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

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

doi:10.1186/s40779-023-00459-7

Your Location：

Home >

Browse articles >

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

RESEARCH | Updated：2025-12-13

- Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis
- Military Medical Research Vol. 11, Issue 1, Pages: 19-33(2024)
- Affiliations：
  
  1.Institute of Mental Health, Peking University Sixth Hospital, Beijing 100191, China
  2.National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China
  3.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
  4.Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing 100096, China
  5.Department of Psychiatry, Jining Medical University, Jining 272067, Shandong, China
  6.Henan Key Lab of Biological Psychiatry, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 435001, Henan, China
  7.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
  8.Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London WC2R 2LS, UK
  9.State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
  10.Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
  11.Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
  12.Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
  13.Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai 200438, China
  14.Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
  15.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
  16.PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
  17.Chinese Institute for Brain Research, Beijing 102206, China
- Author bio：
  
  * huangz@hsc.pku.edu.cn;
  daizhang@bjmu.edu.cn;
  dryue@bjmu.edu.cn
- Funds：
- DOI：10.1186/s40779-023-00459-7
  CLC：
- Published：2024-02
- Accepted：
Scan QR Code
Cite this article as: Guo LK, Su Y, Zhang YYN, Yu H, Lu Z, Li WQ, et al. Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis. Mil Med Res. 2023;10(1):24.
DOI：

Cite this article as: Guo LK, Su Y, Zhang YYN, Yu H, Lu Z, Li WQ, et al. Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis. Mil Med Res. 2023;10(1):24. DOI： 10.1186/s40779-023-00459-7.

摘要

Abstract

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 (

=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 (

=1379)

which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine

Risperidone

and Aripiprazole groups. Additionally

healthy controls (

=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)

=0.478; external validation cohort: AUC=0.851 (95%CI 0.841–0.861)

=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.

Trial registration

Chinese Clinical Trial Registry (https://www.chictr.org.cn/)

18 Aug 2009 retrospectively registered: CAPOC-ChiCTR-RNC-09000521 (https://www.chictr.org.cn/showproj.aspx?proj=9014)

CAPEC-ChiCTRRNC-09000522 (https://www.chictr.org.cn/showproj.aspx?proj=9013).

关键词

Keywords

references

Marder SR , Cannon TD . Schizophrenia . N Engl J Med . 2019 ; 381 ( 18 ): 1753 – 61 .

Chong HY , Teoh SL , Wu DBC , Kotirum S , Chiou CF , Chaiyakunapruk N . Global economic burden of schizophrenia: a systematic review . Neuropsychiatr Dis Treat . 2016 ; 12 : 357 – 73 .

Haddad PM , Correll CU . The acute efficacy of antipsychotics in schizophrenia: a review of recent meta-analyses . Ther Adv Psychopharmacol . 2018 ; 8 ( 11 ): 303 – 18 .

Lam M , Chen CY , Li Z , Martin AR , Bryois J , Ma X , et al . Comparative genetic architectures of schizophrenia in East Asian and European populations . Nat Genet . 2019 ; 51 ( 12 ): 1670 – 8 .

Chen J , Zang Z , Braun U , Schwarz K , Harneit A , Kremer T , et al . Association of a reproducible epigenetic risk profile for schizophrenia with brain methylation and function . JAMA Psychiat . 2020 ; 77 ( 6 ): 628 – 36 .

Yu H , Yan H , Wang L , Li J , Tan L , Deng W , et al . Five novel loci associated with antipsychotic treatment response in patients with schizophrenia: a genome-wide association study . Lancet Psychiatry . 2018 ; 5 ( 4 ): 327 – 38 .

Tang H , Dalton CF , Srisawat U , Zhang ZJ , Reynolds GP . Methylation at a transcription factor-binding site on the 5-HT1A receptor gene correlates with negative symptom treatment response in first episode schizophrenia . Int J Neuropsychopharmacol . 2014 ; 17 ( 4 ): 645 – 9 .

Paul SM , Yohn SE , Popiolek M , Miller AC , Felder CC . Muscarinic acetylcholine receptor agonists as novel treatments for schizophrenia . Am J Psychiatry . 2022 ; 179 ( 9 ): 611 – 27 .

