Overview of the Microbiome Among Nurses study (Micro-N) as an example of prospective characterization of the microbiome within cohort studies

Christine Everett, Chengchen Li, Jeremy E. Wilkinson, Long H. Nguyen, Lauren J. McIver, Kerry Ivey, Jacques Izard, Natalia Palacios, A. Heather Eliassen, Walter C. Willett, Alberto Ascherio, Qi Sun, Shelley S. Tworoger, Andrew T. Chan, Wendy S. Garrett, Curtis Huttenhower, Eric B. Rimm, Mingyang Song

Published: 2021-04-20 DOI: 10.1038/s41596-021-00519-z

Microbiome

Prospective Studies

Cohort Studies

Micro-N

Human Health

AI 解读

Generation of mouse–human chimeric embryos

Genome-wide quantification of transcription factor binding at single-DNA-molecule resolution using methyl-transferase footprinting

Generation of CRISPR–Cas9-mediated genetic knockout human intestinal tissue–derived enteroid lines by lentivirus transduction and single-cell cloning

A puromycin-dependent activity-based sensing probe for histochemical staining of hydrogen peroxide in cells and animal tissues

Decoding personal biotic and abiotic airborne exposome

A clinically relevant model of focal embolic cerebral ischemia by thrombus and thrombolysis in rhesus monkeys

Bioengineering human intestinal mucosal grafts using patient-derived organoids, fibroblasts and scaffolds

Biomimetic tail-to-head terpene cyclizations using the resorcin[4]arene capsule catalyst

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Scanorama: integrating large and diverse single-cell transcriptomic datasets

Single-cell RNA sequencing (scRNA-seq)（单细胞RNA测序）

Data integration（数据集成）

Heterogeneity（异质性）

查看全部

Sections

Figures

References

A lack of prospective studies has been a major barrier for assessing the role of the microbiome in human health and disease on a population-wide scale. To address this significant knowledge gap, we have launched a large-scale collection targeting fecal an
Overview of the NHS II Cohort
Overview of the Micro-N project
Collection methods and kits provided by the BIOM-Mass platform as part of the HCMCC
Questionnaire development
Sample processing and storage
The BIOM-Mass data portal
Summary and future prospects
References
ACKNOWLEDGMENTS

