Obesity and Structural Brain Integrity in Older Women: The Women's Health Initiative Magnetic Resonance Imaging Study

DXA-Measured Abdominal Adipose Depots and Structural Brain Integrity in Postmenopausal Women

BACKGROUND

This study extends prior research from the MRI substudy of the Women's Health Initiative Memory Study (WHIMS-MRI) linking BMI to reduced brain atrophy and ischemic lesion load by examining DXA-based measurements of total body fat, total abdominal adipose tissue (TAT), abdominal visceral (VAT) and subcutaneous (SAT) adipose tissue, gynoid fat, and overall leg fat.

METHODS

The analytic sample consisted of 61 postmenopausal women (baseline mean age 69.5 [3.6]) enrolled in WHIMS-MRI who had undergone DXA scans. DXA scans were completed at years 0, 3, and 6, and MRI scans were conducted ~8 years after baseline. Adjusted linear regression models were used to analyze the association between adiposity averaged across the 3-time points and volumes of brain regions previously linked to dementia.

RESULTS

Higher levels of total body fat, TAT, VAT, SAT, gynoid, and overall leg fat were associated with larger hippocampal volume (β 0.02 [95% CI, 0.004-0.04]; 0.11 [0.02-0.21]; 0.26 [0.04-0.47]; 0.18 [0.03-0.33]; 0.18 [0.05-0.30]; 0.07 [0.009-0.12], respectively). No other significant associations were observed.

CONCLUSION

Higher levels of adiposity were positively associated with hippocampal volume. Additional research with larger sample sizes is needed to ascertain the significance of this association.

Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals

Abdominal fat is increasingly linked to brain health. A total of 10,001 healthy participants were scanned on 1.5T MRI with a short whole-body MR imaging protocol. Deep learning with FastSurfer segmented 96 brain regions. Separate models segmented visceral and subcutaneous abdominal fat. Regression analyses of abdominal fat types and normalized brain volumes were evaluated, controlling for age and sex. Logistic regression models determined the risk of brain total gray and white matter volume loss from the highest quartile of visceral fat and lowest quartile of these brain volumes. This cohort had an average age of 52.9 ± 13.1 years with 52.8% men and 47.2% women. Segmented visceral abdominal fat predicted lower volumes in multiple regions including: total gray matter volume (r = -.44, p<.001), total white matter volume (r =-.41, p<.001), hippocampus (r = -.39, p< .001), frontal cortex (r = -.42, p<.001), temporal lobes (r = -.44, p<.001), parietal lobes (r = -.39, p<.001), occipital lobes (r =-.37, p<.001). Women showed lower brain volumes than men related to increased visceral fat. Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 5.9; age 40-59, OR = 5.4; 60-80, OR = 5.1) and low white matter volume: (age 20-39: OR = 3.78; age 40-59, OR = 4.4; 60-80, OR = 5.1). Higher subcutaneous fat is related to brain volume loss. Elevated visceral and subcutaneous fat predicted lower brain volumes and may represent novel modifiable factors in determining brain health.

Associations between adiposity and white matter hyperintensities: Cross-sectional and longitudinal analyses of 34,653 participants

OBJECTIVES

White matter hyperintensities (WMH) increase the risk of stroke and cognitive impairment. This study aims to determine the cross-sectional and longitudinal associations between adiposity and WMH.

METHODS

Participants were enrolled from the UK Biobank cohort. Associations of concurrent, past, and changes in overall and central adiposity with WMH were investigated by linear and nonlinear regression models. The association of longitudinal adiposity and WMH volume changes was determined by a linear mixed model. Mediation analysis investigated the potential mediating effect of blood pressure.

