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‘Fat’s chances’: Loci for phenotypic dispersion in plasma leptin in mouse models of diabetes mellitus


Autoři: Guy M. L. Perry aff001
Působiště autorů: Department of Biology, University of Prince Edward Island, Charlottetown, PEI, Canada aff001
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0222654

Souhrn

Background

Leptin, a critical mediator of feeding, metabolism and diabetes, is expressed on an incidental basis according to satiety. The genetic regulation of leptin should similarly be episodic.

Methodology

Data from three mouse cohorts hosted by the Jackson Laboratory– 402 (174F, 228M) F2 Dilute Brown non-Agouti (DBA/2)×DU6i intercrosses, 142 Non Obese Diabetic (NOD/ShiLtJ×(NOD/ShiLtJ×129S1/SvImJ.H2g7) N2 backcross females, and 204 male Nonobese Nondiabetic (NON)×New Zealand Obese (NZO/HlLtJ) reciprocal backcrosses–were used to test for loci associated with absolute residuals in plasma leptin and arcsin-transformed percent fat (‘phenotypic dispersion’; PDpLep and PDAFP). Individual data from 1,780 mice from 43 inbred strains was also used to estimate genetic variances and covariances for dispersion in each trait.

Principal findings

Several loci for PDpLep were detected, including possibly syntenic Chr 17 loci, but there was only a single position on Chr 6 for PDAFP. Coding SNP in genes linked to the consensus Chr 17 PDpLep locus occurred in immunological and cancer genes, genes linked to diabetes and energy regulation, post-transcriptional processors and vomeronasal variants. There was evidence of intersexual differences in the genetic architecture of PDpLep. PDpLep had moderate heritability (hs2=0.29) and PDAFP low heritability (hs2=0.12); dispersion in these traits was highly genetically correlated r = 0.8).

Conclusions

Greater genetic variance for dispersion in plasma leptin, a physiological trait, may reflect its more ephemeral nature compared to body fat, an accrued progressive character. Genetic effects on incidental phenotypes such as leptin might be effectively characterized with randomization-detection methodologies in addition to classical approaches, helping identify incipient or borderline cases or providing new therapeutic targets.

Klíčová slova:

Fats – Genetic loci – leptin – Molecular genetics – Mouse models – Obesity – Phenotypes


Zdroje

1. Harris R (2014) Direct and indirect effects of leptin on adipocyte metabolism. Biochim Biophys Acta 184: 414–423.

2. Leibel RL, Bahary N, Friedman JM (1990) Genetic variation and nutrition in obesity: approaches to the molecular genetics of obesity. World Rev Nutr Diet 63: 90–101. 1973864

3. Noble JA, Erlich HA (2012) Genetics of type 1 diabetes. Cold Spring Harb Perspect Med 2: a007732. doi: 10.1101/cshperspect.a007732 22315720

4. Kraus D, Herman MA, Kahn BB (2010) Leveraging leptin for type I diabetes? Proc Natl Acad Sci U S A 107: 4793–4794. doi: 10.1073/pnas.1000736107 20212134

5. Coppari R, Bjorbaek C (2012) The potential of leptin for treating diabetes and its mechanism of action. Nat Rev Drug Discov 11: 692–708. doi: 10.1038/nrd3757 22935803

6. Heo M, Leibel RL, Boyer BB, Chung WK, Koulu M, et al. (2001) Pooling analysis of genetic data: the association of leptin receptor (LEPR) polymorphisms with variables related to human adiposity. Genetics 159: 1163–1178. 11729160

7. Almind K, Kahn CR (2004) Genetic determinants of energy expenditure and insulin resistance in diet-induced obesity in mice. Diabetes 53: 3274–3285. 15561960

8. Almind K, Kulkarni RN, Lannon SM, Kahn CR (2003) Identification of interactive loci linked to insulin and leptin in mice with genetic insulin resistance. Diabetes 52: 1535–1543. doi: 10.2337/diabetes.52.6.1535 12765967

