Several corresponding regions of human and mammalian genomes have been shown to affect sensitivity to the manifestation of metabolic syndrome via nutrigenetic interactions. In this study, we assessed the effect of sucrose administration in a newly established congenic strain BN.SHR20, in which a limited segment of rat chromosome 20 from a metabolic syndrome model, spontaneously hypertensive rat (SHR), was introgressed into Brown Norway (BN) genomic background. We mapped the extent of the differential segment and compared the genomic sequences of BN vs. SHR within the segment in silico. The differential segment of SHR origin in BN.SHR20 spans about 9 Mb of the telomeric portion of the short arm of chromosome 20. We identified non-synonymous mutations e.g., in ApoM, Notch4, Slc39a7, Smim29 genes and other variations in or near genes associated with metabolic syndrome in human genome-wide association studies. Male rats of BN and BN.SHR20 strains were fed a standard diet for 18 weeks (control groups) or 16 weeks of standard diet followed by 14 days of high-sucrose diet (HSD). We assessed the morphometric and metabolic profiles of all groups. Adiposity significantly increased only in BN.SHR20 after HSD. Fasting glycemia and the glucose levels during the oral glucose tolerance test were higher in BN.SHR20 than in BN groups, while insulin levels were comparable. The fasting levels of triacylglycerols were the highest in sucrose-fed BN.SHR20, both compared to the sucrose-fed BN and the control BN.SHR20. The non-esterified fatty acids and total cholesterol concentrations were higher in BN.SHR20 compared to their respective BN groups, and the HSD elicited an increase in non-esterified fatty acids only in BN.SHR20. In a new genetically defined model, we have isolated a limited genomic region involved in nutrigenetic sensitization to sucrose-induced metabolic disturbances.

Centre for Experimental Medicine Institute for Clinical and Experimental Medicine 140 21 Prague Czech Republic

Institute of Biology and Medical Genetics The 1st Faculty of Medicine Charles University and the General University Hospital Prague 128 00 Prague Czech Republic

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Alberti K.G., Eckel R.H., Grundy S.M., Zimmet P.Z., Cleeman J.I., Donato K.A., Fruchart J.C., James W.P., Loria C.M., Smith S.C., Jr., et al. Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–1645. doi: 10.1161/CIRCULATIONAHA.109.192644. PubMed DOI

Noubiap J.J., Nansseu J.R., Lontchi-Yimagou E., Nkeck J.R., Nyaga U.F., Ngouo A.T., Tounouga D.N., Tianyi F.L., Foka A.J., Ndoadoumgue A.L., et al. Geographic distribution of metabolic syndrome and its components in the general adult population: A meta-analysis of global data from 28 million individuals. Diabetes Res. Clin. Pract. 2022;188:109924. doi: 10.1016/j.diabres.2022.109924. PubMed DOI

Clark K.C., Kwitek A.E. Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome. Compr. Physiol. 2021;12:3045–3084. doi: 10.1002/cphy.c210010. PubMed DOI PMC

Aitman T., Dhillon P., Geurts A.M. A RATional choice for translational research? Dis. Model Mech. 2016;9:1069–1072. doi: 10.1242/dmm.027706. PubMed DOI PMC

Szpirer C. Rat models of human diseases and related phenotypes: A systematic inventory of the causative genes. J. Biomed. Sci. 2020;27:84. doi: 10.1186/s12929-020-00673-8. PubMed DOI PMC

Seda O., Liska F., Krenova D., Kazdova L., Sedova L., Zima T., Peng J., Pelinkova K., Tremblay J., Hamet P., et al. Dynamic genetic architecture of metabolic syndrome attributes in the rat. Physiol. Genom. 2005;21:243–252. doi: 10.1152/physiolgenomics.00230.2004. PubMed DOI

Wallis R.H., Collins S.C., Kaisaki P.J., Argoud K., Wilder S.P., Wallace K.J., Ria M., Ktorza A., Rorsman P., Bihoreau M.T., et al. Pathophysiological, genetic and gene expression features of a novel rodent model of the cardio-metabolic syndrome. PLoS ONE. 2008;3:e2962. doi: 10.1371/journal.pone.0002962. PubMed DOI PMC

Strahorn P., Graham D., Charchar F.J., Sattar N., McBride M.W., Dominiczak A.F. Genetic determinants of metabolic syndrome components in the stroke-prone spontaneously hypertensive rat. J. Hypertens. 2005;23:2179–2186. doi: 10.1097/01.hjh.0000191904.26853.b8. PubMed DOI

Seda O., Sedova L., Liska F., Krenova D., Prejzek V., Kazdova L., Tremblay J., Hamet P., Kren V. Novel double-congenic strain reveals effects of spontaneously hypertensive rat chromosome 2 on specific lipoprotein subfractions and adiposity. Physiol. Genom. 2006;27:95–102. doi: 10.1152/physiolgenomics.00039.2006. PubMed DOI