RESULTS

In 34,653 participants with available adiposity measures and imaging data, the concurrent obese group had a 25.3% (β [95% CI] = 0.253 [0.222-0.284]) higher WMH volume than the ideal weight group. Increment in all adiposity measures was associated with a higher WMH volume. Among them, waist circumference demonstrated the strongest effect (β [95% CI] = 0.113 [0.101-0.125]). Past adiposity also demonstrated similar effects. Among the subset of 2664 participants with available WMH follow-up data, adiposity measures were predictive of WMH change. Regarding changes of adiposity, compared with ideal weight stable group, those who turned from ideal weight to overweight/obese had a 8.1% higher WMH volume (β [95% CI] = 0.081 [0.039-0.123]), while participants who turned from overweight/obese to ideal weight demonstrated no significant WMH volume change. Blood pressure partly meditates the associations between adiposity and WMH.

CONCLUSIONS

Both concurrent and past adiposity were associated with a higher WMH volume. The detrimental effects of adiposity on WMH occurred throughout midlife and in the elderly and may still exist after changes in obesity status.

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.

Severe Dementia Predicts Weight Loss by the Time of Death

Background: Body mass index (BMI) in midlife is associated with dementia. However, the association between BMI and late-life obesity is controversial. Few studies have investigated the association between BMI and cognitive performance near the time of death using data from autopsy examination. We aimed to investigate the association between BMI and dementia in deceased individuals who underwent a full-body autopsy examination.

Methods: Weight and height were measured before the autopsy exam. Cognitive function before death was investigated using the Clinical Dementia Rating (CDR) scale. The cross-sectional association between BMI and dementia was investigated using linear regression models adjusted for sociodemographic and clinical variables.

Results: We included 1,090 individuals (mean age 69.5 ± 13.5 years old, 46% women). Most participants (56%) had a normal BMI (18.5–24.9 kg/m²), and the prevalence of dementia was 16%. Twenty-four percent of the sample had cancer, including 76 cases diagnosed only by the autopsy examination. Moderate and severe dementia were associated with lower BMI compared with participants with normal cognition in fully adjusted models (moderate: β = −1.92, 95% CI = −3.77 to −0.06, p = 0.042; severe: β = −2.91, 95% CI = −3.97 to −1.86, p < 0.001).

Conclusion: BMI was associated with moderate and severe dementia in late life, but we did not find associations of BMI with less advanced dementia stages.

Association between Long-term Weight Change since Midlife and Risk of Incident Disabling Dementia among Elderly Japanese: the Ohsaki Cohort 2006 Study

Background

Both weight loss and cognitive impairment are common in late-life, but it remains unknown whether weight change is associated with risk of incident dementia among elderly Japanese. Our study aimed to investigate the association between long-term weight change since midlife and risk of incident disabling dementia using a community-based cohort study of elderly Japanese.

Methods

In 2006, we conducted a cohort study of 6,672 disability-free Japanese adults aged ≥65 years. In both 1994 and 2006, the participants reported their weight using a self-reported questionnaire. Based on weight obtained at these two time points, participants were classified into: stable weight (−1.4 to +1.4 kg), weight gain (≥+1.5 kg), and weight loss of −2.4 to −1.5 kg, −3.4 to −2.5 kg, −4.4 to −3.5 kg, −5.4 to −4.5 kg, and ≥−5.5 kg. Incident disabling dementia was retrieved from the public Long-term Care Insurance database. Participants were followed-up for 5.7 years (between April 2007 and November 2012). Cox proportional hazards model was used to estimate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident disabling dementia.

Results

During 32,865 person-years of follow-up, 564 participants were ascertained as having incident disabling dementia. Compared with stable weight, the multivariable-adjusted HRs were 0.97 (95% CI, 0.70–1.34) for weight loss of −2.4 to −1.5 kg, 0.98 (95% CI, 0.70–1.38) for −3.4 to −2.5 kg, 1.28 (95% CI, 0.91–1.81) for −4.4 to −3.5 kg, 1.27 (95% CI, 0.92–1.77) for −5.4 to −4.5 kg, and 1.64 (95% CI, 1.29–2.09) for ≥−5.5 kg.

Conclusion

Our study suggested that a ≥−3.5 kg weight loss over 12 years might be associated with higher risk of incident disabling dementia among elderly Japanese.

