Unstable Body Mass Index and Progression to Probable Alzheimer’s Disease Dementia in Patients with Amnestic Mild Cognitive Impairment

Sex differences in metabolic phenotype and hypothalamic inflammation in the 3xTg-AD mouse model of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is notably associated with cognitive decline resulting from impaired function of hippocampal and cortical areas; however, several other domains and corresponding brain regions are affected. One such brain region is the hypothalamus, shown to atrophy and develop amyloid and tau pathology in AD patients. The hypothalamus controls several functions necessary for survival, including energy and glucose homeostasis. Changes in appetite and body weight are common in AD, often seen several years prior to the onset of cognitive symptoms. Therefore, altered metabolic processes may serve as a biomarker for AD, as well as a target for treatment, considering they are likely both a result of pathological changes and contributor to disease progression. Previously, we reported sexually dimorphic metabolic disturbances in ~ 7-month-old 3xTg-AD mice, accompanied by differences in systemic and hypothalamic inflammation.

METHODS

In the current study, we investigated metabolic outcomes and hypothalamic inflammation in 3xTg-AD males and females at 3, 6, 9, and 12 months of age to determine when these sex differences emerge.

RESULTS

In agreement with our previous study, AD males displayed less weight gain and adiposity, as well as reduced blood glucose levels following a glucose challenge, compared to females. These trends were apparent by 6-9 months of age, coinciding with increased expression of inflammatory markers (Iba1, GFAP, TNF-α, and IL-1β) in the hypothalamus of AD males.

CONCLUSIONS

These findings provide additional evidence for sex-dependent effects of AD pathology on energy and glucose homeostasis, which may be linked to hypothalamic inflammation.

Molecular Aspects of a Diet as a New Pathway in the Prevention and Treatment of Alzheimer's Disease

Alzheimer's disease is the most common cause of dementia in the world. Lack of an established pathology makes it difficult to develop suitable approaches and treatment for the disease. Besides known hallmarks, including amyloid β peptides cumulating in plaques and hyperphosphorylated tau forming NFTs, inflammation also plays an important role, with known connections to the diet. In AD, adhering to reasonable nutrition according to age-related principles is recommended. The diet should be high in neuroprotective foods, such as polyunsaturated fatty acids, antioxidants, and B vitamins. In addition, foods capable of rising BDNF should be considered because of the known profitable results of this molecule in AD. Adhering to beneficial diets might result in improvements in memory, cognition, and biomarkers and might even reduce the risk of developing AD. In this review, we discuss the effects of various diets, foods, and nutrients on brain health and possible connections to Alzheimer's disease.

D’Cunha N, Tsiampalis T, Zec M, Sergi D, Travica N, Marx W, McKune AJ, Panagiotakos DB, Naumovski N. Metabolically Healthy Overweight and Obesity, Transition to Metabolically Unhealthy Status and Cognitive Function: Results from the Framingham Offspring Study

AIMS

To evaluate the association between metabolically healthy overweight/obesity (MHO) status and longitudinal cognitive function while also considering the stability of the condition.

METHODS

In total, 2892 participants (mean age 60.7 (9.4) years) from Framingham Offspring Study completed health assessments every four years since 1971. Neuropsychological testing was repeated every four years starting from 1999 (Exam 7) to 2014 (Exam 9) (mean follow-up: 12.9 (3.5) years). Standardized neuropsychological tests were constructed into three factor scores (general cognitive performance, memory, processing speed/executive function). Healthy metabolic status was defined as the absence of all NCEP ATP III (2005) criteria (excluding waist circumference). MHO participants who scored positively for one or more of NCEP ATPIII parameters in the follow-up period were defined as unresilient MHO.

RESULTS

No significant difference on the change in cognitive function over time was observed between MHO and metabolically healthy normal weight (MHN) individuals (all p > 0.05). However, a lower processing speed/executive functioning scale score was observed in unresilient MHO participants compared to resilient MHO participants (β = -0.76; 95% CI = -1.44, -0.08; p = 0.030).

CONCLUSIONS

Retaining a healthy metabolic status over time represents a more important discriminant in shaping cognitive function compared to body weight alone.

