Volume 41 Issue 1
Jan.  2025
Turn off MathJax
Article Contents
Gan WJ,Wang JR,He J,et al.Two-sample Mendelian randomization analysis of the causal relationship between human immune cell phenotypes and keloids[J].Chin J Burns Wounds,2025,41(1):84-93.DOI: 10.3760/cma.j.cn501225-20231130-00219.
Citation: Gan WJ,Wang JR,He J,et al.Two-sample Mendelian randomization analysis of the causal relationship between human immune cell phenotypes and keloids[J].Chin J Burns Wounds,2025,41(1):84-93.DOI: 10.3760/cma.j.cn501225-20231130-00219.

Two-sample Mendelian randomization analysis of the causal relationship between human immune cell phenotypes and keloids

doi: 10.3760/cma.j.cn501225-20231130-00219
Funds:

General Program of National Natural Science Foundation of China 82172205

Guangdong Basic and Applied Basic Research Foundation Regional Joint Fund 2020A1515110432

More Information
  • Corresponding author: Chen Xiaodong, Email: cxd234@163.com
  • Received Date: 2023-11-30
  •   Objective  To explore the causal relationship between human immune cell phenotypes and keloids.  Methods  This study was based on a two-sample Mendelian randomization (MR) analysis. Human immune cell phenotypes were considered as the exposure factors, and keloid was the outcome. Data on immune cell phenotypes (3 757 samples) and keloids (668 samples) were obtained from the genome-wide association study database. Using single nucleotide polymorphisms (SNPs) significantly associated with immune cell phenotypes as instrumental variables with the influence of weak instrumental variables being excluded, two-sample MR analysis was employed to evaluate the causal relationship between 731 human immune cell phenotypes and keloids. The inverse variance weighted (IVW) method was used to infer causal relationships, and the MR-Egger, weighted median, and weighted mode methods were used for validation. For SNPs of immune cell phenotypes meeting the hypothesis, the Cochran Q test was used to assess heterogeneity, and the MR-Egger regression and MR-PRESSO outlier tests were used to evaluate horizontal pleiotropy.  Results  A total of 18 204 SNPs meeting the significant threshold (P<1×10⁻⁵) were selected as instrumental variables for 731 immune cell phenotypes, and none of these SNPs were weak instrumental variables (with F values all >10). According to the IVW method, 21 immune cell phenotypes were identified with potential causal relationships to keloids, among which the CD62L- monocyte absolute count, CD19 on naive-mature B cell, CD19 on IgD+ B cell, CD27 on plasma blast-plasma cell, CD86 on CD62L+ myeloid dendritic cell, CD45 on natural killer T cell, CD25 on CD39+ CD4+ regulatory T cell, CD45 on monocytic myeloid-derived suppressor cells, CD8 on effector memory CD8+ T cell, and CD45RA on resting CD4+ regulatory T cell showed significant positive correlations with keloids (with odds ratios of 1.12, 1.09, 1.08, 1.21, 1.13, 1.12, 1.17, 1.11, 1.10, and 1.07, respectively, 95% confidence intervals of 1.03-1.23, 1.02-1.16, 1.01-1.15, 1.06-1.38, 1.02-1.25, 1.01-1.24, 1.03-1.33, 1.00-1.23, 1.00-1.20, and 1.01-1.13, respectively, P<0.05), while the activated and secreted CD4+ regulatory T cell absolute count, CD25 on unswitched memory B cell, plasmacytoid dendritic cell absolute count, CD14 on monocytic myeloid-derived suppressor cells, CD8 on natural killer T cell, CD20 on IgD+ CD38+ B cell, CD11c+ CD62L- monocyte absolute count, CD66b++ myeloid cell absolute count, CD11c on granulocytes, CD14 on CD14+ CD16+ monocyte, and CD3 on central memory CD8+ T cell showed significant negative correlations with keloids (with odds ratios of 0.95, 0.93, 0.93, 0.93, 0.91, 0.89, 0.89, 0.88, 0.87, 0.86, and 0.85, respectively, 95% confidence intervals of 0.90-1.00, 0.87-0.99, 0.88-0.99, 0.87-0.99, 0.84-1.00, 0.81-0.98, 0.81-0.98, 0.79-0.99, 0.78-0.96, 0.75-0.99, and 0.74-0.96, respectively, P<0.05). MR-Egger method confirmed the potential causal relationship existing respectively between CD25 on CD39+ CD4+ regulatory T cell, CD86 on CD62L+ myeloid dendritic cell, CD19 on IgD+ B cell, CD45RA on resting CD4+ regulatory T cell, CD3 on central memory CD8+ T cell and keloids (with odds ratios of 1.32, 1.22, 1.11, 1.09, and 0.73, respectively, 95% confidence intervals of 1.03-1.70, 1.04-1.44, 1.02-1.21, 1.01-1.19, and 0.55-0.95, respectively, P<0.05). The weighted median method confirmed the potential causal relationship existing respectively between CD45 on natural killer T cell, activated and secreted CD4+ regulatory T cells absolute count, CD20 on IgD+ CD38+ B cell, CD66b++ myeloid cell absolute count and keloids (with odds ratios of 1.15, 0.93, 0.87, and 0.83, respectively, 95% confidence intervals of 1.01-1.31, 0.86-1.00, 0.77-0.98, and 0.71-0.96, respectively, P<0.05). Among them, the potential causal relationship between CD20 on IgD+ CD38+ B cell and keloids was further verified by the weighted mode method (with odds ratio of 0.86, 95% confidence interval of 0.77-0.97, P<0.05). According to the aforementioned IVW method analysis results, the SNPs associated with the 21 immune cell phenotypes that had a significant causal relationship with keloids showed no significant heterogeneity (P>0.05) or significant horizontal pleiotropy (P>0.05).  Conclusions  From a genetic perspective, the potential causal relationships between 21 human immune cell phenotypes and keloids have been revealed, of which 10 immune cell phenotypes may be risk factors for keloids, while 11 immune cell phenotypes may act as protective factors for keloids.

