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Current Medicinal Chemistry

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ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

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Review Article

Mechanistic Insights of Chemicals and Drugs as Risk Factors for Systemic Lupus Erythematosus

Author(s): Qingjun Pan*, Yun Guo*, Linjie Guo*, Shuzhen Liao, Chunfei Zhao, Sijie Wang and Hua-Feng Liu

Volume 27, Issue 31, 2020

Page: [5175 - 5188] Pages: 14

DOI: 10.2174/0929867326666190404140658

Price: $65

Abstract

Systemic Lupus Erythematosus (SLE) is a chronic and relapsing heterogenous autoimmune disease that primarily affects women of reproductive age. Genetic and environmental risk factors are involved in the pathogenesis of SLE, and susceptibility genes have recently been identified. However, as gene therapy is far from clinical application, further investigation of environmental risk factors could reveal important therapeutic approaches. We systematically explored two groups of environmental risk factors: chemicals (including silica, solvents, pesticides, hydrocarbons, heavy metals, and particulate matter) and drugs (including procainamide, hydralazine, quinidine, Dpenicillamine, isoniazid, and methyldopa). Furthermore, the mechanisms underlying risk factors, such as genetic factors, epigenetic change, and disrupted immune tolerance, were explored. This review identifies novel risk factors and their underlying mechanisms. Practicable measures for the management of these risk factors will benefit SLE patients and provide potential therapeutic strategies.

Keywords: Risk factors, Systemic Lupus Erythematosus, autoimmunity, genetic factors, epigenetic change, immune tolerance.

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[1]
Rekvig, O.P.; Van der Vlag, J. The pathogenesis and diagnosis of systemic lupus erythematosus: still not resolved. Semin. Immunopathol., 2014, 36(3), 301-311.
[http://dx.doi.org/10.1007/s00281-014-0428-6] [PMID: 24763531]
[2]
Kaul, A.; Gordon, C.; Crow, M.K.; Touma, Z.; Urowitz, M.B.; van Vollenhoven, R.; Ruiz-Irastorza, G.; Hughes, G. Systemic lupus erythematosus. Nat. Rev. Dis. Primers, 2016, 2, 16039.
[http://dx.doi.org/10.1038/nrdp.2016.39] [PMID: 27306639]
[3]
Meda, F.; Folci, M.; Baccarelli, A.; Selmi, C. The epigenetics of autoimmunity. Cell. Mol. Immunol., 2011, 8(3), 226-236.
[http://dx.doi.org/10.1038/cmi.2010.78] [PMID: 21278766]
[4]
Ren, J.; Panther, E.; Liao, X.; Grammer, A.C.; Lipsky, P.E.; Reilly, C.M. The impact of protein acetylation/deacetylation on systemic lupus erythematosus. Int. J. Mol. Sci., 2018, 19(12), 4007.
[http://dx.doi.org/10.3390/ijms19124007] [PMID: 30545086]
[5]
Gubbels Bupp, M.R.; Jorgensen, T.N. Androgen-induced immunosuppression. Front. Immunol., 2018, 9, 794.
[http://dx.doi.org/10.3389/fimmu.2018.00794] [PMID: 29755457]
[6]
Sharma, A.K.; Zhou, G.P.; Kupferman, J.; Surks, H.K.; Christensen, E.N.; Chou, J.J.; Mendelsohn, M.E.; Rigby, A.C. Probing the interaction between the coiled coil leucine zipper of cGMP-dependent protein kinase I alpha and the C terminus of the myosin binding subunit of the myosin light chain phosphatase. J. Biol. Chem., 2008, 283(47), 32860-32869.
[http://dx.doi.org/10.1074/jbc.M804916200] [PMID: 18782776]
[7]
Dev, J.; Park, D.; Fu, Q.; Chen, J.; Ha, H.J.; Ghantous, F.; Herrmann, T.; Chang, W.; Liu, Z.; Frey, G.; Seaman, M.S.; Chen, B.; Chou, J.J. Structural basis for membrane anchoring of HIV-1 envelope spike. Science, 2016, 353(6295), 172-175.
[http://dx.doi.org/10.1126/science.aaf7066] [PMID: 27338706]
[8]
Schnell, J.R.; Chou, J.J. Structure and mechanism of the M2 proton channel of influenza A virus. Nature, 2008, 451(7178), 591-595.
[http://dx.doi.org/10.1038/nature06531] [PMID: 18235503]
[9]
Berardi, M.J.; Shih, W.M.; Harrison, S.C.; Chou, J.J. Mitochondrial uncoupling protein 2 structure determined by NMR molecular fragment searching. Nature, 2011, 476(7358), 109-113.
[http://dx.doi.org/10.1038/nature10257] [PMID: 21785437]
[10]
OuYang, B.; Xie, S.; Berardi, M.J.; Zhao, X.; Dev, J.; Yu, W.; Sun, B.; Chou, J.J. Unusual architecture of the p7 channel from hepatitis C virus. Nature, 2013, 498(7455), 521-525.
[http://dx.doi.org/10.1038/nature12283] [PMID: 23739335]
[11]
Oxenoid, K.; Dong, Y.; Cao, C.; Cui, T.; Sancak, Y.; Markhard, A.L.; Grabarek, Z.; Kong, L.; Liu, Z.; Ouyang, B.; Cong, Y.; Mootha, V.K.; Chou, J.J. Architecture of the mitochondrial calcium uniporter. Nature, 2016, 533(7602), 269-273.
[http://dx.doi.org/10.1038/nature17656] [PMID: 27135929]
[12]
Chou, K.C.; Jones, D.; Heinrikson, R.L. Prediction of the tertiary structure and substrate binding site of caspase-8. FEBS Lett., 1997, 419(1), 49-54.
[http://dx.doi.org/10.1016/S0014-5793(97)01246-5] [PMID: 9426218]
[13]
Chou, K.C.; Tomasselli, A.G.; Heinrikson, R.L. Prediction of the tertiary structure of a caspase-9/inhibitor complex. FEBS Lett., 2000, 470(3), 249-256.
[http://dx.doi.org/10.1016/S0014-5793(00)01333-8] [PMID: 10745077]
[14]
Chou, K.C.; Howe, W.J. Prediction of the tertiary structure of the beta-secretase zymogen. Biochem. Biophys. Res. Commun., 2002, 292(3), 702-708.
[http://dx.doi.org/10.1006/bbrc.2002.6686] [PMID: 11922623]
[15]
Chou, K.C. Insights from modelling the 3D structure of the extracellular domain of alpha7 nicotinic acetylcholine receptor. Biochem. Biophys. Res. Commun., 2004, 319(2), 433-438.
[http://dx.doi.org/10.1016/j.bbrc.2004.05.016] [PMID: 15178425]
[16]
Chou, K.C. Modelling extracellular domains of GABA-A receptors: subtypes 1, 2, 3, and 5. Biochem. Biophys. Res. Commun., 2004, 316(3), 636-642.
