Association of serotonin transporter gene polymorphism with efficacy of the antidepressant drugs sertraline and mirtazapine in newly diagnosed patients with major depressive disorders

• Published in: Human psychopharmacology 2022-07, Vol.37 (4), p.e2833-n/a
• Main Authors: Gulfishan, Syed, Halder, Sumita, Kar, Rajarshi, Srivastava, Shruti, Gupta, Rachna
• Format: Article
• Language: English
• Subjects: Antidepressants; BDI score; Clinical significance; Gene polymorphism; Genotype & phenotype; Genotyping; MDD (major depressive disorder); Mental depression; Mental disorders; Patients; Polymorphism; Serotonin transporter; SERT gene polymorphism; Sertraline; Statistical analysis
• ISSN: 0885-6222; 1099-1077
• DOI: 10.1002/hup.2833

Objective We examined the association of serotonin receptor transporter gene polymorphism in patients with MDD with the clinical efficacy of mirtazapine (MZ) and sertraline (ST). Method Newly diagnosed, treatment naïve, 80 MDD patients (aged 18–45) diagnosed using DSM‐5 criteria and with Beck's depression inventory score (BDI) score ≥21 were included and randomly divided into two groups of 40 participants and were administered MZ 15–45 mg/day or ST 25–200 mg/day respectively. Patients were followed up for 6 weeks for evaluation of BDI scores. Genotypic evaluation was done and three allele variants were identified based on the polymerase chain reaction fragment sizes: short (S; 486 bp), long (L; 529 bp), or extralong (XL; 612 or 654 bp) and classified into five genotypes: S/S,S/L, L/L, S/XL, and L/XL. Result We found that 32.5% patients belonged to the S/S genotype, suggesting that individuals with the SS genotype are at higher risk of developing MDD. No statistically significant association was seen with ST or MZ groups on the basis of genotypes. Clinically significant improvement was observed with a more than 50% reduction in BDI scores at 6 weeks of treatment with both drugs. Conclusion Identification of risk population can be carried out by genotype testing. Prior genotyping in MDD patients might help to predict a better clinical outcome with antidepressants.