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GWAS Study

Genome-wide contribution of genotype by environment interaction to variation of diabetes-related traits.

Zheng JS, Arnett DK, Lee YC et al.

24204828 PubMed ID
GWAS Study Type
820 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

ZJ
Zheng JS
AD
Arnett DK
LY
Lee YC
SJ
Shen J
PL
Parnell LD
SC
Smith CE
RK
Richardson K
LD
Li D
BI
Borecki IB
OJ
Ordovás JM
LC
Lai CQ
Chapter II

Abstract

Summary of the research findings

While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P-nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P-nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P-nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.

820 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

820
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
U.S.
Recruitment Country
Chapter IV

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