,925; 19%); the remaining participants were drawn sequentially and randomly from white non-Hispanic participants (89,341; 81%). A total of 110,266 participant samples were included to ensure that at least 100,000 were successfully assayed. The resulting GERA cohort is 42% male, 58% female, and ranges in age from 18 to over 100 years old with an average age of 63 years at the time of the RPGEH survey (2007). The sample is ethnically diverse, generally well-educated with above average income. Approximately 69% of the participants are married or living with a partner. Length of membership in KPNC averages 23.5 years. UCSF and RPGEH investigators worked with the genomics company Affymetrix to design four custom microarrays for genotyping each of the four major race-ethnicity groups included in the GERA Cohort, described in detail in Hoffmann et al., 2011a and 2011b. Following genotyping and quality control procedures, and after removal of invalid, discordant, or withdrawn samples, about 103,000 participants were successfully genotyped. The resulting genotypic data were linked to survey data and data abstracted from the electronic medical records. As described below, all RPGEH participants were mailed new consent forms with explicit discussion of the placement of data in the NIH-maintained dbGaP. About 77% of participants returned completed consent forms, resulting in a final sample size of 78,486 participants in the GERA Cohort with data for deposit into dbGaP. Origins of the RPGEH GERA Cohort The goal in creating the RPGEH GERA cohort was to create a large, multiethnic, and comprehensive population-based resource for research into the genetic and environmental basis of common age-related diseases and their treatment, and factors influencing healthy aging and longevity. The GERA Cohort consists of a diverse cohort of more than 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its Research Program on Genes, Environment and Health (RPGEH). KPNC is an integrated health care delivery system with a population of about 3.3 million people in northern California. The membership of KPNC is representative of the general population in the 14 county area in which facilities are located, although the membership is underrepresented for the extremes of income at both ends of the spectrum. The RPGEH utilizes the longitudinal electronic health records (EHR) of KPNC to obtain clinical, laboratory, imaging and pharmacy information on all cohort members, to which personal demographic, behavioral and health characteristics have been added through member surveys. The GERA Cohort comprises a subsample of the RPGEH participant cohort, and was created through the RC2 award from the NIA, NIMH, and NIH Common Fund as described above. GERA Study Design The GERA Cohort is a subsample, as described above, of the longitudinal cohort enrolled in the Kaiser Permanente RPGEH. The RPGEH cohort includes about 400,000 survey participants of whom about 200,000 have provided broad consent and a sample of saliva or blood for use in studies of genetic and environmental factors in health and disease. The GERA Cohort was developed from a mailed survey sent to all adult members of KPNC who had been members for two years or more in 2007. All survey respondents were contacted and asked to complete a consent form; those who completed consent forms were asked to provide a saliva sample. Additional male participants were added to the RPGEH through inclusion of the Northern California sample of the California Men's Health Study (CMHS) cohort of about 40,000 men from KPNC, ages 45-69 years old at the time of the CMHS survey in 2002-2003. The CMHS participants contributed about 15,400 saliva samples to the RPGEH and were eligible for inclusion in the GERA Cohort. CMHS participants were included according to the same sampling design as for the RPGEH cohort as a whole. Specifically, all minority participants were selected for inclusion in order to maximize representation of minorities in the GERA Cohort, and Non-Hispanic White participants were selected at random to complete the sample of 110,266 GERA Cohort participants. GERA Genotypic Data High-density genotyping was conducted at UCSF using custom designed Affymetrix Axiom arrays, as described in Hoffmann et al. (2011a; 2011b). To