The dynamic association between body mass index and cognition from midlife through late-life, and the effect of sex and genetic influences

Association Between BMI and Neurocognitive Functions Among Middle-aged Obese Adults: Preliminary Findings Using Machine-learning (ML)-based Approach

Background

Studies suggest that obesity predisposes individuals to developing cognitive dysfunction and an increased risk of dementia, but the nature of the relationship remains largely unexplored for better prognostic predictors.

Purpose

This study, the first of its kind in Indian participants with obesity, was intended to explore the use of quantification of different neurocognitive indices with increasing body mass index (BMI) among middle-aged participants with obesity. Additionally, machine-learning models were used to analyse the predictive performance of BMI for different cognitive functions.

Methods

In the cross-sectional analytical study, a total of 137 (n = 137) participants were included. Out of the total, 107 healthy obese (BMI = 23.0-30.0 kg m-2; age between 36 and 55 years of both genders) were recruited from the out-patient department of the Department of Endocrinology and General Medicine, and 30 participants were recruited as the control group, between March 2023 to February 2024. The participants underwent neuropsychological assessments, including mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA) and serum levels of brain-derived neurotrophic factor (BDNF).

Results

Significant (p < .05) differences were observed for neurocognitive functions for the obese group versus the control group. According to the correlation heatmaps, BMI was significantly (p < .05) negatively associated with BDNF. Multivariate linear regression analysis revealed a substantial (p < .05) decline in BDNF with a change in BMI, accenting its significant impact on cognitive ageing. Additionally, consistent decreasing trends were observed across the MoCA and MMSE, confirming the robustness of the findings across diverse analytical methodologies. Furthermore, the linear regression model and super vector machine model contributed additional evidence to the consistency of the trends in cognitive decline linked to BMI variations.

Conclusion

The preliminary results of the present study support that increased BMI is an important physiological indicator that influences neurocognition and neuroplasticity in individuals with obesity.

DNA methylation-based predictors of metabolic traits in Scottish and Singaporean cohorts

Exploring the molecular correlates of metabolic health measures may identify their shared and unique biological processes and pathways. Molecular proxies of these traits may also provide a more objective approach to their measurement. Here, DNA methylation (DNAm) data were used in epigenome-wide association studies (EWASs) and for training epigenetic scores (EpiScores) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio, and blood-based measures of glucose, high-density lipoprotein cholesterol, and total cholesterol in >17,000 volunteers from the Generation Scotland (GS) cohort. We observed a maximum of 12,033 significant findings (p < 3.6 × 10-8) for BMI in a marginal linear regression EWAS. By contrast, a joint and conditional Bayesian penalized regression approach yielded 27 high-confidence associations with BMI. EpiScores trained in GS performed well in both Scottish and Singaporean test cohorts (Lothian Birth Cohort 1936 [LBC1936] and Health for Life in Singapore [HELIOS]). The EpiScores for BMI and total cholesterol performed best in HELIOS, explaining 20.8% and 7.1% of the variance in the measured traits, respectively. The corresponding results in LBC1936 were 14.4% and 3.2%, respectively. Differences were observed in HELIOS for body fat, where the EpiScore explained ∼9% of the variance in Chinese and Malay -subgroups but ∼3% in the Indian subgroup. The EpiScores also correlated with cognitive function in LBC1936 (standardized βrange: 0.08-0.12, false discovery rate p [pFDR] < 0.05). Accounting for the correlation structure across the methylome can vastly affect the number of lead findings in EWASs. The EpiScores of metabolic traits are broadly applicable across populations and can reflect differences in cognition.

Moving Forward to Disentangle the Role of the Brain in Human Obesity

Obesity and the associated medical sequelae pose a major challenge for healthcare systems worldwide [...].

Examining the bidirectional longitudinal associations between body mass index and episodic memory following bariatric surgery

BACKGROUND

The relationship between obesity and episodic memory (i.e., conscious memory for specific events) is hypothesized to be bidirectional. Indeed, studies have shown that metabolic and bariatric surgery (MBS) is associated with episodic memory improvement, and better memory is associated with better postsurgical weight-loss outcomes. However, direct tests of the hypothesized bidirectional association between episodic memory and body mass index (BMI) in MBS are lacking, as few studies have employed repeated, prospective assessments of memory in conjunction with bidirectional modeling techniques.

OBJECTIVES

The present study used latent change score analysis to examine the bidirectional longitudinal associations between episodic memory and BMI in the 2 years following MBS.

