Building on our 25-year track record in comprehensive genomic studies and addressing NHGRI's goal for this RFA, we propose to create, apply and test a powerful, reliable and general strategy for comprehensive identification of risk and protective variants that contribute significantly to any common disease of interest. Toward this end, we will: * Create a Common Disease Consortium (CDC) that brings together a collaborative network of investigators with deep clinical and genetic expertise and >1.1 million well-characterized samples (cases and controls) across diverse populations, including Europeans, African Americans, Hispanics and Asians. The CDC will undertake genetic studies under three major projects related to: (1) Five systemic diseases - early-onset coronary artery disease, type 2 diabetes, inflammatory bowel disease, atrial fibrillation, and stroke; (2) Three severe neurological disorders - autism, schizophrenia and epilepsy; and (3) Two countries with special advantages for genetic studies - Finland and Estonia. Through these three projects, the CDC will explore a range of study designs, population-genetic strategies, genetic architectures, and diverse populations. * Sequence 450,000 samples from the CDC, using the expertise of the Broad Institute's genomics platform to generate high quality data and to drive down sequencing costs. Analyze the sequence data to elucidate the genetic basis of the diseases, by applying state- of-the-art methods from in our preliminary studies and developing new methods to increase power to detect association. Create, disseminate and share data, tools, and resources, to enable the scientific community to access and analyze genetic studies from the CDC and other sources.
We aim to develop, apply and test a powerful, reliable and general strategy for 'comprehensive' identification of risk and protective variants that contribute significantly to common diseases. Toward this end, we have assembled a Common Disease Consortium (including >1,100,000 samples from cases and controls for nine diseases and participants from two unusual national biobanks). We aim to sequence and analyze DNA and phenotypes from 450,000 samples, as well as to improve methods for sequencing and analysis.
|Murphy, Meredith P; Kuramatsu, Joji B; Leasure, Audrey et al. (2018) Cardioembolic Stroke Risk and Recovery After Anticoagulation-Related Intracerebral Hemorrhage. Stroke 49:2652-2658|
|Regier, Allison A; Farjoun, Yossi; Larson, David E et al. (2018) Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. Nat Commun 9:4038|
|Emdin, Connor A; Khera, Amit V; Chaffin, Mark et al. (2018) Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease. Nat Commun 9:1613|
|Khera, Amit V; Chaffin, Mark; Aragam, Krishna G et al. (2018) Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet 50:1219-1224|
|Costello, Maura; Fleharty, Mark; Abreu, Justin et al. (2018) Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms. BMC Genomics 19:332|
|Khera, Amit V; Kathiresan, Sekar (2017) Genetics of coronary artery disease: discovery, biology and clinical translation. Nat Rev Genet 18:331-344|
|Natarajan, Pradeep; Young, Robin; Stitziel, Nathan O et al. (2017) Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting. Circulation 135:2091-2101|
|Stitziel, Nathan O; Khera, Amit V; Wang, Xiao et al. (2017) ANGPTL3 Deficiency and Protection Against Coronary Artery Disease. J Am Coll Cardiol 69:2054-2063|
|Khera, Amit V; Kathiresan, Sekar (2017) Is Coronary Atherosclerosis One Disease or Many? Setting Realistic Expectations for Precision Medicine. Circulation 135:1005-1007|
|Rusu, Victor; Hoch, Eitan; Mercader, Josep M et al. (2017) Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms. Cell 170:199-212.e20|
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