{"title":"预测抗抑郁治疗反应的生物标志物","authors":"Bharathi S. Gadad, M. Jha, M. Trivedi","doi":"10.1093/med/9780190929565.003.0005","DOIUrl":null,"url":null,"abstract":"In clinical practice, patients do not always experience symptomatic remission or treatment response, even after trying various types of antidepressant medications. To improve outcomes and reduce attrition and nonadherence, there is a great need for personalized treatment of major depression. Hence, recent research efforts have focused on the identification of biological markers (or biomarkers) that can predict whether an individual patient will respond to the commonly used antidepressants. In this chapter, we review the biomarkers associated with antidepressant treatment response with particular attention to genetic, proteomic, metabolomic, transcriptomic, epigenetic biological, and biochemical markers. Although the “omics” approach holds great promise for the future, challenges and roadblocks for future research will need to be addressed.","PeriodicalId":11179,"journal":{"name":"Depression","volume":"54 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Biomarkers Predicting Antidepressant Treatment Response\",\"authors\":\"Bharathi S. Gadad, M. Jha, M. Trivedi\",\"doi\":\"10.1093/med/9780190929565.003.0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In clinical practice, patients do not always experience symptomatic remission or treatment response, even after trying various types of antidepressant medications. To improve outcomes and reduce attrition and nonadherence, there is a great need for personalized treatment of major depression. Hence, recent research efforts have focused on the identification of biological markers (or biomarkers) that can predict whether an individual patient will respond to the commonly used antidepressants. In this chapter, we review the biomarkers associated with antidepressant treatment response with particular attention to genetic, proteomic, metabolomic, transcriptomic, epigenetic biological, and biochemical markers. Although the “omics” approach holds great promise for the future, challenges and roadblocks for future research will need to be addressed.\",\"PeriodicalId\":11179,\"journal\":{\"name\":\"Depression\",\"volume\":\"54 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Depression\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/med/9780190929565.003.0005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Depression","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/med/9780190929565.003.0005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In clinical practice, patients do not always experience symptomatic remission or treatment response, even after trying various types of antidepressant medications. To improve outcomes and reduce attrition and nonadherence, there is a great need for personalized treatment of major depression. Hence, recent research efforts have focused on the identification of biological markers (or biomarkers) that can predict whether an individual patient will respond to the commonly used antidepressants. In this chapter, we review the biomarkers associated with antidepressant treatment response with particular attention to genetic, proteomic, metabolomic, transcriptomic, epigenetic biological, and biochemical markers. Although the “omics” approach holds great promise for the future, challenges and roadblocks for future research will need to be addressed.