Southwest American Indians (SAI) suffer from a high obesity prevalence. We previously reported that rs7238987, in cytochrome B5 type A (CYB5A), strongly associated with increased body mass index (BMI) in a population-based study of SAI. CYB5A plays a role in fatty acid oxidation (FAO) and reductions in FAO have been linked to weight gain. However, in vitro studies did not confirm a functional effect of this variant. Therefore, the goal of the current study was to assess variation across the entire CYB5A locus to identify the causal variant contributing to obesity in this population. Genotypic data from a custom Axiom genotyping array on 7,700 SAI was merged with whole-genome sequence data from 335 SAI to impute variation within and 10,000 bp surrounding the CYB5A gene. This region contained 316 variants with a minor allele frequency >0.01; 3 variants had a Combined Annotation Dependent Depletion (CADD) score >10 (top 10% most likely to be deleterious) and a BMI association P ≤ 0.001 (adjusted for age, sex, birth year and the first 5 genetic principle components). Among these potentially deleterious variants, the obesity-risk T-allele in rs548402150, also significantly associated (P = 0.00003) with decreased CYB5A expression in skeletal muscle from biopsy data (n=207). Therefore, rs548402150 was prioritized for functional studies. This C/T variation falls within a CTCF consensus site in the 5’-UTR, which could have the ability to effect gene expression levels. In vitro luciferase reporter assays were used to assess altered promoter activity in human skeletal muscle cells. A 30% decrease in luciferase expression was identified for the promoter carrying the obesity-risk T-allele compared to the non-risk C-allele (P = 0.003). In summary, the further exploration of CYB5A using imputed data has identified a potential casual variant for the observed decreased CYB5A expression and increased risk of obesity in this population. Disclosure S.E. Day: None. M. Traurig: None. P. Piaggi: None. P. Kumar: None. S. Kobes: None. R.L. Hanson: None. C. Bogardus: None. L. Baier: None.

Ecological studies have shown different risks for diabetes (DM) among many ethnic groups, but whether they are due to genetic or non-genetic factors is hard to dissect. We conducted a community-based study aimed at identifying risk factors for DM and related traits in Pacific Islanders from Guam and Saipan. We analyzed the genetic structure of our sample and estimated individual-level admixture using genome-wide SNP data (49,300 variants). We found that genetic ancestry largely derived from 5 populations, representing Marianas Islanders (MI) (mean % heritage, or μ=43%), East Asians (EA, μ=22%), Micronesians (MC, μ=19%), Europeans (EU, μ=13%), and Melanesians (ML, μ=3%). We then tested the association of ancestry estimates with DM, fasting glucose and fasting insulin levels in study participants (n=1,853). Covariates included age, sex and end-stage kidney disease. For fasting insulin, only nondiabetic subjects were used in analyses. All 3 traits were associated with genetic ancestry (p In summary, there were large and statistically significant differences in DM-related traits among Pacific Islanders with different genetic ancestral backgrounds. Although genetic ancestry estimates may still be confounded by shared environmental factors, the present findings suggest that admixture mapping may be a potentially powerful approach for identifying unique DM loci in Pacific Islanders. Disclosure W. Hsueh: None. P. Kumar: None. S. Safabakhsh: None. L. Jones: None. J. Curran: None. W.C. Knowler: None. R.G. Nelson: None. R.L. Hanson: None.

Background Obesity and energy expenditure (EE) are heritable and genetic variants influencing EE may contribute to the development of obesity. We sought to identify genetic variants that affect EE in American Indians, an ethnic group with high prevalence of obesity. Methods Whole-exome sequencing was performed in 373 healthy Pima Indians informative for 24-hour EE during energy balance. Genetic association analyses of all high-quality exonic variants (≥5 carriers) was performed, and those predicted to be damaging were prioritized. Results Rs752074397 introduces a premature stop codon (Cys264Ter) in DAO and demonstrated the strongest association for 24-hour EE, where the Ter allele associated with substantially lower 24-hour EE (mean lower by 268 kcal/d) and sleeping EE (by 135 kcal/d). The Ter allele has a frequency = 0.5% in Pima Indians, whereas is extremely rare in most other ethnic groups (frequency < 0.01%). In vitro functional analysis showed reduced protein levels for the truncated form of DAO consistent with increased protein degradation. DAO encodes D-amino acid oxidase, which is involved in dopamine synthesis which might explain its role in modulating EE. Conclusion Our results indicate that a nonsense mutation in DAO may influence EE in American Indians. Identification of variants that influence energy metabolism may lead to new pathways to treat human obesity. Clinical Trial Registration Number NCT00340132.

BACKGROUND:The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample. RESULTS:A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy. CONCLUSIONS:The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.