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.
| Original language | English |
|---|---|
| Pages (from-to) | 486-491 |
| Number of pages | 6 |
| Journal | Genetic Epidemiology |
| Volume | 40 |
| Issue number | 6 |
| DOIs | |
| State | Published - 1 Sep 2016 |
| Externally published | Yes |
Keywords
- carnitine
- linkage disequilibrium
- metabolomics
- penalization
- rare variants
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