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• NHLBI's Collection of Datasets for Health / Medical / Biomedical Research Use (Public Posting of Genomic Summary Results: Not Allowed)

  This collection contains all of NHLBI's authorized individual-level genomic datasets currently in dbGaP that are approved for Health/Medical/Biomedical (HMB) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. The public posting of Genomic Summary Results are not allowed. Access to this study collection will include additional authorized individual-level HMB datasets that become available. Renewal of this study collection is required annually. To request access to this study collection, select phs003133 in the dbGaP Authorized Access System.

  Study phs003133

• Transcriptome Changes in ASD (NRXN1α+/-) iPSC-derived neurons

  NRXN1 deletions are identified as one of major rare risk factors for autism spectrum disorder (ASD) and other neurodevelopmental disorders. ASD has 30% co-morbidity with epilepsy and the latter is associated with excessive neuronal firing. NRXN1 encodes hundreds of presynaptic neuro-adhesion proteins categorized as NRXN1α/β/γ. Previous studies on cultured cells show that the short NRXN1β primarily exerts excitation effect, whereas the long NRXN1α which is more commonly deleted in patients involves in both excitation and inhibition. However, patient-derived models are essential for understanding functional consequences of NRXN1α deletions in human neurons Quantitative RNA sequencing was performed by BGI using 50bp single-end strategy with BGI-SEQ500 sequencing device on iPSC-derived cortical neurons from 6 control lines; (2VC1, 3VCX1, 3VC2, 4C3, 4CX1, NCRM-1) of 4 healthy donors, and 4 NRXN1α+/- lines; (ND1C1, ND2C11, ND2CX1, ND4-1C2) from 3 ASD patients.

  Study EGAS00001005536

• Mapping the lineage-retained antigen landscape in neuroblastoma

  Neuroblastoma is among the deadliest pediatric solid tumors, and relapse is frequently driven by lineage plasticity between adrenergic (ADRN) and mesenchymal (MES) cell states that escape conventional and targeted therapies. This project aims to identify tumor antigens that are retained across both lineage states and are therefore suitable for T-cell–based immunotherapy resistant to lineage switching, including non-canonical antigens derived from the "dark proteome." To support this aim, we generated paired RNA-sequencing and ribosome profiling (Ribo-seq) data from neuroblastoma cell lines, patient-derived tumor organoids, and primary patient tumors spanning ADRN and MES states. The RNA-seq data enable custom transcriptome assembly to recover non-reference and non-canonical transcripts, while Ribo-seq maps actively translated canonical and non-canonical open reading frames at codon resolution. Together these data provide the molecular substrate for systematic discovery of lineage-retained, translation-supported neuroblastoma antigens.

  Study EGAS00001008445

• MAITS in HCC

  Hepatocellular Carcinoma (HCC) is a leading cause of cancer-related death and can be considered a prototype of inflammation-derived cancer arising from chronic liver injury. The cell composition of the HCC tumor immune microenvironment (TiME) has a major impact on cancer biology as the TiME can have divergent capacities on tumor initiation, progress, and response to therapy. Recent development of multi-omics and single-cell technologies help us to comprehensively quantify the cellular heterogeneity and spatial organization of the TiME and to further our understanding of antitumor immunity. We investigated the cellular composition of liver cancer patient samples (n=8) using single-cell RNA-seq. For this purpose, mononuclear cells were isolated from human liver cancer samples. Three locations within the tumor-bearing liver were used: adjacent liver, rim and tumor core. Then, cells were FACS sorted (either CD45+ cells or MAIT cells) and subjected to 10X Chromium-based scRNA-seq. We investigated immune cell changes and the cellular heterogeneity of the HCC TiME with a focus on MAIT cells. Annotated H5 files are provided. Clinical metadata including TMN stage, sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Further details on the study can be obtained in our paper once it’s published.A complementary dataset derived from ultrahighplex CO-Detection by indEXing (CODEX) from paired patient samples can be accessed through The Cancer Imaging Archives (TCIA) under DOI: https://doi.org/10.7937/bh0r-y074.

