Five Major Psychiatric Disorders and Alzheimer’s Disease: A Bidirectional Mendelian Randomization Study

Abstract

Background: Extensive studies put forward the association between Alzheimer’s disease (AD) and psychiatric disorders; however, it remains unclear whether these associations are causal. Objective: We aimed to assess the potential causal relationship between major psychiatric disorders and AD. Methods: A bidirectional two-sample Mendelian randomization (MR) was applied to evaluate potential causality between five psychiatric disorders and AD by selecting the single-nucleotide polymorphisms from the genome-wide association studies as instrumental variables. Inverse-variance weighted (IVW) method was used as the main analyzing approach to estimate possible causal effects, alternative methods including MR-Egger, the MR pleiotropy residual sum and outlier, and leave-one-out analysis method were implemented as sensitivity analyzing approaches to ensure the robustness of results. Results: All forward and reverse MR analyses consistently suggested absent causal relations between psychiatric disorders and AD risk [forward IVW: ORADHD, 1.030, 95% CI, 0.908–1.168, p = 0.674; ORanxiety disorders, 0.904, 95% CI, 0.722–1.131, p = 0.377; ORASD, 0.973, 95% CI, 0.746–1.272, p = 0.846; ORBIP, 1.033, 95% CI, 0.925–1.153, p = 0.564; and ORschizophrenia, 1.039, 95% CI, 0.986–1.095, p = 0.156; reverse IVW: ORADHD, 0.993, 95% CI, 0.954–1.034, p = 0.746; ORanxiety disorders, 1.000, 95% CI, 0.999–1.000, p = 0.898; ORASD, 1.001, 95% CI, 0.962–1.042, p = 0.949; ORBIP, 0.997, 95% CI, 0.966–1.028, p = 0.831; and ORschizophrenia, 1.013, 95% CI, 0.978–1.051, p = 0.466]. Conclusion: There is no significant evidence supporting the causal association between the five major psychiatric disorders and AD.

Psychiatric disorders and Type 2 diabetes mellitus: A bidirectional Mendelian randomization

“…As mentioned above, the first assumption of MR is that IVs need to be strongly correlated with exposure. Therefore, we chose SNPs that reached the generic‐wide significant threshold () as the preliminary result 23 . Then, we excluded SNPs in linkage disequilibrium using the PLINK algorithm ().…”

“…Therefore, we chose SNPs that reached the generic-wide significant threshold (p < 5 × 10 −8 ) as the preliminary result. 23 Then, we excluded SNPs in linkage disequilibrium using the PLINK algorithm (r 2 threshold < 5 × 10 −8 , window size = 5000kb ). Meanwhile, we calculated the statistical value of the F statistic of the IVs.…”

Causal relationships between susceptibility and severity of COVID-19 and neuromyelitis optica spectrum disorder (NMOSD) in European population: a bidirectional Mendelian randomized study

“…Due to the limited sample size of NMOSD, we established a P-value of 5 × 10 –6 for instrumental variable selection in relation to exposure IVs. Afterwards, we removed SNPs that exhibited linkage disequilibrium (r 2 < 0.001 within a 5000kb range) and retrieved the remaining SNPs from the outcome datasets ( 31 ). Additionally, we cross-referenced the Phenoscanner database ( http://www.phenoscanner.medschl.cam.ac.uk/ ) to identify SNPs linked to the exposure that may be associated with confounding variables or outcomes (p < 5 × 10 –8 ).…”

The associations between plasma soluble Trem1 and neurological diseases: a Mendelian randomization study

“…In addition, the threshold was set at P < 5 × 10 –8 in the inverse analysis (Additional file 1 : Tables S5–S9). Next, we excluded SNPs that were in linkage disequilibrium ( r 2 threshold < 0.001 within a 10-Mb window), and we extracted the retained SNPs from the outcome datasets [ 29 ]. For the SNPs that were not available in the outcome GWAS dataset, proxy SNPs in LD ( r 2 > 0.8) were used to replace them [ 30 ].…”