Exome sequencing followed by genotyping suggests SYPL2 as a susceptibility gene for morbid obesity.

Jiao H, Arner P, Gerdhem P, Strawbridge RJ, Näslund E, Thorell A, Hamsten A, Kere J, Dahlman I

Eur. J. Hum. Genet. 23 (9) 1216-1222 [2015-09-00; online 2014-11-20]

Recently developed high-throughput sequencing technology shows power to detect low-frequency disease-causing variants by deep sequencing of all known exons. We used exome sequencing to identify variants associated with morbid obesity. DNA from 100 morbidly obese adult subjects and 100 controls were pooled (n=10/pool), subjected to exome capture, and subsequent sequencing. At least 100 million sequencing reads were obtained from each pool. After several filtering steps and comparisons of observed frequencies of variants between obese and non-obese control pools, we systematically selected 144 obesity-enriched non-synonymous, splicing site or 5' upstream single-nucleotide variants for validation. We first genotyped 494 adult subjects with morbid obesity and 496 controls. Five obesity-associated variants (nominal P-value<0.05) were subsequently genotyped in 1425 morbidly obese and 782 controls. Out of the five variants, only rs62623713:A>G (NM_001040709:c.A296G:p.E99G) was confirmed. rs62623713 showed strong association with body mass index (beta=2.13 (1.09, 3.18), P=6.28 × 10(-5)) in a joint analysis of all 3197 genotyped subjects and had an odds ratio of 1.32 for obesity association. rs62623713 is a low-frequency (2.9% minor allele frequency) non-synonymous variant (E99G) in exon 4 of the synaptophysin-like 2 (SYPL2) gene. rs62623713 was not covered by Illumina or Affymetrix genotyping arrays used in previous genome-wide association studies. Mice lacking Sypl2 has been reported to display reduced body weight. In conclusion, using exome sequencing we identified a low-frequency coding variant in the SYPL2 gene that was associated with morbid obesity. This gene may be involved in the development of excess body fat.

Mutation Analysis Facility (MAF)

NGI Stockholm (Genomics Applications)

NGI Stockholm (Genomics Production)

NGI Uppsala (SNP&SEQ Technology Platform)

National Genomics Infrastructure

PubMed 25406998

DOI 10.1038/ejhg.2014.255

Crossref 10.1038/ejhg.2014.255

pii: ejhg2014255
pmc: PMC4538196