Association of Early Weight Change With Cognitive Decline in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVE

To examine whether early weight change is associated with subsequent deterioration in cognitive function, including overall performance and specific domains, in Parkinson disease (PD).

METHODS

This observational study used data from the Parkinson Progression Markers Initiative cohort. The patients underwent annual nonmotor assessments covering neuropsychiatric, sleep-related, and autonomic symptoms for up to 8 years of follow-up. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) and detailed neuropsychological testing. Linear mixed-effects models were applied to investigate the association of early weight change with longitudinal evolution of cognitive and other nonmotor symptoms.

RESULTS

A total of 358 patients with early PD were classified into weight loss (decrease of >3% body weight during the first year; n = 98), weight maintenance (within ±3%; n = 201), and weight gain (increase of >3%; n = 59) groups. The weight loss group showed a significantly faster decline in MoCA scores than the weight maintenance group (β = -0.19, 95% CI -0.28 to -0.10). With respect to specific cognitive domains, the weight loss group showed a steeper decline in sematic fluency test scores (β = -0.37, 95% CI -0.66 to -0.08) and MoCA phonemic fluency scores (β = -0.18, 95% CI -0.31 to -0.05) and, to a lesser extent, Letter-Number Sequencing scores (β = -0.07, 95% CI -0.14 to 0.01) compared with the weight maintenance group. Conversely, the weight gain group showed a slower decline in the Symbol Digit Modalities Test scores (β = 0.34, 95% CI 0.05 to 0.63), although no association was found with longitudinal changes in MoCA scores. We did not find any significant effects of weight change on the progression of other nonmotor symptoms.

DISCUSSION

Early weight loss was associated with a faster progression of decline in global cognitive function and executive function in patients with PD, whereas early weight gain was associated with a slower progression of decline in processing speed and attention. The impact of early weight change on nonmotor symptoms seemed to be specific to cognition.

Time restricted feeding is associated with poor performance in specific cognitive domains of Suburb-Dwelling older Chinese

The purpose of this study was to investigate the association between time restricted feeding (TRF) and different areas of cognitive function in the elderly in Chinese communities. This study consisted of 1353 community-dwelling Chinese older adults aged 60 years and older in Chongming area, Shanghai (563 males; the mean age, 73.38 ± 6.16 years). Mild cognitive impairment (MCI) and six different cognitive domains was assessed by the Chinese-version of Mini Mental State Examination (MMSE). Recording the eating time of each meal through oral inquiry to calculate the time window between the first meal and the last meal of the average day. Participants with an eating time window duration of more than 10 h were then identified, as well as those with eating time restricted to less than 10 h (TRF). Our study found that TRF may be associated with a higher incidence rate of cognitive impairment. TRF only limited the eating time window and did not change the frequency of participants' dietary intake. We used a linear regression model to study the association of TRF with cognitive function. After adjusting for confounding variables, the results showed that TRF was related to MMSE score (P < 0.001), "Orientation to place" (P < 0.001) and "Attention/calculation" (P < 0.001) functions. Among Chinese older community-dwellers, TRF was associated with a higher prevalence of CI and negatively correlated with the "Orientation to place" and "attention/calculation" functions.

Concepts of dementia prevention in the health promotion among older adults: A narrative review

The number of older adults with dementia is predicted to markedly increase in the coming decades. A person suffers from dementia every 3 seconds globally, and one out of every 7 people suffers from dementia in Taiwan. The purpose of this narrative review is to integrate existing concepts of dementia prevention into health promotion and improve older adults' quality of life. This narrative review was performed using the PubMed database by searching for basic research and systematic reviews on dementia prevention and health promotion among older adults. We established a framework for dementia prevention and health promotion with regard to the physical, mental, spiritual, and social health aspects. We identified the following strategies related to older adults towards dementia prevention and health promotion in follows: Physical health promotion: cognitive activities, physical activities, body mass index, balanced diet, rainbow diet, Mediterranean diet, dietary approaches to stop hypertension diet, mind diet, no smoking and drinking, avoiding the "three highs" (i.e., hyperglycemia, hyperlipidemia, and hypertension), and head trauma; Mental health promotion: Positive thinking, Brief Symptom Rating Scale (BSRS-5), depression scale, and ascertained dementia 8 questionnaire (AD8) screening; Spiritual health promotion: religious beliefs, spiritual music, meditative activities, mindfulness, yoga, Qi-gong, Tai-chi, and Baduanjin; and Social health promotion: A supportive family system, socialization, social support, social networks, social interaction, and social participation. The conclusion of this narrative review was to integrate the concepts of dementia prevention and health promotion among older adults.

