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

Hibler, E. A., Klimentidis, Y. C., Jurutka, P. W., Kohler, L. N., Lance, P., Roe, D. J., Thompson, P. A., & Jacobs, E. T. (2015). CYP24A1 and CYP27B1 Polymorphisms, Concentrations of Vitamin D Metabolites, and Odds of Colorectal Adenoma Recurrence. Nutrition and cancer, 67(7), 1131-41.

Development of colorectal adenoma and cancer are associated with low circulating 25-hydroxyvitamin D [25(OH)D] levels. However, less is known regarding colorectal neoplasia risk and variation in CYP27B1 or CYP24A1, genes encoding the enzymes responsible for the synthesis and catabolism of 1α,25-hydroxyvitamin D [1,25(OH)2D]. This study examined associations between CYP27B1 and CYP24A1 polymorphisms, circulating 25(OH)D and 1,25(OH)2D concentrations, and colorectal adenoma recurrence in a pooled sample from 2 clinical trials (n = 1,188). Nominal associations were observed between increasing copies of the T allele in CYP24A1 rs927650 and 25(OH)D concentrations (P = 0.02); as well as colorectal adenoma recurrence, with odds ratios (95% confidence intervals) of 1.30 (0.99-1.70) and 1.38 (1.01-1.89) for heterozygotes and minor allele homozygotes, respectively (P = 0.04). In addition, a statistically significant relationship between CYP24A1 rs35051736, a functional polymorphism, and odds for advanced colorectal adenoma recurrence was observed (P 0.001). Further, nominally statistically significant interactions were observed between rs2296241 and 25(OH)D as well as rs2762939 and 1,25(OH)2D (P(interaction) = 0.10, respectively). Overall, CYP24A1 polymorphisms may influence the development of advanced lesions, and modify the effect of vitamin D metabolites on adenoma recurrence. Further study is necessary to characterize the differences between circulating vitamin D metabolite measurements compared to cellular level activity in relation to cancer risk.

Klimentidis, Y. C., Wineinger, N. E., Vazquez, A. I., & de Los Campos, G. (2014). Multiple metabolic genetic risk scores and type 2 diabetes risk in three racial/ethnic groups. The Journal of clinical endocrinology and metabolism, 99(9), E1814-8.

CONTEXT/RATIONALE: Meta-analyses of genome-wide association studies have identified many single-nucleotide polymorphisms associated with various metabolic and cardiovascular traits, offering us the opportunity to learn about and capitalize on the links between cardiometabolic traits and type 2 diabetes (T2D).

Klimentidis, Y. C., Zhou, J., & Wineinger, N. E. (2014). Identification of allelic heterogeneity at type-2 diabetes loci and impact on prediction. PloS one, 9(11), e113072.

Although over 60 single nucleotide polymorphisms (SNPs) have been identified by meta-analysis of genome-wide association studies for type-2 diabetes (T2D) among individuals of European descent, much of the genetic variation remains unexplained. There are likely many more SNPs that contribute to variation in T2D risk, some of which may lie in the regions surrounding established SNPs--a phenomenon often referred to as allelic heterogeneity. Here, we use the summary statistics from the DIAGRAM consortium meta-analysis of T2D genome-wide association studies along with linkage disequilibrium patterns inferred from a large reference sample to identify novel SNPs associated with T2D surrounding each of the previously established risk loci. We then examine the extent to which the use of these additional SNPs improves prediction of T2D risk in an independent validation dataset. Our results suggest that multiple SNPs at each of 3 loci contribute to T2D susceptibility (TCF7L2, CDKN2A/B, and KCNQ1; p5×10(-8)). Using a less stringent threshold (p5×10(-4)), we identify 34 additional loci with multiple associated SNPs. The addition of these SNPs slightly improves T2D prediction compared to the use of only the respective lead SNPs, when assessed using an independent validation cohort. Our findings suggest that some currently established T2D risk loci likely harbor multiple polymorphisms which contribute independently and collectively to T2D risk. This opens a promising avenue for improving prediction of T2D, and for a better understanding of the genetic architecture of T2D.

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.