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413 results on '"Luo, Zuojie"'

1. Gallstones, cholecystectomy, and cancer risk: an observational and Mendelian randomization study

Author

Zhu, Yuanyue, Shen, Linhui, Huo, Yanan, Wan, Qin, Qin, Yingfen, Hu, Ruying, Shi, Lixin, Su, Qing, Yu, Xuefeng, Yan, Li, Qin, Guijun, Tang, Xulei, Chen, Gang, Xu, Yu, Wang, Tiange, Zhao, Zhiyun, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Gu, Xuejiang, Luo, Zuojie, Chen, Li, Li, Qiang, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Chen, Lulu, Zeng, Tianshu, Zhao, Jiajun, Mu, Yiming, Wang, Weiqing, Ning, Guang, Lu, Jieli, Xu, Min, Bi, Yufang, and Hu, Weiguo

Published
2024
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6. Associations of sleeping patterns and isotemporal substitution of other behavior with the prevalence of CKD in Chinese adults

Author

Ding, Yi, Xu, Xiaoli, Xin, Zhuojun, Cao, Qiuyu, Huang, Jiaojiao, Wu, Xianglin, Huo, Yanan, Wan, Qin, Qin, Yingfen, Hu, Ruying, Shi, Lixin, Su, Qing, Yu, Xuefeng, Yan, Li, Qin, Guijun, Tang, Xulei, Chen, Gang, Xu, Min, Wang, Tiange, Zhao, Zhiyun, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Chen, Li, Li, Qiang, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Yang, Tao, Deng, Huacong, Chen, Lulu, Zeng, Tianshu, Zhao, Jiajun, Mu, Yiming, Wu, Shengli, Chen, Yuhong, Lu, Jieli, Wang, Weiqing, Ning, Guang, Xu, Yu, Bi, Yufang, and Li, Mian

Published
2024
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8. Association of social determinants, lifestyle, and metabolic factors with mortality in Chinese adults: A nationwide 10-year prospective cohort study

Author

Lu, Jieli, Li, Mian, He, Jiang, Xu, Yu, Zheng, Ruizhi, Zheng, Jie, Qin, Guijun, Qin, Yingfen, Chen, Yuhong, Tang, Xulei, Ye, Zhen, Xu, Min, Wang, Tiange, Shi, Lixin, Su, Qing, Yu, Xuefeng, Yan, Li, Zhao, Zhiyun, Wan, Qin, Chen, Gang, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Gu, Xuejiang, Luo, Zuojie, Chen, Li, Hou, Xinguo, Huo, Yanan, Li, Qiang, Qiao, Hong, Zhang, Yinfei, Zeng, Tianshu, Hu, Chunyan, Cao, Qiuyu, Jia, Xiaojing, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Qi, Hongyan, Wu, Xueyan, Zhang, Di, Dai, Meng, Li, Donghui, Lai, Shenghan, Chen, Lulu, Zhao, Jiajun, Mu, Yiming, Hu, Weiguo, Ning, Guang, Hu, Ruying, Bi, Yufang, and Wang, Weiqing

Published
2024
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9. Association of circulating long-chain free fatty acids and incident diabetes risk among normoglycemic Chinese adults: a prospective nested case–control study

Author

Wang, Shuangyuan, Hu, Chunyan, Lin, Hong, Jia, Xiaojing, Hu, Ruying, Zheng, Ruizhi, Li, Mian, Xu, Yu, Xu, Min, Zheng, Jie, Zhao, Xinjie, Li, Yanli, Chen, Lulu, Zeng, Tianshu, Ye, Zhen, Shi, Lixin, Su, Qing, Chen, Yuhong, Yu, Xuefeng, Yan, Li, Wang, Tiange, Zhao, Zhiyun, Qin, Guijun, Wan, Qin, Chen, Gang, Dai, Meng, Zhang, Di, Qiu, Bihan, Zhu, Xiaoyan, Liu, Ruixin, Wang, Xiao, Tang, Xulei, Gao, Zhengnan, Shen, Feixia, Gu, Xuejiang, Luo, Zuojie, Qin, Yingfen, Chen, Li, Hou, Xinguo, Huo, Yanan, Li, Qiang, Wang, Guixia, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Zhao, Jiajun, Mu, Yiming, Xu, Guowang, Lai, Shenghan, Li, Donghui, Ning, Guang, Wang, Weiqing, Bi, Yufang, and Lu, Jieli

Published
2024
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11. Early adulthood weight change, midlife “Life’s essential 8” health status and risk of cardiometabolic diseases: a chinese nationwide cohort study

