Sexually-dimorphic targeting of functionally-related genes in COPD

BMC Systems Biology

Dawn L DeMeo⁴  Guo-Cheng Yuan²  Stephen I Rennard³  Bartolome Celli⁴  Edwin K Silverman⁴  John Quackenbush¹  Kimberly Glass¹ 

[1] Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA;Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA;Division of Pulmonary, Critical Care, Sleep and Allergy, University of Nebraska Medical Center, Omaha, NE, USA;Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA

关键词: Chronic Obstructive Lung Disease;    Sexual-dimorphism;    Regulatory networks;    Gene regulation;    Network modeling;   

Others  :  1091515
DOI  :  10.1186/s12918-014-0118-y

 received in 2014-08-11, accepted in 2014-10-09,  发布年份 2014

【 摘 要 】

Background

There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism.

Results

Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways.

Conclusions

Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.

【 授权许可】

   
2014 Glass et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Heron M: Deaths: leading causes for 2010. Natl Vital Stat Rep 2013, 62(6):1-97.
• [2]Silverman EK, Weiss ST, Drazen JM, Chapman HA, Carey V, Campbell EJ, Denish P, Silverman RA, Celedon JC, Reilly JJ, Ginns LC, Speizer FE: Gender-related differences in severe, early-onset chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2000, 162(6):2152-2158.
• [3]Sin DD, Cohen SB, Day A, Coxson H, Pare PD: Understanding the biological differences in susceptibility to chronic obstructive pulmonary disease between men and women. Proc Am Thorac Soc 2007, 4(8):671-674.
• [4]Han MK, Postma D, Mannino DM, Giardino ND, Buist S, Curtis JL, Martinez FJ: Gender and chronic obstructive pulmonary disease: why it matters. Am J Respir Crit Care Med 2007, 176(12):1179-1184.
• [5]Sorheim IC, Johannessen A, Gulsvik A, Bakke PS, Silverman EK, DeMeo DL: Gender differences in COPD: are women more susceptible to smoking effects than men? Thorax 2010, 65(6):480-485.
• [6]Martinez FJ, Curtis JL, Sciurba F, Mumford J, Giardino ND, Weinmann G, Kazerooni E, Murray S, Criner GJ, Sin DD, Hogg J, Ries AL, Han M, Fishman AP, Make B, Hoffman EA, Mohsenifar Z, Wise R: Sex differences in severe pulmonary emphysema. Am J Respir Crit Care Med 2007, 176(3):243-252.
• [7]Hemsing N, Greaves L: Women, environments and chronic disease: shifting the gaze from individual level to structural factors. Environ Health Insights 2009, 2:127-135.
• [8]Schiebinger L: Scientific research must take gender into account. Nature 2014, 507(7490):9.
• [9]Pollitzer E: Biology: cell sex matters. Nature 2013, 500(7460):23-24.
• [10]Kim AM, Tingen CM, Woodruff TK: Sex bias in trials and treatment must end. Nature 2010, 465(7299):688-689.
• [11]Vige A, Gallou-Kabani C, Junien C: Sexual dimorphism in non-Mendelian inheritance. Pediatr Res 2008, 63(4):340-347.
• [12]van Nas A, Guhathakurta D, Wang SS, Yehya N, Horvath S, Zhang B, Ingram-Drake L, Chaudhuri G, Schadt EE, Drake TA, Arnold AP, Lusis AJ: Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks. Endocrinology 2009, 150(3):1235-1249.
• [13]Civelek M, Lusis AJ: Systems genetics approaches to understand complex traits. Nat Rev Genet 2014, 15(1):34-48.
• [14]Arnold AP, Lusis AJ: Understanding the sexome: measuring and reporting sex differences in gene systems. Endocrinology 2012, 153(6):2551-2555.
