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American Indians (AI) experience high rates of both liver disease and type 2 diabetes (T2D), yet few studies have investigated the contributions of T2D and other known risk factors to liver disease in AI. We used magnetic resonance imaging (MRI)-estimated proton density fat fraction (PDFF) and MR elastography (MRE)-estimated stiffness to assess hepatic fat and fibrosis, respectively, and assessed whether obesity, T2D, and heavy episodic alcohol (ETOH) consumption are associated with these liver measures in AI. The Strong Heart Family Study (SHFS) is a population-based family study of AI recruited from 12 communities located within Arizona (AZ), the Dakotas, and Oklahoma (OK). Metabolic measures were assessed during a clinic visit in 2006-2009. A re-exam including MRI and MRE has been conducted on 109 participants to date from AZ and OK (mean age 50.6 ± 11.3 years, 72% women, 71% obese (BMI ≥ 30 kg/m2), 57% had T2D, and 28% reported ETOH consumption). Median liver PDFF was 8.9% (1rst and 3rd quartiles: 4.3%, 14.6%), with 71% of participants having elevated liver fat (PDFF ≥ 5%). Median liver stiffness was 2.6 kPa, with 23% showing mild liver fibrosis (stiffness 2.8 - 3.63 kPa) and 8.3% advanced liver fibrosis (stiffness > 3.63 kPa). In cross-sectional analyses, liver PDFF was significantly higher in obese vs. non-obese participants (Wilcoxon rank sum test, p Disclosure S.A. Cole: None. W.C. Henderson: None. T. Ali: None. C. West: None. M.S. Middleton: Consultant; Self; Kowa Pharmaceutical Europe Co. Ltd., Median, Novo Nordisk Inc. Stock/Shareholder; Self; General Electric, Pfizer Inc. A. Silva: None. D.N. Batakis: None. A.L. Louie: None. B.V. Howard: None. J.D. Dvorak: None. R. Devereux: Consultant; Self; Acer. J.G. Umans: None. C. Sirlin: Advisory Panel; Self; AMRA Medical, Bristol-Myers Squibb Company, VirtualScopics. Consultant; Self; Fulcrum Therapeutics. Other Relationship; Self; Celgene Corporation, Enanta Pharmaceuticals, Inc., Genzyme, Gilead Sciences, Inc., Gilead Sciences, Inc., ICON plc., Intercept Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., NuSirt Biopharma, Inc., Shire, Synageva, Takeda Pharmaceutical Company Limited, VirtualScopics. Y. Zhang: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK110096)

Telomeres play a central role in cellular aging, and shorter telomere length has been associated with age-related disorders including diabetes. However, a causal link between telomere shortening and diabetes risk has not been established. In a well-characterized longitudinal cohort of American Indians participating in the Strong Heart Family Study, we examined whether leukocyte telomere length (LTL) at baseline predicts incident diabetes independent of known diabetes risk factors. Among 2,328 participants free of diabetes at baseline, 292 subjects developed diabetes during an average 5.5 years of follow-up. Compared with subjects in the highest quartile (longest) of LTL, those in the lowest quartile (shortest) had an almost twofold increased risk of incident diabetes (hazard ratio [HR] 1.83 [95% CI 1.26–2.66]), whereas the risk for those in the second (HR 0.87 [95% CI 0.59–1.29]) and the third (HR 0.95 [95% CI 0.65–1.38]) quartiles was statistically nonsignificant. These findings suggest a nonlinear association between LTL and incident diabetes and indicate that LTL could serve as a predictive marker for diabetes development in American Indians, who suffer from disproportionately high rates of diabetes.

Genetic variants in SLC16A11 were recently reported to be associated with type 2 diabetes in Mexican and other Latin American populations. The diabetes risk haplotype had a frequency of 50% in Native Americans from Mexico but was rare in Europeans and Africans. In the current study, we analyzed SLC16A11 in 12,811 North American Indians and found that the diabetes risk haplotype, tagged by the rs75493593 A allele, was nominally associated with type 2 diabetes (P = 0.001, odds ratio 1.11). However, there was a strong interaction with BMI (P = 5.1 × 10−7) such that the diabetes association was stronger in leaner individuals. rs75493593 was also strongly associated with BMI in individuals with type 2 diabetes (P = 3.4 × 10−15) but not in individuals without diabetes (P = 0.77). Longitudinal analyses suggest that this is due, in part, to an association of the A allele with greater weight loss following diabetes onset (P = 0.02). Analyses of global gene expression data from adipose tissue, skeletal muscle, and whole blood provide evidence that rs75493593 is associated with expression of the nearby RNASEK gene, suggesting that RNASEK expression may mediate the effect of genotype on diabetes.

