Yann C Klimentidis

Yann C Klimentidis

Associate Professor, Public Health
Assistant Professor, Genetics - GIDP
Associate Professor, BIO5 Institute
Primary Department
Contact
(520) 621-0147

Work Summary

I use human genetic data to find associations of genetic markers with complex traits and diseases, to shed light on disease pathophysiology, causal pathways, and health disparities, and to inform precision medicine.

Research Interest

Yann C. Klimentidis, PhD, is an Associate Professor in the Department of Epidemiology and Biostatistics in the Mel and Enid Zuckerman College of Public Health at the University of Arizona. His research centers on improving our understanding of the links between genetic variation, lifestyle factors, metabolic disease, and health disparities. In the past, he has used measures of genetic admixture and genomic tests of natural selection to understand the genetic basis of population differences in disease susceptibility. His most recent work examines the use various statistical approaches for the analysis of high-dimensional genetic data for improving prediction of genetic susceptibility to type-2 diabetes. In addition, his work examines gene-by-lifestyle interactions in type-2 diabetes, as well as understanding the causal links between metabolic traits such as dyslipidemia and type-2 diabetes. Keywords: Genetics, epidemiology, Cardiometabolic disease, Physical activity

Publications

Reynolds, R. J., Vazquez, A. I., Srinivasasainagendra, V., Klimentidis, Y. C., Bridges, S. L., Allison, D. B., & Singh, J. A. (2015). Serum urate gene associations with incident gout, measured in the Framingham Heart Study, are modified by renal disease and not by body mass index. Rheumatology international.

We hypothesized that serum urate-associated SNPs, individually or collectively, interact with BMI and renal disease to contribute to risk of incident gout. We measured the incidence of gout and associated comorbidities using the original and offspring cohorts of the Framingham Heart Study. We used direct and imputed genotypes for eight validated serum urate loci. We fit binomial regression models of gout incidence as a function of the covariates, age, type 2 diabetes, sex, and all main and interaction effects of the eight serum urate SNPs with BMI and renal disease. Models were also fit with a genetic risk score for serum urate levels which corresponds to the sum of risk alleles at the eight SNPs. Model covariates, age (P = 5.95E-06), sex (P = 2.46E-39), diabetes (P = 2.34E-07), BMI (P = 1.14E-11) and the SNPs, rs1967017 (P = 9.54E-03), rs13129697 (P = 4.34E-07), rs2199936 (P = 7.28E-03) and rs675209 (P = 4.84E-02) were all associated with incident gout. No BMI by SNP or BMI by serum urate genetic risk score interactions were statistically significant, but renal disease by rs1106766 was statistically significant (P = 6.12E-03). We demonstrated that minor alleles of rs1106766 (intergenic, INHBC) were negatively associated with the risk of incident gout in subjects without renal disease, but not for individuals with renal disease. These analyses demonstrate that a significant component of the risk of gout may involve complex interplay between genes and environment.

Lemas, D. J., Klimentidis, Y. C., Wiener, H. H., O'Brien, D. M., Hopkins, S. E., Allison, D. B., Fernandez, J. R., Tiwari, H. K., & Boyer, B. B. (2013). Obesity polymorphisms identified in genome-wide association studies interact with n-3 polyunsaturated fatty acid intake and modify the genetic association with adiposity phenotypes in Yup'ik people. Genes & nutrition, 8(5).

n-3 Polyunsaturated fatty acids (n-3 PUFAs) have anti-obesity effects that may modulate risk of obesity, in part, through interactions with genetic factors. Genome-wide association studies (GWAS) have identified genetic variants associated with body mass index (BMI); however, the extent to which these variants influence adiposity through interactions with n-3 PUFAs remains unknown. We evaluated 10 highly replicated obesity GWAS single nucleotide polymorphisms (SNPs) for individual and cumulative associations with adiposity phenotypes in a cross-sectional sample of Yup'ik people (n = 1,073) and evaluated whether genetic associations with obesity were modulated by n-3 PUFA intake. A genetic risk score (GRS) was calculated by adding the BMI-increasing alleles across all 10 SNPs. Dietary intake of n-3 PUFAs was estimated using nitrogen stable isotope ratio (δ(15)N) of red blood cells, and genotype-phenotype analyses were tested in linear models accounting for familial correlations. GRS was positively associated with BMI (p = 0.012), PBF (p = 0.022), ThC (p = 0.025), and waist circumference (p = 0.038). The variance in adiposity phenotypes explained by the GRS included BMI (0.7 %), PBF (0.3 %), ThC (0.7 %), and WC (0.5 %). GRS interactions with n-3 PUFAs modified the association with adiposity and accounted for more than twice the phenotypic variation (~1-2 %), relative to GRS associations alone. Obesity GWAS SNPs contribute to adiposity in this study population of Yup'ik people and interactions with n-3 PUFA intake potentiated the risk of fat accumulation among individuals with high obesity GRS. These data suggest the anti-obesity effects of n-3 PUFAs among Yup'ik people may, in part, be dependent upon an individual's genetic predisposition to obesity.

Aslibekyan, S., Vaughan, L. K., Wiener, H. W., Lemas, D. J., Klimentidis, Y. C., Havel, P. J., Stanhope, K. L., O'brien, D. M., Hopkins, S. E., Boyer, B. B., & Tiwari, H. K. (2014). Evidence for novel genetic loci associated with metabolic traits in Yup'ik people. American journal of human biology : the official journal of the Human Biology Council, 25(5).

To identify genomic regions associated with fasting plasma lipid profiles, insulin, glucose, and glycosylated hemoglobin in a Yup'ik study population, and to evaluate whether the observed associations between genetic factors and metabolic traits were modified by dietary intake of marine derived omega-3 polyunsaturated acids (n-3 PUFA).

Klimentidis, Y. C., Zhou, J., & Kittles, R. A. (2015). Among men only, West-African genetic ancestry is associated with lower central adiposity. International Journal of Obesity.
Lebron-Aldea, D., Dhurandhar, E. J., Perez-Rodriguez, P., Klimentidis, Y. C., Tiwari, H. K., & Vazquez, A. I. (2014). Genome-enabled models for type 2 diabetes risk assessment. Frontiers in Genetics.