9. Brockmann GA, Kratzsch J, Haley CS, Renne U, Schwerin M, et al. (2000) Single QTL effects, epistasis, and pleiotropy account for two-thirds of the phenotypic F(2) variance of growth and obesity in DU6i x DBA/2 mice. Genome Res 10: 1941–1957. doi: 10.1101/gr.gr1499r 11116089

10. Allan MF, Eisen EJ, Pomp D (2005) Genomic mapping of direct and correlated responses to long-term selection for rapid growth rate in mice. Genetics 170: 1863–1877. doi: 10.1534/genetics.105.041319 15944354

11. Reifsnyder PC, Churchill G, Leiter EH (2000) Maternal environment and genotype interact to establish diabesity in mice. Genome Res 10: 1568–1578. doi: 10.1101/gr.147000 11042154

12. Flier J, Maratos-Flier E (2017) Leptin's physiological role: does the emperor of energy balance have no clothes? Cell Metabolism 26: 24–26. doi: 10.1016/j.cmet.2017.05.013 28648981

13. Wherett D, Ho J, Huot C, Legault L, Nakhla M, et al. (2018) Type 1 diabetes in children and adolescents. Canadian Journal of Diabetes 42: S234–S236. doi: 10.1016/j.jcjd.2017.10.036 29650103

14. Allensworth-James ML, Odle A, Haney A, Childs G (2015) Sex differences in somatotrope dependency on leptin receptors in young mice: ablation of LEPR causes severe growth hormone deficiency and abdominal obesity in males. Endocrinology 156: 3253–3264. doi: 10.1210/EN.2015-1198 26168341

15. Bagnasco M, Kalra PS, Kalra SP (2002) Ghrelin and leptin pulse discharge in fed and fasted rats. Endocrinology 143: 726–729. doi: 10.1210/endo.143.2.8743 11796530

16. Hill W, Zhang X-S (2004) Effects on phenotypic variability of directional selection arising through genetic differences in residual variability. Genetical Research Cambridge 83: 121–132.

17. Perry G, Nehrke K, Bushinsky D, Reid R, Lewandowski K, et al. (2012) Sex modifies genetic effects on residual variance in urinary calcium excretion in rat (Rattus norvegicus). Genetics 192: 1003–1013.

18. Rönnegard L, Valdar W (2012) Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability. BMC Genetics 13: 63. doi: 10.1186/1471-2156-13-63 22827487

19. Hill W, Mulder H (2010) Genetic analysis of environmental variation. Genetical Research (Cambridge) 92: 381–395.

20. Perry G (in review) A locus for phenotypic dispersion in diabetic insulitis in backcrosses of affected and unaffected house mouse (Mus musculus).

21. Bahary N, Leibel RL, Joseph L, Friedman JM (1990) Molecular mapping of the mouse db mutation. Proc Natl Acad Sci U S A 87: 8642–8646. doi: 10.1073/pnas.87.21.8642 1978328

22. Hershey T, Perantie DC, Warren SL, Zimmerman EC, Sadler M, et al. (2005) Frequency and timing of severe hypoglycemia affects spatial memory in children with type 1 diabetes. Diabetes Care 28: 2372–2377. doi: 10.2337/diacare.28.10.2372 16186265

23. Brockmann GA, Tsaih SW, Neuschl C, Churchill GA, Li R (2009) Genetic factors contributing to obesity and body weight can act through mechanisms affecting muscle weight, fat weight, or both. Physiol Genomics 36: 114–126. doi: 10.1152/physiolgenomics.90277.2008 18984673

24. Leiter EH, Reifsnyder PC, Wallace R, Li R, King B, et al. (2009) NOD x 129.H2(g7) backcross delineates 129S1/SvImJ-derived genomic regions modulating type 1 diabetes development in mice. Diabetes 58: 1700–1703. doi: 10.2337/db09-0120 19336673

25. SAS (2011) Base SAS(R) 9.3 Procedures Guide. Cary, NC: SAS Institute, Inc.

26. Steel R, Torrie J (1980) Principles and Procedures of Statistics. New York: McGraw-Hill Book Co.

27. Lerner I (1977) Genetic homeostasis. London: Oliver and Boyd.

28. Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I (2001) Controlling the false discovery rate in behavior genetics research. Behav Brain Res 125: 279–284. doi: 10.1016/s0166-4328(01)00297-2 11682119