[http://dx.doi.org/10.1016/j.bbrc.2004.02.098] [PMID: 15033447]
[17]
Chou, K.C. Coupling interaction between thromboxane A2 receptor and alpha-13 subunit of guanine nucleotide-binding protein. J. Proteome Res., 2005, 4(5), 1681-1686.
[http://dx.doi.org/10.1021/pr050145a] [PMID: 16212421]
[18]
Chou, K.C. Insights from modeling the tertiary structure of human BACE2. J. Proteome Res., 2004, 3(5), 1069-1072.
[http://dx.doi.org/10.1021/pr049905s] [PMID: 15473697]
[19]
Chou, K.C. Insights from modeling the 3D structure of DNA-CBF3b complex. J. Proteome Res., 2005, 4(5), 1657-1660.
[http://dx.doi.org/10.1021/pr050135+] [PMID: 16212418]
[20]
Chou, K.C. Modeling the tertiary structure of human cathepsin-E. Biochem. Biophys. Res. Commun., 2005, 331(1), 56-60.
[http://dx.doi.org/10.1016/j.bbrc.2005.03.123] [PMID: 15845357]
[21]
Chou, K.C. Structural bioinformatics and its impact to biomedical science. Curr. Med. Chem., 2004, 11(16), 2105-2134.
[http://dx.doi.org/10.2174/0929867043364667] [PMID: 15279552]
[22]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Aristoff, P.A.; Tarpley, W.G.; Reusser, F. Steady-state kinetic studies with the non-nucleoside HIV-1 reverse transcriptase inhibitor U-87201E. J. Biol. Chem., 1993, 268(9), 6119-6124.
[PMID: 7681060]
[23]
Althaus, I.W.; Gonzales, A.J.; Chou, J.J.; Romero, D.L.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Resnick, L.; Busso, M.E.; So, A.G. The quinoline U-78036 is a potent inhibitor of HIV-1 reverse transcriptase. J. Biol. Chem., 1993, 268(20), 14875-14880.
[PMID: 7686907]
[24]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; LeMay, R.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Thomas, R.C.; Aristoff, P.A. Steady-state kinetic studies with the polysulfonate U-9843, an HIV reverse transcriptase inhibitor. Experientia, 1994, 50(1), 23-28.
[http://dx.doi.org/10.1007/BF01992044] [PMID: 7507441]
[25]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Thomas, R.C.; Aristoff, P.A.; Tarpley, W.G. Kinetic studies with the non-nucleoside human immunodeficiency virus type-1 reverse transcriptase inhibitor U-90152E. Biochem. Pharmacol., 1994, 47(11), 2017-2028.
[http://dx.doi.org/10.1016/0006-2952(94)90077-9] [PMID: 7516658]
[26]
Althaus, I.W.; Chou, K.C.; Lemay, R.J.; Franks, K.M.; Deibel, M.R.; Kezdy, F.J.; Resnick, L.; Busso, M.E.; So, A.G.; Downey, K.M.; Romero, D.L.; Thomas, R.C.; Aristoff, P.A.; Tarpley, W.G.; Reusser, F. The benzylthio-pyrimidine U-31,355, a potent inhibitor of HIV-1 reverse transcriptase. Biochem. Pharmacol., 1996, 51(6), 743-750.
[http://dx.doi.org/10.1016/0006-2952(95)02390-9] [PMID: 8602869]
[27]
Chou, K.C.; Forsén, S. Graphical rules for enzyme-catalysed rate laws. Biochem. J., 1980, 187(3), 829-835.
[http://dx.doi.org/10.1042/bj1870829] [PMID: 7188428]
[28]
Zhou, G.P.; Deng, M.H. An extension of Chou’s graphic rules for deriving enzyme kinetic equations to systems involving parallel reaction pathways. Biochem. J., 1984, 222(1), 169-176.
[http://dx.doi.org/10.1042/bj2220169] [PMID: 6477507]
[29]
Chou, K.C.; Kézdy, F.J.; Reusser, F. Kinetics of processive nucleic acid polymerases and nucleases. Anal. Biochem., 1994, 221(2), 217-230.
[http://dx.doi.org/10.1006/abio.1994.1405] [PMID: 7529005]
[30]
Xu, Y.; Ding, J.; Wu, L.Y.; Chou, K.C. iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition. PLoS One, 2013, 8(2) e55844
[http://dx.doi.org/10.1371/journal.pone.0055844] [PMID: 23409062]
[31]
Xu, Y.; Shao, X.J.; Wu, L.Y.; Deng, N.Y.; Chou, K.C. iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins. PeerJ, 2013, 1 e171
[http://dx.doi.org/ 10.7717/peerj.171] [PMID: 24109555]
[32]
Qiu, W.R.; Xiao, X.; Lin, W.Z.; Chou, K.C. iMethyl-PseAAC: identification of protein methylation sites via a pseudo amino acid composition approach. BioMed Res. Int., 2014, 2014 947416
[http://dx.doi.org/10.1155/2014/947416] [PMID: 24977164]
[33]
Xu, Y.; Wen, X.; Shao, X.J.; Deng, N.Y.; Chou, K.C. iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition. Int. J. Mol. Sci., 2014, 15(5), 7594-7610.
[http://dx.doi.org/10.3390/ijms15057594] [PMID: 24857907]
[34]
Xu, Y.; Wen, X.; Wen, L.S.; Wu, L.Y.; Deng, N.Y.; Chou, K.C. iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition. PLoS One, 2014, 9(8) e105018
[http://dx.doi.org/10.1371/journal.pone.0105018] [PMID: 25121969]
[35]
Chen, W.; Feng, P.; Ding, H.; Lin, H.; Chou, K.C. iRNA-Methyl: identifying N(6)-methyladenosine sites using pseudo nucleotide composition. Anal. Biochem., 2015, 490, 26-33.
[http://dx.doi.org/10.1016/j.ab.2015.08.021] [PMID: 26314792]
[36]
Chen, W.; Tang, H.; Ye, J.; Lin, H.; Chou, K.C. iRNA-PseU: identifying RNA pseudouridine sites. Mol. Ther. Nucleic Acids, 2016, 5(7) e332
[http://dx.doi.org/10.1038/mtna.2016.37] [PMID: 28427142]
[37]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K.C. iSuc-PseOpt: identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into pseudo components and optimizing imbalanced training dataset. Anal. Biochem., 2016, 497, 48-56.
[http://dx.doi.org/10.1016/j.ab.2015.12.009] [PMID: 26723495]
[38]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K.C. pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach. J. Theor. Biol., 2016, 394, 223-230.
[http://dx.doi.org/10.1016/j.jtbi.2016.01.020] [PMID: 26807806]
[39]
Jia, J.; Zhang, L.; Liu, Z.; Xiao, X.; Chou, K.C. pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC. Bioinformatics, 2016, 32(20), 3133-3141.