Author

Cao, Qiuyu, Li, Mian, Qin, Guijun, Yan, Li, He, Jiang, Xu, Min, Xu, Yu, Wang, Tiange, Chen, Yuhong, Wang, Shuangyuan, Lin, Hong, Zhao, Zhiyun, Gao, Zhengnan, Zeng, Tianshu, Hu, Ruying, Yu, Xuefeng, Chen, Gang, Su, Qing, Mu, Yiming, Chen, Lulu, Tang, Xulei, Wan, Qin, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Qin, Yingfen, Chen, Li, Huo, Yanan, Li, Qiang, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Zhao, Jiajun, Shi, Lixin, Ning, Guang, Wang, Weiqing, Lu, Jieli, and Bi, Yufang

Published
2023
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15. Risk of cardiovascular disease, death, and renal progression in diabetes according to albuminuria and estimated glomerular filtration rate

Author

Niu, Jingya, Zhang, Xiaoyun, Li, Mian, Wu, Shujing, Zheng, Ruizhi, Chen, Li, Huo, Yanan, Xu, Min, Wang, Tiange, Zhao, Zhiyun, Wang, Shuangyuan, Lin, Hong, Qin, Guijun, Yan, Li, Wan, Qin, Chen, Lulu, Shi, Lixin, Hu, Ruying, Tang, Xulei, Su, Qing, Yu, Xuefeng, Qin, Yingfen, Chen, Gang, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Chen, Yuhong, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Li, Qiang, Mu, Yiming, Zhao, Jiajun, Bi, Yufang, Ning, Guang, Wang, Weiqing, Lu, Jieli, and Xu, Yu

Published
2023
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16. Abnormal brain regional activity in acute thyrotoxic myopathy assessed by resting-state functional MRI.

Author

Kuang, Yaqi, Liang, Xinghuan, Ye, Wei, Fu, Shien, Qin, Yingfen, Ma, Yan, and Luo, Zuojie

Subjects
PREFRONTAL cortex, MOTOR cortex, FRONTAL lobe, FUNCTIONAL connectivity, AUTOMATED teller machines
Abstract

Background: The neurophysiological mechanisms underlying manifestations of bulbar paralysis in acute thyrotoxic myopathy (ATM) and the afflicted brain areas are unclear. Purpose: We used resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate the regional brain activities in patients with ATM. Material and Methods: In total, 16 patients with ATM, 16 patients with hyperthyroidism without ATM, and 16 healthy controls underwent functional MRI scans. By calculating the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), we assessed variations in resting-state cerebral activity. The correlation between the resting-state functional indexes and clinical assessments was also explored. Results: Compared to the hyperthyroid patients, patients with ATM had stronger ReHo in the left precentral gyrus, reduced ReHo in the left orbitofrontal gyrus (OFG), and decreased FC in the left precentral gyri, left superior frontal gyrus (SFG), and left middle frontal gyrus (MFG). Patients with ATM showed reduced fALFF and ReHo in the right SFG and decreased ReHo in the bilateral supplementary motor area (SMA). A significantly decreased FC in the left SFG and left MFG, right precentral gyrus, and the orbital part of the right interior frontal gyrus was observed in patients with ATM compared to healthy controls. Additionally, fALFF and ReHo values were positively correlated with serum thyroid-related hormones and antibodies. Conclusion: The findings of rs-fMRI demonstrate that particular brain regions' functional activity was aberrant in individuals with ATM, especially in SFG area. This finding may help with better understanding of underlying pathophysiology of patients with ATM. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Hypertension Defined by 2017 ACC/AHA Guideline, Ideal Cardiovascular Health Metrics, and Risk of Cardiovascular Disease: A Nationwide Prospective Cohort Study

Author

Wu, Shujing, Xu, Yu, Zheng, Ruizhi, Lu, Jieli, Li, Mian, Chen, Li, Huo, Yanan, Xu, Min, Wang, Tiange, Zhao, Zhiyun, Wang, Shuangyuan, Lin, Hong, Dai, Meng, Zhang, Di, Niu, Jingya, Qin, Guijun, Yan, Li, Wan, Qin, Chen, Lulu, Shi, Lixin, Hu, Ruying, Tang, Xulei, Su, Qing, Yu, Xuefeng, Qin, Yingfen, Chen, Gang, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Chen, Yuhong, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Li, Qiang, Mu, Yiming, Zhao, Jiajun, Bi, Yufang, Wang, Weiqing, and Ning, Guang

Published
2022
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19. Association of soy food with cardiovascular outcomes and all-cause mortality in a Chinese population: a nationwide prospective cohort study

