{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T01:44:58Z","timestamp":1785548698686,"version":"3.56.0"},"reference-count":48,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA105417"],"award-info":[{"award-number":["CA105417"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>Genetics play an important role in the development of metabolic diseases. However, the relative influence of genetic variation on metabolism is not well defined, particularly in tissues, where metabolic dysfunction that leads to disease occurs. We used inbred strains of laboratory mice to evaluate the impact of genetic variation on the metabolomes of tissues that play central roles in metabolic diseases. We chose a set of four common inbred strains that have different levels of susceptibility to obesity, insulin resistance, and other common metabolic disorders. At the ages used, and under standard husbandry conditions, these lines are not overtly diseased. Using global metabolomics profiling, we evaluated water-soluble metabolites in liver, skeletal muscle, and adipose from A\/J, C57BL\/6J, FVB\/NJ, and NOD\/ShiLtJ mice fed a standard mouse chow diet. We included both males and females to assess the relative influence of strain, sex, and strain-by-sex interactions on metabolomes. The mice were also phenotyped for systems level traits related to metabolism and energy expenditure. Strain explained more variation in the metabolite profile than did sex or its interaction with strain across each of the tissues, especially in liver. Purine and pyrimidine metabolism and pathways related to amino acid metabolism were identified as pathways that discriminated strains across all three tissues. Based on the results from ANOVA, sex and sex-by-strain interaction had modest influence on metabolomes relative to strain, suggesting that the tissue metabolome remains largely stable across sexes consuming the same diet. Our data indicate that genetic variation exerts a fundamental influence on tissue metabolism.<\/jats:p>","DOI":"10.3390\/metabo12040337","type":"journal-article","created":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T05:13:08Z","timestamp":1649481188000},"page":"337","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Independent and Interactive Effects of Genetic Background and Sex on Tissue Metabolomes of Adipose, Skeletal Muscle, and Liver in Mice"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9720-0038","authenticated-orcid":false,"given":"Ann E.","family":"Wells","sequence":"first","affiliation":[{"name":"UT-ORNL Graduate School of Genome Science and Technology, University of Tennessee-Knoxville, Knoxville, TN 37996, USA"},{"name":"The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William T.","family":"Barrington","sequence":"additional","affiliation":[{"name":"Department of Molecular and Cellular Medicine, Texas A&M Health Science Center, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Dearth","sequence":"additional","affiliation":[{"name":"Department of Chemistry, University of Tennessee-Knoxville, Knoxville, TN 37996, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7975-247X","authenticated-orcid":false,"given":"Nikhil","family":"Milind","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2834-8186","authenticated-orcid":false,"given":"Gregory W.","family":"Carter","sequence":"additional","affiliation":[{"name":"The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David W.","family":"Threadgill","sequence":"additional","affiliation":[{"name":"Department of Molecular and Cellular Medicine, Texas A&M Health Science Center, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shawn R.","family":"Campagna","sequence":"additional","affiliation":[{"name":"Department of Chemistry, University of Tennessee-Knoxville, Knoxville, TN 37996, USA"},{"name":"Biological and Small Molecule Mass Spectrometry Core, University of Tennessee-Knoxville, Knoxville, TN 37996, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1923-9110","authenticated-orcid":false,"given":"Brynn H.","family":"Voy","sequence":"additional","affiliation":[{"name":"UT-ORNL Graduate School of Genome Science and Technology, University of Tennessee-Knoxville, Knoxville, TN 37996, USA"},{"name":"Department of Animal Science, University of Tennessee-Knoxville, Knoxville, TN 37996, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"371","DOI":"10.3945\/ajcn.116.130252","article-title":"Genetic and environmental effects on body mass index from infancy to the onset of adulthood: An individual-based pooled analysis of 45 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) study","volume":"104","author":"Silventoinen","year":"2016","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"R93","DOI":"10.1093\/hmg\/ddv263","article-title":"Genetics of human metabolism: An update","volume":"24","author":"Raffler","year":"2015","journal-title":"Hum. Mol. Genet."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1038\/s41467-019-13770-6","article-title":"Heritability estimates for 361 blood metabolites across 40 genome-wide association studies","volume":"11","author":"Hagenbeek","year":"2020","journal-title":"Nat Commun."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1038\/ng.3809","article-title":"Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites","volume":"49","author":"Long","year":"2017","journal-title":"Nat. Genet."