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.

An application study-subjective cognitive decline Questionnaire9 in detecting mild cognitive impairment (MCI)

Objective: Subjective cognitive decline (SCD) complaints as the early manifestation of mild cognitive impairment (MCI) may be harbingers of objective cognitive decline. SCD-questinnaire9 (SCD-Q9) is developed to investigate the early sign for MCI. However, few studies have reported its power for discriminating MCI from healthy controls (HCs). Therefore, this study aims to investigate the discrimination power of SCD-Q9 as a brief screening tool for early detection of SCD in MCI.Methods: 84 HCs and 205 people with MCI were recruited. Their demographic information and scores of SCD-Q9 were compared. A binary logistic regression model was used to analyze the potential affecting factors of MCI, and the Receiver Operating Characteristic analysis was applied to test the discrimination powers of those factors, including SCD-Q9.Results: (1) Single and total scores of SCD-Q9 were all lower in the MCI group than those in the HC group. (2) Ageing, lower education and higher total scores of SCD-Q9 were associated with MCI. (3) Area Under the Curves (AUC) of SCD-Q9 for discriminating MCI from HC group was 0.815 and when integrating age and education, the AUC improved slightly and reached 0.839. Additionally, the sensitivity and specificity were 68.8% and 85.7%, respectively when a cut-off value of 3 was applied. Conclusions: SCD-Q9 may be able to detect the subjective cognitive decline in MCI early, but it may be used together with other screening questionnaires to improve its sensitivity and further verification of its power is needed.

Pathogenesis, Murine Models, and Clinical Implications of Metabolically Healthy Obesity

Although obesity is commonly associated with numerous cardiometabolic pathologies, some people with obesity are resistant to detrimental effects of excess body fat, which constitutes a condition called “metabolically healthy obesity” (MHO). Metabolic features of MHO that distinguish it from metabolically unhealthy obesity (MUO) include differences in the fat distribution, adipokine types, and levels of chronic inflammation. Murine models are available that mimic the phenotype of human MHO, with increased adiposity but preserved insulin sensitivity. Clinically, there is no established definition of MHO yet. Despite the lack of a uniform definition, most studies describe MHO as a particular case of obesity with no or only one metabolic syndrome components and lower levels of insulin resistance or inflammatory markers. Another clinical viewpoint is the dynamic and changing nature of MHO, which substantially impacts the clinical outcome. In this review, we explore the pathophysiology and some murine models of MHO. The definition, variability, and clinical implications of the MHO phenotype are also discussed. Understanding the characteristics that differentiate people with MHO from those with MUO can lead to new insights into the mechanisms behind obesity-related metabolic derangements and diseases.

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.

Association Between Physical Performance and Cognitive Function in Chinese Community-Dwelling Older Adults: Serial Mediation of Malnutrition and Depression

Purpose

We aimed to propose a serial mediational model to further analyze the relationship between poor physical performance, malnutrition, depression and cognitive impairment in Chinese community-dwelling older adults.

Patients and Methods

This study consisted of 1386 community-dwelling Chinese older adults aged 65 years and older in Shanghai, China. Mild cognitive impairment (MCI) was assessed by the Mini-Mental State Examination (MMSE) and Instrumental Activities Of Daily Living (IADL). Physical performance was assessed by short physical performance battery (SPPB). Malnutrition was defined with the Mini Nutritional Assessment (MNA). Depressive symptoms were evaluated by the 30-item Geriatric Depression Scale (GDS). Serial multiple mediator models were used.

