Search Results - EGA European Genome-Phenome Archive

Transcriptomics of human olfactory mucosa

The olfactory gene repertoire is largely species-specific, shaped by the nature and necessity of chemosensory information for survival in each species' niche. We are intrigued by this interspecific variation and started to investigate the olfactory transcriptome in primates for evidence of selection at the level of receptor gene choice. Having collected this data from two primates, we now wish to extend the analysis to humans. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001003213

A rare CTSC mutation in Papillon-Lefèvre Syndrome

Papillon-Lefèvre Syndrome (PLS) is an autosomal recessive monogenic disease caused by loss-of-function mutations in the CTSC gene. In this study we performed whole genome sequencing on two siblings, with the PLS-typical symptoms. After sequencing the CTSC gene was analyzed to confirm the PLS diagnosis genetically.

Study EGAS00001005040

Application of short-RNA-seq in post-mortem human hippocampi from the Calgary Brain Bank (CBB) to assess transcriptome-wide deregulation in processing of SINE Alu RNAs in Alzheimer’s disease

Here, we investigate through short-RNA_seq in human hippocampi from the Calgary Brain Bank (CBB) whether Alu RNAs are processed in human brains, and whether their processing ratio is deregulated in brains of AD patients compared to healthy aging individuals.

Study EGAS00001004973

DNA methylation changes associated with hyperglycemia in type 1 diabetes

This dataset includes DNA methylation profiles from 112 young with Type 1 Diabetes (T1D) at T1D diagnosis, who were longitudinally monitored for hyperglycemia over an average duration of 3 years. These datasets were generated using whole-genome bisulfite sequencing. It includes 1872 fastq files (i.e. 936 paired-end fastq files) generated through 150 bp paired-end sequencing on Illumina HiSeqX.

Dataset EGAD50000000545

WES of head and neck cancer patients refractory to anti-PD-1 therapy

Whole exome sequencing (WES) was performed on baseline (before low-dose 5-aza treatment) blood and tumor paired samples from 12 participants with head and neck cancer who were refractory to anti-PD-1 therapy. DNA extractions were performed by the Broad Institute of MIT and Harvard using Qiagen AllPrep DNA/RNA kits (Cat. 80204). In total, 24 150-bp pair-end WES data were generated by Illumina.

Dataset EGAD50000001011

APS-1 Immune Panel Sequencing

Single cell sequencing of expanded regulatory T cells (Tregs) in 8 APS-1 patients and 8 age and gender matched controls (same patients and controls as for global gene expression and TCR sequencing, excluding one for each group (control sample and patient sample #13)). Each Sample has two technical repeats. 10x Genomics Target Hybridization Kit and Human Immunology Panel was used with GEX libraries.

Dataset EGAD50000000262

H3Africa AWI-Gen Phase 1 WGS data from 100 South Africans

These samples were sequenced at the Broad Institute on an Illumina HiSeqX at 30x -- PCR Free. The CRAMS and VCF are as produced by Broad. The VCFs produced were generated by the Broad using GATK.

Dataset EGAD00001006418

Chromatin accessibility of clear cell renal cell carcinoma

To investigate chromatin accessibility in ccRCC, we performed ATAC-seq in 3 ccRCC cell lines (786-O, A498, UMRC-2), and 1 normal kidney epithelium cell line (HK-2), cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions

Study EGAS50000001325

10X single-cell Multiome (RNA+ATAC) of bone marrow-derived HSPC

10X genomics chromium single-cell ATAC+RNA (Multiome) was use to prepare single-nucleus RNA- and ATAC-seq libraries, sequenced on an Illumina NovaSeq 6000 platform. BAM files are provided. Samples from 6 donors were sequenced after sorting for primitive HSPCs in 5 libraries; each library comprises a single donor, except one with cells from 1 male and 1 female donor.

Dataset EGAD50000002326

10X snMultiome (ATAC+GEX) for the study of "SPEN loss drives extra-follicular diffuse large B cell lymphoma with female-specific lethality and TLR pathway therapeutic vulnerabilities"

10X snMultiome (ATAC+GEX) sequencing of 1 human reactive tonsil sample and 1 DLBCL sample for the study of "SPEN loss drives extra-follicular diffuse large B cell lymphoma with female-specific lethality and TLR pathway therapeutic vulnerabilities"

Dataset EGAD50000002277

Case Report: Pre-Clinical Combination Targeting VEGF and PI3K in a Rare, Aggressive Mixed Endometrial Carcinoma

We report a rare case of a young patient (VENUS 167) initially diagnosed with grade 1 endometrioid endometrial cancer, which, following endocrine treatment, presented with mixed aggressive carcinoma with three distinct histologic patterns: grade 1 endometrioid, large cell neuroendocrine, and undifferentiated carcinoma. The NGS fastq data are WES, RNAseq and ATAC

Dataset EGAD50000002397

Molecular and clinical effects of selective TYK2 inhibition with deucravacitinib in psoriasis

Investigate changes in IL-23/Th17- and type I interferon-pathway biomarkers and gene responses, and measures of selectivity for TYK2 over Janus kinases (JAKs) 1–3, in patients with moderate to severe psoriasis receiving deucravacitinib.

