Modeling the Relationships Among Late-Life Body Mass Index, Cerebrovascular Disease, and Alzheimer's Disease Neuropathology in an Autopsy Sample of 1,421 Subjects from the National Alzheimer's Coordinating Center Data Set

Different associations between body mass index and Alzheimer's markers depending on metabolic health

BACKGROUND

Increasing evidence supports the association between body mass index (BMI), Alzheimer's disease, and vascular markers. Recently, metabolically unhealthy conditions have been reported to affect the expression of these markers. We aimed to investigate the effects of BMI status on Alzheimer's and vascular markers in relation to metabolic health status.

METHODS

We recruited 1,736 Asians without dementia (71.6 ± 8.0 years). Participants were categorized into underweight, normal weight, or obese groups based on their BMI. Each group was further divided into metabolically healthy (MH) and unhealthy (MU) groups based on the International Diabetes Foundation definition of metabolic syndrome. The main outcome was Aβ positivity, defined as a Centiloid value of 20.0 or above and the presence of vascular markers, defined as severe white matter hyperintensities (WMH). Logistic regression analyses were performed for Aβ positivity and severe WMH with BMI status or interaction terms between BMI and metabolic health status as predictors. Mediation analyses were performed with hippocampal volume (HV) and baseline Mini-Mental State Examination (MMSE) scores as the outcomes, and linear mixed models were performed for longitudinal change in MMSE scores.

RESULTS

Being underweight increased the risk of Aβ positivity (odds ratio [OR] = 2.37, 95% confidence interval [CI] 1.13-4.98), whereas obesity decreased Aβ positivity risk (OR = 0.63, 95% CI 0.50-0.80). Especially, obesity decreased the risk of Aβ positivity (OR = 0.38, 95% CI 0.26-0.56) in the MH group, but not in the MU group. Obesity increased the risk of severe WMH (OR = 1.69, 1.16-2.47). Decreased Aβ positivity mediate the relationship between obesity and higher HV and MMSE scores, particularly in the MH group. Obesity demonstrated a slower decline in MMSE (β = 1.423, p = 0.037) compared to being normal weight, especially in the MH group.

CONCLUSIONS

Our findings provide new evidence that metabolic health has a significant effect on the relationship between obesity and Alzheimer's markers, which, in turn, lead to better clinical outcomes.

The Association Between Neuropathological Lesions and Body Mass Index Is Independent of Cognitive Abilities

Background

The association of moderate and severe dementia with low body mass index (BMI) is well described, but weight decline seems to also occur in individuals with preclinical neuropathologies. Considering that up to one-fifth of individuals with normal cognition meet the criteria for a dementia-related neuropathological diagnosis, autopsy studies are key to detecting preclinical neurodegenerative and cerebrovascular diseases that could be underlying weight changes.

Objective

We investigated the association between dementia-related brain lesions and BMI and evaluated whether the cognitive function was a mediator of this association.

Methods

In 1,170 participants, sociodemographic data, clinical history, and cognitive post-mortem evaluation were assessed with an informant. Neuropathological evaluation was performed in all cases. Linear regression models were used to investigate the association between neuropathological lesions (exposure variable) and BMI (outcome) adjusted for demographic, clinical, and cognitive variables in the whole sample, and in only those with normal cognition. Corrections for multiple comparisons were performed. In addition, a mediation analysis was performed to investigate the direct and indirect effects of cognitive abilities on the association between neuropathology and BMI.

Results

Individuals with lower BMI had a higher burden of neuropathological lesions and poorer cognitive abilities. Only neurofibrillary tangles (NFT) and neuropathological comorbidity were associated with low BMI, while other neurodegenerative and cerebrovascular lesions were not. NFT were indirectly associated with BMI through cognitive abilities, and also directly, even in participants with normal cognition.

Conclusions

Neurofibrillary tangles were directly associated with low BMI even in individuals with preclinical Alzheimer's disease.

Nutrition markers and discharge outcome in deep and lobar intracerebral hemorrhage

INTRODUCTION

Malnutrition is common in stroke patients and has been associated with poor functional outcomes and increased mortality after stroke. Previous research on nutrition status and post-intracerebral hemorrhage (ICH) outcomes, however, is limited and conflicting.