29. Broman K, Wu H, Sen S, Churchill G (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19: 889–890. doi: 10.1093/bioinformatics/btg112 12724300

30. Cox A, Ackert-Bicknell C, Dumont D, Ding Y, Bell J, et al. (2009) A new standard genetic map for the laboratory mouse. Genetics 182: 1335–1344. doi: 10.1534/genetics.109.105486 19535546

31. Svenson KL, Von Smith R, Magnani PA, Suetin HR, Paigen B, et al. (2007) Multiple trait measurements in 43 inbred mouse strains capture the phenotypic diversity characteristic of human populations. J Appl Physiol (1985) 102: 2369–2378.

32. Groeneveld E, Kovac M, Wang T (1990) PEST, a general purpose BLUP package for multivariate prediction and estimation. Proceedings of the 4th World Congress in Genetics Applied to Livestock 13: 488–491.

33. Kovac M, Groeneveld E, Garcia-Cortes L (2002) A package for the optimization of dispersion parameters. Montpellier, France: 7th World Congress on Genetics Applied to Livestock Production.

34. Henderson C (1975) Best linear unbiased estimation and prediction under a selection model. Biometrics 31: 423–447. 1174616

35. Henderson C (1986) Estimation of variances in animal model and reduced animal model for single traits and single records. Journal of Dairy Science 69: 1394–1402.

36. Mogil JS, Wilson SG, Bon K, Lee SE, Chung K, et al. (1999) Heritability of nociception II. 'Types' of nociception revealed by genetic correlation analysis. Pain 80: 83–93. doi: 10.1016/s0304-3959(98)00196-1 10204720

37. Eppig JT, Smith CL, Blake JA, Ringwald M, Kadin JA, et al. (2017) Mouse Genome Informatics (MGI): Resources for Mining Mouse Genetic, Genomic, and Biological Data in Support of Primary and Translational Research. Methods Mol Biol 1488: 47–73. doi: 10.1007/978-1-4939-6427-7_3 27933520

38. Yachdav G, Kloppmann E, Kajan L, Hecht M, Goldberg T, et al. (2014) PredictProtein—an open resource for online prediction of protein structural and functional features. Nucleic Acids Res 42: W337–343. doi: 10.1093/nar/gku366 24799431

39. Rost B, Sander C (1994) Combining evolutionary information and neural networks to predict protein secondary structure. Proteins 19: 55–72. doi: 10.1002/prot.340190108 8066087

40. Rost B, Yachdav G, Liu J (2004) The PredictProtein server. Nucleic Acids Res 32: W321–326. doi: 10.1093/nar/gkh377 15215403

41. Kabsch W, Sander C (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22: 2577–2637. doi: 10.1002/bip.360221211 6667333

42. Ofran Y, Rost B (2007) ISIS: interaction sites identified from sequence. Bioinformatics 23: e13–16. doi: 10.1093/bioinformatics/btl303 17237081

43. Hönigschmid P (2012) Improvement of DNA- and RNA-protein binding prediction. Munich: Technical University of Munich.

44. Karplus P, Schultz G (1985) Prediction of chain flexibility of peptide antigens. Naturwissenshaften.

45. Carugo O, Argos P (1997) Correlation between side chain mobility and conformation in protein structures. Protein Eng 10: 777–787. doi: 10.1093/protein/10.7.777 9342144

46. Schlessinger A, Yachdav G, Rost B (2006) PROFbval: predict flexible and rigid residues in proteins. Bioinformatics 22: 891–893. doi: 10.1093/bioinformatics/btl032 16455751

47. Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sunderland, MA: Sinauer Associates Inc.

