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      Type 2 diabetes mellitus and biomarkers of neurodegeneration

      research-article
      , MBBCh, , PhD, , PhD, , MD, , PhD, , PhD
      , MB BCh (Collab), , PhD (Collab), , PhD (Collab), , MD (Collab), , PhD (Collab), , PhD (Collab)
      Neurology
      Lippincott Williams & Wilkins

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          Abstract

          Objective:

          Our objective was to investigate whether type 2 diabetes mellitus (T2DM) influences neurodegeneration in a manner similar to Alzheimer disease (AD), by promoting brain β-amyloid (Aβ) or tau.

          Methods:

          We studied the cross-sectional associations of T2DM with cortical thickness, brain Aβ load, and CSF levels of Aβ and tau in a sample of people from the Alzheimer's Disease Neuroimaging Initiative with diagnoses of AD dementia, mild cognitive impairment, and normal cognition. All (n = 816) received MRI, and a subsample underwent brain amyloid imaging (n = 102) and CSF Aβ and tau measurements (n = 415). Analyses were performed across and within cognitive diagnostic strata.

          Results:

          There were 124 people with T2DM (mean age 75.5 years) and 692 without T2DM (mean age 74.1 years). After adjusting for age, sex, total intracranial volume, APO ε4 status, and cognitive diagnosis, T2DM was associated with lower bilateral frontal and parietal cortical thickness (mL) (β = −0.03, p = 0.01). T2DM was not associated with 11C Pittsburgh compound B standardized uptake value ratio (AU) in any brain region or with CSF Aβ 42 levels (pg/mL). T2DM was associated with greater CSF total tau (pg/mL) (β = 16.06, p = 0.04) and phosphorylated tau (β = 5.84, p = 0.02). The association between T2DM and cortical thickness was attenuated by 15% by the inclusion of phosphorylated tau.

          Conclusions:

          T2DM may promote neurodegeneration independent of AD dementia diagnosis, and its effect may be driven by tau phosphorylation. The mechanisms through which T2DM may promote tau phosphorylation deserve further study.

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          Most cited references19

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          Dementia and cognitive decline in type 2 diabetes and prediabetic stages: towards targeted interventions.

          Type 2 diabetes is associated with dementia, and also with more slight cognitive decrements. In this Review we discuss trajectories from normal cognition to dementia in people with type 2 diabetes, and explore opportunities for treatment. Slight diabetes-associated cognitive decrements and dementia affect different age groups and show a different evolution. These cognitive entities should therefore not be regarded as a continuum, although their effects might be additive. Vascular damage is a key underlying process in both entities. Glucose-mediated processes and other metabolic disturbances might also have a role. No treatment has been established, but management of vascular risk factors and optimisation of glycaemic control could have therapeutic benefit. We identify possible opportunities for intervention to improve cognitive outcomes in people with type 2 diabetes, and suggest how treatment can be tailored to individual risk profiles and comorbidities. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core.

            This is a progress report of the Alzheimer's Disease Neuroimaging Initiative (ADNI) positron emission tomography (PET) Core. The Core has supervised the acquisition, quality control, and analysis of longitudinal [(18)F]fluorodeoxyglucose PET (FDG-PET) data in approximately half of the ADNI cohort. In an "add on" study, approximately 100 subjects also underwent scanning with [(11)C] Pittsburgh compound B PET for amyloid imaging. The Core developed quality control procedures and standardized image acquisition by developing an imaging protocol that has been widely adopted in academic and pharmaceutical industry studies. Data processing provides users with scans that have identical orientation and resolution characteristics despite acquisition on multiple scanner models. The Core labs have used many different approaches to characterize differences between subject groups (Alzheimer's disease, mild cognitive impairment, controls), to examine longitudinal change over time in glucose metabolism and amyloid deposition, and to assess the use of FDG-PET as a potential outcome measure in clinical trials. ADNI data indicate that FDG-PET increases statistical power over traditional cognitive measures, might aid subject selection, and could substantially reduce the sample size in a clinical trial. Pittsburgh compound B PET data showed expected group differences, and identified subjects with significant annual increases in amyloid load across the subject groups. The next activities of the PET core in ADNI will entail developing standardized protocols for amyloid imaging using the [(18)F]-labeled amyloid imaging agent AV45, which can be delivered to virtually all ADNI sites. ADNI has demonstrated the feasibility and utility of multicenter PET studies and is helping to clarify the role of biomarkers in the study of aging and dementia. Copyright 2010 The Alzheimer
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              Diabetes, Alzheimer disease, and vascular dementia: a population-based neuropathologic study.