Author

Xue, Ting, Wen, Junping, Wan, Qin, Qin, Guijun, Yan, Li, Wang, Guixia, Qin, Yingfen, Luo, Zuojie, Tang, Xulei, Huo, Yanan, Hu, Ruying, Ye, Zhen, Shi, Lixin, Gao, Zhengnan, Su, Qing, Mu, Yiming, Zhao, Jiajun, Chen, Lulu, Zeng, Tianshu, Yu, Xuefeng, Li, Qiang, Shen, Feixia, Chen, Li, Zhang, Yinfei, Wang, Youmin, Deng, Huacong, Liu, Chao, Wu, Shengli, Yang, Tao, Li, Mian, Xu, Yu, Xu, Min, Wang, Tiange, Zhao, Zhiyun, Lu, Jieli, Bi, Yufang, Wang, Weiqing, Chen, Gang, and Ning, Guang

Published
2022
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20. Interaction between smoking and diabetes in relation to subsequent risk of cardiovascular events

Author

Yang, Yang, Peng, Nianchun, Chen, Gang, Wan, Qin, Yan, Li, Wang, Guixia, Qin, Yingfen, Luo, Zuojie, Tang, Xulei, Huo, Yanan, Hu, Ruying, Ye, Zhen, Qin, Guijun, Gao, Zhengnan, Su, Qing, Mu, Yiming, Zhao, Jiajun, Chen, Lulu, Zeng, Tianshu, Yu, Xuefeng, Li, Qiang, Shen, Feixia, Chen, Li, Zhang, Yinfei, Wang, Youmin, Deng, Huacong, Liu, Chao, Wu, Shengli, Yang, Tao, Li, Mian, Xu, Yu, Xu, Min, Zhao, Zhiyun, Wang, Tiange, Lu, Jieli, Bi, Yufang, Wang, Weiqing, Ning, Guang, Zhang, Qiao, and Shi, Lixin

Published
2022
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21. Association between triglyceride glucose index and breast cancer in 142,184 Chinese adults: findings from the REACTION study

Author

Wu, Xueyan, primary, Wang, Shuangyuan, additional, Lin, Lin, additional, Jia, Xiaojing, additional, Hu, Chunyan, additional, Qi, Hongyan, additional, Lin, Hong, additional, Zheng, Ruizhi, additional, Li, Mian, additional, Xu, Yu, additional, Xu, Min, additional, Chen, Lulu, additional, Zeng, Tianshu, additional, Hu, Ruying, additional, Ye, Zhen, additional, Shi, Lixin, additional, Su, Qing, additional, Yu, Xuefeng, additional, Yan, Li, additional, Wang, Tiange, additional, Zhao, Zhiyun, additional, Zheng, Jie, additional, Qin, Guijun, additional, Wan, Qin, additional, Chen, Gang, additional, Dai, Meng, additional, Tang, Xulei, additional, Gao, Zhengnan, additional, Shen, Feixia, additional, Gu, Xuejiang, additional, Luo, Zuojie, additional, Qin, Yingfen, additional, Chen, Li, additional, Hou, Xinguo, additional, Huo, Yanan, additional, Li, Qiang, additional, Wang, Guixia, additional, Zhang, Yinfei, additional, Liu, Chao, additional, Wang, Youmin, additional, Wu, Shengli, additional, Yang, Tao, additional, Deng, Huacong, additional, Zhao, Jiajun, additional, Mu, Yiming, additional, Ning, Guang, additional, Wang, Weiqing, additional, Bi, Yufang, additional, Chen, Yuhong, additional, and Lu, Jieli, additional

Published
2024
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22. Age-specific modifiable risk factor profiles for cardiovascular disease and all-cause mortality: a nationwide, population-based, prospective cohort study

Author

Wang, Tiange, Zhao, Zhiyun, Yu, Xuefeng, Zeng, Tianshu, Xu, Min, Xu, Yu, Hu, Ruying, Chen, Gang, Su, Qing, Mu, Yiming, Chen, Lulu, Tang, Xulei, Yan, Li, Qin, Guijun, Wan, Qin, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Qin, Yingfen, Chen, Li, Huo, Yanan, Li, Qiang, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Zhao, Jiajun, Xu, Yiping, Li, Mian, Chen, Yuhong, Wang, Shuangyuan, Ning, Guang, Bi, Yufang, Shi, Lixin, Lu, Jieli, and Wang, Weiqing

Published
2021
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23. Non-alcoholic fatty liver disease, metabolic goal achievement with incident cardiovascular disease and eGFR-based chronic kidney disease in patients with prediabetes and diabetes

