Genetic influences on antidepressant side effects: a CYP2C19 gene variation and polygenic risk study in the Estonian Biobank

Antidepressant side effects are prevalent, leading to significant treatment discontinuity among patients. A deeper understanding of the underlying mechanisms could help identify individuals at risk of side effects and improve treatment outcomes.We aim to investigate the role of genetic variation in CYP2C19 and polygenic scores (PGS) for psychiatric and side effect-related phenotypes in experiencing antidepressant side effects.We pooled Estonian Biobank data from the Mental Health online Survey (N = 86,244), the Adverse Drug Events Questionnaire (N = 49,366) and from unstructured electronic health records using natural language processing (N = 206,066) covering 25 common side effects. The results were meta-analysed with previously published results from the Australian Genetics of Depression Study. Among 13,729 antidepressant users, 52.0% reported side effects. In a subgroup of 9,563 individuals taking antidepressants metabolised by CYP2C19, poor metabolisers had 49% higher odds of reporting a side effect (OR = 1.49, 95%CI = 1.09-2.04), while ultrarapid metabolisers had 17% lower odds (OR = 0.83, 95%CI = 0.70-0.99) compared to normal metabolisers. PGSs for schizophrenia and depression showed the most associations with overall and specific side effects. PGSs for higher body mass index (BMI), anxiety, and systolic blood pressure were associated with respective side effects among any antidepressant and selective serotonin reuptake inhibitor (SSRI) users. Meta-analysis confirmed robust evidence linking a higher BMI PGS and weight gain across nine antidepressants and moderate evidence linking PGS for headache with headache from sertraline. Our findings underscore the role of genetic factors in experiencing antidepressant side effects and have potential implications for personalised medicine approaches to improve antidepressant treatment outcomes.

Authors

Institutions

Publication Details

Journal
European Journal of Human Genetics
Published
2025-06-27
DOI
https://doi.org/10.1038/s41431-025-01894-x
Citations
7
Primary Topic
Treatment of Major Depression
Type
article
Field-Weighted Citation Impact
9.76

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic influences on antidepressant side effects: a CYP2C19 gene variation and polygenic risk study in the Estonian Biobank

Kadri Kõiv, Kelli Lehto, Kairit Sirts, Lili Milani et al.
7 citations
European Journal of Human Genetics
Treatment of Major Depression
9.76
article

Genetic influences on antidepressant side effects: a CYP2C19 gene variation and polygenic risk study in the Estonian Biobank

Kadri Kõiv, Kelli Lehto, Kairit Sirts, Lili Milani, Hanna Maria Kariis, Dage Särg, Kristi Krebs, Maris Alver, Maarja Jõeloo
article en
7 citations

Abstract

Antidepressant side effects are prevalent, leading to significant treatment discontinuity among patients. A deeper understanding of the underlying mechanisms could help identify individuals at risk of side effects and improve treatment outcomes.We aim to investigate the role of genetic variation in CYP2C19 and polygenic scores (PGS) for psychiatric and side effect-related phenotypes in experiencing antidepressant side effects.We pooled Estonian Biobank data from the Mental Health online Survey (N = 86,244), the Adverse Drug Events Questionnaire (N = 49,366) and from unstructured electronic health records using natural language processing (N = 206,066) covering 25 common side effects. The results were meta-analysed with previously published results from the Australian Genetics of Depression Study. Among 13,729 antidepressant users, 52.0% reported side effects. In a subgroup of 9,563 individuals taking antidepressants metabolised by CYP2C19, poor metabolisers had 49% higher odds of reporting a side effect (OR = 1.49, 95%CI = 1.09-2.04), while ultrarapid metabolisers had 17% lower odds (OR = 0.83, 95%CI = 0.70-0.99) compared to normal metabolisers. PGSs for schizophrenia and depression showed the most associations with overall and specific side effects. PGSs for higher body mass index (BMI), anxiety, and systolic blood pressure were associated with respective side effects among any antidepressant and selective serotonin reuptake inhibitor (SSRI) users. Meta-analysis confirmed robust evidence linking a higher BMI PGS and weight gain across nine antidepressants and moderate evidence linking PGS for headache with headache from sertraline. Our findings underscore the role of genetic factors in experiencing antidepressant side effects and have potential implications for personalised medicine approaches to improve antidepressant treatment outcomes.

European Journal of Human GeneticsVol. 33(10)
University of Tartu (EE)
Tartu Ülikool
Good health and well-being
Openalex Percentile: Top 2%
Treatment of Major Depression
9.76
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.