Results

The mean age of the final analysis sample was 73.62±6.14, and 57.6% (n=809) were females. The prevalence of MCI was 14.35% (n=199). Physical performance (p<0.001), nutritional status (p=0.025), and depressive symptoms (p=0.002) were correlated with MCI. The serial mediational model revealed that MNA and GDS scores significantly mediated association of SPPB and MMSE scores (c'=0.4728, p<0.001). Furthermore, depressive symptoms significantly mediated the association of physical performance and cognition (p=0.0311), while malnutrition had no independent mediating effect between these two factors (p=0.794).

Conclusion

Our study examined the serial multiple mediation roles of nutritional status and depressive symptoms on the relationship between physical performance and cognitive function in community-dwelling Chinese older adults. Older adults who were in poor physical condition tend to have worse nutritional status, more severe depression, and poorer cognitive function.

The risk of Alzheimer's disease according to dynamic changes in metabolic health and obesity: a nationwide population-based cohort study

We evaluated the association of metabolic health and obesity phenotypes with the risk of Alzheimer's disease (AD). This study enrolled 136,847 elderly participants aged 60 or above from the Korean National Health Insurance System. At baseline examinations in 2009 and 2010, subjects were categorized into four groups: the metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) groups. Based on the phenotypic transition after 2 years, the subjects were further categorized into 16 subgroups. They were followed from 2009 to 2015 to monitor for AD development. The MHO phenotype protected subjects from AD, relative to the MHNO phenotype (HR, 0.73; 95% CI, 0.65-0.81). Among subjects initially classified as MHO, 41.8% remained MHO, with a significantly lower risk of AD compared with the stable MHNO group (HR, 0.62; 95% CI, 0.50-0.77). Among MUO subjects at baseline, those who changed phenotype to MUNO were at higher risk of AD (HR, 1.47; 95% CI, 1.28-1.70), and the transition to the MHO phenotype protected subjects from AD (HR, 0.62; 95% CI, 0.50-0.78). The MHO phenotype conferred a decreased risk of AD. Maintenance or recovery of metabolic health might mitigate AD risk among obese individuals.

Weight Loss and the Risk of Dementia: A Meta-analysis of Cohort Studies

BACKGROUND

Weight loss is a common phenomenon among the elderly and is identified as an important indicator of health status. Many epidemiology studies have investigated the association between weight loss and dementia, but the results were inconsistent.

OBJECTIVE

To examine and determine the association between weight loss and the risk of dementia.

METHODS

Eligible cohort studies involving weight loss and dementia were searched from PubMed, Embase, and Ovid databases through October 2018. Pooled relative risks (RRs) with its 95% confidence intervals (CIs) were used to estimate the effects of weight loss on the risk of dementia. Subgroup and sensitivity analyses were performed to explore the potential sources of heterogeneity. The Begg's test and Egger's test were used to assess the publication bias.

RESULTS

A total of 20 cohort studies with 38,141 participants were included in this meta-analysis. Weight loss was significantly associated with the risk of dementia (RR=1.26, 95% CI=1.15-1.38). BMI decline ≥0.8 units (RR=1.31, 95% CI=1.10-1.56) and ≥4% (RR=1.19, 95% CI=1.03-1.38) could increase the risk of dementia. The risk of all-cause dementia for people with weight loss increased by 31% (RR=1.31, 95% CI=1.15-1.49), and 25% higher for incident Alzheimer's disease (RR=1.25, 95% CI=1.07-1.46). Weight loss in participants with normal weight had a similar dementia risk (RR=1.21, 95% CI=1.06-1.38) with the overweight individuals (RR=1.22, 95% CI=1.11-1.34).

CONCLUSION

Weight loss may be associated with an increased risk of dementia, especially for Alzheimer's disease. Maintaining weight stability may help prevent dementia.

