Laura M Raffield1,2,3, Amanda J Cox4, Barry I Freedman5, Christina E Hugenschmidt6, Fang-Chi Hsu7, Benjamin C Wagner8, Jianzhao Xu2,3, Joseph A Maldjian8, Donald W Bowden9,10,11,12. 1. Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, USA. 2. Center for Human Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA. 3. Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA. 4. Molecular Basis of Disease, Griffith University, Southport, QLD, Australia. 5. Department of Internal Medicine-Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA. 6. Department of Gerontology and Geriatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA. 7. Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA. 8. Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA. 9. Center for Human Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA. dbowden@wakehealth.edu. 10. Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA. dbowden@wakehealth.edu. 11. Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA. dbowden@wakehealth.edu. 12. Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA. dbowden@wakehealth.edu.
Abstract
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.
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.
Entities:
Keywords:
Diabetes Heart Study; Glycemic control; Magnetic resonance imaging; Type 2 diabetes
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