Body Mass Index, Abdominal Adiposity, and Incidence of Parkinson Disease in French Women From the E3N Cohort Study

Novel Insights Into the Causal Effects and Shared Genetics Between Body Fat and Parkinson Disease

AIMS

Existing observational studies examining the effect of body fat on the risk of Parkinson disease (PD) have yielded inconsistent results. We aimed to investigate this causal relationship at the genetic level.

METHODS

We employed two-sample Mendelian randomization (TSMR) to investigate the causal effects of body fat on PD, with multiple sex-specific body fat measures being involved. We performed Bayesian colocalization analysis and cross-trait meta-analysis to reveal pleiotropic genomic loci shared between body mass index (BMI) and PD. Finally, we used the MAGMA tool to perform tissue enrichment analysis of the genome-wide association study hits of BMI.

RESULTS

TSMR analysis suggests that except waist circumference, higher measures of body fatness are associated with a decreased risk of PD, including BMI (OR: 0.83), body fat percentage (OR: 0.69), body fat mass (OR: 0.77), and hip circumference (OR: 0.83). The observed effects were slightly more pronounced in females than males. Colocalization analysis highlighted two colocalized regions (chromosome 3p25.3 and chromosome 17p12) shared by BMI and PD and pointed to some genes as possible players, including SRGAP3, MTMR14, and ADORA2B. Cross-trait meta-analysis successfully identified 10 novel genomic loci, involving genes of TOX3 and MAP4K4. Tissue enrichment analysis showed that BMI-associated genetic variants were enriched in multiple brain tissues.

CONCLUSIONS

We found that nonabdominal body fatness exerts a robust protective effect against PD. Our colocalization analysis and cross-trait meta-analysis identified pleiotropic genetic variation shared between BMI and PD, providing new clues for understanding the association between body fat and PD.

Identifying potential causal effects of Parkinson's disease: A polygenic risk score-based phenome-wide association and mendelian randomization study in UK Biobank

There is considerable uncertainty regarding the associations between various risk factors and Parkinson's Disease (PD). This study systematically screened and validated a wide range of potential PD risk factors from 502,364 participants in the UK Biobank. Baseline data for 1851 factors across 11 categories were analyzed through a phenome-wide association study (PheWAS). Polygenic risk scores (PRS) for PD were used to diagnose Parkinson's Disease and identify factors associated with PD diagnosis through PheWAS. Two-sample Mendelian randomization (MR) analysis was employed to assess causal relationships. PheWAS results revealed 267 risk factors significantly associated with PD-PRS among the 1851 factors, and of these, 27 factors showed causal evidence from MR analysis. Compelling evidence suggests that fluid intelligence score, age at first sexual intercourse, cereal intake, dried fruit intake, and average total household income before tax have emerged as newly identified risk factors for PD. Conversely, maternal smoking around birth, playing computer games, salt added to food, and time spent watching television have been identified as novel protective factors against PD. The integration of phenotypic and genomic data may help to identify risk factors and prevention targets for PD.

Consumption of milk and other dairy products and incidence of Parkinson's disease: a prospective cohort study in French women

Previous studies showed positive associations between milk intake and Parkinson's disease (PD) in men but not in women, but few studies were available in women. Due to the long prodromal PD phase, reverse causation represents a major threat to investigations of diet in PD; cohort studies with a long follow-up are needed. We investigated associations between intake of milk and other dairy products with PD incidence in women from the E3N cohort study (1993-2018). PD diagnoses were validated using medical records and drug claim databases. Diet was assessed via a dietary questionnaire. Hazard ratios (HR) were estimated using multivariable Cox regression models. Exposures were lagged by 5y in main analyses and longer lags in sensitivity analyses. We examined the impact of adjustment for premotor symptoms (constipation/depression). During a mean follow-up of 18.8y, 845 of 71,542 women developed PD. Main analyses showed a J-shaped association between total milk intake and PD (P-non linearity = 0.045), with a significant linear positive association among drinkers (HR/1-SD = 1.09, 95% CI = 1.01-1.18, P = 0.024), that was explained in secondary analyses by a different pattern of association for plain milk (alone or with cereals) and milk added to drinks (tea/coffee/chicory). PD incidence increased significantly with plain milk consumption (HR/1-SD = 1.08 [1.02-1.14], P = 0.014). A U-shaped relation was observed for milk added to drinks (P-non linearity = 0.038), with lower PD incidence in women with moderate consumption (HR = 0.77 [0.61-0.97], P = 0.030) and no difference between non-drinkers and those with the highest consumption (HR = 0.98 [0.79-1.21], P = 0.848). Findings were similar in analyses using longer lags and adjusted for constipation/depression. Consumption of other dairy products was not associated with PD. A J-shaped association between total milk intake and PD was explained by a different pattern of association for plain milk intake and milk added to drinks. Reverse causation is unlikely to explain a positive association of plain milk with PD incidence in women. The U-shaped relation for milk added to drinks could be explained by an interaction between milk and coffee/tea/chicory. Further studies are warranted to elucidate the underlying mechanisms.

