克罗恩病和牙周炎的共有免疫相关基因及其作为诊断生物标志物的潜力

doi:10.13591/j.cnki.kqyx.2024.03.005

摘要/Abstract

摘要：

目的通过研究牙周炎和克罗恩病(Crohn's disease,CD)的共有免疫相关基因,探讨两种疾病间的共同病理生理学,并评估相关基因作为诊断生物标志物的价值。方法从GEO数据库下载CD和牙周炎的基因表达数据。对数据预处理后进行差异表达分析以获得差异表达基因(differentially expressed genes,DEGs),然后对共同DEGs进行功能富集和疾病本体分析并构建蛋白质-蛋白质相互作用(protein-protein interaction,PPI)网络。对CD和牙周炎数据库进行加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)以确定与疾病最相关的关键模块,从而进一步筛选出串扰基因,通过单样本基因集浓缩分析(ssGSEA)对CD和牙周炎的免疫细胞图谱进行评估,筛选CD和牙周炎中与免疫最相关的基因构建诊断模型,并在验证数据集中验证其准确性。结果共鉴定出143个共同DEGs,功能富集分析强调免疫在CD和牙周炎中发挥重要作用。通过WGCNA分析得到11个串扰基因,随后免疫浸润分析最终确定了4个与CD、牙周炎和免疫相关的基因(HLA-DMA、CD38、PIM2、TGM2);使用这4个基因构建的诊断模型在训练数据集和外部验证数据集中都具有良好的诊断性能。结论 HLA-DMA、CD38、PIM2、TGM2基因参与了CD和牙周炎的发生发展,在免疫反应中扮演重要角色,以这4个基因构建的诊断模型对两种疾病都有良好的诊断效力。

关键词: 免疫, 诊断, 牙周炎, 克罗恩病, 生物标志物, 生物信息学

Abstract:

Objective To investigate shared immune-related genes between periodontitis and Crohn's disease (CD), explore their common pathophysiology, and assess the value of relevant genes as diagnostic biomarkers. Methods Gene expression data for CD and periodontitis were obtained from the GEO database. After data preprocessing, differential expression analysis was performed to identify differentially expressed genes (DEGs). Functional enrichment and disease ontology analysis were conducted on the common DEGs, and a protein-protein interaction (PPI) network was constructed. Weighted gene co-expression network analysis (WGCNA) was applied to the CD and periodontitis databases to determine key modules most relevant to the diseases. Perturbation genes were further selected. Immunocyte profiles in CD and periodontitis were assessed using single-sample gene set enrichment analysis (ssGSEA). A diagnostic model for CD and periodontitis, based on genes most associated with immunity, was constructed and validated using an independent dataset. Results A total of 143 common differentially expressed genes were identified. Functional enrichment analysis highlighted the significant role of immunity in both CD and periodontitis. WGCNA analysis identified 11 perturbation genes, and subsequent immune infiltration analysis revealed four genes (Genes HLA-DMA, CD38, PIM2 and TGM2) closely associated with CD, periodontitis and immune response. The diagnostic model built using these four genes demonstrated excellent diagnostic performance in both the training and external validation datasets. Conclusion Genes HLA-DMA, CD38, PIM2 and TGM2 are involved in the development of CD and periodontitis, playing crucial roles in immune responses. The diagnostic model constructed with these four genes exhibits strong diagnostic efficacy for both diseases.

Key words: immunity, diagnostic, periodontitis, Crohn's disease, biomarkers, bioinformatics

中图分类号:

R574
R781.4

张志豪, 杨益, 王月秋, 孙思怡, 陈虹, 舒菲, 刘梅. 克罗恩病和牙周炎的共有免疫相关基因及其作为诊断生物标志物的潜力[J]. 口腔医学, 2024, 44(3): 184-191.

ZHANG Zhihao, YANG Yi, WANG Yueqiu, SUN Siyi, CHEN Hong, SHU Fei, LIU Mei. Immune-related genes shared between Crohn's disease and periodontitis and their potential as diagnostic biomarkers[J]. Stomatology, 2024, 44(3): 184-191.

