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Estimating disease risk using genetic data

Award Number: R43HG009089
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 04/14/2017
PERIOD OF PERFORMANCE END DATE: 03/31/2019

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Estimating disease risk using genetic data - Project Summary In the past 10 years, over 21,000 genetic variants have been linked to complex human traits through genome-wide association studies (GWAS). However, the predictive power of many of these variants remains limited, and it is still unclear how best to use the wealth of information generated by GWAS to impact personal health and clinical practice. For nearly 10 years, 23andMe has been not only a driving force in direct-to-consumer genetic testing but also has established an innovative crowd-sourced genetics research platform. This platform has yielded a compelling data resource and many genetic discoveries. In this proposal, we will address the next phase of 23andMe human genetics research: the development of highly scalable and accurate disease risk estimation. Two of the key challenges in human genetics research are (1) to determine how to use results of GWAS to paint an accurate picture of an individual's disease risk, and (2) to determine how these estimates can provide information of personal and clinical utility. These challenges are difficult due to many factors including the wide spectrum of disease classes, the paucity of genetic and phenotypic data and significant methodological and computational challenges. In this proposal, we present a plan to utilize the genetic and phenotypic data stores at 23andMe to ¿develop validated risk estimation algorithms¿. In Phase I, we will build a computational pipeline that will be used to develop predictive algorithms for estimating disease risk (Aim #1) and use this pipeline to evaluate predictive ability of different estimation approaches in a broad class of human complex traits (Aim #2). In Phase II, we will validate these algorithms in external cohorts and build customer-facing reports that we will test for user comprehension. We believe that the development of accurate risk estimation capability will have a major impact on both consumer genetics and clinical genetics markets.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2019 ( Subtotal = $0 )
2019	2017	23ANDME, INC.	899 W EVELYN AVE	MOUNTAIN VIEW	CA	94041	SANTA CLARA	USA	Human Genome Research	000	1	8/15/2019	NEW	$0
														Subtotal = $0

Issue Date FY: 2017 ( Subtotal = $241,905 )
2017	2017	23ANDME, INC.	899 W EVELYN AVE	MOUNTAIN VIEW	CA	94041	SANTA CLARA	USA	Human Genome Research	000	1	4/14/2017	NEW	$241,905
														Subtotal = $241,905

Grand Total All Awards = $241,905

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Estimating disease risk using genetic data

Award Number: R43HG009089

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 04/14/2017

PERIOD OF PERFORMANCE END DATE: 03/31/2019

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