Genes and Pathways Contributing to Obesity: A Systems Biology View

Progress in Molecular Biology and Translational Science

Volumn 94, Issue , 2010, Pages 9-38

  Drake, Thomas A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Adipose tissue; Genetics; Liver; Networks; Obesity; Systems biology

Indexed keywords

ANIMAL; GENE REGULATORY NETWORK; GENETICS; HUMAN; METABOLISM; OBESITY; REVIEW; SYSTEMS BIOLOGY;

ANIMALS; GENE REGULATORY NETWORKS; HUMANS; METABOLIC NETWORKS AND PATHWAYS; OBESITY; SYSTEMS BIOLOGY;

EID: 79952756801     PISSN: 18771173     EISSN: 18780814     Source Type: Book Series    
DOI: 10.1016/B978-0-12-375003-7.00002-9     Document Type: Chapter

References (87)

1. Weiss, J.N., Yang, L., Qu, Z., Systems biology approaches to metabolic and cardiovascular disorders: network perspectives of cardiovascular metabolism. J Lipid Res 47 (2006), 2355–2366.
2. Ideker, T., Lauffenburger, D., Building with a scaffold: emerging strategies for high- to low-level cellular modeling. Trends Biotechnol 21 (2003), 255–262.
3. Ideker, T., Galitski, T., Hood, L., A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet 2 (2001), 343–372.
4. Kitano, H., Computational systems biology. Nature 420 (2002), 206–210.
5. Kitano, H., Systems biology: a brief overview. Science 295 (2002), 1662–1664.
6. Albert, R., Scale-free networks in cell biology. J Cell Sci 118 (2005), 4947–4957.
7. Barabasi, A.L., Scale-free networks: a decade and beyond. Science 325 (2009), 412–413.
8. Jeong, H., Mason, S.P., Barabasi, A.L., Oltvai, Z.N., Lethality and centrality in protein networks. Nature 411 (2001), 41–42.
9. Halaas, J.L., Gajiwala, K.S., Maffei, M., Cohen, S.L., Chait, B.T., Rabinowitz, D., et al. Weight-reducing effects of the plasma protein encoded by the obese gene. Science 269 (1995), 543–546.
10. Flint, J., Valdar, W., Shifman, S., Mott, R., Strategies for mapping and cloning quantitative trait genes in rodents. Nat Rev Genet 6 (2005), 271–286.
11. Lindgren, C.M., Heid, I.M., Randall, J.C., Lamina, C., Steinthorsdottir, V., Qi, L., et al. Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS Genet, 5, 2009, e1000508.
12. Jansen, R.C., Nap, J.P., Genetical genomics: the added value from segregation. Trends Genet 17 (2001), 388–391.
13. Drake, T.A., Schadt, E.E., Davis, R.C., Lusis, A.J., Integrating genetic and gene expression data to study the metabolic syndrome and diabetes in mice. Am J Ther 12 (2005), 503–511.
14. Rockman, M.V., Kruglyak, L., Genetics of global gene expression. Nat Rev Genet 7 (2006), 862–872.
15. Aten, J.E., Fuller, T.F., Lusis, A.J., Horvath, S., Using genetic markers to orient the edges in quantitative trait networks: the NEO software. BMC Syst Biol, 2, 2008, 34.
16. Schadt, E.E., Lamb, J., Yang, X., Zhu, J., Edwards, S., Guhathakurta, D., et al. An integrative genomics approach to infer causal associations between gene expression and disease. Nat Genet 37 (2005), 710–717.
17. Benson, M., Breitling, R., Network theory to understand microarray studies of complex diseases. Curr Mol Med 6 (2006), 695–701.
18. Schadt, E.E., Molecular networks as sensors and drivers of common human diseases. Nature 461 (2009), 218–223.
19. Wu, S., Lusis, A.J., Drake, T.A., A systems-based framework for understanding complex metabolic and cardiovascular disorders. J Lipid Res 50:Suppl. (2009), S358–S363.
20. Langfelder, P., Horvath, S., WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics, 9, 2008, 559.
21. van Nas, A., Guhathakurta, D., Wang, S.S., Yehya, N., Horvath, S., Zhang, B., et al. Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks. Endocrinology 150 (2009), 1235–1249.
