Associations of Body Mass Index and Obesity-Related Genetic Variants with Serum Metabolites
Jitender Kumar, Robert Karlsson, Corey D. Broeckling, Mun-Gwan Hong, Jonathan A. Prince, Jessica E. Prenni, Erik Ingelsson and Fredrik Wiklund
Affiliation: Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Dag Hammarskjölds Vag 14B, First Floor, MTC Building, Science Park, Uppsala University, SE-751 85 Uppsala, Sweden.
Keywords: Body mass index, genetic risk score, ultra-performance liquid chromatography, untargeted metabolomics.
Objectives: Body mass index (BMI) is one of the most important risk factors for different metabolic and cardiovascular
disorders. Previously, both genetic and environmental agents associated with BMI have been described. The
main focus of this exploratory study was to find the circulating metabolites associated with BMI utilizing an untargeted
metabolomics approach. Additionally, significant metabolites identified were studied for their relation with BMIassociated
single nucleotide polymorphisms (SNPs).
Materials and Methods: A total of 971 individuals from the Cancer of the Prostate in Sweden study (discovery sample-
275 prostate cancers patients and 182 controls; replication sample- 514 prostate cancer patients) were utilized. Blood
samples were collected and serum metabolic profiling was obtained using ultra-performance liquid chromatography followed
by mass spectrometry. Genotyping data was available for 26 out of 32 SNPs (21 genotyped and 5 proxies) previously
robustly associated with BMI in individuals of European descent. Weighted genetic risk score was generated using
these SNPs and studied for its association with metabolites.
Results: A total of 6138 and 5209 metabolite features were detected in discovery and replication samples, respectively.
Out of 6138 metabolite features in discovery sample, 201 were found to be significantly associated with BMI (p<8.15*10-6)
after multiple testing correction. These 201 features were further investigated in the replication samples and 16 were
found to be significantly associated with BMI (p<2.49*10-4). Seven of these significant features were isotopes for four of
the primary metabolites. Four metabolites were putatively identified: monoacylglyceride (18:1), diacylglyrcerol (32:1)
and two phosphatidylcholines (34:0 and 36:0). Weighted genetic score of BMI-associated SNPs was not associated with
these four metabolites.
Conclusion: Four identifiable metabolites (monoacylglyceride, diacyclglyrcerol and two phosphatidylcholines) were
found to be significantly associated with BMI in both discovery and replication samples. Common variants associated
with BMI did not show association with these four metabolites.
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