Cognitive deficits in non-demented diabetic elderly appear independent of brain amyloidosis

Impact of diabetes on the progression of Alzheimer's disease via trajectories of amyloid-tau-neurodegeneration (ATN) biomarkers

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.

The association of glucose metabolism measures and diabetes status with Alzheimer's disease biomarkers of amyloid and tau: A systematic review and meta-analysis

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.

Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative

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.

Review: Relationship of type 2 diabetes to human brain pathology

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.