     

  • loading
  • [1]
    雷继安,周圆,秦泽莲.炎症反应参与瘢痕疙瘩形成的研究进展[J].中华烧伤杂志,2021,37(6):591-595.DOI: 10.3760/cma.j.cn501120-20200312-00154.
    [2]
    OgawaR,AkitaS,AkaishiS,et al.Diagnosis and treatment of keloids and hypertrophic scars-Japan Scar Workshop consensus document 2018[J/OL].Burns Trauma,2019,7:39[2023-11-30]. https://pubmed.ncbi.nlm.nih.gov/31890718/.DOI: 10.1186/s41038-019-0175-y.
    [3]
    贾赤宇,陈泠西.瘢痕疙瘩的肿瘤特征[J].中华烧伤杂志,2021,37(4):301-305.DOI: 10.3760/cma.j.cn501120-20200529-00289.
    [4]
    WangZC,ZhaoWY,CaoY,et al.The roles of inflammation in keloid and hypertrophic scars[J].Front Immunol,2020,11:603187.DOI: 10.3389/fimmu.2020.603187.
    [5]
    LeeAR,LeeSY,ChoiJW,et al.Establishment of a humanized mouse model of keloid diseases following the migration of patient immune cells to the lesion: patient-derived keloid xenograft (PDKX) model[J].Exp Mol Med,2023,55(8):1713-1719.DOI: 10.1038/s12276-023-01045-6.
    [6]
    HellwegeJN,RussellSB,WilliamsSM,et al.Gene-based evaluation of low-frequency variation and genetically-predicted gene expression impacting risk of keloid formation[J].Ann Hum Genet,2018,82(4):206-215.DOI: 10.1111/ahg.12245.
    [7]
    YinX,BuW,FangF,et al.Keloid biomarkers and their correlation with immune infiltration[J].Front Genet,2022,13:784073.DOI: 10.3389/fgene.2022.784073.
    [8]
    XuH,ZhuZ,HuJ,et al.Downregulated cytotoxic CD8+ T-cell identifies with the NKG2A-soluble HLA-E axis as a predictive biomarker and potential therapeutic target in keloids[J].Cell Mol Immunol,2022,19(4):527-539.DOI: 10.1038/s41423-021-00834-1.
    [9]
    JinQ,GuiL,NiuF,et al.Macrophages in keloid are potent at promoting the differentiation and function of regulatory T cells[J].Exp Cell Res,2018,362(2):472-476.DOI: 10.1016/j.yexcr.2017.12.011.
    [10]
    LeeCC,TsaiCH,ChenCH,et al.An updated review of the immunological mechanisms of keloid scars[J].Front Immunol,2023,14:1117630.DOI: 10.3389/fimmu.2023.1117630.
    [11]
    DaviesNM,HolmesMV,Davey SmithG.Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians[J].BMJ,2018,362:k601.DOI: 10.1136/bmj.k601.
    [12]
    SandersonE,GlymourMM,HolmesMV,et al. Mendelian randomization[J].Nat Rev Methods Primers,2022,2:6.DOI: 10.1038/s43586-021-00092-5.
    [13]
    Gagliano TaliunSA,EvansDM.Ten simple rules for conducting a mendelian randomization study[J].PLoS Comput Biol,2021,17(8):e1009238.DOI: 10.1371/journal.pcbi.1009238.
    [14]
    OrrùV,SteriM,SidoreC,et al.Complex genetic signatures in immune cells underlie autoimmunity and inform therapy[J].Nat Genet,2020,52(10):1036-1045.DOI: 10.1038/s41588-020-0684-4.
