Brain atrophy in type 2 diabetes: regional distribution and influence on cognition.
TL;DR: T2DM was associated with poorer visuospatial construction, planning, visual memory, and speed independent of age, sex, education, and vascular risk factors and the strength of these associations was attenuated when adjusted for hippocampal and total gray volumes but was unchanged by adjustment for cerebrovascular lesions or white matter volume.
Abstract: OBJECTIVE Type 2 diabetes (T2DM) is associated with brain atrophy and cerebrovascular disease. We aimed to define the regional distribution of brain atrophy in T2DM and to examine whether atrophy or cerebrovascular lesions are feasible links between T2DM and cognitive function. RESEARCH DESIGN AND METHODS This cross-sectional study used magnetic resonance imaging (MRI) scans and cognitive tests in 350 participants with T2DM and 363 participants without T2DM. With voxel-based morphometry, we studied the regional distribution of atrophy in T2DM. We measured cerebrovascular lesions (infarcts, microbleeds, and white matter hyperintensity [WMH] volume) and atrophy (gray matter, white matter, and hippocampal volumes) while blinded to T2DM status. With use of multivariable regression, we examined for mediation or effect modification of the association between T2DM and cognitive measures by MRI measures. RESULTS T2DM was associated with more cerebral infarcts and lower total gray, white, and hippocampal volumes (all P P ≤ 0.05) independent of age, sex, education, and vascular risk factors. The strength of these associations was attenuated by almost one-half when adjusted for hippocampal and total gray volumes but was unchanged by adjustment for cerebrovascular lesions or white matter volume. CONCLUSIONS Cortical atrophy in T2DM resembles patterns seen in preclinical Alzheimer disease. Neurodegeneration rather than cerebrovascular lesions may play a key role in T2DM-related cognitive impairment.
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TL;DR: Intervention studies which suggest that the restoration of insulin activity in the hippocampus may be an effective strategy to alleviate the cognitive decline associated with T2DM and AD are discussed.
Abstract: Clinical studies suggest a link between type 2 diabetes mellitus (T2DM) and insulin resistance (IR) and cognitive dysfunction, but there are significant gaps in our knowledge of the mechanisms underlying this relationship. Animal models of IR help to bridge these gaps and point to hippocampal IR as a potential mediator of cognitive dysfunction in T2DM, as well as in Alzheimer disease (AD). This Review highlights these observations and discusses intervention studies which suggest that the restoration of insulin activity in the hippocampus may be an effective strategy to alleviate the cognitive decline associated with T2DM and AD.
392 citations
TL;DR: A literature search was conducted to identify molecular commonalities between obesity, diabetes, and AD and found the chronic inflammatory response and oxidative stress associated with T2DM, amyloid-β (Aβ) protein accumulation, and mitochondrial dysfunction link T2 DM and AD.
Abstract: Type 2 diabetes (T2DM), Alzheimer's disease (AD), and insulin resistance are age-related conditions and increased prevalence is of public concern. Recent research has provided evidence that insulin resistance and impaired insulin signalling may be a contributory factor to the progression of diabetes, dementia, and other neurological disorders. Alzheimer's disease (AD) is the most common subtype of dementia. Reduced release (for T2DM) and decreased action of insulin are central to the development and progression of both T2DM and AD. A literature search was conducted to identify molecular commonalities between obesity, diabetes, and AD. Insulin resistance affects many tissues and organs, either through impaired insulin signalling or through aberrant changes in both glucose and lipid (cholesterol and triacylglycerol) metabolism and concentrations in the blood. Although epidemiological and biological evidence has highlighted an increased incidence of cognitive decline and AD in patients with T2DM, the common molecular basis of cell and tissue dysfunction is rapidly gaining recognition. As a cause or consequence, the chronic inflammatory response and oxidative stress associated with T2DM, amyloid-β (Aβ) protein accumulation, and mitochondrial dysfunction link T2DM and AD.
356 citations
Cites background from "Brain atrophy in type 2 diabetes: r..."
...Moreover, crosssectional and longitudinal studies have indicated that global brain atrophy is strongly associated with T2DM and the rate of atrophy is greater than that seen in normal ageing [6, 7]....