48. Charron Y, Willert J, Lipkowitz B, Kusecek B, Herrmann BG, et al. (2019) Two isoforms of the RAC-specific guanine nucleotide exchange factor TIAM2 act oppositely on transmission ratio distortion by the mouse t-haplotype. PLoS Genet 15: e1007964. doi: 10.1371/journal.pgen.1007964 30817801

49. Yoshizawa M, Hoshino M, Sone M, Nabeshima Y (2002) Expression of stef, an activator of Rac1, correlates with the stages of neuronal morphological development in the mouse brain. Mech Dev 113: 65–68. doi: 10.1016/s0925-4773(01)00650-5 11900975

50. Banfi B, Malgrange B, Knisz J, Steger K, Dubois-Dauphin M, et al. (2004) NOX3, a superoxide-generating NADPH oxidase of the inner ear. J Biol Chem 279: 46065–46072. doi: 10.1074/jbc.M403046200 15326186

51. Chen G, Adeyemo AA, Zhou J, Chen Y, Doumatey A, et al. (2007) A genome-wide search for linkage to renal function phenotypes in West Africans with type 2 diabetes. Am J Kidney Dis 49: 394–400. doi: 10.1053/j.ajkd.2006.12.011 17336700

52. Oo HZ, Sentani K, Sakamoto N, Anami K, Naito Y, et al. (2014) Overexpression of ZDHHC14 promotes migration and invasion of scirrhous type gastric cancer. Oncol Rep 32: 403–410. doi: 10.3892/or.2014.3166 24807047

53. Rinaldi A, Kwee I, Poretti G, Mensah A, Pruneri G, et al. (2006) Comparative genome-wide profiling of post-transplant lymphoproliferative disorders and diffuse large B-cell lymphomas. Br J Haematol 134: 27–36. doi: 10.1111/j.1365-2141.2006.06114.x 16803564

54. Khvotchev M, Sudhof TC (1998) Developmentally regulated alternative splicing in a novel synaptojanin. J Biol Chem 273: 2306–2311. doi: 10.1074/jbc.273.4.2306 9442075

55. Nemoto Y, De Camilli P (1999) Recruitment of an alternatively spliced form of synaptojanin 2 to mitochondria by the interaction with the PDZ domain of a mitochondrial outer membrane protein. EMBO J 18: 2991–3006. doi: 10.1093/emboj/18.11.2991 10357812

56. Anderegg U, Breitschwerdt K, Kohler MJ, Sticherling M, Haustein UF, et al. (2005) MEL4B3, a novel mRNA is induced in skin tumors and regulated by TGF-beta and pro-inflammatory cytokines. Exp Dermatol 14: 709–718. doi: 10.1111/j.0906-6705.2005.00349.x 16098131

57. Wu JI, Centilli MA, Vasquez G, Young S, Scolnick J, et al. (2007) Tint maps to mouse chromosome 6 and may interact with a notochordal enhancer of Brachyury. Genetics 177: 1151–1161. doi: 10.1534/genetics.107.079715 17954925

58. Wang H, Liu Y, Hou J, Zheng M, Robinson H, et al. (2007) Structural insight into substrate specificity of phosphodiesterase 10. Proc Natl Acad Sci U S A 104: 5782–5787. doi: 10.1073/pnas.0700279104 17389385

59. MacMullen CM, Vick K, Pacifico R, Fallahi-Sichani M, Davis RL (2016) Novel, primate-specific PDE10A isoform highlights gene expression complexity in human striatum with implications on the molecular pathology of bipolar disorder. Transl Psychiatry 6: e742. doi: 10.1038/tp.2016.3 26905414

60. Nawrocki AR, Rodriguez CG, Toolan DM, Price O, Henry M, et al. (2014) Genetic deletion and pharmacological inhibition of phosphodiesterase 10A protects mice from diet-induced obesity and insulin resistance. Diabetes 63: 300–311. doi: 10.2337/db13-0247 24101672

61. Hankir MK, Kranz M, Gnad T, Weiner J, Wagner S, et al. (2016) A novel thermoregulatory role for PDE10A in mouse and human adipocytes. EMBO Mol Med 8: 796–812. doi: 10.15252/emmm.201506085 27247380

62. Gorgoni B, Gray NK (2004) The roles of cytoplasmic poly(A)-binding proteins in regulating gene expression: a developmental perspective. Brief Funct Genomic Proteomic 3: 125–141. doi: 10.1093/bfgp/3.2.125 15355595

63. Takai Y, Nakanishi H (2003) Nectin and afadin: novel organizers of intercellular junctions. J Cell Sci 116: 17–27. doi: 10.1242/jcs.00167 12456712

64. Siiskonen H, Oikari S, Pasonen-Seppanen S, Rilla K (2015) Hyaluronan synthase 1: a mysterious enzyme with unexpected functions. Front Immunol 6: 43. doi: 10.3389/fimmu.2015.00043 25699059

65. Brown D (2018) The genetics of physiological dispersion in signs of diabetes using murine models. Charlottetown, PE, Canada: University of Prince Edward Island. 120 p.