22. Dobrin, R., Zhu, J., Molony, C., Argman, C., Parrish, M.L., Carlson, S., et al. Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease. Genome Biol, 10, 2009, R55.
23. Gargalovic, P.S., Imura, M., Zhang, B., Gharavi, N.M., Clark, M.J., Pagnon, J., et al. Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids. Proc Natl Acad Sci USA 103 (2006), 12741–12746.
24. Romanoski, C.E., Lee, S., Kim, M.J., Ingram-Drake, L., Plaisier, C.L., Yordanova, R., et al. Systems genetics analysis of gene-by-environment interactions in human cells. Am J Hum Genet 86 (2010), 399–410.
25. Chen, M., Kendziorski, C., A statistical framework for expression quantitative trait loci mapping. Genetics 177 (2007), 761–771.
26. Cookson, W., Liang, L., Abecasis, G., Moffatt, M., Lathrop, M., Mapping complex disease traits with global gene expression. Nat Rev Genet 10 (2009), 184–194.
27. Drake, T.A., Schadt, E.E., Lusis, A.J., Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice. Mamm Genome 17 (2006), 466–479.
28. Farber, C.R., Lusis, A.J., Integrating global gene expression analysis and genetics. Adv Genet 60 (2008), 571–601.
29. Franke, L., Jansen, R.C., eQTL analysis in humans. Methods Mol Biol 573 (2009), 311–328.
30. Li, Y., Breitling, R., Jansen, R.C., Generalizing genetical genomics: getting added value from environmental perturbation. Trends Genet 24 (2008), 518–524.
31. Pomp, D., Nehrenberg, D., Estrada-Smith, D., Complex genetics of obesity in mouse models. Annu Rev Nutr 28 (2008), 331–345.
32. Skelly, D.A., Ronald, J., Akey, J.M., Inherited variation in gene expression. Annu Rev Genomics Hum Genet 10 (2009), 313–332.
33. Tesson, B.M., Jansen, R.C., eQTL analysis in mice and rats. Methods Mol Biol 573 (2009), 285–309.
34. Doss, S., Schadt, E.E., Drake, T.A., Lusis, A.J., Cis-acting expression quantitative trait loci in mice. Genome Res 15 (2005), 681–691.
35. Ghazalpour, A., Doss, S., Sheth, S.S., Ingram-Drake, L.A., Schadt, E.E., Lusis, A.J., et al. Genomic analysis of metabolic pathway gene expression in mice. Genome Biol, 6, 2005, R59.
36. Yang, X., Deignan, J.L., Qi, H., Zhu, J., Qian, S., Zhong, J., et al. Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks. Nat Genet 41 (2009), 415–423.
37. Chen, Y., Zhu, J., Lum, P.Y., Yang, X., Pinto, S., MacNeil, D.J., et al. Variations in DNA elucidate molecular networks that cause disease. Nature 452 (2008), 429–435.
38. Ghazalpour, A., Doss, S., Zhang, B., Wang, S., Plaisier, C., Castellanos, R., et al. Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet, 2, 2006, e130.
39. Lusis, A.J., Attie, A.D., Reue, K., Metabolic syndrome: from epidemiology to systems biology. Nat Rev Genet 9 (2008), 819–830.
40. Iyer, A., Fairlie, D.P., Prins, J.B., Hammock, B.D., Brown, L., Inflammatory lipid mediators in adipocyte function and obesity. Nat Rev Endocrinol 6 (2010), 71–82.
41. Maury, E., Brichard, S.M., Adipokine dysregulation, adipose tissue inflammation and metabolic syndrome. Mol Cell Endocrinol 314 (2010), 1–16.
42. Nishimura, S., Manabe, I., Nagai, R., Adipose tissue inflammation in obesity and metabolic syndrome. Discov Med 8 (2009), 55–60.
43. Emilsson, V., Thorleifsson, G., Zhang, B., Leonardson, A.S., Zink, F., Zhu, J., et al. Genetics of gene expression and its effect on disease. Nature 452 (2008), 423–428.
44. Dimas, A.S., Deutsch, S., Stranger, B.E., Montgomery, S.B., Borel, C., Attar-Cohen, H., et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science 325 (2009), 1246–1250.
