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. 2024;2(1):42.
doi: 10.1038/s44294-024-00035-x. Epub 2024 Dec 6.

Genomic insights into gestational weight gain uncover tissue-specific mechanisms and pathways

Elizabeth A Jasper  1   2   3 , Jacklyn N Hellwege  4   5   6 , Catherine A Greene  1   3 , Todd L Edwards  3   4   5   7 , Digna R Velez Edwards  1   3   4
Affiliations

Genomic insights into gestational weight gain uncover tissue-specific mechanisms and pathways

Elizabeth A Jasper et al. NPJ Womens Health. 2024.

Abstract

Gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and offspring. The Early Growth Genetics Consortium previously identified genetic variants contributing to GWG from fetal and maternal genomes. However, their biologic mechanisms and tissue-specificity are unknown. We evaluated the association between genetically predicted gene expression in relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) tissues from GTEx (v7) and fetal (placenta) tissue and early, late, and total GWG using S-PrediXcan. We tested for pathway enrichment using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After Bonferroni correction, we found no associations between maternal or fetal gene expression and GWG. Among nominally significant (P < 0.05) maternal genes, there was enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, that varied across pregnancy. These results indicate the likely influence of diverse pathways, varying by tissue and weeks of gestation, on GWG.

Keywords: Diseases; Reproductive biology.

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Conflict of interest statement

Competing interestsThe authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Miami plot for analyses using maternal genotypes.
The bottom of the graphic is a Manhattan plot which displays significant SNPs from the previous GWAS. The top of the graphic is the results from S-PrediXcan, with symbols now corresponding to genetically predicted expression levels of genes and the significance of their association with gestational weight gain. The x-axis are chromosomes. The y-axis is log and negative log p-values for the GWAS and S-PrediXcan analyses. Colors correspond to specific tissues and definitions of gestational weight gain.
Fig. 2
Fig. 2. Miami plot for analyses using fetal genotypes.
The bottom of the graphic is a Manhattan plot which displays significant SNPs from the previous GWAS. The top of the graphic is the results from S-PrediXcan, with symbols now corresponding to genetically predicted expression levels of genes and the significance of their association with gestational weight gain. The x-axis are chromosomes. The y-axis is log and negative log p-values for the GWAS and S-PrediXcan analyses. Colors correspond to specific definitions of gestational weight gain.
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