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• HBCC Postmortem Psychiatric Molecular Studies

  This postmortem study examines molecular, genetic and epigenetic signatures in the brains of hundreds of subjects with or without mental disorders conducted by the DIRP NIMH Human Brain Collection Core (HBCC). The brain tissues are obtained under protocols approved by the CNS IRB (NCT00001260), with the permission of the next-of-kin (NOK) through the Offices of the Chief Medical Examiners (MEOs) in the District of Columbia, Northern Virginia and Central Virginia. Additional samples were obtained from the University of Maryland Brain and Tissue Bank (contracts NO1-HD-4-3368 and NO1-HD-4-3383) (http://www.medschool.umaryland.edu/btbank/ and the Stanley Medical Research Institute: http://www.stanleyresearch.org/brain-research/). Clinical characterization, neuropathological screening, toxicological analyses, and dissections of various brain regions were performed as previously described (Lipska et al. 2006; PMID: 16997002). All patients met DSM-IV criteria for a lifetime Axis I diagnosis of psychiatric disorders including schizophrenia or schizoaffective disorder, bipolar disorder and major depression. Controls had no history of psychiatric diagnoses or addictions. SNP array: Array-based genotyping was performed on most samples published in this collection. The number of SNPs assayed via Illumina chips varied between 650,000 and 5 Million. Cerebellar tissue was generally used for genotyping studies. # Diagnosis SNP Array 1 Anxiety Disorder 1 2 Autism Spectrum Disorder 13 3 Bipolar Disorder 114 4 Control 387 5 Eating Disorder (ED) 2 6 Major Depressive Disorder (MDD) 186 7 Obsessive Compulsive Disorder (OCD) 5 8 Post-Traumatic Stress Disorder (PTSD) 0 9 Schizophrenia 220 10 Other 7 11 Tic Disorder 3 12 Undetermined 1 13 Williams Syndrome 2 Table: Numbers of samples in each diagnostic category. DNA extraction: 45-80 mg of cerebellar tissue was pulverized for DNA extractions. The QIAamp DNA mini Kit (Qiagen) method was employed for tissue DNA extraction. The tissue was initially lysed using Tissue Lyser (Qiagen) and extractions were accomplished according to manufacturer's protocol. The DNA was captured in 500uL elution buffer. The concentrations were measured using Thermo Scientific's NanoDrop 1000/NanoDrop ONE. The mean yield was 128.85 uG (+/- 79.48), the mean ratio of 260/280 was 1.87 (+/- 0.105), and the mean ratio of 260/230 was 2.48 (+/-1.75). Genotyping methods: Three types of Illumina Beadarray chips were used: HumanHap650Y, Human1M-Duo, and HumanOmni5M-Quad (San Diego, California). The genotyping was done according to the manufacturer's protocol (Illumina Proprietary, Catalog # WG-901-5003, Part # 15025910 Rev.A, June 2011). Approximately, 400ng DNA was used and each DNA sample was QC tested for 260/280 ratio by nanodrop and DNA band intactness on 2% agarose gel. Briefly, the samples were whole-genome amplified, fragmented, precipitated and resuspended in appropriate hybridization buffer. Denatured samples were hybridized on prepared Bead Array Chips. After hybridization, the Bead Chip oligonucleotides were extended by a single fluorescent labeled base, which was detected by fluorescence imaging with an Illumina Bead Array Reader, iScan. Normalized bead intensity data obtained for each sample were loaded into the Illumina Genome Studio (Illumina, v.2.0.3) with cluster position files provided by Illumina, and fluorescence intensities were converted into SNP genotypes. Microarray: We generated RNA expression data using array technology for psychiatric subjects compared to non-psychiatric subjects as controls. We used tissues from three different brain regions i.e. hippocampus, dorsolateral prefrontal cortex (DLPFC), and dura mater for a large cohort of individuals (total number 552 subjects for hippocampus, 800 for DLPFC and 146 for dura). Total RNA was extracted from ~100 mg of tissue using the RNeasy kit (Qiagen) according to the manufacturer's protocol. RNA quality and quantity were examined using the Bioanalyzer (Agilent, Inc) and NanoDrop (Thermo Scientific, Inc), respectively. Samples with RNA integrity number (RIN) # Diagnosis DLPFC Hippo Dura 1 Anxiety Disorder 1 0 0 2 Autism Spectrum Disorder 14 6 0 3 Bipolar Disorder 90 49 0 4 Control 336 270 75 5 Eating Disorder (ED) 2 1 0 6 Major Depressive Disorder (MDD) 144 87 0 7 Obsessive Compulsive Disorder (OCD) 5 3 0 8 Post-Traumatic Stress Disorder (PTSD) 6 0 0 9 Schizophrenia 192 