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Research Paper

Epigenome-wide association study and network analysis for IgA Nephropathy from CD19+ B-cell in Chinese Population

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Pages 1283-1294 | Received 07 Jul 2020, Accepted 19 Nov 2020, Published online: 07 Jan 2021

References

  • Wyatt RJ, Julian BA. IgA nephropathy. N Engl J Med. 2013;368(25):2402–2414.
  • Kiryluk K, Li Y, Sanna-Cherchi S, et al. Geographic differences in genetic susceptibility to IgA nephropathy: GWAS replication study and geospatial risk analysis. PLoS Genet. 2012;8:e1002765.
  • Donadio JV, Grande JP. IgA nephropathy. N Engl J Med. 2002;347:738–748.
  • D’Amico G. The commonest glomerulonephritis in the world: igA nephropathy. Q J Med. 1987;64:709–727.
  • Barratt J, Feehally J. IgA nephropathy. J Am Soc Nephrol. 2005;16:2088–2097.
  • Lai KN. Pathogenesis of IgA nephropathy. Nat Rev Nephrol. 2012;8:275–283.
  • Yu XQ, Li M, Zhang H, et al. A genome-wide association study in Han Chinese identifies multiple susceptibility loci for IgA nephropathy. Nat Genet. 2011;44:178–182.
  • Li M, Foo JN, Wang JQ, et al. Identification of new susceptibility loci for IgA nephropathy in Han Chinese. Nat Commun. 2015;6:7270.
  • Kiryluk K, Li Y, Scolari F, et al. Discovery of new risk loci for IgA nephropathy implicates genes involved in immunity against intestinal pathogens. Nat Genet. 2014;46:1187–1196.
  • Gharavi AG, Kiryluk K, Choi M, et al. Genome-wide association study identifies susceptibility loci for IgA nephropathy. Nat Genet. 2011;43:321–327.
  • Saka S, Hirawa N, Oka A, et al. Genome-wide association study of IgA nephropathy using 23 465 microsatellite markers in a Japanese population. J Hum Genet. 2015;60:573–580.
  • Feehally J, Farrall M, Boland A, et al. HLA has strongest association with IgA nephropathy in genome-wide analysis. J Am Soc Nephrol. 2010;21:1791–1797.
  • Zhu Z, Lee PH, Chaffin MD, et al. A genome-wide cross-trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases. Nat Genet. 2018;50:857–864.
  • Foo JN, Liu J, Yu XQ. GWAS reveal novel IgA nephropathy risk loci. Oncotarget. 2015;6:15738–15739.
  • Deaton AM, Webb S, Kerr AR, et al. Cell type-specific DNA methylation at intragenic CpG islands in the immune system. Genome Res. 2011;21:1074–1086.
  • Chu AY, Tin A, Schlosser P, et al. Epigenome-wide association studies identify DNA methylation associated with kidney function. Nat Commun. 2017;8:1286.
  • Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15:R31.
  • Susztak K. Understanding the epigenetic syntax for the genetic alphabet in the kidney. J Am Soc Nephrol. 2014;25:10–17.
  • Muto M, Manfroi B, Suzuki H, et al. Toll-Like Receptor 9 Stimulation Induces Aberrant Expression of a Proliferation-Inducing Ligand by Tonsillar Germinal Center B Cells in IgA Nephropathy. J Am Soc Nephrol. 2017;28:1227–1238.
  • Soares MF. An update on pathology of IgA nephropathy. Jornal Brasileiro De Nefrologia Orgao Oficial De Sociedades Brasileira E Latino-Americana De Nefrologia. 2016;38:435–440.
  • Gan L, Zhou Q, Li X, et al. Intrinsic renal cells induce lymphocytosis of Th22 cells from IgA nephropathy patients through B7-CTLA-4 and CCL-CCR pathways. Mol Cell Biochem. 2018;441:191–199.
  • Gale DP, Molyneux K, Wimbury D, et al. Galactosylation of IgA1 Is associated with common variation in C1GALT1. J Am Soc Nephrol. 2017;28:2158–2166.
  • Illumina. Infinium MethylationEPIC Kit. 2019.
  • Chen J, Behnam E, Huang J, et al. Fast and robust adjustment of cell mixtures in epigenome-wide association studies with SmartSVA. BMC Genomics. 2017;18:413.