PATIENTS AND METHODS

Monocenter study of patients with spontaneous deep or lobar ICH from a longitudinal cohort enrolling consecutive patients between 1994 and 2022. Nutrition status was assessed using admission body mass index (BMI), albumin, total bilirubin, cholesterol, c-reactive protein, hemoglobin a1c, high-density lipoprotein, hemoglobin, low-density lipoprotein, mean corpuscular volume, alanine transaminase, and triglycerides. Main outcome was favorable discharge outcome (mRS 0-2). Multivariable logistic regression was conducted with adjustment for baseline differences.

RESULTS

Among 2170 patients, 1152 had deep and 1018 had lobar ICH. Overweight BMI was associated with higher odds of favorable discharge outcome in all (aOR = 3.01, 95% CI 1.59-5.69, p = 0.001) and lobar (aOR = 3.26, 95% CI 1.32-8.08, p = 0.011) ICH after adjustment for baseline differences. This association did not reach statistical significance in deep (aOR = 2.77, 95% CI 0.99-7.72, p = 0.052) ICH. No lab values were associated with functional outcome in all, deep, or lobar ICH after adjustment.

DISCUSSION AND CONCLUSION

Overweight BMI was associated with favorable discharge status after ICH. These findings could inform future studies to determine whether overweight BMI has a protective effect in ICH patients.

Patterns of Aging Changes in Bodyweight May Predict Alzheimer's Disease

Relationships between patterns of aging-changes in bodyweight and AD are not fully understood. We compared mean age-trajectories of weight between those who did and did not develop late-onset-AD, and evaluated impact of age at maximum weight (AgeMax), and slope of decline in weight, on AD risk. Women with late-onset-AD had lower weight three or more decades before AD onset, and ∼10 years younger AgeMax, compared to AD-free women. APOE4 carriers had younger AgeMax and steeper slope. Older AgeMax and flatter slope predicted lower AD risk. Premature decline in weight could be a sign of accelerated physical aging contributing to AD.

Body Mass Index Trajectories Preceding Incident Mild Cognitive Impairment and Dementia

Importance

Body mass index (BMI) trajectories before the onset of mild cognitive impairment (MCI) and during the progression from MCI to dementia remain unclear.

Objective

To assess the long-term BMI trajectories preceding incident MCI and dementia and explore whether they are associated with brain pathologies.

Design, Setting, and Participants

The Rush Memory and Aging Project (MAP) was an ongoing community-based cohort study. This study included cognitively intact participants aged 60 to 90 years at baseline with annual follow-up from October 1997 to December 2020 (maximum follow-up of 22 years). During the follow-up, participants underwent brain autopsies. Data were analyzed from August 2021 to February 2022 using mixed-effect models.

Exposures

BMI was calculated using height and weight measured at baseline and follow-ups.

Main Outcomes and Measures

Incident MCI and dementia were diagnosed following standard criteria. Neuropathological assessments (including global Alzheimer disease and vascular pathology) were performed for autopsies.

Results

A total of 1390 participants (mean [SD] age, 78.4 [6.5] years; 1063 female [76.5%]) were included in the study. In the analysis of BMI trajectories before MCI (n = 939), during the follow-up (median [IQR] duration, 6 [3-9] years), 371 participants (39.5%) developed MCI, of whom 88 (23.7%) progressed to dementia. Those who developed MCI were older (mean [SD] age, 79.6 [5.9] years vs 76.9 [6.6] years), consumed less alcohol (median [IQR] consumption, 0 [0-5.8] g/day vs 1.1 [0-6.9] g/day), had a lower BMI (mean [SD], 27.2 [4.9] vs 28.2 [5.9]), and were more likely to be apolipoprotein E (APOE) ε4 carriers (89 of 371 [24.0%] vs 98 of 568 [17.3%]) compared with those who remained cognitively intact over follow-up. Those who developed dementia were older (mean [SD] age, 81.0 [5.2] years vs 79.1 [6.0] years), had a lower level of physical activity (median [IQR] activity, 1.0 [0-2.5] h/week vs 1.8 [0.2-3.8] h/week), and were more likely to be APOE ε4 carriers than those who were dementia-free (33 of 88 [37.5%] vs 56 of 283 [19.8%]). Compared with participants who remained cognitively intact, in those with incident MCI, BMI tended to decline earlier and faster. From 7 years before diagnosis, people with incident MCI had an associated significantly lower BMI (mean difference, -0.96; 95% CI, -1.85 to -0.07) than those who were cognitively intact. Among people with incident MCI, the slopes of BMI decline did not differ significantly between those who did and did not develop dementia (β, -0.03; 95% CI, -0.21 to 0.15). In the analysis of BMI trajectories before autopsy (n = 358), BMI was associated with a faster declination among participants with a high burden of global Alzheimer disease pathology (β for pathology × time highest vs lowest tertile, -0.14; 95% CI, -0.26 to -0.02) or vascular pathology (β for pathology × time2 highest vs lowest tertile, 0.02; 95% CI, 0-0.05).