maximize genome-wide coverage of common and less common variants, four specific arrays were designed for individuals of Non-Hispanic White (EUR), East Asian (EAS), African-American (AFR), and Latino (LAT) race/ethnicity. There was broad overlap among the SNPs on the arrays, which were designed using a hybrid greedy imputation algorithm (Hoffmann et al., 2011b) applied to genotype information validated by Affymetrix from the 1000 Genomes Project. However, in order to capture low frequency variants specific to particular race-ethnicity groups, SNP content varies between arrays. A more detailed description of the process of genotyping and results is included in Genotyping of DNA Samples. Description of the analyses of population structure and development of principal components for adjustment of population structure is included in Population Structure Analysis. GERA Phenotypic Data RPGEH and CMHS Survey Data. The sources of data on demographic and behavioral factors deposited in dbGaP for the GERA Cohort are the RPGEH and CMHS surveys. Data on common demographic factors such as gender, race/ethnicity, marital status, and education and on behavioral factors such as smoking, alcohol consumption, and body mass index, have been cleaned, edited, reconciled between the two surveys, and compiled into summary indices, where appropriate, for deposition into dbGaP. A more complete description of the survey variables is included in Survey Variables Documentation. Please note that the terms of use of the GERA Cohort Data, as specified in the Data Use Certification (DUC), prohibit the use of survey variables as outcomes in analyses. For example, a genome-wide association study (GWAS) of education or smoking is not permitted as specified by the DUC. Only health conditions can be used as outcome variables in analyses. Health Conditions derived from Kaiser Permanente Electronic Medical Records. Data on the occurrence of health conditions in participants in the GERA Cohort have been derived from summarizing ICD-9 coded diagnoses in Kaiser Permanente's electronic medical records. An algorithm that aggregates specific ICD-9 codes into appropriate diagnostic groups for selected conditions is applied to outpatient and inpatient databases; see Disease and Conditions Definitions Documentation for details. The criterion for including a condition as "present" for a participant is the occurrence of two or more diagnoses within a diagnostic category occurring on separate days. Two or more is used as the criterion in order to reduce false positives due to mistakes or rule-out diagnoses. When compared with validated disease registries, the criterion of 2+ diagnoses yields high specificity and good sensitivity. ICD-9 codes in the electronic records are specified in several ways. For outpatient visits occurring during the period 1995 to 2006, diagnoses were assigned by the treating physician who endorsed specific diagnoses on an optically scanned list that varied by specialty. Beginning in 2006 with the advent of an integrated, fully electronic medical record, outpatient diagnoses are made by physicians/ providers using a pull down menu. Discharge diagnoses from inpatient stays are specified by physicians and coded by specially trained coders. Databases of ICD-9 codes for diagnoses assigned at outpatient visits, or as one of the discharge diagnoses following inpatient stays, are complete and available for all KPNC members dating back to 1995. Although the average length of KPNC membership among GERA cohort members is 23.5 years in 2007, not all have been members since 1995, so the history for some conditions, such as those that are not chronic or recurrent, may not be complete for all cohort members. The year of first membership in KPNC is included as a variable in the list of survey variables, enabling investigators to estimate the number of years of observation of each Cohort member. RPGEH Access and Collaborations Website and Procedures The RPGEH maintains a web portal for inquiries and applications for collaboration and access to data. The url is: https://rpgehportal.kaiser.org/. RPGEH has an application process and an Access Review Committee that reviews applications for collaboration and use. For more details, please contact RPGEH through the website.