Pravenec M., Zidek V., Simakova M., Kren V., Krenova D., Horky K., Jachymova M., Mikova B., Kazdova L., Aitman T.J., et al. Genetics of Cd36 and the clustering of multiple cardiovascular risk factors in spontaneous hypertension. J. Clin. Investig. 1999;103:1651–1657. doi: 10.1172/JCI6691. PubMed DOI PMC

Kloting N., Wilke B., Kloting I. Phenotypic and genetic analyses of subcongenic BB.SHR rat lines shorten the region on chromosome 4 bearing gene(s) for underlying facets of metabolic syndrome. Physiol. Genom. 2004;18:325–330. doi: 10.1152/physiolgenomics.00047.2004. PubMed DOI

Seda O., Liska F., Sedova L., Kazdova L., Krenova D., Kren V. A 14-gene region of rat chromosome 8 in SHR-derived polydactylous congenic substrain affects muscle-specific insulin resistance, dyslipidaemia and visceral adiposity. Folia Biol. 2005;51:53–61. PubMed

Sedova L., Pravenec M., Krenova D., Kazdova L., Zidek V., Krupkova M., Liska F., Kren V., Seda O. Isolation of a Genomic Region Affecting Most Components of Metabolic Syndrome in a Chromosome-16 Congenic Rat Model. PLoS ONE. 2016;11:e0152708. doi: 10.1371/journal.pone.0152708. PubMed DOI PMC

Ma M.C.J., Pettus J.M., Jakoubek J.A., Traxler M.G., Clark K.C., Mennie A.K., Kwitek A.E. Contribution of independent and pleiotropic genetic effects in the metabolic syndrome in a hypertensive rat. PLoS ONE. 2017;12:e0182650. doi: 10.1371/journal.pone.0182650. PubMed DOI PMC

Clark K.C., Wagner V.A., Holl K.L., Reho J.J., Tutaj M., Smith J.R., Dwinell M.R., Grobe J.L., Kwitek A.E. Body Composition and Metabolic Changes in a Lyon Hypertensive Congenic Rat and Identification of Ercc6l2 as a Positional Candidate Gene. Front. Genet. 2022;13:903971. doi: 10.3389/fgene.2022.903971. PubMed DOI PMC

Seda O., Sedova L., Kazdova L., Krenova D., Kren V. Metabolic characterization of insulin resistance syndrome feature loci in three brown Norway-derived congenic strains. Folia Biol. 2002;48:81–88. PubMed

Pausova Z., Sedova L., Berube J., Hamet P., Tremblay J., Dumont M., Gaudet D., Pravenec M., Kren V., Kunes J. Segment of rat chromosome 20 regulates diet-induced augmentations in adiposity, glucose intolerance, and blood pressure. Hypertension. 2003;41:1047–1055. doi: 10.1161/01.HYP.0000064347.49341.0B. PubMed DOI

Seda O., Kazdova L., Krenova D., Kren V. Rosiglitazone fails to improve hypertriglyceridemia and glucose tolerance in CD36-deficient BN.SHR4 congenic rat strain. Physiol. Genom. 2003;12:73–78. doi: 10.1152/physiolgenomics.00113.2002. PubMed DOI

Seda O., Sedova L., Oliyarnyk O., Kazdova L., Krenova D., Corbeil G., Hamet P., Tremblay J., Kren V. Pharmacogenomics of metabolic effects of rosiglitazone. Pharmacogenomics. 2008;9:141–155. doi: 10.2217/14622416.9.2.141. PubMed DOI

Krupkova M., Janku M., Liska F., Sedova L., Kazdova L., Krenova D., Kren V., Seda O. Pharmacogenetic model of retinoic acid-induced dyslipidemia and insulin resistance. Pharmacogenomics. 2009;10:1915–1927. doi: 10.2217/pgs.09.113. PubMed DOI

Pravenec M., Klir P., Kren V., Zicha J., Kunes J. An analysis of spontaneous hypertension in spontaneously hypertensive rats by means of new recombinant inbred strains. J. Hypertens. 1989;7:217–221. doi: 10.1097/00004872-198903000-00008. PubMed DOI

Bottger A., van Lith H.A., Kren V., Krenova D., Bila V., Vorlicek J., Zidek V., Musilova A., Zdobinska M., Wang J.M., et al. Quantitative trait loci influencing cholesterol and phospholipid phenotypes map to chromosomes that contain genes regulating blood pressure in the spontaneously hypertensive rat. J. Clin. Investig. 1996;98:856–862. doi: 10.1172/JCI118858. PubMed DOI PMC

