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Published on: August 15, 2019
Progressive effects of single-nucleotide polymorphisms on 16 phenotypic traits based on longitudinal data
Donghe Li1, Hahn Kang2, Sanghun Lee3
1Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Background:
There are many research studies have estimated the heritability of phenotypic traits, but few have considered longitudinal changes in several phenotypic traits together.
Objective:
To evaluate the progressive effect of single nucleotide polymorphisms (SNPs) on prominent health-related phenotypic traits by determining SNP-based heritability ([Formula: see text]) using longitudinal data.
Methods:
Sixteen phenotypic traits associated with major health indices were observed biennially for 6843 individuals with 10-year follow-up in a Korean community-based cohort. Average SNP heritability and longitudinal changes in the total period were estimated using a two-stage model. Average and periodic differences for each subject were considered responses to estimate SNP heritability. Furthermore, a genome-wide association study (GWAS) was performed for significant SNPs.
Results:
Each SNP heritability for the phenotypic mean of all sixteen traits through 6 periods (baseline and five follow-ups) were significant. Gradually, the forced vital capacity in one second (FEV1) reflected the only significant SNP heritability among longitudinal changes at a false discovery rate (FDR)-adjusted 0.05 significance level ([Formula: see text], FDR = 0.0012). On estimating chromosomal heritability, chromosome 2 displayed the highest heritability upon periodic changes in FEV1. SNPs including rs2272402 and rs7209788 displayed a genome-wide significant association with longitudinal changes in FEV1 (P = 1.22 × 10-8 for rs2272402 and P = 3.36 × 10-7 for rs7209788). De novo variants including rs4922117 (near LPL, P = 2.13 × 10-15) of log-transformed high-density lipoprotein (HDL) ratios and rs2335418 (near HMGCR, P = 3.2 [Formula: see text] 10-9) of low-density lipoprotein were detected on GWAS.
Conclusion:
Significant genetic effects on longitudinal changes in FEV1 among the middle-aged general population and chromosome 2 account for most of the genetic variance.
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