{"title":"微生物组研究的一个隐藏的干扰因素:在样本收集前几年使用的药物。","authors":"Oliver Aasmets, Nele Taba, Kertu Liis Krigul, Reidar Andreson, Elin Org","doi":"10.1128/msystems.00541-25","DOIUrl":null,"url":null,"abstract":"<p><p>Medication usage is a known contributor to the inter-individual variability of the gut microbiome. However, medications are often used repeatedly and for long periods, a notion yet unaccounted for in microbiome studies. Recently, we and others showed that not only the usage of antibiotics and antidepressants at sampling, but also past consumption, is associated with the gut microbiome. This effect can be \"additive\"-the more a medication is used, the stronger the impact on the microbiome. Here, by utilizing retrospective medication usage data from the electronic health records and the observational Estonian microbiome cohort shotgun metagenomics data set (<i>n</i> = 2,509), we systematically evaluate the long-term effects of antibiotics and human-targeted medications on the gut microbiome. We show that past usage of medications is associated with the gut microbiome. For example, the effects of antibiotics, psycholeptics, antidepressants, proton pump inhibitors, and beta-blockers are detectable several years after use. Furthermore, by analyzing a subcohort (<i>n</i> = 328) with a second microbiome characterization, we show that similar changes in the gut microbiome occur after treatment initiation or discontinuation, possibly indicating causal effects.IMPORTANCEThis is the first study using detailed retrospective medication usage data from electronic health records to systematically assess the long-term effects of medication usage on the gut microbiome. We identified carryover and additive effects on the gut microbiome for a range of antibiotics and non-antibiotic medications, such as benzodiazepine derivatives, antidepressants and glucocorticoids, among others. These findings highlight a collateral effect of diverse drug classes on the gut microbiome, which warrants accounting for long-term medication usage history when assessing disease-microbiome associations.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0054125"},"PeriodicalIF":4.6000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A hidden confounder for microbiome studies: medications used years before sample collection.\",\"authors\":\"Oliver Aasmets, Nele Taba, Kertu Liis Krigul, Reidar Andreson, Elin Org\",\"doi\":\"10.1128/msystems.00541-25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Medication usage is a known contributor to the inter-individual variability of the gut microbiome. However, medications are often used repeatedly and for long periods, a notion yet unaccounted for in microbiome studies. Recently, we and others showed that not only the usage of antibiotics and antidepressants at sampling, but also past consumption, is associated with the gut microbiome. This effect can be \\\"additive\\\"-the more a medication is used, the stronger the impact on the microbiome. Here, by utilizing retrospective medication usage data from the electronic health records and the observational Estonian microbiome cohort shotgun metagenomics data set (<i>n</i> = 2,509), we systematically evaluate the long-term effects of antibiotics and human-targeted medications on the gut microbiome. We show that past usage of medications is associated with the gut microbiome. For example, the effects of antibiotics, psycholeptics, antidepressants, proton pump inhibitors, and beta-blockers are detectable several years after use. Furthermore, by analyzing a subcohort (<i>n</i> = 328) with a second microbiome characterization, we show that similar changes in the gut microbiome occur after treatment initiation or discontinuation, possibly indicating causal effects.IMPORTANCEThis is the first study using detailed retrospective medication usage data from electronic health records to systematically assess the long-term effects of medication usage on the gut microbiome. We identified carryover and additive effects on the gut microbiome for a range of antibiotics and non-antibiotic medications, such as benzodiazepine derivatives, antidepressants and glucocorticoids, among others. These findings highlight a collateral effect of diverse drug classes on the gut microbiome, which warrants accounting for long-term medication usage history when assessing disease-microbiome associations.</p>\",\"PeriodicalId\":18819,\"journal\":{\"name\":\"mSystems\",\"volume\":\" \",\"pages\":\"e0054125\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"mSystems\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1128/msystems.00541-25\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"mSystems","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1128/msystems.00541-25","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
A hidden confounder for microbiome studies: medications used years before sample collection.
Medication usage is a known contributor to the inter-individual variability of the gut microbiome. However, medications are often used repeatedly and for long periods, a notion yet unaccounted for in microbiome studies. Recently, we and others showed that not only the usage of antibiotics and antidepressants at sampling, but also past consumption, is associated with the gut microbiome. This effect can be "additive"-the more a medication is used, the stronger the impact on the microbiome. Here, by utilizing retrospective medication usage data from the electronic health records and the observational Estonian microbiome cohort shotgun metagenomics data set (n = 2,509), we systematically evaluate the long-term effects of antibiotics and human-targeted medications on the gut microbiome. We show that past usage of medications is associated with the gut microbiome. For example, the effects of antibiotics, psycholeptics, antidepressants, proton pump inhibitors, and beta-blockers are detectable several years after use. Furthermore, by analyzing a subcohort (n = 328) with a second microbiome characterization, we show that similar changes in the gut microbiome occur after treatment initiation or discontinuation, possibly indicating causal effects.IMPORTANCEThis is the first study using detailed retrospective medication usage data from electronic health records to systematically assess the long-term effects of medication usage on the gut microbiome. We identified carryover and additive effects on the gut microbiome for a range of antibiotics and non-antibiotic medications, such as benzodiazepine derivatives, antidepressants and glucocorticoids, among others. These findings highlight a collateral effect of diverse drug classes on the gut microbiome, which warrants accounting for long-term medication usage history when assessing disease-microbiome associations.
mSystemsBiochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍:
mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.