Publications

2018

Balakrishnan, Poojitha, Dhananjay Vaidya, Saroja Voruganti, Karin Haack, Jack W Kent, Kari E North, Sandra Laston, et al. (2018) 2018. “Genetic Variants Related to Cardiometabolic Traits Are Associated to B Cell Function, Insulin Resistance, and Diabetes Among AmeriCan Indians: The Strong Heart Family Study.”. Frontiers in Genetics 9: 466. https://doi.org/10.3389/fgene.2018.00466.

Background: Genetic research may inform underlying mechanisms for disparities in the burden of type 2 diabetes mellitus among American Indians. Our objective was to assess the association of genetic variants in cardiometabolic candidate genes with B cell dysfunction via HOMA-B, insulin resistance via HOMA-IR, and type 2 diabetes mellitus in the Strong Heart Family Study (SHFS). Methods and Results: We examined the association of variants, previously associated with cardiometabolic traits (∼200,000 from Illumina Cardio MetaboChip), using mixed models of HOMA-B residuals corrected for HOMA-IR (cHOMA-B), log transformed HOMA-IR, and incident diabetes, adjusted for age, sex, population stratification, and familial relatedness. Center-specific estimates were combined using fixed effect meta-analyses. We used Bonferroni correction to account for multiple testing (P < 4.13 × 10-7). We also assessed the association between variants in candidate diabetes genes with these metabolic traits. We explored the top SNPs in an independent, replication sample from Southwestern Arizona. We identified significant associations with cHOMA-B for common variants at 26 loci of which 8 were novel (PRSS7, FCRL5, PEL1, LRP12, IGLL1, ARHGEF10, PARVA, FLJ16686). The most significant variant association with cHOMA-B was observed on chromosome 5 for an intergenic variant near PARP8 (rs2961831, P = 6.39 × 10-9). In the replication study, we found a signal at rs4607517 near GCK/YKT6 (P = 0.01). Variants near candidate diabetes genes (especially GCK and KCNQ1) were also nominally associated with HOMA-IR and cHOMA-B. Conclusion: We identified variants at novel loci and confirmed those at known candidate diabetes loci associations for cHOMA-B. This study also provided evidence for association of variants at KCNQ2, CTNAA2, and KCNQ1with cHOMA-B among American Indians. Further studies are needed to account for the high heritability of diabetes among the American Indian participants of the SHFS cohort.

Bastarrachea, Raul A, Hugo A Laviada-Molina, Edna J Nava-Gonzalez, Irene Leal-Berumen, Claudia Escudero-Lourdes, Fabiola Escalante-Araiza, Vanessa-Giselle Peschard, et al. (2018) 2018. “Deep Multi-OMICs and Multi-Tissue Characterization in a Pre- and Postprandial State in Human Volunteers: The GEMM Family Study Research Design.”. Genes 9 (11). https://doi.org/10.3390/genes9110532.

Cardiovascular disease (CVD) and type 2 diabetes (T2D) are increasing worldwide. This is mainly due to an unhealthy nutrition, implying that variation in CVD risk may be due to variation in the capacity to manage a nutritional load. We examined the genomic basis of postprandial metabolism. Our main purpose was to introduce the GEMM Family Study (Genetics of Metabolic Diseases in Mexico) as a multi-center study carrying out an ongoing recruitment of healthy urban adults. Each participant received a mixed meal challenge and provided a 5-hours' time course series of blood, buffy coat specimens for DNA isolation, and adipose tissue (ADT)/skeletal muscle (SKM) biopsies at fasting and 3 h after the meal. A comprehensive profiling, including metabolomic signatures in blood and transcriptomic and proteomic profiling in SKM and ADT, was performed to describe tendencies for variation in postprandial response. Our data generation methods showed preliminary trends indicating that by characterizing the dynamic properties of biomarkers with metabolic activity and analyzing multi-OMICS data it could be possible, with this methodology and research design, to identify early trends for molecular biology systems and genes involved in the fasted and fed states.

Spratlen, Miranda J, Maria Grau-Perez, Jason G Umans, Joseph Yracheta, Lyle G Best, Kevin Francesconi, Walter Goessler, et al. (2018) 2018. “Arsenic, One Carbon Metabolism and Diabetes-Related Outcomes in the Strong Heart Family Study.”. Environment International 121 (Pt 1): 728-40. https://doi.org/10.1016/j.envint.2018.09.048.

BACKGROUND: Inorganic arsenic exposure and inter-individual differences in its metabolism have been associated with cardiometabolic risk. A more efficient arsenic metabolism profile (lower MMA%, higher DMA%) has been associated with reduced risk for arsenic-related health outcomes; however, this profile has also been associated with increased risk for diabetes-related outcomes. The mechanism behind these contrasting associations is equivocal; we hypothesized one carbon metabolism (OCM) may play a role.

