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RNA, Ribosomal, 16S / 16s Rrna Sequencing · Journal article
Gut Microbes · August 4, 2026
Early or partial results. Treat as a signal, not a conclusion.
This observational cohort study of 168 meconium samples found no significant associations between maternal pre-pregnancy BMI, gestational weight gain, or lifestyle factors and overall microbial diversity. Unsupervised clustering identified five distinct meconium microbiota types with different taxonomic profiles, suggesting intrinsic organization independent of the measured maternal variables.
Prospective single-center cohort study. Pregnant women enrolled at Fondazione IRCCS Policlinico San Matteo, Pavia; specific eligibility criteria stated but not detailed in the abstract.. Intervention: Meconium microbiota characterization at delivery. n = 168. Single centre: Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
168 meconium samples analyzed from 200 enrolled pregnant women No significant associations observed between GWG, pre-BMI, or other lifestyle factors and overall microbial diversity Unsupervised learning revealed five distinct meconium microbial clusters with different taxonomic profiles
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These findings suggest that meconium microbiota organization may be driven by factors not captured in standard maternal lifestyle and anthropometric measures. Clinicians should recognize that early microbial community structure may have intrinsic variation independent of modifiable maternal factors, though the functional or health implications of the identified microbiota types remain unknown.
Observational cohort study identifying novel meconium microbiota clusters with no significant associations to maternal lifestyle factors; findings are exploratory and require longitudinal validation.
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These findings suggest that meconium microbiota organization may be driven by factors not captured in standard maternal lifestyle and anthropometric measures. Clinicians should recognize that early microbial community structure may have intrinsic variation independent of modifiable maternal factors, though the functional or health implications of the identified microbiota types remain unknown.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
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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