Association Between Body Composition Patterns, Cardiovascular Disease, and Risk of Neurodegenerative Disease in the UK Biobank

BACKGROUND AND OBJECTIVES

Accumulating evidence connects diverse components of body composition (e.g., fat, muscle, and bone) to neurodegenerative disease risk, yet their interplay remains underexplored. This study examines the associations between patterns of body composition and the risk of neurodegenerative diseases, exploring the mediating role of cardiovascular diseases (CVDs).

METHODS

This retrospective analysis used data from the UK Biobank, a prospective community-based cohort study. We included participants free of neurodegenerative diseases and with requisite body composition measurements at recruitment, who were followed from 5 years after recruitment until April 1, 2023, to identify incident neurodegenerative diseases. We assessed the associations between different components and major patterns of body composition (identified by principal component analysis) with the risk of neurodegenerative diseases, using multivariable Cox models. Analyses were stratified by disease susceptibility, indexed by polygenetic risk scores for Alzheimer and Parkinson diseases, APOE genotype, and family history of neurodegenerative diseases. Furthermore, we performed mediation analysis to estimate the contribution of CVDs to these associations. In addition, in a subcohort of 40,790 participants, we examined the relationship between body composition patterns and brain aging biomarkers (i.e., brain atrophy and cerebral small vessel disease).

RESULTS

Among 412,691 participants (mean age 56.0 years, 55.1% female), 8,224 new cases of neurodegenerative diseases were identified over an average follow-up of 9.1 years. Patterns identified as "fat-to-lean mass," "muscle strength," "bone density," and "leg-dominant fat distribution" were associated with a lower rate of neurodegenerative diseases (hazard ratio [HR] = 0.74-0.94) while "central obesity" and "arm-dominant fat distribution" patterns were associated with a higher rate (HR = 1.13-1.18). Stratification analysis yielded comparable risk estimates across different susceptibility groups. Notably, 10.7%-35.3% of the observed associations were mediated by CVDs, particularly cerebrovascular diseases. The subcohort analysis of brain aging biomarkers corroborated the findings for "central obesity," "muscle strength," and "arm-dominant fat distribution" patterns.

DISCUSSION

Our analyses demonstrated robust associations of body composition patterns featured by "central obesity," "muscle strength," and "arm-dominant fat distribution" with both neurodegenerative diseases and brain aging, which were partially mediated by CVDs. These findings underscore the potential of improving body composition and early CVD management in mitigating risk of neurodegenerative diseases.

Association of Body Mass Index and Parkinson Disease: A Bidirectional Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

The role of body mass index (BMI) in Parkinson disease (PD) is unclear. Based on the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in PD (Courage-PD) consortium, we used 2-sample Mendelian randomization (MR) to replicate a previously reported inverse association of genetically predicted BMI with PD and investigated whether findings were robust in analyses addressing the potential for survival and incidence-prevalence biases. We also examined whether the BMI-PD relation is bidirectional by performing a reverse MR.

METHODS

We used summary statistics from a genome-wide association study (GWAS) to extract the association of 501 single-nucleotide polymorphisms (SNPs) with BMI and from the Courage-PD and international Parkinson Disease Genomics Consortium (iPDGC) to estimate their association with PD. Analyses are based on participants of European ancestry. We used the inverse-weighted method to compute odds ratios (ORIVW per 4.8 kg/m2 [95% CI]) of PD and additional pleiotropy robust methods. We performed analyses stratified by age, disease duration, and sex. For reverse MR, we used SNPs associated with PD from 2 iPDGC GWAS to assess the effect of genetic liability toward PD on BMI.

