Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants

Association of waist-to-hip ratio adjusted for body mass index with cognitive impairment in middle-aged and elderly patients with type 2 diabetes mellitus: a cross-sectional study

BACKGROUND

Numerous reports indicate that both obesity and type 2 diabetes mellitus (T2DM) are factors associated with cognitive impairment (CI). The objective was to assess the relationship between abdominal obesity as measured by waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and CI in middle-aged and elderly patients with T2DM.

METHODS

A cross-sectional study was conducted, in which a total of 1154 patients with T2DM aged ≥ 40 years were included. WHRadjBMI was calculated based on anthropometric measurements and CI was assessed utilizing the Montreal Cognitive Assessment (MoCA). Participants were divided into CI group (n = 509) and normal cognition group (n = 645). Correlation analysis and binary logistic regression were used to explore the relationship between obesity-related indicators including WHRadjBMI, BMI as well as waist circumference (WC) and CI. Meanwhile, the predictive power of these indicators for CI was estimated by receiver operating characteristic (ROC) curves.

RESULTS

WHRadjBMI was positively correlated with MoCA scores, independent of sex. The Area Under the Curve (AUC) for WHRadjBMI, BMI and WC were 0.639, 0.521 and 0.533 respectively, and WHRadjBMI had the highest predictive power for CI. Whether or not covariates were adjusted, one-SD increase in WHRadjBMI was significantly related to an increased risk of CI with an adjusted OR of 1.451 (95% CI: 1.261-1.671). After multivariate adjustment, the risk of CI increased with rising WHRadjBMI quartiles (Q4 vs. Q1 OR: 2.980, 95%CI: 2.032-4.371, P for trend < 0.001).

CONCLUSIONS

Our study illustrated that higher WHRadjBMI is likely to be associated with an increased risk of CI among patients with T2DM. These findings support the detrimental effects of excess visceral fat accumulation on cognitive function in middle-aged and elderly T2DM patients.

Obesity and brain volumes: mediation by cardiometabolic and inflammatory measures

BACKGROUND

This study aimed to investigate the relationship between overall obesity, central obesity and brain volumes, as well as to determine the extent to which cardiometabolic and inflammatory measures act as mediators in the association between body mass index (BMI), waist-hip ratio (WHR) and brain volumes.

METHODS

In the context of counterfactual framework, mediation analysis was used to explore the potential mediation in which cardiometabolic and inflammatory measures may mediate the relationship between BMI, WHR, and brain volumes.

RESULTS

Among 2413 community-dwelling participants, those with high BMI or WHR levels experienced an approximately brain ageing of 4 years. Especially, individuals with high WHR or BMI under the age of 65 exhibited white matter hyperintensity volume (WMHV) differences equivalent to around 5 years of ageing. Conversely, in the high-level WHR population over the age of 65, premature brain ageing in gray matter volume (GMV) exceeded 4.5 years. For GMV, more than 45% of the observed effect of WHR was mediated by glycaemic metabolism indicators. This proportion increases to 78.70% when blood pressure, triglyceride, leucocyte count, and neutrophil count are jointly considered with glycaemic metabolism indicators. Regarding WHR and BMI's association with WMHV, cardiometabolic and inflammatory indicators, along with high-density lipoprotein cholesterol, mediated 35.50% and 20.20% of the respective effects.

CONCLUSIONS

Overall obesity and central obesity were associated with lower GMV and higher WMHV, a process that is partially mediated by the presence of cardiometabolic and inflammatory measures.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression

Cross-sectional studies have demonstrated strong associations between physical frailty and depression. However, the evidence from prospective studies is limited. Here, we analyze data of 352,277 participants from UK Biobank with 12.25-year follow-up. Compared with non-frail individuals, pre-frail and frail individuals have increased risk for incident depression independent of many putative confounds. Altogether, pre-frail and frail individuals account for 20.58% and 13.16% of depression cases by population attributable fraction analyses. Higher risks are observed in males and individuals younger than 65 years than their counterparts. Mendelian randomization analyses support a potential causal effect of frailty on depression. Associations are also observed between inflammatory markers, brain volumes, and incident depression. Moreover, these regional brain volumes and three inflammatory markers-C-reactive protein, neutrophils, and leukocytes-significantly mediate associations between frailty and depression. Given the scarcity of curative treatment for depression and the high disease burden, identifying potential modifiable risk factors of depression, such as frailty, is needed.