    [15]
    SidoreC,BusoneroF,MaschioA,et al.Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers[J].Nat Genet,2015,47(11):1272-1281.DOI: 10.1038/ng.3368.
    [16]
    SakaueS,KanaiM,TanigawaY,et al.A cross-population atlas of genetic associations for 220 human phenotypes[J].Nat Genet,2021,53(10):1415-1424.DOI: 10.1038/s41588-021-00931-x.
    [17]
    LvX,HuZ,LiangF,et al.Causal relationship between ischemic stroke and its subtypes and frozen shoulder: a two-sample Mendelian randomization analysis[J].Front Neurol,2023,14:1178051.DOI: 10.3389/fneur.2023.1178051.
    [18]
    BurgessS,ThompsonSG,Genetics CollaborationCRP CHD.Avoiding bias from weak instruments in Mendelian randomization studies[J].Int J Epidemiol,2011,40(3):755-764.DOI: 10.1093/ije/dyr036.
    [19]
    BurgessS,ThompsonSG.Interpreting findings from Mendelian randomization using the MR-Egger method[J].Eur J Epidemiol,2017,32(5):377-389.DOI: 10.1007/s10654-017-0255-x.
    [20]
    GauglitzGG,KortingHC,PavicicT,et al.Hypertrophic scarring and keloids: pathomechanisms and current and emerging treatment strategies[J].Mol Med,2011,17(1/2):113-125.DOI: 10.2119/molmed.2009.00153.
    [21]
    BurgessS,ButterworthA,ThompsonSG.Mendelian randomization analysis with multiple genetic variants using summarized data[J].Genet Epidemiol,2013,37(7):658-665.DOI: 10.1002/gepi.21758.
    [22]
    YangWY,ShaoY,Lopez-PastranaJ,et al.Pathological conditions re-shape physiological Tregs into pathological Tregs[J/OL].Burns Trauma,2015,3(1):1[2023-11-30].https://pubmed.ncbi.nlm.nih.gov/26623425/.DOI: 10.1186/s41038-015-0001-0.
    [23]
    MuraoN,SeinoK,HayashiT,et al.Treg-enriched CD4+ T cells attenuate collagen synthesis in keloid fibroblasts[J].Exp Dermatol,2014,23(4):266-271.DOI: 10.1111/exd.12368.
    [24]
    ShortWD,WangX,KeswaniSG.The role of T lymphocytes in cutaneous scarring[J].Adv Wound Care (New Rochelle),2022,11(3):121-131.DOI: 10.1089/wound.2021.0059.
    [25]
    ChenY,JinQ,FuX,et al.Connection between T regulatory cell enrichment and collagen deposition in keloid[J].Exp Cell Res,2019,383(2):111549.DOI: 10.1016/j.yexcr.2019.111549.
    [26]
    TianY,BaborM,LaneJ,et al.Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA[J].Nat Commun,2017,8(1):1473.DOI: 10.1038/s41467-017-01728-5.
    [27]
    CheungJ,ZahorowskaB,SuranyiM,et al.CD4+CD25+ T regulatory cells in renal transplantation[J].Front Immunol,2022,13:1017683.DOI: 10.3389/fimmu.2022.1017683.
    [28]
