Polygenic risk scores (PRSs) are promising tools for advancing precision medicine. However, existing PRS construction methods rely on static summary statistics derived from genome-wide association studies (GWASs), which are often updated at lengthy intervals. As genetic data and health outcomes are continuously being generated at an ever-increasing pace, the current PRS training and deployment paradigm is suboptimal in maximizing the prediction accuracy of PRSs for incoming patients in healthcare settings. Here, we introduce real-time PRS-CS (rtPRS-CS), which enables online, dynamic refinement and calibration of PRS as each new sample is collected, without the need to perform intermediate GWASs. Through extensive simulation studies, we evaluate the performance of rtPRS-CS across various genetic architectures and training sample sizes. Leveraging quantitative traits from the Mass General Brigham Biobank and UK Biobank, we show that rtPRS-CS can integrate massive streaming data to enhance PRS prediction over time. We further apply rtPRS-CS to 22 schizophrenia cohorts in 7 Asian regions, demonstrating the clinical utility of rtPRS-CS in dynamically predicting and stratifying disease risk across diverse genetic ancestries.

H.H. received consultancy fees from Ono Pharmaceutical and honorarium from Xian Janssen Pharmaceutical. The other authors declare no competing interests.

J.D.T is supported by the Mass General Brigham Training Program in Precision and Genomic Medicine (T32HG010464). R.D. is supported by National Institute of General Medical Sciences (NIGMS) R01GM148494. H.H. acknowledges supports from National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) K01DK114379 and R01DK129364, National Institute of Mental Health (NIMH) U01MH109539 and R01MH130675, Brain and Behavior Research Foundation Young Investigator Grant (28450), the Zhengxu and Ying He Foundation, and the Stanley Center for Psychiatric Research. T.G. is supported by National Human Genome Research Institute (NHGRI) R01HG012354, U01HG011723, and NIMH R01MH130899.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The use of Mass General Brigham Biobank (MGBB) data was approved by the Mass General Brigham Institutional Review Board. Collection of the UK Biobank (UKBB) data was approved by the Research Ethics Committee of the UKBB. UKBB data used in the present work were obtained under application 32568. The use of schizophrenia cohorts of East Asian ancestry in the present work was approved by the Stanley Global Asia Initiatives. The following institutions provided ethics oversight for the collection of schizophrenia samples: Samsung Medical Center; Bio-X Institutes of Shanghai Jiao Tong University; Xi'an Jiaotong University; The Second Xiangya Hospital of Central South University; Peking University Sixth Hospital; Fujita Health University; Tokyo Metropolitan Institute of Medical Science; University Medical Center Utrecht; The University of Western Australia; The University of Indonesia; RIKEN Center for Integrative Medical Sciences; Nagoya University; Osaka University; Niigata University; Chonnam National University Hospital; and Mass General Brigham (Protocols 2014P001342 and 2011P002207). Informed consent and permission to share the data were obtained from all subjects, in compliance with the guidelines specified by the recruiting center's institutional review board.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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Mass General Brigham Biobank (MGBB) data are not publicly available due to privacy and ethical restrictions. De-identified data may be shared under an approved Data Use Agreement. UK Biobank (UKBB) data can be accessed under an approved application. The UKBB data used in the present study were obtained under application 32568. Data from schizophrenia cohorts are available through application to the Stanley Global Asia Initiatives: SGAIbroadinstitute.org. These data are subject to controlled access due to compliance requirements, participant consent and national laws. Application to access these data requires a brief research proposal that will be reviewed by the principal investigator of each cohort and, if necessary, by the respective ethics committee.