Clinical trajectories preceding incident dementia up to 15 years before diagnosis: a large prospective cohort study

BACKGROUND

Dementia has a long prodromal stage with various pathophysiological manifestations; however, the progression of pre-diagnostic changes remains unclear. We aimed to determine the evolutional trajectories of multiple-domain clinical assessments and health conditions up to 15 years before the diagnosis of dementia.

METHODS

Data was extracted from the UK-Biobank, a longitudinal cohort that recruited over 500,000 participants from March 2006 to October 2010. Each demented subject was matched with 10 healthy controls. We performed logistic regressions on 400 predictors covering a comprehensive range of clinical assessments or health conditions. Their evolutional trajectories were quantified using adjusted odds ratios (ORs) and FDR-corrected p-values under consecutive timeframes preceding the diagnosis of dementia.

FINDINGS

During a median follow-up of 13.7 [Interquartile range, IQR 12.9-14.2] years until July 2022, 7620 subjects were diagnosed with dementia. In general, upon approaching the diagnosis, demented subjects witnessed worse functional assessments and a higher prevalence of health conditions. Associations up to 15 years preceding the diagnosis comprised declined physical strength (hand grip strength, OR 0.65 [0.63-0.67]), lung dysfunction (peak expiratory flow, OR 0.78 [0.76-0.81]) and kidney dysfunction (cystatin C, OR 1.13 [1.11-1.16]), comorbidities of coronary heart disease (OR 1.78 [1.67-1.91]), stroke (OR 2.34 [2.1-1.37]), diabetes (OR 2.03 [1.89-2.18]) and a series of mental disorders. Cognitive functions in multiple tests also demonstrate decline over a decade before the diagnosis. Inadequate activity (3-5 year, overall time of activity, OR 0.82 [0.73-0.92]), drowsiness (3-5 year, sleep duration, OR 1.13 [1.04-1.24]) and weight loss (0-5 year, weight, OR 0.9 [0.83-0.98]) only exhibited associations within five years before the diagnosis. In addition, serum biomarkers of enriched endocrine, dysregulations of ketones, deficiency of brand-chain amino acids and polyunsaturated fatty acids were found in a similar prodromal time window and can be witnessed as the last pre-symptomatic conditions before the diagnosis.

INTERPRETATION

Our findings present a comprehensive temporal-diagnostic landscape preceding incident dementia, which could improve selection for preventive and early disease-modifying treatment trials.

Socioeconomic status, lifestyle and risk of incident dementia: a prospective cohort study of 276730 participants

Healthy lifestyle might alleviate the socioeconomic inequities in health, but the extent of the joint and interactive effects of these two factors on dementia are unclear. This study aimed to detect the joint and interactive associations of socioeconomic status (SES) and lifestyle factors with incident dementia risk, and the underlying brain imaging alterations. Cox proportional hazards analysis was performed to test the joint and interactive associations. Partial correlation analysis was performed to reflect the brain imaging alterations. A total of 276,730 participants with a mean age of 55.9 (±8.0) years old from UK biobank were included. Over 8.5 (±2.6) years of follow-up, 3013 participants were diagnosed with dementia. Participants with high SES and most healthy lifestyle had a significantly lower risk of incident dementia (HR=0.19, 95% CI=0.14 to 0.26, P<2×10-16), Alzheimer's disease (AD, HR=0.19, 95% CI=0.13 to 0.29, P=8.94×10-15), and vascular dementia (HR=0.24, 95% CI=0.12 to 0.48, P=7.57×10-05) compared with participants with low SES and an unhealthy lifestyle. Significant interactions were found between SES and lifestyle on dementia (P=0.002) and AD (P=0.001) risks; the association between lifestyle and dementia was stronger among those of high SES. The combination of high SES and healthy lifestyle was positively associated with higher volumes in brain regions vulnerable to dementia-related atrophy. These findings suggest that SES and lifestyle significantly interact and influence dementia with its related brain structure phenotypes.

Associations between antipsychotics exposure and dementia risk: A prospective cohort study of 415,100 participants

BACKGROUND

Antipsychotics (APs) are among the most widely prescribed medications, and have been shown to cause cognitive decline. But previous studies on their effects on dementia risk are controversial and scarce. We aimed to examine the relationships of APs exposure with the risk of dementia.

