SLCO1B1 Gene Variants and Urine Arsenic Metabolites in the Strong Heart Family Study

Background: Several studies have evaluated associations among various dietary nutrients (eg n-3 fatty acids, caffeine, magnesium) and depression in different populations. Such analyses, however, may not adequately address possible interactions among nutrients and may overlook unmeasured micronutrients. We examined the relationships among four diet patterns and depression in American Indians (AI) from the Strong Heart Family Study. Methods: Four diet patterns were extracted using factor analysis with principal component factoring method based on a sample of 3245 AI aged 14 years or older (excluding extreme calorie intakes, n=203; total var=38%). Linear Regressionmodels of the depression scale by the Center for Epidemiological Studies of Depression (CES-D) were constructed to examine the association between diet patterns and continuous CES-D measures adjusting for age, gender, BMI, waist circumference, Diabetes, education level, physical activity and Locus of Control (LOC) assessed by Multidimensional Health Locus of Control Form-B. Logistic regression models of symptoms of depression vs no depression were also run to estimate the associations of diet patterns to depression. Results: Factor 1 (in quintiles), the “less healthy” pattern, includes more fast food, snack chips, fried potatoes, prepared main dishes, sweet beverages, and animal fats. Participants who scored high on this pattern had an increase risk of depression (OR=1.09, 95%CI=1.02-1.18, p=.02). Factor 2, the “traditional AI/Southwestern” pattern consists of traditional American Indian foods common in the Southwest, as well as of meat, stew and dry beans. It is positively related to depression (OR=1.11, 95%CI=1.04-1.20, p=.002). Factor 3 resembles a healthy diet associated with fish, fruits, dark whole bread and low-fat healthier meat and dairy products. Participants who scored high on this pattern were less likely to have depression (OR=.93, 95%CI=.87-.99, p=.03). Factor 4, the “junk-food” pattern includes high amounts of coffee, tea, candy bars, sugar, syrup, animal fats, sweetened grains, doughnuts, cookies, pies, cakes, ice cream, and non-dairy creamer. Participants who scored high on this pattern were more likely to have depression (OR=1.12, 95%CI=1.05-1.20, p=.001). Depression was higher in women (OR =1.99, 95%CI=1.6-2.5, p<.001) and those with abdominal obesity (in cm; OR=1.02, p=.02) and lower in those with greater physical activity (OR=.88, p=.001), increasing age (OR=.99, p=.01), and more education (OR=.89, p<.001). Conclusion: A healthy eating pattern as well as greater physical activity and higher education were independently associated with lower depression, while depression was higher in those with central obesity. The results suggest that interventions aimed toward weight loss may also improve rates of depression in some populations.

Download Full-text

Abstract MP50: Metabolic Predictors of Type 2 Diabetes in American Indians: The Strong Heart Family Study

Circulation ◽

10.1161/circ.129.suppl_1.mp50 ◽

2014 ◽

Vol 129 (suppl_1) ◽

Author(s):

Yun Zhu ◽

Jiang He ◽

Lyle G Best ◽

Elisa T Lee ◽

Barbara V Howard ◽

...

Keyword(s):