Ventriglio A , Bellomo A , Ricci F , Magnifico G , Rinaldi A , Borraccino L , et al . New pharmacological targets for the treatment of schizophrenia: a literature review . Curr Top Med Chem . 2021 ; 21 ( 16 ): 1500 – 16 .

De Berardis D , de Filippis S , Masi G , Vicari S , Zuddas A . A neurodevelopment approach for a transitional model of early onset schizophrenia . Brain Sci . 2021 ; 11 ( 2 ): 275 .

Naveen M , Patil AN , Pattanaik S , Kaur A , Banerjee D , Grover S . ABCB1 and DRD3 polymorphism as a response predicting biomarker and tool for pharmacogenetically guided clozapine dosing in Asian Indian treatment resistant schizophrenia patients . Asian J Psychiatr . 2020 ; 48 : 101918 .

Lu AK , Lin JJ , Tseng HH , Wang XY , Jang FL , Chen PS , et al . DNA methylation signature aberration as potential biomarkers in treatment-resistant schizophrenia: constructing a methylation risk score using a machine learning method . J Psychiatr Res . 2023 ; 157 : 57 – 65 .

Yu H , Wang L , Lv L , Ma C , Du B , Lu T , et al . Genome-wide association study suggested the PTPRD polymorphisms were associated with weight gain effects of atypical antipsychotic medications . Schizophr Bull . 2016 ; 42 ( 3 ): 814 – 23 .

Moher D , Hopewell S , Schulz KF , Montori V , Gotzsche PC , Devereaux PJ , et al . CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials . BMJ . 2010 ; 340 : c869 .

Moons KGM , Altman DG , Reitsma JB , Ioannidis JP , Macaskill P , Steyerberg EW , et al . Transparent Reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration . Ann Intern Med . 2015 ; 162 ( 1 ): W1 - 73 .

Cheng W , Luo N , Zhang Y , Zhang X , Tan H , Zhang D , et al . DNA methylation and resting brain function mediate the association between childhood urbanicity and better speed of processing . Cereb Cortex . 2021 ; 31 ( 10 ): 4709 – 18 .

Howes OD , McCutcheon R , Agid O , de Bartolomeis A , van Beveren NJ , Birnbaum ML , et al . Treatment-resistant schizophrenia: treatment response and resistance in psychosis (TRRIP) working group consensus guidelines on diagnosis and terminology . Am J Psychiatry . 2017 ; 174 ( 3 ): 216 – 29 .

Horvath S . DNA methylation age of human tissues and cell types . Genome Biol . 2013 ; 14 ( 10 ): R115 .

Cross-Disorder Group of the Psychiatric Genomics C , Lee SH , Ripke S , Neale BM , Faraone SV , Purcell SM , et al . Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs . Nat Genet . 2013 ; 45 ( 9 ): 984 – 94 .

Li HJ , Zhang C , Hui L , Zhou DS , Li Y , Zhang CY , et al . Novel risk loci associated with genetic risk for bipolar disorder among Han Chinese individuals: a genome-wide association study and meta-analysis . JAMA Psychiat . 2021 ; 78 ( 3 ): 320 – 30 .

Giannakopoulou O , Lin K , Meng X , Su MH , Kuo PH , Peterson RE , et al . The genetic architecture of depression in individuals of East Asian ancestry: a genome-wide association study . JAMA Psychiat . 2021 ; 78 ( 11 ): 1258 – 69 .

Wu Y , Qi T , Wang H , Zhang F , Zheng Z , Phillips-Cremins JE , et al . Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data . Nat Commun . 2020 ; 11 ( 1 ): 2061 .

Kunkle BW , Vardarajan BN , Naj AC , Whitehead PL , Rolati S , Slifer S , et al . Early-onset Alzheimer disease and candidate risk genes involved in endolysosomal transport . JAMA Neurol . 2017 ; 74 ( 9 ): 1113 – 22 .

Shadrin AA , Kaufmann T , van der Meer D , Palmer CE , Makowski C , Loughnan R , et al . Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology . Neuroimage . 2021 ; 244 : 118603 .

van Erp TGM , Walton E , Hibar DP , Schmaal L , Jiang W , Glahn DC , et al . Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro imaging genetics through meta analysis (ENIGMA) consortium . Biol Psychiatry . 2018 ; 84 ( 9 ): 644 – 54 .