[http://dx.doi.org/10.1093/bioinformatics/btw387] [PMID: 27354696]
[40]
Liu, Z.; Xiao, X.; Yu, D.J.; Jia, J.; Qiu, W.R.; Chou, K.C. pRNAm-Pc: predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties. Anal. Biochem., 2016, 497, 60-67.
[http://dx.doi.org/10.1016/j.ab.2015.12.017] [PMID: 26748145]
[41]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, Z.C.; Chou, K.C. iHyd-PseCp: identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC. Oncotarget, 2016, 7(28), 44310-44321.
[http://dx.doi.org/10.18632/oncotarget.10027] [PMID: 27322424]
[42]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, Z.C.; Chou, K.C. iPTM-mLys: identifying multiple lysine PTM sites and their different types. Bioinformatics, 2016, 32(20), 3116-3123.
[http://dx.doi.org/10.1093/bioinformatics/btw380] [PMID: 27334473]
[43]
Qiu, W.R.; Xiao, X.; Xu, Z.C.; Chou, K.C. iPhos-PseEn: identifying phosphorylation sites in proteins by fusing different pseudo components into an ensemble classifier. Oncotarget, 2016, 7(32), 51270-51283.
[http://dx.doi.org/10.18632/oncotarget.9987] [PMID: 27323404]
[44]
Xu, Y.; Chou, K.C. Recent progress in predicting posttranslational modification sites in proteins. Curr. Top. Med. Chem., 2016, 16(6), 591-603.
[http://dx.doi.org/10.2174/1568026615666150819110421] [PMID: 26286211]
[45]
Feng, P.; Ding, H.; Yang, H.; Chen, W.; Lin, H.; Chou, K.C. iRNA-PseColl: identifying the occurrence sites of different RNA modifications by incorporating collective effects of nucleotides into PseKNC. Mol. Ther. Nucleic Acids, 2017, 7, 155-163.
[http://dx.doi.org/10.1016/j.omtn.2017.03.006] [PMID: 28624191]
[46]
Liu, L.M.; Xu, Y.; Chou, K.C. iPGK-PseAAC: identify lysine phosphoglycerylation sites in proteins by incorporating four different tiers of amino acid pairwise coupling information into the general PseAAC. Med. Chem., 2017, 13(6), 552-559.
[http://dx.doi.org/10.2174/1573406413666170515120507] [PMID: 28521678]
[47]
Qiu, W.R.; Jiang, S.Y.; Sun, B.Q.; Xiao, X.; Cheng, X.; Chou, K.C. iRNA-2methyl: identify RNA 2′-O-methylation sites by incorporating sequence-coupled effects into general PseKNC and ensemble classifier. Med. Chem., 2017, 13(8), 734-743.
[http://dx.doi.org/10.2174/1573406413666170623082245] [PMID: 28641529]
[48]
Qiu, W.R.; Jiang, S.Y.; Xu, Z.C.; Xiao, X.; Chou, K.C. iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition. Oncotarget, 2017, 8(25), 41178-41188.
[http://dx.doi.org/10.18632/oncotarget.17104] [PMID: 28476023]
[49]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, D.; Chou, K.C. iPhos-PseEvo: identifying human phosphorylated proteins by incorporating evolutionary information into general PseAAC via grey system theory. Mol. Inform., 2017, 36(5-6)
[http://dx.doi.org/10.1002/minf.201600010] [PMID: 28488814]
[50]
Xu, Y.; Wang, Z.; Li, C.; Chou, K.C. iPreny-PseAac: identify C-terminal cysteine prenylation sites in proteins by incorporating two tiers of sequence couplings into PseAAC. Med. Chem., 2017, 13(6), 544-551.
[http://dx.doi.org/10.2174/1573406413666170419150052] [PMID: 28425870]
[51]
Chen, W.; Ding, H.; Zhou, X.; Lin, H.; Chou, K.C. iRNA(m6A)-PseDNC: identifying N6-methyladenosine sites using pseudo dinucleotide composition. Anal. Biochem., 2018, 561-562, 59-65.
[http://dx.doi.org/10.1016/j.ab.2018.09.002] [PMID: 30201554]
[52]
Chen, W.; Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chou, K.C. iRNA-3typea: identifying three types of modification at RNA’s adenosine sites. Mol. Ther. Nucleic Acids, 2018, 11, 468-474.
[http://dx.doi.org/10.1016/j.omtn.2018.03.012] [PMID: 29858081]
[53]
Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chen, W.; Chou, K.C. iDNA6mA-PseKNC: identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC. Genomics, 2019, 111(1), 96-102.
[http://dx.doi.org/10.1016/j.ygeno.2018.01.005] [PMID: 29360500]
[54]
Khan, Y.D.; Rasool, N.; Hussain, W.; Khan, S.A.; Chou, K.C. iPhosT-PseAAC: identify phosphothreonine sites by incorporating sequence statistical moments into PseAAC. Anal. Biochem., 2018, 550, 109-116.
[http://dx.doi.org/10.1016/j.ab.2018.04.021] [PMID: 29704476]
[55]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, Z.C.; Jia, J.H.; Chou, K.C. iKcr-PseEns: identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier. Genomics, 2018, 110(5), 239-246.
[http://dx.doi.org/10.1016/j.ygeno.2017.10.008] [PMID: 29107015]
[56]
Chou, K.C. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins, 2001, 43(3), 246-255.
[http://dx.doi.org/10.1002/prot.1035] [PMID: 11288174]
[57]
Chen, W.; Lei, T.Y.; Jin, D.C.; Lin, H.; Chou, K.C. PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition. Anal. Biochem., 2014, 456, 53-60.
[http://dx.doi.org/10.1016/j.ab.2014.04.001] [PMID: 24732113]
[58]
Chen, W.; Lin, H.; Chou, K.C. Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences. Mol. Biosyst., 2015, 11(10), 2620-2634.
[http://dx.doi.org/10.1039/C5MB00155B] [PMID: 26099739]
[59]
Liu, B.; Liu, F.; Wang, X.; Chen, J.; Fang, L.; Chou, K.C. Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences. Nucleic Acids Res., 2015, 43(W1), W65-W71.
[http://dx.doi.org/10.1093/nar/gkv458] [PMID: 25958395]
[60]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mEuk: predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC. Genomics, 2018, 110(1), 50-58.
[http://dx.doi.org/10.1016/j.ygeno.2017.08.005] [PMID: 28818512]
[61]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc_bal-mGneg: predict subcellular localization of gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC. J. Theor. Biol., 2018, 458, 92-102.
[http://dx.doi.org/10.1016/j.jtbi.2018.09.005] [PMID: 30201434]
[62]
Chou, K.C.; Cheng, X.; Xiao, X. pLoc_bal-mHum: predict subcellular localization of human proteins by PseAAC and quasi-balancing training dataset. Genomics, 2018, 111(6), 1274-1282.