The Integrative HMP (iHMP) Research Network Consortium. The integrative human microbiome project. Nature 569, 641–648 (2019).
Sinha, R. et al. Next steps in studying the human microbiome and health in prospective studies, Bethesda, MD, May 16–17, 2017. Microbiome 6, 210 (2018).
Costea, P. I. et al. Towards standards for human fecal sample processing in metagenomic studies. Nat. Biotechnol. 35, 1069–1076 (2017).
Sinha, R. et al. Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium. Nat. Biotechnol. 35, 1077–1086 (2017).
Bao, Y. et al. Origin, methods, and evolution of the three Nurses’ Health Studies. Am. J. Public Health 106, 1573–1581 (2016).
Ogino, S. et al. Integrative analysis of exogenous, endogenous, tumour and immune factors for precision medicine. Gut 67, 1168–1180 (2018).
Rice, M. S. et al. Breast cancer research in the Nurses’ Health Studies: exposures across the life course. Am. J. Public Health 106, 1592–1598 (2016).
Townsend, M. K., Aschard, H., De Vivo, I., Michels, K. B. & Kraft, P. Genomics, telomere length, epigenetics, and metabolomics in the Nurses’ Health Studies. Am. J. Public Health 106, 1663–1668 (2016).
Abu-Ali, G. S. et al. Metatranscriptome of human faecal microbial communities in a cohort of adult men. Nat. Microbiol 3, 356–366 (2018).
Mehta, R. S. et al. Stability of the human faecal microbiome in a cohort of adult men. Nat. Microbiol 3, 347–355 (2018).
Huang, T. et al. The Mind-Body Study: study design and reproducibility and interrelationships of psychosocial factors in the Nurses’ Health Study II. Cancer Causes Control 30, 779–790 (2019).
Bartosch, S., Fite, A., Macfarlane, G. T. & McMurdo, M. E. Characterization of bacterial communities in feces from healthy elderly volunteers and hospitalized elderly patients by using real-time PCR and effects of antibiotic treatment on the fecal microbiota. Appl. Environ. Microbiol. 70, 3575–3581 (2004).
Nagata, N. et al. Effects of bowel preparation on the human gut microbiome and metabolome. Sci. Rep. 9, 4042 (2019).
Jalanka, J. et al. Effects of bowel cleansing on the intestinal microbiota. Gut 64, 1562–1568 (2015).
Sinha, R. et al. Collecting fecal samples for microbiome analyses in epidemiology studies. Cancer Epidemiol. Biomark. Prev. 25, 407–416 (2016).
Carroll, I. M., Ringel-Kulka, T., Siddle, J. P., Klaenhammer, T. R. & Ringel, Y. Characterization of the fecal microbiota using high-throughput sequencing reveals a stable microbial community during storage. PLoS ONE 7, e46953 (2012).
Wu, G. D. et al. Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags. BMC Microbiol. 10, 206 (2010).
Lauber, C. L., Zhou, N., Gordon, J. I., Knight, R. & Fierer, N. Effect of storage conditions on the assessment of bacterial community structure in soil and human-associated samples. FEMS Microbiol. Lett. 307, 80–86 (2010).
Dominianni, C., Wu, J., Hayes, R. B. & Ahn, J. Comparison of methods for fecal microbiome biospecimen collection. BMC Microbiol. 14, 103 (2014).
Choo, J. M., Leong, L. E. & Rogers, G. B. Sample storage conditions significantly influence faecal microbiome profiles. Sci. Rep. 5, 16350 (2015).
Franzosa, E. A. et al. Relating the metatranscriptome and metagenome of the human gut. Proc. Natl Acad. Sci. USA 111, E2329–E2338 (2014).
Drew, D. A. et al. Fecal microbiome in epidemiologic studies—letter. Cancer Epidemiol. Biomark. Prev. 25, 869 (2016).
Lloyd-Price, J. et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 569, 655–662 (2019).
Human Microbiome Project, C. A framework for human microbiome research. Nature 486, 215–221 (2012).
Dong, T. S. & Gupta, A. Influence of early life, diet, and the environment on the microbiome. Clin. Gastroenterol. Hepatol. 17, 231–242 (2019).
Stewart, C. J. et al. Temporal development of the gut microbiome in early childhood from the TEDDY study. Nature 562, 583–588 (2018).
Jensen, M. A., Ferretti, V., Grossman, R. L. & Staudt, L. M. The NCI Genomic Data Commons as an engine for precision medicine. Blood 130, 453–459 (2017).
Faith, J. J. et al. The long-term stability of the human gut microbiota. Science 341, 1237439 (2013).
Lloyd-Price, J. et al. Strains, functions and dynamics in the expanded Human Microbiome Project. Nature 550, 61–66 (2017).
Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011).
Ianiro, G., Tilg, H. & Gasbarrini, A. Antibiotics as deep modulators of gut microbiota: between good and evil. Gut 65, 1906–1915 (2016).
David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).
Tigchelaar, E. F. et al. Cohort profile: LifeLines DEEP, a prospective, general population cohort study in the northern Netherlands: study design and baseline characteristics. BMJ Open 5, e006772 (2015).
Falony, G. et al. Population-level analysis of gut microbiome variation. Science 352, 560–564 (2016).
Fu, B. C. et al. Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience. Ann. Epidemiol. 26, 373–379 (2016).
Rockett, H. R., Berkey, C. S., Field, A. E. & Colditz, G. A. Cross-sectional measurement of nutrient intake among adolescents in 1996. Prev. Med 33, 27–37 (2001).
Song, S. J. et al. Preservation methods differ in fecal microbiome stability, affecting suitability for field studies. mSystems http://doi.org/10.1128/mSystems.00021-16 (2016).
Anderson, E. L. et al. A robust ambient temperature collection and stabilization strategy: Enabling worldwide functional studies of the human microbiome. Sci. Rep. 6, 31731 (2016).
Luo, T. et al. Effects of specimen collection methodologies and storage conditions on the short-term stability of oral microbiome taxonomy. Appl. Environ. Microbiol. 82, 5519–5529 (2016).

Overview of the Microbiome Among Nurses study (Micro-N) as an example of prospective characterization of the microbiome within cohort studies

Supplementary information

Supplementary Information

推荐阅读