Metabolically healthy obesity and lipids may be protective factors for pathological changes of alzheimer's disease in cognitively normal adults

The associations between obesity and Alzheimer's disease (AD) at different ages have been debated. Recent evidence implied the protective effects of metabolically healthy obesity on AD. We hypothesized that obesity and lipids could mitigate the detrimental impacts of AD pathological changes among metabolically healthy individuals in late life. In this study, a total of 604 metabolically healthy participants with normal cognition were included from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) database. Multiple linear regression models were used to test the associations of body mass index (BMI) or lipids with cerebrospinal fluid (CSF) biomarkers after adjustment for age, gender, education, and Apolipoprotein E-ɛ4 (APOE-ɛ4). The results showed the lower CSF levels of total tau protein (t-tau: p = .0048) and phosphorylated tau protein (p-tau: p = .0035) in obese participants than in non-obese participants, even after correcting for covariates. Moreover in late life, higher BMI was associated with decreased CSF t-tau (β: -0.15, p = .0145) and p-tau (β: -0.17, p = .0052). As for lipids, higher levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) were associated with decreased CSF t-tau (TC: β: -0.16, p = .0115; LDL-C: β: -0.16, p = .0082) and p-tau (TC: β: -0.15, p = .0177; LDL-C: β: -0.14, p = .0225) in obese participants. Furthermore, these associations were only significant in participants with late-life obesity and APOE-ɛ4 non-carriers. Overall, in a cognitively normal population, we found metabolically healthy obesity and lipids in late life might be protective factors for neurodegenerative changes.

Variability in body weight precedes diagnosis in dementia: A nationwide cohort study

BACKGROUND

While there have been disagreements concerning whether obesity and increase in body weight elevate the risk of dementia, variability in body weight has been recently recognized as a new biometric associated with a high risk for a number of diseases. This nationwide, population-based cohort study examined the association between body weight variability and dementia.

METHODS

A total of 2,812,245 adults (mean age, 51.7 years; standard deviation, 8.6) without a history of dementia who underwent at least three health examinations between 2005 and 2012 in a nationwide cohort were followed-up until the date of dementia diagnosis (based on prescribed drugs and disease code) or until 2016 (median follow-up duration, 5.38 years; interquartile range, 5.16-5.61). Cox regression models were used to evaluate the risk of Alzheimer's disease and vascular dementia according to body weight variability.

RESULTS

The hazard ratios (95% confidence intervals) of the highest quartiles of variability were 1.42 (1.35-1.49) for Alzheimer's disease and 1.47 (1.32-1.63) for vascular dementia compared to the lowest quartile group as a reference. This association was consistent in various subgroup analyses and sensitivity analyses.

CONCLUSIONS

Body weight variability could predict Alzheimer's disease and vascular dementia, which may provide new insights into the prevention and management of dementia.

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.

Malnutrition is Associated with Behavioral and Psychiatric Symptoms of Dementia in Older Women with Mild Cognitive Impairment and Early-Stage Alzheimer's Disease

We examined the nutritional status and its association with behavioral psychiatric symptoms of dementia (BPSD) among 741 memory clinic patients (normal cognition (NC), 152; mild cognitive impairment (MCI), 271; early-stage Alzheimer disease (AD), 318). Nutritional status and BPSD were assessed using the Mini Nutritional Assessment Short-Form (MNA-SF) and the Dementia Behavior Disturbance Scale (DBD), respectively. Compared to subjects with NC, more subjects with MCI and early-stage AD were at risk of malnutrition (MNA-SF, 8-11: NC, 34.2%; MCI, 47.5%; early-stage AD, 53.8%) and were malnourished (MNA-SF, 0-7: NC, 4.6%; MCI, 5.9%; early-stage AD, 8.2%). Among patients with MCI or early-stage AD, those at risk of/with malnutrition showed higher DBD scores than those well-nourished (12.7 ± 9.0 vs. 9.5 ± 7.3; p < 0.001). Moreover, analysis of covariance adjusting for confounders showed that nutritional status was significantly associated with specific BPSD, including "verbal aggressiveness/emotional disinhibition" (F = 5.87, p = 0.016) and "apathy/memory impairment" (F = 15.38, p < 0.001), which were revealed by factor analysis of DBD. Our results suggest that malnutrition is common among older adults with mild cognitive decline, and possibility that nutritional problems are associated with individual BPSD.