[http://dx.doi.org/10.1016/j.ygeno.2018.08.007]] [PMID: 30179658 ]
[63]
Xiao, X.; Cheng, X.; Chen, G.; Mao, Q.; Chou, K.C. pLoc_bal-mGpos: predict subcellular localization of gram-positive bacterial proteins by quasi-balancing training dataset and PseAAC. Genomics, 2018, 111(4), 886-892.
[http://dx.doi.org/10.1016/j.ygeno.2018.05.017]] [PMID: 29842950]
[64]
Liu, Z.; Xiao, X.; Qiu, W.R.; Chou, K.C. iDNA-Methyl: identifying DNA methylation sites via pseudo trinucleotide composition. Anal. Biochem., 2015, 474, 69-77.
[http://dx.doi.org/10.1016/j.ab.2014.12.009] [PMID: 25596338]
[65]
Xiao, X.; Min, J.L.; Lin, W.Z.; Liu, Z.; Cheng, X.; Chou, K.C. iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach. J. Biomol. Struct. Dyn., 2015, 33(10), 2221-2233.
[http://dx.doi.org/10.1080/07391102.2014.998710] [PMID: 25513722]
[66]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K.C. iPPBS-Opt: a sequence-based ensemble classifier for identifying protein-protein binding sites by optimizing imbalanced training datasets. Molecules, 2016, 21(1) E95
[http://dx.doi.org/10.3390/molecules21010095] [PMID: 26797600]
[67]
Liu, B.; Yang, F.; Huang, D.S.; Chou, K.C. iPromoter-2L: a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC. Bioinformatics, 2018, 34(1), 33-40.
[http://dx.doi.org/10.1093/bioinformatics/btx579] [PMID: 28968797]
[68]
Chou, K.C. Low-frequency collective motion in biomacromolecules and its biological functions. Biophys. Chem., 1988, 30(1), 3-48.
[http://dx.doi.org/10.1016/0301-4622(88)85002-6] [PMID: 3046672]
[69]
Chou, K.C. Low-frequency vibrations of DNA molecules. Biochem. J., 1984, 221(1), 27-31.
[http://dx.doi.org/10.1042/bj2210027] [PMID: 6466317]
[70]
Chou, K.C. Identification of low-frequency modes in protein molecules. Biochem. J., 1983, 215(3), 465-469.
[http://dx.doi.org/10.1042/bj2150465] [PMID: 6362659]
[71]
Chou, K.C.; Zhang, C.T.; Maggiora, G.M. Solitary wave dynamics as a mechanism for explaining the internal motion during microtubule growth. Biopolymers, 1994, 34(1), 143-153.
[http://dx.doi.org/10.1002/bip.360340114] [PMID: 8110966]
[72]
Chou, K.C. Low-frequency resonance and cooperativity of hemoglobin. Trends Biochem. Sci., 1989, 14(6), 212-213.
[http://dx.doi.org/10.1016/0968-0004(89)90026-1] [PMID: 2763333]
[73]
Chou, K.C.; Maggiora, G.M.; Mao, B. Quasi-continuum models of twist-like and accordion-like low-frequency motions in DNA. Biophys. J., 1989, 56(2), 295-305.
[http://dx.doi.org/10.1016/S0006-3495(89)82676-1] [PMID: 2775828]
[74]
Chen, W.; Feng, P.M.; Lin, H.; Chou, K.C. iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition. Nucleic Acids Res., 2013, 41(6) e68
[http://dx.doi.org/10.1093/nar/gks1450] [PMID: 23303794]
[75]
Feng, P.M.; Chen, W.; Lin, H.; Chou, K.C. iHSP-PseRAAAC: identifying the heat shock protein families using pseudo reduced amino acid alphabet composition. Anal. Biochem., 2013, 442(1), 118-125.
[http://dx.doi.org/10.1016/j.ab.2013.05.024] [PMID: 23756733]
[76]
Ding, H.; Deng, E.Z.; Yuan, L.F.; Liu, L.; Lin, H.; Chen, W.; Chou, K.C. iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels. BioMed Res. Int., 2014, 2014 286419
[http://dx.doi.org/10.1155/2014/286419] [PMID: 24991545]
[77]
Chen, W.; Feng, P.M.; Lin, H.; Chou, K.C. iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition. BioMed Res. Int., 2014, 2014 623149
[http://dx.doi.org/10.1155/2014/623149] [PMID: 24967386]
[78]
Lin, H.; Deng, E.Z.; Ding, H.; Chen, W.; Chou, K.C. iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition. Nucleic Acids Res., 2014, 42(21), 12961-12972.
[http://dx.doi.org/10.1093/nar/gku1019] [PMID: 25361964]
[79]
Chen, W.; Feng, P.; Ding, H.; Lin, H.; Chou, K.C. Using deformation energy to analyze nucleosome positioning in genomes. Genomics, 2016, 107(2-3), 69-75.
[http://dx.doi.org/10.1016/j.ygeno.2015.12.005] [PMID: 26724497]
[80]
Chen, W.; Ding, H.; Feng, P.; Lin, H.; Chou, K.C. iACP: a sequence-based tool for identifying anticancer peptides. Oncotarget, 2016, 7(13), 16895-16909.
[http://dx.doi.org/10.18632/oncotarget.7815] [PMID: 26942877]
[81]
Zhang, C.J.; Tang, H.; Li, W.C.; Lin, H.; Chen, W.; Chou, K.C. iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition. Oncotarget, 2016, 7(43), 69783-69793.
[http://dx.doi.org/10.18632/oncotarget.11975] [PMID: 27626500]
[82]
Chen, W.; Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chou, K.C. iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences. Oncotarget, 2017, 8(3), 4208-4217.
[http://dx.doi.org/10.18632/oncotarget.13758] [PMID: 27926534]
[83]
Su, Z.D.; Huang, Y.; Zhang, Z.Y.; Zhao, Y.W.; Wang, D.; Chen, W.; Chou, K.C.; Lin, H. iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC. Bioinformatics, 2018, 34(24), 4196-4204.
[http://dx.doi.org/10.1093/bioinformatics/bty508] [PMID: 29931187]
[84]
Yang, H.; Qiu, W.R.; Liu, G.; Guo, F.B.; Chen, W.; Chou, K.C.; Lin, H. iRSpot-Pse6NC: identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC. Int. J. Biol. Sci., 2018, 14(8), 883-891.
[http://dx.doi.org/10.7150/ijbs.24616] [PMID: 29989083]
[85]
Chou, K.C. Some remarks on protein attribute prediction and pseudo amino acid composition. J. Theor. Biol., 2011, 273(1), 236-247.
[http://dx.doi.org/10.1016/j.jtbi.2010.12.024] [PMID: 21168420]
[86]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mVirus: predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC. Gene, 2017, 628, 315-321.
[http://dx.doi.org/10.1016/j.gene.2017.07.036] [PMID: 28728979]
[87]
Cheng, X.; Zhao, S.G.; Lin, W.Z.; Xiao, X.; Chou, K.C. pLoc-mAnimal: predict subcellular localization of animal proteins with both single and multiple sites. Bioinformatics, 2017, 33(22), 3524-3531.
