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Kim EW, Kim KY, Kim E. Impact of diabetes on the progression of Alzheimer's disease via trajectories of amyloid-tau-neurodegeneration (ATN) biomarkers. J Nutr Health Aging 2025; 29:100444. [PMID: 39662155 DOI: 10.1016/j.jnha.2024.100444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2024] [Revised: 11/28/2024] [Accepted: 11/28/2024] [Indexed: 12/13/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is characterized by the accumulation of abnormal proteins, such as β-amyloid and tau, in the brain, which precedes cognitive impairment. Although diabetes mellitus (DM) is a well-established risk factor for AD, few studies have investigated how the presence of DM affects the sequential pathogenesis of AD, specifically within the amyloid-tau-neurodegeneration (ATN) and cognition framework. OBJECTIVES This study aims to investigate the trajectories of ATN biomarkers in relation to the presence of DM in the preclinical and prodromal stages of AD. DESIGN Participants with normal cognition (CN) or mild cognitive impairment (MCI) at baseline were included. Subjects were followed for 12-192 months, with neuroimaging and cognitive assessments conducted at every 12 or 24 months. SETTING This study utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. PARTICIPANTS A total of 603 participants aged 55-90 years were included, comprising 284 CN (25 with DM, 259 without DM) and 319 MCI (39 with DM, 280 without DM) individuals. MEASUREMENTS ATN biomarkers were identified using florbetapir positron emission tomography (PET), flortaucipir PET, and magnetic resonance imaging (MRI), respectively. Cognition was assessed using the Clinical Dementia Rating-Sum of Boxes (CDR-SB) and Mini-Mental State Examination (MMSE). Moderation analysis was conducted to investigate the effect of DM on the association between ATN biomarkers of AD. RESULTS Elevated amyloid standardized uptake value ratios (SUVRs) were associated with increased tau levels in the hippocampus, and this association was significantly enhanced by the presence of DM in MCI participants (p = 0.021). DM also strengthened the association between increased tau SUVR levels and neurodegeneration (indicated by decreased entorhinal cortical volumes; p = 0.005) in those with MCI. Furthermore, DM enhanced the association of decreased entorhinal (p = 0.012) and middle temporal cortex (p = 0.031) volumes with increased (worsened) CDR-SB scores in MCI participants. However, DM did not predict significant longitudinal changes in ATN pathology or cognitive decline in CN participants. CONCLUSIONS Our study suggests that DM may increase the risk of AD by accelerating each step of the A-T-N cascade in the prodromal stage of AD, underscoring the importance of DM management in preventing the MCI conversion to AD.
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Affiliation(s)
- Eun Woo Kim
- Graduate School of Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Nursing, Seoyeong University, Gwangju 61268, Republic of Korea
| | - Keun You Kim
- Department of Psychiatry, Seoul Metropolitan Government Seoul National University (SMG-SNU) Boramae Medical Center, Seoul National University College of Medicine, Seoul 07061, Republic of Korea; Department of Psychiatry, Laboratory for Alzheimer's Molecular Psychiatry, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
| | - Eosu Kim
- Graduate School of Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Psychiatry, Laboratory for Alzheimer's Molecular Psychiatry, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Metabolism-Dementia Research Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
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van Gils V, Rizzo M, Côté J, Viechtbauer W, Fanelli G, Salas-Salvadó J, Wimberley T, Bulló M, Fernandez-Aranda F, Dalsgaard S, Visser PJ, Jansen WJ, Vos SJB. The association of glucose metabolism measures and diabetes status with Alzheimer's disease biomarkers of amyloid and tau: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 159:105604. [PMID: 38423195 DOI: 10.1016/j.neubiorev.2024.105604] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 03/02/2024]
Abstract
Conflicting evidence exists on the relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) biomarkers. Therefore, we conducted a random-effects meta-analysis to evaluate the correlation of glucose metabolism measures (glycated hemoglobin, fasting blood glucose, insulin resistance indices) and DM status with AD biomarkers of amyloid-β and tau measured by positron emission tomography or cerebrospinal fluid. We selected 37 studies from PubMed and Embase, including 11,694 individuals. More impaired glucose metabolism and DM status were associated with higher tau biomarkers (r=0.11[0.03-0.18], p=0.008; I2=68%), but were not associated with amyloid-β biomarkers (r=-0.06[-0.13-0.01], p=0.08; I2=81%). Meta-regression revealed that glucose metabolism and DM were specifically associated with tau biomarkers in population settings (p=0.001). Furthermore, more impaired glucose metabolism and DM status were associated with lower amyloid-β biomarkers in memory clinic settings (p=0.004), and in studies with a higher prevalence of dementia (p<0.001) or lower cognitive scores (p=0.04). These findings indicate that DM is associated with biomarkers of tau but not with amyloid-β. This knowledge is valuable for improving dementia and DM diagnostics and treatment.
