Identification of distinct trajectories in preclinical type 2 diabetes and their associations with outcomes

Type 2 Diabetes Mellitus (T2DM) is increasingly prevalent and significantly impacts patients’ lives. However, the phenotypic and genetic heterogeneity of the preclinical stage of T2DM, along with the subsequent effects on various clinical outcomes, remain unclear, impeding progress in disease screening and prevention. To address this gap, we employed a robust machine learning algorithm (Subtype and Stage Inference, SuStaIn) with cross-sectional clinical data from the UK Biobank (20,305 preclinical-T2DM participants and 20,305 controls) to identify underlying subtypes and their progression trajectories for preclinical-T2DM. Our analysis revealed one subtype distinguished by elevated circulating leptin levels and decreased leptin receptor levels, coupled with increased BMI, diminished lipid metabolism, and heightened susceptibility to psychiatric conditions such as anxiety disorder, depression disorder, and bipolar disorder. Conversely, individuals in the second subtype manifested typical abnormalities in glucose metabolism, including rising glucose and HbA1c levels, with observed correlations with neurodegenerative disorders. Over ten-year follow-up observations of these individuals reveal differential deterioration in brain and heart organs, and statistically significant difference in disease risk and clinical outcomes between the two subtypes. Our findings indicate a heterogenous pathobiological basis underlying the progression of preclinical-T2DM, with clinical implications for understanding human health from a multiorgan perspective, and improving disease risk screening, prediction, and prevention efforts. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was partially supported by the National Key Research and Development Program of China under Grant No 2022YFF1202400 ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the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. Yes 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). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data used and generated in this study are provided in the Supplementary Data. The phenotypic, genotypic, proteomic, metabolic data used in the study that supports subtype and stage modelling and association analyses were obtained from the UK Biobank under application number 89757. Access to the UK Biobank data is available to all researchers with approval (). All GWAS data for the outcomes used in this study are publicly available from FinnGen database (), Psychiatric Genomics Consortium (PGC, ) and GWAS Catalog (). Statistic details of the GWAS datasets and download links for all the datasets are available in Supplementary Table 7.