Body Shape and Alzheimer's Disease: A Mendelian Randomization Analysis

Effect of caffeine intake on self-reported and genetic prediction of osteoarthritis: an epidemiological study and Mendelian randomization analysis

Background

Osteoarthritis (OA) holds the distinction of being the most widespread musculoskeletal disorder. Any disruptions in the integrity of the articular cartilage can result in joint malfunction, discomfort, and impaired physical functioning. Increasing evidence indicates the negative impacts of caffeine intake on hyaline cartilage. The primary objective of this study was to delve deeper into understanding the potential link between the consumption of caffeine and the risk of developing OA.

Methods

In this study, we constructed logistic regression models to evaluate the correlation between caffeine consumption and the risk of osteoarthritis using data from the National Health and Nutrition Examination Survey. Following that, we utilized genome-wide association studies to conduct a Mendelian randomization (MR) analysis investigating the association between coffee consumption and the likelihood of developing knee OA. We employed various statistical methods, including inverse variance weighting (IVW), weighted median, weighted mode, simple mode, and MR-Egger regression, to ensure comprehensive analysis and robust conclusions. To evaluate heterogeneity and the potential impact of pleiotropy, we conducted several statistical tests, including Cochran's Q test, MR-Egger intercept test, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR Steiger test.

Results

The weighted multivariate logistic regression analysis showed that the relationship between high caffeine intake (95-206 and ≥206 mg/day) and OA prevalence remained significantly high even after adjusting for covariates using the lowest caffeine intake (< 11 mg/day) as reference: Model 1-OR (95% Cl) = 1.365 (1.18-1.58) and 1.59 (1.38-1.83); Model 2-OR (95% Cl) = 1.21 (1.04-1.42) and 1.44 (1.23-1.68); and Model 3-OR (95% Cl) = 1.19 (1.01-1.40) and 1.30 (1.10-1.52), respectively (p < 0.05). The findings from the fixed effects inverse variance weighted (IVW) analysis revealed a statistically significant link between coffee intake and the likelihood of developing knee osteoarthritis: OR = 1.94; 95% confidence interval (Cl) =1.471-2.517; (p < 0.001). Consistent findings were obtained across various other methods, including MR-Egger regression, weighted median, weighted mode, and simple mode analyses.

Conclusion

Our study showed a positive correlation between OA prevalence and high caffeine intake (≥95 mg/day).

Dementia prevention: the Mendelian randomisation perspective

Understanding the causes of Alzheimer's disease and related dementias remains a challenge. Observational studies investigating dementia risk factors are limited by the pervasive issues of confounding, reverse causation and selection biases. Conducting randomised controlled trials for dementia prevention is often impractical due to the long prodromal phase and the inability to randomise many potential risk factors. In this essay, we introduce Mendelian randomisation as an alternative approach to examine factors that may prevent or delay Alzheimer's disease. Mendelian randomisation is a causal inference method that has successfully identified risk factors and treatments in various other fields. However, applying this method to dementia risk factors has yielded unexpected findings. Here, we consider five potential explanations and provide recommendations to enhance causal inference from Mendelian randomisation studies on dementia. By employing these strategies, we can better understand factors affecting dementia risk.

Genetically proxied lean mass and risk of Alzheimer's disease: mendelian randomisation study

Objective

To examine whether genetically proxied lean mass is associated with risk of Alzheimer's disease.

Design

Mendelian randomisation study.

Setting

The UK Biobank study and genome wide association study meta-analyses of Alzheimer's disease and cognitive performance.

Participants

Summary level genetic data from: 450 243 UK Biobank participants with impedance measures of lean mass and fat mass; an independent sample of 21 982 patients with Alzheimer's disease and 41 944 controls without Alzheimer's disease; a replication sample of 7329 patients with Alzheimer's disease and 252 879 controls; and 269 867 individuals taking part in a genome wide association study of cognitive performance.

Main outcome measure

Effect of genetically proxied lean mass on the risk of Alzheimer's disease, and the related phenotype of cognitive performance.

Results

An increase in genetically proxied appendicular lean mass of one standard deviation was associated with a 12% reduced risk of Alzheimer's disease (odds ratio 0.88, 95% confidence interval 0.82 to 0.95, P=0.001). This finding was replicated in an independent cohort of patients with Alzheimer's disease (0.91, 0.83 to 0.99, P=0.02) and was consistent in sensitivity analyses that are more robust to the inclusion of pleiotropic variants. Higher genetically proxied appendicular lean mass was also associated with increased cognitive performance (standard deviation increase in cognitive performance for each standard deviation increase in appendicular lean mass 0.09, 95% confidence interval 0.06 to 0.11, P=0.001), and adjusting for potential mediation through genetically proxied cognitive performance did not reduce the association between appendicular lean mass and risk of Alzheimer's disease. Similar results were found for the outcomes of Alzheimer's disease and cognitive performance when the risk factors of genetically proxied trunk lean mass and whole body lean mass were used, respectively, adjusted for genetically proxied fat mass.

