Genetic analysis of a mouse cross implicates an anti-inflammatory gene in control of atherosclerosis susceptibility
- PMID: 28116503
- PMCID: PMC5374004
- DOI: 10.1007/s00335-016-9677-0
Genetic analysis of a mouse cross implicates an anti-inflammatory gene in control of atherosclerosis susceptibility
Abstract
Nearly all genetic crosses generated from Apoe-/- or Lldlr-/- mice for genetic analysis of atherosclerosis have used C57BL/6 J (B6) mice as one parental strain, thus limiting their mapping power and coverage of allelic diversity. SM/J-Apoe -/- and BALB/cJ-Apoe -/- mice differ significantly in atherosclerosis susceptibility. 224 male F2 mice were generated from the two Apoe -/- strains to perform quantitative trait locus (QTL) analysis of atherosclerosis. F2 mice were fed 5 weeks of Western diet and analyzed for atherosclerotic lesions in the aortic root. Genome-wide scans with 144 informative SNP markers identified a significant locus near 20.2 Mb on chromosome 10 (LOD score: 6.03), named Ath48, and a suggestive locus near 49.5 Mb on chromosome 9 (LOD: 2.29; Ath29) affecting atherosclerotic lesion sizes. Using bioinformatics tools, we prioritized 12 candidate genes for Ath48. Of them, Tnfaip3, an anti-inflammatory gene, is located precisely underneath the linkage peak and contains two non-synonymous SNPs leading to conservative amino acid substitutions. Thus, this study demonstrates the power of forward genetics involving the use of a different susceptible strain and bioinformatics tools in finding atherosclerosis susceptibility genes.
Conflict of interest statement
The authors declare no conflicting interests.
Figures











Similar articles
-
Polygenic Control of Carotid Atherosclerosis in a BALB/cJ × SM/J Intercross and a Combined Cross Involving Multiple Mouse Strains.G3 (Bethesda). 2017 Feb 9;7(2):731-739. doi: 10.1534/g3.116.037879. G3 (Bethesda). 2017. PMID: 28040783 Free PMC article.
-
Genetic architecture of atherosclerosis dissected by QTL analyses in three F2 intercrosses of apolipoprotein E-null mice on C57BL6/J, DBA/2J and 129S6/SvEvTac backgrounds.PLoS One. 2017 Aug 24;12(8):e0182882. doi: 10.1371/journal.pone.0182882. eCollection 2017. PLoS One. 2017. PMID: 28837567 Free PMC article.
-
Quantitative trait loci affecting atherosclerosis at the aortic root identified in an intercross between DBA2J and 129S6 apolipoprotein E-null mice.PLoS One. 2014 Feb 20;9(2):e88274. doi: 10.1371/journal.pone.0088274. eCollection 2014. PLoS One. 2014. PMID: 24586312 Free PMC article.
-
Identifying novel genes for atherosclerosis through mouse-human comparative genetics.Am J Hum Genet. 2005 Jul;77(1):1-15. doi: 10.1086/431656. Epub 2005 May 19. Am J Hum Genet. 2005. PMID: 15931593 Free PMC article. Review.
-
Quantitative trait locus mapping for atherosclerosis susceptibility.Curr Opin Lipidol. 2003 Oct;14(5):499-504. doi: 10.1097/00041433-200310000-00011. Curr Opin Lipidol. 2003. PMID: 14501589 Review.
Cited by
-
Regional Variation in Genetic Control of Atherosclerosis in Hyperlipidemic Mice.G3 (Bethesda). 2020 Dec 3;10(12):4679-4689. doi: 10.1534/g3.120.401856. G3 (Bethesda). 2020. PMID: 33109727 Free PMC article.
-
Integrative multi-omics analysis of IFNγ-induced macrophages and atherosclerotic plaques reveals macrophage-dependent STAT1-driven transcription in atherosclerosis.Front Immunol. 2025 Jun 18;16:1590953. doi: 10.3389/fimmu.2025.1590953. eCollection 2025. Front Immunol. 2025. PMID: 40607379 Free PMC article.