METHODS

Data were obtained from a prospective cohort of 415,100 UK Biobank (UKB) participants. We investigated the effects of APs exposure and their various classes on dementia risk by using multivariable Cox proportional hazard models and further the dose-response effects of oral APs.

RESULTS

After a mean follow-up of 8.64 years, 5235 (1.3 %) participants developed all-cause dementia (ACD), among whom 2313 (0.6 %) developed Alzheimer's disease (AD), and 1213 (0.3 %) developed vascular dementia (VaD). Exposure to any APs conferred increased risks of ACD (HR: 1.33, 95 % CI = 1.17-1.51, P < 0.001) and VaD (HR: 1.90, 95 % CI = 1.51-2.40, P < 0.001), but not AD (HR: 1.22, 95 % CI = 1.00-1.48, P = 0.051). Cumulative dose-response relationships of oral APs with the risks of ACD and VaD were observed (P for trend, P < 0.05).

LIMITATIONS

Our study is observational and does not show evidence of causality. Since there are relatively few cases of dementia in the UKB, APs exposure may be higher than estimated in our study.

CONCLUSIONS

APs exposure increased the risk of developing dementia. Dose-response relationships were found between oral APs and dementia risk. Efforts to raise awareness of doctors and patients about this potential drug-related risk are critical to reducing APs use.

Association between Body Mass Index and Brain Health in Adults: A 16-Year Population-Based Cohort and Mendelian Randomization Study

Background: The cumulative effect of body mass index (BMI) on brain health remains ill-defined. The effects of overweight on brain health across different age groups need clarification. We analyzed the effect of cumulative BMI on neuroimaging features of brain health in adults of different ages. Methods: This study was based on a multicenter, community-based cohort study. We modeled the trajectories of BMI over 16 years to evaluate cumulative exposure. Multimodality neuroimaging data were collected once for volumetric measurements of the brain macrostructure, white matter hyperintensity (WMH), and brain microstructure. We used a generalized linear model to evaluate the association between cumulative BMI and neuroimaging features. Two-sample Mendelian randomization analysis was performed using summary level of BMI genetic data from 681,275 individuals and neuroimaging genetic data from 33,224 individuals to analyze the causal relationships. Results: Clinical and neuroimaging data were obtained from 1,074 adults (25 to 83 years). For adults aged under 45 years, brain volume differences in participants with a cumulative BMI of >26.2 kg/m2 corresponded to 12.0 years [95% confidence interval (CI), 3.0 to 20.0] of brain aging. Differences in WMH were statistically substantial for participants aged over 60 years, with a 6.0-ml (95% CI, 1.5 to 10.5) larger volume. Genetic analysis indicated causal relationships between high BMI and smaller gray matter and higher fractional anisotropy in projection fibers. Conclusion: High cumulative BMI is associated with smaller brain volume, larger volume of white matter lesions, and abnormal microstructural integrity. Adults younger than 45 years are suggested to maintain their BMI below 26.2 kg/m2 for better brain health. Trial Registration: This study was registered on clinicaltrials.gov (Clinical Indicators and Brain Image Data: A Cohort Study Based on Kailuan Cohort; No. NCT05453877; https://clinicaltrials.gov/ct2/show/NCT05453877).

Transition to healthier lifestyle associated with reduced risk of incident dementia and decreased hippocampal atrophy

BACKGROUND

Research has estimated the associations of lifestyle at one-time point with the risk of dementia and hippocampal volume, but the impact of lifestyle transition on dementia and hippocampal volume remains unclear. This study aims to examine the associations of lifestyle transition with the risk of dementia and hippocampal volume.

METHODS

Based on data from the UK Biobank, a weighted lifestyle score was constructed by incorporating six lifestyle factors. Within each baseline lifestyle group (i.e., healthy, intermediate, and unhealthy), lifestyle transition was classified into decline, maintenance, and improvement. Cox proportional hazard regression was used to estimate the association of lifestyle transition and incident dementia (N = 16,305). A multiple linear regression model was used to estimate the association between lifestyle transition and hippocampal volume (N = 5849).