BMI, Weight Change, and Dementia Risk in Patients With New-Onset Type 2 Diabetes: A Nationwide Cohort Study

OBJECTIVE

This study examined the association between baseline BMI, percentage weight change, and the risk of dementia in patients newly diagnosed with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Using the South Korean National Health Insurance Service-National Health Screening Cohort database, we identified 167,876 subjects aged ≥40 years diagnosed with new-onset type 2 diabetes between 2007 and 2012. Their weight changes were monitored for ∼2 years after diagnosis, with follow-up assessments occurring for an average of 3.5 years. The hazard ratios (HRs) and Bonferroni-adjusted 95% CIs of all-cause dementia, Alzheimer disease (AD), and vascular dementia were estimated using multivariable Cox proportional hazards regression models.

RESULTS

We identified 2,563 incident dementia cases during follow-up. Baseline BMI among patients with new-onset type 2 diabetes was inversely associated with the risk of all-cause dementia and AD, independent of confounding variables (P for trend <0.001). The percentage weight change during the 2 years after a diagnosis of type 2 diabetes showed significant U-shaped associations with the risk of all-cause dementia development (P < 0.001); the HRs of the disease increased significantly when weight loss or gain was >10% (1.34 [95% CI 1.11-1.63] and 1.38 [1.08-1.76], respectively). Additionally, weight loss >10% was associated with an increased risk of AD (HR 1.26 [95% CI 1.01-1.59]).

CONCLUSIONS

A lower baseline BMI was associated with increased risks of all-cause dementia and AD in patients with new-onset type 2 diabetes. Weight loss or weight gain after the diagnosis of diabetes was associated with an increased risk of all-cause dementia. Weight loss was associated with an increased risk of AD.

Risk of Incident Dementia According to Metabolic Health and Obesity Status in Late Life: A Population-Based Cohort Study

CONTEXT

The risk for dementia among subjects who are obese with normal metabolic profiles, or called metabolically healthy obese (MHO), remains uninvestigated.

OBJECTIVE

To determine the association between late-life metabolic health and obesity status and risk of incident dementia.

DESIGN

Retrospective cohort study.

SETTING

The National Health Insurance System, Republic of Korea.

PATIENTS

A total of 12,296,863 adults >50 years old who underwent health examinations from 2009 to 2012 without baseline history of dementia.

MAIN OUTCOME MEASURE

Incident overall dementia, Alzheimer's disease (AD), and vascular dementia (VaD).

RESULTS

Among subjects ≥60 years old, 363,932 (6.4%) developed dementia during a median follow-up of 65 months (interquartile range 51 to 74 months). The MHO group showed the lowest incidence of overall dementia [hazard ratio (HR) 0.85; 95% CI, 0.84 to 0.86] and AD (HR 0.87; 95% CI, 0.86 to 0.88), but not VaD, compared with the metabolically healthy nonobese group. All components of metabolic syndrome except obesity significantly elevated the risk of dementia, and these associations were more pronounced in VaD. In particular, being underweight dramatically increased the risk of dementia.

CONCLUSIONS

The MHO phenotype in late life demonstrated lower risk of overall dementia and AD but not VaD. Additional studies in other populations are warranted to elucidate current results and may predict individuals most at risk for developing dementia.

Association of obesity, diabetes and hypertension with cognitive impairment in older age

Background

Age-related cognitive impairment is rising in prevalence but is not yet fully characterized in terms of its epidemiology. Here, we aimed to elucidate the role of obesity, diabetes and hypertension as candidate risk factors.

Methods

Original baseline data from 3 studies (OCTOPUS, DECS, SuDoCo) were obtained for secondary analysis of cross-sectional associations of diabetes, hypertension, blood pressure, obesity (body mass index [BMI] ≥30 kg/m²) and BMI with presence of cognitive impairment in log-binomial regression analyses. Cognitive impairment was defined as scoring more than 2 standard deviations below controls on at least one of 5–11 cognitive tests. Underweight participants (BMI<18.5 kg/m²) were excluded. Results were pooled across studies in fixed-effects inverse variance models.

Results

Analyses totaled 1545 participants with a mean age of 61 years (OCTOPUS) to 70 years (SuDoCo). Cognitive impairment was found in 29.0% of participants in DECS, 8.2% in SuDoCo and 45.6% in OCTOPUS. In pooled analyses, after adjustment for age, sex, diabetes and hypertension, obesity was associated with a 1.29-fold increased prevalence of cognitive impairment (risk ratio [RR] 1.29; 95% CI 0.98, 1.72). Each 1 kg/m² increment in BMI was associated with 3% increased prevalence (RR 1.03; 95% CI 1.00, 1.06). None of the remaining risk factors were associated with impairment.

