Metabolic effect of cyp2c19 and cyp2d6 on antidepressant response: a meta-analysis of 13 depression pharmacogenetic studies

Pharmacogenetics has explored the influence of genetic factors on antidepressant efficacy. Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms in these genes predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variation on antidepressant response. In this study, 5843 patients diagnosed with major depressive disorder were collated from 13 clinical studies with prospective measures of depression symptoms during treatment. Participants had European (91%) or East Asian (9%) ancestry. Two measures of antidepressant response from baseline scores were used: a bivariate phenotype of remission, and a continuous measure of percentage improvement. For CYP2C19 and CYP2D6, imputed genotypes were used to translate genetic polymorphisms to (1) four metabolic phenotypes (poor, intermediate, normal, and ultrarapid metabolizers) and (2) a continuous activity score. We tested the association between CYP2C19 and CYP2D6 metabolic activity and treatment response in all samples and stratified the association to antidepressants primarily metabolised by CYP2C19 and CYP2D6. Random effect meta-analysis was applied across studies with effect size pooled and inverse-variance weighted, followed by the subgroup meta-analysis to test the effect difference between European and East Asian ancestry. Seven star (*) alleles in CYP2C19 and 16 alleles in CYP2D6 were identified from the imputed genotypes and were classified as having no, decreased, normal and increased function. Four metabolizer groups (poor, intermediate, normal, ultrarapid) for CYP2C19 and three metabolizer groups (poor, intermediate, and normal) for CYP2D6 were translated from star alleles. CYP2D6 metabolizer status was incomplete as the structural variants (such as *5) cannot be identified. A higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033), but did not meet correction for multiple testing. No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19 and CYP2D6, no association was found between metabolic phenotypes and antidepressant response. Activity scores of CYP2C19 and CYP2D6 were not associated with either remission or percentage improvement. Comparing the European and East Asian studies, metabolic phenotypes showed substantial differences in frequency, but no difference in effect on antidepressant response. Our study showed metabolic phenotypes of CYP2C19 and CYP2D6 imputed from genetic variation in 5843 individuals were not associated with antidepressant efficacy. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Information including side effects, antidepressant dose, as well as studies from different ancestries could more fully capture the influence of metabolic phenotypes and increase the power of effect assessment. Other genetic measures such as polygenic scores for antidepressant response are being tested in all samples and stratified by antidepressant class. This unique genetic and clinical resource should yield further evidence to optimise antidepressant prescribing.