Study phs000674

Common Fund (CF) Genotype-Tissue Expression Project (GTEx)

Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the Biobank page for more information. GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at www.gtexportal.org.

Study phs000424

Genome-wide Association Study for Non-syndromic Clefts in the African Population: CIDR

The focus of this project is to identify genetic variants that are associated with orofacial clefts in African populations in sub-Saharan Africa. Most genetic studies of CLP (including the vast majority of GWAS) have been conducted in populations of European origin with only a few focused on Asian or African populations. We choose to study the genetics of these complex traits in African populations because, African populations have the greatest genetic variation amongst the various populations in the world by virtue of being the primary ancestral population to modern humans (Cavalli-Sforza and Feldman, 2003; Ramsay et al., 2011). Therefore, the potential for finding novel loci for CLP is quite high. To date 6 genome wide association studies (GWAS) for cleft lip with or without cleft palate (CL/P) have been conducted and 18 risk loci identified (Birnbaum et al., 2009; Grant et al., 2009 ; Beaty et al., 2010; Mangold et al., 2010; Ludwig et al., 2012; Sun et al., 2015). All these studies have either been conducted in European populations, Asian populations or both. There is currently no published GWAS for clefts in African populations. African populations represent a novel and richly productive populations for genetic and environmental exposure studies for CL/P. Investigating the presence of genetic variants in diverse population groups can identify novel variants and candidate genes that are population specific. Environmental factors may also increase the risks in certain population groups due to genetic susceptibility and/or specific exposures. Understanding the role these susceptibility genes play in the effects of environmental risk factors can inform strategies designed towards reducing the outcome of these complex traits, e.g. through the modification of the environmental influences. The study population comprises a large number of individuals (3205 individuals) from Africa (Ghana, Ethiopia and Nigeria). There are cases, case triads (nuclear families), as well as controls with no history of OFC nor other developmental defects.

Study phs001090

National Institute on Aging - Late Onset Alzheimer's Disease Family Study: Genome-Wide Association Study for Susceptibility Loci

Alzheimer disease is the most common neurodegenerative disorder of the elderly affecting an estimated five million Americans. Genetic factors contribute to the risk for disease with heritability estimates ranging from 57% to 79%. More than a decade ago, the ε4 variant of APOE was identified and remains the most consistently replicated genetic variant influencing the risk of late onset Alzheimer disease. A segregation analysis suggests there may be four additional genes influencing the age-at-onset of Alzheimer disease. In 2007 there were 968 association studies in 398 candidate genes reported, but none replicated consistently. There are many reasons for the lack of consistency, but one important reason for the lack of progress is the paucity of a sufficient number of well characterized families and patients available to the entire scientific community. The extensive effort and expense required to ascertain such a population has been addressed by the NIA-LOAD Family Study. Its goal is to identify and recruit families with two or more siblings with the late-onset form of Alzheimer's disease and a cohort of unrelated, non-demented controls similar in age and ethnic background, and to make the samples, the clinical and genotyping data and preliminary analyses available to qualified investigators world-wide. Genotyping by the Center for Inherited Disease Research (CIDR) was performed using the Illumina Infinium II assay protocol with hybridization to Illumina Human 610Quadv1_B Beadchips. This genotyping represents the largest collection of families ever assembled with Alzheimer's disease combining the NIA-LOAD Genetics Initiative Multiplex Family Study, the National Cell Repository for Alzheimer's Disease (NCRAD) with additional controls from the University of Kentucky. These genotyping results will serve as a focal point for future research that will identify all of the remaining genetic variants in Alzheimer's disease.

Study phs000168

Local In Time Statistics for processual research

Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

Study EGAS00001002520

Best Practices for DACs

Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

Documentation access/data-access-committee/best-practices

Gut 16S rRNA/FINRISK 2002

Gut microbiome 16S rRNA raw data for N=7174 FINRISK 2002 participants. FINRISK fecal samples were mailed to the Knight laboratory at the University of California (San Diego, CA), for microbiota sequencing using the standard Earth Microbiome Project protocols (https://earthmicrobiome.org/protocols-and-standards/). DNA was extracted using a magnetic bead-based DNA extraction protocol. Amplicon sequence data for the V4 region of the 16S rRNA gene was generated using 515F (Parada) and 806R (Apprill) primers. For a total of 25μl reaction volume, 13 µl PCR-grade water was combined with 10 µl PCR master mix (Platinum Hot Start PCR Master Mix, 2x, ThermoFisher), 0.5 µl forward primer (10 µM), 0.5 µl reverse primer (10 µM), and 1 µl template DNA. Amplification was performed in triplicate reactions, and triplicate PCR reactions were pooled afterwards. Expected products were visualized on agarose gels (300–350 bp) and quantified with Quant-iT PicoGreen dsDNA kit (Invitrogen). Equal amounts (240 ng) of amplicon were combined for each sample and cleaned (MoBio UltraClean PCR Clean-Up Kit). Cleaned amplicon pools were sequenced with 515F and 806R primers.