METHODS: We evaluated the association between OCM-related variables (nutrient intake and genetic variants) and both arsenic metabolism biomarkers (iAs%, MMA% and DMA%) and diabetes-related outcomes (metabolic syndrome, diabetes, HOMA2-IR and waist circumference) in 935 participants free of prevalent diabetes and metabolic syndrome from the Strong Heart Family Study, a family-based prospective cohort comprised of American Indian tribal members aged 14+ years.

RESULTS: Of the 935 participants free of both diabetes and metabolic syndrome at baseline, 279 (29.8%) developed metabolic syndrome over a median of 5.3 years of follow-up and of the 1458 participants free of diabetes at baseline, 167 (11.3%) developed diabetes over follow-up. OCM nutrients were not associated with arsenic metabolism, however, higher vitamin B6 was associated with diabetes-related outcomes (higher HOMA2-IR and increased risk for diabetes and metabolic syndrome). A polymorphism in an OCM-related gene, methionine synthase (MTR), was associated with both higher MMA% (β = 2.57, 95% CI: 0.22, 4.92) and lower HOMA2-IR (GMR = 0.79, 95% CI = 0.66, 0.93 per 5 years of follow-up). Adjustment for OCM variables did not affect previously reported associations between arsenic metabolism and diabetes-related outcomes; however, the association between the MTR variant and diabetes-related outcomes were attenuated after adjustment for arsenic metabolism.

CONCLUSIONS: Our findings suggest MMA% may be a partial mediator in the association between OCM and diabetes-related outcomes. Additional mediation analyses with longer follow-up period are needed to confirm this finding. Further research is needed to determine whether excess B vitamin intake is associated with increased risk for diabetes-related outcomes.

2017

Peng, Hao, Mihriye Mete, Sameer Desale, Amanda M Fretts, Shelley A Cole, Lyle G Best, Jue Lin, et al. (2017) 2017. “Leukocyte Telomere Length and Ideal Cardiovascular Health in American Indians: The Strong Heart Family Study.”. European Journal of Epidemiology 32 (1): 67-75. https://doi.org/10.1007/s10654-016-0199-6.

Telomere length, a marker of biological aging, has been associated with cardiovascular disease (CVD) and its risk factors. Ideal cardiovascular health (CVH), defined by the American Heart Association (AHA), has also been associated with a reduced risk of CVD, but the relationship between telomere length and ideal CVH is unclear. We measured leukocyte telomere length (LTL) by qPCR in 2568 American Indians in the Strong Heart Family Study (SHFS). All participants were free of overt CVD at enrollment (2001-2003). CVH indices included four behavioral factors (smoking, physical activity, diet, BMI) and three health factors (blood pressure, cholesterol, fasting glucose). Each index was categorized as poor, intermediate, or ideal according to the AHA's guideline. CVH was further categorized into below average (0-1), average (2-3) and above average (≥4) based on the total number of ideal indices. Results showed that, 29, 50 and 21 % of study participants had below average, average, and above average CVH, respectively. Participants with above average CVH had significantly longer LTL than those with below average CVH (β = 0.034, P = 0.042) after adjusting for age, sex, education level, marital status, processed meat consumption, alcohol consumption, and study site. Compared to the U.S. general population, American Indians achieved lower rates for five out of the seven ideal CVH metrics, including smoking, BMI, physical activity, diet, and blood pressure. Achieving four or more ideal CVH metrics was significantly associated with longer LTL. This finding suggests that achieving an ideal CVH may prevent or delay CVD, probably through promoting healthy aging.

Balakrishnan, Poojitha, Dhananjay Vaidya, Nora Franceschini, Saroja Voruganti, Matthew O Gribble, Karin Haack, Sandra Laston, et al. (2017) 2017. “Association of Cardiometabolic Genes With Arsenic Metabolism Biomarkers in American Indian Communities: The Strong Heart Family Study (SHFS).”. Environmental Health Perspectives 125 (1): 15-22. https://doi.org/10.1289/EHP251.

BACKGROUND: Metabolism of inorganic arsenic (iAs) is subject to inter-individual variability, which is explained partly by genetic determinants.

OBJECTIVES: We investigated the association of genetic variants with arsenic species and principal components of arsenic species in the Strong Heart Family Study (SHFS).