RESULTS

Summary statistics for BMI are based on 806,834 participants (54% women). Summary statistics for PD are based on 8,919 (40% women) cases and 7,600 (55% women) controls from Courage-PD, and 19,438 (38% women) cases and 24,388 (51% women) controls from iPDGC. In Courage-PD, we found an inverse association between genetically predicted BMI and PD (ORIVW 0.82 [0.70-0.97], p = 0.012) without evidence for pleiotropy. This association tended to be stronger in younger participants (≤67 years, ORIVW 0.71 [0.55-0.92]) and cases with shorter disease duration (≤7 years, ORIVW 0.75 [0.62-0.91]). In pooled Courage-PD + iPDGC analyses, the association was stronger in women (ORIVW 0.85 [0.74-0.99], p = 0.032) than men (ORIVW 0.92 [0.80-1.04], p = 0.18), but the interaction was not statistically significant (p-interaction = 0.48). In reverse MR, there was evidence for pleiotropy, but pleiotropy robust methods showed a significant inverse association.

DISCUSSION

Using an independent data set (Courage-PD), we replicate an inverse association of genetically predicted BMI with PD, not explained by survival or incidence-prevalence biases. Moreover, reverse MR analyses support an inverse association between genetic liability toward PD and BMI, in favor of a bidirectional relation.

Association of metabolic syndrome and its components with Parkinson's disease: a cross-sectional study

BACKGROUND

The interrelation between metabolic syndrome (MetS) and Parkinson's disease (PD) likely arises from shared pathological mechanisms. This study thus aims to examine the impact of MetS and its components on PD.

METHODS

This study utilized data extracted from the National Health and Nutrition Examination Survey database spanning 1999 to 2020. The random forest algorithm was applied to fill in the missing data. Propensity score optimal full matching was conducted. The data were adjusted by total weights derived from both sampling and matching weights. The weighted data were utilized to create multifactor logistic regression models. Odds ratios (ORs) and average marginal effects, along with their corresponding 95% confidence intervals (CIs), were calculated.

RESULTS

MetS did not significantly affect the risk of PD (OR: 1.01; 95% CI: 0.77, 1.34; P = 0.92). Hypertension elevated the risk of PD (OR: 1.33; 95% CI: 1.01, 1.76; P = 0.045), accompanied by a 0.26% increased probability of PD occurrence (95% CI: 0.01%, 0.52%; P = 0.04). Diabetes mellitus (DM) had a 1.38 times greater likelihood of developing PD (OR:1.38; 95% CI: 1.004, 1.89; P = 0.046), corresponding to a 0.32% increased probability of PD occurrence (95% CI: -0.03%, 0.67%; P = 0.07). Nevertheless, no correlation was observed between hyperlipidemia, waist circumference and PD.

CONCLUSION

MetS does not affect PD; however, hypertension and DM significantly increase the risk of PD.

Obstructive sleep apnea in Parkinson's disease: A prevalent, clinically relevant and treatable feature

Parkinson's disease (PD) is a chronic neurodegenerative disease characterized by motor and non-motor symptoms, including obstructive sleep apnea (OSA), a common comorbid sleep disorder. The prevalence of OSA in PD is high, and its impact on quality of life, accident risk, and limited treatment options underscores the need for vigilant monitoring and effective interventions. OSA is observed in 20-70% of PD patients, whereas the general population exhibits a lower prevalence ranging from 2 to 14%. These discrepancies in prevalence may be attributed to differences in demographic characteristics, sample sizes with selection bias, and variations in scoring systems for apnea and hypopnea events used across different studies. This review highlights the potential pathogenesis of comorbid OSA in PD and provides an overview of ongoing clinical trials investigating interventions for this condition. Several mechanisms have been implicated in the development of OSA in PD, including intermittent hypoxemia, sleep fragmentation, alterations in the glymphatic system homeostasis, upper airway obstruction, and inflammation. Given the adverse effects of PD comorbid OSA, early intervention measures are crucial. It is imperative to conduct longitudinal studies and clinical trials to elucidate the pathogenesis and develop novel and effective interventions for OSA in PD patients. These efforts aim to delay the progression of PD, enhance patients' quality of life, and alleviate the burden on society and families.