Conclusions and Relevance

Results of this cohort study suggest that among cognitively intact people, significantly lower BMI occurs beginning approximately 7 years before MCI diagnosis. After MCI diagnosis, BMI declines at the same pace in people who develop dementia and those who do not. High brain pathologies may underly the BMI decline preceding dementing disorders.

Body mass index related to executive function and hippocampal subregion volume in subjective cognitive decline

Objective

This study aims to explore whether body mass index (BMI) level affects the executive function and hippocampal subregion volume of subjective cognitive decline (SCD).

Materials and methods

A total of 111 participants were included in the analysis, including SCD (38 of normal BMI, 27 of overweight and obesity) and normal cognitive control (NC) (29 of normal BMI, 17 of overweight and obesity). All subjects underwent the Chinese version of the Stroop Color-Word Test (SCWT) to measure the executive function and a high-resolution 3D T1 structural image acquisition. Two-way ANOVA was used to examine the differences in executive function and gray matter volume in hippocampal subregions under different BMI levels between the SCD and NC.

Result

The subdimensions of executive function in which different BMI levels interact with SCD and NC include inhibition control function [SCWT C-B reaction time(s): F (1,104) = 5.732, p = 0.018], and the hippocampal subregion volume of CA1 [F (1,99) = 8.607, p = 0.004], hippocampal tail [F (1,99) = 4.077, p = 0.046], and molecular layer [F (1,99) = 6.309, p = 0.014]. After correction by Bonferroni method, the population × BMI interaction only had a significant effect on the CA1 (p = 0.004). Further analysis found that the SCWT C-B reaction time of SCD was significantly longer than NC no matter whether it is at the normal BMI level [F (1,104) = 4.325, p = 0.040] or the high BMI level [F (1,104) = 21.530, p < 0.001], and the inhibitory control function of SCD was worse than that of NC. In the normal BMI group, gray matter volume in the hippocampal subregion (CA1) of SCD was significantly smaller than that of NC [F (1,99) = 4.938, p = 0.029]. For patients with SCD, the high BMI group had worse inhibitory control function [F (1,104) = 13.499, p < 0.001] and greater CA1 volume compared with the normal BMI group [F (1,99) = 7.619, p = 0.007].

Conclusion

The BMI level is related to the inhibition control function and the gray matter volume of CA1 subregion in SCD. Overweight seems to increase the gray matter volume of CA1 in the elderly with SCD, but it is not enough to compensate for the damage to executive function caused by the disease. These data provide new insights into the relationship between BMI level and executive function of SCD from the perspective of imaging.

Changes in Adiposity and Cerebrospinal Fluid Biomarkers Following a Modified Mediterranean Ketogenic Diet in Older Adults at Risk for Alzheimer’s Disease

Background

Ketogenic diets have been used to treat both obesity and neurological disorders, including epilepsy and more recently Alzheimer’s disease (AD), likely due to favorable effects on both central and peripheral metabolism. Improvements in body composition have also been reported; however, it is unclear if diet-induced changes in adiposity are related to improvements in AD and related neuropathology.

Purpose

We examined the effects of a Modified Mediterranean Ketogenic (MMK) diet vs. an American Heart Association (AHA) diet on body weight, body composition, and body fat distribution and their association with cerebrospinal fluid (CSF) biomarkers in older adults at risk for AD.

Methods

Twenty adults (mean age: 64.3 ± 6.3 years, 35% Black, 75% female) were randomly assigned to a crossover trial starting with either the MMK or AHA diet for 6 weeks, followed by a 6-week washout and then the opposite diet for 6 weeks. At baseline and after each diet adiposity was assessed by dual-energy x-ray absorptiometry and CSF biomarkers were measured. Linear mixed effect models were used to examine the effect of diet on adiposity. Spearman correlations were examined to assess associations between adiposity and CSF biomarkers.