Study EGAS00001005875

ChIP-seq of blasts from leukemia patients and CD34+ cells from healthy donors

CTCF ChIP-seq of 14 leukemia patients: 6 AML without 3q rearrangements, 1 AML with 3q26, 1 AML with t(3;8) and 6 T-ALL H3K27ac ChIP-seq of AML patients: 4 cases with t(3;8), another with inv(3) and another with normal karyotype. H3K27ac ChIP-seq of CD34+ cells from one healthy donor RUNX1 ChIP-seq of one t(3;8) AML patient

Dataset EGAD00001006817

Digital tEchnology For Lung Cancer Treatment

DEFLeCT metadata: 1) A table containing the mutational profile for all human genes across the cohort of the 81 PROMOLE lung cancer samples. 2) A table containing the expression levels for all human genes across the cohort of the 81 PROMOLE lung cancer samples. 3) A table containing the clinical, histology data and follow-ups of the cohort of 81 PROMOLE lung cancer patients.

Dataset EGAD00001010838

MiRNome_pituitary_adenoma

Small RNA (<100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

Dataset EGAD00001004998

The University of Hong Kong Colon Cancer Ganciclovir Study WGS Data

Human clonal intestinal organoids were treated with 1µM MMF (Roche), 20 μM GCV (Hainan Poly Pharm Co Ltd), or in combinations (1 µM MMF + 20 μM GCV or 1 µM MMF + 40 μM GCV) continuously for 4-6 weeks. DNA was extracted after drug treatment. WGS was performed with 150 bp PE sequencing at 30X using an Illumina Novaseq sequencer.

Dataset EGAD00001009667

Papua New Guinean Genome Altitude Project Dataset 1

The PGAP dataset 1 includes 81 whole genome sequences for Papua New Guinean individuals sampled in Daru (N=38) and Mount Wilhelm (N=43). DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer. The PGAP dataset provides Fastq, mapped cram files (GRCh38) and phenotype measurements.

Dataset EGAD00001010143

BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_BG_T=24hrs_RPMI_T=5days, on genome GRCh38

Bisulfite-Seq data for 1 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days sample(s). 18 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002385

BLUEPRINT release August 2016, Bisulfite-Seq for Type 1 diabetes mellitus, on genome GRCh38

Bisulfite-Seq data for 4 Type 1 diabetes mellitus sample(s). 32 run(s), 4 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002392

BLUEPRINT release August 2014, ChIP-Seq for macrophage

ChIP-Seq data for 1 macrophage sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001000929

BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - Attached_T=1hr, on genome GRCh38

Bisulfite-Seq data for 1 monocyte - Attached_T=1hr sample(s). 23 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002475

BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_BG_T=24hrs, on genome GRCh38

Bisulfite-Seq data for 1 monocyte - RPMI_BG_T=24hrs sample(s). 21 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002441

BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_LPS_T=4hrs, on genome GRCh38

Bisulfite-Seq data for 1 monocyte - RPMI_LPS_T=4hrs sample(s). 18 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002432

Human Embryonic Multi-tissue ChIP-seq (Manchester)

Histone ChIP-seq of 13 human embryonic tissues from weeks 6-8 of gestation. H3K4me3, H3K27me3 and H3K27ac. Biological replicates (n=2) for 11 tissues. Tissues (n): Brain (2); Retinal Pigmented Epithelium (eye)(2); Palate(2); Tongue (1); Left ventricle (heart)(2); Lung(2); Liver(2); Pancreas (2*); Stomach(1); Upper limb (2); Lower limb (2); Adrenal gland (2); Kidney (2)

Dataset EGAD00001004335

BLUEPRINT release August 2015, ChIP-Seq for Leukemia, on genome GRCh38

ChIP-Seq data for 1 Leukemia sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

Dataset EGAD00001001528

BLUEPRINT September 2016, ChIPmentation Acute Lymphocytic Leukemia from bone marrow, on Genome GRCh38

ChIPmentation data for 1 sample(s) Acute Lymphocytic Leukemia from bone marrow, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002930

BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_LPS_T=24hrs, on genome GRCh38

Bisulfite-Seq data for 1 monocyte - RPMI_LPS_T=24hrs sample(s). 22 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

Dataset EGAD00001002302

Whole exome sequencing of advanced gastric cancer

To define the cellular characteristics of malignant ascites of advanced gastric cancer patients and search for therapeutic strategies, we obtained 5 malignant ascites and 1 cerebrospinal fluid from five patients with gastric cancer. We analyzed single-cell RNA-seq data of 180 cells from 4 malignant ascites and 1 cerebrospinal fluid metastasis using Fluidigm® C1™ System. Whole exome sequencing data was also generated from blood or tumor tissue.

