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Household paired design reduces variance and increases power in multi-city gut microbiome study in multiple sclerosis

Xiaoyuan Zhou, Sneha Singh, Ryan Baumann, Patrick Barba, James Landefeld, Patrizia Casaccia, Ilana Katz Sand, Zongqi Xia, Howard Weiner, Tanuja Chitnis, Siddharthan Chandran, Peter Connick, David Otaegui, Tamara Castillo-Trivino, Stacy J. Caillier, Adam Santaniello, Gail Ackermann, Greg Humphrey, Laura Negrotto, Mauricio Farez, Reinhard Hohlfeld, Anne-Katrin Probstel, Xiaoming Jia, Jennifer Graves, Amit Bar-or, Jorge R. Oksenberg, Jeffery Gelfand, Michael R. Wilson, Elizabeth Crabtree, Scott S. Zamvil, Jorge Correale, Bruce A. C. Cree, Stephen L. Hauser, Rob Knight, Sergio E. Baranzini

MULTIPLE SCLEROSIS JOURNAL(2021)

Cited 21|Views15
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Abstract
Background: Evidence for a role of human gut microbiota in multiple sclerosis (MS) risk is mounting, yet large variability is seen across studies. This is, in part, due to the lack of standardization of study protocols, sample collection methods, and sequencing approaches. Objective: This study aims to address the effect of a household experimental design, sample collection, and sequencing approaches in a gut microbiome study in MS subjects from a multi-city study population. Methods: We analyzed 128 MS patient and cohabiting healthy control pairs from the International MS Microbiome Study (iMSMS). A total of 1005 snap-frozen or desiccated Q-tip stool samples were collected and evaluated using 16S and shallow whole-metagenome shotgun sequencing. Results: The intra-individual variance observed by different collection strategies was dramatically lower than inter-individual variance. Shallow shotgun highly correlated with 16S sequencing. Participant house and recruitment site accounted for the two largest sources of microbial variance, while higher microbial similarity was seen in household-matched participants as hypothesized. A significant proportion of the variance in dietary intake was also dominated by geographic distance. Conclusion: A household pair study largely overcomes common inherent limitations and increases statistical power in population-based microbiome studies.
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Key words
Multiple sclerosis,gut microbiome,16S rRNA sequencing,shallow whole-metagenome sequencing,diet
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