-
In Search for Genes Related to Atherosclerosis and Dyslipidemia Using Animal Models.Int J Mol Sci. 2020 Mar 18;21(6):2097. doi: 10.3390/ijms21062097. Int J Mol Sci. 2020. PMID: 32197550 Free PMC article. Review.
-
Data on genetic linkage of oxidative stress with cardiometabolic traits in an intercross derived from hyperlipidemic mouse strains.Data Brief. 2020 Jan 23;29:105165. doi: 10.1016/j.dib.2020.105165. eCollection 2020 Apr. Data Brief. 2020. PMID: 32025547 Free PMC article.
-
Genetic connection of carotid atherosclerosis with coat color and body weight in an intercross between hyperlipidemic mouse strains.Physiol Genomics. 2022 May 1;54(5):166-176. doi: 10.1152/physiolgenomics.00006.2022. Epub 2022 Apr 6. Physiol Genomics. 2022. PMID: 35384748 Free PMC article.
References
-
- CARDIoGRAMplusC4D Consortium. Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, Ingelsson E, Saleheen D, Erdmann J, Goldstein BA, Stirrups K, Konig IR, Cazier JB, Johansson A, Hall AS, Lee JY, Willer CJ, Chambers JC, Esko T, Folkersen L, Goel A, Grundberg E, Havulinna AS, Ho WK, Hopewell JC, Eriksson N, Kleber ME, Kristiansson K, Lundmark P, Lyytikainen LP, Rafelt S, Shungin D, Strawbridge RJ, Thorleifsson G, Tikkanen E, Van Zuydam N, Voight BF, Waite LL, Zhang W, Ziegler A, Absher D, Altshuler D, Balmforth AJ, Barroso I, Braund PS, Burgdorf C, Claudi-Boehm S, Cox D, Dimitriou M, Do R, DIAGRAM Consortium CARDIOGENICS Consortium Doney AS, El Mokhtari N, Eriksson P, Fischer K, Fontanillas P, Franco-Cereceda A, Gigante B, Groop L, Gustafsson S, Hager J, Hallmans G, Han BG, Hunt SE, Kang HM, Illig T, Kessler T, Knowles JW, Kolovou G, Kuusisto J, Langenberg C, Langford C, Leander K, Lokki ML, Lundmark A, McCarthy MI, Meisinger C, Melander O, Mihailov E, Maouche S, Morris AD, Muller-Nurasyid M, MuTHER Consortium Nikus K, Peden JF, Rayner NW, Rasheed A, Rosinger S, Rubin D, Rumpf MP, Schafer A, Sivananthan M, Song C, Stewart AF, Tan ST, Thorgeirsson G, van der Schoot CE, Wagner PJ, Wellcome Trust Case Control Consortium Wells GA, Wild PS, Yang TP, Amouyel P, Arveiler D, Basart H, Boehnke M, Boerwinkle E, Brambilla P, Cambien F, Cupples AL, de Faire U, Dehghan A, Diemert P, Epstein SE, Evans A, Ferrario MM, Ferrieres J, Gauguier D, Go AS, Goodall AH, Gudnason V, Hazen SL, Holm H, Iribarren C, Jang Y, Kahonen M, Kee F, Kim HS, Klopp N, Koenig W, Kratzer W, Kuulasmaa K, Laakso M, Laaksonen R, Lee JY, Lind L, Ouwehand WH, Parish S, Park JE, Pedersen NL, Peters A, Quertermous T, Rader DJ, Salomaa V, Schadt E, Shah SH, Sinisalo J, Stark K, Stefansson K, Tregouet DA, Virtamo J, Wallentin L, Wareham N, Zimmermann ME, Nieminen MS, Hengstenberg C, Sandhu MS, Pastinen T, Syvanen AC, Hovingh GK, Dedoussis G, Franks PW, Lehtimaki T, Metspalu A, Zalloua PA, Siegbahn A, Schreiber S, Ripatti S, Blankenberg SS, Perola M, Clarke R, Boehm BO, O’Donnell C, Reilly MP, Marz W, Collins R, Kathiresan S, Hamsten A, Kooner JS, Thorsteinsdottir U, Danesh J, Palmer CN, Roberts R, Watkins H, Schunkert H, Samani NJ. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 2013;45:25–33. - PMC - PubMed