  • Nollet F, Kools P, van Roy F. Phylogenetic analysis of the cadherin superfamily allows identification of six major subfamilies besides several solitary members. J Mol Biol. 2000;299:551–572.
  • Weinrich SL, Pruzan R, Ma L, et al. Reconstitution of human telomerase with the template RNA component hTR and the catalytic protein subunit hTRT. Nat Genet. 1997;17:498–502.
  • Wu M, Wang PF, Lee JS, et al. Molecular regulation of H3K4 trimethylation by Wdr82, a component of human Set1/COMPASS. Mol Cell Biol. 2008;28:7337–7344.
  • Messer G, Zemmour J, Orr HT, et al. HLA-J, a second inactivated class I HLA gene related to HLA-G and HLA-A. Implications for the evolution of the HLA-A-related genes. J Iimmunol. 1992;148:4043–4053.
  • Kim YJ, Kim NY, Lee MK, et al. Overexpression and unique rearrangement of VH2 transcripts in immunoglobulin variable heavy chain genes in ankylosing spondylitis patients. Exp Mol Med. 2010;42:319–326.
  • Behnia R, Panic B, Whyte JR, et al. Targeting of the Arf-like GTPase Arl3p to the Golgi requires N-terminal acetylation and the membrane protein Sys1p. Nat Cell Biol. 2004;6:405–413.
  • Huang TS, Wang KC, Quon S, et al. LINC00341 exerts an anti-inflammatory effect on endothelial cells by repressing VCAM1. Physiol Genomics. 2017;49:339–345.
  • Schelling JR. Tubular atrophy in the pathogenesis of chronic kidney disease progression. Pediatr Nephrol. 2016;31:693–706.
  • Lusco MA, Fogo AB, Najafian B, et al. AJKD atlas of renal pathology: tubular atrophy. Am J Kidney Dis. 2016;67:e33–34.
  • Wing MR, Ramezani A, Gill HS, et al. Epigenetics of progression of chronic kidney disease: fact or fantasy? Semin Nephrol. 2013;33:363–374.
  • Wing MR, Devaney JM, Joffe MM, et al. S. Chronic Renal Insufficiency Cohort, DNA methylation profile associated with rapid decline in kidney function: findings from the CRIC study. Nephrol Dialysis Trans. 2014;29:864–872.
  • Rodriguez-Romo R, Berman N, Gomez A, et al. Epigenetic regulation in the acute kidney injury to chronic kidney disease transition. Nephrology. 2015;20:736–743.
  • Hu Z, Snitkin ES, DeLisi C. VisANT: an integrative framework for networks in systems biology. Brief Bioinform. 2008;9:317–325.
  • Liesche F, Kolbl AC, Ilmer M, et al. Role of N-acetylgalactosaminyltransferase 6 in early tumorigenesis and formation of metastasis. Mol Med Rep. 2016;13:4309–4314.
  • Li J, Zhu X, Yu K, et al. Genome-wide analysis of DNA methylation and acute coronary syndrome. Circ Res. 2017;120:1754–1767.
  • Zhang H, Coblentz C, Watanabe-Smith K, et al. Gain-of-function mutations in granulocyte colony-stimulating factor receptor (CSF3R) reveal distinct mechanisms of CSF3R activation. J Biol Chem. 2018;293:7387–7396.
  • Folgueira C, Seoane LM, Casanueva FF. The brain-stomach connection. Front Horm Res. 2014;42:83–92.
  • Hu X, Kim H, Raj T, et al. Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells. PLoS Genet. 2014;10:e1004404.
  • Uyen TN, Sakashita K, Al-Kzayer LF, et al. Aberrant methylation of protocadherin 17 and its prognostic value in pediatric acute lymphoblastic leukemia. Pediatr Blood Cancer. 2017;64. DOI:https://doi.org/10.1002/pbc.26259
  • Lin YL, Wang YP, Li HZ, et al. Aberrant promoter methylation of PCDH17 (Protocadherin 17) in serum and its clinical significance in renal cell carcinoma. Med Sci Monit. 2017;23:3318–3323.
  • Yin X, Xiang T, Mu J, et al. Protocadherin 17 functions as a tumor suppressor suppressing Wnt/beta-catenin signaling and cell metastasis and is frequently methylated in breast cancer. Oncotarget. 2016;7:51720–51732.