[http://dx.doi.org/10.1093/bioinformatics/btx476] [PMID: 29036535]
[88]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mGneg: predict subcellular localization of gram-negative bacterial proteins by deep gene ontology learning via general PseAAC. Genomics, 2017, S0888-7543(17), 30102-30107..
[http://dx.doi.org/10.1016/j.ygeno.2017.10.002] [PMID: 28989035]
[89]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information. Bioinformatics, 2018, 34(9), 1448-1456.
[http://dx.doi.org/10.1093/bioinformatics/btx711] [PMID: 29106451]
[90]
Chou, K.C. Some remarks on predicting multi-label attributes in molecular biosystems. Mol. Biosyst., 2013, 9(6), 1092-1100.
[http://dx.doi.org/10.1039/c3mb25555g] [PMID: 23536215]
[91]
Cheng, X.; Lin, W.Z.; Xiao, X.; Chou, K.C. pLoc_bal-mAnimal: predict subcellular localization of animal proteins by balancing training dataset and PseAAC. Bioinformatics, 2019, 35(3), 398-406.
[http://dx.doi.org/10.1093/bioinformatics/bty628] [PMID: 30010789]
[92]
Xiao, X.; Cheng, X.; Chen, G.; Mao, Q.; Chou, K.C. pLoc_bal-mVirus: predict subcellular localization of multi-label virus proteins by PseAAC and IHTS treatment to balance training dataset. Med. Chem., 2019, 15(5), 496-509.
[http://dx.doi.org/10.2174/1573406415666181217114710]] [PMID: 30556503]
[93]
Chou, K.C.; Cheng, X.; Xiao, X. pLoc_bal-mEuk: predict subcellular localization of eukaryotic proteins by general PseAAC and quasi-balancing training dataset. Med. Chem., 2019, 15(5), 472-485.
[http://dx.doi.org/10.2174/1573406415666181218102517]] [PMID: 30569871]
[94]
Miller, F.W.; Alfredsson, L.; Costenbader, K.H.; Kamen, D.L.; Nelson, L.M.; Norris, J.M.; De Roos, A.J. epidemiology of environmental exposures and human autoimmune diseases: findings from a national institute of environmental health sciences expert panel workshop. J. Autoimmun., 2012, 39(4), 259-271.
[http://dx.doi.org/10.1016/j.jaut.2012.05.002] [PMID: 22739348]
[95]
Lu-Fritts, P.Y.; Kottyan, L.C.; James, J.A.; Xie, C.; Buckholz, J.M.; Pinney, S.M.; Harley, J.B. Association of systemic lupus erythematosus with uranium exposure in a community living near a uranium-processing plant: a nested case-control study. Arthritis Rheumatol., 2014, 66(11), 3105-3112.
[http://dx.doi.org/10.1002/art.38786] [PMID: 25103365]
[96]
Cozier, Y.C.; Barbhaiya, M.; Castro-Webb, N.; Conte, C.; Tedeschi, S.K.; Leatherwood, C.; Costenbader, K.H.; Rosenberg, L. Relationship of cigarette smoking and alcohol consumption to incidence of systemic lupus erythematosus in the black women’s health study. Arthritis Care Res. (Hoboken), 2019, 71(5), 671-677.
[http://dx.doi.org/10.1002/acr.23703]] [PMID: 30091287]
[97]
Leiss, H.; Niederreiter, B.; Bandur, T.; Schwarzecker, B.; Blüml, S.; Steiner, G.; Ulrich, W.; Smolen, J.S.; Stummvoll, G.H. Pristane-induced lupus as a model of human lupus arthritis: evolvement of autoantibodies, internal organ and joint inflammation. Lupus, 2013, 22(8), 778-792.
[http://dx.doi.org/10.1177/0961203313492869] [PMID: 23817510]
[98]
Zandman-Goddard, G.; Solomon, M.; Rosman, Z.; Peeva, E.; Shoenfeld, Y. Environment and lupus-related diseases. Lupus, 2012, 21(3), 241-250.
[http://dx.doi.org/10.1177/0961203311426568] [PMID: 22065092]
[99]
Parks, C.G.; De Roos, A.J. Pesticides, chemical and industrial exposures in relation to systemic lupus erythematosus. Lupus, 2014, 23(6), 527-536.
[http://dx.doi.org/10.1177/0961203313511680] [PMID: 24763537]
[100]
Bernatsky, S.; Fournier, M.; Pineau, C.A.; Clarke, A.E.; Vinet, E.; Smargiassi, A. Associations between ambient fine particulate levels and disease activity in patients with systemic lupus erythematosus (SLE). Environ. Health Perspect., 2011, 119(1), 45-49.
[http://dx.doi.org/10.1289/ehp.1002123] [PMID: 20870568]
[101]
Kamen, D.L. Environmental influences on systemic lupus erythematosus expression. Rheum. Dis. Clin. North Am., 2014, 40(3), 401-412.
[http://dx.doi.org/10.1016/j.rdc.2014.05.003] [PMID: 25034153]
[102]
Brown, J.M.; Pfau, J.C.; Pershouse, M.A.; Holian, A. Silica, apoptosis, and autoimmunity. J. Immunotoxicol., 2005, 1(3), 177-187.
[http://dx.doi.org/10.1080/15476910490911922] [PMID: 18958651]
[103]
Cooper, G.S.; Wither, J.; Bernatsky, S.; Claudio, J.O.; Clarke, A.; Rioux, J.D.; Fortin, P.R.; Fortin, P.R. CaNIOS GenES Investigators. Occupational and environmental exposures and risk of systemic lupus erythematosus: silica, sunlight, solvents. Rheumatology (Oxford), 2010, 49(11), 2172-2180.
[http://dx.doi.org/10.1093/rheumatology/keq214] [PMID: 20675707]
[104]
Dietert, R.R.; Luebke, R.W. Immunotoxicity, immune dysfunction, and chronic disease, 2012.
[http://dx.doi.org/10.1007/978-1-61779-812-2]
[105]
Dietert, R.R. Role of developmental immunotoxicity and immune dysfunction in chronic disease and cancer. Reprod. Toxicol., 2011, 31(3), 319-326.
[http://dx.doi.org/10.1016/j.reprotox.2010.09.006] [PMID: 20854896]
[106]
Li, J.; McMurray, R.W. Effects of chronic exposure to DDT and TCDD on disease activity in murine systemic lupus erythematosus. Lupus, 2009, 18(11), 941-949.
[http://dx.doi.org/10.1177/0961203309104431] [PMID: 19762394]
[107]
Cheng, X.L.; Zhang, H.; Guo, D.; Qiao, Z.D. Upregulation of fas and fasL expression in nicotine-induced apoptosis of endothelial cells. Methods Find. Exp. Clin. Pharmacol., 2010, 32(1), 13-18.