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TL;DR: It is proposed that fluoxetine, a selective serotonin reuptake inhibitor, has the potential to treat AD and the combination of hypometabolism and autophagy deficiency is likely to be a causative factor for AD.
Abstract: Alzheimer’s disease (AD) is a neurodegenerative disease characterized by progressive memory loss along with neuropsychiatric symptoms and a decline in activities of daily life. Its main pathological features are cerebral atrophy, amyloid plaques, and neurofibrillary tangles in the brains of patients. There are various descriptive hypotheses regarding the causes of AD, including the cholinergic hypothesis, amyloid hypothesis, tau propagation hypothesis, mitochondrial cascade hypothesis, calcium homeostasis hypothesis, neurovascular hypothesis, inflammatory hypothesis, metal ion hypothesis, and lymphatic system hypothesis. However, the ultimate etiology of AD remains obscure. In this review, we discuss the main hypotheses of AD and related clinical trials. Wealthy puzzles and lessons have made it possible to develop explanatory theories and identify potential strategies for therapeutic interventions for AD. The combination of hypometabolism and autophagy deficiency is likely to be a causative factor for AD. We further propose that fluoxetine, a selective serotonin reuptake inhibitor, has the potential to treat AD.
350 citations
TL;DR: The hypothesis that white matter hyperintensities contribute to patterns of brain atrophy found in beyond-normal brain ageing in the general population is supported.
Abstract: White matter hyperintensities are associated with increased risk of dementia and cognitive decline. The current study investigates the relationship between white matter hyperintensities burden and patterns of brain atrophy associated with brain ageing and Alzheimer's disease in a large populatison-based sample (n = 2367) encompassing a wide age range (20-90 years), from the Study of Health in Pomerania. We quantified white matter hyperintensities using automated segmentation and summarized atrophy patterns using machine learning methods resulting in two indices: the SPARE-BA index (capturing age-related brain atrophy), and the SPARE-AD index (previously developed to capture patterns of atrophy found in patients with Alzheimer's disease). A characteristic pattern of age-related accumulation of white matter hyperintensities in both periventricular and deep white matter areas was found. Individuals with high white matter hyperintensities burden showed significantly (P < 0.0001) lower SPARE-BA and higher SPARE-AD values compared to those with low white matter hyperintensities burden, indicating that the former had more patterns of atrophy in brain regions typically affected by ageing and Alzheimer's disease dementia. To investigate a possibly causal role of white matter hyperintensities, structural equation modelling was used to quantify the effect of Framingham cardiovascular disease risk score and white matter hyperintensities burden on SPARE-BA, revealing a statistically significant (P < 0.0001) causal relationship between them. Structural equation modelling showed that the age effect on SPARE-BA was mediated by white matter hyperintensities and cardiovascular risk score each explaining 10.4% and 21.6% of the variance, respectively. The direct age effect explained 70.2% of the SPARE-BA variance. Only white matter hyperintensities significantly mediated the age effect on SPARE-AD explaining 32.8% of the variance. The direct age effect explained 66.0% of the SPARE-AD variance. Multivariable regression showed significant relationship between white matter hyperintensities volume and hypertension (P = 0.001), diabetes mellitus (P = 0.023), smoking (P = 0.002) and education level (P = 0.003). The only significant association with cognitive tests was with the immediate recall of the California verbal and learning memory test. No significant association was present with the APOE genotype. These results support the hypothesis that white matter hyperintensities contribute to patterns of brain atrophy found in beyond-normal brain ageing in the general population. White matter hyperintensities also contribute to brain atrophy patterns in regions related to Alzheimer's disease dementia, in agreement with their known additive role to the likelihood of dementia. Preventive strategies reducing the odds to develop cardiovascular disease and white matter hyperintensities could decrease the incidence or delay the onset of dementia.
297 citations
TL;DR: The brain structural and functional changes that have been associated with type 1 and type 2 diabetes are discussed and the development of new strategies to minimize the impact of diabetes on cognitive function are developed.