METHODS: We examined variants previously associated with cardiometabolic traits (  200,000 from Illumina Cardio MetaboChip) or arsenic metabolism and toxicity (670) among 2,428 American Indian participants in the SHFS. Urine arsenic species were measured by high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS), and percent arsenic species [iAs, monomethylarsonate (MMA), and dimethylarsinate (DMA), divided by their sum × 100] were logit transformed. We created two orthogonal principal components that summarized iAs, MMA, and DMA and were also phenotypes for genetic analyses. Linear regression was performed for each phenotype, dependent on allele dosage of the variant. Models accounted for familial relatedness and were adjusted for age, sex, total arsenic levels, and population stratification. Single nucleotide polymorphism (SNP) associations were stratified by study site and were meta-analyzed. Bonferroni correction was used to account for multiple testing.

RESULTS: Variants at 10q24 were statistically significant for all percent arsenic species and principal components of arsenic species. The index SNP for iAs%, MMA%, and DMA% (rs12768205) and for the principal components (rs3740394, rs3740393) were located near AS3MT, whose gene product catalyzes methylation of iAs to MMA and DMA. Among the candidate arsenic variant associations, functional SNPs in AS3MT and 10q24 were most significant (p < 9.33 × 10-5).

CONCLUSIONS: This hypothesis-driven association study supports the role of common variants in arsenic metabolism, particularly AS3MT and 10q24. Citation: Balakrishnan P, Vaidya D, Franceschini N, Voruganti VS, Gribble MO, Haack K, Laston S, Umans JG, Francesconi KA, Goessler W, North KE, Lee E, Yracheta J, Best LG, MacCluer JW, Kent J Jr., Cole SA, Navas-Acien A. 2017. Association of cardiometabolic genes with arsenic metabolism biomarkers in American Indian communities: the Strong Heart Family Study (SHFS). Environ Health Perspect 125:15-22; http://dx.doi.org/10.1289/EHP251.

Chittoor, Geetha, Karin Haack, Nitesh R Mehta, Sandra Laston, Shelley A Cole, Anthony G Comuzzie, Nancy F Butte, and Saroja Voruganti. (2017) 2017. “Genetic Variation Underlying Renal Uric Acid Excretion in Hispanic Children: The Viva La Familia Study.”. BMC Medical Genetics 18 (1): 6. https://doi.org/10.1186/s12881-016-0366-3.

BACKGROUND: Reduced renal excretion of uric acid plays a significant role in the development of hyperuricemia and gout in adults. Hyperuricemia has been associated with chronic kidney disease and cardiovascular disease in children and adults. There are limited genome-wide association studies associating genetic polymorphisms with renal urate excretion measures. Therefore, we investigated the genetic factors that influence the excretion of uric acid and related indices in 768 Hispanic children of the Viva La Familia Study.

METHODS: We performed a genome-wide association analysis for 24-h urinary excretion measures such as urinary uric acid/urinary creatinine ratio, uric acid clearance, fractional excretion of uric acid, and glomerular load of uric acid in SOLAR, while accounting for non-independence among family members.

RESULTS: All renal urate excretion measures were significantly heritable (p <2 × 10-6) and ranged from 0.41 to 0.74. Empirical threshold for genome-wide significance was set at p <1 × 10-7. We observed a strong association (p < 8 × 10-8) of uric acid clearance with a single nucleotide polymorphism (SNP) in zinc finger protein 446 (ZNF446) (rs2033711 (A/G), MAF: 0.30). The minor allele (G) was associated with increased uric acid clearance. Also, we found suggestive associations of uric acid clearance with SNPs in ZNF324, ZNF584, and ZNF132 (in a 72 kb region of 19q13; p <1 × 10-6, MAFs: 0.28-0.31).

CONCLUSION: For the first time, we showed the importance of 19q13 region in the regulation of renal urate excretion in Hispanic children. Our findings indicate differences in inherent genetic architecture and shared environmental risk factors between our cohort and other pediatric and adult populations.

Olmedo, Pablo, Maria Grau-Perez, Amanda Fretts, Maria Tellez-Plaza, Fernando Gil, Fawn Yeh, Jason G Umans, et al. (2017) 2017. “Dietary Determinants of Cadmium Exposure in the Strong Heart Family Study.”. Food and Chemical Toxicology : An International Journal Published for the British Industrial Biological Research Association 100: 239-46. https://doi.org/10.1016/j.fct.2016.12.015.