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Affiliation(s)
- Veerle van Gils
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Marianna Rizzo
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Jade Côté
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Wolfgang Viechtbauer
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Giuseppe Fanelli
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy; Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental (ANUT-DSM), Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Alimentació, Nutrició, Desenvolupament i Salut Mental, Reus, Spain; CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid 28029, Spain
| | - Theresa Wimberley
- The National Center for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Mònica Bulló
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid 28029, Spain; Nutrition and Metabolic Health Research Group (NuMeH). Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), Reus 43201, Spain; Center of Environmental, Food and Toxicological Technology - TecnATox, Rovira i Virgili University, Reus 43201, Spain
| | - Fernando Fernandez-Aranda
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid 28029, Spain; Department of Clinical Psychology, Bellvitge University Hospital-IDIBELL, Barcelona, Spain; Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Spain
| | - Søren Dalsgaard
- The National Center for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark; iPSYCH - The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark
| | - Pieter Jelle Visser
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Alzheimer Center and Department of Neurology, Amsterdam Neuroscience Campus, VU University Medical Center, Amsterdam, the Netherlands
| | - Willemijn J Jansen
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry & Neuropsychology, Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Morris JC, Petersen RC, Saykin AJ, Shaw LM, Toga AW, Trojanowski JQ. Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement 2018; 15:106-152. [PMID: 30321505 DOI: 10.1016/j.jalz.2018.08.005] [Citation(s) in RCA: 286] [Impact Index Per Article: 40.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Accepted: 08/21/2018] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. METHODS We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/). RESULTS (1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. DISCUSSION ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.
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Affiliation(s)
- Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Pruzin JJ, Nelson PT, Abner EL, Arvanitakis Z. Review: Relationship of type 2 diabetes to human brain pathology. Neuropathol Appl Neurobiol 2018; 44:347-362. [PMID: 29424027 PMCID: PMC5980704 DOI: 10.1111/nan.12476] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Accepted: 01/12/2018] [Indexed: 12/14/2022]
Abstract
Type 2 diabetes (T2D) and Alzheimer's disease (AD) are both highly prevalent diseases worldwide, and each is associated with high-morbidity and high-mortality. Numerous clinical studies have consistently shown that T2D confers a two-fold increased risk for a dementia, including dementia attributable to AD. Yet, the mechanisms underlying this relationship, especially nonvascular mechanisms, remain debated. Cerebral vascular disease (CVD) is likely to be playing a role. But increased AD neuropathologic changes (ADNC), specifically neuritic amyloid plaques (AP) and neurofibrillary tangles (NFT), are also posited mechanisms. The clinicopathological studies to date demonstrate T2D to be consistently associated with infarcts, particularly subcortical lacunar infarcts, but not ADNC, suggesting the association of T2D with dementia may largely be mediated through CVD. Furthermore, growing interest exists in insulin resistance (IR), particularly IR within the brain itself, which may be an associated but distinct phenomenon from T2D, and possibly itself associated with ADNC. Other mechanisms largely related to protein processing and efflux in the central nervous system with altered function in T2D may also be involved. Such mechanisms include islet amyloid polypeptide (or amylin) deposition, co-localized with beta-amyloid and found in more abundance in the AD temporal cortex, blood-brain barrier breakdown and dysfunction, potentially related to pericyte degeneration, and disturbance of brain lymphatics, both in the glial lymphatic system and the newly discovered discrete central nervous system lymph vessels. Medical research is ongoing to further disentangle the relationship of T2D to dementia in the ageing human brain.
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Affiliation(s)
- Jeremy J. Pruzin
- Rush Alzheimer’s Disease Center, Chicago, IL
- Dept of Neurological Sciences, Rush University Medical Center, Chicago, IL
| | - Peter T. Nelson
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY
- Department of Pathology, University of Kentucky, Lexington, KY
| | - Erin L. Abner
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY
- Department of Epidemiology, University of Kentucky, Lexington, KY
| | - Zoe Arvanitakis
- Rush Alzheimer’s Disease Center, Chicago, IL
- Dept of Neurological Sciences, Rush University Medical Center, Chicago, IL
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