    HarrisF,BerdugoYA,TreeT.IL-2-based approaches to Treg enhancement[J].Clin Exp Immunol,2023,211(2):149-163.DOI: 10.1093/cei/uxac105.
    [29]
    AbbasAK,TrottaE,Simeonov DR,et al.Revisiting IL-2: biology and therapeutic prospects[J].Sci Immunol,2018,3(25):eaat1482.DOI: 10.1126/sciimmunol.aat1482.
    [30]
    LykhopiyV,MalviyaV,Humblet-BaronS,et al.IL-2 immunotherapy for targeting regulatory T cells in autoimmunity[J].Genes Immun,2023,24(5):248-262.DOI: 10.1038/s41435-023-00221-y.
    [31]
    ShanM,LiuH,HaoY,et al.The role of CD28 and CD8+ T cells in keloid development[J].Int J Mol Sci,2022,23(16):8862.DOI: 10.3390/ijms23168862.
    [32]
    ChenZ,ZhouL,WonT,et al.Characterization of CD45RO+ memory T lymphocytes in keloid disease[J].Br J Dermatol,2018,178(4):940-950.DOI: 10.1111/bjd.16173.
    [33]
    TannoH,KawakamiK,KannoE,et al.Invariant NKT cells promote skin wound healing by preventing a prolonged neutrophilic inflammatory response[J].Wound Repair Regen,2017,25(5):805-815.DOI: 10.1111/wrr.12588.
    [34]
    SîrbulescuRF,BoehmCK,SoonE,et al.Mature B cells accelerate wound healing after acute and chronic diabetic skin lesions[J].Wound Repair Regen,2017,25(5):774-791.DOI: 10.1111/wrr.12584.
    [35]
    AndersonJB,HarrantAB,Navarro-AlvarezN,et al. 4371 The role of B cells in keloid formation[J]. J Clin Transl Sci,2020, 4(Suppl 1):S18-19. DOI: 10.1017/cts.2020.97.
    [36]
    ShanM,WangY.Viewing keloids within the immune microenvironment[J].Am J Transl Res,2022,14(2):718-727.
    [37]
    RathM,PitiotA,KirrM,et al.Multi-antigen imaging reveals inflammatory DC, ADAM17 and Neprilysin as effectors in keloid formation[J].Int J Mol Sci,2021,22(17):9417.DOI: 10.3390/ijms22179417.
    [38]
    CalventeCJ,TamedaM,JohnsonCD,et al.Neutrophils contribute to spontaneous resolution of liver inflammation and fibrosis via microRNA-223[J].J Clin Invest,2019,129(10):4091-4109.DOI: 10.1172/JCI122258.
    [39]
    SaijouE,EnomotoY,MatsudaM,et al.Neutrophils alleviate fibrosis in the CCl4-induced mouse chronic liver injury model[J].Hepatol Commun,2018,2(6):703-717.DOI: 10.1002/hep4.1178.
    [40]
    ShaoY,GuoZ,YangY,et al.Neutrophil extracellular traps contribute to myofibroblast differentiation and scar hyperplasia through the Toll-like receptor 9/nuclear factor Kappa-B/interleukin-6 pathway[J/OL].Burns Trauma,2022,10:tkac044[2023-11-30].https://pubmed.ncbi.nlm.nih.gov/36406661/.DOI: 10.1093/burnst/tkac044.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(2)  / Tables(4)

    Article Metrics

    Article views (196) PDF downloads(11) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return