[http://dx.doi.org/10.1358/mf.2010.32.1.1428742] [PMID: 20383341]
[108]
Bijl, M.; Horst, G.; Limburg, P.C.; Kallenberg, C.G. Effects of smoking on activation markers, fas expression and apoptosis of peripheral blood lymphocytes. Eur. J. Clin. Invest., 2001, 31(6), 550-553.
[http://dx.doi.org/10.1046/j.1365-2362.2001.00842.x] [PMID: 11422406]
[109]
He, Y.Y.; Yan, Y.; Zhang, H.F.; Lin, Y.H.; Chen, Y.C.; Yan, Y.; Wu, P.; Fang, J.S.; Yang, S.H.; Du, G.H. Methyl salicylate 2-O-β-d-lactoside alleviates the pathological progression of pristane-induced systemic lupus erythematosus-like disease in mice via suppression of inflammatory response and signal transduction. Drug Des. Devel. Ther., 2016, 10, 3183-3196.
[http://dx.doi.org/10.2147/DDDT.S114501] [PMID: 27729775]
[110]
Kunchithapautham, K.; Atkinson, C.; Rohrer, B. Smoke exposure causes endoplasmic reticulum stress and lipid accumulation in retinal pigment epithelium through oxidative stress and complement activation. J. Biol. Chem., 2014, 289(21), 14534-14546.
[http://dx.doi.org/10.1074/jbc.M114.564674] [PMID: 24711457]
[111]
Pocino, M.; Malavé, I.; Baute, L. Zinc administration restores the impaired immune response observed in mice receiving excess copper by oral route. Immunopharmacol. Immunotoxicol., 1990, 12(4), 697-713.
[http://dx.doi.org/10.3109/08923979009019685] [PMID: 2092046]
[112]
Lee, S.; Hayashi, H.; Maeda, M.; Chen, Y.; Matsuzaki, H.; Takei-Kumagai, N.; Nishimura, Y.; Fujimoto, W.; Otsuki, T. Environmental factors producing autoimmune dysregulation-chronic activation of T cells caused by silica exposure. Immunobiology, 2012, 217(7), 743-748.
[http://dx.doi.org/10.1016/j.imbio.2011.12.009] [PMID: 22226303]
[113]
Lee, S.; Hayashi, H.; Maeda, M.; Matsuzaki, H.; Kumagai-Takei, N.; Chen, Y.; Urakami, K.; Kusaka, M.; Nishimura, Y.; Otsuki, T. Immunostimulation by silica particles and the development of autoimmune dysregulation, 2014.
[http://dx.doi.org/10.5772/57544]
[114]
Pollard, K.M. Silica, silicosis, and autoimmunity. Front. Immunol., 2016, 7, 97.
[http://dx.doi.org/10.3389/fimmu.2016.00097] [PMID: 27014276]
[115]
Diamanti-Kandarakis, E.; Bourguignon, J.P.; Giudice, L.C.; Hauser, R.; Prins, G.S.; Soto, A.M.; Zoeller, R.T.; Gore, A.C. Endocrine-disrupting chemicals: an endocrine society scientific statement. Endocr. Rev., 2009, 30(4), 293-342.
[http://dx.doi.org/10.1210/er.2009-0002] [PMID: 19502515]
[116]
Chighizola, C.; Meroni, P.L. The role of environmental estrogens and autoimmunity. Autoimmun. Rev., 2012, 11(6-7), A493-A501.
[http://dx.doi.org/10.1016/j.autrev.2011.11.027] [PMID: 22172713]
[117]
Schug, T.T.; Janesick, A.; Blumberg, B.; Heindel, J.J. Endocrine disrupting chemicals and disease susceptibility. J. Steroid Biochem. Mol. Biol., 2011, 127(3-5), 204-215.
[http://dx.doi.org/10.1016/j.jsbmb.2011.08.007] [PMID: 21899826]
[118]
Rogers, J.A.; Metz, L.; Yong, V.W. Review: endocrine disrupting chemicals and immune responses: a focus on bisphenol-A and its potential mechanisms. Mol. Immunol., 2013, 53(4), 421-430.
[http://dx.doi.org/10.1016/j.molimm.2012.09.013] [PMID: 23123408]
[119]
Inadera, H. The immune system as a target for environmental chemicals: xenoestrogens and other compounds. Toxicol. Lett., 2006, 164(3), 191-206.
[http://dx.doi.org/10.1016/j.toxlet.2006.03.006] [PMID: 16697129]
[120]
Costenbader, K.H.; Gay, S.; Alarcón-Riquelme, M.E.; Iaccarino, L.; Doria, A. Genes, epigenetic regulation and environmental factors: which is the most relevant in developing autoimmune diseases? Autoimmun. Rev., 2012, 11(8), 604-609.
[http://dx.doi.org/10.1016/j.autrev.2011.10.022] [PMID: 22041580]
[121]
Richardson, B.C.; Patel, D.R. Epigenetics in 2013. DNA methylation and miRNA: key roles in systemic autoimmunity. Nat. Rev. Rheumatol., 2014, 10(2), 72-74.
[http://dx.doi.org/10.1038/nrrheum.2013.211] [PMID: 24418763]
[122]
Hedrich, C.M.; Tsokos, G.C. Epigenetic mechanisms in systemic lupus erythematosus and other autoimmune diseases. Trends Mol. Med., 2011, 17(12), 714-724.
[http://dx.doi.org/10.1016/j.molmed.2011.07.005] [PMID: 21885342]
[123]
Quintero-Ronderos, P.; Montoya-Ortiz, G. Epigenetics and autoimmune diseases. Autoimmune Dis., 2012, 2012 593720
[http://dx.doi.org/10.1155/2012/593720] [PMID: 22536485]
[124]
Lu, Q. The critical importance of epigenetics in autoimmunity. J. Autoimmun., 2013, 41, 1-5.
[http://dx.doi.org/10.1016/j.jaut.2013.01.010] [PMID: 23375849]
[125]
Hughes, T.; Sawalha, A.H. The role of epigenetic variation in the pathogenesis of systemic lupus erythematosus. Arthritis Res. Ther., 2011, 13(5), 245.
[http://dx.doi.org/10.1186/ar3484] [PMID: 22044622]
[126]
Collotta, M.; Bertazzi, P.A.; Bollati, V. Epigenetics and pesticides. Toxicology, 2013, 307, 35-41.
[http://dx.doi.org/10.1016/j.tox.2013.01.017] [PMID: 23380243]
[127]
Ji, H.; Khurana Hershey, G.K. Genetic and epigenetic influence on the response to environmental particulate matter. J. Allergy Clin. Immunol., 2012, 129(1), 33-41.
[http://dx.doi.org/10.1016/j.jaci.2011.11.008] [PMID: 22196522]
[128]
Baccarelli, A.; Bollati, V. Epigenetics and environmental chemicals. Curr. Opin. Pediatr., 2009, 21(2), 243-251.