Kirschner M , Hodzic-Santor B , Antoniades M , Nenadic I , Kircher T , Krug A , et al . Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide enigma study . Mol Psychiatry . 2022 ; 27 ( 2 ): 1167 – 76 .

Cheng W , Frei O , van der Meer D , Wang Y , O’Connell KS , Chu Y , et al . Genetic association between schizophrenia and cortical brain surface area and thickness . JAMA Psychiat . 2021 ; 78 ( 9 ): 1020 – 30 .

Sha Z , Schijven D , Francks C . Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization . Mol Psychiatry . 2021 ; 26 ( 12 ): 7652 – 60 .

Wannan CMJ , Cropley VL , Chakravarty MM , Bousman C , Ganella EP , Bruggemann JM , et al . Evidence for network-based cortical thickness reductions in schizophrenia . Am J Psychiatry . 2019 ; 176 ( 7 ): 552 – 63 .

Inloes JM , Hsu KL , Dix MM , Viader A , Masuda K , Takei T , et al . The hereditary spastic paraplegia-related enzyme DDHD2 is a principal brain triglyceride lipase . Proc Natl Acad Sci . 2014 ; 111 ( 41 ): 14924 – 9 .

Gelernter J , Kranzler HR , Sherva R , Koesterer R , Almasy L , Zhao H , et al . Genome-wide association study of opioid dependence: multiple associations mapped to calcium and potassium pathways . Biol Psychiatry . 2014 ; 76 ( 1 ): 66 – 74 .

Uesaka N , Uchigashima M , Mikuni T , Nakazawa T , Nakao H , Hirai H , et al . Retrograde semaphorin signaling regulates synapse elimination in the developing mouse brain . Science . 2014 ; 344 ( 6187 ): 1020 – 3 .

Pasterkamp RJ , Peschon JJ , Spriggs MK , Kolodkin AL . Semaphorin 7A promotes axon outgrowth through integrins and MAPKs . Nature . 2003 ; 424 ( 6947 ): 398 – 405 .

Brown TC , Tran IC , Backos DS , Esteban JA . NMDA receptor-dependent activation of the small GPTpase Rab5 drives the removal of synaptic AMPA receptors during hippocampal LTD . Neuron . 2005 ; 45 ( 1 ): 81 – 94 .

Li Y , Roy BD , Wang W , Zhang L , Zhang L , Sampson SB , et al . Identification of two functionally distinct endosomal recycling pathways for dopamine D2 receptor . J Neurosci . 2012 ; 32 ( 21 ): 7178 – 90 .

Yuen EY , Liu W , Karatsoreos IN , Ren Y , Feng J , McEwen BS , et al . Mechanisms for acute stress-induced enhancement of glutamatergic transmission and working memory . Mol Psychiatry . 2011 ; 16 ( 2 ): 156 – 70 .

Kost GC , Selvaraj S , Lee YB , Kim DJ , Ahn CH , Singh BB . Clavulanic acid increases dopamine release in neuronal cells through a mechanism involving enhanced vesicle trafficking . Neurosci Lett . 2011 ; 504 ( 2 ): 170 – 5 .

Mochel F , Rastetter A , Ceulemans B , Platzer K , Yang S , Shinde DN , et al . Variants in the SK2 channel gene (KCNN2) lead to dominant neurodevelopmental movement disorders . Brain . 2020 ; 143 ( 12 ): 3564 – 73 .

Cormont M , Mari M , Galmiche A , Hofman P , Le Marchand-Brustel Y . A FYVE-finger-containing protein, Rabip4, is a Rab4 effector involved in early endosomal traffic . Proc Natl Acad Sci . 2001 ; 98 ( 4 ): 1637 – 42 .

Jones PA . Functions of DNA methylation: Islands, start sites, gene bodies and beyond . Nat Rev Genet . 2012 ; 13 ( 7 ): 484 – 92 .

Ikegame T , Bundo M , Okada N , Murata Y , Koike S , Sugawara H , et al . Promoter activity-based case-control association study on SLC6A4 highlighting hypermethylation and altered amygdala volume in male patients with schizophrenia . Schizophr Bull . 2020 ; 46 ( 6 ): 1577 – 86 .