125 71 10 Other 5 6 0 11 Tic Disorder 3 3 0 12 Undetermined 1 1 0 13 Williams Syndrome 2 1 0 Table: Numbers of samples in each diagnostic category. RNA-Seq of Dorso-lateral prefrontal cortex: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. RNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. RNA isolation: Total RNA from 468 HBCC samples was isolated from approximately 100 mg homogenized tissue from each sample by TRIzol/chloroform extraction and purification with the Qiagen RNeasy kit (Cat#74106) according to manufacturer's protocol. Samples were processed in randomized batches of 12. The order of extraction for schizophrenia, bipolar, and MDD disorders and control samples was assigned randomly with respect to diagnosis and all other sample characteristics. The mean total RNA yield was 24.2 ug (+/- 9.0). The RNA Integrity Number (RIN) was determined by 4200 Agilent TapeStation System. Samples with RIN DLPFC RNA-Seq quantified expression data are provided for 364 samples. Data were generated, QC'd, processed and quantified as follows: RNA library preparation and sequencing: All samples submitted to the New York Genome Center for RNAseq were prepared for sequencing in randomized batches of 94. The sequencing libraries were prepared using the KAPA Stranded RNAseq Kit with RiboErase (KAPA Biosystems). rRNA was depleted from 1ug of RNA using the KAPA RiboErase protocol that is integrated into the KAPA Stranded RNAseq Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. Schizophrenia Bipolar Control 89 65 210 Table: Numbers of samples in each diagnostic category. RNA-Seq of subgenual anterior cingulate cortex (sgACC): All the 200 post-mortem brain samples (61 controls; 39 bipolar disorder; 46 schizophrenia; 54 major depressive disorder) were collected by the HBCC, DIRP, NIMH. RNA Extraction and Quality Assessment: Tissue from sgACC was pulverized and stored at -80°C. Total RNA was extracted from 50-80 mg of the tissue using QIAGEN RNeasy Lipid Tissue Mini Kit (QIAGEN, Cat. # 74804) with DNase treatment (QIAGEN, Cat. # 79254). The RNA Integrity Number (RIN) for each sample was assessed with high-resolution capillary electrophoresis on the Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, California). The concentration of RNA and their 260/280 ratio (2.1+/- 0.032 SD) were determined with NanoDrop (Thermo Scientific). RNA sequencing: Stranded RNA-Seq libraries were constructed after rRNA depletion using Ribo-Zero GOLD (Illumina). RNA sequencing was performed at National Institute of Health Intramural Sequencing Center (NISC). Schizophrenia Bipolar Control MDD 46 39 61 54 Table: Numbers of samples in each diagnostic category. Whole Genome Sequencing: All brains were collected and dissected at the HBCC, DIRP, NIMH. This study generates whole genome sequencing data using sequencing of DNA in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) or cerebellum of 443 individuals with schizophrenia, bipolar disorder and major depressive disorder and non-psychiatric controls. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. DNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. All specimens were dissected from right or left hemisphere of frozen coronal slabs. DNA Library Preparation and Sequencing: All samples submitted to the New York Genome Center for WGS were prepared for sequencing in randomized batches of 95. The sequencing libraries were prepared using the Illumina PCR-free DNA sample preparation Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. A quantitative PCR assay (KAPA), with primers specific to the adapter sequence, was used to determine the yield and efficiency of the adaptor ligation process. Performed on the Illumina HiSeqX with 30X coverage. Schizophrenia Bipolar Control 115 78 230 Table: Numbers of samples in each diagnostic category. ChIP-Seq: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. This study generates epigenetic data using sequencing of DNA after chromatin immunoprecipitation (ChIP-Seq) for marks H3K4me3 and H3K27ac in the dorsolateral prefrontal cortex (DLPFC). Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029,6574. Chromatin precipitation, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. Chromatin immunoprecipitation (ChIP) assays for histone marks H3K4me3 and H3K27ac were carried out using Native ChIP. Micrococcal Nuclease (MNase) (Sigma, N3755) treatment was used to digest chromatin into mononucleosomes. The following antibodies were used for chromatin pull-down: anti-H3K4me3 (Cell Signaling, Cat# 9751BC, lot 7) and anti-H3K27ac (Active Motif, Cat# 39133, Lot # 31814008). Histone modification-enriched genomic DNA fragments were recovered using Protein A/G magnetic beads (Thermo Scientific, 88803-88938 or Millipore 16-663), and then washed, eluted, and treated with RNAse A and proteinase K. Final ChIP DNA products were isolated using phenol-chloroform extraction followed by ethanol precipitation. The efficiency of each ChIP assay was validated using Qubit concentration measurement and qPCR for positive (GRIN2B, DARPP32) and negative (HBB) control genomic regions. Only ChIP assays that passed quality control were further processed for library preparation and sequencing; this included ChIP DNA that was not detectable on Qubit but showed a good signal and expected enrichment patterns in qPCR. HISTONE_MARK H3K27ac H3K4me3 Input Bipolar 56 4 7 Control 158 11 24 Schizophrenia 79 11 12 Table: Numbers of individuals in each assay grouped by histone mark or input.Long-Read Whole-Genome Sequencing (WGS) Cohort Description: Brain specimens were obtained from the Human Brain Collection Core (HBCC), part of the NIH NeuroBioBank. Samples were collected under protocols approved by the NIH CNS Institutional Review Board (IRB) (NCT03092687), with informed consent from next-of-kin (NOK). Collection was coordinated through the Offices of the Chief Medical Examiners (MEOs) in Washington, D.C., Northern Virginia, and Central Virginia. Clinical metadata and documentation are publicly available via the NIMH Data Archive (NDA) (Collection #3151) https://nda.nih.gov/edit_collection.html?id=3151 Eligibility Criteria No clinical diagnosis of major neuropsychiatric or neurodegenerative diseaseNo diagnosis of cognitive impairment during life All individuals were confirmed to be neurologically normal at time of deathDemographics Initial cohort size: 155 individuals Ancestry: All individuals self-identified as African or African-admixed Mean age at death: 44.2 years (range: 18–85 years) Sex distribution: 36.4% femaleSample Processing: Frozen frontal cortex tissue was dissected and processed according to the public protocol: https://www.protocols.io/view/processing-human-frontal-cortex-brain-tissue-for-p-kxygxzmmov8j/v2. High-molecular-weight DNA was extracted and libraries were prepared using the Oxford Nanopore Technologies (ONT) LSK-114 kit. Sequencing was performed using ONT PromethION flow cells (R10.4.1 chemistry) Data Processing and Quality Control: Basecalling: Conducted using Guppy v6.38 Read Alignment: Reads were aligned to the GRCh38 reference genome using minimap2 Sample Identity Verification: Sample identity was validated by comparing ONT-derived SNP calls with matched short-read WGS genotypes to ensure concordance and prevent sample swaps Variant Calling and Phasing: Reads were base-called with Guppy v6.38. Reads were aligned to GRCh38 using minimap2. We verified sample identity by cross-checking ONT SNV calls with the existing short-read WGS genotypes, confirming no sample switches. The napu pipeline (https://github.com/nanoporegenomics/napu_wf) produced; haplotype-resolved assemblies, joint small-variant (SNV/indel) calls, and multi-caller structural-variant sets, all reported on GRCh38 and phased where possible. Raw signal data were basecalled to obtain 5-methyl-cytosine (5mC) status; methylation tags were added to the phased BAM files. Genome-wide methylation summaries are provided in BED format.Dataset Filtering and Exclusions: All 155 samples underwent sequencing and SNP-based ancestry inference 8 samples were excluded due to ancestry inconsistent with African or African-admixed background 1 sample was excluded due to insufficient sequencing quality Final Sample Set: 146 high-quality samples from individuals of African or African-admixed ancestry were retained for downstream analyses See PMID: 39764002 for further analysis detailsDiagnosis#SamplesControl155Table: Diagnostic Summary.Note: The data derived from HBCC resources were removed from dbGAP and are now available in the NIMH Data Archive (NDA). They include genotypes, short read whole genome sequencing (WGS), epigenetics (DNA methylation, ChIP-seq for histones), RNA expression (qPCR, microarray, RNA-seq, single nucleus RNA-seq) of various brain regions in cases with schizophrenia, bipolar disorder, major depression, substance use disorders and normative controls. Please access our NDA collection (https://nda.nih.gov/edit_collection.html?id=3151) for further detail.