Conclusion

Our results show that older people who are obese have higher prevalence of cognitive impairment compared with normal weight and overweight individuals, and independently of co-morbid hypertension or diabetes. Prospective studies are needed to investigate the temporal relationship of the association.

Body Mass Index in Mild Cognitive Impairment According to Age, Sex, Cognitive Intervention, and Hypertension and Risk of Progression to Alzheimer's Disease

Introduction: Mild cognitive impairment (MCI) is a prodromal stage of dementia. The association of body mass index (BMI) and progression to Alzheimer's disease (AD) in MCI subjects according to age, sex, and cognitive intervention remains unknown. We investigated the relationship between BMI and the risk of progression to AD in subjects with MCI, as well as the effect of BMI on progression to AD depending on age, sex, cognitive intervention, and chronic diseases. Methods: Three hundred and eighty-eight MCI subjects were followed for 36.3 ± 18.4 months, prospectively. They underwent neuropsychological testing more than twice during the follow-up period. The MCI subjects were categorized into underweight, normal weight, overweight, and obese subgroups. The associations between baseline BMI and progression to AD over the follow-up period were estimated using Cox proportional hazard regression models. Data were analyzed after stratification by age, sex, cognitive intervention, and chronic diseases. Results: After adjustment for the covariates, the underweight MCI group had a higher risk of progression to AD [hazard ratio (HR): 2.38, 95% confidence interval (CI): 1.17-4.82] relative to the normal weight group. After stratifying by age, sex, cognitive intervention, and chronic diseases, this effect remained significant among females (HR: 3.15, 95% CI: 1.40-7.10), the older elderly ≥75 years old (HR: 3.52, 95% CI: 1.42-8.72), the non-intervention group (HR: 3.06, 95%CI: 1.18-7.91), and the hypertensive group (HR: 4.71, 95% CI: 1.17-18.99). Conclusion: These data indicate that underweight could be a useful marker for identifying individuals at increased risk for AD in MCI subjects. This association is even stronger in females, older elderly subjects, the non-cognitive intervention group, and the hypertensive group.

Association of body mass index with amnestic and non-amnestic mild cognitive impairment risk in elderly

BACKGROUND

Previous studies focused on the relationship between body mass index and cognitive disorder and obtained many conflicting results. This study explored the potential effects of body mass index on the risk of mild cognitive impairment (amnestic and non-amnestic) in the elderly.

METHODS

The study enrolled 240 amnestic mild cognitive impairment patients, 240 non-amnestic mild cognitive impairment patients and 480 normal cognitive function controls. Data on admission and retrospective data at baseline (6 years ago) were collected from their medical records. Cognitive function was evaluated using Mini-Mental State Examination and Montreal Cognitive Assessment.

RESULTS

Being underweight, overweight or obese at baseline was associated with an increased risk of amnestic mild cognitive impairment (OR: 2.30, 95%CI: 1.50 ~ 3.52; OR: 1.74, 95%CI: 1.36 ~ 2.20; OR: 1.71, 95%CI: 1.32 ~ 2.22, respectively). Being overweight or obese at baseline was also associated with an increased risk of non-amnestic mild cognitive impairment (OR: 1.51, 95%CI: 1.20 ~ 1.92; OR: 1.52, 95%CI: 1.21 ~ 1.97, respectively). In subjects with normal weights at baseline, an increased or decreased body mass index at follow-up was associated with an elevated risk of amnestic mild cognitive impairment (OR: 1.80, 95%CI: 1.10 ~ 3.05; OR: 3.96, 95%CI: 2.88 ~ 5.49, respectively), but only an increased body mass index was associated with an elevated risk of non-amnestic mild cognitive impairment (OR: 1.71, 95%CI: 1.16 ~ 2.59).

CONCLUSIONS

Unhealthy body mass index levels at baseline and follow-up might impact the risk of both types of mild cognitive impairment (amnestic and non-amnestic).