Dataset EGAD50000000287

Novel Factors for Unexplained Phenotypes of Subclinical Carotid Atherosclerosis

The overall goal for this study was to determine the genetic factors associated with extreme phenotypes of subclinical atherosclerosis (protective and deleterious). Study participants were selected from the Northern Manhattan Study (NOMAS), a population based cohort study investigating stroke and stroke risk factors in Northern Manhattan. Cases and controls were individuals at the extreme ends of the distribution for carotid intima-media thickness and carotid plaque, with cases defined as individuals with subclinical atherosclerosis that could not be explained by traditional vascular risk factors (USAth) and controls defined as individuals with unexplained protection against atherosclerosis (UPAth).

Study phs001560

Biesecker Lab (NHGRI) Whole Genome Medical Sequencing for Gene Discovery

We aim to use whole-genome medical sequencing (WGMS) to discover causative molecular lesions for a set of rare, severe phenotypes hypothesized to be caused by either somatic mutations, germline de nova heterozygous mutations, germline inherited recessive, or germline inherited dominant mutations in currently unknown or uncharacterized genes. The goal of this research is threefold: to identify causative sequence variants for disorders whose molecular etiology was previously unknown, to apply this insight to both the rare disorders under study and more common phenotypes, and to enhance the study of mutation on a genome-wide level.

Study phs001348

Stanford Center for Urologic Genomics: Genomic Analysis of Benign Prostatic Hyperplasia

Benign prostatic hyperplasia (BPH) entails growth in the central regions of the prostate gland and is common among older men. BPH obstructs urinary outflow, resulting in voiding symptoms for which current treatments that target prostate physiology are only partially effective. A better understanding of BPH may suggest new treatment strategies that target its pathophysiology. The overall goal of the study is to apply next-generation sequencing-based approaches to investigate BPH, to discover new insight into BPH disease processes and new targets for precision therapy, and to determine whether the hyperplasia reflects underlying clonal expansions of prostatic cells.

Study phs001698

Development of Novel Synovial Sarcoma Organoids Models for Drug Discovery

Although synovial sarcoma has been studied using established cell lines and mouse models, effective treatments remain limited. We treated five patients with synovial sarcoma between 2022 and 2023 and established organoid cultures from resected tumor specimens using a modified air-liquid interface method. After serial passaging, organoids were successfully xenografted into NOD-scid IL2Rgnull (NSG) mice in three cases. The established organoids retained SS18-SSX fusion transcripts and demonstrated histological and genetic similarities to the original tumors. These organoid models provide a reliable platform for studying synovial sarcoma biology and hold promise for the development of novel therapeutic strategies.

Study JGAS000806

Single-cell gene expression data from CD8+ T cells from two Austrian COVID19 patients stimulated with wildtype and mutant SARS-Cov-2 peptides

The data contains single-cell gene sequencing data (10x Genomics) from FACS-purified CD8 T lymphocytes from two Austrian patients. The cells were stimulated with one MHC class I peptides obtained from a common (wild type) variant and an emerging mutant variant of the SARS-Cov-2 virus. Then the samples were multiplexed using hashtag oligos. We provide the raw and aligned sequence data for: i. The single-cell experiments ii. The PCR-amplified samples for enrichment of the hashtag oligo multiplexing barcodes iii. The PCR-amplified samples for enrichment of the T Cell Receptor (TCR) VDJ region for immuno-profiling. The samples and libraries were processed and obtained in collaboration between St. Anna Children's Cancer Research Institute (CCRI), CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the Medical University of Vienna. The cell barcodes and processed data has been submitted to the GEO database with GEO accession GSE166651.

Dataset EGAD00001006995

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