Author

Li, Mian, Zhao, Zhiyun, Qin, Guijun, Chen, Li, Lu, Jieli, Huo, Yanan, Chen, Lulu, Zeng, Tianshu, Xu, Min, Chen, Yuhong, Wang, Tiange, Wang, Shuangyuan, Xu, Yiping, Shi, Lixin, Tang, Xulei, Su, Qing, Yu, Xuefeng, Yan, Li, Wan, Qin, Chen, Gang, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Hu, Ruying, Ye, Zhen, Wu, Shengli, Deng, Huacong, Yang, Tao, Li, Qiang, Qin, Yingfen, Mu, Yiming, Zhao, Jiajun, Ning, Guang, Bi, Yufang, Xu, Yu, and Wang, Weiqing

Published
2021
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24. Age-related disparities in diabetes risk attributable to modifiable risk factor profiles in Chinese adults: a nationwide, population-based, cohort study

Author

Wang, Tiange, Zhao, Zhiyun, Wang, Guixia, Li, Qiang, Xu, Yu, Li, Mian, Hu, Ruying, Chen, Gang, Su, Qing, Mu, Yiming, Tang, Xulei, Yan, Li, Qin, Guijun, Wan, Qin, Gao, Zhengnan, Yu, Xuefeng, Shen, Feixia, Luo, Zuojie, Qin, Yingfen, Chen, Li, Huo, Yanan, Zeng, Tianshu, Chen, Lulu, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Zhao, Jiajun, Shi, Lixin, Xu, Yiping, Xu, Min, Chen, Yuhong, Wang, Shuangyuan, Lu, Jieli, Bi, Yufang, Ning, Guang, and Wang, Weiqing

Published
2021
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26. Examining the Linear Association Between Blood Pressure Levels and Cardiovascular Diseases in the Absence of Major Risk Factors in China

Author

Zheng, Ruizhi, Xu, Yu, Li, Mian, Lu, Jieli, Wu, Shujing, Niu, Jingya, Zhao, Zhiyun, Chen, Li, Huo, Yanan, Xu, Min, Wang, Tiange, Wang, Shuangyuan, Lin, Hong, Qin, Guijun, Yan, Li, Wan, Qin, Chen, Lulu, Shi, Lixin, Hu, Ruying, Tang, Xulei, Su, Qing, Yu, Xuefeng, Qin, Yingfen, Chen, Gang, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Chen, Yuhong, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Li, Qiang, Mu, Yiming, Zhao, Jiajun, Wang, Weiqing, Ning, Guang, and Bi, Yufang

Published
2022
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27. Association of early adulthood weight and subsequent weight change with cardiovascular diseases: Findings from REACTION study

Author

Zhu, Yuanyue, Zheng, Ruizhi, Hu, Chunyan, Qin, Guijun, Wang, Bin, Wang, Tiange, Yu, Xuefeng, Tang, Xulei, Hu, Ruying, Su, Qing, Zhang, Jie, Zhang, Yi, Zhao, Zhiyun, Xu, Yu, Li, Mian, Chen, Yuhong, Wang, Shuangyuan, Shi, Lixin, Wan, Qin, Chen, Gang, Dai, Meng, Zhang, Di, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Qin, Yingfen, Chen, Li, Huo, Yanan, Li, Qiang, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Chen, Lulu, Zhao, Jiajun, Mu, Yiming, Yan, Li, Wang, Weiqing, Ning, Guang, Bi, Yufang, Lu, Jieli, and Xu, Min

Published
2021
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29. Remnant cholesterol is more positively related to diabetes, prediabetes, and insulin resistance than conventional lipid parameters and lipid ratios: A multicenter, large sample survey.

Author

Li, Binqi, Liu, Yang, Zhou, Xin, Chen, Lulu, Yan, Li, Tang, Xulei, Gao, Zhengnan, Wan, Qin, Luo, Zuojie, Qin, Guijun, Ning, Guang, Gu, Weijun, and Mu, Yiming

Subjects
MULTIPLE regression analysis, LOGISTIC regression analysis, PREDIABETIC state, INSULIN resistance, DIABETES
Abstract