• [15]D’Haeseleer P, Liang S, Somogyi R: Genetic network inference: from co-expression clustering to reverse engineering. Bioinformatics 2000, 16(8):707-726.
• [16]Guthke R, Moller U, Hoffmann M, Thies F, Topfer S: Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection. Bioinformatics 2005, 21(8):1626-1634.
• [17]Hartemink AJ, Gifford DK, Jaakkola TS, Young RA: Combining location and expression data for principled discovery of genetic regulatory network models. Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing 2002, 437-449.
• [18]Kato T, Tsuda K, Asai K: Selective integration of multiple biological data for supervised network inference. Bioinformatics 2005, 21(10):2488-2495.
• [19]Youn A, Reiss DJ, Stuetzle W: Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model. Bioinformatics 2010, 26(15):1879-1886.
• [20]Hecker M, Lambeck S, Toepfer S, van Someren E, Guthke R: Gene regulatory network inference: data integration in dynamic models-a review. Biosystems 2009, 96(1):86-103.
• [21]Glass K, Huttenhower C, Quackenbush J, Yuan GC: Passing messages between biological networks to refine predicted interactions. PLoS One 2013, 8(5):e64832.
• [22]Glass K, Quackenbush J, Spentzos D, Haibe-Kains B, Yuan GC: A Network Model for Angiogenesis in Ovarian Cancer (submitted). 2014.
• [23]Bjornstrom L, Sjoberg M: Mechanisms of estrogen receptor signaling: convergence of genomic and nongenomic actions on target genes. Mol Endocrinol 2005, 19(4):833-842.
• [24]Heemers HV, Tindall DJ: Androgen receptor (AR) coregulators: a diversity of functions converging on and regulating the AR transcriptional complex. Endocr Rev 2007, 28(7):778-808.
• [25]Singh D, Fox SM, Tal-Singer R, Plumb J, Bates S, Broad P, Riley JH, Celli B: Induced sputum genes associated with spirometric and radiological disease severity in COPD ex-smokers. Thorax 2011, 66(6):489-495.
• [26]Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003, 4(2):249-264.
• [27]Dai M, Wang P, Boyd AD, Kostov G, Athey B, Jones EG, Bunney WE, Myers RM, Speed TP, Akil H, Watson SJ, Meng F: Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res 2005, 33(20):e175.
• [28]Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 2005, 102(43):15545-15550.
• [29]Berenson CS, Kruzel RL, Eberhardt E, Sethi S: Phagocytic dysfunction of human alveolar macrophages and severity of chronic obstructive pulmonary disease. J Infect Dis 2013, 208(12):2036-2045.
• [30]Taylor AE, Finney-Hayward TK, Quint JK, Thomas CM, Tudhope SJ, Wedzicha JA, Barnes PJ, Donnelly LE: Defective macrophage phagocytosis of bacteria in COPD. Eur Respir J 2010, 35(5):1039-1047.
• [31]Elowitz MB, Levine AJ, Siggia ED, Swain PS: Stochastic gene expression in a single cell. Science 2002, 297(5584):1183-1186.
• [32]Neuert G, Munsky B, Tan RZ, Teytelman L, Khammash M, van Oudenaarden A: Systematic identification of signal-activated stochastic gene regulation. Science 2013, 339(6119):584-587.
• [33]Sandelin A, Alkema W, Engstrom P, Wasserman WW, Lenhard B: JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res 2004, 32(Database issue):D91-D94.
• [34]Ravasi T, Suzuki H, Cannistraci CV, Katayama S, Bajic VB, Tan K, Akalin A, Schmeier S, Kanamori-Katayama M, Bertin N, Carninci P, Daub CO, Forrest AR, Gough J, Grimmond S, Han JH, Hashimoto T, Hide W, Hofmann O, Kamburov A, Kaur M, Kawaji H, Kubosaki A, Lassmann T, van Nimwegen E, MacPherson CR, Ogawa C, Radovanovic A, Schwartz A, Teasdale RD, et al.: An atlas of combinatorial transcriptional regulation in mouse and man. Cell 2010, 140(5):744-752.