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1186\/s13059-021-02413-z","article-title":"Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease","volume":"22","author":"Chu","year":"2021","journal-title":"Genome Biol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1038\/nrd1157","article-title":"Opinion: Understanding \u2018global\u2019 systems biology: Metabonomics and the continuum of metabolism","volume":"2","author":"Nicholson","year":"2003","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1016\/j.cell.2015.11.001","article-title":"Personalized Nutrition by Prediction of Glycemic Responses","volume":"163","author":"Zeevi","year":"2015","journal-title":"Cell"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1958","DOI":"10.2337\/diabetes.52.8.1958","article-title":"Variation in Type 2 Diabetes-Related Traits in Mouse Strains Susceptible to Diet-Induced Obesity","volume":"52","author":"Rossmeisl","year":"2003","journal-title":"Diabetes"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1016\/0026-0495(95)90123-X","article-title":"Differential effects of fat and sucrose on the development of obesity and diabetes in C57BL\/6J and A\/J mice","volume":"44","author":"Surwit","year":"1995","journal-title":"Metabolism"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"R1025","DOI":"10.1152\/ajpregu.1992.262.6.R1025","article-title":"Dietary obesity in nine inbred mouse strains","volume":"262","author":"West","year":"1992","journal-title":"Am. J. Physiol. Integr. Comp. Physiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3258","DOI":"10.1210\/en.2004-0219","article-title":"Genetic Background (C57BL\/6J Versus FVB\/N) Strongly Influences the Severity of Diabetes and Insulin Resistance in ob\/ob Mice","volume":"145","author":"Haluzik","year":"2004","journal-title":"Endocrinology"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Madsen, R., Banday, V., Moritz, T., Trygg, J., and Lejon, K. (2012). Altered Metabolic Signature in Pre-Diabetic NOD Mice. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0035445"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/S0166-4328(02)00200-0","article-title":"Behavioral and physiological mouse assays for anxiety: A survey in nine mouse strains","volume":"136","author":"Bouwknecht","year":"2002","journal-title":"Behav. Brain Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.1093\/carcin\/14.11.2353","article-title":"FVB\/N mice: An inbred strain sensitive to the chemical induction of squamous cell carcinomas in the skin","volume":"14","author":"Hennings","year":"1993","journal-title":"Carcinogenesis"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1101\/gr.5941007","article-title":"mtDNA phylogeny and evolution of laboratory mouse strains","volume":"17","author":"Goios","year":"2007","journal-title":"Genome Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/S0014-5793(00)02147-5","article-title":"An NMR-based metabonomic approach to investigate the biochemical consequences of genetic strain differences: Application to the C57BL10J and Alpk:ApfCD mouse","volume":"484","author":"Gavaghan","year":"2000","journal-title":"FEBS Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"9810","DOI":"10.1038\/s41598-018-27958-1","article-title":"Instability of personal human metabotype is linked to all-cause mortality","volume":"8","author":"Lacruz","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1007\/s11306-014-0629-y","article-title":"Long term conservation of human metabolic phenotypes and link to heritability","volume":"10","author":"Yousri","year":"2014","journal-title":"Metabolomics"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1038\/nature04648","article-title":"Pharmaco-metabonomic phenotyping and personalized drug treatment","volume":"440","author":"Clayton","year":"2006","journal-title":"Nature"},{"key":"ref_20","first-page":"251","article-title":"Defining Personal Nutrition and Metabolic Health Through Metabonomics","volume":"4","author":"Rezzi","year":"2007","journal-title":"Ernst Scher. Found Symp. Proc."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1007\/s00394-019-01988-5","article-title":"Modifying effect of metabotype on diet\u2013diabetes associations","volume":"59","author":"Riedl","year":"2019","journal-title":"Eur. J. Nutr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1420","DOI":"10.1073\/pnas.0705685105","article-title":"Evidence of different metabolic phenotypes in humans","volume":"105","author":"Assfalg","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"646","DOI":"10.14336\/AD.2020.0909","article-title":"Metabolomics Signatures of Aging: Recent Advances","volume":"12","author":"Adav","year":"2021","journal-title":"Aging Dis."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Burlikowska, K., Stryjak, I., Bogusiewicz, J., Kupcewicz, B., Jaroch, K., and Bojko, B. (2020). Comparison of Metabolomic Profiles of Organs in Mice of Different Strains Based on SPME-LC-HRMS. Metabolites, 10.","DOI":"10.3390\/metabo10060255"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1021\/acs.jproteome.7b00750","article-title":"Tissue Level Diet and Sex-by-Diet Interactions Reveal Unique Metabolite and Clustering Profiles Using Untargeted Liquid Chromatography-Mass Spectrometry on Adipose, Skeletal Muscle, and Liver Tissue in C57BL6\/J Mice","volume":"17","author":"Wells","year":"2018","journal-title":"J. Proteome Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3212","DOI":"10.1021\/ac902837x","article-title":"Metabolomic Analysis via Reversed-Phase Ion-Pairing Liquid Chromatography Coupled to a Stand Alone Orbitrap Mass Spectrometer","volume":"82","author":"Lu","year":"2010","journal-title":"Anal. Chem."