Bourdon C., Hojna S., Jordan M., Berube J., Kren V., Pravenec M., Liu P., Arab S., Pausova Z. Genetic locus on rat chromosome 20 regulates diet-induced adipocyte hypertrophy: A microarray gene expression study. Physiol. Genom. 2009;38:63–72. doi: 10.1152/physiolgenomics.90209.2008. PubMed DOI PMC

Smith J.R., Hayman G.T., Wang S.J., Laulederkind S.J.F., Hoffman M.J., Kaldunski M.L., Tutaj M., Thota J., Nalabolu H.S., Ellanki S.L.R., et al. The Year of the Rat: The Rat Genome Database at 20: A multi-species knowledgebase and analysis platform. Nucleic Acids Res. 2020;48:D731–D742. doi: 10.1093/nar/gkz1041. PubMed DOI PMC

Hubisz M.J., Pollard K.S., Siepel A. PHAST and RPHAST: Phylogenetic analysis with space/time models. Brief. Bioinform. 2011;12:41–51. doi: 10.1093/bib/bbq072. PubMed DOI PMC

Cahova M., Dankova H., Palenickova E., Papackova Z., Kazdova L. The opposite effects of high-sucrose and high-fat diet on Fatty Acid oxidation and very low density lipoprotein secretion in rat model of metabolic syndrome. J. Nutr. Metab. 2012;2012:757205. doi: 10.1155/2012/757205. PubMed DOI PMC

Buniello A., MacArthur J.A.L., Cerezo M., Harris L.W., Hayhurst J., Malangone C., McMahon A., Morales J., Mountjoy E., Sollis E., et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47:D1005–D1012. doi: 10.1093/nar/gky1120. PubMed DOI PMC

Misselbeck K., Parolo S., Lorenzini F., Savoca V., Leonardelli L., Bora P., Morine M.J., Mione M.C., Domenici E., Priami C. A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome. Nat. Commun. 2019;10:5215. doi: 10.1038/s41467-019-13208-z. PubMed DOI PMC

Nielsen J. Systems Biology of Metabolism: A Driver for Developing Personalized and Precision Medicine. Cell Metab. 2017;25:572–579. doi: 10.1016/j.cmet.2017.02.002. PubMed DOI

Brown A.E., Walker M. Genetics of Insulin Resistance and the Metabolic Syndrome. Curr. Cardiol. Rep. 2016;18:75. doi: 10.1007/s11886-016-0755-4. PubMed DOI PMC

Dehghan M., Mente A., Zhang X., Swaminathan S., Li W., Mohan V., Iqbal R., Kumar R., Wentzel-Viljoen E., Rosengren A., et al. Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): A prospective cohort study. Lancet. 2017;390:2050–2062. doi: 10.1016/S0140-6736(17)32252-3. PubMed DOI

Khan T.A., Sievenpiper J.L. Controversies about sugars: Results from systematic reviews and meta-analyses on obesity, cardiometabolic disease and diabetes. Eur. J. Nutr. 2016;55:25–43. doi: 10.1007/s00394-016-1345-3. PubMed DOI PMC

Melancon S., Bachelard H., Badeau M., Bourgoin F., Pitre M., Lariviere R., Nadeau A. Effects of high-sucrose feeding on insulin resistance and hemodynamic responses to insulin in spontaneously hypertensive rats. Am. J. Physiol. Heart Circ. Physiol. 2006;290:H2571–H2581. doi: 10.1152/ajpheart.01002.2005. PubMed DOI

Klevstig M.J., Markova I., Burianova J., Kazdova L., Pravenec M., Novakova O., Novak F. Role of FAT/CD36 in novel PKC isoform activation in heart of spontaneously hypertensive rats. Mol. Cell. Biochem. 2011;357:163–169. doi: 10.1007/s11010-011-0886-2. PubMed DOI

Seda O., Sedova L., Vcelak J., Vankova M., Liska F., Bendlova B. ZBTB16 and metabolic syndrome: A network perspective. Physiol. Res. 2017;66:S357–S365. doi: 10.33549/physiolres.933730. PubMed DOI

Liška F., Mancini M., Krupková M., Chylíková B., Křenová D., Šeda O., Šilhavý J., Mlejnek P., Landa V., Zídek V., et al. Plzf as a candidate gene predisposing the spontaneously hypertensive rat to hypertension, left ventricular hypertrophy, and interstitial fibrosis. Am. J. Hypertens. 2014;27:99–106. doi: 10.1093/ajh/hpt156. PubMed DOI

Mattson D.L., Dwinell M.R., Greene A.S., Kwitek A.E., Roman R.J., Jacob H.J., Cowley A.W., Jr. Chromosome substitution reveals the genetic basis of Dahl salt-sensitive hypertension and renal disease. Am. J. Physiol. Renal Physiol. 2008;295:F837–F842. doi: 10.1152/ajprenal.90341.2008. PubMed DOI PMC