Dominguez-Salas P , Moore SE , Baker MS , Bergen AW , Cox SE , Dyer RA , et al . Maternal nutrition at conception modulates DNA methylation of human metastable epialleles . Nat Commun . 2014 ; 5 : 3746 .

Planterose Jiménez B , Liu F , Caliebe A , Montiel Gonzalez D , Bell JT , Kayser M , et al . Equivalent DNA methylation variation between monozygotic co-twins and unrelated individuals reveals universal epigenetic interindividual dissimilarity . Genome Biol . 2021 ; 22 ( 1 ): 18 .

Hadley JA , Nenert R , Kraguljac NV , Bolding MS , White DM , Skidmore FM , et al . Ventral tegmental area/midbrain functional connectivity and response to antipsychotic medication in schizophrenia . Neuropsychopharmacology . 2014 ; 39 ( 4 ): 1020 – 30 .

International Consortium on Lithium G (ConLi+Gen) , Amare AT , Schubert KO , Hou L , Clark SR , Papiol S , et al . Association of polygenic score for schizophrenia and HLA antigen and inflammation genes with response to lithium in bipolar affective disorder: a genome-wide association study . JAMA Psychiat . 2018 ; 75 ( 1 ): 65 – 74 .

Li A , Zalesky A , Yue W , Howes O , Yan H , Liu Y , et al . A neuroimaging biomarker for striatal dysfunction in schizophrenia . Nat Med . 2020 ; 26 ( 4 ): 558 – 65 .

Davies C , Segre G , Estrade A , Radua J , De Micheli A , Provenzani U , et al . Prenatal and perinatal risk and protective factors for psychosis: a systematic review and meta-analysis . Lancet Psychiatry . 2020 ; 7 ( 5 ): 399 – 410 .

Hannon E , Dempster E , Viana J , Burrage J , Smith AR , Macdonald R , et al . An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation . Genome Biol . 2016 ; 17 ( 1 ): 176 .

Jaffe AE , Gao Y , Deep-Soboslay A , Tao R , Hyde TM , Weinberger DR , et al . Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex . Nat Neurosci . 2016 ; 19 ( 1 ): 40 – 7 .

Ruderfer DM , Charney AW , Readhead B , Kidd BA , Kahler AK , Kenny PJ , et al . Polygenic overlap between schizophrenia risk and antipsychotic response: a genomic medicine approach . Lancet Psychiatry . 2016 ; 3 ( 4 ): 350 – 7 .

Santoro ML , Ota V , de Jong S , Noto C , Spindola LM , Talarico F , et al . Polygenic risk score analyses of symptoms and treatment response in an antipsychotic-naive first episode of psychosis cohort . Transl Psychiatry . 2018 ; 8 ( 1 ): 174 .

De Luca V , Chaudhary Z , Al-Chalabi N , Qian J , Borlido C , Gerretsen P , et al . Genome-wide methylation analysis of treatment resistant schizophrenia . J Neural Transm (Vienna) . 2023 ; 130 ( 2 ): 165 – 9 .

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

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

A prediction model for moderate to severe acute kidney injury in people with heart failure

Amisulpride augmentation therapy improves cognitive performance and psychopathology in clozapine-resistant treatment-refractory schizophrenia: a 12-week randomized, double-blind, placebo-controlled trial

Spine system changes in soldiers after load carriage training in a plateau environment: A prediction model research

Analysis on the Reason of Larger Wheel/Rail Lateral Force for Loaded Car with 3D-axle Welded-frame Bogies during Negotiating

Related Author

Yu-Ya-Nan Zhang

Zhe Lu

Hao Yan

Tian-Lan Lu

Jun Li

Yun-Dan Liao

Zhe-Wei Kang

Li-Fang Wang

Related Institution

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

National Clinical Research Center for Kidney Disease, State Laboratory of Organ Failure Research, Division of Nephrology, Nanfang Hospital, Southern Medical University

Division of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Sir Run Run Shaw Hospital, Zhejiang University School of Medicine

Department of Nephrology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University

⁰