Abstract: Both type 1 and type 2 diabetes have been associated with reduced performance on multiple domains of cognitive function and with structural abnormalities in the brain. With an aging population and a growing epidemic of diabetes, central nervous system-related complications of diabetes are expected to rise and could have challenging future public health implications. In this review, we will discuss the brain structural and functional changes that have been associated with type 1 and type 2 diabetes. Diabetes duration and glycemic control may play important roles in the development of cognitive impairment in diabetes, but the exact underlying pathophysiological mechanisms causing these changes in cognition and structure are not well understood. Future research is needed to better understand the natural history and the underlying mechanisms, as well as to identify risk factors that predict who is at greatest risk of developing cognitive impairment. This information will lead to the development of new strategies to minimize the impact of diabetes on cognitive function.
293 citations
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TL;DR: The investigation showed that recognition of the six stages required qualitative evaluation of only a few key preparations, permitting the differentiation of six stages.
Abstract: Eighty-three brains obtained at autopsy from nondemented and demented individuals were examined for extracellular amyloid deposits and intraneuronal neurofibrillary changes. The distribution pattern and packing density of amyloid deposits turned out to be of limited significance for differentiation of neuropathological stages. Neurofibrillary changes occurred in the form of neuritic plaques, neurofibrillary tangles and neuropil threads. The distribution of neuritic plaques varied widely not only within architectonic units but also from one individual to another. Neurofibrillary tangles and neuropil threads, in contrast, exhibited a characteristic distribution pattern permitting the differentiation of six stages. The first two stages were characterized by an either mild or severe alteration of the transentorhinal layer Pre-alpha (transentorhinal stages I-II). The two forms of limbic stages (stages III-IV) were marked by a conspicuous affection of layer Pre-alpha in both transentorhinal region and proper entorhinal cortex. In addition, there was mild involvement of the first Ammon's horn sector. The hallmark of the two isocortical stages (stages V-VI) was the destruction of virtually all isocortical association areas. The investigation showed that recognition of the six stages required qualitative evaluation of only a few key preparations.
13,699 citations
Additional excerpts
...A notable parallel is that a similar distribution of cortical atrophy was described in early Alzheimer disease in neuropathological studies (31) and a longitudinal MRI study (17), where gray matter loss began in the temporal, entorhinal, and parietal lobes before progressing to orbitofrontal regions and more so in the left hemisphere....
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TL;DR: It is demonstrated that the use of local optimisation methods together with the standard multi-resolution approach is not sufficient to reliably find the global minimum, so a global optimisation method is proposed that is specifically tailored to this form of registration.
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"Brain atrophy in type 2 diabetes: r..." refers methods in this paper
...Three-dimensional T1 and GRE sequences were registered in the standard Montreal Neurological Institute space using the FunctionalMRI of the Brain Linear Image Registration Tool (22)....
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...Three-dimensional T1 and GRE sequences were registered in the standard Montreal Neurological Institute space using the Functional MRI of the Brain Linear Image Registration Tool (22)....
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TL;DR: When used in concert with authors' deeper knowledge of an experiment, the TD system provides consistent and comprehensive labels for brain activation foci, which is better than that of the expert group.
Abstract: An automated coordinate-based system to retrieve brain labels from the 1988 Talairach Atlas, called the Talairach Daemon (TD), was previously introduced (Lancaster et al., 1997). In the present study, the TD system and its 3-D database of labels for the 1988 Talairach atlas were tested for labeling of functional activation foci. TD system labels were compared with author-designated labels of activation coordinates from over 250 published functional brain-mapping studies and with manual atlas-derived labels from an expert group using a subset of these activation coordinates. Automated labeling by the TD system compared well with authors' labels, with a 70% or greater label match averaged over all locations. Author-label matching improved to greater than 90% within a search range of 65 mm for most sites. An adaptive grey matter (GM) range-search utility was evaluated using individual activations from the M1 mouth region (30 subjects, 52 sites). It provided an 87% label match to Brodmann area labels (B A4&B A 6) within a search range of 65 mm. Using the adaptive GM range search, the TD system's overall match with authors' labels (90%) was better than that of the expert group (80%). When used in concert with authors' deeper knowledge of an experiment, the TD system provides consistent and comprehensive labels for brain activation foci. Additional suggested applications of the TD system include interactive labeling, anatomical grouping of activation foci, lesion-deficit analysis, and neuroanatomy education. Hum. Brain Mapping 10:120 -131, 2000. © 2000 Wiley-Liss, Inc.
3,380 citations