              To investigate the relation of diabetes to dementia, Alzheimer disease (AD), and vascular dementia (VaD), through analyses of incidence, mortality, and neuropathologic outcomes in a prospective population-based study of the oldest old. The Vantaa 85+ study included 553 residents living in the city of Vantaa, Finland, and aged ≥85 years on April 1, 1991. Survivors were reexamined in 1994, 1996, 1999, and 2001. Autopsies were performed in 291 persons who died during the follow-up (48% of total population). Diabetes was assessed according to self-report, medical record of physician-diagnosed diabetes, or use of antidiabetic medication. Macroscopic infarcts were identified from 1-cm coronal slices of cerebral hemispheres, 5-mm transverse brainstem slices, and sagittal cerebellum slices. Methenamine silver staining was used for β-amyloid, methenamine silver-Bodian staining for neurofibrillary tangles, and modified Bielschowsky method for neuritic plaques. Cox proportional hazards and multiple logistic regression models were used to analyze the association of diabetes with dementia and neuropathology, respectively. Diabetes at baseline doubled the incidence of dementia, AD, and VaD, and increased mortality. Individuals with diabetes were less likely to have β-amyloid (hazard ratio [HR] [95% confidence interval (CI)] was 0.48 [0.23-0.98]) and tangles (HR [95% CI] 0.72 [0.39-1.33]) but more likely to have cerebral infarcts (HR [95% CI] 1.88 [1.06-3.34]) after all adjustments. Elderly patients with diabetes develop more extensive vascular pathology, which alone or together with AD-type pathology (particularly in APOE ε4 carriers) results in increased dementia risk.
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                Author and article information

                Contributors
                Journal
                Neurology
                Neurology
                neurology
                neur
                neurology
                NEUROLOGY
                Neurology
                Lippincott Williams & Wilkins (Hagerstown, MD )
                0028-3878
                1526-632X
                29 September 2015
                29 September 2015
                : 85
                : 13
                : 1123-1130
                Affiliations
                From the Stroke and Ageing Research Group (C.M., T.G.P., V.S.), Vascular Brain Ageing Division, Department of Medicine, School of Clinical Sciences, Monash University, Melbourne; Neurosciences (C.M., T.G.P., V.S.), Monash Medical Centre, Monash Health, Melbourne; Caulfield General Medical Centre (C.M.), Alfred Health, Melbourne; Developmental Imaging (R.B.), Murdoch Children's Research Institute, Melbourne; School of Medicine and Pharmacology (D.G.B.), Fremantle Hospital, University of Western Australia; and Menzies Research Institute Tasmania (M.L.C., V.S.), University of Tasmania, Hobart, Australia.
                Author notes
                Correspondence to Dr. Srikanth: velandai.srikanth@ 123456monash.edu

                Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI investigators contributed to the design and implementation of ADNI and/or provided data. The ADNI list is available on the Neurology® Web site at Neurology.org.

                Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.

                Article
                PMC5573049 PMC5573049 5573049 NEUROLOGY2015657221
                10.1212/WNL.0000000000001982
                5573049
                26333802
                2ed71134-aa6a-4bb7-8f42-5b9a45a1e1ef
                © 2015 American Academy of Neurology
                History
                : 26 March 2015
                : 03 June 2015
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