SETTING

University hospital; public practice.

METHODS

Episodic memory function and BMI were assessed in adults prior to MBS, and at 1, 6, 12, 18, and 24-months postsurgery.

RESULTS

A total of 124 participants (41% lost at 2-year follow-up) showed, on average, favorable weight-loss and episodic memory outcomes following MBS. Crucially, presurgery episodic memory predicted initial change in BMI at 1-month postsurgery, and postsurgery episodic memory at 1- and 6-months predicted change in BMI at 6- and 12-months postsurgery. No evidence was found for pre- and postsurgery BMI predicting changes in episodic memory.

CONCLUSIONS

Results supported a unidirectional prospective relationship between episodic memory and weight change following MBS, such that better memory pre- and postsurgery predicted improved weight-loss outcomes. These findings highlight the likely importance of episodic memory function for weight change and support the potential benefit of targeting memory processes to improve weight-loss outcomes.

Interactive Relations of Body Mass Index, Cardiorespiratory Fitness, and Sex to Cognitive Function in Older Adults

OBJECTIVE

The course of cognitive aging is influenced by multiple health factors. This cross-sectional study investigated the interactive relations between body mass index (BMI), maximum oxygen consumption (VO2max), and sex on neuropsychological outcomes in community-dwelling predominantly older adults.

METHODS

Participants were 164 healthy adults [M (SD) = 64.6 (12.5) years, 56% men, 87% white] who participated in an investigation of cardiovascular risk factors and brain health. Multivariable regression analysis, adjusted for age, education, ethnicity, smoking, alcohol consumption, and depression, examined the interactive relations of BMI, VO2max, and sex to multiple neuropsychological outcomes.

RESULTS

Significant BMI*VO2max*sex interactions for Grooved Pegboard dominant (p = .019) and nondominant (p = .005) hands revealed that men with lower VO2max (l/min) displayed worse performance with each hand as BMI increased (p's < .02). A significant BMI*sex interaction for Logical Memory-Delayed Recall (p = .036) (after adjustment for blood glucose) showed that men, but not women, with higher BMI demonstrated worse performance (p = .036). Lastly, significant main effects indicated that lower VO2max was related to poorer logical memory, and higher BMI was associated with poorer Trail Making B and Stroop interference scores (p's < .05).

CONCLUSIONS

Among men, higher cardiorespiratory fitness may protect against the negative impact of greater BMI on manual dexterity and motor speed, making VO2max a target for intervention. Higher BMI is further associated with poorer executive function and verbal memory (in men), and lower VO2max is associated with poorer verbal memory.

Investigating causality and shared genetic architecture between body mass index and cognitive function: a genome-wide cross-trait analysis and bi-directional Mendelian randomization study

Background and objectives

Observational studies have established a connection between body mass index (BMI) and an increased risk of cognitive decline. However, a comprehensive investigation into the causal relationships between BMI and cognitive function across diverse age groups, as well as the genetic underpinnings of this relationship, has been notably lacking. This study aims to investigate causality and the shared genetic underpinnings of between BMI and cognitive function by conducting a thorough genome-wide analysis, thereby provide valuable insights for developing personalized intervention strategies to promote cognitive health.

Methods

Genetic associations between BMI and cognitive function were thoroughly investigated through covariate genetic analysis and chained imbalance score regression, utilizing data from genome-wide association studies (GWAS). Bi-directional Mendelian Randomization (MR) was employed to uncover associations and potential functional genes were further scrutinized through Cross-trait meta-analysis and Summary-data-based MR (SMR). Subsequently, a detailed examination of the expression profiles of the identified risk SNPs in tissues and cells was conducted.

Results

The study found a significant negative correlation between BMI and cognitive function (β = -0.16, P = 1.76E-05), suggesting a causal linkage where higher BMI values were predictive of cognitive impairment. We identified 5 genetic loci (rs6809216, rs7187776, rs11713193, rs13096480, and rs13107325) between BMI and cognitive function by cross-trait meta-analysis and 5 gene-tissue pairs were identified by SMR analysis. Moreover, two novel risk genes TUFM and MST1R were shared by both cross-trait analysis and SMR analysis, which had not been observed in previous studies. Furthermore, significant enrichment of single nucleotide polymorphisms (SNPs) at tissue- and cell-specific levels was identified for both BMI and cognitive function, predominantly within the brain.

