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Metabolic subgroups of Diversity Outbred mice show distinct phenotypic and transcriptomic signatures of obesity and insulin resistance

ABSTRACT: Clinicians and researchers are turning towards precision medicine to treat and prevent obesity and diabetes, given the known contributions of genetics to these metabolic diseases and the wide variability reported in response to treatments. Animal models that incorporate the genetic diversity present in the human population may help discover novel genetic contributors to metabolic disease and test potential treatments. We characterized the Diversity Outbred (DO) mouse population as a model in which to study interindividual variability in metabolic disease and investigated the presence of metabolic subgroups within the population. Glucose metabolism was assessed in male Diversity Outbred (DO) mice after consumption of a high-fat diet for 14 weeks and profiled transcriptomic changes in liver, adipose, and muscle—key tissues involved in glucose homeostasis. To identify metabolic subgroups, we applied classification and regression tree analyses to metabolic phenotype measures as well as transcriptomic data. These findings suggest that DO mice exhibit a diversity of metabolic phenotypes that can be segmented into subgroups using a machine learning approach. The metabolic subgroups observed in the DO may be a useful for probing the phenotypic variability in metabolic disease observed in humans.

ORGANISM(S): Mus musculus

PROVIDER: GSE194145 | GEO | 2022/12/30

REPOSITORIES: GEO

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Project description:Mycobacterium tuberculosis infects two billion people across the globe, and results in 8-9 million new tuberculosis (TB) cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. Here, we investigate the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using immune and inflammatory mediators; and clinical, microbiological, and granuloma correlates of disease identified five new loci on mouse chromosomes 1, 2, 4, 16; and three known loci on chromosomes 3 and 17. Further, multiple positively correlated traits shared loci on chromosomes 1, 16, and 17 and had similar patterns of allele effects, suggesting these loci contain critical genetic regulators of inflammatory responses to M. tuberculosis. To narrow the list of candidate genes, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks to generate scores representing functional relationships. The scores were used to rank candidates for each mapped trait, resulting in 11 candidate genes: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Although all candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling, and all contain single nucleotide polymorphisms (SNPs), SNPs in only four genes (S100a8, Itgb5, Fstl1, Zfp318) are predicted to have deleterious effects on protein functions. We performed methodological and candidate validations to (i) assess biological relevance of predicted allele effects by showing that Diversity Outbred mice carrying PWH/PhJ alleles at the H-2 locus on chromosome 17 QTL have shorter survival; (ii) confirm accuracy of predicted allele effects by quantifying S100A8 protein in inbred founder strains; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this body of work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and functionally relevant gene candidates that may be major regulators of complex host-pathogens interactions contributing to granuloma necrosis and acute inflammation in pulmonary TB.

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Metabolic subgroups of Diversity Outbred mice show distinct phenotypic and transcriptomic signatures of obesity and insulin resistance

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