Results

At baseline there was a high prevalence of overweight/obesity and central adiposity, and higher visceral fat and lower peripheral fat were associated with an adverse CSF biomarker profile. The MMK and AHA diets led to similar improvements in body composition and body fat distribution. Significant correlations were found between changes in adiposity and changes in CSF biomarkers (r’s = 0.63–0.92, p’s < 0.05), with notable differences by diet. Decreases in body fat on the MMK diet were related to changes in Aβ biomarkers, whereas decreases in body fat on the AHA diet were related to changes in tau biomarkers and cholinesterase activity. Interestingly, increases in CSF Aβ on the MMK diet occurred in those with less fat loss.

Conclusion

An MMK diet leads to favorable changes in body composition, body fat distribution, and CSF biomarkers. Our data suggest that modest weight loss that maximizes visceral fat loss and preserves peripheral fat, may have the greatest impact on brain health.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT02984540].

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

BACKGROUND

Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer's disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses.

OBJECTIVE

To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors/biomarkers.

METHODS

We used biomarker/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class.

RESULTS

For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma Aβ1-42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and Aβ1-40, higher depressive symptomology, and lower body mass index.

CONCLUSION

Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers/risk factors discriminating the higher and lower LHC/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers/risk factors from multiple modalities.

Invited Commentary: Body Mass Index and Risk of Dementia-Potential Explanations for Life-Course Differences in Risk Estimates and Future Research Directions

The relationship between body mass index (BMI) and health outcomes of older adults, including dementia, remains controversial. Many studies find inverse associations between BMI and dementia among older adults, while in other studies high BMI in midlife is associated with increased dementia risk. In this issue, Li et al. (Am J Epidemiol. 2021;190(12):2503-2510) examine BMI from mid- to late life and risk of dementia using the extensive follow-up of the Framingham Offspring Study. They found changing trends in the association between BMI and dementia from a positive association for midlife (ages 40-49) to an inverse trend in late life. Their work demonstrates the importance of studying dementia risk factors across the life course. Midlife obesity might be an important modifiable risk factor for dementia. However, because incipient dementia can lead to weight loss, reverse causation remains a key source of bias that could explain an inverse trend between BMI and dementia in older ages. The extent of other biases, including unmeasured confounding, inaccuracy of BMI as a measure for adiposity, or selective survival, are also unclear. Triangulating evidence on body composition and dementia risk could lead to better targets for dementia intervention, but future work will need to evaluate specific pathways.

Extension of Mendelian Randomization to Identify Earliest Manifestations of Alzheimer Disease: Association of Genetic Risk Score for Alzheimer Disease With Lower Body Mass Index by Age 50 Years

Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006-2010, who were without dementia, aged 39-73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): -0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = -0.03, 95% CI: -0.06, -0.01) and 60- to 73-year-olds (β = -0.09, 95% CI:-0.12, -0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis.

Chronic Traumatic Encephalopathy and Neuropathological Comorbidities

With age, the presence of multiple neuropathologies in a single individual becomes increasingly common. Given that traumatic brain injury and the repetitive head impacts (RHIs) that occur in contact sports have been associated with the development of many neurodegenerative diseases, including chronic traumatic encephalopathy (CTE), Alzheimer's disease, Lewy body disease, and amyotrophic lateral sclerosis, it is becoming critical to understand the relationship and interactions between these pathologies. In fact, comorbid pathology is common in CTE and likely influenced by both age and the severity and type of exposure to RHI as well as underlying genetic predisposition. Here, we review the major comorbid pathologies seen with CTE and in former contact sports athletes and discuss what is known about the associations between RHI, age, and the development of neuropathologies. In addition, we examine the distinction between CTE and age-related pathology including primary age-related tauopathy and age-related tau astrogliopathy.

Hypertension and Alzheimer's disease: indirect effects through circle of Willis atherosclerosis

Hypertension is common among older adults and is believed to increase susceptibility to Alzheimer's disease, but mechanisms underlying this relationship are unclear. Hypertension also promotes circle of Willis atherosclerosis, which contributes to cerebral hypoperfusion and arterial wall stiffening, two potential mechanisms linking hypertension to Alzheimer's disease. To examine the role of circle of Willis atherosclerosis in the association between hypertension and Alzheimer's disease neuropathology, we analysed post-mortem neuropathological data on 2198 decedents from the National Alzheimer's Coordinating Center database [mean (standard deviation) age at last visit 80.51 (1.95) and 47.1% female] using joint simultaneous (i.e. mediation) modelling. Within the overall sample and among Alzheimer's dementia decedents, hypertension was indirectly associated with increased neuritic plaques and neurofibrillary tangles through its association with circle of Willis atherosclerosis. Similar indirect effects were observed for continuous measures of systolic and diastolic blood pressure. These results suggest that hypertension may promote Alzheimer's disease pathology indirectly through intracranial atherosclerosis by limiting cerebral blood flow and/or dampening perivascular clearance. Circle of Willis atherosclerosis may be an important point of convergence between vascular risk factors, cerebrovascular changes and Alzheimer's disease neuropathology.