To localize quantitative trait loci for insulin metabolism and obesity, genome scans/linkage analyses were performed on >900 members of 32 extended families participating in phase 3 of the Strong Heart Study, an investigation of the genetic and environmental determinants of cardiovascular disease in American-Indian populations from Arizona, Oklahoma, and North and South Dakota. Linkage analyses of fasting insulin and two obesity-related phenotypes, BMI and percent fat mass, were performed independently in each of the three populations. For log fasting insulin, we found a genome-wide maximum, robust logarithm of odds (LOD) score of 3.42 at 51 cM on chromosome 2p in the Dakotas. Bivariate linkage analyses of log fasting insulin with both BMI and fat mass indicate a situation of incomplete pleiotropy, as well as several significant bivariate LOD scores in the Dakotas.

Type 2 diabetes is a complex disease that arises from physiological disruptions of the body’s sensitivity to insulin and ability to metabolize glucose. Multipoint linkage analyses for insulin sensitivity phenotypes were conducted in 1,280 Mexican Americans from 41 families who participated in the San Antonio Family Heart Study. A significant linkage signal (logarithm of odds [LOD] = 2.98) affecting corrected insulin response to glucose was detected on chromosome 13q between D13787 and D13S252, in the region where the MODY-4 gene has previously been mapped. Another signal on chromosome 13 was observed at D13S285 (LOD = 1.86), where the insulin receptor substrate 2 gene resides. Significant linkage (LOD = 3.09) for insulin response to glucose was found on chromosome 8 between D8S1130 and D8S1106, near the lipoprotein lipase and macrophage scavenger receptor genes. Multipoint analysis of abdominal skinfold with an LOD of 2.68 showed signals in the same region. There was also suggestive evidence for linkage of quantitative insulin sensitivity check index and fasting glucose to a previously reported location at D9S301 (LOD = 2.19). These results indicate that chromosomal locations on 8p and 13q might harbor genes that affect a variety of insulin- and glucose-related phenotypes that contribute to the observed variations in these important risk factors for diabetes in Mexican Americans.

OBJECTIVE Genome-wide association studies that compare the statistical association between thousands of DNA variations and a human trait have detected 958 loci across 127 different diseases and traits. However, these statistical associations only provide evidence for genomic regions likely to harbor a causal gene(s) and do not directly identify such genes. We combined gene variation and expression data in a human cohort to identify causal genes. RESEARCH DESIGN AND METHODS Global gene transcription activity was obtained for each individual in a large human cohort (n = 1,240). These quantitative transcript data were tested for correlation with genotype data generated from the same individuals to identify gene expression patterns influenced by the variants. RESULTS Variant rs8050136 lies within intron 1 of the FTO gene on chromosome 16 and marks a locus strongly associated with type 2 diabetes and obesity and widely replicated across many populations. We report that genetic variation at this locus does not influence FTO gene expression levels (P = 0.38), but is strongly correlated with expression of RBL2 (P = 2.7 × 10−5), ∼270,000 base pairs distant to FTO. CONCLUSIONS These data suggest that variants at FTO influence RBL2 gene expression at large genetic distances. This observation underscores the complexity of human transcriptional regulation and highlights the utility of large human cohorts in which both genetic variation and global gene expression data are available to identify disease genes. Expedient identification of genes mediating the effects of genome-wide association study–identified loci will enable mechanism-of-action studies and accelerate understanding of human disease processes under genetic influence.