图/表 7

图1

图2

图3

图4

图5

图6

图7

参考文献 45

[1]	van der Sloot KWJ, Amini M, Peters V, et al. Inflammatory bowel diseases: Review of known environmental protective and risk factors involved[J]. Inflamm Bowel Dis, 2017, 23(9):1499-1509. doi: 10.1097/MIB.0000000000001217 pmid: 28777099
[2]	Torres J, Mehandru S, Colombel JF, et al. Crohn's disease[J]. Lancet, 2017, 389(10080):1741-1755. doi: S0140-6736(16)31711-1 pmid: 27914655
[3]	McDonald LC, Gerding DN, Johnson S, et al. Clinical practice guidelines for Clostridium difficile infection in adults and children: 2017 update by the infectious diseases society of America (IDSA) and society for healthcare epidemiology of America (SHEA)[J]. Clin Infect Dis, 2018, 66(7):e1-e48. doi: 10.1093/cid/cix1085
[4]	Argollo M, Gilardi D, Peyrin-Biroulet C, et al. Comorbidities in inflammatory bowel disease: A call for action[J]. Lancet Gastroenterol Hepatol, 2019, 4(8):643-654.
[5]	Ni J, Wu GD, Albenberg L, et al. Gut microbiota and IBD: Causation or correlation?[J]. Nat Rev Gastroenterol Hepatol, 2017, 14(10):573-584. doi: 10.1038/nrgastro.2017.88 pmid: 28743984
[6]	Bunte K, Beikler T. Th17 cells and the IL-23/IL-17 axis in the pathogenesis of periodontitis and immune-mediated inflammatory diseases[J]. Int J Mol Sci, 2019, 20(14):3394. doi: 10.3390/ijms20143394
[7]	Imai J, Ichikawa H, Kitamoto S, et al. A potential pathogenic association between periodontal disease and Crohn's disease[J]. JCI Insight, 2021, 6(23):e148543. doi: 10.1172/jci.insight.148543
[8]	de Vries SAG, Tan CXW, Bouma G, et al. Salivary function and oral health problems in Crohn's disease patients[J]. Inflamm Bowel Dis, 2018, 24(6):1361-1367. doi: 10.1093/ibd/izy017 pmid: 29718221
[9]	She YY, Kong XB, Ge YP, et al. Periodontitis and inflammatory bowel disease: A meta-analysis[J]. BMC Oral Health, 2020, 20(1):67. doi: 10.1186/s12903-020-1053-5
[10]	Kitamoto S, Nagao-Kitamoto H, Hein R, et al. The bacterial connection between the oral cavity and the gut diseases[J]. J Dent Res, 2020, 99(9):1021-1029. doi: 10.1177/0022034520924633 pmid: 32464078
[11]	Abdelbary MMH, Hatting M, Bott A, et al. The oral-gut axis: Salivary and fecal microbiome dysbiosis in patients with inflammatory bowel disease[J]. Front Cell Infect Microbiol, 2022, 12: 1010853. doi: 10.3389/fcimb.2022.1010853
[12]	谢雨桐, 胡颖哲, 高鹏玉, 等. 牙周炎与肠道菌群相关性研究进展[J]. 口腔医学, 2022, 42(11):1047-1051.
[13]	Demmer RT, Behle JH, Wolf DL, et al. Transcriptomes in healthy and diseased gingival tissues[J]. J Periodontol, 2008, 79(11):2112-2124. doi: 10.1902/jop.2008.080139 pmid: 18980520
[14]	Kebschull M, Demmer RT, Grün B, et al. Gingival tissue transcriptomes identify distinct periodontitis phenotypes[J]. J Dent Res, 2014, 93(5):459-468. doi: 10.1177/0022034514527288 pmid: 24646639
[15]	Palmer NP, Silvester JA, Lee JJ, et al. Concordance between gene expression in peripheral whole blood and colonic tissue in children with inflammatory bowel disease[J]. PLoS One, 2019, 14(10):e0222952. doi: 10.1371/journal.pone.0222952
[16]	Vancamelbeke M, Vanuytsel T, Farré R, et al. Genetic and transcriptomic bases of intestinal epithelial barrier dysfunction in inflammatory bowel disease[J]. Inflamm Bowel Dis, 2017, 23(10):1718-1729. doi: 10.1097/MIB.0000000000001246 pmid: 28885228
[17]	Ritchie ME, Phipson B, Wu D, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies[J]. Nucleic Acids Res, 2015, 43(7):e47. doi: 10.1093/nar/gkv007
[18]	Villanueva RAM, Chen ZJ. ggplot2: Elegant graphics for data analysis (2nd Ed.)[J]. Meas, 2019, 17(3):160-167.
[19]	Wu TZ, Hu EQ, Xu SB, et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data[J]. Innovation (Camb), 2021, 2(3):100141.
[20]	Yu GC, Wang LG, Yan GR, et al. DOSE: An R/Bioconductor package for disease ontology semantic and enrichment analysis[J]. Bioinformatics, 2015, 31(4):608-609. doi: 10.1093/bioinformatics/btu684 pmid: 25677125
[21]	Consortium TGO. The Gene Ontology Resource: 20 years and still GOing strong[J]. Nucleic Acids Res, 2019, 47(D1):D330-D338. doi: 10.1093/nar/gky1055
[22]	Kanehisa M, Furumichi M, Sato Y, et al. KEGG: Integrating viruses and cellular organisms[J]. Nucleic Acids Res, 2021, 49(D1):D545-D551. doi: 10.1093/nar/gkaa970 pmid: 33125081
[23]	Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets[J]. Nucleic Acids Res, 2019, 47(D1):D607-D613. doi: 10.1093/nar/gky1131
