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Maternal influences on infant gut microbiome and health

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Why This Matters

This study highlights the critical influence of maternal factors on the development of the infant gut microbiome, which has significant implications for early health interventions and disease prevention. Understanding these maternal-infant interactions can guide personalized healthcare strategies and improve long-term health outcomes for children. The extensive data collection and longitudinal approach provide valuable insights into how early-life factors shape health trajectories.

Key Takeaways

Study design

The samples for this study were obtained from the Lifelines NEXT (LLNEXT) cohort, a birth cohort designed to study the effects of intrinsic and extrinsic predictors of health and disease in a four-generation design23. LLNEXT is embedded within the Lifelines (LL) cohort study, a prospective three-generation population-based cohort study recording the health and health-related aspects of 167,729 individuals living in the northern Netherlands56,57. From 2016 to 2023, 1,452 pregnant women were recruited for LLNEXT, along with their partners and infants, and monitored up to at least 1 year after birth. Several biomaterials, including faeces, breast milk and vaginal swabs, were collected from participants. Data on medical, social, lifestyle and environmental factors were collected through questionnaires at 14 different timepoints and through connected devices. The LLNEXT study was approved by the Ethics Committee of the University Medical Center Groningen (UMCG), document number METC UMCG METc2015/600. Written informed consent forms were signed by the participants or their parents/legal guardians. The present study included the first 714 mother–infant pairs recruited between 2016 and 2019.

Predictors

Extensive predictor data were collected for all participants through questionnaires and medical records from the LLNEXT and LL cohort studies (if the parents were part of LL). Information from several sources were combined to ensure completeness. Data regarding predictors included information from mothers from before pregnancy, during pregnancy, at delivery and after pregnancy. Information from infants were obtained during birth and over the first year after birth. Predictors were investigated both cross-sectionally (for example, static predictors such as delivery mode; n = 316 predictors; Supplementary Table 1) and longitudinally (for example, dynamic predictors such as feeding mode; n = 158 predictors; Supplementary Table 2).

Pre-pregnancy predictors

Maternal pre-pregnancy BMI (kg m−2) data were obtained from the LL cohort study and complemented with medical records of LLNEXT to obtain BMI measurements for mothers up to 8 years before conception.

Maternal pre-pregnancy smoking history was classified as ‘yes’ if the mother reported smoking consistently for at least one full year at any point in her life. This period of smoking in the woman in LLNEXT occurred between the ages of 10 and 29, with a median age of 15 years.

Pregnancy and delivery predictors

Maternal education and income were reported at week 18 of pregnancy (P18). Mother education was categorized as follows: elementary to lower-secondary education (including incomplete and completed special primary education, primary or pre-vocational education and general secondary education), upper-secondary education (including vocational or secondary vocational education and higher general and pre-university education); or tertiary education (including higher professional education and university)58. Maternal income per month was derived using data from the Dutch Social and Cultural Plan59 and categorized as low (<€800–1,800), middle (€1,800–2,400) and high (>€2,400) income. Questionnaires related to maternal reproductive and dental health, as well as substance use were also completed at P18.

Maternal food preference and avoidance questionnaires, comprising 94 items, were completed at P12 and P32 and were developed by Wageningen University & Research (WUR). Food preference and avoidance items were evaluated using a Likert scale ranging from 0 (strong aversion) to 10 (strong preference). Given that these items were highly correlated (r > 0.8) at both timepoints, the questionnaires were combined, and missing data were imputed using a linear regression approach of one timepoint to another.

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