  Study phs003279

• A Whole Genome Association Search for Type 2 Diabetes Genes in African Americans

  Over 2.8 million African Americans have type 2 diabetes mellitus (T2DM). This represents approximately 13% of the African American population and a significant proportion of the 21 million Americans living with diabetes. On average, an African American individual is twice as likely to have T2DM as a European American peer. Our research group has been actively involved in the study of African American diabetes genetics for over 15 years. We hypothesize that genes contributing to the development of T2DM in African Americans exist and can be located using modern molecular genetic methods. With the exception of TCF7L2(Transcription factor 7-like 2) evidence to date suggests variants that contribute T2DM risk in European-derived populations are not significant contributors to African American T2DM risk. We have performed a SNP-based Whole Genome Association (WGA) analysis on the Affymetrix 6.0 in a case control population of over 1000 African American T2DM cases and over 1000 non-diabetic controls. The DNAs have been collected from participants using uniform criteria from North Carolina and neighboring states. Genotype data will be subjected to extensive genetic analysis with the goal of defining a priority list of SNPs for genotyping in independent populations for confirmation and further detailed analysis.

  Study phs000140

• Angelman, Rett, Prader-Willi Syndrome Consortium (ARP) Rett Syndrome Natural History Protocol

  This observational study will involve the comprehensive assessment of the clinical features of Rett syndrome with this Rare Diseases Clinical Research Network. A clinical database of 1350 individuals with Rett syndrome including MECP2 mutation status for the purpose of elaborating phenotype-genotype correlations will be established. Eligible participants will be enrolled in the natural history study for 11 years from the 4 clinic sites currently involved with Rett syndrome (BCM, GGC, and UAB, CHB) as well as from the several thousand registrants in the International Rett Syndrome Foundation registry who will be invited to the nearest consortium site involved in Rett syndrome. Potential participants are expected to have had determination of their MECP2 mutation status, but will not be excluded should no mutation be present. All individuals who meet criteria and are currently receiving care from study sites will be invited to participate (N>600). Additional participants will be invited through the assistance of the International Rett Syndrome Foundation (IRSF). All individuals with RS registered with IRSF will be invited to participate in this study via the IRSF website and the IRSF newsletter. Potential participants will be apprised of the participating study sites and invited to contact one of the sites based on feasibility of travel. Inasmuch as the enrollment goal of 1350 participants is 40% of the current IRSF registry, we believe this will be a representative sampling. Bias can certainly occur based on travel requirements, level of interest, and other factors. However, inclusion of such a large sample should minimize sampling bias. No travel expenses will be covered, so it is likely that participants will be those with geographic proximity to Houston, Greenwood, Birmingham, or Boston. From the sample pool described above, the aim is to conduct the observational longitudinal (natural history) study on up to 1350 participants with classic Rett syndrome and variant forms of Rett syndrome, that is, participants who fully meet the established clinical criteria for Rett syndrome and those who meet some but not all of these criteria. All participants expressing MECP2 mutations irrespective of phenotype will be eligible for enrollment. For each of the eight common genetic mutations as well as those with large scale deletions, the prevalence of the following RS characteristics will be estimated for each age category and overall: seizure presence and frequency, ambulation status, scoliosis, ECG abnormality, breathing irregularities while awake, feeding difficulties, growth as measured in percentiles from NCHS standards curves, the presence of osteopenia as evidenced by bone fracture, and the presence of gallbladder disease. Both incidence and prevalence estimates will be made using a combination of data obtained at the regularly scheduled clinical visits and that obtained from the medical history. Incidence estimates will be calculated using time-to-event analyses (e.g., Kaplan-Meier survival curves) with appropriate calculations of standard errors and 95% confidence intervals. Cox proportional hazard regression models will be used to allow control for other factors, and t-tests will be calculated on the coefficients themselves. Appropriate transformations on explanatory variables will be used as deemed necessary in Cox models. Prevalence estimates will be calculated from estimates of proportions with exact confidence intervals. For a sample size of 275, the standard error of the estimate will not exceed 0.03 (3%) and for a sample size of 60, the standard error of the estimate will not exceed 0.06 (6%).

