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[Preprint]. 2024 May 30:rs.3.rs-4427250.
doi: 10.21203/rs.3.rs-4427250/v1.

Genomic Insights into Gestational Weight Gain: Uncovering Tissue-Specific Mechanisms and Pathways

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Genomic Insights into Gestational Weight Gain: Uncovering Tissue-Specific Mechanisms and Pathways

Elizabeth Jasper et al. Res Sq. .

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Abstract

Increasing gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and their children. The Early Growth Genetics (EGG) Consortium identified previously genetic variants that could contribute to early, late, and total GWG from fetal and maternal genomes. However, the biologic mechanisms and tissue-Specificity of these variants in GWG is unknown. We evaluated the association between genetically predicted gene expression in five relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) from GTEx (v7) and fetal (placenta) tissues and early, late, and total GWG using S-PrediXcan. We tested enrichment of pre-defined biological pathways for nominally (P < 0.05) significant associations using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After multiple testing correction, we did not find significant associations between maternal and fetal gene expression and early, late, or total GWG. There was significant enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, among nominally significant genes from the maternal analyses (false discovery rate p-values: 0.016 to 9.37×10). Enriched biological pathways varied across pregnancy. Though additional research is necessary, these results indicate that diverse biological pathways are likely to impact GWG, with their influence varying by tissue and weeks of gestation.

Keywords: S-PrediXcan; gene expression; gestational weight gain; placenta.

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Conflict of interest statement

Competing Interests The authors report no conflict of interest.

Figures

Figure 1
Figure 1
Miami Plot for Analyses Using Maternal Genotypes The bottom of the graphic is a Manhattan plot which displays significant SNPs from GWAS. The top of the graphic is the results from S-PrediXcan, with symbols now representing entire genes and their genetically determined expression levels. The x-axis are chromosomes. The y-axis is log and negative log p-values from the GWAS and S-PrediXcan analyses. Colors correspond to Specific tissues and definitions of gestational weight gain.
Figure 2
Figure 2
Miami Plot for Analyses Using Fetal Genotypes The bottom of the graphic is a Manhattan plot which displays significant SNPs from GWAS. The top of the graphic is the results from S-PrediXcan, with symbols now representing entire genes and their genetically determined expression levels. The x-axis are chromosomes. The y-axis is log and negative log p-values from the GWAS and S-PrediXcan analyses. Colors correspond to Specific tissues and definitions of gestational weight gain.

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