45. Cheung, V.G., Spielman, R.S., Ewens, K.G., Weber, T.M., Morley, M., Burdick, J.T., Mapping determinants of human gene expression by regional and genome-wide association. Nature 437 (2005), 1365–1369.
46. Dixon, A.L., Liang, L., Moffatt, M.F., Chen, W., Heath, S., Wong, K.C., et al. A genome-wide association study of global gene expression. Nat Genet 39 (2007), 1202–1207.
47. Goring, H.H., Curran, J.E., Johnson, M.P., Dyer, T.D., Charlesworth, J., Cole, S.A., et al. Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet 39 (2007), 1208–1216.
48. Stranger, B.E., Nica, A.C., Forrest, M.S., Dimas, A., Bird, C.P., Beazley, C., et al. Population genomics of human gene expression. Nat Genet 39 (2007), 1217–1224.
49. Myers, A.J., Gibbs, J.R., Webster, J.A., Rohrer, K., Zhao, A., Marlowe, L., et al. A survey of genetic human cortical gene expression. Nat Genet 39 (2007), 1494–1499.
50. Schadt, E.E., Molony, C., Chudin, E., Hao, K., Yang, X., Lum, P.Y., et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol, 6, 2008, e107.
51. Hagg, S., Skogsberg, J., Lundstrom, J., Noori, P., Nilsson, R., Zhong, H., et al. Multi-organ expression profiling uncovers a gene module in coronary artery disease involving transendothelial migration of leukocytes and LIM domain binding 2: the Stockholm Atherosclerosis Gene Expression (STAGE) study. PLoS Genet, 5, 2009, e1000754.
52. Grundberg, E., Kwan, T., Ge, B., Lam, K.C., Koka, V., Kindmark, A., et al. Population genomics in a disease targeted primary cell model. Genome Res 19 (2009), 1942–1952.
53. Wang, K., Narayanan, M., Zhong, H., Tompa, M., Schadt, E.E., Zhu, J., Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases. PLoS Comput Biol, 5, 2009, e1000616.
54. Ferrara, C.T., Wang, P., Neto, E.C., Stevens, R.D., Bain, J.R., Wenner, B.R., et al. Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling. PLoS Genet, 4, 2008, e1000034.
55. Illig, T., Gieger, C., Zhai, G, Romisch-Margl, W., Wang-Sattler, R., Prehn, C., et al. A genome-wide perspective of genetic variation in human metabolism. Nat Genet 42 (2010), 137–141.
56. Hicks, A.A., Pramstaller, P.P., Johansson, A., Vitart, V., Rudan, I., Ugocsai, P., et al. Genetic determinants of circulating sphingolipid concentrations in European populations. PLoS Genet, 5, 2009, e1000672.
57. Palsson, B., Metabolic systems biology. FEBS Lett 583 (2009), 3900–3904.
58. Mo, M.L., Palsson, B.O., Understanding human metabolic physiology: a genome-to-systems approach. Trends Biotechnol 27 (2009), 37–44.
59. Sigurdsson, M.I., Jamshidi, N., Jonsson, J.J., Palsson, B.O., Genome-scale network analysis of imprinted human metabolic genes. Epigenetics 4 (2009), 43–46.
60. Oberhardt, M.A., Palsson, B.O., Papin, J.A., Applications of genome-scale metabolic reconstructions. Mol Syst Biol, 5, 2009, 320.
61. Shlomi, T., Cabili, M.N., Herrgard, M.J., Palsson, B.O., Ruppin, E., Network-based prediction of human tissue-specific metabolism. Nat Biotechnol 26 (2008), 1003–1010.
62. Duarte, N.C., Becker, S.A., Jamshidi, N., Thiele, I., Mo, M.L., Vo, T.D., et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci USA 104 (2007), 1777–1782.
63. Jamshidi, N., Palsson, B.O., Systems biology of SNPs. Mol Syst Biol, 2, 2006, 38.
64. Li, F., Thiele, I., Jamshidi, N., Palsson, B.O., Identification of potential pathway mediation targets in Toll-like receptor signaling. PLoS Comput Biol, 5, 2009, e1000292.
65. Chesler, E.J., Miller, D.R., Branstetter, L.R., Galloway, L.D., Jackson, B.L., Philip, V.M., et al. The Collaborative Cross at Oak Ridge National Laboratory: developing a powerful resource for systems genetics. Mamm Genome 19 (2008), 382–389.