RESULTS

During a median follow-up period of 8.6 years, 120 (0.7 %) dementia events were documented. Among participants with healthy baseline lifestyles, the improvement group had a lower risk of incident dementia (HR: 0.18, 95 % CI: 0.04-0.81) and a larger hippocampal volume (β = 111.69, P = 0.026) than the decline group. Similar results were observed among participants with intermediate baseline lifestyles regarding dementia risk but not hippocampal volume. No benefits were observed in the improvement group among those with unhealthy baseline lifestyles.

LIMITATIONS

A lower incidence of dementia than other cohort study and this may have resulted in an underestimation of the risk of dementia.

CONCLUSIONS

Earlier transitions to healthier lifestyle were associated with reduced risk of incident dementia and decreased hippocampal atrophy.

Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome-host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the "microbiota-gut-brain axis". The microbiota-gut-brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood-brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota-gut-brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

A case for seeking sex-specific treatments in Alzheimer's disease

There is no satisfactory explanation for the sex-related differences in the incidence of many diseases and this is also true of Alzheimer's disease (AD), where females have a higher lifetime risk of developing the disease and make up about two thirds of the AD patient population. The importance of understanding the cause(s) that account for this disproportionate distribution cannot be overestimated, and is likely to be a significant factor in the search for therapeutic strategies that will combat the disease and, furthermore, potentially point to a sex-targeted approach to treatment. This review considers the literature in the context of what is known about the impact of sex on processes targeted by drugs that are in clinical trial for AD, and existing knowledge on differing responses of males and females to these drugs. Current knowledge strongly supports the view that trials should make assessing sex-related difference in responses a priority with a focus on exploring the sex-stratified treatments.

Development and validation of prediction model for older adults with cognitive frailty

OBJECTIVE

This study sought to develop and validate a 6-year risk prediction model in older adults with cognitive frailty (CF).

METHODS

In the secondary analysis of Chinese Longitudinal Healthy Longevity Survey (CLHLS), participants from the 2011-2018 cohort were included to develop the prediction model. The CF was assessed by the Chinese version of Mini-Mental State Exam (CMMSE) and the modified Fried criteria. The stepwise regression was used to select predictors, and the logistic regression analysis was conducted to construct the model. The model was externally validated using the temporal validation method via the 2005-2011 cohort. The discrimination was measured by the area under the curve (AUC), and the calibration was measured by the calibration plot. A nomogram was conducted to vividly present the prediction model.

RESULTS

The development dataset included 2420 participants aged 60 years or above, and 243 participants suffered from CF during a median follow-up period of 6.91 years (interquartile range 5.47-7.10 years). Six predictors, namely, age, sex, residence, body mass index (BMI), exercise, and physical disability, were finally used to develop the model. The model performed well with the AUC of 0.830 and 0.840 in the development and external validation datasets, respectively.

CONCLUSION

The study could provide a practical tool to identify older adults with a high risk of CF early. Furthermore, targeting modifiable factors could prevent about half of the new-onset CF during a 6-year follow-up.

Different sedentary behaviors, genetic susceptibility of hypertension, and new-onset hypertension: Mediating effects of body mass index and grip strength

BACKGROUND

The association between different sedentary behaviors and hypertension risk remains unclear. We aimed to explore the relationship between different domains of sedentary behaviors and new-onset hypertension, investigate whether genetic susceptibility to hypertension modifies the relationship, and examine the extent to which the relationship is mediated by body mass index (BMI) and grip strength.

METHODS

212 714 participants without baseline hypertension in the UK Biobank were enrolled. The three major sedentary behaviors (TV-watching, nonoccupational computer use, and driving) were measured using touch screen questionnaires. The primary outcome was new-onset hypertension.

RESULTS

During a median follow-up of 11.9 years, 13 983 participants developed hypertension. There was a linear positive association between TV-watching time and new-onset hypertension (p for nonlinearity =0.868). A J-shaped association was found for nonoccupational computer use time and driving time with new-onset hypertension, with an inflection point of 0.5 h/day for both (both p for nonlinearity <0.001). Polygenetic risk scores for hypertension (based on 118 related single-nucleotide polymorphisms) did not significantly modify these associations (all p-interactions >0.05). Furthermore, the detrimental effects of long-term sedentary behaviors on hypertension were mediated by BMI by 21%-30%, and the beneficial effects of limited sitting time (within 0.5 h/day) for driving and nonoccupational computer use were mediated by grip strength by 6-25%.