Conclusion

This study uncovers a causal relationship between BMI and cognitive function, with the discovery of TUFM and MST1R as shared genetic factors associated with both conditions. This novel finding offers new insights into the development of preventative strategies for cognitive decline in obese individuals, and further enhances our understanding of the underlying pathophysiology of these conditions. Furthermore, these findings could serve as a guide for the development of innovative therapeutic approaches to address cognitive decline in obese individuals.

Association of changes in predicted body composition with subsequent risk of dementia

OBJECTIVE

The effect of body composition change on the risk of dementia is not clear. This study analyzed the associations of changes in predicted lean body mass index (pLBMI), predicted appendicular skeletal muscle mass index (pASMI), and predicted body fat mass index (pBFMI) with the risk of dementia.

METHODS

In this nationwide cohort study, data were obtained from the Korean National Health Insurance Service database. The exposure was defined as changes in pLBMI, pASMI, and pBFMI derived from validated prediction equations. The outcome was dementia, defined based on the dementia diagnosis with prescription of anti-dementia medication. Cox proportional hazards regression analyses were performed to obtain the hazard ratio with a 95% confidence interval for risk of dementia according to changes in predicted body composition.

RESULTS

A total of 13,215,208 individuals with no prior record of dementia who underwent health screenings twice between 2009-2010 and 2011-2012 were included. A 1-kg/m2 increase in pLBMI and pASMI had an association with reduced risk of dementia (aHR: 0.85, 95% CI 0.84-0.87; aHR: 0.70, 95% CI 0.69-0.72, respectively for men, and aHR: 0.69, 95% CI 0.67-0.71; aHR: 0.59, 95% CI 0.57-0.61, respectively for women). A 1-kg/m2 increase in pBFMI had an association with a raised risk of dementia (aHR: 1.19, 95% CI 1.17-1.21 for men and aHR: 1.53, 95% CI 1.48-1.57 for women). These results remained consistent regardless of sex or weight change.

INTERPRETATION

Increase in pLBMI or pASMI, or reduction in pBFMI was linked to lower risk of dementia.

Energy Expenditure Validation of an Exergame Platform: Ring Fit Adventure Use in Adults with Overweight and Obesity

Objective: This study aims at comparing the energy expenditure (EE) and heart rate (HR) data from Ring Fit Adventure (RFA) with those from indirect calorimetry (COSMED) and a heart rate monitor (Polar FT7). A secondary goal is to evaluate self-reported enjoyment and perceived effort levels. Materials and Methods: Thirty participants (age = 21.8 ± 2.2; body mass index = 31.8 ± 4.4) were recruited for two laboratory visits. The first visit involved baseline measurements. In the second visit, participants performed a 55-minute ad libitum exercise session with the RFA in adventure mode with moderate difficulty. During this session, EE, HR, perceived effort, and enjoyment of physical activity were recorded. Results: Although no statistically significant overestimation of EE was found between the RFA and the metabolic cart, two-way analysis of variance results show a main effect of condition (RFA vs. Polar FT7) on HR (122.8 ± 20.1 bpm and 129.0 ± 18.6 bpm; P = 0.007; ᶯp2 = 0.235). Based on comprehensive statistical evaluations, including the mean absolute percent error, intraclass correlations, typical error of measurement, and limits of agreement, the data suggest that the RFA provides reliable estimates for EE and HR. Overall, participants enjoyed the game considerably (71.3 ± 5.9/80 arbitrary units), and their reported perceived exertion was low. Conclusion: This study underscores that the RFA values are relatively accurate and precise, and thus it can be safely suggested for individuals with overweight and obesity to adopt an active lifestyle.

Leptin receptor reactivation restores brain function in early-life Lepr-deficient mice

Obesity is a chronic disease caused by excessive fat accumulation that impacts the body and brain health. Insufficient leptin or leptin receptor (LepR) is involved in the disease pathogenesis. Leptin is involved with several neurological processes, and it has crucial developmental roles. We have previously demonstrated that leptin deficiency in early life leads to permanent developmental problems in young adult mice, including an imbalance in energy homeostasis, alterations in melanocortin and the reproductive system and a reduction in brain mass. Given that in humans, obesity has been associated with brain atrophy and cognitive impairment, it is important to determine the long-term consequences of early-life leptin deficiency on brain structure and memory function. Here, we demonstrate that leptin-deficient (LepOb) mice exhibit altered brain volume, decreased neurogenesis and memory impairment. Similar effects were observed in animals that do not express the LepR (LepRNull). Interestingly, restoring the expression of LepR in 10-week-old mice reverses brain atrophy, in addition to neurogenesis and memory impairments in older animals. Our findings indicate that leptin deficiency impairs brain development and memory, which are reversible by restoring leptin signalling in adulthood.

