Large-Scale Meta-Analysis of TNF-α rs1800629 Polymorphism in Schizophrenia: Evidence from 7,624 Cases and 8,933 Controls

Objective: Schizophrenia is a multifaceted psychiatric disorder that affects about 1% of the world’s population and arises from a combination of genetic, environmental, and neurodevelopmental influences. Recent studies highlight the role of immune system disturbances and neuroinflammation in its development, with tumor necrosis factor-alpha (TNF-α) identified as a pivotal cytokine. This meta-analysis aims to clarify the relationship between the TNF-α rs1800629 genetic variant and the risk of schizophrenia by synthesizing data from published research.
Methods: Two independent reviewers systematically searched PubMed, Web of Science, Embase, Cochrane Library, and Chinese National Knowledge Infrastructure for studies published up to January 19, 2024. Odds ratios and 95% confidence intervals were computed using a fixedeffects model, taking into account the absence of significant heterogeneity.
Results: A total of 33 case-control studies were included, encompassing 7,624 individuals with schizophrenia and 8,933 healthy controls from diverse backgrounds (21 studies on Asian populations, 11 on Caucasian, and one on a mixed group) conducted between 2001 and 2020. The pooled analysis did not reveal a significant link between the TNF-α rs1800629 polymorphism and susceptibility to schizophrenia under any genetic model. Further subgroup analyses by ethnicity (Asian, Caucasian), country (China, Poland), genotyping technique, and publication year also yielded no notable associations.
Conclusions: This comprehensive meta-analysis offers strong evidence that the TNF-α rs1800629 variant is not significantly associated with schizophrenia risk, either globally or within specific ethnic groups. These findings indicate that this polymorphism likely does not play a major role in schizophrenia susceptibility, underscoring the importance of future investigations into other TNF-α variants, gene-gene interactions, or alternative inflammatory mechanisms.