Gou Wanglong

Gou Wanglong,principal investigator

Xi'an Jiaotong University School of Public Health

Research Areas (Directions):

Gut Microbiota Epidemiology

Nutritional Epidemiology

Systems Biology

Education:

2018.9-2022.6 West Lake University School of Life Sciences, Biology, Ph.D.

2014.9-2017.4 Northwestern Polytechnical University School of Automation, Computational Biology, M.S.

2010.9-2014.6 LiaoNing Petrochemical University School of Information and Control Engineering, Automation, B.E.

Work Experience:

2025.9-Present Xi'an Jiaotong University School of Public Health, principal investigator

2024.7-2025.8 Westlake Laboratory of Life Sciences and Biomedicine (Zhejiang Province Laboratory), Assistant Researcher

2022.7-2024.7 West Lake University School of Life Sciences, Postdoctoral Researcher

2017.4-2018.5 Digital China Systems Integration Service Co., Ltd. Engineering Institute, Data Analyst

Biography:

My research spans multiple disciplines including epidemiology, nutrition, bioinformatics, and machine learning. It primarily focuses on characterizing the molecular landscape of metabolic diseases using multi-omics and artificial intelligence, constructing early-warning models, and identifying novel biomarkers and nutritional intervention strategies for metabolic diseases. In the past five years, I have published 52 SCI papers. First (or co-first) author papers have been published in renowned international journals such asNature Medicine,Cell Reports Medicine(cover story),Gut,Diabetes Care,JAMA Network Open,Protein & Cell,Diabetologia,EBioMedicine,BMC Medicine, andAJCN. My research findings have been cited over 1900 times by top-tier journals includingNature,Nature Reviews Microbiology, andCell Metabolism. I have presided over one project from the National Natural Science Foundation of China (Young Scientists Fund) and one project from the China Postdoctoral Science Foundation (General Program). I have participated in two projects from the National Natural Science Foundation of China (General Program) and three other projects. I hold two authorized patents and have contributed to two textbooks. I serve as a Guest Editor for the international journalNutrientsand as a reviewer for multiple SCI journals.

Representative Publications (# Co-first author):

1. Gou W, Zheng JS. Updating the evidence on ultra-processed foods and health.Nat Med.2025; 31:2119–2120.

1. Gou W, Wang H, Su C, Fu Y, Wang X, Gao C, Shuai M, Miao Z, Zhang J, Jia X, Du W, Zhang K, Zhang B, Zheng JS. The temporal dynamics of gut mycobiome and its association with cardiometabolic health in a nationwide cohort of 12,641 Chinese adults.Cell Rep Med.2024;5(10):101775.

This study, based on a large-scale, multi-regional gut fungi database, characterized the composition, temporal dynamics, and association with cardiometabolic health of the gut mycobiome in a middle-aged and older Chinese population. This paper was selected as the cover story forCell Reports Medicine.

1. 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.

This study integrated an interpretable machine learning framework to propose a novel gut microbiome risk score algorithm for type 2 diabetes (T2D), identifying 14 gut microbiome markers associated with T2D risk and validating their causal relationship with T2D through animal experiments. This achievement was selected for the "2021 Top 15 Global Original Nutritional Research" list independently curated by the Chinese Nutrition Society and has been cited over 160 times by journals including Nature (as of Sept. 2025).

1. Gou W, Xiao C, Liang X, Miao Z, Shi M, Wu Y, Lu S, Wang X, Fu Y, Hu W, Zheng JS. Physical activity during pregnancy and preterm birth among women with gestational diabetes.JAMA Netw Open.2024;7(12):e2451799.

This study systematically assessed the relationship between physical activity patterns in the first trimester and preterm birth risk among women with gestational diabetes mellitus (GDM) using wearable devices, providing important evidence for GDM-specific management guidelines. The study garnered significant attention upon publication (Altmetric score 73).

1. Fu Y,Gou W#, Wu P, Lai Y, Liang X, Zhang K, Shuai M, Tang J, Chen J, Yuan J, Zhao B, Yang Y, Liu X, Hu Y, Pan A, Pan X, Zheng JS. Landscape of the gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health.Gut.2024;73(8):1302-1312.

This study systematically characterized the dynamics of the gut mycobiome during pregnancy and its association with birth outcomes.

1. Gou W, Miao Z, Deng K, Zheng J-S. Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health.Protein Cell.2023; 14 (11), 787-806.

Invited review (1 of 9) for the Microbiome Special Issue of Protein & Cell and the 2023 China Gut Conference. It details the progress in "nutri-microbiome epidemiology" and outlines future directions.

