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Advanced BrainAGE in older adults with type 2 diabetes mellitus
Katja Franke1, Christian Gaser1, Brad Manor2
1Structural Brain Mapping Group, Department of Psychiatry, Jena University Hospital Jena, Germany ; Department of Neurology, Jena University Hospital Jena, Germany.
Abstract:
Aging alters brain structure and function and diabetes mellitus (DM) may accelerate this process. This study investigated the effects of type 2 DM on individual brain aging as well as the relationships between individual brain aging, risk factors, and functional measures. To differentiate a pattern of brain atrophy that deviates from normal brain aging, we used the novel BrainAGE approach, which determines the complex multidimensional aging pattern within the whole brain by applying established kernel regression methods to anatomical brain magnetic resonance images (MRI). The "Brain Age Gap Estimation" (BrainAGE) score was then calculated as the difference between chronological age and estimated brain age. 185 subjects (98 with type 2 DM) completed an MRI at 3Tesla, laboratory and clinical assessments. Twenty-five subjects (12 with type 2 DM) also completed a follow-up visit after 3.8 ± 1.5 years. The estimated brain age of DM subjects was 4.6 ± 7.2 years greater than their chronological age (p = 0.0001), whereas within the control group, estimated brain age was similar to chronological age. As compared to baseline, the average BrainAGE scores of DM subjects increased by 0.2 years per follow-up year (p = 0.034), whereas the BrainAGE scores of controls did not change between baseline and follow-up. At baseline, across all subjects, higher BrainAGE scores were associated with greater smoking and alcohol consumption, higher tumor necrosis factor alpha (TNFα) levels, lower verbal fluency scores and more severe deprepession. Within the DM group, higher BrainAGE scores were associated with longer diabetes duration (r = 0.31, p = 0.019) and increased fasting blood glucose levels (r = 0.34, p = 0.025). In conclusion, type 2 DM is independently associated with structural changes in the brain that reflect advanced aging. The BrainAGE approach may thus serve as a clinically relevant biomarker for the detection of abnormal patterns of brain aging associated with type 2 DM.
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