To localize quantitative trait loci for insulin metabolism and obesity, genome scans/linkage analyses were performed on900 members of 32 extended families participating in phase 3 of the Strong Heart Study, an investigation of the genetic and environmental determinants of cardiovascular disease in American-Indian populations from Arizona, Oklahoma, and North and South Dakota. Linkage analyses of fasting insulin and two obesity-related phenotypes, BMI and percent fat mass, were performed independently in each of the three populations. For log fasting insulin, we found a genome-wide maximum, robust logarithm of odds (LOD) score of 3.42 at 51 cM on chromosome 2p in the Dakotas. Bivariate linkage analyses of log fasting insulin with both BMI and fat mass indicate a situation of incomplete pleiotropy, as well as several significant bivariate LOD scores in the Dakotas.

Type 2 diabetes is a complex disease that arises from physiological disruptions of the body's sensitivity to insulin and ability to metabolize glucose. Multipoint linkage analyses for insulin sensitivity phenotypes were conducted in 1,280 Mexican Americans from 41 families who participated in the San Antonio Family Heart Study. A significant linkage signal (logarithm of odds [LOD] = 2.98) affecting corrected insulin response to glucose was detected on chromosome 13q between D13787 and D13S252, in the region where the MODY-4 gene has previously been mapped. Another signal on chromosome 13 was observed at D13S285 (LOD = 1.86), where the insulin receptor substrate 2 gene resides. Significant linkage (LOD = 3.09) for insulin response to glucose was found on chromosome 8 between D8S1130 and D8S1106, near the lipoprotein lipase and macrophage scavenger receptor genes. Multipoint analysis of abdominal skinfold with an LOD of 2.68 showed signals in the same region. There was also suggestive evidence for linkage of quantitative insulin sensitivity check index and fasting glucose to a previously reported location at D9S301 (LOD = 2.19). These results indicate that chromosomal locations on 8p and 13q might harbor genes that affect a variety of insulin- and glucose-related phenotypes that contribute to the observed variations in these important risk factors for diabetes in Mexican Americans.

Hyperinsulinemia predicts the development of type 2 diabetes, and family studies suggest that insulin levels are regulated in part by genes. We conducted a genome-wide scan to detect genes influencing variation in fasting serum insulin concentrations in 391 nondiabetic individuals from 10 large multigenerational families. Approximately 380 microsatellite markers with an average spacing of 10 cM were genotyped in all study subjects. Insulin concentrations measured by radioimmunoassay were transformed by their natural logarithms before analysis. In multipoint analysis, peak evidence for linkage occurred on chromosome 3p approximately 109 cM from pter in the region of 3p14.2-p14.1. The multipoint logarithm of odds (LOD) score was 3.07, occurring in the region flanked by markers D3S1600 and D3S1285 (P value by simulation

The beta-3 adrenergic receptor (ADRB3) has been implicated as a regulator of energy expenditure, and a polymorphism in codon 64 of this gene (Trp64Arg) has been associated in some studies with obesity and insulin resistance. However, many studies have failed to detect an effect of this variant, and the importance of the Trp64Arg variant in human obesity remains controversial. We performed a quantitative linkage analysis of the ADRB3 and obesity, using 12 markers (including the intragenic Trp64Arg polymorphism) spanning a 57-cM region of chromosome 8. The study population consisted of 470 individuals from 10 large multigenerational families of Mexican-American ancestry residing in San Antonio, TX. In two-point analysis, logarithm of odds (LOD) scores >1.0 were observed for six markers surrounding ADRB3 in a 33-cM region spanned by markers D8S1477 and D8S1136. The multipoint LOD score was 3.21, occurring between markers D8S1121 and ADRB3, approximately 2-3 cM from ADRB3. Adjusting for the presence of the Arg64 allele or excluding from the analysis the 11 individuals homozygous for the Arg64 allele did not reduce the evidence for linkage. A genome scan was conducted at 10 cM map density to detect other loci influencing variation in BMI. Multipoint LOD scores >1.0 were observed in four other regions, including two on chromosome 17, one on chromosome 6q, and one on chromosome 2p. These data suggest that the ADRB3 should continue to be regarded as a strong candidate gene for obesity even though evidence for an effect of the Trp64Arg polymorphism could not be established. It is also possible that a gene closely linked to ADRB3 may influence susceptibility to obesity.