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• Gene-Environment Interactions (GxE) and Complex Traits

  Functional variants associated with complex traits tend to fall in non-coding regions and affect regulatory mechanisms that are not yet well characterized. Furthermore, it is generally difficult to determine in which tissues and conditions they may have a functional impact. This is because the effect of a genetic variant on a molecular pathway, and ultimately on the individual's phenotype, may be modulated by "environmental" factors. We denominate such variants "gene-expression environment-specific quantitative trait nucleotides" GxE-QTNs. Achieving a better understanding of the mechanisms underlying GxE is a critical step in understanding the link between genotype and complex phenotype. It is also crucial to develop computationally efficient and statistically sound methods capable to integrate tissue/condition-specific functional genomics data to predict and validate when a sequence variant is functional. In this study we developed novel experimental and computational approaches to screen, analyze and functionally characterize genetic variants for complex traits modulated by environmental exposures. To identify and characterize genes with GxE, we analyzed allele specific gene expression in a panel of five relevant tissues (e.g. the vascular endothelium for cardiovascular diseases) under 50 controlled environmental conditions (e.g. glucocorticoids treatment, as a proxy for stress exposure). These data should be useful to develop computational tools that integrate different sources of evidence including data collected by ENCODE, RoadMap Epigenome and GTEx projects to functionally annotate GWAS variants. The experimental and computational tools developed by this project have widespread applicability, for example, can be used to tackle the functional basis of complex traits in other environmental contexts (e.g. other types of stress and hormonal levels) and genetic backgrounds. This resource represents the first comprehensive catalog of genetic variants that interact with environmental exposure in determining human complex traits.

  Study phs001176

• NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Asthma): Genetic variants affecting susceptibility and severity

  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 exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: 19892860). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (phs000355, Illumina platform).

  Study phs000422

• Epigenetics of Cocaine and Nicotine Addiction

  This project characterizes DNA methylation and gene expression changes that occur in the human brain, specifically in neurons from the rostral striatum. Major advances from NIDA funded initiatives for noninvasive neuroimaging studies have made it possible to study neuroanatomical, neurochemical and functional changes in the human brain that contribute to the vulnerability to abuse drugs, together with the neurotoxic consequences of years of drug misuse. Animal models have been developed to explain the fundamental behavioral and biological mechanisms of addiction, including reward, tolerance and dependence. From these studies, we learned that cocaine abuse not only alters the epigenetic status of genes, but also induces particular epigenetic modifications depending on the frequency of the drug's administration. Certain genes are switched on by infrequent (short-term exposure) administration, while others are switched on only after chronic administration (addiction/dependence). Animal studies have also suggested that cocaine-seeking habits modeling chronic cocaine addiction in humans depend upon dopamine-dependent serial connectivity linking the ventral (nucleus accumbens) with the dorsal striatum (caudate nucleus). The primary goal of this study is to identify DNA methylation and gene expression changes that occur in the transition from recreational cocaine use to cocaine addiction. High throughput sequencing studies were designed to investigate unique postmortem human brain specimens from individuals that met criteria for cocaine dependence, as compared to unaffected age-matched controls. Brain biospecimens were available from the University of Miami Brain Endowment BankTM, from a collection of phenotypically well-characterized postmortem tissues sampled from chronic cocaine abusers that came to autopsy. This biobank of postmortem brain specimens and annotated genomic data serve as a research resource to support NIDA's scientific mission.

  Study phs001377

• Genomic Answers for Kids (GA4K)

  Identification of complex genetic variants including defects in gene regulatory circuits and uncharacterized genes present challenges for rare disease diagnosis. In Genomic Answers for Kids program we apply the joint interpretation of patient genome sequence with genomic endophenotypes to expand the clinically actionable genome among pediatric cases of suspected genetic disease. Our objective is to examine the role of novel and under-interpreted sequence variation by combining complete DNA sequences, personal epigenetic variations and massively parallel functional screens. To achieve this we perform augmented whole genome sequence (WGS) interpretation including reanalysis of clinical exomes as well as generating WGS for patients with negative exome results all be subject to family-based semi-automated recall pipeline to discover missed diagnostic variation. We use linked-read and long-read sequencing technologies to focus on putative structural variants missed in short-read genome and exome analysis by the optimized integration of linked and long read technologies that also improve identification of transmission patterns of all variants, as well as resolving genomic regions resistant to standard alignment. We also include tissue DNA sequencing to investigate somatic mosaicism. To further assist with WGS interpretation for uncommon variation we capture snapshots of patient transcriptomes and epigenomes in individual cells using single-cell RNA (scRNA) and sc open chromatin (scATAC) as well as bulk whole genome bisulphite genome sequencing for methylome interpretation. Alternative splicing is functionally assessed in available patient tissues using RNA-seq, including full length cDNA sequences by IsoSeq (PacBio) methodology. Our overarching goal is an increase rate of diagnostic genomic findings up to two-fold among rare disease, resulting in the majority (>50%) of patient cases resolved by the integrated system developed in our program.