  Study phs000574

• Genome-Wide Association Study of Endometrial Cancer in the Epidemiology of Endometrial Cancer Consortium (E2C2)

  Endometrial cancer, the most common gynecological malignancy in the United States, has both an environmental and genetic component. To this end, we conducted a genome-wide association study to identify genes involved in endometrial cancer using studies from the NCI-supported Epidemiology of Endometrial Cancer Consortium (E2C2). For the discovery stage we included samples from 6 cohort and 7 case control studies through 2007. The total number of cases genotyped were 2,307, white women of European descent, and 2,307 matched controls using the Illumina HumanOmniExpress platform. We conducted the replication using the Infinium HumanExome BeadChip, which successfully genotyped 177,139 variants in 1055 cases and 1778 controls from four ethnically diverse studies that are part of the Epidemiology of Endometrial Cancer Consortium (E2C2). The overall goal is to determine whether certain genotypes are predictive of future endometrial cancer risk, and whether the genotypes interact with established endometrial risk factors.

  Study phs000893

• PREDICT-HD Huntington Disease Study

  The purpose of this project is to make clinical measurements from the PREDICT-HD consortium available through the dbGaP mechanism. The phenotype data will first be converted into a community open standard and subsequently exported to dbGaP for archival and open access distribution of the results of the studies. This will permit members of the scientific community to utilize a permanent resource for investigating the interactions of phenotypes upon an international cohort of early Huntington Disease. In version 2 cut of the data we provided HD CAG repeat lengths for both alleles as well as enrollment age of all participants. We have also generated unique identifiers prospectively compatible with the larger initiative GWAS in Huntington's Disease project (also on DbGaP). As such, the version 1 cut of the data was mainly proof of concept and should be deprecated. Going forward, all updates will add-on to version 2 cut of the data. In version 3 cut of the data, we provided baseline or the first usable MRI T1-weighted imaging analysis subcortical and cortical segmentations and cortical parcellations based on a customized Freesurfer 5.2 pipeline developed at The University of Iowa. The customizations to the standard pipeline were mainly to improve bias field correction and image normalization such that segmentation of gray, white, internal csf, dura and surface CSF are optimized for the Freesurfer pipeline. There are 1111 subjects with results in this data release. In version 4 cut of the data, we provided all longitudinal clinical measurements for all subjects (total of 1476) assessmented or enrolled through the end of 2013. Additionally, we are providing measurements on 39 baseline FDG PET images spatially normalized by SPM5 into MNI space, relative regional metabolic values computed in 120 volumes of interest (VOI) defined in the Automated Anatomical Labeling (AAL) Atlas (Tzourio-Mazoyer et al. 2002), and global metabolic values calculated by SPM standard mean voxel value (within per image fullmean/8 mask). This project is a funded ancillary study of PREDICT-HD. In version 5 cut of the data, we provided the first of many forthcoming results from ancilliary studies of PREDICT-HD. In this data cut, we provide individual subject results derived from structural MRI data. The earliest MRI session for each subject was used. The results summarized represent source based morphometry loading coefficients for 23 components (see: "Patterns of Co-Occurring Gray Matter Concentration Loss across the Huntington Disease Prodrome", Ciarochi et al., 2016, Front Neurol. 2016; 7: 147, Published online 2016 Sep 21. doi: 10.3389/fneur.2016.00147]. In this version 6 cut of the data, we provide a full set of derived data, more than 10,000 raw MRI images, and ancillary study data sets. For sample information please link to: PREDICT-HD Biospecimen Resources

  Study phs000222

• Genome-wide genetic and epigenetic dataset of pancreatic acinar cell carcinomas

  Pancreatic acinar cell carcinoma (ACC) is an aggressive exocrine tumor with largely unknown biology. To identify potential targets for personalized treatment, integrative genome- and epigenome-wide analyses were performed. The results show frequently aberrant DNA methylation, abundant chromosomal amplifications and deletions, and mutational signatures suggesting defective DNA repair. In contrast to pancreatic ductal adenocarcinoma, no recurrent point mutations are known. The tumor suppressors ID3, ARID1A, APC, and CDKN2A are frequently impaired also on the protein level and thus potentially affect ACC tumorigenesis. Consequently, this work identifies potential novel therapeutic targets in ACC for drugs recently approved for precision cancer therapy.