1. Gou W, Wang H, Tang XY, He Y, Su C, Zhang J, Sun TY, Jiang Z, Miao Z, Fu Y, Zhao H, Chen YM, Zhang B, Zhou H, Zheng, JS. Early-life exposure to the Great Chinese Famine and gut microbiome disruption across adulthood for type 2 diabetes: three population-based cohort studies.BMC Med.2023;21(1):414.

This study was the first to explore the potential mechanisms linking early-life malnutrition to T2D incidence from the perspective of the gut microbiome, providing a new perspective for understanding the Developmental Origins of Health and Disease (DOHaD) hypothesis. This work was interviewed and reported by Zhejiang Daily.

1. Gou W, Yue L, Tang XY, Wu YY, Cai X, Shuai M, Miao Z, Fu Y, Chen H, Jiang Z, Wang J, Tian Y, Xiao C, Xiang N, Wu Z, Chen YM, Guo T, Zheng JS. Circulating proteome and progression of type 2 diabetes.J Clin Endocrinol Metab.2022;20:dgac098.

Based on a nested case-control design, this study identified circulating protein markers for T2D and investigated their interaction with diet on T2D risk.

1. Gou W, Fu Y, Yue L, Chen GD, Cai X, Shuai M, Xu F, Yi X, Chen H, Zhu Y, Xiao ML, Jiang Z, Miao Z, Xiao C, Shen B, Wu X, Zhao H, Ling W, Wang J, Chen YM, Guo T, Zheng JS. Gut microbiota, inflammation, and molecular signatures of host response to infection.J Genet Genomics.2021; 3:S1673-8527(21)00094-1.

This study integrated gut microbiome, proteomic, and metabolomic data to "simulate" the host's molecular response to COVID-19 infection. The research attracted widespread attention and has been cited over 150 times (including the preprint version).

1. Wang H,Gou W#, Su C, Du W, Zhang J, Miao Z, Xiao C, Jiang Z, Wang Z, Fu Y, Jia X, Ouyang Y, Jiang H, Huang F, Li L, Zhang B, Zheng JS. Association of gut microbiota with glycaemic traits and incident type 2 diabetes, and modulation by habitual diet: a population-based longitudinal cohort study in Chinese adults.Diabetologia.2022;65(7):1145-1156.

This study revealed differences in gut bacteria between populations in Northern and Southern China and elucidated the longitudinal association between gut microbiome-diet interactions and the risk of incident T2D.

1. Fu Y,Gou W#, Zhong H, Tian Y, Zhao H, Liang X, Shuai M, Zhuo LB, Jiang Z, Tang J, Ordovas JM, Chen YM, Zheng JS. Diet-gut microbiome interaction and its impact on host blood glucose homeostasis: a series of nutritional n-of-1 trials.EBioMedicine.2025 Jan;111:105483.

Utilizing an N-of-1 trial design, this study revealed the influence of the gut microbiome on host personalized dietary responses. This paper was selected as the cover article for that month's issue of EBioMedicine.

1. 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.

This study employed interpretable machine learning to identify key early-life risk factors for childhood obesity among preterm infants.

1. Wu Y,Gou W#, Yan Y, Liu CY, Yang Y, Chen D, Xie K, Jiang Z, Fu, Y, Zhu H, Zheng JS, Chen Y M. Gut microbiota and acylcarnitine metabolites connect the beneficial association between equol and adiposity in adults: a prospective cohort study.Am J Clin Nutr,2022; 116(6):1831-1841.

This study suggested that equol may mitigate obesity risk through the gut microbiota and acylcarnitine metabolites.

1. Zhang X, Guan F,Gou W#, Wang Q, Du S, Su C, Zhang J, Zheng J-S, Wang H, Zhang B. Multi-trajectories of BMI, waist circumference, gut microbiota, and incident dyslipidemia: a 27-year prospective study.mSystems.2025 May 20;10(5):e0024325.

This study investigated the relationship between longitudinal fluctuations in BMI/waist circumference and incident dyslipidemia, and explored the underlying mechanisms using gut microbiome and metabolomic data.

Full Publication List:

ResearchGate: https://www.researchgate.net/profile/Wanglong-Gou

Google Scholar: https://scholar.google.com/citations?hl=en&user=YNHJbv8AAAAJ&view_op=list_works

Contact Information:

Email: gouwanglong@xjtu.edu.cn

Tel: 029-82655108

Address: Room 3140, Hongren Building (Building 21), Western China Science and Technology Innovation Harbor

We warmly welcome motivated undergraduates, graduate students, and postdoctoral researchers with relevant backgrounds to join our research group. Interested individuals please send your CV and related information to the email address above.