Weight Loss is a Preclinical Signal of Cerebral Amyloid Deposition and Could Predict Cognitive Impairment in Elderly Adults

BACKGROUND

Higher late-life body mass index (BMI) was associated with reduced risk of Alzheimer's disease (AD), which might be explained by a reverse causal relationship.

OBJECTIVE

To investigate whether weight loss was a preclinical manifestation of AD pathologies and could be a predictor of cognitive impairment.

METHODS

A total of 1,194 participants (mean age = 73.2 [range: 54 to 91] years, female = 44.5%) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were grouped according to AD biomarker profile as indicated by amyloid (A) and tau (TN) status and clinical stage by clinical dementia rating (CDR). BMI across the biomarker-defined clinical stages was compared with Bonferroni correction. Pearson correlation analysis was performed to test the relationship between the amyloid change by PET and the BMI change. Multiple regression models were used to explore the influences of amyloid pathologies on BMI change as well as the effects of weight loss on longitudinal changes of global cognitive function.

RESULTS

BMI was significantly decreased in AD preclinical stage (amyloid positive [A+] and CDR = 0) and dementia stage (A+/TN+ and CDR = 0.5 or 1), compared with the healthy controls (A-/TN-and CDR = 0, p < 0.005), while no significant differences were observed between preclinical AD and AD dementia. Amyloid PET change was inversely correlated with BMI change (p = 0.023, β= -14). Individuals in amyloid positive group exhibited faster weight loss (time×group interaction p = 0.019, β= -0.20) compared to the amyloid negative group. Greater weight loss predicted higher risk of developing cognitive disorders.

CONCLUSION

Elders who experienced greater weight loss might belong to preclinical stage of AD and could be targeted for primary prevention of the disease.

Late-life obesity is a protective factor for prodromal Alzheimer's disease: a longitudinal study

Higher body mass index (BMI) in late-life has recently been considered as a possible protective factor for Alzheimer's disease (AD), which yet remains conflicting. To test this hypothesis, we have evaluated the cross-sectional and longitudinal associations of BMI categories with CSF biomarkers, brain β-amyloid (Aβ) load, brain structure, and cognition and have assessed the effect of late-life BMI on AD risk in a large sample (n = 1,212) of non-demented elderly from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. At baseline, higher late-life BMI categories were associated with higher levels of CSF Aβ42 (p=0.037), lower levels of CSF total-tau (t-tau, p=0.026) and CSF t-tau/Aβ42 (p=0.008), lower load of Aβ in the right hippocampus (p=0.030), as well as larger volumes of hippocampus (p<0.0001), entorhinal cortex (p=0.009) and middle temporal lobe (p=0.040). But no association was found with CSF phosphorylated-tau (p-tau) or CSF p-tau/Aβ42. Longitudinal studies showed that higher BMI individuals experienced a slower decline in cognitive function. In addition, Kaplan–Meier survival analysis revealed that higher late-life BMI had a reduced risk of progression to AD over time (p = 0.009). Higher BMI in late-life decreased the risk of AD, and this process may be driven by AD-related biomarkers.

An Assessment of the Relationship between Structural and Functional Imaging of Cerebrovascular Disease and Cognition-Related Fibers

