Applications of Mendelian randomization in psychiatry: a comprehensive systematic review

Psychiatric diseases exact a heavy socioeconomic toll, and it is particularly difficult to identify their risk factors and causative mechanisms due to their multifactorial nature, the limited physiopathological insight, the many confounding factors, and the potential reverse causality between the risk factors and psychiatric diseases. These characteristics make Mendelian randomization (MR) a precious tool for studying these disorders. MR is an analytical method that employs genetic variants linked to a certain risk factor, to assess if an observational association between that risk factor and a health outcome is compatible with a causal relationship. We report the first systematic review of all existing applications and findings of MR in psychiatric disorders, aiming at facilitating the identification of risk factors that may be common to different psychiatric diseases, and paving the way to transdiagnostic MR studies in psychiatry, which are currently lacking. We searched Web of Knowledge, Scopus, and Pubmed databases (until 3 May 2022) for articles on MR in psychiatry. The protocol was preregistered in PROSPERO (CRD42021285647). We included methodological details and results from 50 articles, mainly on schizophrenia, major depression, autism spectrum disorders, and bipolar disorder. While this review shows how MR can offer unique opportunities for unraveling causal links in risk factors and etiological elements of specific psychiatric diseases and transdiagnostically, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.

Introduction the many confounding factors, and to the potential reverse causality between the risk factors and these diseases. These characteristics make mendelian randomization (MR) a precious tool for studying psychiatric diseases. MR is an analytical method that employs genetic variants linked to a certain risk factor, to assess if an observational association between that risk factor and a health outcome is compatible with a causal relationship.

Protocol and registration
Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
The protocol is listed in the PROSPERO register (registration number: CRD42021285647).
Methods, Search strategy and selection criteria 6 Eligibility criteria Specify study characteristics (e.g., PICOS, length of followup) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.
We included original published articles written in English, with no restrictions on publication date.
-Population: psychiatric patients of any age, with any psychiatric diagnosis according to DSM or ICD criteria -Intervention: employment of MR in genetic analysis, applied to identification of risk factors, to neuroimaging correlations or to other settings relating to psychiatry (including studies that focused on how psychiatric diseases might be risk factors for other conditions -Comparisons: presence or absence of genetic traits that are determinants of exposure to a certain risk factor (which could be a psychiatric disorder or other risk factors) -Outcome: the risk for a certain condition (both psychiatric and not). -Study design: all study designs apart from case reports, case series, conference abstracts and presentations, pilot/feasibility studies, reviews, meta-analyses, and systematic reviews.
Articles were excluded if they: a) were case reports, case series, conference abstracts and presentations, pilot/feasibility studies, reviews, meta-analyses, and systematic reviews; b) were written in languages other than English. The identified articles were screened by title and abstract, and the full text of surviving articles were further inspected for eligibility against a priori defined inclusion and exclusion criteria.

Methods
Methods, Search strategy and selection criteria, Figure 1 10 Data collection process Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
Data extraction was performed by independent researchers (LFS, SG). Any discrepancy was discussed until a consensus was reached. Disagreements were resolved by a third reviewer (GR).

Methods, Data extraction 11 Data items
List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
The following variables were extracted from each article: authors and year of publication, sample size, genetic information analyzed, main MR method, main findings, presence of pleiotropy analysis, psychiatric disorder considered as an outcome.
Methods, Data extraction 12

Risk of bias in individual studies
Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
The quality of the selected studies was assessed independently by two reviewers (SG, LG) with the Newcastle-Ottawa Scale (NOS).

Methods, Risk of bias 13 Summary measures
State the principal summary measures (e.g., risk ratio, difference in means).
The main findings of the individual studies were reported in Tables 1-5   Tables 1-5 14

Synthesis of results
Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis.
The main findings of the individual studies were reported in tables 1-5. Data from individual studies could not be combined due to high heterogeneity. Tables 1-5 15

Risk of bias across studies
Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
The risk of bias and concerns regarding applicability were analyzed for each domain of the NOS.

Methods, Data analysis 16 Additional analyses
Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, metaregression), if done, indicating which were pre-specified.

Study selection
Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
All details are depicted in the PRISMA flow-chart (Figure 2), and described in the main text.
Results; Figure 2 18 Study characteristi cs For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.