Type 2 Diabetes ◽

Amino Acids ◽

American Indians ◽

Family Study ◽

Fasting Glucose ◽

Plasma Metabolites ◽

Metabolic Alterations ◽

Incident Cases ◽

Strong Heart Family Study

Background: Type 2 diabetes (T2D) is characterized by profound metabolic abnormalities. Current glycemic indicators have limitations in identifying early metabolic alterations. Objective: To identify novel metabolic predictors of T2D in American Indians participating in the Strong Heart Family Study. Methods: Among 2,129 participants who had normal fasting glucose (NFG) at baseline (2001-2003) and also attended clinical examination after 5-year follow-up (2006-2009), 142 developed incident T2D, 514 developed incident impaired fasting glucose (IFG), and 1,473 remained to be NFG. The current analysis included all incident cases of T2D (n=142), 146 incident IFG (randomly selected from 514 participants with incident IFG) and 144 NFG (randomly selected from 1,473 participants with NFG at both visits). Baseline plasma metabolites were detected by high-resolution LC/MS. The prospective association of each metabolite with risk for T2D or IFG was investigated using weighted Cox’s hazard regression with frailty model, adjusting for sex, study center, age, BMI, renal function, fasting glucose and fasting insulin at baseline. Multiple testing was corrected by Bonferroni correction (significance level 2.8х10-6). Results: Thirty-nine metabolites from several major fuel sources, including sugar amino acids, amino acids, lipids, alkaloids, alkylamines, carboxylic acids, steroids, and aromatic homomonocylic/heteropolycyclic compounds, significantly predicted future risk of T2D (10 metabolites), or IFG (27 metabolites), or both (2 metabolites). Of these, N1,N12-diacetylspermine and betanidin, respectively, were the strongest predictors for increased (HR=4.59, 95% CI, 2.55-8.24, P=3.49х10-7) and decreased risk of T2D (HR=0.38, 95% CI, 0.28-0.52, P=4.64х10-10). The corresponding strongest predictors for IFG were hexanoic acid (HR=2.34, 95% CI, 1.84-2.98, P=3.15х10-12) and l-palmitoylcarnitine (HR=0.26, 95% CI, 0.18-0.37, P=1.14х10-13), respectively. Two metabolites, betanidin and dopamine, significantly predicted future onset of both T2D (HR=0.38, 95% CI, 0.28,0.52, P=4.64х10-10 for betanidin; HR=2.48, 95% CI, 1.71-3.58, P=1.42х10-6 for dopamine) and IFG (HR=0.52, 95% CI, 0.43,0.62, P=1.35х10-12 for betanidin; HR=2.24, 95% CI, 1.73,2.89, P=5.79х10-10 for dopamine). Multiple unknown compounds were also independently associated with risk of T2D, IFG or both. Conclusions: This study identifies both novel and known metabolic alterations associated with risk of diabetes in American Indians, an ethnic group suffering from disproportionately high rates of T2D. The incomplete overlapping of metabolic profiles between T2D and IFG highlights differential metabolic states of diabetes development. Our results not only provide novel insights in disease pathogenesis but also valuable data on potential new targets for risk prediction and treatment.

Download Full-text

Abstract 16704: Leukocyte Telomere Length and Risk of Stroke: The Strong Heart Family Study

Circulation ◽

10.1161/circ.142.suppl_3.16704 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Caroline Goode ◽

Jinying Zhao ◽

Richard B Devereux ◽

Santosh Murthy ◽

Alexander E Merkler ◽

...

Keyword(s):

Diabetes Mellitus ◽

Risk Factors ◽

Atrial Fibrillation ◽

Telomere Length ◽

Family Study ◽

Leukocyte Telomere Length ◽

Potential Biomarker ◽

Primary Model ◽

Strong Heart Family Study

Introduction: Leukocyte telomere length (LTL) is a potential biomarker of aging and associated with several age-related diseases. Current research on an association between LTL and incident stroke has had inconclusive results. We hypothesized that LTL is associated with incident stroke among American Indians (AI) in the Strong Heart Family Study (SHFS). Methods: The SHFS is a population-based cohort study of cardiovascular disease (CVD) and its risk factors. Participants (n=2,769) recruited from regions in Arizona, Oklahoma and the Dakotas were assessed for LTL and CVD risk factors during a clinic visit between 2001 and 2003. Incident stroke events were identified through the end of 2018 (mean follow-up: 16.4 years). We assessed the association between LTL and incident stroke using frailty models based on the proportional hazards, accounting for family relatedness and established stroke risk factors that include sex, geographical location, education, smoking, atrial fibrillation, diabetes mellitus, and hypertension. Results: Among 2,769 participants, the mean age was 40.6±17.2 and 41.4% were male. During follow-up, there were 79 (2.9%) incident stroke cases. In the primary model, which adjusted for demographic variables (sex, location and education), the hazard ratios (HR) for stroke in participants in the first and second LTL quartiles were significantly higher than those in the highest (longest) LTL quartile, with HRs of 3.1 (95%CI: 1.4 - 6.6) and 3.5 (95%CI: 1.7 - 7.5), respectively. After adjusting for smoking, atrial fibrillation, diabetes mellitus, and hypertension, the association between LTL and stroke was attenuated, but remained significant when comparing the second shortest LTL quartile to the longest LTL quartile, HR: 2.3 (95% CI: 1.1 – 5.0). Conclusions: In summary, LTL was associated with incident stroke among SHFS participants. Those with shorter LTL have higher risk of stroke. Longer follow-up time may add more power to data analyses since the SHFS is relatively young, with an average baseline age of 40 years. If results are confirmed in other populations, LTL may serve as a biomarker identifying high risk individuals for the purpose of stroke prevention.

Download Full-text