-
- Cooper JT, Stroka DM, Brostjan C, Palmetshofer A, Bach FH, Ferran C. A20 blocks endothelial cell activation through a NF-kappaB-dependent mechanism. J Biol Chem. 1996;271:18068–18073. - PubMed
-
- Dansky HM, Shu P, Donavan M, Montagno J, Nagle DL, Smutko JS, Roy N, Whiteing S, Barrios J, McBride TJ, Smith JD, Duyk G, Breslow JL, Moore KJ. A phenotype-sensitizing Apoe-deficient genetic background reveals novel atherosclerosis predisposition loci in the mouse. Genetics. 2002;160:1599–1608. - PMC - PubMed
-
- global Lipids Genetics Consortium Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Do R, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkila K, Hypponen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikainen LP, Magnusson PK, Mangino M, Mihailov E, Montasser ME, Muller-Nurasyid M, Nolte IM, O’Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney AS, Doring A, Elliott P, Epstein SE, Eyjolfsson GI, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJ, Khaw KT, Kim E, Klopp N, Komulainen P, Kumari M, Langenberg C, Lehtimaki T, Lin SY, Lindstrom J, Loos RJ, Mach F, McArdle WL, Meisinger C, Mitchell BD, Muller G, Nagaraja R, Narisu N, Nieminen TV, Nsubuga RN, Olafsson I, Ong KK, Palotie A, Papamarkou T, Pomilla C, Pouta A, Rader DJ, Reilly MP, Ridker PM, Rivadeneira F, Rudan I, Ruokonen A, Samani N, Scharnagl H, Seeley J, Silander K, Stancakova A, Stirrups K, Swift AJ, Tiret L, Uitterlinden AG, van Pelt LJ, Vedantam S, Wainwright N, Wijmenga C, Wild SH, Willemsen G, Wilsgaard T, Wilson JF, Young EH, Zhao JH, Adair LS, Arveiler D, Assimes TL, Bandinelli S, Bennett F, Bochud M, Boehm BO, Boomsma DI, Borecki IB, Bornstein SR, Bovet P, Burnier M, Campbell H, Chakravarti A, Chambers JC, Chen YD, Collins FS, Cooper RS, Danesh J, Dedoussis G, de Faire U, Feranil AB, Ferrieres J, Ferrucci L, Freimer NB, Gieger C, Groop LC, Gudnason V, Gyllensten U, Hamsten A, Harris TB, Hingorani A, Hirschhorn JN, Hofman A, Hovingh GK, Hsiung CA, Humphries SE, Hunt SC, Hveem K, Iribarren C, Jarvelin MR, Jula A, Kahonen M, Kaprio J, Kesaniemi A, Kivimaki M, Kooner JS, Koudstaal PJ, Krauss RM, Kuh D, Kuusisto J, Kyvik KO, Laakso M, Lakka TA, Lind L, Lindgren CM, Martin NG, Marz W, McCarthy MI, McKenzie CA, Meneton P, Metspalu A, Moilanen L, Morris AD, Munroe PB, Njolstad I, Pedersen NL, Power C, Pramstaller PP, Price JF, Psaty BM, Quertermous T, Rauramaa R, Saleheen D, Salomaa V, Sanghera DK, Saramies J, Schwarz PE, Sheu WH, Shuldiner AR, Siegbahn A, Spector TD, Stefansson K, Strachan DP, Tayo BO, Tremoli E, Tuomilehto J, Uusitupa M, van Duijn CM, Vollenweider P, Wallentin L, Wareham NJ, Whitfield JB, Wolffenbuttel BH, Ordovas JM, Boerwinkle E, Palmer CN, Thorsteinsdottir U, Chasman DI, Rotter JI, Franks PW, Ripatti S, Cupples LA, Sandhu MS, Rich SS, Boehnke M, Deloukas P, Kathiresan S, Mohlke KL, Ingelsson E, Abecasis GR. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45:1274–1283. - PMC - PubMed
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Molecular Biology Databases
Miscellaneous