In order to assess the relationship between structural and functional imaging of cerebrovascular disease and cognition-related fibers, this paper chooses a total of 120 patients who underwent cerebral small vessel disease (CSVD) treatment at a designated hospital by this study from June 2013 to June 2018 and divides them into 3 groups according to the random number table method: vascular dementia (VaD) group, vascular cognitive impairment no dementia (VCIND) group, and noncognition impairment (NCI) group with 40 cases of patients in each group. Cognitive function measurement and imaging examination were performed for these 3 groups of patients, and the observation indicators of cognitive state examination (CSE), mental assessment scale (MAS), clock drawing test (CDT), adult intelligence scale (AIS), frontal assessment battery (FAB), verbal fluency test (VFT), trail making test (TMT), cognitive index (CI), white matter lesions (WML), third ventricle width (TVW), and frontal horn index (FHI) were tested, respectively. The results shows that the average scores of CSE, MAS, AIS, and VFT in the VaD and VCIND group are lower than those of the NCI group and the differences are statistically significant (P < 0.05); the average scores of FAB, TMT, and CI in the VaD group are higher than those of the VCIND group and the differences are also statistically significant (P < 0.05); the average scores of FHI and TVW in the VaD group are lower than those of the VCIND and NCI group with statistically significant differences (P < 0.05); the average scores of WML, CDT, and AIS in the VaD group are higher than those of the VCIND and NCI group with statistically significant differences (P < 0.05). Therefore, it is believed that the structural and functional imaging features of cerebrovascular disease are closely related to cognition-related fibers, and the incidence of white matter lesions is closely related to the degree of lesions and cognitive dysfunction of cerebral small vessel disease, in which a major risk factor for cognitive dysfunction in patients with small blood vessels is the severity of white matter lesions; brain imaging and neuropsychiatric function assessment can better understand the relationship between cerebrovascular disease and cognitive impairment. The results of this study provide a reference for the further research studies on the relationship between structural and functional imaging of cerebrovascular disease and cognition-related fibers.

Revised Framingham Stroke Risk Profile: Association with Cognitive Status and MRI-Derived Volumetric Measures

BACKGROUND

The Framingham Stroke Risk Profile (FSRP) was created in 1991 to estimate 10-year risk of stroke. It was revised in 2017 (rFSRP) to reflect the modern data on vascular risk factors and stroke risk.

OBJECTIVE

This study examined the association between the rFSRP and cognitive and brain aging outcomes among participants from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS).

METHODS

Cross-sectional rFSRP was computed at baseline for 19,309 participants (mean age = 72.84, SD = 8.48) from the NACC-UDS [9,697 (50.2%) normal cognition, 4,705 (24.4%) MCI, 4,907 (25.4%) dementia]. Multivariable linear, logistic, or ordinal regressions examined the association between the rFSRP and diagnostic status, neuropsychological test performance, CDR® Sum of Boxes, as well as total brain volume (TBV), hippocampal volume (HCV), and log-transformed white matter hyperintensities (WMH) for an MRI subset (n = 1,196). Models controlled for age, sex, education, racial identity, APOEɛ4 status, and estimated intracranial volume for MRI models.

RESULTS

The mean rFSRP probability was 10.42% (min = 0.50%, max = 95.71%). Higher rFSRP scores corresponded to greater CDR Sum of Boxes (β= 0.02, p = 0.028) and worse performance on: Trail Making Test A (β= 0.05, p < 0.001) and B (β= 0.057, p < 0.001), and Digit Symbol (β= -0.058, p < 0.001). Higher rFSRP scores were associated with increased odds for a greater volume of log-transformed WMH (OR = 1.02 per quartile, p = 0.015). No associations were observed for diagnosis, episodic memory or language test scores, HCV, or TBV.

CONCLUSION

These results support the rFSRP as a useful metric to facilitate clinical research on the associations between cerebrovascular disease and cognitive and brain aging.

The Association Between Body Mass Index, and Cognitive, Functional, and Behavioral Declines for Incident Dementia

BACKGROUND

Association between high adiposity and the clinical progression of dementia remains puzzling.

OBJECTIVE

To separately examine the association between body mass index (BMI) and cognitive, functional, and behavioral declines before, at, and after diagnosis of dementia, and further stratified by age groups, and sex.

METHODS

A total of 1,141 individuals with incident dementia were identified from the Uniform Data Set of the National Alzheimer's Coordinating Center. Cognitive function was evaluated by Mini-Mental State Exam, functional abilities were assessed using Functional Activities Questionnaire, and behavioral symptoms were captured by Neuropsychiatric Inventory Questionnaire at each follow-up visit. We used separate linear-mixed effects models to examine the association.

RESULTS

Compared to moderate baseline BMI, high baseline BMI was associated with 0.30-point slower annual progression rates in functional decline. For individuals aged 76 and over, high baseline BMI was associated with 0.42-point faster progression rates in cognitive decline annually. A U-shaped association between baseline BMI and cognitive decline was observed among men.

CONCLUSION

BMI levels before dementia diagnosis may facilitate the identification of different risk profiles for progression rates of cognitive and functional declines in individuals who developed dementia.