Neuroimaging of Sex/Gender Differences in Obesity: A Review of Structure, Function, and Neurotransmission

While the global prevalence of obesity has risen among both men and women over the past 40 years, obesity has consistently been more prevalent among women relative to men. Neuroimaging studies have highlighted several potential mechanisms underlying an individual’s propensity to become obese, including sex/gender differences. Obesity has been associated with structural, functional, and chemical alterations throughout the brain. Whereas changes in somatosensory regions appear to be associated with obesity in men, reward regions appear to have greater involvement in obesity among women than men. Sex/gender differences have also been observed in the neural response to taste among people with obesity. A more thorough understanding of these neural and behavioral differences will allow for more tailored interventions, including diet suggestions, for the prevention and treatment of obesity.

Pathways of Prevention: A Scoping Review of Dietary and Exercise Interventions for Neurocognition

Alzheimer's disease and related dementias (ADRD) represent an increasingly urgent public health concern, with an increasing number of baby boomers now at risk. Due to a lack of efficacious therapies among symptomatic older adults, an increasing emphasis has been placed on preventive measures that can curb or even prevent ADRD development among middle-aged adults. Lifestyle modification using aerobic exercise and dietary modification represents one of the primary treatment modalities used to mitigate ADRD risk, with an increasing number of trials demonstrating that exercise and dietary change, individually and together, improve neurocognitive performance among middle-aged and older adults. Despite several optimistic findings, examination of treatment changes across lifestyle interventions reveals a variable pattern of improvements, with large individual differences across trials. The present review attempts to synthesize available literature linking lifestyle modification to neurocognitive changes, outline putative mechanisms of treatment improvement, and discuss discrepant trial findings. In addition, previous mechanistic assumptions linking lifestyle to neurocognition are discussed, with a focus on potential solutions to improve our understanding of individual neurocognitive differences in response to lifestyle modification. Specific recommendations include integration of contemporary causal inference approaches for analyzing parallel mechanistic pathways and treatment-exposure interactions. Methodological recommendations include trial multiphase optimization strategy (MOST) design approaches that leverage individual differences for improved treatment outcomes.

Measures of obesity are associated with MRI markers of brain aging: The Northern Manhattan Study

OBJECTIVE

To examine associations between measures of obesity in middle to early-old age with later-life MRI markers of brain aging.

METHODS

We analyzed data from the Northern Manhattan MRI Sub-Study (n = 1,289). Our exposures of interest were body mass index (BMI), waist circumference (WC), waist-to-hip ratio, and plasma adiponectin levels. Our outcomes of interest were total cerebral volume (TCV), cortical thickness, white matter hyperintensity volume (WMHV), and subclinical brain infarcts (SBI). Using multivariable linear and logistic regression models adjusted for sociodemographics, health behaviors, and vascular risk factors, we estimated β coefficients (or odds ratios) and 95% confidence intervals (CIs) and tested interactions with age, sex, and race/ethnicity.

RESULTS

On average at baseline, participants were aged 64 years and had 10 years of education; 60% were women and 66% were Caribbean Hispanic. The mean (SD) time lag between baseline and MRI was 6 (3) years. Greater BMI and WC were significantly associated with thinner cortices (BMI β [95% CI] -0.089 [-0.153, -0.025], WC β [95% CI] -0.103 [-0.169, -0.037]) in fully adjusted models. Similarly, compared to those with BMI <25, obese participants (BMI ≥30) exhibited smaller cortical thickness (β [95% CI] -0.207 [-0.374, -0.041]). These associations were particularly evident for those aged <65 years. Similar but weaker associations were observed for TCV. Most associations with WMHV and SBI did not reach statistical significance.

CONCLUSIONS

Adiposity in early-old age is related to reduced global gray matter later in life in this diverse sample. Future studies are warranted to elucidate causal relationships and explore region-specific associations.