Associations of childhood, adolescence, and midlife cognitive function with DNA methylation age acceleration in midlife

Prior studies showed increased age acceleration (AgeAccel) is associated with worse cognitive function among old adults. We examine the associations of childhood, adolescence and midlife cognition with AgeAccel based on DNA methylation (DNAm) in midlife. Data are from 359 participants who had cognition measured in childhood and adolescence in the Child Health and Development study, and had cognition, blood based DNAm measured during midlife in the Disparities study. Childhood cognition was measured by Raven's Progressive Matrices and Peabody Picture Vocabulary Test (PPVT). Adolescent cognition was measured only by PPVT. Midlife cognition included Wechsler Test of Adult Reading (WTAR), Verbal Fluency (VF), Digit Symbol (DS). AgeAccel measures including Horvath, Hannum, PhenoAge, GrimAge and DunedinPACE were calculated from DNAm. Linear regressions adjusted for potential confounders were utilized to examine the association between each cognitive measure in relation to each AgeAccel. There are no significant associations between childhood cognition and midlife AgeAccel. A 1-unit increase in adolescent PPVT, which measures crystalized intelligence, is associated with 0.048-year decrease of aging measured by GrimAge and this association is attenuated after adjustment for adult socioeconomic status. Midlife crystalized intelligence measure WTAR is negatively associated with PhenoAge and DunedinPACE, and midlife fluid intelligence measure (DS) is negatively associated with GrimAge, PhenoAge and DunedinPACE. AgeAccel is not associated with VF in midlife. In conclusion, our study showed the potential role of cognitive functions at younger ages in the process of biological aging. We also showed a potential relationship of both crystalized and fluid intelligence with aging acceleration.

Methylome-wide studies of six metabolic traits

Exploring the molecular correlates of metabolic health measures may identify the shared and unique biological processes and pathways that they track. Here, we performed epigenome-wide association studies (EWASs) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio (WHR), and blood-based measures of glucose, high-density lipoprotein (HDL) cholesterol, and total cholesterol. We considered blood-based DNA methylation (DNAm) from >750,000 CpG sites in over 17,000 volunteers from the Generation Scotland (GS) cohort. Linear regression analyses identified between 304 and 11,815 significant CpGs per trait at P<3.6×10-8, with 37 significant CpG sites across all six traits. Further, we performed a Bayesian EWAS that jointly models all CpGs simultaneously and conditionally on each other, as opposed to the marginal linear regression analyses. This identified between 3 and 27 CpGs with a posterior inclusion probability ≥ 0.95 across the six traits. Next, we used elastic net penalised regression to train epigenetic scores (EpiScores) of each trait in GS, which were then tested in the Lothian Birth Cohort 1936 (LBC1936; European ancestry) and Health for Life in Singapore (HELIOS; Indian-, Malay- and Chinese-ancestries). A maximum of 27.1% of the variance in BMI was explained by the BMI EpiScore in the subset of Malay-ancestry Singaporeans. Four metabolic EpiScores were associated with general cognitive function in LBC1936 in models adjusted for vascular risk factors (Standardised βrange: 0.08 - 0.12, PFDR < 0.05). EpiScores of metabolic health are applicable across ancestries and can reflect differences in brain health.

Neurocognitive correlates of metabolic dysregulation in individuals with mood disorders: a systematic review and meta-analysis

Individuals with mood disorders are predisposed to metabolic dysfunction, while those with metabolic dysregulation such as diabetes and obesity experience more severe depressive symptoms. Both metabolic dysfunction and mood disorders are independently associated with cognitive deficits. Therefore, given their close association, this study aimed to explore the association between metabolic dysfunction in individuals with mood disorders in relation to cognitive outcomes. A comprehensive search comprised of these three domains was carried out; a random-effects meta-analysis pooling mean cognitive outcomes was conducted (PROSPERO ID: CRD42022295765). Sixty-three studies were included in this review; 26 were synthesized in a quantitative meta-analysis. Comorbid metabolic dysregulation was associated with significantly lower global cognition among individuals with mood disorders. These trends were significant within each mood disorder subgroup, including major depressive disorder, bipolar disorder, and self-report depression/depressive symptoms. Type 2 diabetes was associated with the lowest cognitive performance in individuals with mood disorders, followed by peripheral insulin resistance, body mass index ⩾25 kg/m2, and metabolic syndrome. Significant reduction in scores was also observed among individual cognitive domains (in descending order) of working memory, attention, executive function, processing speed, verbal memory, and visual memory. These findings demonstrate the detrimental effects of comorbid metabolic dysfunction in individuals with mood disorders. Further research is required to understand the underlying mechanisms connecting mood disorders, metabolism, and cognition.

