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OurHealth - Cardiovascular Disease in South Asians

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003821.v2.p1
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The OurHealth Study aims to build a biobank comprising South Asian samples from participants residing in the United States. Primary objectives are to (1) identify genetic and non-genetic drivers of cardiometabolic disease in South Asians, (2) engage participants and researchers in scientific advances and research opportunities to accelerate discovery, and (3) assess the impact of returning polygenic risk scores for cardiovascular-related health conditions. Participants use a web-based platform to complete electronic informed consent, and contribute data via (1) online health surveys, (2) mailed saliva biospecimens for sequencing, and (3) optional electronic health record sharing. Surveys capture medical history, medication data, lifestyle factors, family history, mental health history, and detailed information about cultural and ancestral background. Biospecimens, procured via saliva self-collection kits, undergo DNA isolation and are sequenced using the "blended genome exome" (BGE) method, which consists of sequencing on the NovaSeqX 10B Flowcell followed by Dynamic Read Analysis for GENomics (DRAGEN) analysis for alignment to GRCh38, mapping, and variant calling. BGE uses low-coverage whole genome sequencing (lcWGS) (2-3x) combined with deep-coverage exome sequencing (30-40x), improving on SNP arrays for common variant imputation across European and non-European populations while also capturing rare coding variants. Relative to array genotyping, coverage, genotyping breadth, imputation generalizability, and cost are more optimal.BGE requires imputation for which the 1000G + HGDP reference panel was used, and GLIMPSE2 was used for imputation emitting genotyping dosages (i.e., 0-2 multimodal continuous). Quality control (QC) included the following procedures. Sample QC excluded those with mean coverage <0.5X for lcWGS and <20X for WES, higher than expected dup rate, >3% contamination from FREEMIX/VerifyBamID, sex aneuploidy and genotype/phenotype sex-mismatch due to potential phenotyping errors, fingerprinting discordance, and sample metric-level outliers were ancestry-aware, given expected distribution differences. Variant QC metrics including allele frequencies, imputation INFO scores, and Hardy-Weinberg Equilibrium (HWE) p-values are provided with the data; the genotype files provided are not filtered.For more information about the OurHealth study, navigate to the OurHealth study website. For more information about the OurHealth dataset, including working with OurHealth data in AnVIL, navigate to the PRIMED Consortium OurHealth webpage.]]> OurHealth recruits adults (≥18 years) who identify as South Asian and reside in the United States.]]> South Asians living in the United States, aligned with definitions defined by the American Heart Association and American College of Cardiology as individuals ancestrally from Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, or Sri Lanka, are recognized to have greater cardiometabolic disease risk than other groups. However, nationwide research infrastructure to discover and characterize drivers of this increased risk remains limited. To address this need, OurHealth was developed as a nationwide initiative based out of Massachusetts General Hospital, pairing both remote participation with culturally tailored outreach to enhance study accessibility, support granular phenotyping, and address logistical barriers to inclusion in genomic research. OurHealth lays the groundwork for precision cardiometabolic risk prediction in South Asians, offering a model for engagement and research across populations.]]>
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2025-12-05
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