Body Weight Variation Patterns as Predictors of Cognitive Decline over a 5 Year Follow-Up among Community-Dwelling Elderly (MAPT Study)

This study aimed to analyze associations between weight variation patterns and changes in cognitive function and hippocampal volume among non-demented, community-dwelling elderly. Sample was formed of 1394 adults >70 years (63.9% female), all volunteers from the Multidomain Alzheimer Preventive Trial (MAPT). Weight loss was defined as ≥5% of body weight decrease in the first year of follow-up; weight gain as ≥5% of weight increase; and stability if <5% weight variation. Cognition was examined by a Z-score combining four tests. Measures were assessed at baseline, 6, 12, 24, 36, 48, and 60 months of follow-up. Hippocampal volume was evaluated with magnetic resonance imaging in 349 subjects in the first year and at 36 months. Mixed models were performed. From the 1394 participants, 5.5% (n = 76) presented weight loss, and 9.0% (n = 125) presented weight gain. Cognitive Z-score decreased among all groups after 5 years, but decline was more pronounced among those who presented weight loss (adjusted between-group mean difference vs. stable: -0.24, 95%CI: -0.41 to -0.07; p = 0.006). After 3 years, hippocampal atrophy was observed among all groups, but no between-group differences were found. In conclusion, weight loss ≥5% in the first year predicted higher cognitive decline over a 5 year follow-up among community-dwelling elderly, independently of body mass index.

Sex differences in brain aging and predictors of neurodegeneration in cognitively healthy older adults

We evaluated sex differences in MRI-based volume loss and differences in predictors of this neurodegeneration in cognitively healthy older adults. Mixed-effects regression was used to compare regional brain volume trajectories of 295 male and 328 female cognitively healthy Baltimore Longitudinal Study of Aging participants, aged 55-92 years, with up to 20 years of follow-up and to assess sex differences in the associations of age, hypertension, obesity, APOE e4 carrier status, and high-density lipoprotein cholesterol with regional brain volume trajectories. For both sexes, older age was associated with steeper volumetric declines in many brain regions, with sex differences in volume loss observed in frontal, temporal, and parietal regions. In males, hypertension and higher high-density lipoprotein cholesterol were protective against volume loss in the hippocampus, entorhinal cortex, and parahippocampal gyrus. In females, hypertension was associated with steeper volumetric decline in gray matter, and obesity was protective against volume loss in temporal gray matter. Predictors of volume change may affect annual rates of volume change differently between men and women.

Lifestyle Risk Factors and Findings on Brain Magnetic Resonance Imaging of Older Adult American Indians: The Strong Heart Study

BACKGROUND

Clinical stroke is prevalent in American Indians, but the lifestyle risk factors for vascular brain injury have not been well-studied in this population. The purpose of this study was to correlate brain magnetic resonance imaging (MRI) findings with obesity, alcohol use, and smoking behaviors in elderly American Indians from the Strong Heart Study.

METHODS

Cranial MRI scans (n = 789) were analyzed for dichotomous measures of infarcts, hemorrhages, white matter hyperintensities (WMH), and cerebral atrophy and continuous measures of total brain, WMH, and hippocampal volume. Poisson regression was used to estimate prevalence ratios, and linear regression was used to estimate measures of association for continuous outcomes. Models were adjusted for the risk factors of interest as well as age, sex, study site, income, education, hypertension, diabetes, and low-density lipoprotein cholesterol.

RESULTS

Smoking was associated with increased hippocampal atrophy (p = 0.002) and increased prevalence of sulcal widening (p < 0.001). Relative to nonsmokers, smokers with more than 25 pack-years of smoking had a 27% (95% CI 7-47%) increased prevalence of high-grade sulci, p = 0.005. Body mass index was inversely associated with prevalence of nonlacunar infarcts and sulcal widening (all p = 0.004). Alcohol use was not significantly associated with any of the measured MRI findings.

CONCLUSIONS

This study found similar associations between smoking and vascular brain injury among American Indians, as seen in other populations. In particular, these findings support the role of smoking as a key correlate for cerebral atrophy.