Dataset EGAD00001005740

Mutational landscape of normal epithelial cells in Lynch Syndrome patients

Lynch Syndrome (LS) is an autosomal dominant disease conferring a high risk of colorectal cancer due to germline heterozygous mutations in a DNA mismatch repair (MMR) gene. Although cancers in LS patients show elevated somatic mutation burdens, information on mutation rates in normal tissues and understanding of the trajectory from normal to cancer cell is limited. Here we whole-genome sequenced 152 crypts from normal and neoplastic epithelial tissues from LS patients. In normal tissues the repertoire of mutational processes and mutation rates were similar to those found in wild type individuals. A morphologically normal colonic crypt with an increased mutation burden and mutational signatures consistent with MMR deficiency was identified, which may represent a very early stage of LS pathogenesis. Phylogenetic tress of tumour crypts indicated that the most recent ancestor cell of each tumour was already MMR deficient and had experienced multiple clonal evolution cycles. This study demonstrates the genomic stability of epithelial cells with heterozygous germline MMR gene mutations and highlights important differences in the pathogenesis of LS from other colorectal cancer predisposition syndromes.

Dataset EGAD00001008092

Identification of intronic sequences promoting natural skipping of ABCA4 exon 15 using long-read transcriptomics and midigene assays

Stargardt disease is an inherited retinal disease that leads to progressive loss of vision, and is caused by biallelic variants in the ABCA4 gene. A significant proportion of ABCA4 variants of variable penetrance affect pre-mRNA splicing. Previously, we observed the exclusion of certain ABCA4 exons into the final transcript in the absence of any disease-causing variants. In this study, we explored this phenomenon that we coined natural exon skipping (NES) for the entire ABCA4 transcript, using targeted RT-PCR analysis as well as long-read transcriptome sequencing of control retina samples. For the most abundant NES event, which is skipping of ABCA4 exon 15, overlapping ABCA4 deletion constructs were employed to identify responsible cis-regulatory sequence motifs. Subsequently, antisense oligonucleotides (AONs) were designed and tested to reverse NES and restore fully-spliced ABCA4 mRNA. We identified intronic regions on each side of exon 15 that, when deleted, increased the inclusion of exon 15 in the final transcripts. Interestingly, these motifs appear to work in a synergistic manner. Further fine-mapping of these regions revealed several cis-regulatory motifs that may be responsible for inducing NES, on each side of the exon. AONs targeting these motifs unfortunately did not decrease the skipping of exon 15. In conclusion, we discovered an intriguing phenomenon that, in the absence of disease-causing variants, results in the skipping of one or more exons in the ABCA4 transcript. These NES events appear to be regulated by cis-regulatory motifs within the flanking introns. This work captured the extend of NES throughout ABCA4 transcript and the role of cis-regulatory motifs in pre-mRNA splicing.. The use of AONs targeting cis-regulatory motifs is an innovative strategy for splicing modulation, suitable for complementing future variant-specific splicing modulation therapies in ABCA4 retinopathies.

Study EGAS50000000071

High Density SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation

This research builds upon an extensive resource of melanoma cases and hospital based controls collected over several years at the U.T. M.D. Anderson Cancer Center. The goal of this research is to identify novel susceptibility and outcome-related genes for melanoma using a systematic genome-wide association-based approach. Our goal is to conduct high-density SNP association and outcome studies. This dbGaP study contains samples from 2000 European ancestry cases and 1000 European ancestry controls using the Illumina OMNI1-Quad SNP chip. As a part of an ongoing R01 project, we have epidemiological data together with candidate gene results for 1000 of the melanoma cases and the controls. With regard to the outcome aspect of our design, as part of our melanoma Specialized Program of Research Excellence (SPORE) grant, our MelCore database contains comprehensive, prospectively maintained clinical information from all melanoma patients included in the study cohort, including primary tumor histopathology and staging information, standard and investigational blood tumor markers, details of surgical and systemic therapies, and extensive follow-up information, including time to relapse or recurrence, pattern of recurrence and survival duration. Finally, we intend to collaborate with the GenoMEL collaboration so we can jointly evaluate each other's findings. The goal of our analysis will be to identify novel genetic factors predisposing the development of melanoma, as well as genetic factors controlling melanoma stage at presentation, recurrence and progression. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to melanoma through large-scale genome-wide association studies of 2000 European ancestry cases and 1000 European ancestry controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

Study phs000187

Center for Common Disease Genomics [CCDG] - Cardiovascular: PEGASUS-TIMI 54

This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules. Source: ccdg.rutgers.eduFor this study, The Broad Institute of MIT and Harvard generated genetic data for 7,481 individuals from the PEGASUS-TIMI 54 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.  