Conclusions

These findings suggest that lean mass might be a possible modifiable protective factor for Alzheimer's disease. The mechanisms underlying this finding, as well as the clinical and public health implications, warrant further investigation.

Association of Body Mass Index and the Risk of Gastro-Esophageal Cancer: A Mendelian Randomization Study in a Japanese Population

There are growing concerns that body mass index (BMI) is related to cancer risk at various anatomical sites, including the upper gastrointestinal tract, and the existence of a causal relationship remains unclear. The Mendelian randomization (MR) method uses instrumental genetic variables of risk factors to explore whether a causal relationship exists while preventing confounding. In our study, genome-wide association study (GWAS) data from the BioBank Japan (BBJ) project were used. Genetic variants were chosen as instrumental variables using inverse-variance weighting (IVW), MR-Egger regression and weighted-median methods to estimate the causal relationship between BMI and the risk of gastro-esophageal cancer. We found no evidence to support a causal association between BMI and risk of gastric cancer [odds ratio (OR) =0.99 per standard deviation (SD) increase in BMI; 95% confidence interval (CI): (0.76-1.30); P = 0.96] or esophageal cancer [0.78(0.50-1.22); P = 0.28] using the IVW method. Sensitivity analysis did not reveal any sign of horizontal pleiotropy. Additionally, in the gender-stratified analysis, no causal association was found. Findings from this study do not support a causal effect of BMI on gastro-esophageal cancer risk. However, we cannot rule out a modest or nonlinear effect of BMI.

Body shape and risk of glaucoma: A Mendelian randomization

Background

Body size (BS) is one of the risk factors for the development of many clinical diseases, but the relationship between BS and glaucoma is controversial. Herein, we try to use Mendelian randomization (MR) method to study BS causal association with glaucoma risk from the genetic level.

Methods

The Body Size was determined through anthropometric traits (ATs), such as body mass index (BMI), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), waist-to-hip ratio (WHR), and waist circumference (WC). Association of single nucleotide polymorphisms (SNPs) with each AT and glaucoma were determined individually from the aggregated data of the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the FinnGen study summary data (8,591 cases with glaucoma and 210,201 controls). To explore the role of BS and glaucoma, a two-sample MR analysis was performed on genome-wide association study (GWAS) data. Besides, three MR methods [inverse variance weighted (IVW), Weighted median, and MR-Egger regression] were used to get the whole causal estimate for multiple instrumental SNPs.

Results

BMI (OR = 1.20; 95% CI = 1.02-1.41; P = 0.03) and WC (OR = 1.32; 95% CI =1.04-1.69; P = 0.03) were associated with a risk of glaucoma. Besides, genetically predicted WHRadjBMI (OR = 1.10; 95% CI = 0.88-1.35; P = 0.43) and WHR (OR = 1.22; 95% CI = 0.93-1,572; P = 0.14) were not associated with glaucoma. No heterogeneity and directional pleiotropy were detected.

Conclusion

The data of this study revealed that increased BMI and WC are potential risk factors for glaucoma, and WHRadjBMI and WHR are not associated with the occurrence of glaucoma.

Self-reported and genetically predicted effects of coffee intake on rheumatoid arthritis: Epidemiological studies and Mendelian randomization analysis

Background and aims

Causal research concerning coffee intake and rheumatoid arthritis (RA) risk is controversial. The objective of this study was to further explore the causal relationship between coffee intake and RA risk.

Methods

The 4,310 participants from NHANES 2003–2006 were included in an epidemiological study to assess the association between coffee intake and RA by weighted multivariate logistic regression. The inverse variance weighted (IVW) method of two-sample Mendelian randomization (MR), employing genetic data from UK Biobank (428,860 cases) of coffee intake and MR-Base platform (14,361 cases and 43,923 controls) of RA, was performed to estimate the causal relationship between coffee intake and RA.

Results

Weighted multivariate logistic regression suggested no significant correlation between coffee intake and RA. Compared to the no-coffee group, the odds ratio for RA in the <1, 1–3, ≥4 cups/day group were 1.297, 1.378, and 1.125 (P = 0.204, 0.098, and 0.698, respectively). In the IVW of MR analysis, there was no causal relationship between coffee intake and RA (OR = 1.47, P = 0.218).

Conclusion

Our study did not support a causal association between coffee intake and RA risk. However, it is necessary to consider valid information on coffee intake, including brewing method, type of coffee, and quantity, in further analysis of coffee intake and RA.

