首页|Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia:randomized trials and multiomics analysis

Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia:randomized trials and multiomics analysis

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Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers.Previous studies have indicated the association between treatment response and genetic and epigenetic factors,but no effective biomarkers have been identified.Hence,further research is imperative to enhance precision medicine in SCZ treatment.Methods:Participants with SCZ were recruited from two randomized trials.The discovery cohort was recruited from the CAPOC trial(n=2307)involved 6 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,Quetiapine,Aripiprazole,Ziprasidone,and Haloperidol/Perphenazine(subsequently equally assigned to one or the other)groups.The external validation cohort was recruited from the CAPEC trial(n=1379),which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,and Aripiprazole groups.Additionally,healthy controls(n=275)from the local community were utilized as a genetic/epigenetic reference.The genetic and epigenetic(DNA methylation)risks of SCZ were assessed using the polygenic risk score(PRS)and polymethylation score,respectively.The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis,methylation quantitative trait loci,colocalization,and promoteranchored chromatin interaction.Machine learning was used to develop a prediction model for treatment response,which was evaluated for accuracy and clinical benefit using the area under curve(AUC)for classification,R2 for regression,and decision curve analysis.Results:Six risk genes for SCZ(LINC01795,DDHD2,SBNO1,KCNG2,SEMA7A,and RUFY1)involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response.The developed and externally validated prediction model,which incorporated clinical information,PRS,genetic risk score(GRS),and proxy methylation level(proxyDNAm),demonstrated positive benefits for a wide range of patients receiving different APDs,regardless of sex[discovery cohort:AUC=0.874(95%CI 0.867-0.881),R2=0.478;external validation cohort:AUC=0.851(95%CI 0.841-0.861),R2=0.507].Conclusions:This study presents a promising precision medicine approach to evaluate treatment response,which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ.

SchizophreniaAntipsychotic drugTreatment responsePrediction modelGeneticsEpigenetics

Liang-Kun Guo、Yi Su、Yu-Ya-Nan Zhang、Hao Yu、Zhe Lu、Wen-Qiang Li、Yong-Feng Yang、Xiao Xiao、Hao Yan、Tian-Lan Lu、Jun Li、Yun-Dan Liao、Zhe-Wei Kang、Li-Fang Wang、Yue Li、Ming Li、Bing Liu、Hai-Liang Huang、Lu-Xian Lv、Yin Yao、Yun-Long Tan、Gerome Breen、Ian Everall、Hong-Xing Wang、Zhuo Huang、Dai Zhang、Wei-Hua Yue

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Institute of Mental Health,Peking University Sixth Hospital,Beijing 100191,China

National Clinical Research Center for Mental Disorders,Peking University Sixth Hospital,Beijing 100191,China

NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder(2018RU006),Chinese Academy of Medical Sciences,Beijing 100191,China

Peking University Huilongguan Clinical Medical School,Beijing Huilongguan Hospital,Beijing 100096,China

Department of Psychiatry,Jining Medical University,Jining 272067,Shandong,China

Henan Key Lab of Biological Psychiatry,the Second Affiliated Hospital of Xinxiang Medical University,Xinxiang 435001,Henan,China

Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province,Kunming Institute of Zoology,Chinese Academy of Sciences,Kunming 650223,China

Institute of Psychiatry,Psychology and Neuroscience,King's College London,London WC2R 2LS,UK

State Key Laboratory of Cognitive Neuroscience and Learning,Beijing Normal University,Beijing 100875,China

Analytic and Translational Genetics Unit,Massachusetts General Hospital,Boston,MA 02114,USA

Stanley Center for Psychiatric Research,the Broad Institute of MIT and Harvard,Cambridge,MA 02141,USA

Department of Medicine,Harvard Medical School,Boston,MA 02115,USA

Department of Biostatistics and Computational Biology,School of Life Sciences,Fudan University,Shanghai 200438,China

Department of Neurology,Xuanwu Hospital,Capital Medical University,Beijing 100053,China

State Key Laboratory of Natural and Biomimetic Drugs,Key Laboratory for Neuroscience for Ministry of Education,School of Pharmaceutical Sciences,Peking University Health Science Center,Beijing 100191,China

PKU-IDG/McGovern Institute for Brain Research,Peking University,Beijing 100871,China

Chinese Institute for Brain Research,Beijing 102206,China

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National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaChinese Academy of Medical Sciences Innovation Fund for Medical SciencesChinese Academy of Medical Sciences Innovation Fund for Medical SciencesProgram of Chinese Institute for Brain Research BeijingKing's College London-Peking University Health Science Center Joint Institute for Medical ResearchKing's College London-Peking University Health Science Center Joint Institute for Medical ResearchNational Key R&D Program of ChinaNational Key R&D Program of China

8182500982071505819013582021-I2M-C&T-B-0992019-I2M-5-0062020-NKX-XM-12BMU2020KCL001BMU2019LCKXJ0122021YFF12011032016YFC1307000

2024

10.1186/s40779-023-00459-7

军事医学研究(英文)

军事医学研究(英文)

CSTPCD
ISSN：2095-7467
年,卷(期)：2024.11(1)
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