2021
DOI: 10.1038/s41596-021-00519-z
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Overview of the Microbiome Among Nurses study (Micro-N) as an example of prospective characterization of the microbiome within cohort studies

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Cited by 8 publications
(5 citation statements)
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“…A total of 837 NHS and 880 HPFS participants were selected and invited into the study. The stool collection protocol in our study followed that of the Micro‐N study, designed and implemented by the Harvard Chan Microbiome Collection Core (HCMCC), as previously described 46 . Briefly, an invitation letter was mailed to eligible NHS and HPFS participants identified as PPS, PD, constipated controls, and healthy controls.…”
Section: Methodsmentioning
confidence: 99%
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“…A total of 837 NHS and 880 HPFS participants were selected and invited into the study. The stool collection protocol in our study followed that of the Micro‐N study, designed and implemented by the Harvard Chan Microbiome Collection Core (HCMCC), as previously described 46 . Briefly, an invitation letter was mailed to eligible NHS and HPFS participants identified as PPS, PD, constipated controls, and healthy controls.…”
Section: Methodsmentioning
confidence: 99%
“…At the time of stool collection, participants completed a 2‐page supplemental stool questionnaire that included questions regarding recent diet, major lifestyle factors, medication (including laxative and stool softener use), and medical history, as well as stool consistency and bowel movement pattern. The supplemental questionnaire used in this study was developed for the Micro‐N study and has been described in detail and published previously 46 …”
Section: Methodsmentioning
confidence: 99%
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“…The field is currently lacking large, accessible datasets focused on in vivo drug-microbiome interactions. At present, high throughput ex vivo studies (Javdan et al, 2020;Zimmermann et al, 2019a) or general observation microbiome studies (Everett et al, 2021;Huttenhower et al, 2012;Proctor et al, 2019) are the best sources of data for ML. A few databases have also been built to collect disease-microbiome or drug-microbiome interactions in a single place (Janssens et al, 2018;Sun et al, 2018).…”
Section: The Power Of Predictionmentioning
confidence: 99%