Association of White Matter Rarefaction, Arteriolosclerosis, and Tau With Dementia in Chronic Traumatic Encephalopathy

IMPORTANCE

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with repetitive head impacts, including those from US football, that presents with cognitive and neuropsychiatric disturbances that can progress to dementia. Pathways to dementia in CTE are unclear and likely involve tau and nontau pathologic conditions.

OBJECTIVE

To investigate the association of white matter rarefaction and cerebrovascular disease with dementia in deceased men older than 40 years who played football and had CTE.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study involves analyses of data from the ongoing Understanding Neurologic Injury and Traumatic Encephalopathy (UNITE) Study, which is conducted via and included brain donors from the Veterans Affairs-Boston University-Concussion Legacy Foundation brain bank between 2008 and 2017. An original sample of 224 men who had played football and were neuropathologically diagnosed with CTE was reduced after exclusion of those younger than 40 years and those missing data.

EXPOSURES

The number of years of football play as a proxy for repetitive head impacts.

MAIN OUTCOMES AND MEASURES

Neuropathological assessment of white matter rarefaction and arteriolosclerosis severity (on a scale of 0-3, where 3 is severe); number of infarcts, microinfarcts, and microbleeds; and phosphorylated tau accumulation determined by CTE stage and semiquantitative rating of dorsolateral frontal cortex (DLFC) neurofibrillary tangles (NFTs) (none or mild vs moderate or severe). Informant-based retrospective clinical interviews determined dementia diagnoses via diagnostic consensus conferences.

RESULTS

A total of 180 men were included. The mean (SD) age of the sample at death was 67.9 (12.7) years. Of 180, 120 [66.7%]) were found to have had dementia prior to death. Moderate to severe white matter rarefaction (84 of 180 [46.6%]) and arteriolosclerosis (85 of 180 [47.2%]) were common; infarcts, microinfarcts, and microbleeds were not. A simultaneous equations regression model controlling for age and race showed that more years of play was associated with more severe white matter rarefaction (β, 0.16 [95% CI, 0.02-0.29]; P = .03) and greater phosphorylated tau accumulation (DLFC NFTs: β, 0.15 [95% CI, 0.004-0.30]; P = .04; CTE stage: β, 0.27 [95% CI, 0.14-0.41]; P < .001). White matter rarefaction (β, 0.16 [95% CI, 0.02-0.29]; P = .03) and DLFC NFTs (β, 0.16 [95% CI, 0.03-0.28]; P = .01) were associated with dementia. Arteriolosclerosis and years of play were not associated, but arteriolosclerosis was independently associated with dementia (β, 0.21 [95% CI, 0.07-0.35]; P = .003).

CONCLUSIONS AND RELEVANCE

Among older men who had played football and had CTE, more years of football play were associated with more severe white matter rarefaction and greater DLFC NFT burden. White matter rarefaction, arteriolosclerosis, and DLFC NFTs were independently associated with dementia. Dementia in CTE is likely a result of neuropathologic changes, including white matter rarefaction and phosphorylated tau, associated with repetitive head impact and pathologic changes not associated with head trauma, such as arteriolosclerosis.

Brain Inflammation Connects Cognitive and Non-Cognitive Symptoms in Alzheimer's Disease

Alzheimer's disease (AD) is the main form of dementia in the elderly and affects greater than 47 million people worldwide. Care for AD patients poses very significant personal and economic demands on individuals and society, and the situation is expected to get even more dramatic in the coming decades unless effective treatments are found to halt the progression of the disease. Although AD is most commonly regarded as a disease of the memory, the entire brain is eventually affected by neuronal dysfunction or neurodegeneration, which brings about a host of other behavioral disturbances. AD patients often present with apathy, depression, eating and sleeping disorders, aggressive behavior, and other non-cognitive symptoms, which deeply affect not only the patient but also the caregiver's health. These symptoms are usually associated with AD pathology but are often neglected as part of disease progression due to the early and profound impact of disease on memory centers such as the hippocampus and entorhinal cortex. Yet, a collection of findings offers biochemical insight into mechanisms underlying non-cognitive symptoms in AD, and indicate that, at the molecular level, such symptoms share common mechanisms. Here, we review evidence indicating mechanistic links between memory loss and non-cognitive symptoms of AD. We highlight the central role of the pro-inflammatory activity of microglia in behavioral alterations in AD patients and in experimental models of the disease. We suggest that a deeper understanding of non-cognitive symptoms of AD may illuminate a new beginning in AD research, offering a fresh approach to elucidate mechanisms involved in disease progression and potentially unveiling yet unexplored therapeutic targets.

