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Identification of Rare Variants in Metabolites of the Carnitine Pathway by Whole Genome Sequencing Analysis
Author(s) -
Yazdani Akram,
Yazdani Azam,
Liu Xiaoming,
Boerwinkle Eric
Publication year - 2016
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.21980
Subject(s) - biology , metabolome , whole genome sequencing , genetics , computational biology , metabolomics , genome wide association study , phenotype , minor allele frequency , genome , allele , identification (biology) , allele frequency , gene , bioinformatics , genotype , single nucleotide polymorphism , botany
ABSTRACT We use whole genome sequence data and rare variant analysis methods to investigate a subset of the human serum metabolome, including 16 carnitine‐related metabolites that are important components of mammalian energy metabolism. Medium pass sequence data consisting of 12,820,347 rare variants and serum metabolomics data were available on 1,456 individuals. By applying a penalization method, we identified two genes FGF8 and MDGA2 with significant effects on lysine and cis‐4‐decenoylcarnitine , respectively, using Δ‐AIC and likelihood ratio test statistics. Single variant analyses in these regions did not identify a single low‐frequency variant (minor allele count > 3) responsible for the underlying signal. The results demonstrate the utility of whole genome sequence and innovative analyses for identifying candidate regions influencing complex phenotypes.