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Identification and Analysis of Causal Variants: Follow-Up on Genome-Wide Association Studies for Arthritis and Musculoskeletal and Skin Diseases (R21)

Sector: Government • Location: United States of America

Source: Grants.gov

Project
Archived

This Funding Opportunity Announcement (FOA), issued by the National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, encourages applications that are exploratory/developmental and highly innovative in nature, and aim to characterize the genetic variations in human genomic regions that have been putatively associated with complex diseases relevant to the

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The project “Identification and Analysis of Causal Variants: Follow-Up on Genome-Wide Association Studies for Arthritis and Musculoskeletal and Skin Diseases (R21)” is an infrastructure initiative in the Government sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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archived

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Description

Description

This Funding Opportunity Announcement (FOA), issued by the National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, encourages applications that are exploratory/developmental and highly innovative in nature, and aim to characterize the genetic variations in human genomic regions that have been putatively associated with complex diseases relevant to the NIAMS mission. The purpose is to accelerate the discovery of causal genes and variants that influence the risk for disease; and conduct follow-up studies of particular genetic variants to gain novel insights into the functions of these variants and the mechanisms by which they may contribute to disease. Genomic regions of interest are primarily those identified by genome-wide association studies (GWAS) although other types of evidence may also inform the rationale for a given study. These studies are essential for the translation of initial GWAS finding into biological insights, and ultimately important for improving our understanding of the molecular mechanisms of disease that could lead to predictive, diagnostic, and therapeutic advances.

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High

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100%

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