  • Hu X, Sui X, Li L, et al. Protocadherin 17 acts as a tumour suppressor inducing tumour cell apoptosis and autophagy, and is frequently methylated in gastric and colorectal cancers. J Pathol. 2013;229:62–73.
  • Falola MI, Wiener HW, Wineinger NE, et al. Genomic copy number variants: evidence for association with antibody response to anthrax vaccine adsorbed. PloS One. 2013;8:e64813.
  • Serrels B, McGivern N, Canel M, et al. IL-33 and ST2 mediate FAK-dependent antitumor immune evasion through transcriptional networks. Sci Signal. 2017;10. DOI:https://doi.org/10.1126/scisignal.aan8355
  • Zhou XJ, Nath SK, Qi YY, et al. Novel identified associations of RGS1 and RASGRP1 variants in IgA Nephropathy. Sci Rep. 2016;6:35781.
  • Hathcock KS, Jeffrey Chiang Y, Hodes RJ. In vivo regulation of telomerase activity and telomere length. Immunol Rev. 2005;205:104–113.
  • Klapper W, Moosig F, Sotnikova A, et al. Telomerase activity in B and T lymphocytes of patients with systemic lupus erythematosus. Ann Rheum Dis. 2004;63:1681–1683.
  • Lin J, Chung S, Ueda K, et al. GALNT6 stabilizes GRP78 protein by o-glycosylation and enhances its activity to suppress apoptosis under stress condition. Neoplasia. 2017;19:43–53.
  • Stuchlova Horynova M, Raska M, Clausen H, et al. Aberrant O-glycosylation and anti-glycan antibodies in an autoimmune disease IgA nephropathy and breast adenocarcinoma. Cell Mol Life Sci. 2013;70:829–839.
  • Zhang J, Wan L, Dai X, et al. Functional characterization of anaphase promoting complex/cyclosome (APC/C) E3 ubiquitin ligases in tumorigenesis. Biochim Biophys Acta. 2014;1845:277–293.
  • Gotoh M, Ichikawa H, Arai E, et al. Comprehensive exploration of novel chimeric transcripts in clear cell renal cell carcinomas using whole transcriptome analysis. Genes Chromosomes Cancer. 2014;53:1018–1032.
  • Kiryluk K, Julian BA, Wyatt RJ, et al. Genetic studies of IgA nephropathy: past, Present, and Future. Pediatr Nephrol. 2010;25:2257–2268.
  • Parikh SV, Malvar A, Song H, et al. Molecular imaging of the kidney in lupus nephritis to characterize response to treatment. Transl Res. 2017;182:1–13.
  • Li C, Zhang G, Li X, et al. A systematic method for mapping multiple loci: an application to construct a genetic network for rheumatoid arthritis. Gene. 2008;408:104–111.
  • Kumar V, Matsuo K, Takahashi A, et al. Common variants on 14q32 and 13q12 are associated with DLBCL susceptibility. J Hum Genet. 2011;56:436–439.
  • Gabrielsen IS, Amundsen SS, Helgeland H, et al. Genetic risk variants for autoimmune diseases that influence gene expression in thymus. Hum Mol Genet. 2016;25:3117–3124.
  • Gillies CE, Putler R, Menon R, et al. N. Nephrotic Syndrome Study, N. Hacohen, K. Kiryluk, M. Kretzler, X. Wen, M.G. Sampson, An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome. Am J Hum Genet. 2018;103:232–244.
  • Huber W, Carey VJ, Gentleman R, et al. Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods. 2015;12:115–121.
  • Fortin JP, Triche TJ Jr., Hansen KD. Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi. Bioinformatics. 2017;33:558–560.
  • Team RC. R: A Language and Environment for Statistical Computing. 2019.
  • Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol. 1995;289–300. DOI:https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
  • Illumina. Infinium MethylationEPIC Product Files. 2017.
  • Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol. 2005;4:Article 17.
  • Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559.
  • Huang da W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37:1–13.
  • Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57.

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