A Clinicopathological Investigation of White Matter Hyperintensities and Alzheimer's Disease Neuropathology

BACKGROUND

White matter hyperintensities (WMH) on magnetic resonance imaging (MRI) have been postulated to be a core feature of Alzheimer's disease. Clinicopathological studies are needed to elucidate and confirm this possibility.

OBJECTIVE

This study examined: 1) the association between antemortem WMH and autopsy-confirmed Alzheimer's disease neuropathology (ADNP), 2) the relationship between WMH and dementia in participants with ADNP, and 3) the relationships among cerebrovascular disease, WMH, and ADNP.

METHODS

The sample included 82 participants from the National Alzheimer's Coordinating Center's Data Sets who had quantitated volume of WMH from antemortem FLAIR MRI and available neuropathological data. The Clinical Dementia Rating (CDR) scale (from MRI visit) operationalized dementia status. ADNP+ was defined by moderate to frequent neuritic plaques and Braak stage III-VI at autopsy. Cerebrovascular disease neuropathology included infarcts or lacunes, microinfarcts, arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy.

RESULTS

60/82 participants were ADNP+. Greater volume of WMH predicted increased odds for ADNP (p = 0.037). In ADNP+ participants, greater WMH corresponded with increased odds for dementia (CDR≥1; p = 0.038). WMH predicted cerebral amyloid angiopathy, microinfarcts, infarcts, and lacunes (ps < 0.04). ADNP+ participants were more likely to have moderate-severe arteriolosclerosis and cerebral amyloid angiopathy compared to ADNP-participants (ps < 0.04).

CONCLUSIONS

This study found a direct association between total volume of WMH and increased odds for having ADNP. In patients with Alzheimer's disease, FLAIR MRI WMH may be able to provide key insight into disease severity and progression. The association between WMH and ADNP may be explained by underlying cerebrovascular disease.

Failure to detect an association between self-reported traumatic brain injury and Alzheimer's disease neuropathology and dementia

INTRODUCTION

Recent research with neuropathologic or biomarker evidence of Alzheimer's disease (AD) casts doubt on traumatic brain injury (TBI) as a risk factor for AD. We leveraged the National Alzheimer's Coordinating Center to examine the association between self-reported TBI with loss of consciousness and AD neuropathologic changes, and with baseline and longitudinal clinical status.

METHODS

The sample included 4761 autopsy participants (453 with remote TBI with loss of consciousness; 2822 with AD neuropathologic changes) from National Alzheimer's Coordinating Center.

RESULTS

Self-reported TBI did not predict AD neuropathologic changes (P > .10). Reported TBI was not associated with baseline or change in dementia severity or cognitive function in participants with or without autopsy-confirmed AD.

DISCUSSION

Self-reported TBI with loss of consciousness may not be an independent risk factor for clinical or pathological AD. Research that evaluates number and severity of TBIs is needed to clarify the neuropathological links between TBI and dementia documented in other large clinical databases.

Innate Immune and Fungal Model of Alzheimer's Disease

Various fungi and bacteria can colonize in the brain and produce physical alterations seen in Alzheimer’s disease (AD). Environmental and genetic factors affect the occurrence of fungal colonization, and how fungi can grow, enter the brain, and interact with the innate immune system. The essence of AD development is the defeat of the innate immune system, whether through vulnerable patient health status or treatment that suppresses inflammation by suppressing the innate immune system. External and mechanical factors that lead to inflammation are a door for pathogenic opportunity. Current research associates the presence of fungi in the etiology of AD and is shown in cerebral tissue at autopsy. From the time of the discovery of AD, much speculation exists for an infective cause. Identifying any AD disease organism is obscured by processes that can take place over years. Amyloid protein deposits are generally considered to be evidence of an intrinsic response to stress or imbalance, but instead amyloid may be evidence of the innate immune response which exists to destroy fungal colonization through structural interference and cytotoxicity. Fungi can remain ensconced for a long time in niches or inside cells, and it is the harboring of fungi that leads to repeated reinfection and slow wider colonization that eventually leads to a grave outcome. Although many fungi and bacteria are associated with AD affected tissues, discussion here focuses on Candida albicans as the archetype of human fungal pathology because of its wide proliferation as a commensal fungus, extensive published research, numerous fungal morphologies, and majority proliferation in AD tissues.