Causality of abdominal obesity on cognition: a trans-ethnic Mendelian randomization study

BACKGROUND

Obesity has been associated with cognition in observational studies; however, whether its effect is confounding or a reverse causality remains inconclusive. This study aimed to investigate the causal relationships of overall obesity, measured by body mass index (BMI), and abdominal adiposity, measured by waist-hip ratio adjusted for BMI (WHRadjBMI), and cognition across European and Asian populations using Mendelian randomization (MR) analysis.

METHODS

We used publicly available genome-wide association study (GWAS) summary data of European ancestry, including BMI (n = 322,154) and WHRadjBMI (n = 210,088) from the GIANT consortium, and cognition performance (n = 257,828) from the UK Biobank and COGENT consortium. Data for individuals of Asian ancestry were retrieved from Taiwan Biobank to perform GWAS for BMI (n = 65,689), WHRadjBMI (n = 65,683), and Mini-Mental State Examination (MMSE, n = 21,273). MR analysis was carried out using the inverse-variance weighted method for the main results. Further, we examined the overall pleiotropy by MR-Egger intercept, and detected and adjusted for possible outliers using MR PRESSO.

RESULTS

No causal effect of BMI on cognition performance (beta [95% CI] = 0.00 [-0.07, 0.07], p value = 0.91) was found for Europeans; however, a 1-SD increase in WHRadjBMI was associated with a 0.07 standardized score decrease in cognition performance (beta [95% CI] = -0.07 [-0.12, -0.02], p value = 0.006). Further, no causal effect of BMI on MMSE (beta [95% CI] = 0.01 [-0.08, 0.10], p = 0.91) was found for Asians; however, a 1-SD increase in WHRadjBMI was associated with a 0.17 standardized score decrease in MMSE (beta [95% CI] = -0.17 [-0.30, -0.03], p = 0.02). In both populations, overall pleiotropy was not detected, and outliers did not affect the robustness of the main findings.

CONCLUSIONS

This trans-ethnic MR study reveals that abdominal adiposity, as measured by WHR adjusted for BMI, impairs cognition, whereas weak evidence suggests that BMI impairs cognition.

Late-Life Obesity Associated with Tau Pathology in Cognitively Normal Individuals: The CABLE Study

BACKGROUND

Existed evidence suggests that midlife obesity increases the risk of Alzheimer's disease (AD), while there is an inverse association between AD and obesity in late life. However, the underlying metabolic changes of AD pathological proteins attributed to obesity in two life stages were not clear.

OBJECTIVE

To investigate the associations of obesity types and obesity indices with AD biomarkers in cerebrospinal fluid (CSF) in different life stages.

METHODS

We recruited 1,051 cognitively normal individuals (61.94±10.29 years, 59.66%male) from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) study with CSF detections for amyloid-β 42 (Aβ 42), total-tau (T-tau), and phosphorylated tau (P-tau). We utilized body mass index, waist circumference, waist-to-height ratio, and metabolic risk factors to determine human obesity types. Multiple linear models and interaction analyses were run to assess the impacts of obesity on AD biomarkers.

RESULTS

The metabolically unhealthy obesity or healthy obesity might exert a reduced tau pathology burden (p <  0.05). Individuals with overweight, general obesity, and central obesity presented lower levels of tau-related proteins in CSF than normal controls (p <  0.05). Specially, for late-life individuals, higher levels of obesity indices were associated with a lower load of tau pathology as measured by CSF T-tau and T-tau/Aβ 42 (p <  0.05). No similar significant associations were observed in midlife.

CONCLUSION

Collectively, late-life general and central obesity seems to be associated with the reduced load of tau pathology, which further consolidates the favorable influence of obesity in specific life courses for AD prevention.

Invited Commentary: Body Mass Index and Risk of Dementia-Potential Explanations for Life-Course Differences in Risk Estimates and Future Research Directions

The relationship between body mass index (BMI) and health outcomes of older adults, including dementia, remains controversial. Many studies find inverse associations between BMI and dementia among older adults, while in other studies high BMI in midlife is associated with increased dementia risk. In this issue, Li et al. (Am J Epidemiol. 2021;190(12):2503-2510) examine BMI from mid- to late life and risk of dementia using the extensive follow-up of the Framingham Offspring Study. They found changing trends in the association between BMI and dementia from a positive association for midlife (ages 40-49) to an inverse trend in late life. Their work demonstrates the importance of studying dementia risk factors across the life course. Midlife obesity might be an important modifiable risk factor for dementia. However, because incipient dementia can lead to weight loss, reverse causation remains a key source of bias that could explain an inverse trend between BMI and dementia in older ages. The extent of other biases, including unmeasured confounding, inaccuracy of BMI as a measure for adiposity, or selective survival, are also unclear. Triangulating evidence on body composition and dementia risk could lead to better targets for dementia intervention, but future work will need to evaluate specific pathways.