  Study phs002206

• Rapid Early Action for Coronary Treatment (REACT-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: This multicenter controlled community study developed and evaluated the impact of a community educational intervention program on participant delay time from onset of symptoms of an acute myocardial infarction (AMI) to arrival at a hospital emergency department.Background: Although early reperfusion or thrombolytic therapy can reduce morbidity and mortality following an AMI, delayed access to medical care in participants is relatively common. Mean delay times from symptom onset to hospital arrival range from more than 4 hours to 24 hours, and the largest component of prolonged delay is participant recognition and action.Participants: A total of 20 communities from 5 field centers in the U.S. were pair-matched (10 pairs) according to geographic proximity and demographic characteristics. After initiation of a 4 month baseline surveillance period, one community in each pair was randomly selected to receive the intervention. The baseline surveillance period was followed by an 18 month community intervention and surveillance period. The community surveillance captured a total of 59,944 adults aged 30 years or older presenting to hospital emergency departments with chest pain, of whom 20,364 met study criteria for suspected acute coronary heart disease (CHD) at admission and discharged with a CHD diagnosis.Conclusions: Delay times were decreased in the intervention and reference communities. The results showed that the multicomponent community intervention program did not differentially reduce delay time from onset of AMI symptoms to arrival at a hospital, but did significantly increase the use of Emergency Medical Services by these participants in the intervention communities. (PMID:10872014).

  Study phs003885

• Genomic Landscape of Multiple Myeloma and of its Precursor Conditions, and its Clinical Implications

  Reliable strategies to capture patients at risk of progression from precursor stages of multiple myeloma (MM) to overt disease are still missing. In this study, we generated whole-genome sequencing (WGS) data from matched tumor and normal samples from 98 individuals from the PCROWD study (Precursor Crowd, NCT02269592). These individuals have either a precursor condition for MM, which can be a monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM), or an active multiple myeloma (MM). To do so, we enriched tumor plasma cells from the bone marrow by magnetic bead selection (CD138+), sequenced the DNA of these samples to a target depth of 60X (tumor), and analyzed them against normal white blood cells (peripheral blood mononuclear cells) from the same individuals sequenced to a target depth of 30X (normal). In our first publication [Alberge, Dutta, Poletti, et al., 2025], we integrated and homogeneously analyzed these data together with data from mostly publicly available datasets (phs003084 and phs000748) to reach 1,030 total samples. We used these data to identify recurrent coding and non-coding candidate drivers, as well as significant hotspots of structural variation, and used those drivers to define and validate a simple “MM-like” score which we could use to place patients' tumors on a gradual axis of progression toward active disease. Our MM precursor genomic map provides new insights on the time of initiation and cell of origin of the disease, on the order of acquisition of genomic alterations, and on mutational processes found across stages of the transformation. Taken together, we highlight here the potential of genome sequencing to better inform risk assessment and monitoring of MM precursor conditions.

  Study phs003846

• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• Whole-exome sequencing (WES) analysis of untreated head and neck cancer patient-derived xenografts (PDXs) matched patient tumor tissue and normal mucosa tissue.

  WES analysis was performed on untreated patient tumor/normal mucosa tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC) to investigate the preservation of tumor-specific genomic alterations in the in vivo context. 183 total samples were sequenced with paired reads on 8-10 lanes from different flowcells. They were loaded as 3538 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 2-4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002325

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002278

• 13K T2D-GENES analysis files

  This data set includes the following summary level data files used for the 13k analysis of T2D-GENES data: wes.variants.list: list of variants to keep for any analysis of the exomes data wes.assoc.samples.list: list of samples to keep for association analysis wes.assoc.variants.list: list of variants to keep for association analysis wes.sv.assoc.txt: single variant association analysis results wes.gene.ptv.variants.list.txt: list of protein truncating variants to use in gene-level analysis wes.gene.ptv.assoc.txt: results from gene-level tests of protein truncating variants wes.gene.nsstrict.variants.list.txt: list of NSstrict variants to use in gene-level analysis wes.gene.nsstrict.assoc.txt: results from gene-level tests of NSstrict variants wes.gene.nsbroad.variants.list.txt: list of NSbroad variants to use in gene-level analysis wes.gene.nsbroad.assoc.txt: results from gene-level tests of NSbroad variants wes.gene.ns.variants.list.txt: list of non synonymous variants to use in gene-level analysis wes.gene.ns.assoc.txt: results from gene-level tests of non synonymous variants

  Dataset EGAD00010001188