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1038\/nchembio.186","article-title":"Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli","volume":"5","author":"Bennett","year":"2009","journal-title":"Nat. Chem. Biol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.ab.2004.09.001","article-title":"Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards","volume":"336","author":"Wu","year":"2005","journal-title":"Anal. Biochem."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1038\/nbt.2377","article-title":"A cross-platform toolkit for mass spectrometry and proteomics","volume":"30","author":"Chambers","year":"2012","journal-title":"Nat. Biotechnol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"9818","DOI":"10.1021\/ac1021166","article-title":"Metabolomic Analysis and Visualization Engine for LC\u2212MS Data","volume":"82","author":"Melamud","year":"2010","journal-title":"Anal. Chem."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Clasquin, M.F., Melamud, E., Rabinowitz, J.D., Clasquin, M.F., Melamud, E., and Rabinowitz, J.D. (2012). LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine. Current Protocols in Bioinformatics, Current Protocols in Bioinformatics, John Wiley & Sons, Inc.","DOI":"10.1002\/0471250953.bi1411s37"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"D521","DOI":"10.1093\/nar\/gkl923","article-title":"HMDB: The Human Metabolome Database","volume":"35","author":"Wishart","year":"2007","journal-title":"Nucleic Acids Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"D603","DOI":"10.1093\/nar\/gkn810","article-title":"HMDB: A knowledgebase for the human metabolome","volume":"37","author":"Wishart","year":"2008","journal-title":"Nucleic Acids Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"D801","DOI":"10.1093\/nar\/gks1065","article-title":"HMDB 3.0\u2014The Human Metabolome Database in 2013","volume":"41","author":"Wishart","year":"2013","journal-title":"Nucleic Acids Res."},{"key":"ref_35","unstructured":"Team, R.C. (2015). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_36","unstructured":"GmbH, M.S. (2022, February 22). XLConnect: Excel Connector for R, Available online: https:\/\/cran.r-project.org\/web\/packages\/XLConnect\/index.html."},{"key":"ref_37","unstructured":"Hastie, T., Tibshirani, R., Narasimhan, B., and Chu, G. (Impute: Imputation for Microarray Data, 2016). Impute: Imputation for Microarray Data."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1186\/1471-2105-11-571","article-title":"Probabilistic principal component analysis for metabolomic data","volume":"11","author":"Nyamundanda","year":"2010","journal-title":"BMC Bioinform."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B Methodol."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Chen, H., and Boutros, P.C. (2011). VennDiagram: A package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform., 12.","DOI":"10.1186\/1471-2105-12-35"},{"key":"ref_41","unstructured":"Sanchez, G. (DiscriMiner: Tools of the Trade for Discriminant Analysis, 2013). DiscriMiner: Tools of the Trade for Discriminant Analysis."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v040.i01","article-title":"The Split-Apply-Combine Strategy for Data Analysis","volume":"40","author":"Wickham","year":"2011","journal-title":"J. Stat. Softw."},{"key":"ref_43","unstructured":"John Fox, S.W. (2011). An {R} Companion to Applied Regression, Sage. [2nd ed.]."},{"key":"ref_44","unstructured":"Harrell, F.E. (Hmisc: Harrell Miscellaneous, 2015). Hmisc: Harrell Miscellaneous."},{"key":"ref_45","unstructured":"Bengtsson, H. (2003, January 20\u201322). The R.oo package\u2014Object-Oriented Programming with References Using Standard R Code. Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), Vienna, Austria."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1093\/bioinformatics\/btr661","article-title":"Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data","volume":"28","author":"Karnovsky","year":"2011","journal-title":"Bioinformatics"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"W251","DOI":"10.1093\/nar\/gkv380","article-title":"MetaboAnalyst 3.0\u2014Making metabolomics more meaningful","volume":"43","author":"Xia","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Langfelder, P., and Horvath, S. (2008). WGCNA: An R package for weighted correlation network analysis. BMC Bioinform., 9.","DOI":"10.1186\/1471-2105-9-559"}],"container-title":["Metabolites"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-1989\/12\/4\/337\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:50:17Z","timestamp":1760136617000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-1989\/12\/4\/337"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,8]]},"references-count":48,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["metabo12040337"],"URL":"https:\/\/doi.org\/10.3390\/metabo12040337","relation":{},"ISSN":["2218-1989"],"issn-type":[{"value":"2218-1989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,8]]}}}