66. Perry G (2019) Genetic effects on dispersion in urinary albumin and creatinine in three house mouse (Mus musculus) cohorts. G3 (Bethesda).

67. Licinio J, Negrao AB, Mantzoros C, Kaklamani V, Wong ML, et al. (1998) Sex differences in circulating human leptin pulse amplitude: clinical implications. J Clin Endocrinol Metab 83: 4140–4147. doi: 10.1210/jcem.83.11.5291 9814504

68. Kohnert KD, Heinke P, Vogt L, Augstein P, Salzsieder E (2018) Applications of variability analysis techniques for continuous glucose monitoring derived time series in diabetic patients. Frontiers in Physiology 9: 1257. doi: 10.3389/fphys.2018.01257 30237767

69. Ridderstrale M, Nilsson E (2008) Type 2 diabetes candidate gene CAPN10: first, but not last. Curr Hypertens Rep 10: 19–24. 18367022

70. Paracchini V, Pedotti P, Taioli E (2005) Genetics of leptin and obesity: a HuGE review. Am J Epidemiol 162: 101–114. doi: 10.1093/aje/kwi174 15972940

71. Myers MG Jr., Leibel RL, Seeley RJ, Schwartz MW (2010) Obesity and leptin resistance: distinguishing cause from effect. Trends Endocrinol Metab 21: 643–651. doi: 10.1016/j.tem.2010.08.002 20846876

72. Zhang S, Zhang Q, Zhang L, Li C, Jiang H (2013) Expression of ghrelin and leptin during the development of type 2 diabetes mellitus in a rat model. Mol Med Rep 7: 223–228. doi: 10.3892/mmr.2012.1154 23129112

73. Westermark P, Andersson A, Westermark GT (2011) Islet amyloid polypeptide, islet amyloid, and diabetes mellitus. Physiol Rev 91: 795–826. doi: 10.1152/physrev.00042.2009 21742788

74. Wagner G, Schwenk P (2000) Evolutionarily stable configurations: functional integration and the evolution of phenotypic stability. Evolutionary Biology 31: 155–217.

75. Gilks WP, Abbott JK, Morrow EH (2014) Sex differences in disease genetics: evidence, evolution, and detection. Trends Genet 30: 453–463. doi: 10.1016/j.tig.2014.08.006 25239223

76. Parks BW, Sallam T, Mehrabian M, Psychogios N, Hui ST, et al. (2015) Genetic architecture of insulin resistance in the mouse. Cell Metab 21: 334–347. doi: 10.1016/j.cmet.2015.01.002 25651185

77. da Silva RP, Zampieri TT, Pedroso JA, Nagaishi VS, Ramos-Lobo AM, et al. (2014) Leptin resistance is not the primary cause of weight gain associated with reduced sex hormone levels in female mice. Endocrinology 155: 4226–4236. doi: 10.1210/en.2014-1276 25144922

78. Shi H, Strader AD, Sorrell JE, Chambers JB, Woods SC, et al. (2008) Sexually different actions of leptin in proopiomelanocortin neurons to regulate glucose homeostasis. Am J Physiol Endocrinol Metab 294: E630–639. doi: 10.1152/ajpendo.00704.2007 18171913

79. Woittiez NJ, Roep BO (2015) Impact of disease heterogeneity on treatment efficacy of immunotherapy in Type 1 diabetes: different shades of gray. Immunotherapy 7: 163–174. doi: 10.2217/imt.14.104 25713991

80. Melmed S, Polonsky K, Larsen P, Kronenberger H (2011) Williams textbook of endocrinology: Saunders.


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