Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index

Abstract

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

Genome-Wide Analysis of Nuclear Magnetic Resonance Metabolites Revealed Parent-of-Origin Effect on Triglycerides in Medium Very Low-Density Lipoprotein in PTPRD Gene

“…This method is based on the assumption that POEs can be identified as increased variance of phenotype in heterozygotes group compared with homozygous individuals groups due to genetic effect differences among maternal and paternal mutation carriers. This approach was successfully tested on anthropometric phenotypes and two genes were identified having POE on BMI [30]. As POEs are often associated with metabolic diseases such as gestational diabetes [31] and metabolic syndrome [32], we aimed to investigate POEs of NMR metabolites measured in blood serum.…”

“…This software implements a method for POE analysis using genetic data of unrelated individuals, based on comparing the phenotypic variance of the heterozygous genotype group to the variance observed in the homozygous groups [30]. The method is based on the assumption that increased variance in the heterozygous group in unrelated individuals arises because that group contains two subgroups (paternal reference allele/maternal alternative allele and maternal reference allele/paternal alternative allele) each with different means.…”

“…The POE analyses in all three population-based cohorts were performed using QUICKTEST software [30]. This software implements a method for POE analysis using genetic data of unrelated individuals, based on comparing the phenotypic variance of the heterozygous genotype group to the variance observed in the homozygous groups [30].…”

“…In contrast, huge amount of genotype data of unrelated individuals has become available in the era of biobanks. Hoggart et al proposed a novel method for finding POEs in genotype data of unrelated individuals harboring SNPs at which such effects occur with increased variability to the phenotypic outcome [30]. This method is based on the assumption that POEs can be identified as increased variance of phenotype in heterozygotes group compared with homozygous individuals groups due to genetic effect differences among maternal and paternal mutation carriers.…”

“…The method is based on the assumption that increased variance in the heterozygous group in unrelated individuals arises because that group contains two subgroups (paternal reference allele/maternal alternative allele and maternal reference allele/paternal alternative allele) each with different means. The POE test utilize the Brown-Forsythe test, modified to test the mean absolute deviation from the median in the heterozygous and homozygous groups [30] (Supplementary Figure 2). The POE test was performed on 5861 individuals in the EGCUT, 516 in the DILGOM and 8438 individuals in the FINRISK1997 cohort.…”