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Raffield L.M.,Molecular Genetics and Genomics Program | Raffield L.M.,Center for Human Genomics | Raffield L.M.,Center for Diabetes Research | Cox A.J.,Griffith University | And 5 more authors.
Acta Diabetologica | Year: 2015

Aims: To examine the relationships between type 2 diabetes (T2D) status, glycemic control, and T2D duration with magnetic resonance imaging (MRI)-derived neuroimaging measures in European Americans from the Diabetes Heart Study (DHS) Mind cohort. Methods: Relationships were examined using marginal models with generalized estimating equations in 784 participants from 514 DHS Mind families. Fasting plasma glucose, glycated hemoglobin, and diabetes duration were analyzed in 682 participants with T2D. Models were adjusted for potential confounders, including age, sex, history of cardiovascular disease, smoking, educational attainment, and use of statins or blood pressure medications. Association was tested with gray and white matter volume, white matter lesion volume, gray matter cerebral blood flow, and white and gray matter fractional anisotropy and mean diffusivity. Results: Adjusting for multiple comparisons, T2D status was associated with reduced white matter volume (p = 2.48 × 10−6) and reduced gray and white matter fractional anisotropy (p ≤ 0.001) in fully adjusted models, with a trend toward increased white matter lesion volume (p = 0.008) and increased gray and white matter mean diffusivity (p ≤ 0.031). Among T2D-affected participants, neither fasting glucose, glycated hemoglobin, nor diabetes duration were associated with the neuroimaging measures assessed (p > 0.05). Conclusions: While T2D was significantly associated with MRI-derived neuroimaging measures, differences in glycemic control in T2D-affected individuals in the DHS Mind study do not appear to significantly contribute to variation in these measures. This supports the idea that the presence or absence of T2D, not fine gradations of glycemic control, may be more significantly associated with age-related changes in the brain. © 2015 Springer-Verlag Italia Source


Raffield L.M.,Molecular Genetics and Genomics Program | Raffield L.M.,Center for Human Genomics | Raffield L.M.,Center for Diabetes Research | Cox A.J.,Center for Human Genomics | And 7 more authors.
Acta Diabetologica | Year: 2015

Aims: It remains unclear whether the high cardiovascular disease (CVD) burden in people with type 2 diabetes (T2D) is associated with genetic variants that contribute to CVD in general populations. Recent studies have examined genetic risk scores of single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies for their cumulative contribution to CVD-related traits. Most analyses combined SNPs associated with a single phenotypic class, e.g., lipids. In the present analysis, we examined a more comprehensive risk score comprised of SNPs associated with a broad range of CVD risk phenotypes. Methods: The composite risk score was analyzed for potential associations with subclinical CVD, self-reported CVD events, and mortality in 983 T2D-affected individuals of European descent from 466 Diabetes Heart Study (DHS) families. Genetic association was examined using marginal models with generalized estimating equations for subclinical CVD and prior CVD events and Cox proportional hazards models with sandwich-based variance estimation for mortality; analyses were adjusted for age and sex. Results: An increase in genetic risk score was significantly associated with higher levels of coronary artery calcified plaque (p = 1.23 × 10−4); however, no significant associations with self-reported myocardial infarction and CVD events and all-cause and CVD mortality were observed. Conclusions: These results suggest that a genetic risk score of SNPs associated with CVD events and risk factors does not significantly account for CVD risk in the DHS, highlighting the limitations of applying current genetic markers for CVD in individuals with diabetes. © 2015, Springer-Verlag Italia. Source


Raffield L.M.,Molecular Genetics and Genomics Program | Raffield L.M.,Center for Human Genomics | Raffield L.M.,Center for Diabetes Research | Cox A.J.,Center for Human Genomics | And 7 more authors.
Journal of Diabetes and its Complications | Year: 2016