[http://dx.doi.org/10.1097/MOP.0b013e32832925cc] [PMID: 19663042]
[129]
Hou, L.; Zhang, X.; Wang, D.; Baccarelli, A. Environmental chemical exposures and human epigenetics. Int. J. Epidemiol., 2011.
[130]
Hou, L.; Wang, D.; Baccarelli, A. Environmental chemicals and microRNAs. Mutat. Res., 2011, 714(1-2), 105-112.
[http://dx.doi.org/10.1016/j.mrfmmm.2011.05.004] [PMID: 21609724]
[131]
Feil, R.; Fraga, M.F. Epigenetics and the environment: emerging patterns and implications. Nat. Rev. Genet., 2012, 13(2), 97-109.
[http://dx.doi.org/10.1038/nrg3142] [PMID: 22215131]
[132]
Chang, C.; Gershwin, M.E. Drug-induced lupus erythematosus: incidence, management and prevention. Drug Saf., 2011, 34(5), 357-374.
[http://dx.doi.org/10.2165/11588500-000000000-00000] [PMID: 21513360]
[133]
Bertsias, G.; Cervera, R.; Boumpas, D.T. Systemic lupus erythematosus: pathogenesis and clinical features. EULAR textbook on rheumatic diseases, 2012, 5, 476-505.,
[134]
Araújo-Fernández, S.; Ahijón-Lana, M.; Isenberg, D.A. Drug-induced lupus: including anti-tumour necrosis factor and interferon induced. Lupus, 2014, 23(6), 545-553.
[http://dx.doi.org/10.1177/0961203314523871] [PMID: 24557776]
[135]
Lowe, G.C.; Henderson, C.L.; Grau, R.H.; Hansen, C.B.; Sontheimer, R.D. A systematic review of drug-induced subacute cutaneous lupus erythematosus. Br. J. Dermatol., 2011, 164(3), 465-472.
[http://dx.doi.org/10.1111/j.1365-2133.2010.10110.x] [PMID: 21039412]
[136]
Aguirre Zamorano, M.A.; López Pedrera, R.; Cuadrado Lozano, M.J. Drug-induced lupus. Med. Clin. (Barc.), 2010, 135(3), 124-129.
[http://dx.doi.org/10.1016/j.medcli.2009.04.035] [PMID: 19576598]
[137]
Vaglio, A.; Grayson, P.C.; Fenaroli, P.; Gianfreda, D.; Boccaletti, V.; Ghiggeri, G.M.; Moroni, G. Drug-induced lupus: traditional and new concepts. Autoimmun. Rev., 2018, 17(9), 912-918.
[http://dx.doi.org/10.1016/j.autrev.2018.03.016] [PMID: 30005854]
[138]
Zarkavelis, G.; Kollas, A.; Kampletsas, E.; Vasiliou, V.; Kaltsonoudis, E.; Drosos, A.; Khaled, H.; Pavlidis, N. Aromatase inhibitors induced autoimmune disorders in patients with breast cancer: a review. J. Adv. Res., 2016, 7(5), 719-726.
[http://dx.doi.org/10.1016/j.jare.2016.04.001] [PMID: 28275510]
[139]
Miyagawa, F.; Sugano, Y.; Sho, M.; Asada, H. TS-1 (tegafur/gimeracil/oteracil)-induced systemic lupus erythematosus with skin lesions and anti-Sm antibody. Eur. J. Dermatol., 2017, 27(6), 646-647.
[http://dx.doi.org/10.1684/ejd.2017.3101] [PMID: 28721931]
[140]
Weber, W.; Tannen, R.; McQueen, C.; Glowinski, I. Acetylation Polymorphism. In: Clinical Pharmacology Proceedings of the 7th International Congress of Pharmacology, Paris1978.6(41).
[http://dx.doi.org/10.1016/C2013-0-03124-6]
[141]
Striebich, C.C. Drug-induced Lupus. Rheumatology Secrets, 3rd ed; 2014, 2(3), 137;
[142]
Merola, J.F. Lupus-like syndromes related to drugs.In Lupus Erythematosus, 2012, 211-221.
[http://dx.doi.org/10.1007/978-1-4614-1189-5_16]
[143]
Yung, R.; Richardson, B. Drug-induced lupus mechanisms, 2011, 385-404..
[http://dx.doi.org/10.1016/B978-0-12-374994-9.10022-1]
[144]
Zhao, S.; Wang, Y.; Liang, Y.; Zhao, M.; Long, H.; Ding, S.; Yin, H.; Lu, Q. MicroRNA-126 regulates DNA methylation in CD4+ T cells and contributes to systemic lupus erythematosus by targeting DNA methyltransferase 1. Arthritis Rheum., 2011, 63(5), 1376-1386.
[http://dx.doi.org/10.1002/art.30196] [PMID: 21538319]
[145]
Jones, P.A. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet., 2012, 13(7), 484-492.
[http://dx.doi.org/10.1038/nrg3230] [PMID: 22641018]
[146]
Strickland, F.M.; Richardson, B.C. Epigenetics in human autoimmunity. Epigenetics in autoimmunity - DNA methylation in systemic lupus erythematosus and beyond. Autoimmunity, 2008, 41(4), 278-286.
[http://dx.doi.org/10.1080/08916930802024616] [PMID: 18432408]
[147]
Hewagama, A.; Richardson, B. The genetics and epigenetics of autoimmune diseases. J. Autoimmun., 2009, 33(1), 3-11.
[http://dx.doi.org/10.1016/j.jaut.2009.03.007] [PMID: 19349147]
[148]
Jiang, X.; Khursigara, G.; Rubin, R.L. Transformation of lupus-inducing drugs to cytotoxic products by activated neutrophils. Science, 1994, 266(5186), 810-813.
[http://dx.doi.org/10.1126/science.7973636] [PMID: 7973636]
[149]
Rubin, R.L. Drug-induced lupus. Toxicology, 2005, 209(2), 135-147.
[http://dx.doi.org/10.1016/j.tox.2004.12.025] [PMID: 15767026]
[150]
Ablin, J.; Verbovetski, I.; Trahtemberg, U.; Metzger, S.; Mevorach, D. Quinidine and procainamide inhibit murine macrophage uptake of apoptotic and necrotic cells: a novel contributing mechanism of drug-induced-lupus. Apoptosis, 2005, 10(5), 1009-1018.
[http://dx.doi.org/10.1007/s10495-005-1189-4] [PMID: 16151636]
[151]
Bouts, Y.M.; Wolthuis, D.F.; Dirkx, M.F.; Pieterse, E.; Simons, E.M.; van Boekel, A.M.; Dieker, J.W.; van der Vlag, J. Apoptosis and NET formation in the pathogenesis of SLE. Autoimmunity, 2012, 45(8), 597-601.
[http://dx.doi.org/10.3109/08916934.2012.719953] [PMID: 22913420]
[152]
Grayson, P.C.; Schauer, C.; Herrmann, M.; Kaplan, M.J. Review: neutrophils as invigorated targets in rheumatic diseases. Arthritis Rheumatol., 2016, 68(9), 2071-2082.
