Supplementary file for "Whole blood-based transcriptional risk score for nonobese type 2 diabetes predicts dynamic changes in glucose metabolism"

Title: Whole blood-based transcriptional risk score for nonobese type 2 diabetes predicts dynamic changes in glucose metabolism

Authors: Yanan Hou, Huajie Dai, Na Chen, Zhiyun Zhao, Qi Wang, Tianzhichao Hou, Jie Zheng, Tiange Wang, Mian Li, Hong Lin, Shuangyuan Wang, Ruizhi Zheng, Jieli Lu, Yu Xu, Yuhong Chen, Ruixin Liu, Guang Ning, Weiqing Wang, Yufang Bi, Jiqiu Wang, Min Xu

Supporting information
Table S1. Clinical characteristics of study participants.
Table S2. Weights of 144 gene transcripts included in wb-TRS, ordered from most negative to most positive associated with nonobese type 2 diabetes.
Table S3. Association of z-score normalized wb-TRS with cardiometabolic traits in initial cohort.
Table S4. Receiver operator characteristic curves for prediction of nonobese type 2 diabetes.
Table S5. Top30 Reactome pathways associated with genes in wb-TRS.
Fig S1. Flowchart of study participants selection.
Fig S2. Cross-validation results for least absolute shrinkage and selection operator (LASSO) logistics-model for nonobese type 2 diabetes in training dataset.
Fig S3. Violin plot of wb-TRS and gene transcripts most negatively (FUOM) and positively (RPF1) associated with nonobese type 2 diabetes.
Fig S4. Stratified analysis. Data are odds ratio (OR) and 95% confidence interval (CI) calculated using multivariable logistic regression models. The results were adjusted for age, sex, body mass index, family history of diabetes, waist circumference, smoking and drinking status, education level, physical activity, systolic and diastolic blood pressure, total cholesterol, triglycerides, high-density and low-density lipoprotein cholesterol.

标题：基于全血的非肥胖2型糖尿病转录风险评分可预测糖代谢动态变化

作者：侯亚楠、戴华杰、陈娜、赵志云、王琪、侯天超、郑杰、王天戈、李勉、林宏、王双元、郑瑞芝、卢杰莉、徐宇、陈宇红、刘瑞欣、宁光、王卫庆、毕宇芳、王继秋、徐敏

补充材料
表S1. 研究参与者的临床特征
表S2. 纳入wb-TRS（全血转录风险评分，whole blood-based transcriptional risk score）的144个基因转录本的权重，按与非肥胖2型糖尿病的关联强度从最负到最正排序
表S3. 初始队列中经z-score标准化的wb-TRS与心脏代谢特征的关联
表S4. 非肥胖2型糖尿病预测的受试者工作特征（ROC）曲线
表S5. 与wb-TRS所包含基因相关的前30条Reactome通路
图S1. 研究参与者筛选流程图
图S2. 训练数据集中非肥胖2型糖尿病的最小绝对收缩和选择算子（LASSO）逻辑回归模型的交叉验证结果
图S3. wb-TRS及与非肥胖2型糖尿病关联最负（FUOM）和最正（RPF1）的基因转录本的小提琴图
图S4. 分层分析。数据为采用多变量logistic回归模型计算的比值比（OR）及95%置信区间（CI）。校正因素包括年龄、性别、体重指数、糖尿病家族史、腰围、吸烟与饮酒状态、受教育程度、体力活动、收缩压与舒张压、总胆固醇、甘油三酯、高密度脂蛋白胆固醇及低密度脂蛋白胆固醇。