[24]	Doncheva NT, Morris JH, Gorodkin J, et al. Cytoscape StringApp: Network analysis and visualization of proteomics data[J]. J Proteome Res, 2019, 18(2):623-632. doi: 10.1021/acs.jproteome.8b00702 pmid: 30450911
[25]	Bader GD, Hogue CWV. An automated method for finding molecular complexes in large protein interaction networks[J]. BMC Bioinformatics, 2003, 4: 2. pmid: 12525261
[26]	Langfelder P, Horvath S. WGCNA: An R package for weighted correlation network analysis[J]. BMC Bioinformatics, 2008, 9: 559. doi: 10.1186/1471-2105-9-559 pmid: 19114008
[27]	Hänzelmann S, Castelo R, Guinney J. GSVA: Gene set variation analysis for microarray and RNA-seq data[J]. BMC Bioinformatics, 2013, 14: 7. doi: 10.1186/1471-2105-14-7 pmid: 23323831
[28]	Bindea G, Mlecnik B, Tosolini M, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer[J]. Immunity, 2013, 39(4):782-795. doi: 10.1016/j.immuni.2013.10.003 pmid: 24138885
[29]	Núñez E, Steyerberg EW, Núñez J. Regression modeling strategies[J]. Rev Esp Cardiol, 2011, 64(6):501-507. doi: 10.1016/j.recesp.2011.01.019
[30]	Bertl K, Burisch J, Pandis N, et al. Periodontitis prevalence in patients with ulcerative colitis and Crohn's disease-PPCC: A case-control study[J]. J Clin Periodontol, 2022, 49(12):1262-1274. doi: 10.1111/jcpe.v49.12
[31]	Sun BY, Liu BY, Gao XJ, et al. Metagenomic analysis of saliva reveals disease-associated microbiotas in patients with periodontitis and Crohn's disease-associated periodontitis[J]. Front Cell Infect Microbiol, 2021, 11: 719411. doi: 10.3389/fcimb.2021.719411
[32]	Qian J, Lu J, Huang Y, et al. Periodontitis salivary microbiota worsens colitis[J]. J Dent Res, 2022, 101(5):559-568. doi: 10.1177/00220345211049781
[33]	Juhász K, Buzás K, Duda E. Importance of reverse signaling of the TNF superfamily in immune regulation[J]. Expert Rev Clin Immunol, 2013, 9(4):335-348. doi: 10.1586/eci.13.14
[34]	Li XX, Bechara R, Zhao JJ, et al. IL-17 receptor-based signaling and implications for disease[J]. Nat Immunol, 2019, 20(12):1594-1602. doi: 10.1038/s41590-019-0514-y pmid: 31745337
[35]	Aletaha D, Smolen JS. Diagnosis and management of rheumatoid arthritis: A review[J]. JAMA, 2018, 320(13):1360-1372. doi: 10.1001/jama.2018.13103 pmid: 30285183
[36]	Ghoreschi K, Balato A, Enerbäck C, et al. Therapeutics targeting the IL-23 and IL-17 pathway in psoriasis[J]. Lancet, 2021, 397(10275):754-766. doi: 10.1016/S0140-6736(21)00184-7 pmid: 33515492
[37]	Ferrante A. HLA-DM: Arbiter conformationis[J]. Immunology, 2013, 138(2):85-92. doi: 10.1111/imm.12030 pmid: 23113687
[38]	Pedersen TK, Brown EM, Plichta DR, et al. The CD4⁺ T cell response to a commensal-derived epitope transitions from a tolerant to an inflammatory state in Crohn's disease[J]. Immunity, 2022, 55(10):1909-1923.e6. doi: 10.1016/j.immuni.2022.08.016 pmid: 36115338
[39]	Almubarak A, Tanagala KKK, Papapanou PN, et al. Disruption of monocyte and macrophage homeostasis in periodontitis[J]. Front Immunol, 2020, 11: 330. doi: 10.3389/fimmu.2020.00330 pmid: 32210958
[40]	Piedra-Quintero ZL, Wilson Z, Nava P, et al. CD38: An immunomodulatory molecule in inflammation and autoimmunity[J]. Front Immunol, 2020, 11: 597959. doi: 10.3389/fimmu.2020.597959
[41]	Mahanonda R, Champaiboon C, Subbalekha K, et al. Human memory B cells in healthy gingiva, gingivitis, and periodontitis[J]. J Immunol, 2016, 197(3):715-725. doi: 10.4049/jimmunol.1600540 pmid: 27335500
[42]	Wang YX, Xiu J, Ren CE, et al. Protein kinase PIM2: A simple PIM family kinase with complex functions in cancer metabolism and therapeutics[J]. J Cancer, 2021, 12(9):2570-2581. doi: 10.7150/jca.53134 pmid: 33854618
[43]	da Silva FAR, Pascoal LB, Dotti I, et al. Whole transcriptional analysis identifies markers of B, T and plasma cell signaling pathways in the mesenteric adipose tissue associated with Crohn's disease[J]. J Transl Med, 2020, 18(1):44. doi: 10.1186/s12967-020-02220-3 pmid: 32000799
[44]	Lai TS, Greenberg CS. TGM2 and implications for human disease: Role of alternative splicing[J]. Front Biosci (Landmark Ed), 2013, 18(2):504-519. doi: 10.2741/4117
[45]	Lukasak BJ, Mitchener MM, Kong LC, et al. TGM2-mediated histone transglutamination is dictated by steric accessibility[J]. Proc Natl Acad Sci USA, 2022, 119(43):e2208672119.