Westlake Gut Project: A consortium of microbiome epidemiology for the gut microbiome and health research in China

2019, A review of 10 years of human microbiome research activities at the US National Institutes of Health, Fiscal Years 2007-2016, Microbiome, 7, 31, 10.1186/s40168-019-0620-y Dominguez-Bello, 2019, Role of the microbiome in human development, Gut, 68, 1108, 10.1136/gutjnl-2018-317503 Fan, 2021, Gut microbiota in human metabolic health and disease, Nat Rev Microbiol, 19, 55, 10.1038/s41579-020-0433-9 Gilbert, 2018, Current understanding of the human microbiome, Nat Med, 24, 392, 10.1038/nm.4517 Renson, 2020, Sick individuals and sick (microbial) populations: challenges in epidemiology and the microbiome, Annu Rev Publ Health, 41, 63, 10.1146/annurev-publhealth-040119-094423 McDonald, 2018, American gut: an open platform for citizen science microbiome research, mSystems, 3, 10.1128/mSystems.00031-18 Tigchelaar, 2015, Cohort profile: LifeLines DEEP, a prospective, general population cohort study in the northern Netherlands: study design and baseline characteristics, BMJ Open, 5, 10.1136/bmjopen-2014-006772 Borodulin, 2018, Cohort profile: the national FINRISK study, Int J Epidemiol, 47, 10.1093/ije/dyx239 Rothschild, 2018, Environment dominates over host genetics in shaping human gut microbiota, Nature, 555, 210, 10.1038/nature25973 Qin, 2022, Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort, Nat Genet, 54, 134, 10.1038/s41588-021-00991-z Scepanovic, 2019, A comprehensive assessment of demographic, environmental, and host genetic associations with gut microbiome diversity in healthy individuals, Microbiome, 7, 130, 10.1186/s40168-019-0747-x He, 2018, Regional variation limits applications of healthy gut microbiome reference ranges and disease models, Nat Med, 24, 1532, 10.1038/s41591-018-0164-x Kurilshikov, 2021, Large-scale association analyses identify host factors influencing human gut microbiome composition, Nat Genet, 53, 156, 10.1038/s41588-020-00763-1 Popkin, 2010, Cohort profile: the China health and nutrition survey--monitoring and understanding socio-economic and health change in China, 1989-2011, Int J Epidemiol, 39, 1435, 10.1093/ije/dyp322 Sun, 2020, Does geographical variation confound the relationship between host factors and the human gut microbiota: a population-based study in China, BMJ Open, 10, 10.1136/bmjopen-2020-038163 He, 2018, Regional variation limits applications of healthy gut microbiome reference ranges and disease models, Nat Med, 24, 1532, 10.1038/s41591-018-0164-x Duan, 2021, The Chinese adolescent cohort study: design, implementation, and major findings, Front Nutr, 8, 10.3389/fnut.2021.747088 Zhang, 2014, Association between dietary intake of flavonoid and bone mineral density in middle aged and elderly Chinese women and men, Osteoporos Int, 25, 2417, 10.1007/s00198-014-2763-9 Gou, 2021, Interpretable machine learning framework reveals robust gut microbiome features associated with type 2 diabetes, Diabetes Care, 44, 358, 10.2337/dc20-1536 Chen, 2021, Metabolically abnormal but normal-weight individuals had a higher risk of type 2 diabetes mellitus in a cohort study of a Chinese population, Front Endocrinol, 12, 10.3389/fendo.2021.724873 Wang, 2021, Plasma lipidomics in early pregnancy and risk of gestational diabetes mellitus: a prospective nested case-control study in Chinese women, Am J Clin Nutr, 114, 1763, 10.1093/ajcn/nqab242 Bolyen, 2019, Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2, Nat Biotechnol, 37, 852, 10.1038/s41587-019-0209-9 Callahan, 2016, DADA2: high-resolution sample inference from Illumina amplicon data, Nat Methods, 13, 581, 10.1038/nmeth.3869 Quast, 2013, The SILVA ribosomal RNA gene database project: improved data processing and web-based tools, Nucleic Acids Res, 41, D590 Gacesa, 2022, Environmental factors shaping the gut microbiome in a Dutch population, Nature, 604, 732, 10.1038/s41586-022-04567-7 Ruuskanen, 2022, Gut microbiome composition is predictive of incident type 2 diabetes in a population cohort of 5,572 Finnish adults, Diabetes Care, 10.2337/dc21-2358 Asnicar, 2021, Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals, Nat Med, 27, 321, 10.1038/s41591-020-01183-8 Falony, 2016, Population-level analysis of gut microbiome variation, Science, 352, 560, 10.1126/science.aad3503 Manor, 2020, Health and disease markers correlate with gut microbiome composition across thousands of people, Nat Commun, 11, 5206, 10.1038/s41467-020-18871-1 Nel Van Zyl, 2020, The effect of storage conditions on microbial communities in stool, PLoS One, 15, 10.1371/journal.pone.0227486 Tedjo, 2015, The effect of sampling and storage on the fecal microbiota composition in healthy and diseased subjects, PLoS One, 10, 10.1371/journal.pone.0126685 Carroll, 2012, Characterization of the fecal microbiota using high-throughput sequencing reveals a stable microbial community during storage, PLoS One, 7, 10.1371/journal.pone.0046953 Zheng, 2020, Regulobiosis: a regulatory and food system-sensitive role for fungal symbionts in human evolution and ecobiology, Asia Pac J Clin Nutr, 29, 9 Sokol, 2017, Fungal microbiota dysbiosis in IBD, Gut, 66, 1039, 10.1136/gutjnl-2015-310746 Shuai, 2022, Mapping the human gut mycobiome in middle-aged and elderly adults: multiomics insights and implications for host metabolic health, Gut, 10.1136/gutjnl-2021-326298 Meade, 2022, Mycotherapy: potential of fungal bioactives for the treatment of mental health disorders and morbidities of chronic pain, J Fungi (Basel, Switzerland), 8 Sun, 2021, Population-level configurations of gut mycobiome across 6 ethnicities in urban and rural China, Gastroenterology, 160, 272, 10.1053/j.gastro.2020.09.014 Zeevi, 2015, Personalized nutrition by prediction of glycemic responses, Cell, 163, 1079, 10.1016/j.cell.2015.11.001