Sign in
GeneticsbioRxiv
Preprint

Precision pharmacological reversal of genotype-specific diet-induced metabolic syndrome in mice informed by transcriptional regulation

Phillip WulfridgeiD, Adam DavidovichiD, Anna C. SalvadoriD, Gabrielle C. Manno, Rakel TryggvadóttiriD, Adrian IdriziiD, M. Nazmul HudaiD, Brian J. BennettiD, L. Garry AdamsiD, Kasper D. HanseniD, David W. ThreadgilliD, Andrew P. FeinbergiD

Abstract

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genomic DNA methylation analyses and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects reveals a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the Farnesoid X receptor pathway, and found that GW4064 exerts genotype-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis, as well as increased inflammatory-related gene expression changes in NOD. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention, and a mouse platform for guiding this approach.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISZhang '19Baker '25Rivas '26Lamanna '26Halder '26Hawro '26
61% semantic matchSystems Biology
Guanglin Zhang, Hyae Ran Byun, Zhe Ying+7 more·Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease·Oct 25, 2019· 29 citations