Study phs002243

Charles R. Bronfman Institute for Personalized Medicine (IPM) BioBank Genome Wide Association Study of Cardiovascular, Renal and Metabolic Phenotypes

The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Minorities are strikingly underrepresented in GWAS, including Coronary Artery Disease (CAD) and Chronic Kidney Disease; multigenic genetic risk scores for CAD have been recently validated in European ancestry populations, but not in AA or HL populations. Several important opportunities exist for extending additional GWAS to minority populations with a shared risk spectrum of CAD and CKD. For example, progressive CKD is a major and independent risk factor for CVD with an inverse relationship between estimated GFR (eGFR), and risk for mortality and cardiovascular events. This increased risk is only partially explained by the prevalence of cardiovascular risk factors among these patients. We conducted a GWAS of CAD and CKD related phenotypes in IPM Biobank with the primary objective to explore the genetics of overlapping CAD and CKD predominantly in minority populations characterized by increased risk.

Study phs000388

Small RNA Contents of Extracellular Vesicles from Patients with Cognitive Decline

In this proposal, we examined samples from living neurologically normal individuals (n=72), cognitively normal Parkinson's disease (PD; n=21), PD with mild cognitive impairment (PD-MCI; n=18), PD with dementia (PDD; n=23), and dementia with Lewy-bodies (DLB; n=18), Alzheimer’s disease (AD; n=33) and mild cognitive impairment (MCI, n=38). The main goal for this study was to assess the diagnostic utility of small RNA contents from extracellular vesicles (EVs) for the prediction of cognitive decline. Plasma samples were collected and the RNA from extracellular vesicles (EVs) was isolated using the Qiagen exoRNeasy kit, and the small RNA contents were sequenced using the PerkinElmer NextFlex kit (v2). While PD is typically thought of as a motor disorder, there are significant non-motor symptoms that can be devastating. One of the most common non-motor symptoms of PD is dementia (PDD). While PD subjects that develop dementia all have Lewy bodies, there is often co-pathology with tau and β-amyloid found at autopsy or by PET amyloid imaging; thus, subjects diagnosed with AD were also included in the study. The development of the category, mild cognitive impairment (MCI) in AD, and in PD, provides an opportunity to identify and examine a transitional state between normal aging and dementia; this is a patient population ideally suited for therapeutic intervention. Progress in the detection, validation, and standardization of molecular biomarkers from biofluids, such as extracellular RNAs (exRNAs), would be efficient and cost-effective aids in the assessment of disease progression, cognitive decline, and response to therapeutics. We have provided the raw fastq files for the sequencing data from each sample. We are also providing demographic information, as complete as we have for each person; including age, diagnosis, sex, and cognitive assessments.

Study phs003300

Center for Common Disease Genomics [CCDG] - Cardiovascular: ENGAGE Atrial Fibrillation-TIMI 48

This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for 13,667 individuals from the ENGAGE AF-TIMI 48 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all cases with atrial fibrillation.

Study phs002774

The National Myelodysplastic Syndromes (MDS) Study

Myelodysplastic syndromes (MDS) are the most common cause of adult bone marrow failure in the US and occur predominantly in people over the age of 60. Much of the morbidity and mortality for MDS is due to complications from low blood counts (e.g., infections and bleeding). MDS is caused by acquired DNA mutations that occur in a patient's blood cells as they grow older. Accumulating evidence suggests that MDS patients may traverse through a series of antecedent hematopoietic conditions defined by, i) clonal hematopoiesis (i.e., detectable somatic mutations in a person's blood cells) without low blood counts, a condition that affects up to 10% of individuals 70 years old and is termed Clonal Hematopoiesis of Indeterminate Potential (CHIP), or ii) clonal hematopoiesis with low blood counts (i.e., cytopenias) but no evidence of bone marrow dysplasia, termed Clonal Cytopenia of Undetermined Significance (CCUS). Nearly all CCUS patients will develop MDS over a ten year period, highlighting the prognostic importance of this disease. A better understanding of the genetic mutations, including non-coding and structural variants (SVs), occurring in CCUS and MDS could provide valuable insight into the natural history of MDS development. The NHLBI is conducting a longitudinal, observational study to create a standardized clinical dataset linked to a prospectively collected, consistently processed, and well-characterized biospecimen repository derived from approximately 1750 participants with suspected or newly diagnosed MDS or MDS/myeloproliferative neoplasm (MPN) overlap. These volunteers will donate biological specimens (like bone marrow and blood) and medical information, including details of their symptoms, how they perceive their quality of life, the treatments they receive, and what their doctor says about the severity of their illness over time. This information will be collected at pre-determined time points for the duration of the study. Study participants may be followed for life.

Study phs002714

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