Bidirectional Mendelian randomization study of psychiatric disorders and Parkinson’s disease

Abstract

IntroductionAlthough the relationship between psychiatric disorders and Parkinson’s disease (PD) has attracted continuous research attention, the causal linkage between them has not reached a definite conclusion.MethodsTo identify the causal relationship between psychiatric disorders and PD, we used public summary-level data from the most recent and largest genome-wide association studies (GWASs) on psychiatric disorders and PD to conduct a bidirectional two-sample Mendelian randomization (MR). We applied stringent control steps in instrumental variable selection using the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method to rule out pleiotropy. The inverse-variance weighted (IVW) method was used to identify the causal relationship between psychiatric disorders and PD. Multiple MR analysis methods, including MR-Egger, weighted-median, and leave-one-out analyses, were used for sensitivity analysis, followed by heterogeneity tests. Further validation and reverse MR analyses were conducted to strengthen the results of the forward MR analysis.ResultsThe lack of sufficient estimation results could suggest a causal relationship between psychiatric disorders and PD in the forward MR analysis. However, the subsequent reverse MR analysis detected a causal relationship between PD and bipolar disorder (IVW: odds ratios [OR] =1.053, 95% confidence interval [CI] =1.02–1.09, p = 0.001). Further analysis demonstrated a causal relationship between genetically predicted PD and the risk of bipolar disorder subtype. No pleiotropy or heterogeneity was detected in the analyses.DiscussionOur study suggested that while psychiatric disorders and traits might play various roles in the risk of developing PD, PD might also be involved in the risk of developing psychiatric disorders.

Assessing the causal relationship between psychiatric disorders and obstructive sleep apnea: a bidirectional Mendelian randomization

“…Leave-one-out analyses further confirmed that individual SNPs did not influence the causal relationship. For SCZ, despite stringent controls and no outliers detected pre-MR analysis, the MR-PRESSO global test indicated pleiotropy among IVs ( P = 0.037), suggesting unreliability of causation estimates from IVW and MR-Egger due to violation of the InSIDE assumption ( 38 ). However, estimates from the weighted median method were also non-significant (OR: 0.997, 95% CI: 0.964–1.032, P = 0.884).…”

“…Additionally, MR pleiotropy residual sum and outlier (MR-PRESSO) test analysis were conducted to eliminate outlier IVs. A stringent filtering step was adopted, discarding SNPs with a P -value < 1 in the outlier test and repeating this process until no outliers remained ( 38 ). Finally, the Steiger test was applied to each SNP to ascertain if the R 2 of the exposure exceeded that of the outcome, excluding SNPs where the test indicated a ‘FALSE’ direction.…”

Susceptibility and severity of COVID-19 and risk of psychiatric disorders in European populations: a Mendelian randomization study

“…MR-Egger method often yields inaccurate and statistically less significant results, especially when the number of SNPs is small. In addition, the value of the MR-Egger intercept term was far from zero, indicating horizontal pleiotropy ( p < 0.05) ( 32 , 33 ). Therefore, in our MR study, the MR-Egger method was mainly performed to detect pleiotropy.…”