Introduction: Early gut microbiota development plays an important role in lifelong human health, and meconium offers a unique matrix to understand prenatal microbial exposures. This study from the LIMIT cohort aimed at investigating associations between maternal pre-pregnancy body mass index (pre-BMI) and gestational weight gain (GWG), as well as other maternal lifestyle and environmental factors, with the structure of meconium microbiota at delivery. Methods: Two hundred pregnant women were enrolled during the pre-hospital care before birth at Fondazione IRCCS Policlinico San Matteo (Pavia), according to the inclusion/exclusion criteria. Mothers were grouped based on their GWG gain category according to the IOM guidelines. 168 meconium samples were analyzed using a targeted long-reads sequence approach. Bacterial 16S rRNA (V1-V8) amplicons were sequenced using the Oxford Nanopore PromethION platform. Supervised analyses assessed associations between maternal variables and bacterial diversity, while an unsupervised learning approach based on the Partitioning Around Medoids (PAM) clustering algorithm was applied to identify specific microbial clusters unrelated to the cohort's metadata. Results: No significant associations were observed between GWG, pre-BMI or other lifestyle factors and overall microbial diversity. Unsupervised learning revealed five distinct meconium microbial clusters, i.e. "microbiota-types", related to different taxonomic profiles, determined by the variations in specific bacterial species. Conclusion: No significant influence of the studied variables was observed on meconium microbiota. However, the meconium microbial communities appear to organize into enterotype-like structures, highlighting the need for longitudinal studies to identify key determinants of early colonization.

Early-life microbiota in the LIMIT cohort: unveiling meconium microbiota types beyond maternal lifestyle

El Masri, Dana;Loperfido, Federica
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Bianco, Irene;Maccarini, Beatrice;Sottotetti, Francesca;Loddo, Nicolò;Ghirardello, Stefano;Monti, Maria Cristina;Alemayohu, Mulubirhan Assefa;Cena, Hellas;De Giuseppe, Rachele
2026-01-01

Abstract

Introduction: Early gut microbiota development plays an important role in lifelong human health, and meconium offers a unique matrix to understand prenatal microbial exposures. This study from the LIMIT cohort aimed at investigating associations between maternal pre-pregnancy body mass index (pre-BMI) and gestational weight gain (GWG), as well as other maternal lifestyle and environmental factors, with the structure of meconium microbiota at delivery. Methods: Two hundred pregnant women were enrolled during the pre-hospital care before birth at Fondazione IRCCS Policlinico San Matteo (Pavia), according to the inclusion/exclusion criteria. Mothers were grouped based on their GWG gain category according to the IOM guidelines. 168 meconium samples were analyzed using a targeted long-reads sequence approach. Bacterial 16S rRNA (V1-V8) amplicons were sequenced using the Oxford Nanopore PromethION platform. Supervised analyses assessed associations between maternal variables and bacterial diversity, while an unsupervised learning approach based on the Partitioning Around Medoids (PAM) clustering algorithm was applied to identify specific microbial clusters unrelated to the cohort's metadata. Results: No significant associations were observed between GWG, pre-BMI or other lifestyle factors and overall microbial diversity. Unsupervised learning revealed five distinct meconium microbial clusters, i.e. "microbiota-types", related to different taxonomic profiles, determined by the variations in specific bacterial species. Conclusion: No significant influence of the studied variables was observed on meconium microbiota. However, the meconium microbial communities appear to organize into enterotype-like structures, highlighting the need for longitudinal studies to identify key determinants of early colonization.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1558255
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