Background: Nowadays, psychiatric morbidities are more and more common, which imposes huge social and economic burden on all countries across the world. Mental illnesses are found to be related to genetics. Over the past few years, a large number of risk genes and loci related to psychiatric morbidities have been reported. The brain-derived neurotrophic factor (BDNF) is one of the main candidates in neuropsychiatric genetics. However, different studies have shown inconsistencies regarding effect modification of BDNF polymorphisms on psychiatric morbidities. Therefore, in the present study, we aim to qualitatively and quantitatively summarize the relationship between BDNF single nucleotide polymorphisms (SNPs) and various psychiatric morbidities through a meta-analysis.
Methods: PubMed, Web of Science and Embase will be searched using a specified search strategy to identify relevant studies up to April 2020. The meta-analysis will be performed on (1) allele model, (2) dominant model, (3) recessive model, (4) homozygote, and (5) heterozygote model. Sensitivity analyses will be conducted to explore the impact of individual studies on the overall result by evaluating the odd ratios (ORs) with their corresponding 95% confidence intervals (CIs) before and after removing each of the studies from our meta-analysis. Chi-square test will be used to determine whether the observed allele or genotype frequencies in the controls are consistent with HWE. The statistical heterogeneity will be verified by I statistics. The fixed effects model is needed to estimate the ORs and 95% CIs when there was no heterogeneity between results of included studies (I < 50%); instead, the random effects model should be used when results of included studies showed significant heterogeneity (I > 50%). Publication bias will be evaluated with the use of Begg test and Egger test (P < .05 is considered statistically significant).
Discussion: With this protocol, a methodology is established that explores the effect modification of BDNF polymorphisms on the association with psychiatric morbidities. Findings from this meta-analysis can provide significant insight into the etiology of psychiatric morbidities.
Registration: Open Science Framework (OSF) Preregistration. September 15, 2020. OSF.IO/QS7XT.