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• Atherosclerosis Risk in Communities (ARIC) Cohort

  The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were examined with the baseline visit occurring in 1987-89, the second visit in 1990-92, the third visit in 1993-95, the fourth visit in 1996-98, the fifth visit in 2011-13, the sixth visit 2016-17 and the seventh visit 2018-19. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, these four communities were investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducted community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. Community Surveillance for non-cohorts ended in event year 2014. ARIC is currently funded through 2028. The ARIC Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000280 ARIC Cohort. phs000557 ARIC_CARe phs000090 GENEVA_ARIC phs000223 PAGE_CALiCo_ARIC phs000398 GO-ESP: HeartGo_ARIC phs000668 CHARGE_ARIC phs000860 MICORTEX phs001536 CCDG_ARIC

  Study phs000280

• NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

  Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

  Study phs001662

• Increased trunk fat is associated with altered gene expression in breast tissue of normal weight women

  Dac EGAC00001002031

• Oxidative phosphorylation is a key ontogenetic feature of monocyte immunometabolism promoting myeloid differentiation after birth

  Dac EGAC00001003420

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Study EGAS00001006820

• Transcriptional mechanisms of resistance to anti-PD-1 therapy

  Purpose: To explore factors associated with response and resistance to anti-PD-1 therapy, we analyzed multiple disease sites at autopsy in a patient with widely metastatic melanoma who had a heterogeneous response.Materials and Methods: Twenty-six melanoma specimens (four pre-mortem, 22 post-mortem) were subjected to whole-exome sequencing. Candidate immunologic markers and gene expression were assessed in ten cutaneous metastases showing response or progression during therapy.Results: The melanoma was driven by biallelic inactivation of NF1. All lesions had highly concordant mutational profiles and copy number alterations, indicating linear clonal evolution. Expression of candidate immunologic markers was similar in responding and progressing lesions. However, progressing cutaneous metastases were associated with over-expression of genes associated with extracellular matrix and neutrophil function.Conclusions: Although mutational and immunologic differences have been proposed as the primary determinants of heterogeneous response/resistance to targeted therapies and immunotherapies, respectively, differential lesional gene expression profiles may also dictate anti-PD-1 outcomes.

  Study EGAS00001002195

• Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab

  We report herein an extensive exploratory biomarker analysis of refractory tumors taken from pediatric patients prior to receiving atezolizumab monotherapy in the phase 1-2 iMATRIX-atezolizumab trial (NCT02541604). A high percentage of CD8+ T cells and elevated protein levels of programmed cell death ligand 1 (PD-L1) were associated with progression-free survival (PFS). T-cell receptor (TCR) sequencing revealed that diverse infiltrating TCR repertoire at baseline was prognostic. We found no associations between panel-based tumor mutation burden (TMB) or specific genetic aberrations with PFS in this study. Through a pan-cancer gene co-expression network analysis, we developed a novel tumor-agnostic Pediatric Cytotoxicity and Antigen Presentation (PedCAP) signature that was associated with improved PFS in the iMATRIX-atezo study. Our study highlights features of immune response in pediatric cancers when treated with immune checkpoint inhibitors and provides a multi-biomarker pediatric immunogram framework to guide prospective clinical trials in pediatric cancers.

  Study EGAS00001006004

• EGAD00000000019

  840 families where both parents have been genotyped together with the child with severe malaria

  Dataset EGAD00000000019

• Tumor sample of a serious ovarian carcinoma

  Tumor sample of a serious ovarian carcinoma

  Dataset EGAD00001000139

• Blood sample of serious ovarian carcinoma patient

  Blood sample of serious ovarian carcinoma patient

  Dataset EGAD00001000140