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Type 2 diabetes and cognitive impairment: contributions from neuroimaging.

ABSTRACT: Type 2 diabetes mellitus (T2D) and Alzheimer disease (AD) are major public health burdens associated with aging. As the age of the population rapidly increases, a sheer increase in the incidence of these diseases is expected. Research has identified T2D as a risk factor for cognitive impairment and potentially AD, but the neurobiological pathways that are affected are only beginning to be understood. The rapid advances in neuroimaging in the past decade have added significant understanding to how T2D affects brain structure and function and possibly lead to AD. This article provides a review of studies that have utilized structural and functional neuroimaging to identify neural pathways that link T2D to impaired cognitive performance and potentially AD. A primary focus of this article is the potential for neuroimaging to assist in understanding the mechanistic pathways that may provide translational opportunities for clinical intervention.

SUBMITTER: Ryan JP

PROVIDER: S-EPMC4049175 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Type 2 diabetes and cognitive impairment: contributions from neuroimaging.

Ryan John P JP Fine David F DF Rosano Caterina C Rosano Caterina C

Journal of geriatric psychiatry and neurology 20140105 1

Type 2 diabetes mellitus (T2D) and Alzheimer disease (AD) are major public health burdens associated with aging. As the age of the population rapidly increases, a sheer increase in the incidence of these diseases is expected. Research has identified T2D as a risk factor for cognitive impairment and potentially AD, but the neurobiological pathways that are affected are only beginning to be understood. The rapid advances in neuroimaging in the past decade have added significant understanding to ho ...[more]

PMID: 24394151

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Project description:Studies have suggested that insulin resistance plays a role in cognitive impairment in individuals with type 2 diabetes. We aimed to determine whether an improvement in insulin resistance could explain cognitive performance variations over 36 weeks in older individuals with mild cognitive impairment (MCI) and type 2 diabetes.A total of 97 older individuals (mean +/- SD age 76 +/- 6 years) who had recently (<2 months) started an antidiabetes treatment of metformin (500 mg twice a day) (n = 30) or metformin (500 mg/day)+rosiglitazone (4 mg/day) (n = 32) or diet (n = 35) volunteered. The neuropsychological test battery consisted of the Mini-Mental State Examination (MMSE), Rey Verbal Auditory Learning Test (RAVLT) total recall, and Trail Making Tests (TMT-A and TMT-B) performed at baseline and every 12 weeks for 36 weeks along with clinical testing.At baseline, no significant differences were found between groups in clinical or neuropsychological parameters. Mean +/- SD values in the entire population were as follows: A1C 7.5 +/- 0.5%, fasting plasma glucose (FPG) 8.6 +/- 1.3 mmol/l, fasting plasma insulin (FPI) 148 +/- 74 pmol/l, MMSE 24.9 +/- 2.4, TMT-A 61.6 +/- 42.0, TMT-B 162.8 +/- 78.7, the difference between TMT-B and TMT-A [DIFFBA] 101.2 +/- 58.1, and RAVLT 24.3 +/- 2.1. At follow-up, ANOVA models tested changes in metabolic control parameters (FPI, FPG, and A1C). Such parameters improved in the metformin and metformin/rosiglitazone groups (P(trend) < 0.05 in both groups). ANCOVA repeated models showed that results for the metformin/rosiglitazone group remained stable for all neuropsychological tests, and results for the diet group remained stable for the MMSE and TMT-A and declined for the TMT-B (P(trend) = 0.024), executive efficiency (DIFFBA) (P(trend) = 0.026), and RAVLT memory test (P(trend) = 0.011). Results for the metformin group remained stable for the MMSE and TMTs but declined for the RAVLT (P(trend) = 0.011). With use of linear mixed-effects models, the interaction term, FPI x time, correlated with cognitive stability on the RAVLT in the metformin/rosiglitazone group (beta = -1.899; P = 0.009).Rosiglitazone may protect against cognitive decline in older individuals with type 2 diabetes and MCI.

Project description:OBJECTIVE:To identify a neuroimaging signature predictive of brain amyloidosis as a screening tool to identify individuals with mild cognitive impairment (MCI) that are most likely to have high levels of brain amyloidosis or to be amyloid-free. METHODS:The prediction model cohort included 62 MCI subjects screened with structural magnetic resonance imaging (MRI) and (11) C-labeled Pittsburgh compound B positron emission tomography (PET). We identified an anatomical shape variation-based neuroimaging predictor of brain amyloidosis and defined a structural MRI-based brain amyloidosis score (sMRI-BAS). Amyloid beta positivity (A?(+) ) predictive power of sMRI-BAS was validated on an independent cohort of 153 MCI patients with cerebrospinal fluid A?1-42 biomarker data but no amyloid PET scans. We compared the A?(+) predictive power of sMRI-BAS to those of apolipoprotein E (ApoE) genotype and hippocampal volume, the 2 most relevant candidate biomarkers for the prediction of brain amyloidosis. RESULTS:Anatomical shape variations predictive of brain amyloidosis in MCI embraced a characteristic spatial pattern known for high vulnerability to Alzheimer disease pathology, including the medial temporal lobe, temporal-parietal association cortices, posterior cingulate, precuneus, hippocampus, amygdala, caudate, and fornix/stria terminals. A?(+) prediction performance of sMRI-BAS and ApoE genotype jointly was significantly better than the performance of each predictor separately (area under the curve [AUC] = 0.88 vs AUC = 0.70 and AUC = 0.81, respectively) with >90% sensitivity and specificity at 20% false-positive rate and false-negative rate thresholds. Performance of hippocampal volume as an independent predictor of brain amyloidosis in MCI was only marginally better than random chance (AUC = 0.56). INTERPRETATION:As one of the first attempts to use an imaging technique that does not require amyloid-specific radioligands for identification of individuals with brain amyloidosis, our findings could lead to development of multidisciplinary/multimodality brain amyloidosis biomarkers that are reliable, minimally invasive, and widely available.

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Type 2 diabetes and cognitive impairment: contributions from neuroimaging.

Publications

Type 2 diabetes and cognitive impairment: contributions from neuroimaging.

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