66. Churchill, G.A., Airey, D.C., Allayee, H., Angel, J.M., Attie, A.D., Beatty, J., et al. The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nat Genet 36 (2004), 1133–1137.
67. Bennett, B.J., Farber, C.R., Orozco, L., Kang, H.M., Ghazalpour, A., Siemers, N., et al. A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Res 20 (2010), 281–290.
68. Grubb, S.C., Maddatu, T.P., Bult, C.J., Bogue, M.A., Mouse phenome database. Nucleic Acids Res 37 (2009), D720–D730.
69. Bharucha, K.N., The epicurean fly: using Drosophila melanogaster to study metabolism. Pediatr Res 65 (2009), 132–137.
70. DiAngelo, J.R., Birnbaum, M.J., Regulation of fat cell mass by insulin in Drosophila melanogaster. Mol Cell Biol 29 (2009), 6341–6352.
71. Flynn, E.J. III, Trent, C.M., Rawls, J.F., Ontogeny and nutritional control of adipogenesis in zebrafish (Danio rerio). J Lipid Res 50 (2009), 1641–1652.
72. Jones, K.T., Ashrafi, K., Caenorhabditis elegans as an emerging model for studying the basic biology of obesity. Dis Model Mech 2 (2009), 224–229.
73. Mak, H.Y., Nelson, L.S., Basson, M., Johnson, C.D., Ruvkun, G., Polygenic control of Caenorhabditis elegans fat storage. Nat Genet 38 (2006), 363–368.
74. Ruden, D.M., Lu, X., Evolutionary conservation of metabolism explains how Drosophila nutrigenomics can help us understand human nutrigenomics. Genes Nutr 1 (2006), 75–83.
75. Schlegel, A., Stainier, D.Y., Lessons from “lower” organisms: what worms, flies, and zebrafish can teach us about human energy metabolism. PLoS Genet, 3, 2007, e199.
76. Watts, J.L., Fat synthesis and adiposity regulation in Caenorhabditis elegans. Trends Endocrinol Metab 20 (2009), 58–65.
77. Rada-Iglesias, A., Ameur, A., Kapranov, P., Enroth, S., Komorowski, J., Gingeras, T.R., et al. Whole-genome maps of USF1 and USF2 binding and histone H3 acetylation reveal new aspects of promoter structure and candidate genes for common human disorders. Genome Res 18 (2008), 380–392.
78. Ansorge, W.J., Next-generation DNA sequencing techniques. N Biotechnol 25 (2009), 195–203.
79. Zhu, J., Zhang, B., Smith, E.N., Drees, B., Brem, R.B., Kruglyak, L., et al. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat Genet 40 (2008), 854–861.
80. Wingren, C., Borrebaeck, C.A., Antibody-based microarrays. Methods Mol Biol 509 (2009), 57–84.
81. Oresic, M., Metabolomics, a novel tool for studies of nutrition, metabolism and lipid dysfunction. Nutr Metab Cardiovasc Dis 19 (2009), 816–824.
82. Gstaiger, M., Aebersold, R., Applying mass spectrometry-based proteomics to genetics, genomics and network biology. Nat Rev Genet 10 (2009), 617–627.
83. Voshol, H., Ehrat, M., Traenkle, J., Bertrand, E., van Oostrum, J., Antibody-based proteomics: analysis of signaling networks using reverse protein arrays. FEBS J 276 (2009), 6871–6879.
84. Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13 (2003), 2498–2504.
85. Mehrabian, M., Allayee, H., Stockton, J., Lum, P.Y., Drake, T.A., Castellani, L.W., et al. Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits. Nat Genet 37 (2005), 1224–1233.
86. Wu, S., Mar-Heyming, R., Dugum, E.Z., Kolaitis, N.A., Qi, H., Pajukanta, P., et al. Upstream Please provide volume and page numbers for this reference. transcription factor 1 influences plasma lipid and metabolic traits in mice. Hum Mol Genet 19 (2009), 597–608.
87. Tu, Z., Argmann, C., Wong, K.K., Mitnaul, L.J., Edwards, S., Sach, I.C., et al. Integrating siRNA and protein–protein interaction data to identify an expanded insulin signaling network. Genome Res 19 (2009), 1057–1067.