  Study EGAS00001002533

• Duplexseq of the interstrand crosslinks_WGS

  One of the most dangerous forms of DNA damage are interstrand crosslinks (ICLs), which covalently crosslink the two strands of the DNA double helix. The repair of these lesions is crucial for cellular survival due to their ability to block transcription and DNA replication. Initially, the major pathway that has been described in ICL repair involves a network of 22 genes that are mutated in a severe human genetic disease known as Fanconi Anemia (FA). Using synthetic lethality screens in the near-haploid human HAP1 cell line, we recently identified two potentially novel regulators of ICL repair, C1orf112 and THAP12. Loss of C1orf112 and THAP12 causes hypersensitivity to ICL-inducing DNA damaging agents, such as Mitomycin C (MMC). Additionally, C1orf112-depleted cells show elevated levels of micronuclei and accumulation of DNA damage in S-phase. To better understand how C1orf112 and THAP12 mediate the repair of ICLs, we want to perform mutational signature analysis, using the BotSeq method. Therefore, WT, C1orf112 and THAP12 knockout cells were cultured in vehicle or MMC treated conditions for 10 days and the genomic DNA was isolated. FANCA and FANCD2 knockout cells are taken along as controls in this experimental setting. . This dataset contains all the data available for this study on 2023-04-20.

  Dataset EGAD00001010298

• Integrative genomic profiling of hepatocellular adenomas reveals recurrent FRK activating mutations and mutational processes of malignant transformation

  Hepatocellular adenomas (HCA) are benign liver tumors predominantly developed in women using oral contraception. Here, exome sequencing identified novel recurrent somatic FRK mutations that induce constitutive kinase activity, STAT3 activation and cell proliferation sensitive to Src inhibitors. We also found new recurrent mutations activating JAK1, gp130 or ß-catenin. Chromosome copy-number and methylation profiling revealed patterns that correlated with specific gene mutations and tumor phenotypes. Finally, integrative analysis of HCA transformed to hepatocellular carcinoma revealed ß-catenin mutation as an early alteration and TERT promoter mutations as associated with the last step of the adenoma-carcinoma transition. In conclusion, we identified the genomic diversity in benign hepatocyte proliferation, new therapeutic targets and the key genomic determinants of the adenoma-carcinoma transformation sequence. Significance: Malignant transformation of benign adenoma into malignant carcinoma is frequently observed in several epithelial tumor types. Adenoma-carcinoma transition is crucial for the patient prognosis, however, little is known on the molecular mechanisms involved. Here, we performed an integrated genomic analysis of hepatocellular adenomas (HCA). Among several novel gene mutations, we identified recurrent somatic mutation activating FRK, a Src-like kinase. FRK activating mutations induce STAT3 activation and cell proliferation that can be targeted by Src inhibitors. Focusing on malignant transformation of HCA in hepatocellular carcinoma, we identified CTNNB1 and TERT promoter mutation as early and late genomic events involved in adenoma-carcinoma transition. In conclusion, we propose new therapeutic targets and an identification of adenomas with the highest risk of malignant transformation. Highlights: - FRK is activated by somatic recurrent mutations. - FRK mutants promote cell proliferation sensitive to src inhibitors. - CTNNB1 activation is an early event in HCA transformation. - TERT promoter mutations are associated with adenoma-carcinoma transition.

  Study EGAS00001000679

• A system-wide approach to monitor responses to synergistic BRAF and EGFR inhibition in colorectal cancer cells

  Molecular heterogeneity of tumors, epigenetic changes and a diverse range of molecular mechanisms are main contributors to drug resistance, which represents one of the great challenges in cancer treatment. A deeper understanding of the molecular biology of cancer has resulted in better targeted therapies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has to some extent also been observed in colorectal cancer (CRC) patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block resistance. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant CRC cells as a well-define model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both well-known and novel responses. We primarily observe widespread upregulation of tyrosine kinases (RTKs) and and metabolic pathways. This points to by which the treated cells switch energy sources as a defensive response entering a quiescent like state, while activating signalling to re-activate the MAPK pathway.

  Study EGAS00001002654

• NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (Ischemic Stroke Genetic Study, ISGS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Ischemic Stroke Genetics Study (ISGS) is a study of newly onset cases (~600) with ischemic stroke (a stroke due to sudden interruption of blood flow to a part of the brain) compared with sex- and age-matched non-stroke participants. The study was conducted to determine the genes and their variants that contribute to an individual's risk of developing an ischemic stroke. The coordination of the recruitment and flow of the samples occurred at the Mayo Clinic, Jacksonville, FL, under the direction of James F. Meschia, MD. The University of Virginia (Stephen S. Rich, PhD) served as the analytic site for the genetic data. All GWAS data on ISGS participants have been deposited into dbGaP. As part of the NHLBI Exome Sequencing Project, DNA from a subset of ISGS participants will undergo exome sequencing. For the NHLBI ESP, a subset of 92 individuals with lacunar (small vessel) or atherosclerotic (large vessel) TOAST subtypes were selected from among all ISGS participants, excluding those individuals with TOAST subtypes of stroke of other etiology or of stroke with undetermined etiology. All 92 samples pass initial quality control metrics and 89 samples completed exome sequencing. A total of 75 participants with appropriate consent and variant calls had their genetic and phenotypic data deposited into dbGaP.