• [35]Wu CFJ: Bootstrap and other resampling methods in regression analysis. Ann Stat 1986, 14(4):1261-1295.
• [36]Karnam G, Rygiel TP, Raaben M, Grinwis GC, Coenjaerts FE, Ressing ME, Rottier PJ, de Haan CA, Meyaard L: CD200 receptor controls sex-specific TLR7 responses to viral infection. PLoS Pathog 2012, 8(5):e1002710.
• [37]Geurs TL, Hill EB, Lippold DM, French AR: Sex differences in murine susceptibility to systemic viral infections. J Autoimmun 2012, 38(2–3):J245-J253.
• [38]Hughes GC: Progesterone and autoimmune disease. Autoimmun Rev 2012, 11(6–7):A502-A514.
• [39]Faner R, Gonzalez N, Cruz T, Kalko SG, Agusti A: Systemic inflammatory response to smoking in chronic obstructive pulmonary disease: evidence of a gender effect. PLoS One 2014, 9(5):e97491.
• [40]Aravamudan B, Thompson MA, Pabelick CM, Prakash YS: Mitochondria in lung diseases. Expert Rev Respir Med 2013, 7(6):631-646.
• [41]Hara H, Araya J, Ito S, Kobayashi K, Takasaka N, Yoshii Y, Wakui H, Kojima J, Shimizu K, Numata T, Kawaishi M, Kamiya N, Odaka M, Morikawa T, Kaneko Y, Nakayama K, Kuwano K: Mitochondrial fragmentation in cigarette smoke-induced bronchial epithelial cell senescence. Am J Physiol Lung Cell Mol Physiol 2013, 305(10):L737-L746.
• [42]Hoffmann RF, Zarrintan S, Brandenburg SM, Kol A, de Bruin HG, Jafari S, Dijk F, Kalicharan D, Kelders M, Gosker HR, Ten Hacken NH, van der Want JJ, van Oosterhout AJ, Heijink IH: Prolonged cigarette smoke exposure alters mitochondrial structure and function in airway epithelial cells. Respir Res 2013, 14:97. BioMed Central Full Text
• [43]Puente-Maestu L, Perez-Parra J, Godoy R, Moreno N, Tejedor A, Gonzalez-Aragoneses F, Bravo JL, Alvarez FV, Camano S, Agusti A: Abnormal mitochondrial function in locomotor and respiratory muscles of COPD patients. Eur Respir J 2009, 33(5):1045-1052.
• [44]Meyer A, Zoll J, Charles AL, Charloux A, de Blay F, Diemunsch P, Sibilia J, Piquard F, Geny B: Skeletal muscle mitochondrial dysfunction during chronic obstructive pulmonary disease: central actor and therapeutic target. Exp Physiol 2013, 98(6):1063-1078.
• [45]Wolff JN, Gemmell NJ: Mitochondria, maternal inheritance, and asymmetric fitness: why males die younger. Bioessays 2013, 35(2):93-99.
• [46]Camus MF, Clancy DJ, Dowling DK: Mitochondria, maternal inheritance, and male aging. Curr Biol 2012, 22(18):1717-1721.
• [47]Gavrilova-Jordan LP, Price TM: Actions of steroids in mitochondria. Semin Reprod Med 2007, 25(3):154-164.
• [48]Yager JD, Chen JQ: Mitochondrial estrogen receptors–new insights into specific functions. Trends Endocrinol Metab 2007, 18(3):89-91.
• [49]Klinge CM: Estrogenic control of mitochondrial function and biogenesis. J Cell Biochem 2008, 105(6):1342-1351.
• [50]Capllonch-Amer G, Llado I, Proenza AM, Garcia-Palmer FJ, Gianotti M: Opposite effects of 17-beta estradiol and testosterone on mitochondrial biogenesis and adiponectin synthesis in white adipocytes. J Mol Endocrinol 2014, 52(2):203-214.
• [51]Yang SH, Liu R, Perez EJ, Wen Y, Stevens SM Jr, Valencia T, Brun-Zinkernagel AM, Prokai L, Will Y, Dykens J, Koulen P, Simpkins JW: Mitochondrial localization of estrogen receptor beta. Proc Natl Acad Sci U S A 2004, 101(12):4130-4135.
