Multiomics analysis of umbilical cord hematopoietic stem cells from a multiethnic cohort of Hawaii reveals the intergenerational effect of maternal prepregnancy obesity and risks for cancers.
Yuheng Du, Paula A Benny, Yuchen Shao, Ryan J Schlueter, Alexandra Gurary, Annette Lum-Jones, Cameron B Lassiter, Fadhl M AlAkwaa, Maarit Tiirikainen, Dena Towner, W Steven Ward, Lana X Garmire
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引用次数: 0
Abstract
Background: Maternal obesity is a health concern that may predispose newborns to a high risk of medical problems later in life. To understand the intergenerational effect of maternal obesity, we hypothesized that the maternal obesity effect is mediated by epigenetic changes in the CD34+/CD38-/Lin- hematopoietic stem cells (uHSCs) in the offspring. To investigate this, we conducted a DNA methylation centric multiomics study. We measured DNA methylation and gene expression of the CD34+/CD38-/Lin- uHSCs and metabolomics of the cord blood, all from a multiethnic cohort from Kapiolani Medical Center for Women and Children in Honolulu, Hawaii (n=72, collected between 2016 and 2018).
Results: Differential methylation analysis unveiled a global hypermethylation pattern in the maternal prepregnancy obese group (BH adjusted P < 0.05), after adjusting for major clinical confounders. KEGG pathway enrichment, WGCNA, and PPI analyses revealed that hypermethylated CpG sites were involved in critical biological processes, including cell cycle, protein synthesis, immune signaling, and lipid metabolism. Utilizing Shannon entropy on uHSCs methylation, we discerned notably higher quiescence of uHSCs impacted by maternal obesity. Additionally, the integration of multiomics data-including methylation, gene expression, and metabolomics-provided further evidence of dysfunctions in adipogenesis, erythropoietin production, cell differentiation, and DNA repair, aligning with the findings at the epigenetic level. Furthermore, we trained a random forest classifier using the CpG sites in the genes of the top pathways associated with maternal obesity, and applied it to predict cancer versus adjacent normal sample labels in 14 Cancer Genome Atlas (TCGA) cancer types. Five of 14 cancers showed balanced accuracy of 0.6 or higher: LUSC (0.87), PAAD (0.83), KIRC (0.71), KIRP (0.63) and BRCA (0.60).
Conclusions: This study revealed the significant correlation between prepregnancy maternal obesity and multiomics-level molecular changes in the uHSCs of offspring, particularly at the DNA methylation level. These maternal-obesity-associated epigenetic markers in uHSCs may contribute to increased risks in certain cancers of the offspring. Larger and multicenter cohort validation studies are warranted to follow up the current single-site study.
期刊介绍:
GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.