Brain-Derived Neurotrophic Factor (BDNF) is required for neuron growth and maintenance. Single nucleotide polymorphisms (SNP) are reported in BDNF gene, which reduces proteins activity, Val66Met polymorphism is very well studied and reported as a risk factor for psychiatric diseases. Numerous case-control studies have evaluated the role BDNF Val 66Met (dbSNP: rs6265;196G>A) polymorphism in OCD susceptibility and provided ambiguous findings, hence present meta-analysis was designed to get an exact association between BDNF Val66Met polymorphism and OCD risk. A total of 14 case - control articles were identified through PubMed, Google Scholar, Science Direct and Springer link databases search, up to July 11, 2024. Odds ratios (ORs) with 95% con¬fidence intervals (CIs) were used as association measure. All statistical analyses were done by MetaDiSc (version 1.4).

Fourteen case-control studies involving 2,765 OCD cases and 5,585 controls were included in present meta-analysis. The results showed that the BDNF Val66Met polymorphism was not associated with OCD risk (allele contrast odds ratio ORAvsG = 0.96, 95% CI= 0.82-1.12, p= 0.000; homozygote ORAAvsGG = = 0.79, 95%CI= 0.59-1.06, p= 0.0058; dominant model ORAA+GAvsGG = 0.96, 95%CI= 0.86-1. 06, p= 0.17). In conclusion, the BDNF Val66Met polymorphism was not related to increased OCD susceptibility.

Mental disorders have emerged as a significant global challenge in the field of public health, necessitating advanced therapeutic strategies. While antipsychotic agents remain the cornerstone of treatment strategy, conventional population-based drug treatment frequently fails to account for substantial inter-individual variability in pharmacokinetic (PK) and pharmacodynamic (PD) parameters. The emergence of precision medicine frameworks has catalyzed the development of therapeutic drug monitoring (TDM)-guided precision pharmacotherapeutic strategies, which are increasingly recognized as essential tools for optimizing treatment effects. This article synthesizes contemporary research advancements, with a focused analysis of the evolving role of TDM in personalizing antipsychotic regimens. Through critical evaluation of drug-effect relationships, this work elucidates evidence-based strategies to address current limitations in antipsychotic medication management, aiming to inform optimized clinical decision-making for heterogeneous patient populations.