Characterisation of insomnia as an environmental risk factor for asthma via Mendelian randomization and gene environment interaction

Asthma is a complex disease that is reportedly associated with insomnia. However, the causal directionality of this association is still unclear. We used asthma and insomnia-associated single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) summary statistics to test the causal directionality between insomnia and asthma via Mendelian randomization (MR) analysis. We also performed a cross-trait meta-analysis using UK Biobank GWAS summary statistics and a gene–environment interaction study using data from UK Biobank. The interaction of genetic risk score for asthma (GRS_asthma) with insomnia on asthma was tested by logistic regression. Insomnia was a risk factor for the incidence of asthma, as revealed by three different methods of MR analysis. However, asthma did not act as a risk factor for insomnia. The cross-trait meta-analysis identified 28 genetic loci shared between asthma and insomnia. In the gene–environment interaction study, GRS_asthma interacted with insomnia to significantly affect the risk of asthma. The results of this study highlight the importance of insomnia as a risk factor of asthma, and warrant further analysis of the mechanism through which insomnia affects the risk of asthma.

Extension of Mendelian Randomization to Identify Earliest Manifestations of Alzheimer Disease: Association of Genetic Risk Score for Alzheimer Disease With Lower Body Mass Index by Age 50 Years

Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006-2010, who were without dementia, aged 39-73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): -0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = -0.03, 95% CI: -0.06, -0.01) and 60- to 73-year-olds (β = -0.09, 95% CI:-0.12, -0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis.

The association between fatty acid intake and breast cancer based on the NHANES and Mendelian randomization study

BACKGROUND

Observational studies have examined the association between fatty acid intake and breast cancer (BC), and the association might vary depending on menopausal status, but the results remain controversial. The objective of this study was to investigate the associations between fatty acid intake and BC.

METHODS

The National Health and Nutrition Examination Survey (NHANES) 1999-2016 was used in the study, and stratified analysis by menopausal status was performed. Logistic regression models were used to evaluate the associations between BC and intake of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (PUFAs), adjusting for covariates. Three two-sample Mendelian randomization (MR) methods-inverse variance weighted (IVW), weighted median, and Mendelian randomization-Egger (MR-Egger) regression-were applied to further verify the associations between intake of fatty acids and BC.

RESULTS

Higher intake of MUFAs was associated with lower risk of BC in premenopausal women: ORs (95 %CI): 0.325 (0.110, 0.964). IVW showed that increased intake of MUFAs was associated with a reduced risk of BC: 0.997 (0.995, 1.000), p = 0.024. No associations between BC and SFAs, MUFAs or PUFAs were found in postmenopausal women or in the overall population.

CONCLUSIONS

Increasing intake of MUFAs might reduce the risk of BC in premenopausal women. The protective effect of MUFAs on BC was also supported by MR study.

Life Course Adiposity and Alzheimer's Disease: A Mendelian Randomization Study

BACKGROUND

Several studies showed that life course adiposity was associated with Alzheimer's disease (AD). However, the underlying causality remains unclear.

OBJECTIVE

We aimed to examine the causal relationship between life course adiposity and AD using Mendelian randomization (MR) analysis.

METHODS

Instrumental variants were obtained from large genome-wide association studies (GWAS) for life course adiposity, including birth weight (BW), childhood body mass index (BMI), adult BMI, waist circumference (WC), waist-to-hip ratio (WHR), and body fat percentage (BFP). A meta-analysis of GWAS for AD including 71,880 cases and 383,378 controls was used in this study. MR analyses were performed using inverse variance weighted (IVW), weighted median, and MR-Egger regression methods. We calculated odds ratios (ORs) per genetically predicted standard deviation (1-SD) unit increase in each trait for AD.

RESULTS

Genetically predicted 1-SD increase in adult BMI was significantly associated with higher risk of AD (IVW: OR = 1.03, 95% confidence interval [CI] = 1.01-1.05, p = 2.7×10-3) after Bonferroni correction. The weighted median method indicated a significant association between BW and AD (OR = 0.94, 95% CI = 0.90-0.98, p = 1.8×10-3). We also found suggestive associations of AD with WC (IVW: OR = 1.03, 95% CI = 1.00-1.07, p = 0.048) and WHR (weighted median: OR = 1.04, 95% CI = 1.00-1.07, p = 0.029). No association was detected of AD with childhood BMI and BFP.

CONCLUSION

Our study demonstrated that lower BW and higher adult BMI had causal effects on increased AD risk.