Genome-wide interaction of genotype by erythrocyte n-3 fatty acids contributes to phenotypic variance of diabetes-related traits

Abstract

Background: Little is known about the interplay between n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level. The present study aimed to examine variance contributions of genotype by environment (GxE) interactions for different erythrocyte n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level in a non-Hispanic white population living in the U.S.A. (n = 820). A tool for Genome-wide Complex Trait Analysis (GCTA) was used to estimate the genome-wide GxE variance contribution of four diabetes-related traits: HOMA-Insulin Resistance (HOMA-IR), fasting plasma insulin, glucose and adiponectin. A GxE genome-wide association study (GWAS) was conducted to further elucidate the GCTA results. Replication was conducted in the participants of the Boston Puerto Rican Health Study (BPRHS) without diabetes (n = 716).

Results: In GOLDN, docosapentaenoic acid (DPA) contributed the most significant GxE variance to the total phenotypic variance of both HOMA-IR (26.5%, P-nominal = 0.034) and fasting insulin (24.3%, P-nominal = 0.042). The ratio of arachidonic acid to eicosapentaenoic acid + docosahexaenoic acid contributed the most significant GxE variance to the total variance of fasting glucose (27.0%, P-nominal = 0.023). GxE variance of the arachidonic acid/eicosapentaenoic acid ratio showed a marginally significant contribution to the adiponectin variance (16.0%, P-nominal = 0.058). None of the GCTA results were significant after Bonferroni correction (P < 0.001). For each trait, the GxE GWAS identified a far larger number of significant single-nucleotide polymorphisms (P-interaction ≤ 10E-5) for the significant E factor (significant GxE variance contributor) than a control E factor (non-significant GxE variance contributor). In the BPRHS, DPA contributed a marginally significant GxE variance to the phenotypic variance of HOMA-IR (12.9%, P-nominal = 0.068) and fasting insulin (18.0%, P-nominal = 0.033).

Conclusion: Erythrocyte n-3 fatty acids contributed a significant GxE variance to diabetes-related traits at the genome-wide level.

Figure 1

GxE variance estimation of n-3 polyunsaturated fatty acids for four diabetes-related traits. The GxE variance is shown as the percentage of the total phenotypic variance of each trait (heritability). *P < 0.05 indicates significant contribution to total variance. Data are expressed as mean ± SE.

Figure 2

Estimated heritability (%) of diabetes-related traits. Solid bars depict the heritability based on additive genetic variance. Unfilled bars represent heritability, as a percentage, arising from the sum of additive genetic variance and genetic variance by GxE interaction. GxE heritability was calculated as the GxE variance divided by the total phenotypic variance. DPA, docosapentaenoic acid; AA, arachidonic acid; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid. Data are expressed as mean ± SE.

Figure 3

QQ-plot for HOMA-IR. Two plots on the left are for the main effect and GxE interaction of ALA (control E factor), while two plots on the right are for the DPA, which contributed a nominal significance to the GxE variance.

Figure 4

QQ-plot for fasting insulin. Two plots on the left are for the main effect and GxE interaction of ALA (control E factor), while two plots on the right are for the DPA, which contributed a nominal significance to the GxE variance.

Figure 5

QQ-plot for fasting glucose. Two plots on the left are for the main effect and GxE interaction of ALA (control E factor), while two plots on the right are for the AA/(DHA + EPA), which contributed a nominal significance to the GxE variance.

Figure 6

QQ-plot for fasting adiponectin. Two plots on the left are for the main effect and GxE interaction of n-6 PUFA (control E factor), while two plots on the right are for the AA/EPA, which contributed a nominal significance to the GxE variance.