Exploring Fecal Calprotectin Levels, Maternal and Infant Microbiota, Infant Health, Nutrition, and Adverse Pregnancy Outcomes With Patient With Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic gastrointestinal condition that often presents during reproductive years, with approximately 25% of IBD patients having children after diagnosis. IBD during pregnancy can negatively impact infant health, as infants born to parents with IBD frequently exhibit higher fecal calprotectin (FCP) levels, a marker of gastrointestinal inflammation. Elevated FCP levels have been associated with increased risks of asthma, eczema, and IBD later in life. The purpose of this study is to examine how the maternal gut microbiome, diet, and breastmilk composition influence infant FCP levels and to identify factors that may guide dietary interventions to improve infant health outcomes. Specifically, the study aims to: (1) identify pregnancy-related maternal gut microbiota and dietary factors linked to elevated infant FCP levels, (2) determine infant gut microbiota and dietary factors associated with high FCP levels, (3) validate a supervised machine learning model capable of predicting high FCP levels in infants at 1 year of age using microbiota and dietary data, and (4) characterize human milk oligosaccharide (HMO) composition in breastmilk of mothers with and without IBD and its association with infant gut microbiota and FCP levels. This prospective study will evaluate changes in microbiota and dietary habits during and after pregnancy among maternal IBD patients (with active or quiescent disease) and non-IBD controls and their infants. Participants will be recruited during pregnancy (1st, 2nd, and early 3rd trimesters), and data and samples will be collected at four timepoints: 3rd trimester (week 34-35), 2 weeks postpartum, 3 months postpartum, and 1 year postpartum. Collected data will include 3-day dietary recalls, maternal and infant stool samples (for microbiota composition and FCP levels), optional breastmilk and breast skin swabs, vaginal swabs, and pregnancy and infant outcomes. These data will be integrated into a machine learning model to predict high infant FCP levels at 1 year, considering known covariates and factors identified in this study. The primary outcome is to determine the association between maternal gut microbiota composition-specifically the abundance of anti-inflammatory bacteria such as Faecalibacterium and Bifidobacterium-during the third trimester and early postpartum period, and infant FCP levels at 3 months and 1 year, accounting for maternal adherence to Mediterranean dietary patterns. Secondary outcomes include developing and validating a machine learning model for predicting elevated infant FCP at 1 year, characterizing and comparing HMO profiles between IBD and non-IBD mothers and their associations with infant gut microbiota and FCP levels, comparing pregnancy outcomes between mothers with ulcerative colitis, Crohn's disease, and non-IBD controls-including the impact of IBD therapy and mode of delivery-and examining the associations between maternal diet, microbiota composition (gut, skin, and vaginal), and pregnancy and infant outcomes across all study timepoints.