  Study phs000979

• Biallelic loss of function PAX4 variants are a Novel Cause of Transient Neonatal Diabetes

  The identification of genes in which loss of function (LoF) variants cause neonatal diabetes mellitus (NDM) can provide unique insights into the development and function of human pancreatic beta cells. We describe the identification of biallelic PAX4 LoF variants in 2 unrelated individuals with transient NDM: one due to a homozygous p.(Arg126*) PAX4 stop gain variant and a second due to a homozygous c.-352_104del 2.65kb deletion affecting the first 4 exons and promoter of the PAX4 Matched Annotation from NCBI and EMBL-EBI select transcript. We confirmed reduced transcript expression due to nonsense mediated decay for the e p.(Arg126*) variant in CRISPR-edited iPSC-derived pancreatic endoderm cells. Analysis of PAX4 binding through integration of CUT&RUN and RNA-sequencing in PAX4 depleted endocrine cells identified genes directly regulated by PAX4 involved in both pancreatic islet development and glucose-sensitive insulin secretion. The remitting and relapsing diabetes in both probands demonstrates that in contrast to mice PAX4 is not essential for the development of pancreatic beta-cells and supports differences in the requirements of functional beta-cell mass across the life-course.

  Study EGAS50000000857

• DAC for EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer

  This is the Data Access Committee for the EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer (temp ID 800).

  Dac EGAC50000000563

• Identifying genetic variants that alter TCR usage in the peripheral repertoire

  The relationship between genetic variation and CD8+ T-cell receptor (TCR) repertoire usage in patients receiving Immune Checkpoint Blockade (ICB) therapy for cancer is unexplored. We have conducted a genome-wide and human leukocyte antigen (HLA)-focused analysis of CD8+ T-cell TCR repertoire to identify genetic determinants of variable gene (V-gene) and CDR3 K-mer usage from samples taken prior to and after ICB (n=250). We identify 11 cis and 10 trans V-gene associations, primarily to the MHC, that meet genome-wide significance. TCR clones containing HLA associated V-genes were less stable across treatment, whilst at the single-cell level, genetically associated clones demonstrate subset enrichment and increased tumor reactivity expression profiles. Notably, patients with HLA-matched TCR clones demonstrate improved overall survival. Our work indicates a complex relationship between genotype and TCR repertoire in the context of ICB treatment, with novel implications for understanding factors relating to therapeutic response and patient outcomes.

  Study EGAS00001008189

• Human Epilepsy Genetics: Mosaic Mutations in Focal Epilepsy

  This study investigates the role of somatic mosaic mutations in human focal epilepsies, including focal cortical dysplasia (FCD) and mesial temporal lobe epilepsy (mTLE). It leverages genomic and single-cell transcriptomic data from surgically resected brain tissue to identify pathogenic variants and characterize their effects on specific cell types and molecular pathways. The study employs methods such as deep whole-exome and targeted sequencing, single-nucleus RNA sequencing (snRNA-seq), and integrated genotype-transcriptome profiling (e.g., GO-TEN) to define the cellular architecture and functional consequences of mosaic mutations. Data generated under this project aim to elucidate mechanisms of epileptogenesis and support discovery of potential therapeutic targets.

  Study phs004124

• NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program

  The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations.

  Study phs001974

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• Single Cell DNA Methylation Analysis for Forensic Epigenetics

  As part of the Epigenetic CHaracterization and Observation (ECHO) program, the Genomic Analysis Laboratory at the Salk Institute generated the DNA methylation profiles of certain PBMC cell types to determine the change in methylation levels before, during or after exposure to certain biological or chemical agents. Samples from individuals who either handled anthrax in controlled environments or who tested positive to MRSA, MSSA, HIV, COVID-19 or exposed to Flu virus or organophosphates, or control samples were used in single-nucleus methylation (snmC-seq) assays to quantify DNA methylation levels of cytosine residues of the DNA. Around 5-10% cytosine sites were sampled in the assay. Using computational analyses, regions in the genome differentially methylated in response to the exposure were identified. This information can be used to develop diagnostic tools to predict the type of infection or time since exposure.