  Study phs000546

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Epigenome wide DNA methylation assay of gingivo-buccal oral squamous cell carcinoma using single base resolution high throughput array

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out epigenomic (n=87) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India and genome-wide DNA methylation assays were performed. DNA was isolated using DNeasy Blood and Tissue Kit (Qiagen). The purity and concentration was estimated using NanoDrop 2000 (Thermo Fisher Scientific). Approximately 500 ng genomic DNA from each sample was used for sodium bisulfite conversion using the EZ DNA methylation Gold Kit (Zymo Research, USA). Genome-wide DNA methylation was assayed using iScan (Illumina), for paired tumour and adjacent normal samples of 25 patients using the Infinium Human Methylation450 BeadChip and of 62 patients using the Infinium MethylationEPIC BeadChip.

  Study EGAS00001003896

• Oncogenic FOXL2C134W has gain-of-function chromatin remodeling activity that reprograms glucocorticoid receptor occupancy to promote ovarian granulosa cell tumor growth

  Adult type ovarian granulosa cell tumors (AGCTs) are rare malignancies with near universal somatic mutation c.C402G (p.Cys134Trp) in FOXL2, a forkhead box-family transcription factor important for ovarian function. Relapsed AGCT is incurable and the mechanism of the unique FOXL2 mutation remains incompletely understood. To identify FOXL2C134W-dependent pharmacologic synergies, we created and characterized endogenous FOXL2 isogenic AGCT cells and an AGCT tumoroid biobank. A drug screen identified that glucocorticoids promote FOXL2C134W-dependent AGCT growth. Epigenetic investigation revealed that the Cys134Trp mutation exposes latent DNA sequence-specific pioneering activity in FOXL2, a unique oncogenic mechanism. FOXL2C134W pioneering activity redirects glucocorticoid receptor chromatin occupancy to drive hyaluronan synthase 2 gene expression and increase extracellular hyaluronan secretion. Treatment of AGCT models with hyaluronidase reduces viability and this effect can be rescued by dexamethasone. Thus, gain-of-function pioneering activity contributes to the oncogenic mechanism of FOXL2C134W and creates a potentially targetable synergy with glucocorticoid signaling.

  Study EGAS50000000622

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• National Institute of Mental Health (NIMH) Amish Mennonite Bipolar Genetics Study (AmBiGen)

  Bipolar affective disorder is a severe, heritable condition affecting about one percent of the population. The mode of inheritance is poorly understood and probably involves multiple loci of small to moderate effect. In this project, we use genetic mapping and sequencing methods to identify genetic markers and variations that contribute to the risk of bipolar disorder. Individuals diagnosed with bipolar disorder are studied, along with their relatives. Phenotypic information obtained from clinical interviews and family history is correlated with genotypic information obtained from genetic marker and sequencing methods. The goal is to identify genes involved in bipolar disorder and related conditions so that better methods of diagnosis, treatment, and prevention can be developed.

  Study phs000899

• Prospective Analysis of Genotypes in Adults Undergoing Therapy for Lung Cancer (Paclitaxel Cohort)

  Lung cancer is frequently treated with paclitaxel in combination with several other agents; however, paclitaxel treatment is often ineffective or limited by treatment-related toxicities. Heritable variants in genes associated with absorption, distribution, metabolism, and elimination may predict paclitaxel clinical outcome and toxicity. We designed a prospective multi-institutional study that recruited 546 patients receiving therapy with a 5-year follow up. All patients were genotyped using the Drug Metabolizing Enzymes and Transporters (DMET) platform, which ascertains 1931 genotypes in 235 genes. Genotypes were compared to the progression-free survival of paclitaxel therapy and clinically-significant paclitaxel toxicities. Seven genetic variants were associated with paclitaxel PFS (in ABCB11, ABCC3, ABCG1, CYP8B1, NR3C1, FMO6P, and GSTM3), whereas four genetic variants (in VKORC1, SLC22A14, GSTA2, and DCK) were associated with paclitaxel toxicities. The present SNPs have limited clinical utility but suggest that certain genes are related to important paclitaxel pathways in lung cancer.

