Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation
Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I2=0%, subgroup difference p=0.72). 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. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2023 |
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| Enthalten in: |
medRxiv : the preprint server for health sciences - (2023) vom: 11. Dez. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Danyang [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Revised 22.12.2023 published: Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1101/2023.06.26.23291890 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM359268196 |
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| 100 | 1 | |a Li, Danyang |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation |
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| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I2=0%, subgroup difference p=0.72). 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. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes | ||
| 650 | 4 | |a Preprint | |
| 650 | 4 | |a CYP2C19 | |
| 650 | 4 | |a CYP2D6 | |
| 650 | 4 | |a antidepressants | |
| 650 | 4 | |a pharmacogenetics | |
| 700 | 1 | |a Pain, Oliver |e verfasserin |4 aut | |
| 700 | 1 | |a Fabbri, Chiara |e verfasserin |4 aut | |
| 700 | 1 | |a Wong, Win Lee Edwin |e verfasserin |4 aut | |
| 700 | 1 | |a Lo, Chris Wai Hang |e verfasserin |4 aut | |
| 700 | 1 | |a Ripke, Stephan |e verfasserin |4 aut | |
| 700 | 1 | |a Cattaneo, Annamaria |e verfasserin |4 aut | |
| 700 | 1 | |a Souery, Daniel |e verfasserin |4 aut | |
| 700 | 1 | |a Dernovsek, Mojca Z |e verfasserin |4 aut | |
| 700 | 1 | |a Henigsberg, Neven |e verfasserin |4 aut | |
| 700 | 1 | |a Hauser, Joanna |e verfasserin |4 aut | |
| 700 | 1 | |a Lewis, Glyn |e verfasserin |4 aut | |
| 700 | 1 | |a Mors, Ole |e verfasserin |4 aut | |
| 700 | 1 | |a Perroud, Nader |e verfasserin |4 aut | |
| 700 | 1 | |a Rietschel, Marcella |e verfasserin |4 aut | |
| 700 | 1 | |a Uher, Rudolf |e verfasserin |4 aut | |
| 700 | 1 | |a Maier, Wolfgang |e verfasserin |4 aut | |
| 700 | 1 | |a Baune, Bernhard T |e verfasserin |4 aut | |
| 700 | 1 | |a Biernacka, Joanna M |e verfasserin |4 aut | |
| 700 | 1 | |a Bondolfi, Guido |e verfasserin |4 aut | |
| 700 | 1 | |a Domschke, Katharina |e verfasserin |4 aut | |
| 700 | 1 | |a Kato, Masaki |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Yu-Li |e verfasserin |4 aut | |
| 700 | 1 | |a Serretti, Alessandro |e verfasserin |4 aut | |
| 700 | 1 | |a Tsai, Shih-Jen |e verfasserin |4 aut | |
| 700 | 1 | |a Weinshilboum, Richard |e verfasserin |4 aut | |
| 700 | 0 | |a GSRD Consortium |e verfasserin |4 aut | |
| 700 | 0 | |a Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium |e verfasserin |4 aut | |
| 700 | 1 | |a McIntosh, Andrew M |e verfasserin |4 aut | |
| 700 | 1 | |a Lewis, Cathryn M |e verfasserin |4 aut | |
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