Dataset Information

Influence of eight ABCB1 polymorphisms on antidepressant response in a prospective cohort of treatment-free Russian patients with moderate or severe depression: An explorative psychopharmacological study with naturalistic design.

ABSTRACT:

Background

Many antidepressants are substrates of P-glycoprotein, an efflux transporter in the blood-brain-barrier encoded by the ABCB1 gene. Genetic variations might influence the transport rate of antidepressants and hence their pharmacological effects. This study investigates the influence of eight polymorphisms in the ABCB1 gene on antidepressant treatment response.

Method

152 patients were included from psychiatric departments of the Mental Health Research Institute in Tomsk. The difference in Hamilton-Depression-Rating-Scale (HAMD-17)-scores between baseline and week two, week two and four, and baseline and week four was used to estimate timing of improvement of depression. Associations between the ABCB1 gene-polymorphisms and reduction in HAMD-17 score were assessed using independent t-test and multiple linear regression.

Results

Tricyclic antidepressants were associated with a higher reduction of HAMD-17 score when compared to SSRIs. The SNP rs2235040 A-allele had a significant positive influence on the ΔHAMD-17_(0→2W) score but a significant negative influence on the ΔHAMD-17_(2→4W) score. The rs4148739 G-allele had a significant negative influence on the ΔHAMD-17_(0→2W) score but a significant positive influence on the ΔHAMD-17_(2→4W) score. The SNP rs2235015 T-allele is significant negatively related to the ΔHAMD-17_(2→4W) score.

Conclusion

ABCB1 Genetic variations appear to affect speed but not magnitude of antidepressant drug response.

SUBMITTER: Geers LM

PROVIDER: S-EPMC9285790 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We studied seven genes that reflect events relevant to antidepressant action at four sequential levels: (1) entry into the brain, (2) binding to monoaminergic transporters, and (3) distal effects at the transcription level, resulting in (4) changes in neurotrophin and neuropeptide receptors. Those genes are ATP-binding cassette subfamily B member 1 (ABCB1), the noradrenaline, dopamine, and serotonin transporters (SLC6A2, SLC6A3 and SLC6A4), cyclic AMP-responsive element binding protein 1 (CREB1), corticotropin-releasing hormone receptor 1 (CRHR1) and neurotrophic tyrosine kinase type 2 receptor (NTRK2). Sequence variability for those genes was obtained in exonic and flanking regions. A total of 56 280 000 bp across were sequenced in 536 unrelated Mexican Americans from Los Angeles (264 controls and 272 major depressive disorder (MDD)). We detected in those individuals 419 single nucleotide polymorphisms (SNPs); the nucleotide diversity was 0.00054 + or - 0.0001. Of those, a total of 204 novel SNPs were identified, corresponding to 49% of all previously reported SNPs in those genes: 72 were in untranslated regions, 19 were in coding sequences of which 7 were non-synonymous, 86 were intronic and 27 were in upstream/downstream regions. Several SNPs or haplotypes in ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1 and NTRK2 were associated with MDD, and in ABCB1, SLC6A2 and NTRK2 with antidepressant response. After controlling for age, gender and baseline 21-item Hamilton Depression Rating Scale (HAM-D21) score, as well as correcting for multiple testing, the relative reduction of HAM-D21 score remained significantly associated with two NTRK2-coding SNPs (rs2289657 and rs56142442) and the haplotype CAG at rs2289658 (splice site), rs2289657 and rs2289656. Further studies in larger independent samples will be needed to confirm these associations. Our data indicate that extensive assessment of sequence variability may contribute to increase understanding of disease susceptibility and drug response. Moreover, these results highlight the importance of direct re-sequencing of key candidate genes in ethnic minority groups in order to discover novel genetic variants that cannot be simply inferred from existing databases.