Association Between Insulin Resistance, Plasma Leptin, and Neurocognition in Vascular Cognitive Impairment

BACKGROUND

Greater body weight has been associated impairments in neurocognition and greater dementia risk, although the mechanisms linking weight and neurocognition have yet to be adequately delineated.

OBJECTIVE

To examine metabolic mechanisms underlying the association between obesity and neurocognition.

METHODS

We conducted a secondary analysis of weight, neurocognition, and the potentially mediating role of metabolic and inflammatory biomarkers among 160 participants from the ENLIGHTEN trial of vascular cognitive impairment, no dementia (CIND). Neurocognition was assessed using a 45-minute assessment battery assessing Executive Function, Verbal and Visual Memory. We considered three metabolic biomarkers: insulin resistance (homeostatic model assessment [HOMA-IR]), plasma leptin, and insulin-like growth factor (IGF-1). Inflammation was assessed using C-reactive protein. Multiple regression analyses were used.

RESULTS

Participants included 160 sedentary older adults with CIND. Participants tended to be overweight or obese (mean BMI = 32.5 [SD = 4.8]). Women exhibited higher BMI (p = 0.043), CRP (p < 0.001), and leptin (p < 0.001) compared with men. Higher BMI levels were associated with worse performance on measures of Executive Function (β= -0.16, p = 0.024) and Verbal Memory (β= -0.16, p = 0.030), but not Visual Memory (β= 0.05, p = 0.500). Worse metabolic biomarker profiles also were associated with lower Executive Function (β= -0.12, p = 0.050). Mediation analyses suggested leptin was a plausible candidate as a mediator between BMI and Executive Function.

CONCLUSIONS

In overweight and obese adults with vascular CIND, the association between greater weight and poorer executive function may be mediated by higher leptin resistance.

Obesity and Alzheimer's disease, does the obesity paradox really exist? A magnetic resonance imaging study

Mid-life obesity is an established risk factor for Alzheimer's disease (AD) dementia, whereas late-life obesity has been proposed as a protective state. Weight loss, which predates cognitive decline, might explain this obesity paradox on AD risk. We aimed to assess the impact of late life obesity on brain structure taking into account weight loss as a potential confounder. We included 162 elderly controls of the Alzheimer's Disease Neuroimaging Initiative (ADNI) with available 3T MRI scan. Significant weight loss was defined as relative weight loss ≥5% between the baseline and last follow-up visit. To be able to capture weight loss, only subjects with a minimum clinical and anthropometrical follow-up of 12 months were included. Individuals were categorized into three groups according to body mass index (BMI) at baseline: normal-weight (BMI<25 Kg/m2), overweight (BMI 25-30 Kg/m2) and obese (BMI>30 Kg/m2). We performed both an interaction analysis between obesity and weight loss, and stratified group analyses in the weight-stable and weigh-loss groups. We found a significant interaction between BMI and weight loss affecting brain structure in widespread cortical areas. The stratified analyses showed atrophy in occipital, inferior temporal, precuneus and frontal regions in the weight stable group, but increased cortical thickness in the weight-loss group. In conclusion, our data support that weight loss negatively confounds the association between late-life obesity and brain atrophy. The obesity paradox on AD risk might be explained by reverse causation.

Microvascular Endothelial Function and Neurocognition Among Adults With Major Depressive Disorder

BACKGROUND

Cardiovascular risk factors (CVRFs) and endothelial dysfunction have been associated independently with poorer neurocognition in middle-aged adults, particularly on tests of frontal lobe function. However, to our knowledge, no studies have examined markers of microvascular dysfunction on neurocognition or the potential interaction between macro- and microvascular biomarkers on neurocognition in middle-aged and older adults with major depressive disorder (MDD).

METHODS

Participants included 202 adults with MDD who were not receiving mental health treatment. Microvascular endothelial function was assessed using a noninvasive marker of forearm reactive hyperemia velocity while macrovascular endothelial function was assessed using flow-mediated dilation (FMD) of the brachial artery. CVRFs were assessed using the Framingham Stroke Risk Profile and fasting lipid levels. A standardized neurocognitive assessment battery was used to assess three cognitive domains: executive function, working memory, and verbal memory.