• [52]Yang SH, Sarkar SN, Liu R, Perez EJ, Wang X, Wen Y, Yan LJ, Simpkins JW: Estrogen receptor beta as a mitochondrial vulnerability factor. J Biol Chem 2009, 284(14):9540-9548.
• [53]Manente AG, Valenti D, Pinton G, Jithesh PV, Daga A, Rossi L, Gray SG, O’Byrne KJ, Fennell DA, Vacca RA, Nilsson S, Mutti L, Moro L: Estrogen receptor beta activation impairs mitochondrial oxidative metabolism and affects malignant mesothelioma cell growth in vitro and in vivo. Oncogenesis 2013, 2:e72.
• [54]Simoes DC, Psarra AM, Mauad T, Pantou I, Roussos C, Sekeris CE, Gratziou C: Glucocorticoid and estrogen receptors are reduced in mitochondria of lung epithelial cells in asthma. PLoS One 2012, 7(6):e39183.
• [55]Remels AH, Schrauwen P, Broekhuizen R, Willems J, Kersten S, Gosker HR, Schols AM: Peroxisome proliferator-activated receptor expression is reduced in skeletal muscle in COPD. Eur Respir J 2007, 30(2):245-252.
• [56]Liang H, Ward WF: PGC-1alpha: a key regulator of energy metabolism. Adv Physiol Educ 2006, 30(4):145-151.
• [57]Austin S, St-Pierre J: PGC1alpha and mitochondrial metabolism–emerging concepts and relevance in ageing and neurodegenerative disorders. J Cell Sci 2012, 125(Pt 21):4963-4971.
• [58]Tharappel JC, Cholewa J, Espandiari P, Spear BT, Gairola CG, Glauert HP: Effects of cigarette smoke on the activation of oxidative stress-related transcription factors in female A/J mouse lung. J Toxicol Environ Health A 2010, 73(19):1288-1297.
• [59]Yang Z, Hikosaka K, Sharkar MT, Tamakoshi T, Chandra A, Wang B, Itakura T, Xue X, Uezato T, Kimura W, Miura N: The mouse forkhead gene Foxp2 modulates expression of the lung genes. Life Sci 2010, 87(1–2):17-25.
• [60]Hersh CP, Silverman EK, Gascon J, Bhattacharya S, Klanderman BJ, Litonjua AA, Lefebvre V, Sparrow D, Reilly JJ, Anderson WH, Lomas DA, Mariani TJ: SOX5 is a candidate gene for chronic obstructive pulmonary disease susceptibility and is necessary for lung development. Am J Respir Crit Care Med 2011, 183(11):1482-1489.
• [61]Han SH, Yang BC, Ko MS, Oh HS, Lee SS: Length difference between equine ZFX and ZFY genes and its application for molecular sex determination. J Assist Reprod Genet 2010, 27(12):725-728.
• [62]Jiang M, Xu S, Yue W, Zhao X, Zhang L, Zhang C, Wang Y: The role of ZFX in non-small cell lung cancer development. Oncol Res 2012, 20(4):171-178.
• [63]Zha W, Cao L, Shen Y, Huang M: Roles of mir-144-ZFX pathway in growth regulation of non-small-cell lung cancer. PLoS One 2013, 8(9):e74175.
• [64]Sakamoto KM, Frank DA: CREB in the pathophysiology of cancer: implications for targeting transcription factors for cancer therapy. Clin Cancer Res 2009, 15(8):2583-2587.
• [65]Paramanik V, Thakur MK: Role of CREB signaling in aging brain. Arch Ital Biol 2013, 151(1):33-42.
• [66]deGraffenried LA, Hopp TA, Valente AJ, Clark RA, Fuqua SA: Regulation of the estrogen receptor alpha minimal promoter by Sp1, USF-1 and ERalpha. Breast Cancer Res Treat 2004, 85(2):111-120.
• [67]Xing W, Archer TK: Upstream stimulatory factors mediate estrogen receptor activation of the cathepsin D promoter. Mol Endocrinol 1998, 12(9):1310-1321.
• [68]Ikeda K, Inoue S, Orimo A, Tsutsumi K, Muramatsu M: Promoter analysis of mouse estrogen-responsive finger protein (efp) gene: mouse efp promoter contains an E-box that is also conserved in human. Gene 1998, 216(1):155-162.