  Study phs003204

• The Genomic and Transcriptomic Landscape of a HeLa Cell Line

  HeLa is the most widely used model cell line for studying human cellular and molecular biology. To date, no genomic reference for this cell line has been released, and experiments have relied on the human reference genome. Effective design and interpretation of molecular genetic studies performed using HeLa cells require accurate genomic information. Here we present a detailed genomic and transcriptomic characterization of a HeLa cell line. We performed DNA and RNA sequencing of a HeLa Kyoto cell line and analyzed its mutational portfolio and gene expression profile. Segmentation of the genome according to copy number revealed a remarkably high level of aneuploidy and numerous large structural variants at unprecedented resolution. Some of the extensive genomic rearrangements are indicative of catastrophic chromosome shattering, known as chromothripsis. Our analysis of the HeLa gene expression profile revealed that several pathways, including cell cycle and DNA repair, exhibit significantly different expression patterns from those in normal human tissues. Our results provide the first detailed account of genomic variants in the HeLa genome, yielding insight into their impact on gene expression and cellular function as well as their origins. This study underscores the importance of accounting for the strikingly aberrant characteristics of HeLa cells when designing and interpreting experiments, and has implications for the use of HeLa as a model of human biology. Copyright Landry et al., "The Genomic and Transcriptomic Landscape of a HeLa Cell Line," G3: Genes | Genomes | Genetics (2013).

  Study phs000643

• Genetics and Pathobiology of Disorders of Keratinization

  The goal of this study was to identify potential drivers of disorders of keratinization in human. Individuals diagnosed with disorders of keratinization were recruited with no exclusion criteria. Saliva or blood samples were taken from consented patients or family members and DNA harvested immediately. Whole exome sequencing was performed (150-bp paired end reads) to 80X coverage via an Illumina NovaSeq 6000 sequencer. Identification of germline mutations was performed using GATK.

  Study phs004172

• RNA Transcriptomic and DNA Methylation Landscape in FTLD-TDP and Controls

  Frontotemporal lobar degeneration (FTLD) is one of the leading causes of dementia in individuals younger than 65 years, with the aggregation of TDP-43 as one of the most common forms of FTLD. FTLD-TDP is clinically, genetically and pathologically heterogeneous, with GRN and C9orf72 as the most common genetic forms (although more than 50% of the cases are genetically unexplained), and A, B and C as the most common pathological subtypes. To investigate the molecular differences between the different forms of FTLD-TDP, we performed bulk RNA sequencing (RNAseq) and reduced representation bisulfite sequencing (RRBS) from different brain regions of FTLD-TDP patients and controls. The RNAseq dataset includes samples from the frontal cortex of 149 individuals, comprising 127 FTLD-TDP cases (genetically unexplained types A (27), B (20) and C (22), 24 GRN mutation carriers, and 34 C9orf72 expansion carriers) and 22 controls. The RRBS dataset includes samples from the frontal cortex of 158 individuals —119 FTLD-TDP cases (genetically unexplained types A (25), B (24), and C (25), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 39 controls; and from the cerebellum of 151 individuals —113 FTLD-TDP cases (genetically unexplained types A (24), B (21), and C (23), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 38 controls. In total, the study consists of data from 183 unique individuals, with some overlap across the different datasets.

  Study phs004075

• Framingham Cohort

  Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the "Variables" tab above. The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000007 Framingham Cohort. phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES phs002558 Framingham ADSP phs002559 Framingham BRIDGET phs002560 Framingham Cholesterol phs002611 Framingham Post-Mortem Brain Tissue phs002938 Framingham Molecular QTL The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.

  Study phs000007

• WES data of pediatric cancer patients with P/LP variants in HBOC-related genes

  The current study aimed to identify (likely) pathogenic germline variants(LP/PVs) in 25 adult-onset HBOC-related genes within a cohort of 372 pediatric cancer patients. For this purpose we performed (paired-end) whole exome sequencing (WES) using Ilumina sequencing technology. The files uploaded here belong to the 27 individuals with such a LP/PV. The project provides insight into the prevalence and spectrum of such variants in childhood cancer, contributing to the understanding of genetic predisposition in pediatric oncology.

  Dataset EGAD50000001561

• Genetic analyses in patients with T or NK cells-associated disorders

  We conduct somatic gene mutation analysis in various diseases involving T cells or NK cells and clarify the gene mutation profile. By comparing clinical information and the results of mutation analysis, we will identify gene groups that influence the onset and refractoriness of the disease. As the analysis continues, the results of mutation analysis may become part of diagnostic criteria in the future, or provide basic data for the development of new therapeutic agents.

  Study JGAS000658

• Whole-exome-sequencing in Motor neuron disease (MND)

  To identify the genetic cause and modifiers of Motor neuron disease (MND), we performed Whole-exome-sequencing of Motor neuron disease (MND) patients.