Sex difference in the association between BMI and cognitive impairment in Chinese older adults

BACKGROUND

The association between body mass index (BMI) and cognitive impairment (CI) has been the subject of extensive research, yet the precise dose-response effects remain undefined.

METHODS

Older adults were selected from the 2011/2012 survey at baseline and the new recruits from the 2014 and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Multiple logistic regression models were used to evaluate the association between BMI categories and CI, and Restricted Cubic Spline (RCS) was used to explore the nonlinear relationship between BMI and CI.

RESULTS

The study included 29,380 older adults aged from 65 to 117 years, with an average age of 82 years. Of these, 13,465 were men, and 5359 exhibited cognitive impairment. The logistic model indicated that in female participants, being underweight was positively correlated with CI (OR:1.32; 95%CI 1.20-1.46), whereas being overweight was inversely correlated with CI (OR:0.86; 95%CI 0.75-0.99), and we didn't find any association between BMI category and CI in male participants. RCS modeling revealed a U-shaped relationship between BMI and CI. When stratified by sex, men exhibited a similar trend, with the lowest risk at a BMI of 22.774 kg/ m2, while women had the lowest risk of CI at a BMI of 24.817 kg/ m2.

LIMITATION

This was a cross-sectional study, it cannot provide information on causal relationships.

CONCLUSION

A U-shaped relationship was observed between BMI and CI in older adults, more pronounced in the male population, suggesting that male older adults may need to manage their BMI more rigorously.

Nutrition risk and cognitive performance in community-living older adults without cognitive impairment: a cross-sectional analysis of the Canadian Longitudinal Study on Aging

Malnutrition is correlated with poor cognition; however, an understanding of the association between nutrition risk, which precedes malnutrition, and cognition is lacking. This study aimed to determine if nutrition risk measured with the SCREEN-8 tool is associated with cognitive performance among cognitively healthy adults aged 55+, after adjusting for demographic and lifestyle covariates. Sex- and age-stratified analyses were also explored. Baseline data from the Canadian Longitudinal Study on Aging was used. Cognition was determined using a 6-measure composite score based on four executive functions and two memory tasks, taking into account age, sex, and education. Multivariable linear regression was performed while adjusting for body mass index (BMI), lifestyle, and health covariates in the entire sample (n = 11 378) and then stratified by sex and age. Approximately half of participants were female (54.5%) aged 65+ (54.1%). Greater nutrition risk was associated with poorer cognitive performance in the entire sample (F[1, 11 368] = 5.36, p = 0.021) and among participants aged 55-64 (n = 5227; F[1, 5217] = 5.45, p = 0.020). Sex differences in lifestyle and health factors associated with cognition were apparent, but nutrition risk was not associated with cognition in sex-stratified models. Based on this analysis, there may be an association between nutrition risk and cognitive performance in older adults. When screening for either cognitive impairment or nutrition risk, complementary assessments for these conditions is warranted, as early intervention may provide benefit.

Examining the heterogeneity by employment status in dynamics between BMI and cognition: a longitudinal cohort study of the Korean aging population

PURPOSE

This study investigated the potential heterogeneity by employment status in the relationship between body mass index (BMI) trajectory and cognitive function among an aging population.

METHODS

We analyzed 2010-2018 cohort data from the Korean Longitudinal Study of Aging involving 4889 individuals aged over 45. We used statistical techniques of quadratic terms, interaction terms, time-invariant unobserved fixed effects, and time-lag effects to estimate the dynamic and interactive relationships among study variables.

RESULTS

The effect of BMI on cognitive function was heterogeneous based on employment status. For the nonemployed group, the impact of BMI on cognitive function showed an inverted U-shape with a turning point (BMI 25); a higher BMI (up to 25) was associated with higher cognitive function, but further increases beyond this threshold led to decreased cognitive function. For the employed group, however, the impact of BMI on cognitive function was nonsignificant. The nonlinear effect of BMI on cognitive function for the nonemployed group was robust across various subgroups and specifications.