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

The relationship between late-life body mass index (BMI) and Alzheimer's disease (AD) is poorly understood due to the lack of research in samples with autopsy-confirmed AD neuropathology (ADNP). The role of cerebrovascular disease (CVD) in the interplay between late-life BMI and ADNP is unclear. We conducted a retrospective longitudinal investigation and used joint modeling of linear mixed effects to investigate causal relationships among repeated antemortem BMI measurements, CVD (quantified neuropathologically), and ADNP in an autopsy sample of subjects across the AD clinical continuum. The sample included 1,421 subjects from the National Alzheimer's Coordinating Center's Uniform Data Set and Neuropathology Data Set with diagnoses of normal cognition (NC; n = 234), mild cognitive impairment (MCI; n = 201), or AD dementia (n = 986). ADNP was defined as moderate to frequent neuritic plaques and Braak stageIII-VI. Ischemic Injury Scale (IIS) operationalized CVD. Joint modeling examined relationships among BMI, IIS, and ADNP in the overall sample and stratified by initial visit Clinical Dementia Rating score. Subject-specific random intercept for BMI was the predictor for ADNP due to minimal BMI change (p = 0.3028). Analyses controlling for demographic variables and APOE ɛ4 showed lower late-life BMI predicted increased odds of ADNP in the overall sample (p < 0.001), and in subjects with CDR of 0 (p = 0.0021) and 0.5 (p = 0.0012), but not ≥1.0 (p = 0.2012). Although higher IIS predicted greater odds of ADNP (p < 0.0001), BMI did not predict IIS (p = 0.2814). The current findings confirm lower late-life BMI confers increased odds for ADNP. Lower late-life BMI may be a preclinical indicator of underlying ADNP.

Late-Life Vascular Risk Factors and Alzheimer Disease Neuropathology in Individuals with Normal Cognition

Vascular risk factors (VRFs) have been associated with clinically diagnosed Alzheimer disease (AD), but few studies have examined the association between VRF and AD neuropathology (ADNP) in cognitively normal individuals. We used longitudinal data from the National Alzheimer's Disease Center's Uniform Data Set and Neuropathology Data Set to examine the association between VRF and ADNP (moderate to frequent neuritic plaques; Braak stage III-VI) in those with normal cognition. Our sample included 53 participants with ADNP and 140 without ADNP. Body mass index (BMI), resting heart rate (HR), and pulse pressure (PP) were measured at each visit; values were averaged across participant visits and examined annual change in BMI, PP, and HR. Hypertension, diabetes, and hypercholesterolemia were self-reported. In the multivariable logistic regression analyses, average BMI and HR were associated with lower odds of ADNP, and annual increases in HR and BMI were associated with higher odds of ADNP. A previously experienced decline in BMI or HR in late-life (therefore, currently low BMI and low HR) as well as a late-life increase in BMI and HR may indicate underlying AD pathology. Additional clinicopathological research is needed to elucidate the role of changes in late-life VRF and AD pathogenesis.

Progression and predictors of mild cognitive impairment in Chinese elderly: A prospective follow-up in the Shanghai Aging Study

Introduction

The Shanghai Aging Study is a community-based study aiming to investigate the incidence and progression of cognitive decline in Chinese elderly, with the operational procedures and diagnostic criteria similar to cohort studies in developed countries.

Methods

We prospectively evaluated 362 individuals with mild cognitive impairment (MCI) diagnosed at baseline through a clinical and neuropsychological interview. Diagnoses of dementia and MCI were made using standard criteria via consensus diagnosis.

Results

The conversion rate to dementia was 6.0 per 100 person-years, while the reversion rate to cognitive normal was 7.8 per 100 person-years. Amnestic MCI multiple domains was the most risky type for dementia (conversion rate: 14.2 per 100 person-years). Older age (hazard ratio [HR] = 1.09), apolipoprotein E (APOE ε4) (HR = 2.15), and low MMSE score (HR = 1.18) were predictors for dementia.

Discussion

Approximately 6% of elderly with MCI progress to dementia annually. Prospective studies are needed to further examine risk and protective predictors and to seek proper interventions for cognitive decline.