Premature Infant Gut Microbiome relationships with childhood behavioral scales: preliminary insights - Ozorio Dutra, Samia Valeria; Sarkar, Anujit; Yoo, Ji Youn; Shaffer-Hudkins, Emily; Groer, Maureen (Frontiers in Nutrition, 2024)
Introduction:Very Low Birth Weight (VLBW) infants, born weighing less than 1500 grams, are at risk for both gut dysbiosis and later neuropsychological developmental deficits. Behavioral effects, while related to neurodevelopment, are often more subtle and difficult to measure. The extent of later neurobehavioral consequences associated with such microbial dysbiosis has yet to be determined. We explored associations between the infants' gut microbiome and early childhood behavior at 4 years of age and identified the bacterial taxa through a multivariate analysis by linear models. Methods: Parents completed the Childhood Behavioral Checklist (CBCL) focused on different DSM diagnostic categories: affective, anxiety, pervasive developmental, attention deficit/hyperactivity, and oppositional defiant. All the CBCL scores were corrected for gender, delivery method, gestational age, infant birth weight, occurrence of sepsis, and days on antibiotics prior statistical analyses. Canonical correlation analysis (CCA) was performed to determine the relationship between early life gut microbiome and the adjusted CBCL scores. The association of bacterial Amplicon sequence Variants (ASVs) to the CBCL scores were tested with multivariate analysis by linear models (MaAsLin). Results: Nineteen children who were previously born with very low birth weight and studied while hospitalized in the Neonatal Intensive Care Unit (NICU) were included in this study. Statistically significant associations were observed between early life gut bacteria such as Veillonella dispar, Enterococcus, Escherichia coli, and Rumincococcus to later behavior at 4 years. No significant association could be observed with early-life gut microbiome alpha diversity and behavioral measures at 4 years. Discussion: These preliminary observational data provide insight