• [69]Dillner NB, Sanders MM: Upstream stimulatory factor (USF) is recruited into a steroid hormone-triggered regulatory circuit by the estrogen-inducible transcription factor delta EF1. J Biol Chem 2002, 277(37):33890-33894.
• [70]Dasgupta C, Chen M, Zhang H, Yang S, Zhang L: Chronic hypoxia during gestation causes epigenetic repression of the estrogen receptor-alpha gene in ovine uterine arteries via heightened promoter methylation. Hypertension 2012, 60(3):697-704.
• [71]Jiang B, Mendelson CR: USF1 and USF2 mediate inhibition of human trophoblast differentiation and CYP19 gene expression by Mash-2 and hypoxia. Mol Cell Biol 2003, 23(17):6117-6128.
• [72]Wang F, Samudio I, Safe S: Transcriptional activation of cathepsin D gene expression by 17beta-estradiol: mechanism of aryl hydrocarbon receptor-mediated inhibition. Mol Cell Endocrinol 2001, 172(1–2):91-103.
• [73]Mollerup S, Berge G, Baera R, Skaug V, Hewer A, Phillips DH, Stangeland L, Haugen A: Sex differences in risk of lung cancer: expression of genes in the PAH bioactivation pathway in relation to smoking and bulky DNA adducts. Int J Cancer 2006, 119(4):741-744.
• [74]Fan YM, Hernesniemi J, Oksala N, Levula M, Raitoharju E, Collings A, Hutri-Kahonen N, Juonala M, Marniemi J, Lyytikainen LP, Seppala I, Mennander A, Tarkka M, Kangas AJ, Soininen P, Salenius JP, Klopp N, Illig T, Laitinen T, Ala-Korpela M, Laaksonen R, Viikari J, Kähönen M, Raitakari OT, Lehtimäki T: Upstream Transcription Factor 1 (USF1) allelic variants regulate lipoprotein metabolism in women and USF1 expression in atherosclerotic plaque. Sci Rep 2014, 4:4650.
• [75]Wu S, Mar-Heyming R, Dugum EZ, Kolaitis NA, Qi H, Pajukanta P, Castellani LW, Lusis AJ, Drake TA: Upstream transcription factor 1 influences plasma lipid and metabolic traits in mice. Hum Mol Genet 2010, 19(4):597-608.
• [76]Rada-Iglesias A, Ameur A, Kapranov P, Enroth S, Komorowski J, Gingeras TR, Wadelius C: 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 2008, 18(3):380-392.
• [77]Irrcher I, Ljubicic V, Hood DA: Interactions between ROS and AMP kinase activity in the regulation of PGC-1alpha transcription in skeletal muscle cells. Am J Physiol Cell Physiol 2009, 296(1):C116-C123.
• [78]Yoboue ED, Devin A: Reactive oxygen species-mediated control of mitochondrial biogenesis. Int J Cell Biol 2012, 2012:403870.
• [79]Restrepo J, Ott E, Hunt B: Characterizing the dynamical importance of network nodes and links. Phys Rev Lett 2006, 97(9):094102.
• [80]Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U: Network motifs: simple building blocks of complex networks. Science 2002, 298(5594):824-827.
• [81]Barabasi AL, Albert R: Emergence of scaling in random networks. Science 1999, 286(5439):509-512.
• [82]Girvan M, Newman ME: Community structure in social and biological networks. Proc Natl Acad Sci U S A 2002, 99(12):7821-7826.
• [83]Ma H, Sorokin A, Mazein A, Selkov A, Selkov E, Demin O, Goryanin I: The Edinburgh human metabolic network reconstruction and its functional analysis. Mol Syst Biol 2007, 3:135.
• [84]Stormo GD: DNA binding sites: representation and discovery. Bioinformatics 2000, 16(1):16-23.
• [85]Wasserman WW, Sandelin A: Applied bioinformatics for the identification of regulatory elements. Nat Rev Genet 2004, 5(4):276-287.