CONCLUSIONS

There was a positive association for hands-independence sedentary behavior (TV-watching), and a J-shaped association for hands-dependence sedentary behaviors (nonoccupational computer use and driving) with new-onset hypertension, regardless of genetic risks of hypertension. These relationships were partly mediated by BMI and grip strength.

Towards an adiposity-related disease framework for the diagnosis and management of obesities

Obesity is a complex disease that relapses frequently and associates with multiple complications that comprise a worldwide health priority because of its rising prevalence and association with numerous complications, including metabolic disorders, mechanic pathologies, and cancer, among others. Noteworthy, excess adiposity is accompanied by chronic inflammation, oxidative stress, insulin resistance, and subsequent organ dysfunction. This dysfunctional adipose tissue is initially stored in the visceral depot, overflowing subsequently to produce lipotoxicity in ectopic depots like liver, heart, muscle, and pancreas, among others. People living with obesity need a diagnostic approach that considers an exhaustive pathophysiology and complications assessment. Thus, it is essential to warrant a holistic diagnosis and management that guarantees an adequate health status, and quality of life. The present review summarizes the different complications associated with obesity, at the same time, we aim to fostering a novel framework that enhances a patient-centered approach to obesity management in the precision medicine era.

Alzheimer's Disease: Causal Effect between Obesity and APOE Gene Polymorphisms

Currently studies on the correlation between obesity and Alzheimer's disease (AD) are still unclear. In addition, few indicators have been used to evaluate obesity, which has failed to comprehen-sively study the correlations between body fat mass, body fat distribution, and AD. Thus, this study innovatively utilized bioinformatics and Mendelian randomization (MR) to explore the key targets of obesity-induced AD, and investigate the causal associations between different types of obesity and key targets. The common targets of obesity and AD were screened using the GeneCards database, and functional and pathway annotations were carried out, thereby revealing the key target. MR analysis was conducted between body anthropometric indexes of obesity and the key target using an IVW model. Bioinformatics analysis revealed Apolipoprotein E (APOE) as the key target of obesity-induced AD. MR results showed that body mass index (BMI) had a negative causal association with APOE2, while body fat percentage (BFP) and trunk fat percentage (TFP) had no significant causal association with APOE2; BMI, BFP, and TFP had a negative causal association with APOE3, and none had any significant causal association with APOE4. In conclusion, there is a correlation between obesity and AD, which is mainly due to the polymorphism of the APOE gene rather than adipose tissue distribution. APOE3 carriers may be more susceptible to obesity, while the risk of AD caused by APOE2 and APOE4 may not be induced by obesity. This study sheds new light on current disputes. At the same time, it is suggested to regulate the body fat mass of APOE3 carriers in the early stage, and to reduce the risk of AD.

Genetic Insights into Obesity and Brain: Combine Mendelian Randomization Study and Gene Expression Analysis

As a major public-health concern, obesity is imposing an increasing social burden around the world. The link between obesity and brain-health problems has been reported, but controversy remains. To investigate the relationship among obesity, brain-structure changes and diseases, a two-stage analysis was performed. At first, we used the Mendelian-randomization (MR) approach to identify the causal relationship between obesity and cerebral structure. Obesity-related data were retrieved from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and the UK Biobank, whereas the cortical morphological data were from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Further, we extracted region-specific expressed genes according to the Allen Human Brian Atlas (AHBA) and carried out a series of bioinformatics analyses to find the potential mechanism of obesity and diseases. In the univariable MR, a higher body mass index (BMI) or larger visceral adipose tissue (VAT) was associated with a smaller global cortical thickness (pBMI = 0.006, pVAT = 1.34 × 10-4). Regional associations were found between obesity and specific gyrus regions, mainly in the fusiform gyrus and inferior parietal gyrus. Multivariable MR results showed that a greater body fat percentage was linked to a smaller fusiform-gyrus thickness (p = 0.029) and precuneus surface area (p = 0.035). As for the gene analysis, region-related genes were enriched to several neurobiological processes, such as compound transport, neuropeptide-signaling pathway, and neuroactive ligand-receptor interaction. These genes contained a strong relationship with some neuropsychiatric diseases, such as Alzheimer's disease, epilepsy, and other disorders. Our results reveal a causal relationship between obesity and brain abnormalities and suggest a pathway from obesity to brain-structure abnormalities to neuropsychiatric diseases.