Background: Treatment-resistant depression (TRD) affects up to 30–40% of patients with major depressive disorder and remains a major therapeutic challenge. Genetic and epigenetic factors are increasingly recognized as key contributors to both vulnerability and treatment response. Methods: We conducted a narrative review of studies published between 2021 and 2025, focusing exclusively on DNA- and RNA-based biomarkers of TRD. Twelve studies met the inclusion criteria, covering candidate gene analyses, genome-wide association studies (GWAS), neuroimaging–genetic approaches, and microRNA profiling. Results: Genetic investigations consistently implicate neuroplasticity-related genes (BDNF, NTRK2, PTEN, SYN1, MAPK1, and GSK3B) in the risk of TRD and its relapse. Variants in glutamatergic receptor genes (GRIN2A, GRIN2B, GRIA2, GRIA3) were predicted to result in a rapid and sustained response to ketamine. Genomic approaches further demonstrated that composite genetic panels outperform single-variant predictors. In parallel, microRNAs such as miR-1202, miR-16, miR-135, miR-124, miR-223, and miR-146a emerged as dynamic biomarkers of treatment response, particularly in cohorts treated with ketamine or electroconvulsive therapy. Conclusions: DNA- and RNA-based biomarkers provide promising avenues for improving the understanding and management of TRD. Their integration into clinical frameworks could support patient stratification, individualized treatment selection, and real-time monitoring of therapeutic efficacy. Future research should prioritize replication, methodological harmonization, and longitudinal validation to facilitate the translation of findings into precision psychiatry.

Introduction: Clance Impostor Phenomenon Scale (CIPS) is the most common and psychometrically sound instrument used to measure the impostor phenomenon. The aim of this study was to translate and make a cultural adaptation of the CIPS from English into Croatian. Materials and Methods: The translation process included two independent forward translations, combination of the forward translations into one single translation, back-translation, back-translation review, pre-piloting and drafting of the final translation after several revisions and minor adjustments by a professional reviewer. Results: We noticed no semantic differences when comparing the original and the back-translated versions of the CIPS. Thus, the final translation was only slightly changed in comparison with the first version. Conclusions: The version of the CIPS which was translated and culturally adapted into Croatian represents a reliable translation ready to be used in Croatia and Bosnia and Herzegovina.

Background: Treatment-resistant depression (TRD) affects up to 30–40% of patients with major depressive disorder and remains a major therapeutic challenge. Genetic and epigenetic factors are increasingly recognized as key contributors to both vulnerability and treatment response. Methods: We conducted a narrative review of studies published between 2021 and 2025, focusing exclusively on DNA- and RNA-based biomarkers of TRD. Thirteen studies met the inclusion criteria, covering candidate gene analyses, genome-wide association studies (GWAS), neuroimaging–genetic approaches, and microRNA profiling. Results: Genetic investigations consistently implicate neuroplasticity-related genes (BDNF, NTRK2, PTEN, SYN1, MAPK1, and GSK3B) in the risk of TRD and its relapse. Variants in glutamatergic receptor genes (GRIN2A, GRIN2B, GRIA2, GRIA3) were predicted to result in a rapid and sustained response to ketamine. Genomic approaches further demonstrated that composite genetic panels outperform single-variant predictors. In parallel, microRNAs such as miR-1202, miR-16, miR-135, miR-124, miR-223, and miR-146a emerged as dynamic biomarkers of treatment response, particularly in cohorts treated with ketamine or electroconvulsive therapy. Conclusions: DNA- and RNA-based biomarkers provide promising avenues for improving the understanding and management of TRD. Their integration into clinical frameworks could support patient stratification, individualized treatment selection, and real-time monitoring of therapeutic efficacy. Future research should prioritize replication, methodological harmonization, and longitudinal validation to facilitate the translation of findings into precision psychiatry.