Functional genomic characterization of the locus in African Americans.

Physiol Genomics

Division of Molecular Genetics, Department of Pediatrics, College of Physicians and Surgeons, Columbia University Medical Center, New York, New York.

Published: November 2019

Background: SNPs in the first intron of the fat mass and obesity-associated () gene represent the strongest genome-wide associations with adiposity [body mass index (BMI)]; the molecular basis for these associations is under intense investigation. In European populations, the focus of most genome-wide association studies conducted to date, the single nucleotide polymorphisms (SNPs) have indistinguishable associations due to the high level of linkage disequilibrium (LD). However, in African American (AA) individuals, reduced LD and increased haplotype diversity permit finer distinctions among obesity-associated SNPs. Such distinctions are important to mechanistic inferences and for selection of disease SNPs relevant to specific populations.

Methods: To identify specific SNP(s) directly related to adiposity, we performed: ) haplotype analyses of individual-level data in 3,335 AAs from the Atherosclerosis Risk in Communities Cohort (ARIC) study; as well as ) statistical fine-mapping using summary statistics from a study of in over 20 000 AAs and over 1000 functional genomic annotations.

Results: Our haplotype analyses suggest that in AAs at least two distinct signals underlie the intron 1 -adiposity signal. Fine mapping showed that two SNPs have the highest posterior probability of association (PPA) with BMI: rs9927317 (PPA = 0.94) and rs62033405 (PPA = 0.99). These variants overlap possible enhancer sites and the 5'-regions of transcribed genes in the substantia nigra, chondrocytes, and white adipocytes.

Conclusions: We found two SNPs in with the highest probability of direct association with BMI in AAs, as well as tissue-specific mechanisms by which these variants may contribute to the pathogenesis of obesity.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6879815PMC
http://dx.doi.org/10.1152/physiolgenomics.00057.2019DOI Listing

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