A whole blood-based transcriptional risk score for nonobese type 2 diabetes predicts dynamic changes in glucose metabolic traits

Background The performance of peripheral blood transcriptional markers in evaluating the risk of type 2 diabetes (T2D) with normal weight is unknown. We developed a whole blood-based transcriptional risk score (wb-TRS) for nonobese T2D and assessed its contributions to disease risk and dynamic changes in glucose metabolism. Methods and findings We developed the wb-TRS in 1105 participants aged ≥40 years and in normal weight for up to 10 years from a well-defined community-based cohort with blood transcriptome data and validated it in an external dataset (253 overweight/obese participants from a dietary intervention trial with 3 repeated transcriptome data). Potential biology significance and causal inference were also explored. The wb-TRS included 144 transcripts. Compared to the lowest tertile, wb-TRS in tertile 3 associated with 8.68-folds (95% confidence interval [CI], 3.51-21.5), and each 1-unit increment associated with 2.57-folds (95% CI, 1.86-3.56) higher risk of nonobese T2D, after adjustments for traditional risk factors. Furthermore, baseline wb-TRS was significantly associated with dynamic changes in average, daytime, nighttime and 24h glucose and HbA1c, and area under the curve of glucose measured in the continuous glucose monitoring during 6-month of intervention. The wb-TRS improved the predicting performance for nonobese T2D in a model with fasting glucose, triglycerides and demographic and anthropometric parameters. Mitch analysis implicated oxidative phosphorylation, cholesterol metabolism and mTORC1 signaling involved in nonobese T2D pathogenesis. Transcriptome-wide Mendelian randomization supported causal effects of gene transcripts such as RAB1A and GCC1-PAX4 on nonobese T2D risk. Conclusions A whole blood based nonobese T2D associated TRS was validated to predict dynamic changes in glucose metabolism. These findings also suggested several genes and biological pathways that might involve in the pathogenesis of nonobese T2D. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was funded by the National Natural Science Foundation of China (82270859, 91957124, 91857205, 81930021, 81970728, 82070880 and 82088102), the Shanghai Municipal Education Commission Gaofeng Clinical Medicine Grant Support (20152508 Round 2), the Shanghai Shenkang Hospital Development Center (SHDC12019101, SHDC2020CR1001A, and SHDC2020CR3064B). MX, JW, ML, TW, ZZ, RL, YX, JL, YB, WW, and GN are members of the innovative research team of high level local universities in Shanghai. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study protocol was approved by the Institutional Review Board of Rui-Jin Hospital affiliated to Shanghai Jiao Tong University School of Medicine. All participants gave written consent for the study. 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 eQTLs data used in this study are available on the eQLTGen Consortium website [https://eqtlgen.org/]. The summary statistics of genome-wide association study of T2D was available in the Asian Genetic Epidemiology Network (AGEN) [https://blog.nus.edu.sg/agen/] and the DIAbetes Genetics Replication And Meta analysis (DIAGRAM) [http://www.diagram-consortium.org/downloads.html/]. RNA seq related additional data reported in this manuscript are available from the corresponding author upon reasonable request. * AUC : area under the curve BMI : body mass index CPM : count per million CI : confidence interval DBP : diastolic blood pressure DPMH : Dietary Pattern and Metabolic Health eQTL : expression quantitative trait locus GEE : generalized estimating equation HbA1c : hemoglobin A1c HOMA-IR : homeostasis model assessment of insulin resistance HOMA-β : homeostasis model assessment of beta cell function HDL-C : high-density lipoprotein cholesterol MET : metabolic equivalent of task Mitch analysis : a multi-contrast gene set enrichment analysis LDL-C : low-density lipoprotein cholesterol LASSO : least absolute shrinkage and selection operator OGTT : oral glucose tolerance test OR : odds ratio RCS : restricted cubic spline RNA-seq : RNA sequencing SBP : systolic blood pressure T2D : Type 2 diabetes TRS : transcriptional risk score TWMR : Transcriptome-wide Mendelian randomization TSGE : Tissue-specific gene expression