RESULTS

Greater microvascular dysfunction was associated with poorer neurocognition across all three domains. Microvascular function continued to predict verbal memory performance after accounting for background factors and CVRFs. Macro- and microvascular function interacted to predict working memory performance (F = 4.51_{1, 178}, p = 0.035), with a similar nonsignificant association for executive function (F = 2.73_{1, 178}, p = 0.095), with moderate associations observed between microvascular function and neurocognition in the presence of preserved FMD (r₆₁ = 0.40, p = 0.001), but not when FMD was impaired (r₆₃ = -0.05, p = 0.675).

CONCLUSION

Greater microvascular dysfunction is associated with poorer neurocognition among middle-aged and older adults. This association was strongest in participants with preserved macrovascular function.

Longitudinal microstructural changes of cerebral white matter and their association with mobility performance in older persons

Mobility impairment in older persons is associated with brain white matter hyperintensities (WMH), a common finding in magnetic resonance images and one established imaging biomarker of small vessel disease. The contribution of possible microstructural abnormalities within normal-appearing white matter (NAWM) to mobility, however, remains unclear. We used diffusion tensor imaging (DTI) measures, i.e. fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), to assess microstructural changes within supratentorial NAWM and WMH sub-compartments, and to investigate their association with changes in mobility performance, i.e. Tinetti assessment and the 2.5-meters walk time test. We analyzed baseline (N = 86, age ≥75 years) and 4-year (N = 41) follow-up data. Results from cross-sectional analysis on baseline data showed significant correlation between WMH volume and NAWM-FA (r = -0.33, p = 0.002), NAWM-AD (r = 0.32, p = 0.003) and NAWM-RD (r = 0.39, p = 0.0002). Our longitudinal analysis showed that after 4-years, FA and AD decreased and RD increased within NAWM. In regional tract-based analysis decrease in NAWM-FA and increase in NAWM-RD within the genu of the corpus callosum correlated with slower walk time independent of age, gender and WMH burden. In conclusion, global DTI indices of microstructural integrity indicate that significant changes occur in the supratentorial NAWM over four years. The observed changes likely reflect white matter deterioration resulting from aging as well as accrual of cerebrovascular injury associated with small vessel disease. The observed association between mobility scores and regional measures of NAWM microstructural integrity within the corpus callosum suggests that subtle changes within this structure may contribute to mobility impairment.

Long-term Impact of Weight Loss Intervention on Changes in Cognitive Function: Exploratory Analyses from the Action for Health in Diabetes Randomized Controlled Clinical Trial

Background

Diabetes adversely impacts cognition. Lifestyle change can improve diabetes control and potentially improve cognition. We examined whether weight loss through reduced caloric intake and increased physical activity was associated with slower cognitive aging in older adults with type 2 diabetes mellitus.

Methods

The Look AHEAD randomized controlled clinical trial delivered 10 years of intensive lifestyle intervention (ILI) that yielded long-term weight losses. During 5 years spanning the end of intervention and postintervention follow-up, repeated cognitive assessments were obtained in 1,091 individuals who had been assigned to ILI or a control condition of diabetes support and education (DSE). We compared the means and slopes of scores on cognitive testing over these repeated assessments.

Results

Compared with DSE, assignment to ILI was associated with a -0.082 SD deficit in mean global cognitive function across repeated assessments (p = .010). However, overweight (body mass index [BMI] < 30 kg/m2) ILI participants had 0.099 (95% confidence interval [CI]: -0.006, 0.259) better mean global cognitive function compared with overweight DSE participants, while obese (BMI ≥ 30 kg/m2) ILI participants had -0.117 (-0.185, -0.049) SD worse mean composite cognitive function scores (interaction p = .014) compared to obese DSE participants. For both overweight and obese participants, cognitive decline was marginally (-0.014 SD/y overall) steeper for ILI participants (p = .068), with 95% CI for differences in slopes excluding 0 for measures of attention and memory.