Background: Not many large‐sample investigations are available that compare the potency of the relationship of remnant cholesterol (RC) and other lipid parameters with diabetes and prediabetes. The goals of our study are to discover the relationship between RC and prediabetes, diabetes, and insulin resistance (IR) and to investigate RC, high‐density lipoprotein cholesterol (HDL‐C), non‐HDL‐C, triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), total cholesterol (TC), TC/HDL‐C, LDL‐C/HDL‐C, and TG/HDL‐C, which are the lipid parameters that are most positively related to diabetes, prediabetes, and IR. Methods: This research enrolled 36 684 subjects from China's eight provinces. We employed multiple logistic regression analysis for testing the relationship between lipid parameters and diabetes, prediabetes, and IR. Results: After adjusting for potential confounders, and comparing the results with other lipid parameters, the positive relationship between RC and diabetes (odds ratio [OR] 1.417, 95% confidence interval [CI]: 1.345–1.492), prediabetes (OR 1.555, 95% CI: 1.438–1.628), and IR (OR 1.488, 95% CI: 1.404–1.577) was highest. RC was still related to diabetes, prediabetes, and IR even when TG <2.3 mmol/L (diabetes: OR 1.256, 95% CI: 1.135–1.390; prediabetes: OR 1.503, 95% CI: 1.342–1.684; and IR: OR 1.278, 95% CI: 1.140–1.433), LDL‐C <2.6 mmol/L (diabetes: OR 1.306, 95% CI: 1.203–1.418; prediabetes: OR 1.597, 95% CI: 1.418–1.798; and IR: OR 1.552, 95% CI: 1.416–1.701), or HDL‐C ≥1 mmol/L (diabetes: OR 1.456, 95% CI: 1.366–1.550; prediabetes: OR 1.553, 95% CI: 1.421–1.697; and IR: OR 1.490, 95% CI: 1.389–1.598). Conclusion: RC is more positively related to diabetes, prediabetes, and IR than conventional lipids and lipid ratios in the general population, the relationships between RC and diabetes, prediabetes, and IR are stable, even if HDL‐C, LDL‐C, or TG are at appropriate levels. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Clinical characteristics and complication risks in data‐driven clusters among Chinese community diabetes populations.

Author

Li, Binqi, Yang, Zizhong, Liu, Yang, Zhou, Xin, Wang, Weiqing, Gao, Zhengnan, Yan, Li, Qin, Guijun, Tang, Xulei, Wan, Qin, Chen, Lulu, Luo, Zuojie, Ning, Guang, Gu, Weijun, and Mu, Yiming

Subjects
GLYCOSYLATED hemoglobin, GLYCEMIC control, DIABETES complications, LOGISTIC regression analysis, CHRONIC kidney failure
Abstract

Background: Novel diabetes phenotypes were proposed by the Europeans through cluster analysis, but Chinese community diabetes populations might exhibit different characteristics. This study aims to explore the clinical characteristics of novel diabetes subgroups under data‐driven analysis in Chinese community diabetes populations. Methods: We used K‐means cluster analysis in 6369 newly diagnosed diabetic patients from eight centers of the REACTION (Risk Evaluation of cAncers in Chinese diabeTic Individuals) study. The cluster analysis was performed based on age, body mass index, glycosylated hemoglobin, homeostatic modeled insulin resistance index, and homeostatic modeled pancreatic β‐cell functionality index. The clinical features were evaluated with the analysis of variance (ANOVA) and chi‐square test. Logistic regression analysis was done to compare chronic kidney disease and cardiovascular disease risks between subgroups. Results: Overall, 2063 (32.39%), 658 (10.33%), 1769 (27.78%), and 1879 (29.50%) populations were assigned to severe obesity‐related and insulin‐resistant diabetes (SOIRD), severe insulin‐deficient diabetes (SIDD), mild age‐associated diabetes mellitus (MARD), and mild insulin‐deficient diabetes (MIDD) subgroups, respectively. Individuals in the MIDD subgroup had a low risk burden equivalent to prediabetes, but with reduced insulin secretion. Individuals in the SOIRD subgroup were obese, had insulin resistance, and a high prevalence of fatty liver, tumors, family history of diabetes, and tumors. Individuals in the SIDD subgroup had severe insulin deficiency, the poorest glycemic control, and the highest prevalence of dyslipidemia and diabetic nephropathy. Individuals in MARD subgroup were the oldest, had moderate metabolic dysregulation and the highest risk of cardiovascular disease. Conclusion: The data‐driven approach to differentiating the status of new‐onset diabetes in the Chinese community was feasible. Patients in different clusters presented different characteristics and risks of complications. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Association of insulin resistance and β-cell dysfunction with incident diabetes among adults in China: a nationwide, population-based, prospective cohort study

