Brain β-Amyloid Links the Association of Change in Body Mass Index With Cognitive Decline in Community-Dwelling Older Adults

Dynamic Features of Body Mass Index in Late Life Predict Cognitive Trajectories and Alzheimer's Disease: A Longitudinal Study

Background

The causal relationships of late-life body mass index (BMI) with Alzheimer's disease (AD) remains debated.

Objective

We aimed to assess the associations of dynamic BMI features (ΔBMIs) with cognitive trajectories, AD biomarkers, and incident AD risk.

Methods

We analyzed an 8-year cohort of 542 non-demented individuals who were aged ≥65 years at baseline and had BMI measurements over the first 4 years. ΔBMIs were defined as changing extent (change ≤ or >5%), variability (standard deviation), and trajectories over the first 4 years measured using latent class trajectory modeling. Linear mixed-effect models were utilized to examine the influence of ΔBMIs on changing rates of AD pathology biomarkers, hippocampus volume, and cognitive functions. Cox proportional hazards models were used to test the associations with AD risk. Stratified analyzes were conducted by the baseline BMI group and age.

Results

Over the 4-year period, compared to those with stable BMI, individuals who experienced BMI decreases demonstrated accelerated declined memory function (p = 0.006) and amyloid-β deposition (p = 0.034) while BMI increases were associated with accelerated hippocampal atrophy (p = 0.036). Three BMI dynamic features, including stable BMI, low BMI variability, and persistently high BMI, were associated with lower risk of incident AD (p < 0.005). The associations were validated over the 8-year period after excluding incident AD over the first 4 years. No stratified effects were revealed by the BMI group and age.

Conclusions

High and stable BMI in late life could predict better cognitive trajectory and lower risk of AD.

Current Perspectives: Obesity and Neurodegeneration - Links and Risks

Obesity is increasing in prevalence across all age groups. Long-term obesity can lead to the development of metabolic and cardiovascular diseases through its effects on adipose, skeletal muscle, and liver tissue. Pathological mechanisms associated with obesity include immune response and inflammation as well as oxidative stress and consequent endothelial and mitochondrial dysfunction. Recent evidence links obesity to diminished brain health and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Both AD and PD are associated with insulin resistance, an underlying syndrome of obesity. Despite these links, causative mechanism(s) resulting in neurodegenerative disease remain unclear. This review discusses relationships between obesity, AD, and PD, including clinical and preclinical findings. The review then briefly explores nonpharmacological directions for intervention.

Brain Insulin Signaling is Associated with Late-Life Cognitive Decline

Type-2 diabetes is associated with an increased risk of dementia, and the underlying mechanism might involve abnormal insulin signaling in the brain. The objective of this study was to examine the association of postmortem brain insulin signaling with late-life cognitive decline. Among participants of Religious Orders Study, a community-based clinical-pathological cohort, 150 deceased and autopsied older individuals (75 with diabetes matched to 75 without by age at death, sex, and education) had postmortem brain insulin signaling measurements collected in the prefrontal cortex using ELISA and immunohistochemistry. By using adjusted linear mixed-effects models, we examined the association of postmortem brain insulin signaling with late-life cognitive function assessed longitudinally (mean follow-up duration = 9.4 years) using a battery of neuropsychological tests. We found that a higher level of serine/threonine-protein kinase (AKT) phosphorylation (pT308AKT1/total AKT1) was associated with a faster decline in global cognition (estimate = -0.023, p = 0.030), and three domains: episodic memory (estimate = -0.024, p = 0.032), working memory (estimate = -0.018, p = 0.012), and visuospatial abilities (estimate = -0.013, p = 0.027). The level of insulin receptor substrate-1 (IRS1) phosphorylation (pS307IRS1/total IRS1) was not associated with decline in global cognition or most cognitive domains, except for perceptual speed (estimate = 0.020, p = 0.020). The density of pS616IRS1-stained cells was not associated with decline in global cognition or any of the domains. In conclusion, these findings provide novel evidence for an association between brain insulin signaling and late-life cognitive decline. AKT phosphorylation is associated with a decline in global cognition and memory in particular, whereas IRS1 phosphorylation is associated with a decline in perceptual speed.

nlive: an R package to facilitate the application of the sigmoidal and random changepoint mixed models

BACKGROUND

The use of mixed effect models with a specific functional form such as the Sigmoidal Mixed Model and the Piecewise Mixed Model (or Changepoint Mixed Model) with abrupt or smooth random change allows the interpretation of the defined parameters to understand longitudinal trajectories. Currently, there are no interface R packages that can easily fit the Sigmoidal Mixed Model allowing the inclusion of covariates or incorporating recent developments to fit the Piecewise Mixed Model with random change.

RESULTS

To facilitate the modeling of the Sigmoidal Mixed Model, and Piecewise Mixed Model with abrupt or smooth random change, we have created an R package called nlive. All needed pieces such as functions, covariance matrices, and initials generation were programmed. The package was implemented with recent developments such as the polynomial smooth transition of the piecewise mixed model with improved properties over Bacon-Watts, and the stochastic approximation expectation-maximization (SAEM) for efficient estimation. It was designed to help interpretation of the output by providing features such as annotated output, warnings, and graphs. Functionality, including time and convergence, was tested using simulations. We provided a data example to illustrate the package use and output features and interpretation. The package implemented in the R software is available from the Comprehensive R Archive Network (CRAN) at https://CRAN.R-project.org/package=nlive .