Conclusions

The behavioral weight loss intervention was associated with small relative deficits in cognitive function among individuals who were obese and marginally greater cognitive decline overall compared to control. ClinicalTrials.gov Identifier: NCT00017953.

Diffuse microvascular dysfunction and loss of white matter integrity predict poor outcomes in patients with acute ischemic stroke

We sought to investigate the relationship between blood-brain barrier (BBB) permeability and microstructural white matter integrity, and their potential impact on long-term functional outcomes in patients with acute ischemic stroke (AIS). We studied 184 AIS subjects with perfusion-weighted MRI (PWI) performed <9 h from last known well time. White matter hyperintensity (WMH), acute infarct, and PWI-derived mean transit time lesion volumes were calculated. Mean BBB leakage rates (K2 coefficient) and mean diffusivity values were measured in contralesional normal-appearing white matter (NAWM). Plasma matrix metalloproteinase-2 (MMP-2) levels were studied at baseline and 48 h. Admission stroke severity was evaluated using the NIH Stroke Scale (NIHSS). Modified Rankin Scale (mRS) was obtained at 90-days post-stroke. We found that higher mean K2 and diffusivity values correlated with age, elevated baseline MMP-2 levels, greater NIHSS and worse 90-day mRS (all p < 0.05). In multivariable analysis, WMH volume was associated with mean K2 ( p = 0.0007) and diffusivity ( p = 0.006) values in contralesional NAWM. In summary, WMH severity measured on brain MRI of AIS patients is associated with metrics of increased BBB permeability and abnormal white matter microstructural integrity. In future studies, these MRI markers of diffuse cerebral microvascular dysfunction may improve prediction of cerebral tissue infarction and functional post-stroke outcomes.

Weight loss in the healthy elderly might be a non-cognitive sign of preclinical Alzheimer's disease

Weight loss has been proposed as a sign of pre-clinical Alzheimer Disease (AD). To test this hypothesis, we have evaluated the association between longitudinal changes in weight trajectories, cognitive performance, AD biomarker profiles and brain structure in 363 healthy controls from the Alzheimer´s Disease Neuroimaging Initiative (mean follow-up 50.5±30.5 months). Subjects were classified according to body weight trajectory into a weight loss group (WLG; relative weight loss ≥ 5%) and a non-weight loss group (non-WLG; relative weight loss < 5%). Linear mixed effects models were used to estimate the effect of body weight changes on ADAS-Cognitive score across time. Baseline CSF tau/AΔ₄₂ ratio and AV45 PET uptake were compared between WLG and non-WLG by analysis of covariance. Atrophy maps were compared between groups at baseline and longitudinally at a 2-year follow-up using Freesurfer. WLG showed increased baseline levels of cerebrospinal fluid tau/AΔ₄₂ ratio, increased PET amyloid uptake and diminished cortical thickness at baseline. WLG also showed faster cognitive decline and faster longitudinal atrophy. Our data support weight loss as a non-cognitive manifestation of pre-clinical AD.

Higher Adiposity Is Associated With Slower Cognitive Decline in Hypertensive Patients: Secondary Analysis of the China Stroke Primary Prevention Trial

BACKGROUND

Obesity is a risk factor for many diseases. However, the potential association between adiposity and cognitive decline in hypertensive patients is inconclusive. We performed a secondary data analysis of the CSPPT (China Stroke Primary Prevention Trial) to examine whether adiposity is correlated with longitudinal cognitive performance in hypertensive adults.

