Novel Metabolic Subtypes in Pregnant Women and Risk of Early Childhood Obesity in Offspring
Year: 2023
Type: article
Study design: Observational Study
Abstract: Importance: The in utero metabolic milieu is associated with offspring adiposity. Standard definitions of maternal obesity (according to prepregnancy body mass index [BMI]) and gestational diabetes (GDM) may not be adequate to capture subtle yet important differences in the intrauterine environment that could be involved in programming. Objectives: To identify maternal metabolic subgroups during pregnancy and to examine associations of subgroup classification with adiposity traits in their children. Design, Setting, and Participants: This cohort study included mother-offspring pairs in the Healthy Start prebirth cohort (enrollment: 2010-2014) recruited from University of Colorado Hospital obstetrics clinics in Aurora, Colorado. Follow-up of women and children is ongoing. Data were analyzed from March to December 2022. Exposures: Metabolic subtypes of pregnant women ascertained by applying k-means clustering on 7 biomarkers and 2 biomarker indices measured at approximately 17 gestational weeks: glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglycerides, free fatty acids (FFA), HDL-C:triglycerides ratio, and tumor necrosis factor α. Main Outcomes and Measures: Offspring birthweight z score and neonatal fat mass percentage (FM%). In childhood at approximately 5 years of age, offspring BMI percentile, FM%, BMI in the 95th percentile or higher, and FM% in the 95th percentile or higher. Results: A total of 1325 pregnant women (mean [SD] age, 27.8 [6.2 years]; 322 [24.3%] Hispanic, 207 non-Hispanic Black [15.6%], and 713 [53.8%] non-Hispanic White), and 727 offspring with anthropometric data measured in childhood (mean [SD] age 4.81 [0.72] years, 48% female) were included. We identified the following 5 maternal metabolic subgroups: reference (438 participants), high HDL-C (355 participants), dyslipidemic-high triglycerides (182 participants), dyslipidemic-high FFA (234 participants), and insulin resistant (IR)-hyperglycemic (116 participants). Compared with the reference subgroup, women in the IR-hyperglycemic and dyslipidemic-high FFA subgroups had offspring with 4.27% (95% CI, 1.94-6.59) and 1.96% (95% CI, 0.45-3.47) greater FM% during childhood, respectively. There was a higher risk of high FM% among offspring of the IR-hyperglycemic (relative risk, 8.7; 95% CI, 2.7-27.8) and dyslipidemic-high FFA (relative risk, 3.4; 95% CI, 1.0-11.3) subgroups; this risk was of greater magnitude compared with prepregnancy obesity alone, GDM alone, or both conditions. Conclusions and Relevance: In this cohort study, an unsupervised clustering approach revealed distinct metabolic subgroups of pregnant women. These subgroups exhibited differences in risk of offspring adiposity in early childhood. Such approaches have the potential to refine understanding of the in utero metabolic milieu, with utility for capturing variation in sociocultural, anthropometric, and biochemical risk factors for offspring adiposity.
Source: JAMA Network Open
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,000
Funders: U.S. Department of Health and Human Services, American Diabetes Association, March of Dimes Foundation, National Institutes of Health, Centers for Disease Control and Prevention, Health Resources and Services Administration, National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Child Health and Human Development, National Center for Advancing Translational Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Colorado Clinical and Translational Sciences Institute
Awards: Characterizing metabolic variability during pregnancy to understand pathways of in-utero overnutrition: an integrative analysis of metabolomics and lifestyle data, Institutional Career Development Core, G4227776088, Environmental influences on Child Health Outcomes - The Colorado ECHO Pediatric Cohort, G7256517903, Exploring the Fetal Origins Hypothesis in Diverse Youth, A multi-‘omics approach to identifying youth at high risk of early-onset type 2 diabetes, Colorado Nutrition Obesity Research Center, Health AI and Data Science in Cardiovascular and Pulmonary Disease: Application and Bioethics (HARP-BIO), Environmental influences on Child Health Outcomes - The Colorado ECHO Pediatric Cohort
OpenAlex ID: W4362524068