Aims Anxiety, depression, accelerated cognitive decline, and increased risk of dementia are observed in individuals with type 2 diabetes. Anxiety and depression may contribute to lower performance on cognitive tests and differences in neuroimaging observed in individuals with type 2 diabetes. Methods These relationships were assessed in 655 European Americans with type 2 diabetes from 504 Diabetes Heart Study families. Participants completed cognitive testing, brain magnetic resonance imaging, the Brief Symptom Inventory Anxiety subscale, and the Center for Epidemiologic Studies Depression-10. Results In analyses adjusted for age, sex, educational attainment, and use of psychotropic medications, individuals with comorbid anxiety and depression symptoms had lower performance on all cognitive testing measures assessed (p ≤ 0.005). Those with both anxiety and depression also had increased white matter lesion volume (p = 0.015), decreased gray matter cerebral blood flow (p = 4.43 10- 6), decreased gray matter volume (p = 0.002), increased white and gray matter mean diffusivity (p ≤ 0.001), and decreased white matter fractional anisotropy (p = 7.79 × 10- 4). These associations were somewhat attenuated upon further adjustment for health status related covariates. Conclusions Comorbid anxiety and depression symptoms were associated with cognitive performance and brain structure in a European American cohort with type 2 diabetes. © 2016 Elsevier Inc. All rights reserved. Source


Raffield L.M.,Molecular Genetics and Genomics Program | Raffield L.M.,Center for Genomics and Personalized Medicine Research | Raffield L.M.,Center for Diabetes Research | Cox A.J.,Center for Genomics and Personalized Medicine Research | And 3 more authors.
Neurobiology of Aging | Year: 2015

Patients with type 2 diabetes are at increased risk of age-related cognitive decline and dementia. Neuroimaging measures such as white matter lesion volume, brain volume, and fractional anisotropy may reflect the pathogenesis of these cognitive declines, and genetic factors may contribute to variability in these measures. This study examined multiple neuroimaging measures in 465 participants from 238 families with extensive genotype data in the type 2 diabetes enriched Diabetes Heart Study-Mind cohort. Heritability of these phenotypes and their association with candidate single-nucleotide polymorphisms (SNPs), and SNP data from genome- and exome-wide arrays were explored. All neuroimaging measures analyzed were significantly heritable (ĥ2= 0.55-0.99 in unadjusted models). Seventeen candidate SNPs (from 16 genes/regions) associated with neuroimaging phenotypes in prior studies showed no significant evidence of association. A missense variant (rs150706952, A432V) in PLEKHG4B from the exome-wide array was significantly associated with white matter mean diffusivity (p= 3.66× 10-7) and gray matter mean diffusivity (p= 2.14× 10-7). This analysis suggests genetic factors contribute to variation in neuroimaging measures in a population enriched for metabolic disease and other associated comorbidities. © 2015 Elsevier Inc. Source


Hellwege J.N.,Molecular Genetics and Genomics Program | Hellwege J.N.,Center for Genomics and Personalized Medicine Research | Hellwege J.N.,Center for Diabetes Research | Palmer N.D.,Center for Genomics and Personalized Medicine Research | And 6 more authors.
Gene | Year: 2014

Context: Insulin resistance is not fully explained on a molecular level, though several genes and proteins have been tied to this defect. Knockdowns of the SEPP1 gene, which encodes the selenoprotein P (SeP) protein, have been shown to increase insulin sensitivity in mice. SeP is a liver-derived plasma protein and a major supplier of selenium, which is a proposed insulin mimetic and antidiabetic agent. Objective: SEPP1 single nucleotide polymorphisms (SNPs) were selected for analysis with glucometabolic measures. Participants and measures: The study included1424 Hispanics from families in the Insulin Resistance Atherosclerosis Family Study (IRASFS). Additionally, the multi-ethnic Insulin Resistance Atherosclerosis Study was used. A frequently sampled intravenous glucose tolerance test was used to obtain precise measures of acute insulin response (AIR) and the insulin sensitivity index (SI). Design: 21 SEPP1 SNPs (tagging SNPs (n. = 12) from HapMap, 4 coding variants and 6 SNPs in the promoter region) were genotyped and analyzed for association. Results: Two highly correlated (r2=1) SNPs showed association with AIR (rs28919926; Cys368Arg; p=0.0028 and rs146125471; Ile293Met; p=0.0026) while rs16872779 (intronic) was associated with fasting insulin levels (p=0.0097). In the smaller IRAS Hispanic cohort, few of the associations seen in the IRASFS were replicated, but meta-analysis of IRASFS and all 3 IRAS cohorts (N=2446) supported association of rs28919926 and rs146125471 with AIR (p=0.013 and 0.0047, respectively) as well as rs7579 with SI (p=0.047). Conclusions: Overall, these results in a human sample are consistent with the literature suggesting a role for SEPP1 in insulin resistance. © 2013 Elsevier B.V. Source

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