Yagil Y., Hessner M., Schulz H., Gosele C., Lebedev L., Barkalifa R., Sapojnikov M., Hubner N., Yagil C. Geno-transcriptomic dissection of proteinuria in the uninephrectomized rat uncovers a molecular complexity with sexual dimorphism. Physiol. Genom. 2010;42:301–316. doi: 10.1152/physiolgenomics.00149.2010. PubMed DOI

Auguet T., Bertran L., Binetti J., Aguilar C., Martinez S., Guiu-Jurado E., Sabench F., Adalid L., Porras J.A., Riesco D., et al. Hepatocyte Notch Signaling Deregulation Related to Lipid Metabolism in Women with Obesity and Nonalcoholic Fatty Liver. Obesity. 2020;28:1487–1493. doi: 10.1002/oby.22873. PubMed DOI

Wang H., Zhang F., Zeng J., Wu Y., Kemper K.E., Xue A., Zhang M., Powell J.E., Goddard M.E., Wray N.R., et al. Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank. Sci. Adv. 2019;5:eaaw3538. doi: 10.1126/sciadv.aaw3538. PubMed DOI PMC

Christakoudi S., Evangelou E., Riboli E., Tsilidis K.K. GWAS of allometric body-shape indices in UK Biobank identifies loci suggesting associations with morphogenesis, organogenesis, adrenal cell renewal and cancer. Sci. Rep. 2021;11:10688. doi: 10.1038/s41598-021-89176-6. PubMed DOI PMC

Surakka I., Horikoshi M., Magi R., Sarin A.P., Mahajan A., Lagou V., Marullo L., Ferreira T., Miraglio B., Timonen S., et al. The impact of low-frequency and rare variants on lipid levels. Nat. Genet. 2015;47:589–597. doi: 10.1038/ng.3300. PubMed DOI PMC

Lee S.Y., Long F. Notch signaling suppresses glucose metabolism in mesenchymal progenitors to restrict osteoblast differentiation. J. Clin. Investig. 2018;128:5573–5586. doi: 10.1172/JCI96221. PubMed DOI PMC

Spracklen C.N., Horikoshi M., Kim Y.J., Lin K., Bragg F., Moon S., Suzuki K., Tam C.H.T., Tabara Y., Kwak S.H., et al. Identification of type 2 diabetes loci in 433,540 East Asian individuals. Nature. 2020;582:240–245. doi: 10.1038/s41586-020-2263-3. PubMed DOI PMC

Chen J., Spracklen C.N., Marenne G., Varshney A., Corbin L.J., Luan J., Willems S.M., Wu Y., Zhang X., Horikoshi M., et al. The trans-ancestral genomic architecture of glycemic traits. Nat. Genet. 2021;53:840–860. doi: 10.1038/s41588-021-00852-9. PubMed DOI PMC

Richardson T.G., Leyden G.M., Wang Q., Bell J.A., Elsworth B., Davey Smith G., Holmes M.V. Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation. PLoS Biol. 2022;20:e3001547. doi: 10.1371/journal.pbio.3001547. PubMed DOI PMC

Kazmierczak B., Borrmann L., Bullerdiek J. Assignment of a new gene (LBH) Genomics. 1999;56:136–137. doi: 10.1006/geno.1998.5684. PubMed DOI

Tan Q., Akindehin S.E., Orsso C.E., Waldner R.C., DiMarchi R.D., Muller T.D., Haqq A.M. Recent Advances in Incretin-Based Pharmacotherapies for the Treatment of Obesity and Diabetes. Front. Endocrinol. 2022;13:838410. doi: 10.3389/fendo.2022.838410. PubMed DOI PMC

Bensinger S.J., Tontonoz P. Integration of metabolism and inflammation by lipid-activated nuclear receptors. Nature. 2008;454:470–477. doi: 10.1038/nature07202. PubMed DOI

Raut S.K., Khullar M. Oxidative stress in metabolic diseases: Current scenario and therapeutic relevance. Mol. Cell. Biochem. 2022;477 doi: 10.1007/s11010-022-04496-z. PubMed DOI

Ober C., Loisel D.A., Gilad Y. Sex-specific genetic architecture of human disease. Nat. Rev. Genet. 2008;9:911–922. doi: 10.1038/nrg2415. PubMed DOI PMC

Dabke K., Hendrick G., Devkota S. The gut microbiome and metabolic syndrome. J. Clin. Investig. 2019;129:4050–4057. doi: 10.1172/JCI129194. PubMed DOI PMC

Wong S.K., Chin K.Y., Suhaimi F.H., Fairus A., Ima-Nirwana S. Animal models of metabolic syndrome: A review. Nutr. Metab. 2016;13:65. doi: 10.1186/s12986-016-0123-9. PubMed DOI PMC