International Journal of Molecular Medical Science, 2024, Vol.14, No.4, 216-226 http://medscipublisher.com/index.php/ijmms 224 disparities in access to personalized treatments. By fostering collaboration across disciplines, the field of personalized treatment for depression can continue to advance and ultimately improve patient outcomes. 7 Concluding Remarks The integration of genomic studies into the treatment of depression has shown promising advancements towards personalized medicine. Pharmacogenomic research has identified several single nucleotide polymorphisms (SNPs) that influence the efficacy of antidepressants and mood stabilizers, such as those in genes like COMT, HTR2A, and BDNF. Genome-wide association studies (GWAS) have further highlighted gene sets involved in cyclic adenosine monophosphate mediated signal and chromatin silencing as potential biomarkers for treatment-resistant depression (TRD). Additionally, deep learning models have been developed to predict antidepressant response using genetic and clinical biomarkers, demonstrating significant potential in distinguishing responders from non-responders. However, the translation of these findings into clinical practice remains complex due to the multifaceted nature of gene-environment interactions. The findings from genomic studies have several implications for clinical practice. The identification of genetic markers associated with antidepressant response can guide clinicians in selecting the most effective treatment for individual patients, potentially reducing the trial-and-error approach currently prevalent in depression treatment. Pharmacogenomic testing, as demonstrated in randomized controlled trials, has shown to improve response and remission rates in patients with major depressive disorder (MDD) by informing medication selection based on genetic profiles. Moreover, the development of multivariable diagnostic algorithms that incorporate genomic data alongside other predictors could further enhance the precision of personalized treatment plans. However, the clinical utility of these approaches requires further validation in diverse populations to ensure their efficacy across different ethnic and genetic backgrounds. The journey towards personalized treatment of depression through genomic studies is both promising and challenging. While significant strides have been made in identifying genetic markers and developing predictive models, the complexity of depression as a disorder necessitates a multifaceted approach that integrates genomics with other omic data and clinical characteristics. Future research should focus on large-scale, diverse population studies to validate and refine these genomic tools, ensuring their broad applicability and effectiveness. The ultimate goal is to achieve a more predictive, preventive, and personalized approach to psychiatry, improving outcomes for patients with depression. Acknowledgments The authors extend sincere thanks to two anonymous peer reviewers for their feedback on the manuscript. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Alladi C., Étain B., Bellivier F., and Marie-Claire C., 2018, DNA methylation as a biomarker of treatment response variability in serious mental illnesses: a systematic review focused on bipolar disorder, schizophrenia, and major depressive disorder, International Journal of Molecular Sciences, 19(10): 3026. https://doi.org/10.3390/ijms19103026 PMid:30287754 PMCid:PMC6213157 Amare A., Schubert K., and Baune B., 2017, Pharmacogenomics in the treatment of mood disorders: strategies and opportunities for personalized psychiatry, EPMA Journal, 8: 211-227. https://doi.org/10.1007/s13167-017-0112-8 PMid:29021832 PMCid:PMC5607053 Belmaker R., and Agam G., 2008, Major depressive disorder, The New England Journal of Medicine, 358(1): 55-68. https://doi.org/10.1056/NEJMra073096 PMid:18172175 Brown L., Stanton J., Bharthi K., Maruf A., Müller D., and Bousman C., 2022, Pharmacogenomic testing and depressive symptom remission: a systematic review and meta‐analysis of prospective, controlled clinical trials, Clinical Pharmacology and Therapeutics, 112: 1303-1317. https://doi.org/10.1002/cpt.2748 PMid:36111494 PMCid:PMC9827897
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