Abstract
Introduction Growing evidence links psychiatric disorders to immune system dysfunction, atypical brain development, and psychosocial traits such as intelligence and childhood maltreatment. However, the causal relationships between psychiatric disorders and these potential risk factors remain controversial.
Objectives
To better elucidate the intertwined pathways underlying five major psychiatric disorders and potential risk factors by employing genetic instruments to evaluate possible causal relationships.
Methods
We conducted bidirectional two-sample Mendelian randomization (MR) analyses by leveraging summary statistics from recent GWASs with large sample sizes. Causal relationships were estimated between five major psychiatric disorders (ADHD, ASD, BD, MDD, and SCZ) and various factors, including cytokines, longitudinal brain changes, childhood maltreatment, antisocial behavior, educational attainment, and intelligence, which were used as both exposures and outcomes (average N > 310k). LHC-MR, a novel MR method which controls for correlated horizontal pleiotropy and simultaneously estimate bi-directional causal effects for trait pairs, was utilized to discover potential causalities. MRCI, another advanced MR method for estimating reciprocal causal effects, and standard MR methods were employed to replicate the identified significant causalities. Moreover, potential mediating pathways were investigated.
Results
Causal relationships of 300 trait pairs were examined by LHC-MR, 41 of which achieved significance after multiple testing (p < 1.67e-4). After replication, LHC-MR, MRCI, and standard MR methods agreed on four positive causal effects, including attention-deficit/hyperactivity disorder (ADHD) on the chemokine RANTES and RANTES on major depression (MDD). Mediation analysis further supported that RANTES contributed to the association between ADHD and MDD. Additionally, both schizophrenia and MDD positively increased the risk of childhood maltreatment, perhaps due to premorbid traits which trigger bullying or poor parenting associated with genetic predisposition to these disorders.
Conclusions
The current study contributes to a better understanding of the intertwined causal network between psychiatric disorders and various risk factors, which may help develop public health prevention and intervention.
Competing Interest Statement
Dr. Sham reported being awarded the Suen Chi-Sun Professorship in Clinical Science at the University of Hong Kong. No other disclosures were reported.
Funding Statement
This study did not receive any funding
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
All GWAS summary statistical data in this study are publicly available (listed in the Supplementary Table 1 & 2). All software packages used are publicly available.
I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.
Yes
Data availability
All GWAS summary statistical data in this study are publicly available (listed in the Supplementary Table 1 & 2). All software packages used are publicly available.
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