Quantile-specific penetrance of genes affecting lipoproteins, adiposity and height

Abstract

Quantile-dependent penetrance is proposed to occur when the phenotypic expression of a SNP depends upon the population percentile of the phenotype. To illustrate the phenomenon, quantiles of height, body mass index (BMI), and plasma lipids and lipoproteins were compared to genetic risk scores (GRS) derived from single nucleotide polymorphisms (SNP)s having established genome-wide significance: 180 SNPs for height, 32 for BMI, 37 for low-density lipoprotein (LDL)-cholesterol, 47 for high-density lipoprotein (HDL)-cholesterol, 52 for total cholesterol, and 31 for triglycerides in 1930 subjects. Both phenotypes and GRSs were adjusted for sex, age, study, and smoking status. Quantile regression showed that the slope of the genotype-phenotype relationships increased with the percentile of BMI (P = 0.002), LDL-cholesterol (P = 3×10⁻⁸), HDL-cholesterol (P = 5×10⁻⁶), total cholesterol (P = 2.5×10⁻⁶), and triglyceride distribution (P = 7.5×10⁻⁶), but not height (P = 0.09). Compared to a GRS's phenotypic effect at the 10(th) population percentile, its effect at the 90(th) percentile was 4.2-fold greater for BMI, 4.9-fold greater for LDL-cholesterol, 1.9-fold greater for HDL-cholesterol, 3.1-fold greater for total cholesterol, and 3.3-fold greater for triglycerides. Moreover, the effect of the rs1558902 (FTO) risk allele was 6.7-fold greater at the 90(th) than the 10(th) percentile of the BMI distribution, and that of the rs3764261 (CETP) risk allele was 2.4-fold greater at the 90(th) than the 10(th) percentile of the HDL-cholesterol distribution. Conceptually, it maybe useful to distinguish environmental effects on the phenotype that in turn alters a gene's phenotypic expression (quantile-dependent penetrance) from environmental effects affecting the gene's phenotypic expression directly (gene-environment interaction).

Figure 1. Increase in LDL-cholesterol per increase in the GRS_{LDL-cholesterol} for selected percentiles (upper panel), and for all percentiles as a function of the LDL-percent distribution (lower panel).

Note that the Y-axis represents LDL-cholesterol concentrations in the upper panel, and the slopes for LDL-cholesterol vs. GRS_{LDL-cholesterol} in the lower panel. The correspondence between the upper and lower panels is illustrated by the letter designation of the corresponding slopes at the 10^th (A), 25^th (B), 50^th (C), 75^th (D), and 90^th (E) LDL-percentile distribution. Lighter lines designate ± one standard error.

Figure 2. Slopes for HDL-cholesterol versus GRS_{HDL-cholesterol} and the number of C alleles for rs3764261 (CEPT, Y-axis) by percentiles of the HDL-cholesterol distribution (X-axis).

Lighter lines designate ± one standard error.

Figure 3. Slopes for plasma total cholesterol concentrations versus GRS_{Total cholesterol} and plasma triglyceride concentrations versus GRS_{Triglycerides} (Y-axis) by the percentiles of the lipid distribution (X-axis).

Lighter lines designate ± one standard error.

Figure 4. Slopes for BMI versus GRS_BMI and rs155890 (FTO gene, Y-axis) by the percentile of the BMI distribution (X-axis).

Lighter lines designate ± one standard error.

Figure 5. Slopes for height versus GRS_Height (Y-axis) by the percentile of the height distribution (X-axis).

Lighter lines designate ± one standard error.

Figure 6. Suggested interpretation of quantile-dependent penetrance and gene-environment interaction.