CONCLUSIONS

The findings highlight the risk of obesity (BMI ≥ 25) on cognitive decline, particularly among nonemployed individuals. This illuminates the critical role of labor activity in regulating the impact of BMI on cognitive function among an aging population.

Vascular cognitive impairment - Past, present, and future challenges

Vascular cognitive impairment (VCI) is a lifelong process encompassing a broad spectrum of cognitive disorders, ranging from subtle or mild deficits to prodromal and fully developed dementia, originating from cerebrovascular lesions such as large and small vessel disease. Genetic predisposition and environmental exposure to risk factors such as unhealthy lifestyles, hypertension, cardiovascular disease, and metabolic disorders will synergistically interact, yielding biochemical and structural brain changes, ultimately culminating in VCI. However, little is known about the pathological processes underlying VCI and the temporal dynamics between risk factors and disease mechanisms (biochemical and structural brain changes). This narrative review aims to provide an evidence-based summary of the link between individual vascular risk/disorders and cognitive dysfunction and the potential structural and biochemical pathophysiological processes. We also discuss some key challenges for future research on VCI. There is a need to shift from individual risk factors/disorders to comorbid vascular burden, identifying and integrating imaging and fluid biomarkers, implementing a life-course approach, considering possible neuroprotective influences of positive life exposures, and addressing biological sex at birth and gender differences. Finally, this review highlights the need for future researchers to leverage and integrate multidimensional data to advance our understanding of the mechanisms and pathophysiology of VCI.

Body Mass Index and Cognition: Associations Across Mid- to Late Life and Gender Differences

BACKGROUND

Higher mid-life body mass index (BMI) is associated with lower late-life cognition. Associations between later-life BMI and cognition are less consistent; evidence suggests reverse causation may play a role. We aimed to characterize associations between BMI and cognition across a wide age range during mid- to late life (55-85 years) and examine whether associations vary by gender.

METHODS

We used data from the Health and Retirement Study (HRS) (N = 39,153) to examine the association between BMI and 3 cognitive outcomes: cognitive level, cognitive decline, and cognitive impairment. We used a series of linear regression, mixed effects regression, and logistic regression models, adjusting for potential confounders.

RESULTS

Higher BMI before age 65 (midlife) was associated with lower cognitive performance, faster rates of cognitive decline, and higher odds of cognitive impairment in late life. Averaging across analyses assessing associations between BMI measured before age 60 and late-life cognition, a 5-unit higher level of BMI was associated with a 0.26 point lower cognitive score. Beyond age 65, associations flipped, and higher BMI was associated with better late-life cognitive outcomes. Associations in both directions were stronger in women. Excluding those with BMI loss attenuated findings among women in older ages, supporting the reverse causation hypothesis.

CONCLUSIONS

In this sample, age 65 represented a critical turning point between mid- and late life for the association between BMI and cognition, which has important implications for recruitment strategies for studies focused on risk factors for late-life cognitive outcomes. Evidence of gender differences raises the need to further investigate plausible mechanisms.

Longitudinal Examination of Body Mass Index and Cognitive Function in Older Adults: The HELIAD Study

Given the increase in the aging population and thus in the prevalence of dementia, the identification of protective factors against cognitive decline is necessary. In a cohort of 1076 non-demented adults ≥ 65 years old (59.7% women) from the HELIAD study, we assessed whether changes in body mass index (BMI) were associated with changes in cognition over a 3-year follow-up period separately for those ≤ 75 and >75 years old. We identified six BMI trajectory groups based on participants' BMI status at baseline and at the first follow-up visit; normal to normal BMI was the reference group. Major cognitive domains were evaluated, and a composite index reflecting global cognition was calculated. In participants aged ≤75 years, weight loss-moving from obesity to overweight or normal BMI-was associated with less decline in the memory composite score over time (β = 0.141; p = 0.035), while 3-year maintenance of a BMI ≥ 25 kg/m² was related to greater reduction in the visuospatial composite score over time (β = -0.093; p = 0.020). Regarding participants aged >75 years, 3-year maintenance of a BMI ≥ 30 kg/m² contributed to a slower rate of decline in the memory composite score over time (β = 0.102; p = 0.042), whereas weight loss-from overweight to normal BMI-was associated with a decreased attention/processing speed composite score longitudinally (β = -0.275; p = 0.043). Our findings indicated that the association between changes in BMI and cognitive functioning was modified by age. Weight management may have the potential to delay cognitive decline in older adults.

Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study

Background

Evidence indicates that the adverse health effects of obesity differ between genetically and environmentally influenced obesity. We examined differences in the association between obesity and cardiovascular disease (CVD) between individuals with a genetically predicted low, medium, or high body mass index (BMI).

Methods

We used cohort data from Swedish twins born before 1959 who had BMI measured between the ages of 40-64 years (midlife) or at the age of 65 years or later (late-life), or both, and prospective CVD information from nationwide register linkage through 2016. A polygenic score for BMI (PGSBMI) was used to define genetically predicted BMI. Individuals missing BMI or covariate data, or diagnosed with CVD at first BMI measure, were excluded, leaving an analysis sample of 17,988 individuals. We applied Cox proportional hazard models to examine the association between BMI category and incident CVD, stratified by the PGSBMI. Co-twin control models were applied to adjust for genetic influences not captured by the PGSBMI.

Findings

Between 1984 and 2010, the 17,988 participants were enrolled in sub-studies of the Swedish Twin Registry. Midlife obesity was associated with a higher risk of CVD across all PGSBMI categories, but the association was stronger with genetically predicted lower BMI (hazard ratio from 1.55 to 2.08 for those with high and low PGSBMI, respectively). Within monozygotic twin pairs, the association did not differ by genetically predicted BMI, indicating genetic confounding not captured by the PGSBMI. Results were similar when obesity was measured in late-life, but suffered from low power.

Interpretation

Obesity was associated with CVD regardless of PGSBMI category, but obesity influenced by genetic predisposition (genetically predicted high BMI) was less harmful than obesity influenced by environmental factors (obesity despite genetically predicted low BMI). However, additional genetic factors, not captured by the PGSBMI, still influence the associations.

Funding

The Strategic Research Program in Epidemiology at Karolinska Institutet; Loo and Hans Osterman's Foundation; Foundation for Geriatric Diseases at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare; the Swedish Research Council; and the National Institutes of Health.

Relationship Between Weight-Change Patterns and Cognitive Function: A Retrospective Study

BACKGROUND

Obesity has been linked to cognitive impairment. However, how changes in body mass index (BMI) over the life course influence cognitive function remains unclear.

OBJECTIVE

The influence of distinct weight-change patterns from young adulthood to midlife and late adulthood on cognitive function in older adults was explored.

METHODS

A total of 5,809 individuals aged≥60 years were included and categorized into four groups on the basis of BMI change patterns. Cognitive function was assessed using four cognition tests in the baseline survey. The relationship between the weight-change patterns and cognition was evaluated using regression models.

RESULTS

In comparison with participants who remained at non-obese, those moving from the non-obese to obese weight-change pattern from young (25 years of age) to middle adulthood showed lower Digit Symbol Substitution Test (DSST) scores (β= -1.28; 95% confidence interval [CI]: -2.24 to -0.32). A non-obese to obese change pattern from age 25 years of age to 10 years before baseline was associated with a higher risk of DSST impairment (odds ratio = 1.40; 95% CI: 1.09 to 1.79). In comparison with participants whose heaviest weight was recorded after 60 years of age, those with the heaviest weight between 18 and 40 years of age had lower DSST scores (β= -1.46; 95% CI: -2.77 to -1.52).

CONCLUSION

Our results suggest that the transition from the non-obese to obese category in early adulthood and appearance of the heaviest weight between 18 and 40 years of age are associated with lower cognitive function in later life.

Recent Updates on Associations among Various Obesity Metrics and Cognitive Impairment: from Body Mass Index to Sarcopenic Obesity

Obesity and obesity-associated morbidity continues to be a major public health issue worldwide. Dementia is also a major health concern in aging societies and its prevalence has increased rapidly. Many epidemiologic studies have shown an association between obesity and cognitive impairment, but this relationship is not as well established as other comorbidities. Conflicting results related to the age and sex of participants, and the methodology used to define obesity and dementia may account for the uncertainty in whether obesity is a modifiable risk factor for dementia. More recently, sarcopenia and sarcopenic obesity have been reported to be associated with cognitive impairment. In addition, new mediators such as the muscle-myokine-brain axis and gut-microbiota-brain axis have been suggested and are attracting interest. In this review, we summarize recent evidence on the link between obesity and cognitive impairment, especially dementia. In particular, we focus on various metrics of obesity, from body mass index to sarcopenia and sarcopenic obesity.