Urinary cadmium (Cd) concentrations in the Strong Heart Family Study (SHFS) participants are higher than in the general US population. This difference is unlikely to be related to tobacco smoking. We evaluated the association of consumption of processed meats and other dietary products with urinary Cd concentrations in the SHFS, a family-based study conducted in American Indian communities. We included 1725 participants with urine Cd concentrations (standardized to urine creatinine) and food frequency questionnaire data grouped in 24 categories, including processed meat. Median (IQR) urinary Cd concentrations were 0.42 (0.20-0.85) μg/g creatinine. The age, sex, smoking, education, center, body mass index, and total kcal adjusted geometric mean ratio (GMR) (95%CI) of urinary cadmium concentrations per IQR increase in each dietary category was 1.16 (1.04-1.29) for processed meat, 1.10 (1.00-1.21) for fries and chips, 0.87 (0.80-0.95) for dairy products, and 0.89 (0.82-0.97) for fruit juices. The results remained similar after further adjustment for the dietary categories associated with urinary Cd in the previous model except for fries and chips, which was no longer statistically significant. These findings revealed the potential importance of processed meat products as a dietary source of cadmium.

Franceschini, N, R C Fry, P Balakrishnan, A Navas-Acien, C Oliver-Williams, A G Howard, S A Cole, et al. (2017) 2017. “Cadmium Body Burden and Increased Blood Pressure in Middle-Aged American Indians: The Strong Heart Study.”. Journal of Human Hypertension 31 (3): 225-30. https://doi.org/10.1038/jhh.2016.67.

Cadmium (Cd) is an environmental pollutant that has been associated with cardiovascular disease in populations, but the relationship of Cd with hypertension has been inconsistent. We studied the association between urinary Cd concentrations, a measure of total body burden, and blood pressure in American Indians, a US population with above national average Cd burden. Urinary Cd was measured using inductively coupled plasma mass spectrometry, and adjusted for urinary creatinine concentration. Among 3714 middle-aged American Indian participants of the Strong Heart Study (mean age 56 years, 41% male, 67% ever-smokers, 23% taking antihypertensive medications), urinary Cd ranged from 0.01 to 78.48 μg g-1 creatinine (geometric mean=0.94 μg g-1) and it was correlated with smoking pack-year among ever-smokers (r2=0.16, P<0.0001). Participants who were smokers were on average light-smokers (mean 10.8 pack-years), and urinary Cd was similarly elevated in light- and never-smokers (geometric means of 0.88 μg g-1 creatinine for both categories). Log-transformed urinary Cd was significantly associated with higher systolic blood pressure in models adjusted for age, sex, geographic area, body mass index, smoking (ever vs never, and cumulative pack-years) and kidney function (mean blood pressure difference by lnCd concentration (β)=1.64, P=0.002). These associations were present among light- and never-smokers (β=2.03, P=0.002, n=2627), although not significant among never-smokers (β=1.22, P=0.18, n=1260). Cd was also associated with diastolic blood pressure among light- and never-smokers (β=0.94, P=0.004). These findings suggest that there is a relationship between Cd body burden and increased blood pressure in American Indians, a population with increased cardiovascular disease risk.

Wang, Wenyu, Ying Zhang, Elisa T Lee, Barbara Howard V, Richard B Devereux, Shelley A Cole, Lyle G Best, et al. (2017) 2017. “Risk Factors and Prediction of Stroke in a Population With High Prevalence of Diabetes: The Strong Heart Study.”. World Journal of Cardiovascular Diseases 7 (5): 145-62. https://doi.org/10.4236/wjcd.2017.75014.

BACKGROUND AND OBJECTIVE: American Indians have a high prevalence of diabetes and higher incidence of stroke than that of whites and blacks in the U.S. Stroke risk prediction models based on data from American Indians would be of clinical and public health value.

METHODS AND RESULTS: A total of 3483 (2043 women) Strong Heart Study participants free of stroke at baseline were followed from 1989 to 2010 for incident stroke. Overall, 297 stroke cases (179 women) were identified. Cox models with stroke-free time and risk factors recorded at baseline were used to develop stroke risk prediction models. Assessment of the developed stroke risk prediction models regarding discrimination and calibration was performed by an analogous C-statistic (C) and a version of the Hosmer-Lemeshow statistic (HL), respectively, and validated internally through use of Bootstrapping methods.

RESULTS: Age, smoking status, alcohol consumption, waist circumference, hypertension status, an-tihypertensive therapy, fasting plasma glucose, diabetes medications, high/low density lipoproteins, urinary albumin/creatinine ratio, history of coronary heart disease/heart failure, atrial fibrillation, or Left ventricular hypertrophy, and parental history of stroke were identified as the significant optimal risk factors for incident stroke.

DISCUSSION: The models produced a C = 0.761 and HL = 4.668 (p = 0.792) for women, and a C = 0.765 and HL = 9.171 (p = 0.328) for men, showing good discrimination and calibration.

CONCLUSIONS: Our stroke risk prediction models provide a mechanism for stroke risk assessment designed for American Indians. The models may be also useful to other populations with high prevalence of obesity and/or diabetes for screening individuals for risk of incident stroke and designing prevention programs.