Author

Wang, Tiange, Lu, Jieli, Shi, Lixin, Chen, Gang, Xu, Min, Xu, Yu, Su, Qing, Mu, Yiming, Chen, Lulu, Hu, Ruying, Tang, Xulei, Yu, Xuefeng, Li, Mian, Zhao, Zhiyun, Chen, Yuhong, Yan, Li, Qin, Guijun, Wan, Qin, Dai, Meng, Zhang, Di, Gao, Zhengnan, Wang, Guixia, Shen, Feixia, Luo, Zuojie, Qin, Yingfen, Chen, Li, Huo, Yanan, Li, Qiang, Ye, Zhen, Zhang, Yinfei, Liu, Chao, Wang, Youmin, Wu, Shengli, Yang, Tao, Deng, Huacong, Zhao, Jiajun, Lai, Shenghan, Bi, Yufang, DeFronzo, Ralph A, Wang, Weiqing, and Ning, Guang

Published
2020
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32. The Association between Educational Attainment and the Risk of Nonalcoholic Fatty Liver Disease among Chinese Adults: Findings from the REACTION Study

Author

Zhu, Yuanyue, primary, Wang, Long, additional, Lin, Lin, additional, Huo, Yanan, additional, Wan, Qin, additional, Qin, Yingfen, additional, Hu, Ruying, additional, Shi, Lixin, additional, Su, Qing, additional, Yu, Xuefeng, additional, Yan, Li, additional, Qin, Guijun, additional, Tang, Xulei, additional, Chen, Gang, additional, Wang, Shuangyuan, additional, Lin, Hong, additional, Wu, Xueyan, additional, Hu, Chunyan, additional, Li, Mian, additional, Xu, Min, additional, Xu, Yu, additional, Wang, Tiange, additional, Zhao, Zhiyun, additional, Gao, Zhengnan, additional, Wang, Guixia, additional, Shen, Feixia, additional, Gu, Xuejiang, additional, Luo, Zuojie, additional, Chen, Li, additional, Li, Qiang, additional, Ye, Zhen, additional, Zhang, Yinfei, additional, Liu, Chao, additional, Wang, Youmin, additional, Wu, Shengli, additional, Yang, Tao, additional, Deng, Huacong, additional, Chen, Lulu, additional, Zeng, Tianshu, additional, Zhao, Jiajun, additional, Mu, Yiming, additional, Wang, Weiqing, additional, Ning, Guang, additional, Bi, Yufang, additional, Chen, Yuhong, additional, and Lu, Jieli, additional

Published
2024
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33. Development and validation of a machine learning‐based model to predict isolated post‐challenge hyperglycemia in middle‐aged and elder adults: Analysis from a multicentric study.

Author

Hou, Rui, Dou, Jingtao, Wu, Lijuan, Zhang, Xiaoyu, Li, Changwei, Wang, Weiqing, Gao, Zhengnan, Tang, Xulei, Yan, Li, Wan, Qin, Luo, Zuojie, Qin, Guijun, Chen, Lulu, Ji, Jianguang, He, Yan, Wang, Wei, Mu, Yiming, and Zheng, Deqiang

Subjects
ARTIFICIAL neural networks, MIDDLE-aged persons, MACHINE learning, HYPERGLYCEMIA, GLUCOSE tolerance tests
Abstract

Introduction: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post‐challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2‐h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population. Methods: Data from 54301 eligible participants were obtained from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study in China. Data from 37740 participants were used to develop the diagnostic system. External validation was performed among 16561 participants. Three machine learning algorithms were used to create the predictive models, which were further evaluated by various classification algorithms to establish the best predictive model. Results: Ten features were selected to develop an IPH diagnosis system (IPHDS) based on an artificial neural network. In external validation, the AUC of the IPHDS was 0.823 (95% CI 0.811–0.836), which was significantly higher than the AUC of the Taiwan model [0.799 (0.786–0.813)] and that of the Chinese Diabetes Risk Score model [0.648 (0.635–0.662)]. The IPHDS model had a sensitivity of 75.6% and a specificity of 74.6%. This model outperformed the Taiwan and CDRS models in subgroup analyses. An online site with instant predictions was deployed at https://app‐iphds‐e1fc405c8a69.herokuapp.com/. Conclusions: The proposed IPHDS could be a convenient and user‐friendly screening tool for diabetes during health examinations in a large general population. [ABSTRACT FROM AUTHOR]

Published
2024
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40. The potential causal association between systemic lupus erythematosus and endocrine and metabolic disorders in the East Asian population: A bidirectional two-sample Mendelian randomization study.