CONCLUSIONS

The nlive package for R fits the Sigmoidal Mixed Model and the Piecewise Mixed: abrupt and smooth. The nlive allows fitting these models with only five mandatory arguments that are intuitive enough to the less sophisticated users.

Body mass index and two-year change of in vivo Alzheimer's disease pathologies in cognitively normal older adults

BACKGROUND

Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimer's disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated.

METHODS

This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers.

RESULTS

A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females.

DISCUSSION

The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults.

Brain and spinal cord arteriolosclerosis and its associations with cerebrovascular disease risk factors in community-dwelling older adults

Arteriolosclerosis is common in older brains and related to cognitive and motor impairment. We compared the severity of arteriolosclerosis and its associations with cerebrovascular disease risk factors (CVD-RFs) in multiple locations in the brain and spinal cord. Participants (n = 390) were recruited in the context of a longitudinal community-based clinical-pathological study, the Rush Memory and Aging Project. CVD-RFs were assessed annually for an average of 8.7 (SD = 4.3) years before death. The annual assessments included systolic (SBP) and diastolic (DBP) blood pressure, diabetes mellitus (DM), low- and high-density lipoprotein cholesterol, triglyceride, body mass index, and smoking. Postmortem pathological assessments included assessment of arteriolosclerosis severity using the same rating scale in three brain locations (basal ganglia, frontal, and parietal white matter regions) and four spinal cord levels (cervical, thoracic, lumbar and sacral levels). A single measure was used to summarize the severity of spinal arteriolosclerosis assessments at the four levels due to their high correlations. Average age at death was 91.5 (SD = 6.2) years, and 73% were women. Half showed arteriolosclerosis in frontal white matter and spinal cord followed by parietal white matter (38%) and basal ganglia (27%). The severity of arteriolosclerosis in all three brain locations showed mild-to-moderate correlations. By contrast, spinal arteriolosclerosis was associated with brain arteriolosclerosis only in frontal white matter. Higher DBP was associated with more severe arteriolosclerosis in all three brain locations. DM was associated with more severe arteriolosclerosis only in frontal white matter. Controlling for DBP, higher SBP was inversely associated with arteriolosclerosis in parietal white matter. Blood cholesterol and triglyceride, high body mass index, or smoking were not related to the severity of arteriolosclerosis in any brain region. None of the CVD-RFs were associated with the severity of spinal arteriolosclerosis. These data indicate that severity of arteriolosclerosis and its associations with CVD-RFs may vary in different CNS locations.

Association Between Late-Life Weight Change and Dementia: A Population-based Cohort Study

BACKGROUND

The impact of late-life weight changes on incident dementia is unclear. We aimed to investigate the associations of body mass index (BMI) and weight changes with dementia and to explore the role of APOE ɛ4 in these associations.

METHODS

A total of 1 673 dementia-free participants aged ≥60 and older were followed for an initial 6 years to detect changes in BMI/weight and then for an additional 6 years to detect incident dementia. BMI change ([BMIfirst 6-year follow-up - BMIbaseline]/BMIbaseline) was categorized as stable (≤5%), and moderate (5%-10%) or large (>10%) gain or loss. Weight change (weightfirst 6-year follow-up - weightbaseline) was categorized as stable (≤2.5 kg), and moderate (2.5-7.5 kg) or large (>7.5 kg) gain or loss. Dementia was diagnosed following standard criteria. Data were analyzed using Cox regression models.

RESULTS

Over the second 6-year follow-up period, 102 incident dementia cases were identified. Compared with stable BMI, the hazard ratios (95% CI) of dementia were 2.61 (1.09-5.54) and 2.93 (1.72-4.91) for BMI gain or loss >10%, respectively. The risk of dementia was higher among APOE ɛ4 carriers experiencing a large BMI gain (9.93 [3.49-24.6]) or loss (6.66 [2.83-14.4]) than APOE ɛ4 noncarriers with stable BMI. Similar results were observed for weight change and dementia associations.

CONCLUSIONS

BMI and weight changes showed U-shaped associations with dementia risk. Large bodyweight gain and loss alike are associated with an almost 3-fold higher risk of dementia, which may be amplified by APOE ɛ4.

Independent effect of body mass index variation on amyloid-β positivity

Objectives

The relationship of body mass index (BMI) changes and variability with amyloid-β (Aβ) deposition remained unclear, although there were growing evidence that BMI is associated with the risk of developing cognitive impairment or AD dementia. To determine whether BMI changes and BMI variability affected Aβ positivity, we investigated the association of BMI changes and BMI variability with Aβ positivity, as assessed by PET in a non-demented population.

Methods

We retrospectively recruited 1,035 non-demented participants ≥50 years of age who underwent Aβ PET and had at least three BMI measurements in the memory clinic at Samsung Medical Center. To investigate the association between BMI change and variability with Aβ deposition, we performed multivariable logistic regression. Further distinctive underlying features of BMI subgroups were examined by employing a cluster analysis model.

Results

Decreased (odds ratio [OR] = 1.68, 95% confidence interval [CI] 1.16–2.42) or increased BMI (OR = 1.60, 95% CI 1.11–2.32) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI variability. A greater BMI variability (OR = 1.73, 95% CI 1.07–2.80) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI change. We also identified BMI subgroups showing a greater risk of Aβ positivity.

Conclusion

Our findings suggest that participants with BMI change, especially those with greater BMI variability, are more vulnerable to Aβ deposition regardless of baseline BMI. Furthermore, our results may contribute to the design of strategies to prevent Aβ deposition with respect to weight control.