# Continued follow-up of the Vitamin C and Smoking in Pregnancy (VCSIP) cohorts through the ECHO consortium, focus on Echo-wide protocols, respiratory outcomes, airway function, and epigenetic changes

> **NIH NIH UG3** · OREGON HEALTH & SCIENCE UNIVERSITY · 2024 · $1,112,370

## Abstract

Project Summary
 We are a current Environmental influences on Children's Health Outcomes (ECHO) Cohort awardee (Cohort
Identifier “Maternal Vitamin C Supplementation to Decrease Effects of Smoking during Pregnancy on Infant Lung
Function and Health” [VCSIP]) with expertise in upper and lower airway outcomes and analysis of associated
epigenetic mechanisms. We have been part of the ECHO cohort since its inception in 2016. This application is
to renew our participation in the ECHO Program for an additional seven years (9/2023-8/2030). The overall goal
of this renewal of the ECHO program is to extend the longitudinal follow-up of existing ECHO Cohort participants
and add new pregnant participants. The ECHO Cohort was successfully established by combining data and
biospecimens from multiple maternal-child cohorts such that there is now data and biospecimens from up to
60,000 children and their families. This robust and ongoing data set offers a tremendous opportunity to
collaboratively investigate multiple simultaneous exposures on one or more health outcomes.
 Multiple prenatal factors that can adversely affect lung development and place an infant on a lower lung
function trajectory and increase risk of lung disease. Maternal smoking during pregnancy (MSDP) is a well-
established risk factor for impaired fetal lung development, decreased airway function, and an increased risk for
wheeze and asthma in the offspring. We have shown that supplemental vitamin C (500 mg/day) to pregnant
cigarette smokers significantly improves their offspring's lung function through 5 years of age and decreases the
occurrence of wheeze. We have also demonstrated specific and stable epigenetic changes associated with
MSDP in pathways linked to lung development. The focus of this application are the effects of in utero exposure
to smoking on offspring lung function and respiratory health as modified by in utero exposure to air pollution,
vaping, and/or cannabis as well as the potential modulation by postnatal exposures. In specific aim 1, we will
leverage ECHO Cohort Protocol 3.0 core data elements to characterize the epigenetic signatures in placenta
and offspring associated with MSDP, and examine their additive predictive value relative to additional prenatal
and postnatal exposures. In specific aim 2, we will leverage ECHO cohorts with airway-specialized outcomes
(yearly
exposure
postnatal
spirometry and twice-yearly respiratory questionnaires) to characterize the relationships between fetal
to MSDP on airway function and wheeze during childhood as modified by multi-factorial prenatal and
exposures.We hypothesize that MSDP will significantly affect clinical respiratory outcomes including
wheeze and airway function trajectories up to 21 years of age. We also hypothesize that these effects will be
modified by the multi-factorial exposures that ECHO will be measuring. Given our cohort's excellent track record
during the initial phase of ECHO (2016-present) as outlined in sp...

## Key facts

- **NIH application ID:** 10917310
- **Project number:** 5UG3OD023288-09
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** Cynthia T McEvoy
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,112,370
- **Award type:** 5
- **Project period:** 2016-09-21 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10917310

## Citation

> US National Institutes of Health, RePORTER application 10917310, Continued follow-up of the Vitamin C and Smoking in Pregnancy (VCSIP) cohorts through the ECHO consortium, focus on Echo-wide protocols, respiratory outcomes, airway function, and epigenetic changes (5UG3OD023288-09). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10917310. Licensed CC0.

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