Author

Wang, Tingliang, Zhang, Yun, Chen, Xuelan, Huang, Zhenxing, Liang, Xinghuan, Qin, Yingfen, and Luo, Zuojie

Subjects
EAST Asians, SYSTEMIC lupus erythematosus, ENDOCRINE diseases, METABOLIC disorders, TYPE 2 diabetes
Abstract

Objectives: Observational studies indicate a significant correlation between systemic lupus erythematosus (SLE) and endocrine and metabolic disorders, but the causal association between SLE and endocrine and metabolic disorders remains unclear due to the reverse causality and confounding biases commonly presented in conventional observational research. This study endeavors to uncover the causal association between SLE and three common endocrine and metabolic disorders, including Graves' disease (GD), type 2 diabetes mellitus (T2DM), and osteoporosis (OP). Methods: We used genome-wide association study data for SLE and three endocrine and metabolic disorders in an East Asian population, employing bidirectional two-sample Mendelian randomization (MR) analysis and sensitivity analysis to ascertain the causal association between SLE and endocrine and metabolic disorders. Results: A multiplicative random-effect inverse-variance weighted approach revealed a significant positive correlation between SLE and an elevated risk of GD with an odds ratio (OR) of 1.12 (95% CI: 1.04–1.22, p <.01), and inverse-variance weighted (IVW) analysis also indicated that SLE increased the risk of OP with an OR of 1.035 (95% CI: 1.003–1.068, p <.05). Additionally, GD causally affected SLE in an IVW analysis after Bonferroni correction, with an OR of 1.33 (95% CI: 1.19–1.49, p <.05/3), but the application of multivariable MR analysis resulted in the absence of a causal association of GD on SLE (OR 1.047, 95% CI: 0.952–1.151, p >.05). Lastly, the robustness and validity of the findings were verified through a sensitivity analysis. Conclusions: We confirmed that SLE has a causal effect on GD as well as OP, but no evidence exists to substantiate a causal link between SLE and T2DM. Our study offers valuable contributions for uncovering the etiology of SLE and endocrine and metabolic disorders and furthering disease risk research while providing potential targets for disease monitoring and therapeutic intervention. [ABSTRACT FROM AUTHOR]

Published
2024
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42. The mystery of transient pregnancy-induced cushing’s syndrome: a case report and literature review highlighting GNASsomatic mutations and LHCGR overexpression

Author

Li, Yufei, Lin, Jianfan, Fu, Shien, Li, Li, Huang, Zhenxing, Yang, Haiyan, Liang, Xinghuan, Qin, Yingfen, Zhou, Jia, Liu, Deyun, and Luo, Zuojie

Abstract

Purpose: Transient pregnancy-induced Cushing’s syndrome is a rare condition characterized by the manifestation of symptoms solely during pregnancy, which typically resolve spontaneously following delivery or miscarriage. While it has been established that GNASis associated with adrenal tumors, its specific role in the pathogenesis of pregnancy-induced Cushing’s syndrome remains uncertain.This work aims to examine the association between GNASmutation and pregnancy-induced Cushing’s syndrome. Methods: DNA was extracted from patients’ peripheral blood and tumor tissues for whole-exome sequencing (WES) and Sanger sequencing. We used AlphaFold to predict the protein structure of wild-type and mutant GNASand to make functional predictions, and immunohistochemistry was used to detect disease-associated protein expression. A review and summary of reported cases of transient pregnancy-induced Cushing’s syndrome induced by pregnancy was conducted. Results: Using WES, we identified a somatic mutation in GNAS(NM_000516, c.C601T, p.R201C) that was predicted to have a deleterious effect using computational methods, such as AlphaFold. Human chorionic gonadotropin (hCG) stimulation tests had weakly positive results, and immunohistochemical staining of adrenal adenoma tissue also revealed positivity for luteinizing hormone/chorionic gonadotropin receptor (LHCGR) and cytochrome P450 family 11 subfamily B member 1 (CYP11B1). We reviewed 15 published cases of transient Cushing’s syndrome induced by pregnancy. Among these cases, immunohistochemical staining of the adrenal gland showed positive LHCGR expression in 3 case reports, similar to our findings. Conclusion: Transient pregnancy-induced Cushing’s syndrome may be associated with somatic GNASmutations and altered adrenal pathology due to abnormal activation of LHCGR.

Published
2024
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43. Body roundness index is related to the low estimated glomerular filtration rate in Chinese population: A cross-sectional study

Author

Zhang, Yue, primary, Gao, Wenxing, additional, Ren, Rui, additional, Liu, Yang, additional, Li, Binqi, additional, Wang, Anping, additional, Tang, Xulei, additional, Yan, Li, additional, Luo, Zuojie, additional, Qin, Guijun, additional, Chen, Lulu, additional, Wan, Qin, additional, Gao, Zhengnan, additional, Wang, Weiqing, additional, Ning, Guang, additional, and Mu, Yiming, additional

Published
2023
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44. Data-driven subgroups of prediabetes and the associations with outcomes in Chinese adults