  Study phs001660

• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• Study of the rare and low frequency variants in the Saguenay-Lac-Saint-Jean population

  The Saguenay–Lac-Saint-Jean (SLSJ) region is located in northeastern Quebec and is known for its unique demographic history and founder effect. Since founder populations are enriched with population-specific variants, we characterized the variants distribution in SLSJ and compared it with four European populations (Finnish, Sweden, United Kingdom and France), of which the Finnish population is another founder population. Targeted sequencing of the coding and non-coding immune regulatory regions of the SLSJ asthma familial cohort and the four European populations were performed. Rare and low-frequency coding and noncoding regulatory variants identified in the SLSJ population were then investigated for variant- and gene-level associations with asthma and allergy related-traits (eosinophil percentage, immunoglobulin (Ig)E levels and lung function). Our data showed that (1) rare or deleterious variants were not enriched in the two founder populations as compared to the three non-founder European populations; (2) a larger proportion of founder population-specific variants occurred with higher frequencies; and (3) low-frequency variants appeared to be more deleterious. Furthermore, a rare variant, rs1386931, located in the 3’UTR of CXCR6 and intron of FYCO1 was found to be associated with eosinophil percentage. Gene-based analyses identified NRP2, MRPL44 and SERPINE2 to be associated with various asthma and allergy related traits. Our study demonstrated the usefulness of using a founder population to identify new genes associated with asthma and allergy-related traits; thus better understand the genes and pathways implicated in pathophysiology.

  Study EGAS00001003103

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• Successful Clinical Response in Pneumonia Therapy (SCRIPT)

  The goal of this study is to iteratively identify, validate and refine biomarkers to predict clinical failure, and identify novel targets for therapy, beyond traditional antibiotics, for patients with severe pneumonia requiring intubation, including severe community-acquired pneumonia (CAP), hospital-acquired pneumonia, and ventilator-associated pneumonia (HAP/VAP). We hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution.The major emphasis will be on HAP. Mechanically ventilated CAP patients are a very high-risk group for subsequent VAP, and therefore CAP samples will be included to determine baseline bacteria, microbiome, and host defense patterns for those that do or do not develop HAP/VAP. Hospital-acquired pneumonia is the leading cause of death from nosocomial infections. Even in patients receiving pathogen-appropriate therapy, reported clinical failure rates are increasing, approaching 50% in recent clinical trials. Current approaches to improve outcomes in patients with pneumonia almost exclusively focus on the development of antibiotics to address the problem of resistance. However, the prevalence of antibiotic-resistant pathogens is insufficient to explain the high rates of clinical failure. Instead, we hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution. These factors include pathogen-specific adaptations to the injured lung that modulate the innate and adaptive immune response, as well as changes to the alveolar microbiome, driven by selective pressure within our modern intensive care units. Understanding this complex adaptive system requires the integration of clinical information with unbiased measures of the host, pathogen, and microbiome changes within the alveolar microenvironment. These measures must be repeated over time to identify factors that distinguish successful from failed therapy for pneumonia sufficiently early during the clinical course to allow for effective interventions. To address this challenge, we have assembled a talented group of investigators in the Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center. We will leverage our routine clinical practice of safe alveolar sampling in mechanically ventilated patients with pneumonia with repeated non-bronchoscopic bronchoalveolar lavage (NBBAL) sampling over the course of pneumonia. From this fluid, we will combine flow cytometry with multi-omic technologies (cell population-specific transcriptomics, epigenomics, shotgun microbiome sequencing, and pathogen-specific sequencing). Our systems scientists will integrate these genomic data with robust clinical -omics with the goal of identifying biomarkers that can be prospectively tested in patients and causally evaluated in humanized mouse models.The addition of a pooled sample artificially increases the number of automatically computed subjects by one.

  Study phs002300

• NCI's Datasets for General Research Use

  This collection contains all of NCIs authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually.

  Study phs003014

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833