[http://dx.doi.org/10.1002/art.39745] [PMID: 27159737]
[153]
Grayson, P.C.; Kaplan, M.J. At the Bench: neutrophil extracellular traps (NETs) highlight novel aspects of innate immune system involvement in autoimmune diseases. J. Leukoc. Biol., 2016, 99(2), 253-264.
[http://dx.doi.org/10.1189/jlb.5BT0615-247R] [PMID: 26432901]
[154]
Carmona-Rivera, C.; Purmalek, M.M.; Moore, E.; Waldman, M.; Walter, P.J.; Garraffo, H.M.; Phillips, K.A.; Preston, K.L.; Graf, J.; Kaplan, M.J.; Grayson, P.C. A role for muscarinic receptors in neutrophil extracellular trap formation and levamisole-induced autoimmunity. JCI Insight, 2017, 2(3) e89780
[http://dx.doi.org/10.1172/jci.insight.89780] [PMID: 28194438]
[155]
Irizarry-Caro, J.A.; Carmona-Rivera, C.; Schwartz, D.M.; Khaznadar, S.S.; Kaplan, M.J.; Grayson, P.C. Brief Report: drugs implicated in systemic autoimmunity modulate neutrophil extracellular trap formation. Arthritis Rheumatol., 2018, 70(3), 468-474.
[http://dx.doi.org/10.1002/art.40372] [PMID: 29121457]
[156]
Kretz-Rommel, A.; Rubin, R.L. Disruption of positive selection of thymocytes causes autoimmunity. Nat. Med., 2000, 6(3), 298-305.
[http://dx.doi.org/10.1038/73152] [PMID: 10700232]
[157]
Kretz-Rommel, A.; Duncan, S.R.; Rubin, R.L. Autoimmunity caused by disruption of central T cell tolerance. A murine model of drug-induced lupus. J. Clin. Invest., 1997, 99(8), 1888-1896.
[http://dx.doi.org/10.1172/JCI119356] [PMID: 9109433]
[158]
Mazari, L.; Ouarzane, M.; Zouali, M. Subversion of B lymphocyte tolerance by hydralazine, a potential mechanism for drug-induced lupus. Proc. Natl. Acad. Sci. USA, 2007, 104(15), 6317-6322.
[http://dx.doi.org/10.1073/pnas.0610434104] [PMID: 17404230]
[159]
Perez-Alvarez, R.; Pérez-de-Lis, M.; Ramos-Casals, M. BIOGEAS study group. Biologics-induced autoimmune diseases. Curr. Opin. Rheumatol., 2013, 25(1), 56-64.
[http://dx.doi.org/10.1097/BOR.0b013e32835b1366] [PMID: 23114587]
[160]
Catrina, A.I.; Trollmo, C.; af Klint, E.; Engstrom, M.; Lampa, J.; Hermansson, Y.; Klareskog, L.; Ulfgren, A.K. Evidence that anti-tumor necrosis factor therapy with both etanercept and infliximab induces apoptosis in macrophages, but not lymphocytes, in rheumatoid arthritis joints: extended report. Arthritis Rheum., 2005, 52(1), 61-72.
[http://dx.doi.org/10.1002/art.20764] [PMID: 15641091]
[161]
Atzeni, F.; Talotta, R.; Salaffi, F.; Cassinotti, A.; Varisco, V.; Battellino, M.; Ardizzone, S.; Pace, F.; Sarzi-Puttini, P. Immunogenicity and autoimmunity during anti-TNF therapy. Autoimmun. Rev., 2013, 12(7), 703-708.
[http://dx.doi.org/10.1016/j.autrev.2012.10.021] [PMID: 23207283]
[162]
Williams, E.L.; Gadola, S.; Edwards, C.J. Anti-TNF-induced lupus. Rheumatology (Oxford), 2009, 48(7), 716-720.
[http://dx.doi.org/10.1093/rheumatology/kep080] [PMID: 19416947]
[163]
Cunningham, M.; Gilkeson, G. Estrogen receptors in immunity and autoimmunity. Clin. Rev. Allergy Immunol., 2011, 40(1), 66-73.
[http://dx.doi.org/10.1007/s12016-010-8203-5] [PMID: 20352526]
[164]
Lahita, R.G. The immunoendocrinology of systemic lupus erythematosus. Clin. Immunol., 2016, 172, 98-100.
[http://dx.doi.org/10.1016/j.clim.2016.08.014] [PMID: 27546447]
[165]
Li, J.; McMurray, R.W. Effects of estrogen receptor subtype-selective agonists on autoimmune disease in lupus-prone NZB/NZW F1 mouse model. Clin. Immunol., 2007, 123(2), 219-226.
[http://dx.doi.org/10.1016/j.clim.2007.01.008] [PMID: 17336162]
[166]
Drehmer, M.N.; Andrade, D.; Pereira, I.A.; Marrero, A.R.; Muniz, Y.C.; de Souza, I.R.; Löfgren, S.E. Estrogen receptor alpha gene (ESR1) polymorphism can contribute to clinical findings in systemic lupus erythematosus patients. Lupus, 2017, 26(3), 294-298.
[http://dx.doi.org/10.1177/0961203316668041] [PMID: 27681518]
[167]
Weeding, E.; Sawalha, A.H. Deoxyribonucleic acid methylation in systemic lupus erythematosus: implications for future clinical practice. Front. Immunol., 2018, 9, 875.
[http://dx.doi.org/10.3389/fimmu.2018.00875] [PMID: 29740453]
[168]
Gorjestani, S.; Rider, V.; Kimler, B.F.; Greenwell, C.; Abdou, N.I. Extracellular signal-regulated kinase 1/2 signalling in SLE T cells is influenced by oestrogen and disease activity. Lupus, 2008, 17(6), 548-554.
[http://dx.doi.org/10.1177/0961203307087982] [PMID: 18539708]
[169]
Pan, W.; Zhu, S.; Yuan, M.; Cui, H.; Wang, L.; Luo, X.; Li, J.; Zhou, H.; Tang, Y.; Shen, N. MicroRNA-21 and microRNA-148a contribute to DNA hypomethylation in lupus CD4+ T cells by directly and indirectly targeting DNA methyltransferase 1. J. Immunol., 2010, 184(12), 6773-6781.
[http://dx.doi.org/10.4049/jimmunol.0904060] [PMID: 20483747]
[170]
Strickland, F.M.; Hewagama, A.; Lu, Q.; Wu, A.; Hinderer, R.; Webb, R.; Johnson, K.; Sawalha, A.H.; Delaney, C.; Yung, R.; Richardson, B.C. Environmental exposure, estrogen and two X chromosomes are required for disease development in an epigenetic model of lupus. J. Autoimmun., 2012, 38(2-3), J135-J143.
[http://dx.doi.org/10.1016/j.jaut.2011.11.001] [PMID: 22142890]

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