Author

Zheng, Ruizhi, primary, Xu, Yu, additional, Li, Mian, additional, Gao, Zhengnan, additional, Wang, Guixia, additional, Hou, Xinguo, additional, Chen, Li, additional, Huo, Yanan, additional, Qin, Guijun, additional, Yan, Li, additional, Wan, Qin, additional, Zeng, Tianshu, additional, Chen, Lulu, additional, Shi, Lixin, additional, Hu, Ruying, additional, Tang, Xulei, additional, Su, Qing, additional, Yu, Xuefeng, additional, Qin, Yingfen, additional, Chen, Gang, additional, Gu, Xuejiang, additional, Shen, Feixia, additional, Luo, Zuojie, additional, Chen, Yuhong, additional, Zhang, Yinfei, additional, Liu, Chao, additional, Wang, Youmin, additional, Wu, Shengli, additional, Yang, Tao, additional, Li, Qiang, additional, Mu, Yiming, additional, Zhao, Jiajun, additional, Hu, Chunyan, additional, Jia, Xiaojing, additional, Xu, Min, additional, Wang, Tiange, additional, Zhao, Zhiyun, additional, Wang, Shuangyuan, additional, Lin, Hong, additional, Ning, Guang, additional, Wang, Weiqing, additional, Lu, Jieli, additional, and Bi, Yufang, additional

Published
2023
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45. Remnant cholesterol is independently associated with diabetes, even if the traditional lipid is at the appropriate level: A report from the REACTION study

Author

Li, Binqi, primary, Zhou, Xin, additional, Wang, Weiqing, additional, Gao, Zhengnan, additional, Yan, Li, additional, Qin, Guijun, additional, Tang, Xulei, additional, Wan, Qin, additional, Chen, Lulu, additional, Luo, Zuojie, additional, Ning, Guang, additional, and Mu, Yiming, additional

Published
2023
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46. Blood Pressure Levels, Cardiovascular Events, and Renal Outcomes in Chronic Kidney Disease Without Antihypertensive Therapy: A Nationwide Population-Based Cohort Study

Author

Wu, Shujing, primary, Li, Mian, additional, Lu, Jieli, additional, Tang, Xulei, additional, Wang, Guixia, additional, Zheng, Ruizhi, additional, Niu, Jingya, additional, Chen, Li, additional, Huo, Yanan, additional, Xu, Min, additional, Wang, Tiange, additional, Zhao, Zhiyun, additional, Wang, Shuangyuan, additional, Lin, Hong, additional, Qin, Guijun, additional, Yan, Li, additional, Wan, Qin, additional, Chen, Lulu, additional, Shi, Lixin, additional, Hu, Ruying, additional, Su, Qing, additional, Yu, Xuefeng, additional, Qin, Yingfen, additional, Chen, Gang, additional, Gao, Zhengnan, additional, Shen, Feixia, additional, Luo, Zuojie, additional, Chen, Yuhong, additional, Zhang, Yinfei, additional, Liu, Chao, additional, Wang, Youmin, additional, Wu, Shengli, additional, Yang, Tao, additional, Li, Qiang, additional, Mu, Yiming, additional, Zhao, Jiajun, additional, Ning, Guang, additional, Bi, Yufang, additional, Wang, Weiqing, additional, Xu, Yu, additional, Li, Donghui, additional, Lai, Shenghan, additional, Bloomgarden, Zachary T., additional, Ye, Zhen, additional, and Deng, Huacong, additional

Published
2023
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47. U-shaped association between triglyceride and risk of incident diabetes in normoglycemic males with NAFLD: A population-base cohort study

Author

Xie, Xuemei, primary, Liao, Jixiang, additional, Huang, Chenghu, additional, Li, Xiaowei, additional, Cao, Qiuli, additional, Kong, Lijuan, additional, Okamura, Takuro, additional, Hashimoto, Yoshitaka, additional, Obora, Akihiro, additional, Kojima, Takao, additional, Fukui, Michiaki, additional, Hamaguchi, Masahide, additional, Luo, Zuojie, additional, Qin, Yingfen, additional, Liang, Xinghuan, additional, and Xuan, Xiuping, additional

Published
2023
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50. Lipid accumulation product is closely associated with hypertension and prehypertension in prediabetic population in China: results from the REACTION study

Author

Li, Binqi, primary, Wang, Jie, additional, Zhou, Xin, additional, Wang, Weiqing, additional, Gao, Zhengnan, additional, Tang, Xulei, additional, Yan, Li, additional, Wan, Qin, additional, Luo, Zuojie, additional, Qin, Guijun, additional, Chen, Lulu, additional, Ning, Guang, additional, and Mu, Yiming, additional

Published
2022
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