Potential Protective Link Between Type I Diabetes and Parkinson's Disease Risk and Progression

The potential protective role of Parkinson's disease against hypothyroidism: co-localisation and bidirectional Mendelian randomization study

Background

The association between hypothyroidism and Parkinson's disease (PD) has sparked intense debate in the medical community due to conflicting study results. A better understanding of this association is crucial because of its potential implications for both pathogenesis and treatment strategies.

Methods

To elucidate this complex relationship, we used Bayesian co-localisation (COLOC) and bidirectional Mendelian randomization (MR) analysis. COLOC was first used to determine whether hypothyroidism and PD share a common genetic basis. Subsequently, genetic variants served as instrumental variables in a bidirectional MR to explore causal interactions between these conditions.

Results

COLOC analysis revealed no shared genetic variants between hypothyroidism and PD, with a posteriori probability of hypothesis 4 (PPH4) = 0.025. Furthermore, MR analysis indicated that hypothyroidism does not have a substantial causal effect on PD (OR = 0.990, 95% CI = 0.925, 1.060, p = 0.774). Conversely, PD appears to have a negative causal effect on hypothyroidism (OR = 0.776, 95% CI = 0.649, 0.928, p = 0.005).

Conclusion

Our findings suggest the absence of shared genetic variants between hypothyroidism and PD. Interestingly, PD may inversely influence the risk of developing hypothyroidism, a finding that may inform future research and clinical approaches.

Investigation of the causal association between Parkinson's disease and autoimmune disorders: a bidirectional Mendelian randomization study

Background

To date, an increasing number of epidemiological evidence has pointed to potential relationships between Parkinson's disease (PD) and various autoimmune diseases (AIDs), however, no definitive conclusions has been drawn about whether PD is causally related to AIDs risk.

Methods

By employing summary statistics from the latest and most extensive genome-wide association studies (GWAS), we performed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal associations between PD and a variety of 17 AIDs, encompassing multiple sclerosis, neuromyelitis optica spectrum disorder, myasthenia gravis, asthma, inflammatory bowel disease, Crohn's disease, ulcerative colitis, irritable bowel syndrome, celiac disease, primary biliary cirrhosis, primary sclerosing cholangitis, type 1 diabetes, ankylosing spondylitis, rheumatoid arthritis, systemic lupus erythematosus, psoriasis and vitiligo. Inverse-variance weighted (IVW) was adopted as the main statistical approach to obtain the causal estimates of PD on different AIDs, supplemented by a series of complementary analyses (weighted median, MR Egger regression, and MR-PRESSO) for further strengthening the robustness of results.

Results

Our MR findings suggested that genetically predicted higher liability to PD was causally associated with a decreased risk of irritable bowel syndrome (OR = 0.98; 95% CI: 0.96-0.99; P = 0.032). On the contrary, IVW analysis showed a potential positive correlation between genetically determined PD and the incidence of type 1 diabetes (OR = 1.10; 95%CI: 1.02-1.19; P = 0.010). Subsequent MR tests ended up in similar results, confirming our findings were reliable. Additionally, in the reverse MR analyses, we did not identify any evidence to support the causal relationship of genetic predisposition to AIDs with PD susceptibility.

Conclusion

In general, a bifunctional role that PD exerted on the risk of developing AIDs was detected in our studies, both protecting against irritable bowel syndrome occurrence and raising the incidence of type 1 diabetes. Future studies, including population-based observational studies and molecular experiments in vitro and in vivo, are warranted to validate the results of our MR analyses and refine the underlying pathological mechanisms involved in PD-AIDs associations.

Causal relationship between diabetes mellitus, glycemic traits and Parkinson's disease: a multivariable mendelian randomization analysis

BACKGROUND

Observational studies have indicated an association between diabetes mellitus (DM), glycemic traits, and the occurrence of Parkinson's disease (PD). However, the complex interactions between these factors and the presence of a causal relationship remain unclear. Therefore, we aim to systematically assess the causal relationship between diabetes, glycemic traits, and PD onset, risk, and progression.

METHOD

We used two-sample Mendelian randomization (MR) to investigate potential associations between diabetes, glycemic traits, and PD. We used summary statistics from genome-wide association studies (GWAS). In addition, we employed multivariable Mendelian randomization to evaluate the mediating effects of anti-diabetic medications on the relationship between diabetes, glycemic traits, and PD. To ensure the robustness of our findings, we performed a series of sensitivity analyses.

RESULTS

In our univariable Mendelian randomization (MR) analysis, we found evidence of a causal relationship between genetic susceptibility to type 1 diabetes (T1DM) and a reduced risk of PD (OR = 0.9708; 95% CI: 0.9466, 0.9956; P = 0.0214). In our multivariable MR analysis, after considering the conditions of anti-diabetic drug use, this correlation disappeared with adjustment for potential mediators, including anti-diabetic medications, insulin use, and metformin use.

CONCLUSION

Our MR study confirms a potential protective causal relationship between genetically predicted type 1 diabetes and reduced risk of PD, which may be mediated by factors related to anti-diabetic medications.