  Study JGAS000422

• Transcriptome of human trophoblast stem cells derived from normal and HDP placentas

  Hypertensive disorders of pregnancy (HDP) is a disease driven by abnormal placenta formation, which is a leading cause of maternal and fetal death. For investigation of genetic and epigenetic regulation of human trophoblast differentiation, we have previously established human trophoblast stem cells (hTSCs) from first-trimester placentas. Those hTSCs were able to differentiate into extravillous trophoblasts (EVTs) and syncytiotrophoblasts (STs), and their transcriptome was similar to that of cytotrophoblasts in human placenta. However, since HDP happens in the second half of pregnancy, the conventional hTSC derivation method was not enough to investigate the nature of HDP trophoblasts. In this analysis, we improved the derivation method and successfully established the hTSCs from normal and HDP term placentas after delivery. We performed RNA-seq of normal and HDP hTSCs, and HDP hTSCs recapitulated abnormalities in gene expression reported in HDP placentas.

  Study JGAS000660

• Biomarker Research for Anti EGFR Monoclonal Antibodies by Comprehensive Cancer Genomics

  The purpose of this study is to explore new biomarkers for predicting the effectiveness of an anti-epidermal growth factor receptor (anti-EGFR) antibody in patients with advanced colorectal cancer. The investigation involves analyzing the entire exome, conducting a genome-wide association study (GWAS), and analyzing copy number variations (CNVs) using single nucleotide polymorphism (SNP) arrays. Genetic material from both cancerous and non-cancerous tissues, as well as blood samples from patients who received the antibody treatment, will be used. The goal is to identify genetic mutations and SNPs associated with treatment efficacy and adverse events, and to assess the correlation between their presence and treatment effectiveness using statistical methods.

  Study JGAS000779

• Elucidating the development of cervical cancer and identifying therapeutic targets based on cancer genome analysis.

  The objective of this project is to analyze genomic aberrations and gene expression changes, such as mutations, deletions, and amplifications, in human cervical cancer cells at the somatic cell level, and to contrast these with clinicopathological information to elucidate the molecular mechanisms and characteristics of lcervical cancer development and progression at the genetic level.

  Study JGAS000803

• Application of organoid culture system of human gastrointestinal and thoracic cancer in genome medicine

  In order to establish preclinical models, we have established three kinds of esophageal tumoroids derived from esophageal cancer patient. We performed whole exome sequencing to analyze genetic background of the tumoroids.

  Study JGAS000749

• Reference Panel for Imputation Analysis Based on Whole Genome Sequencing Data of 3,256 Japanese Individuals(BioBank Japan genotype data)

  This reference panel was constructed using whole genome sequencing data from 3,256 Japanese individuals and the 1000 Genomes Project. It provides high accuracy and utility in analyzing genetic polymorphisms, while also reflecting the genetic diversity specific to the Japanese population. This dataset is expected to contribute to the advancement of genetic research and personalized medicine.

  Study JGAS000746

• Genetic analyses in patients with T or NK cells-associated disorders

  We conduct somatic gene mutation analysis in various diseases involving T cells or NK cells and clarify the gene mutation profile. By comparing clinical information and the results of mutation analysis, we will identify gene groups that influence the onset and refractoriness of the disease. As the analysis continues, the results of mutation analysis may become part of diagnostic criteria in the future, or provide basic data for the development of new therapeutic agents.

  Study JGAS000709

• An epidemiological study examining the relationship among food, health, and genome

  We conducted a cohort-based study to investigate the association between the genetic background and diet/lifestyle in 962 healthy Japanese. We analyzed the Ebetsu cohort and some participants living in Tokyo. The SNP array (Japonica Array v2) was used for genotyping. Shotgun metagenomic sequencing of fecal microbiome and metabolome of feces and blood were analyzed.

  Study JGAS000678

• Whole-genome-sequencing and Whole-exome-sequencing in Myopathy

  To identify the genetic cause and modifiers of Myopathy, we performed Whole-genome-sequencing and Whole-exome-sequencing of Myopathy patients.

  Study JGAS000365

• Whole-exome-sequencing in Frontotemporal dementia (FTD)

  To identify the genetic cause and modifiers of Frontotemporal dementia (FTD), we performed Whole-exome-sequencing of FTD patients.

  Study JGAS000374

• Whole-exome-sequencing and Whole-genome-sequencing and RNA-sequencing in Familial amyotrophic lateral sclerosis (ALS)

  To identify the genetic cause and modifiers of Familial amyotrophic lateral sclerosis (ALS), we performed Whole-exome-sequencing and Whole-genome-sequencing and RNA-sequencing of Familial amyotrophic lateral sclerosis (ALS) patients.

  Study JGAS000358