Principal Investigator

Ju-Sheng Zheng

Ju-Sheng Zheng

郑钜圣

  • E-mail：zhengjusheng@westlake.edu.cn
  • Tel: +86-0571-86915303



    • Principal Investigator

    Ju-Sheng got his PhD degree in nutrition at Zhejiang University, Hangzhou, China (2009-2014). Within his PhD program, he received one year’s training in the Nutrition and Genomics Lab at Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University in the USA (2012). He was also a Marie Skłodowska-Curie Individual Fellow supported by the European Commission and a postdoctoral researcher at the MRC Epidemiology Unit, University of Cambridge, UK (2015-2018).

    Ju-Sheng joined the School of Life Sciences at Westlake University as a principal investigator and assistant professor in September 2018. He serves as associate editor for BMC Med and statistical editor for Asia Pac J Clin Nutr. He has published over 90 peer-reviewed papers in leading journals such as BMJ, Gut, Diabetes Care, PLoS Med, Microbiome, BMC Med, Am J Clin Nutr, et al.





    Current Interests

    1. Precision nutrition: using novel study design (n-of-1 clinical trial) or wearable device (such as continuous glucose monitoring) to explore individual’ personalized response to diet and nutrition in the Chinese populations. Using multi-omics technologies to unveil the mechanism behind the link between nutrition and chronic diseases with large-scale human cohort data.

    2. Computational Medicine: Use computational methods and multi-omics datasets (including nutrition biomarkers, genomics, metabolomics, microbiome and proteomics) within human cohorts to investigate the etiology of aging-related diseases or pregnancy-related outcomes, and to identify novel disease biomarkers and prioritize potential drug targets.

    Representitive Publication

    (* corresponding author)
    1. Shuai M, Fu Y, Zhong HL, Gou W, Jiang Z, Liang Y, Miao Z, Xu JJ, Huynh T, Wahlqvist ML*, Chen YM*, Zheng JS*. Mapping the human gut mycobiome in middle-aged and elderly adults: multiomics insights and implications for host metabolic health. Gut 2022. In press. Doi: 10.1136/gutjnl-2021-326298.


    2. Fu Y, Xu F, Jiang L, Miao Z, Liang X, Yang J, Larsson, SC, Zheng JS*. Circulating vitamin C concentration and risk of cancers: a Mendelian randomization study. BMC Med 2021,19(1):171. doi: 10.1186/s12916-021-02041-1


    3. Ma Yu Y, Tian Y, Gou W, Miao Z, Yang M, Ordovas JM, Zheng JS*. Individual postprandial glycemic responses to diet in N-of-1 trials: Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR). J Nutr 2021,151(10):3158-67.


    4. Shuai M, Zuo LS, Miao Z, Gou W, Xu F, Jiang Z, Ling CW, Fu Y, Xiong F, Chen YM*, Zheng JS*. Multi-omics analyses reveal relationships among dairy consumption, gut microbiota and cardiometabolic health. EBioMedicine 2021, 66:103284. doi: 10.1016/j.ebiom.2021.103284.


    5. Gou W, Ling CW, He Y, Jiang Z, Fu Y, Xu F, Miao Z, Sun TY, Lin JS, Zhu HL, Zhou H, Chen YM*, Zheng JS*. Interpretable machine learning framework reveals robust gut microbiome features associated with type 2 diabetes. Diabetes Care 2021, 44(2):358-366. doi: 10.2337/dc20-1536.


    6. Jiang Z, Sun TY, He Y, Gou W, Zuo LS, Fu Y, Miao Z, Shuai M, Xu F, Xiao C, Liang Y, Wang J, Xu Y, Jing LP, Ling W, Zhou H*, Chen YM*, Zheng JS*. Dietary fruit and vegetable intake, gut microbiota, and type 2 diabetes: results from two large human cohort studies. BMC Med. 2020, 18(1):371. doi: 10.1186/s12916-020-01842-0.


    7. Miao Z, Lin JS, Mao Y, Chen GD, Zeng FF, Dong HL, Jiang ZL, Wang JL, Xiao CM, Shuai M, Gou W, Fu Y, Imamura F, Chen YM*, Zheng JS*. Erythrocyte n-6 polyunsaturated fatty acids, gut microbiota and incident type 2 diabetes: a prospective cohort study. Diabetes Care 2020, 43(10):2435-43.


    8. Xu F, Fu Y, Sun TY, Jiang Z, Miao Z, Shuai M, Gou W, Ling CW, Yang J, Wang J*, Chen YM*, Zheng JS* The interplay between host genetics and the gut microbiome reveals common and distinct microbiome features for complex human diseases. Microbiome 2020, 8(1):145.


    9. Fu Y, Gou W, Hu W, Mao Y, Tian Y, Liang X, Guan Y, Huang T, Li K, Guo X, Liu H*, Li D*, Zheng JS*. Integration of an interpretable machine-learning algorithm to identify early life risk factors of childhood obesity among preterm infants: a prospective birth cohort. BMC Med 2020, 18(1):184.


    10. Zheng JS, Sharp SJ, Imamura F, Rajiv C, Thomas GE, Marinka S, Sluijs I, van der Schouw YT, Agudo A, Aune D, Barricarte A, Boeing H, Chirlaque MD, Dorronsoro M, Freisling H, Fatoui DE, Franks PW, Fagherazzi G, Grioni S, Gunter MJ, Kyrø C, Katzke V, Kühn T, Khaw KT, Laouali N, Masala G, Nilsson PM, Overvad K, Panico S, Papier K, Quirós JR, Rolandsson O, Redondo-Sánchez D, Ricceri F, Schulze MB, Spijkerman AMW, Tjønneland A, Tong TYN, Tumino R, Weiderpass E, Danesh J, Butterworth AS, Riboli E, Forouhi NG*, Wareham NJ. Association of plasma biomarkers of fruit and vegetable intake with incident type 2 diabetes: The EPIC-InterAct case-cohort study in eight European countries. BMJ 2020;370:m2194.


    Full list of publications:PubMed