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Understanding and using gene-by-context interactions in human complex trait genetics

Award Number: R35GM146868
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/01/2022
PERIOD OF PERFORMANCE END DATE: 08/31/2027

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Understanding and using gene-by-context interactions in human complex trait genetics - Understanding the genetic architecture of complex traits is critical for personalized medicine, as knowledge of underlying risk loci is required for treatment and prediction of disease state. Genome wide association studies (GWAS) have identified hundreds of thousands of genotype-phenotype associations. This information – incorporated in Polygenic Risk Scores (PRS) – has provided levels of prediction accuracy for some complex diseases and health-related traits comparable to those obtained for monogenic diseases. While this is an important advance, significant problems still need to be overcome to achieve the ultimate goal of precision medicine. First, prediction accuracy is low for most complex traits. Possible reasons for this observation are the higher polygenicity of these traits, requiring larger sample sizes to discover associated loci and estimate their effect; and gene-by-context interactions that are usually ignored in prediction models. Second, results obtained in a population usually transfer poorly to a different population and are therefore not generalizable. This is due to differences in effect sizes across populations because of different patterns of linkage disequilibrium (LD) and allele frequencies and/or gene-by-context interactions. My research program will focus on investigating the role of gene-by-context interactions on the genetic architecture and polygenic prediction of complex traits. My first goal is to elucidate the importance of gene-by-context interactions for complex traits. To do so, I will develop a new analytical strategy using a combination of methods that will increase the power for discoveries. This will result in a comprehensive assessment of the contribution of gene-by-context interactions to complex trait variation. My second goal is to evaluate the utility of accounting for gene-by-context interactions to improve phenotypic prediction. To do so, I will use statistical methods developed for agricultural breeding that have been successful at increasing complex trait prediction accuracy in that field. I will also develop a prediction method that models gene-by-context interactions explicitly, while simultaneously accounting for other sources of effect heterogeneity. The long-term goal of my laboratory is to increase prediction accuracy for medically relevant traits in the general population.


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: 2025 ( Subtotal = $373,848 )
2025	2025	CLEMSON UNIVERSITY	201 SIKES HALL	CLEMSON	SC	29634	PICKENS	USA	Biomedical Research and Research Training	000	4	8/20/2025	NON-COMPETING CONTINUATION	$373,848
														Subtotal = $373,848

Issue Date FY: 2024 ( Subtotal = $374,200 )
2024	2024	CLEMSON UNIVERSITY	201 SIKES HALL	CLEMSON	SC	29634	PICKENS	USA	Biomedical Research and Research Training	000	3	7/24/2024	NON-COMPETING CONTINUATION	$374,200
														Subtotal = $374,200

Issue Date FY: 2023 ( Subtotal = $374,536 )
2023	2023	CLEMSON UNIVERSITY	201 SIKES HALL	CLEMSON	SC	29634	PICKENS	USA	Biomedical Research and Research Training	000	2	8/7/2023	NON-COMPETING CONTINUATION	$374,536
														Subtotal = $374,536

Issue Date FY: 2022 ( Subtotal = $374,856 )
2022	2022	CLEMSON UNIVERSITY	201 SIKES HALL	CLEMSON	SC	29634	PICKENS	USA	Biomedical Research and Research Training	000	1	8/29/2022	NEW	$374,856
														Subtotal = $374,856

Grand Total All Awards = $1,497,440

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Understanding and using gene-by-context interactions in human complex trait genetics

Award Number: R35GM146868

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 09/01/2022

PERIOD OF PERFORMANCE END DATE: 08/31/2027

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