The goal of this prospective longitudinal cohort study is to examine how the human microbiome of pregnant women-including bacteria and fungi in the gastrointestinal tract, vaginal canal, skin, and breastmilk-may influence infant gut inflammation, measured by fecal calprotectin (FCP) levels, and to identify factors that could inform dietary interventions to improve infant health outcomes. Specifically, the study aims to determine which maternal gut microbiome characteristics and dietary patterns during pregnancy are associated with elevated FCP levels in infants, and which infant gut microbiota compositions and dietary factors are linked to high FCP levels. Researchers will compare microbiome signatures and dietary factors in pregnant women and their infants with active or inactive IBD, as well as non-IBD controls, to identify microbial patterns that may predict infant gut inflammation. Participants will provide fecal samples at all study timepoints, one vaginal swab during the third trimester of pregnancy, and optional breastmilk and breast skin swab samples. They will also complete 3-day diet recalls using a smartphone app and participate in a longitudinal follow-up over 12 months after birth to monitor dietary patterns, microbiome profiles, and gut inflammation in both mother and infant.
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.
Study Type
OBSERVATIONAL
Enrollment
80
BC Children's Hospital Research Institute
Vancouver, British Columbia, Canada
NOT_YET_RECRUITINGBC Children's Hospital Research Institute
Vancouver, British Columbia, Canada
RECRUITINGCorrelation between maternal gut microbiota during pregnancy (third trimester) and early postpartum period (2 weeks, 3 months, and 1 year) and infant FCP levels at 3 months and 1 year of age, accounting for maternal adherence to Mediterranean diet.
FCP, a marker of intestinal inflammation, will be quantified in maternal stool samples collected during the third trimester of pregnancy and the early postpartum period (2 weeks, 3 months, and 1 year postpartum), as well as in infant stool samples collected at 3 months and 1 year of age, using enzyme-linked immunosorbent assay (ELISA). Elevated infant FCP is defined as \>400 µg/g. Maternal gut microbiota composition and diversity will be characterized using long-read Oxford Nanopore 16S rRNA sequencing, and microbial metabolites will be quantified using gas chromatography-mass spectrometry (GC-MS). Maternal dietary intake during the third trimester and postpartum period will be assessed using 3-day dietary records completed via the RXFood mobile application. Adherence to the Mediterranean diet will be scored using the Mediterranean Diet Score (MDS; range 0-7), with scores of 4-7 indicating high Mediterranean diet adherence.
Time frame: 24 months
Develop and validate a machine learning model for predicting elevated infant FCP levels at 1 year of age using maternal gut microbiota composition and dietary patterns as predictive features.
This multi-modal integrative supervised machine learning (sPLS-DA33; http://mixomics.org/) will integrate infant and pregnancy gut microbiota and dietary features to predict elevated infant FCP levels at 1 year. These features will be used to train predictive models with Random Forest Classifier and Artificial neural networks (ANN) providing complementary approaches for robust prediction. Cross-validation (20 × 5-fold) will optimize model performance and generalizability.
Time frame: 24 months
Characterize and compare HMO profiles between mothers with and without IBD, and determine their associations with the infant gut microbiota composition and the infant FCP levels at 3 months and 1 year of age.
Human milk oligosaccharide (HMO) composition will be characterized and compared between mothers with IBD and healthy controls using breastmilk samples collected postpartum. Participants will be asked to perform a full breast expression (\~5-10 mL) and the breastmilk will be alliquot and stored at -80 degrees freezer. Breastmilk composition, specifically HMO, will be analyzed using ultra-performance liquid chromatography with fluorescence (UPLC-FL) in Dr. Lars Bode laboratory from the University of California San Diego. The study will identify specific HMO profiles and assess their associations with infant gut microbiota composition and fecal calprotectin (FCP) levels at 3 months and 1 year of age. This analysis will help determine whether maternal IBD status could influence HMO composition and whether specific HMO profiles impact infant gut health and inflammation markers, potentially informing nutritional strategies to support optimal infant gastrointestinal development.
Time frame: 24 months
Compare pregnancy outcomes between mothers with ulcerative colitis or Crohn's disease and those without IBD.
Pregnancy outcomes will be collected via chart review, and via a questionnaire completed by the participant to gather data on health outcomes. This study will compare pregnancy outcomes between mothers with ulcerative colitis (UC) or Crohn's disease (CD) and those without IBD. The analysis will examine the impact of IBD therapies, including steroids and advanced biologics, on maternal and infant health outcomes. Additionally, the study will investigate the relationship between mode of delivery (vaginal versus cesarean section) and outcomes for both mothers and infants. This comparison will provide insights into how IBD disease management and delivery methods influence pregnancy-related health outcomes, contributing to evidence-based care recommendations for pregnant individuals with IBD.
Time frame: 24 months
Correlation between maternal dietary patterns (macro and micronutrients) and maternal microbiota composition (gut, skin, and vaginal) and maternal and infant clinical outcomes, including pregnancy and postpartum complications.
Maternal dietary patterns will be assessed using 3-day food diaries collected via RxFood, an AI-enabled dietary assessment application. Maternal microbiota composition (gut, breast skin, and vaginal) will be analyzed in relation to pregnancy and postpartum complications assessed during the third trimester and at 2 weeks, 3 months, and 1 year postpartum. Infant clinical outcomes will be assessed at birth, 2 weeks, 3 months, and 1 year of age using participant-completed questionnaires and review of relevant medical records.
Time frame: 24 months
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.