Stability in BMI over time is associated with a better cognitive trajectory in older adults

OBJECTIVE

Evidence on simultaneous changes in body mass index (BMI) and cognitive decline, which better reflect the natural course of both health phenomena, is limited.

METHODS

We capitalized on longitudinal data from 15,977 initially non-demented elderly from the Alzheimer's Disease Centers followed for 5 years on average. Changes in BMI were defined as (1) last minus first BMI, (2) mean of all follow-up BMIs minus first BMI, and (3) standard deviation of BMI change from baseline and all follow-up visits (representing variability).

RESULTS

Participants with significant changes in BMI (increase or decrease of ≥5%), or who had greater variability in BMI, had faster cognitive decline. This pattern was consistent irrespective of normal (BMI < 25; N = 5747), overweight (25 ≤ BMI < 30; N = 6302), or obese (BMI ≥ 30; N = 3928) BMI at baseline.

CONCLUSIONS

Stability in BMI predicts better cognitive trajectories suggesting clinical value in tracking BMI change, which is simple to measure, and may point to individuals whose cognition is declining.

Does sleep duration moderate genetic and environmental contributions to cognitive performance?

While prior research has demonstrated a relationship between sleep and cognitive performance, how sleep relates to underlying genetic and environmental etiologies contributing to cognitive functioning, regardless of the level of cognitive function, is unclear. The present study assessed whether the importance of genetic and environmental contributions to cognition vary depending on an individual's aging-related sleep characteristics. The large sample consisted of twins from six studies within the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium spanning mid- to late-life (Average age [Mage] = 57.6, range = 27-91 years, N = 7052, Female = 43.70%, 1525 complete monozygotic [MZ] pairs, 2001 complete dizygotic [DZ] pairs). Quantitative genetic twin models considered sleep duration as a primary moderator of genetic and environmental contributions to cognitive performance in four cognitive abilities (Semantic Fluency, Spatial-Visual Reasoning, Processing Speed, and Episodic Memory), while accounting for age moderation. Results suggested genetic and both shared and nonshared environmental contributions for Semantic Fluency and genetic and shared environmental contributions for Episodic Memory vary by sleep duration, while no significant moderation was observed for Spatial-Visual Reasoning or Processing Speed. Results for Semantic Fluency and Episodic Memory illustrated patterns of higher genetic influences on cognitive function at shorter sleep durations (i.e. 4 hours) and higher shared environmental contributions to cognitive function at longer sleep durations (i.e. 10 hours). Overall, these findings may align with associations of upregulation of neuroinflammatory processes and ineffective beta-amyloid clearance in short sleep contexts and common reporting of mental fatigue in long sleep contexts, both associated with poorer cognitive functioning.

Sex-Specific Patterns of Body Mass Index Relationship with White Matter Connectivity

BACKGROUND

Obesity is an increasingly recognized modifiable risk factor for Alzheimer's disease (AD). Increased body mass index (BMI) is related to distinct changes in white matter (WM) fiber density and connectivity.

OBJECTIVE

We investigated whether sex differentially affects the relationship between BMI and WM structural connectivity.

METHODS

A cross-sectional sample of 231 cognitively normal participants were enrolled from the Knight Alzheimer Disease Research Center. Connectome analyses were done with diffusion data reconstructed using q-space diffeomorphic reconstruction to obtain the spin distribution function and tracts were selected using a deterministic fiber tracking algorithm.

RESULTS

We identified an inverse relationship between higher BMI and lower connectivity in the associational fibers of the temporal lobe in overweight and obese men. Normal to overweight women showed a significant positive association between BMI and connectivity in a wide array of WM fibers, an association that reversed in obese and morbidly obese women. Interaction analyses revealed that with increasing BMI, women showed higher WM connectivity in the bilateral frontoparietal and parahippocampal parts of the cingulum, while men showed lower connectivity in right sided corticostriatal and corticopontine tracts. Subgroup analyses demonstrated comparable results in participants with and without positron emission tomography or cerebrospinal fluid evidence of brain amyloidosis, indicating that the relationship between BMI and structural connectivity in men and women is independent of AD biomarker status.

CONCLUSION

BMI influences structural connectivity of WM differently in men and women across BMI categories and this relationship does not vary as a function of preclinical AD.