METHODS AND RESULTS

The analysis included 16 791 patients in the CSPPT who received at least 2 cognitive assessments by the Mini-Mental State Examination (MMSE) during the follow-up (median, 4.5 years; interquartile range, 4.2-4.8 years). Outcomes included changes in MMSE scores and cognitive impairment (defined as MMSE score less than education-specific cutoff point). A marked reduction in MMSE scores at the final (compared with at the 1-year) follow-up was apparent in both men (n=4838; mean [SD] score, 0.41 [3.62]) and women (n=7190; mean [SD] score, 1.07 [4.61]; both P<0.001). Analysis using a mixed-effects model revealed an association between higher body mass index with less MMSE decline, even after controlling for demographics and comorbidities (men, β=0.0134 [SE, 0.0036]; women, β=0.0133 [SE, 0.0034]; both P<0.001). A total of 1037 men (15.3%) and 3317 women (33.1%) developed cognitive impairment. In multivariable Cox regression analyses, being obese in men (11.3% versus 18.0%; hazard ratio, 0.75; 95% confidence interval, 0.60-0.94) and women (30.1% versus 36.5%; hazard ratio, 0.82; 95% confidence interval, 0.74-0.91) was a protective factor against cognitive impairment compared with normal body mass index.

CONCLUSIONS

Higher adiposity is independently associated with slower cognitive decline in Chinese hypertensive adults.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00794885 CSPPT.

Associations of Brain Structure With Adiposity and Changes in Adiposity in a Middle-Aged and Older Biracial Population

Background

Studies of adiposity and brain pathology in African Americans (AA) are sparse despite higher rates of obesity, dementia, and dementia-associated brain pathology in AA. This study examined relations of adiposity to white matter hyperintensities (WMH) and total brain volume (TBV) in AA and non-Hispanic whites (NHW).

Methods

Waist circumference (WC) and body mass index (BMI) were measured in the Genetic Epidemiology Network of Arteriopathy study at Visits 1 (mean age 57 [±11]) and 2 (mean age 61 [±10], mean 5.2 years later). Brain MRIs were obtained shortly after Visit 2 in 1,702 participants (64% women, 48% AA). Multilevel linear regression using generalized estimating equation estimated associations of adiposity (cross-sectional) or adiposity changes with WMH (accounting for intracranial size) or TBV adjusting for demographics, cardiovascular risk factors, and incorporating adiposity-by-race interactions. Adiposity-by-age interactions were examined.

Results

Concurrent TBV was inversely associated with BMI (β = -2.76 [95% confidence interval (CI): -4.99, -0.53]) and WC (β = -2.19 [CI: -4.04, -0.34]). Concurrent WMH were negatively associated with BMI (β = -0.04 [CI: -0.06, -0.01]) and, among NHW, with WC (β = -0.04 [CI: -0.06, -0.02]) but not with changes in BMI or WC. BMI increases were associated with lower TBV (β = -16.20, [CI: -30.34, -2.06]) in AA but not in NHW (β = -2.76 [CI: -14.02, 8.51]), although race-by-adiposity interactions were not supported. WC increases were not associated with MRI outcomes.

Conclusion

Greater measures of obesity and increases in measures of obesity, which are common in mid-life, could be detrimental to brain health, particularly in AA.

Baseline gray- and white-matter volume predict successful weight loss in the elderly

OBJECTIVE

The purpose of this study was to investigate whether structural brain phenotypes could be used to predict weight loss success following behavioral interventions in older adults with overweight or obesity and cardiometabolic dysfunction.

METHODS

A support vector machine with a repeated random subsampling validation approach was used to classify participants into the upper and lower halves of the weight loss distribution following 18 months of a weight loss intervention. Predictions were based on baseline brain gray matter and white matter volume from 52 individuals who completed the intervention and a magnetic resonance imaging session.

RESULTS

The support vector machine resulted in an average classification accuracy of 72.62% based on gray matter and white matter volume. A receiver operating characteristic analysis indicated that classification performance was robust based on an area under the curve of 0.82.

CONCLUSIONS

Findings suggest that baseline brain structure was able to predict weight loss success following 18 months of treatment. The identification of brain structure as a predictor of successful weight loss was an innovative approach to identifying phenotypes for responsiveness to intensive lifestyle interventions. This phenotype could prove useful in future research focusing on the tailoring of treatment for weight loss.