Association between Type 1 Diabetes Mellitus and Parkinson's Disease: A Mendelian Randomization Study

While much evidence suggests that type 2 diabetes mellitus increases the risk of Parkinson's disease (PD), the relationship between type 1 diabetes mellitus (T1DM) and PD is unclear. To study their association, we performed a two-sample Mendelian randomization (MR) using the following statistical methods: inverse variance weighting (IVW), MR-Egger, weight median, and weighted mode. Independent datasets with no sample overlap were retrieved from the IEU GWAS platform. All the MR methods found a lower risk of PD in T1DM (IVW-OR 0.93, 95% CI 0.91-0.96, p = 3.12 × 10-5; MR-Egger-OR 0.93, 95% CI 0.88-0.98, p = 1.45 × 10-2; weighted median-OR 0.93, 95% CI 0.89-0.98, p = 2.76 × 10-3; and weighted mode-OR 0.94, 95% CI 0.9-0.98, p = 1.58 × 10-2). The findings were then replicated with another independent GWAS dataset on T1DM (IVW-OR 0.97, 95% CI 0.95-0.99, p = 3.10 × 10-3; MR-Egger-OR 0.96, 95% CI 0.93-0.99, p = 1.08 × 10-2; weighted median-OR 0.97, 95% CI 0.94-0.99, p = 1.88 × 10-2; weighted mode-OR 0.97, 95% CI 0.94-0.99, p = 1.43 × 10-2). Thus, our study provides evidence that T1DM may have a protective effect on PD risk, though further studies are needed to clarify the underlying mechanisms.

Causal relationships between type 1 diabetes mellitus and Alzheimer's disease and Parkinson's disease: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous compelling evidence suggests an association between Type 2 diabetes (T2D) and neurodegenerative diseases. However, it remains uncertain whether Type 1 diabetes mellitus (T1DM) exerts a causal influence on the risk of Alzheimer's disease (AD) and Parkinson's disease (PD). Consequently, this study employed a bidirectional two-sample Mendelian Randomization (MR) approach to investigate the causal relationship between T1DM and the genetic susceptibility to AD and PD.

METHODS

We utilized large-scale cohorts derived from publicly available genome-wide association study datasets involving European populations to perform MR analyses. The primary analytical method employed was the inverse-variance weighted (IVW) approach. Furthermore, sensitivity analyses, including assessments of heterogeneity and horizontal pleiotropy, were carried out using Cochran's Q, MR-Egger intercept, and MR-PRESSO tests to enhance the robustness of our conclusions.

RESULTS

Using the IVW-based method, the MR analysis indicated no significant association between genetically determined T1DM and AD (OR = 0.984, 95% CI: 0.958-1.011, p = 0.247). Conversely, T1DM appeared to be associated with a reduced risk of genetic susceptibility to PD (IVW: OR = 0.958, 95% CI: 0.928-0.989, p = 0.001). In the reverse direction, no evidence of reverse causality was observed between AD (OR = 1.010, 95% CI: 0.911-1.116, p = 0.881) or PD (OR = 1.164, 95% CI: 0.686-2.025, p = 0.5202) and T1DM. Additionally, our analysis found no indications of the results being influenced by horizontal pleiotropy.

CONCLUSION

This MR study reveals that T1DM is associated with a reduced genetic susceptibility to PD, whereas no significant genetic susceptibility is observed between T1DM and AD. These findings suggest that T1DM may have a distinct role in the development of neurodegenerative diseases compared to T2D. Further investigations are warranted to elucidate the underlying mechanisms and provide a more comprehensive understanding of this relationship.

The causal effect of educational attainment on stress urinary incontinence: a two-sample mendelian randomization study

BACKGROUND

Stress urinary incontinence (SUI) is characterized by involuntary urine leakage in response to increased abdominal pressure, such as coughing, laughing, or sneezing. It significantly affects women's quality of life and imposes a substantial disease burden. While pregnancy and childbirth have been previously identified as risk factors for SUI, educational attainment may also play a role. Therefore, this paper investigates the causal relationship between educational attainment and SUI using two-sample Mendelian randomization (TSMR) analysis, years of schooling (YOS), and college or university degree (CUD) as proxies.

METHODS

Summary statistics of YOS, CUD, and SUI were obtained from genome-wide association studies (GWAS), and TSMR analysis was applied to explore potential causal relationships between them. Causal effects were mainly estimated using the standard inverse variance weighting (IVW) method, and complementary and sensitivity analyses were also performed using multiple methods.

RESULTS

The results indicate that both YOS (OR = 0.994, 95% CI: 0.992-0.996; P = 7.764E-10) and CUD (OR = 0.987, 95% CI: 0.983-0.991; P = 1.217E-09) may have a negative causal effect on SUI.

CONCLUSIONS

Improving educational attainment may go some way towards reducing the risk of SUI. Therefore, it is important to increase efforts to improve the imbalance in educational development and safeguard women's health.