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An independent replication cohort of 501 individuals with type 1 diabetes and 853 control individuals was used to validate the top common variant associations. HLA typing data were used to identify tag SNPs for\n                      <jats:italic>DQA1-DQB1<\/jats:italic>\n                      haplotypes. We integrated significant signals to construct a Chinese type 1 diabetes GRS (C-GRS). The accuracy of the C-GRS was tested in an independent validation cohort consisting of 262 individuals with type 1 diabetes, 1080 individuals with type 2 diabetes and 208 control individuals.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We identified a variant, rs10232170, in\n                      <jats:italic>BMPER<\/jats:italic>\n                      as a possible novel type 1 diabetes locus (\n                      <jats:italic>p<\/jats:italic>\n                      =9.897\u00d710\n                      <jats:sup>\u22129<\/jats:sup>\n                      ). We identified tag SNPs for 13\n                      <jats:italic>DQA1-DQB1<\/jats:italic>\n                      haplotypes and 12 non-\n                      <jats:italic>DQA1-DQB1<\/jats:italic>\n                      loci. Integrating 33 significant SNPs from HLA and non-HLA regions, C-GRS demonstrated high discriminative power for type 1 diabetes (AUC=0.876). It\u00a0was tested in an independent validation cohort and showed high discrimination (AUC 0.871 for type 1 diabetes vs control group, 0.869 for type 1 diabetes vs type 2 diabetes). The C-GRS outperformed a European-derived GRS (0.871 vs 0.773, and 0.869 vs 0.793, respectively).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions\/interpretation<\/jats:title>\n                    <jats:p>A type 1 diabetes C-GRS comprising 33 SNPs was highly discriminative of type 1 diabetes risk in the Chinese population and could aid in discriminating between type 1 diabetes and type 2 diabetes. This study highlights the potential of genetic information in improving prediction and precision diagnosis of type 1 diabetes in the Chinese population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data availability<\/jats:title>\n                    <jats:p>\n                      The raw sequencing data and summary statistics of genomic DNA derived from human samples have been deposited at the China National Center for Bioinformation (\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/ngdc.cncb.ac.cn\/omix\" ext-link-type=\"uri\">https:\/\/ngdc.cncb.ac.cn\/omix<\/jats:ext-link>\n                      ) under accession number PRJCA023730.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00125-025-06455-x","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T02:02:38Z","timestamp":1750903358000},"page":"1969-1982","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A type 1 diabetes genetic risk score discriminates between type 1 diabetes and type 2 diabetes in a Chinese population"],"prefix":"10.1007","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5385-9113","authenticated-orcid":false,"given":"Jingyi","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2795-714X","authenticated-orcid":false,"given":"Guozhi","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9360-4991","authenticated-orcid":false,"given":"Jiabi","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuoming","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baoqi","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5037-3807","authenticated-orcid":false,"given":"Zhiguo","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raymond","family":"Wan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8665-7983","authenticated-orcid":false,"given":"Xia","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia H. 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The full lists of team members of the Hong Kong Diabetes Biobank Study Group are included in ESM \u2018\n                      \n                      \u2019 section.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Acknowledgements"}},{"value":"The raw sequencing data and summary statistics of genomic DNA derived from human samples have been deposited at the China National Center for Bioinformation (\n                      \n                      ) under accession number PRJCA023730.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data availability"}},{"value":"This work was supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0507300, 2023ZD0508200, 2023ZD0508201, 2023ZD0509100), the National Key Research and Development Program of China (2018YFE0114500), the National Natural Science Foundation of China (82270891, 82200933) and the Science and Technology Innovation Program of Hunan Province (2024RC3054). The analysis of samples from Hong Kong was supported by the Research Grants Council Theme-based Research Scheme (T12-402\/13 N), the Research Impact Fund (R4012-18) and the University Grants Committee Research Grants Matching Scheme (RGMS).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Funding"}},{"value":"RAO has funding from Randox to study GRS for autoimmune disease. The University of Exeter has a licensing and royalty agreement with Randox for a 10 SNP GRS. RAO reports consulting for Janssen, Provention Bio and Sanofi and receives research funding from Randox. RCWM is a member of the editorial board of\n                      Diabetologia\n                      . RCWM has received research funding from AstraZeneca, Bayer, Boehringer Ingelheim, Merck Sharp & Dohme, Novo Nordisk, Pfizer, Roche Diagnostics and Tricida Inc. for carrying out clinical trials or studies, and from AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly and Merck for speaker honoraria or consultancy in advisory boards. All proceeds have been donated to the Chinese University of Hong Kong to support diabetes research. RCWM is a co-founder of GemVCare. CKPL holds a shareholding in GemVCare Limited. JCNC received consultancy fees or speaker honoraria from Applied Therapeutics, Astra Zeneca, Bayer, Boehringer Ingelheim, Celltrion, Eli Lilly, Hua Medicine, Lee Power Pharmaceuticals, Merck, MSD, Pfizer, Roche, Sanofi, Servier, Viatris Pharmaceutical and Zuelling Pharma. JCNC is the Chief Executive Officer (pro bono) of the Asian Diabetes Foundation. She holds patents for using biomarkers to predict diabetes and its complications and is the co-founder of GemVCare. The authors declare that there are no other relationships or activities that might bias, or be perceived to bias, their work.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Authors\u2019 relationships and activities"}},{"value":"YXiao and ZZ conceived the project and designed the experiments. RCWM and RAO supervised the study, interpreted the data, commented and edited the manuscript. JHu conducted the experiments, performed the statistical analysis and analysed the data. YXiao and JHu wrote the manuscript. WAH and MNW assisted in the design of the study, statistical analysis and result interpretation. GJ, JQ, ZW and GY contributed to data analysis and result interpretation. JHu, SL, BF, ZX, RW, XL, CHTT, JD, YXia, YY, JL, PJ, CKPL, AOYL, WYS, CW, JHuang and JCNC participated in the recruitment of participants and contributed to data acquisition. All authors contributed to the article and approved the submitted version. YXiao and ZZ are the guarantors of this work and had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Contribution statement"}}]}}