Identification of shared diagnostic biomarkers and potential co-morbidity mechanisms between primary Sjogren's syndrome and chronic kidney disease.

IF 2.8 3区 医学 Q2 RHEUMATOLOGY
Shushu Jiang, Yin Dong, Zhaohui Wang, Minglu Liang
{"title":"Identification of shared diagnostic biomarkers and potential co-morbidity mechanisms between primary Sjogren's syndrome and chronic kidney disease.","authors":"Shushu Jiang, Yin Dong, Zhaohui Wang, Minglu Liang","doi":"10.1007/s10067-025-07623-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The mechanisms linking primary Sjogren's syndrome (pSS) to chronic kidney disease (CKD) are obscure. Our study sought to uncover shared genetic connections and pathways between these conditions.</p><p><strong>Methods: </strong>Datasets for pSS and CKD were sourced from GEO. WGCNA alongside differential expression assessment was employed to pinpoint common genes. GO and KEGG were applied for gene enrichment. Key genes were selected using LASSO, Random Forest, and SVM-RFE. Clinical prediction models were constructed using multi-factor logistic regression. GSEA and immune infiltration analyses explored the mechanisms linking key genes in pSS and CKD. MR analysis and SMR approach assessed the genetic link between pSS and CKD, evaluating the impact of co-shared genes on these conditions.</p><p><strong>Result: </strong>We identified 104 common genes using WGCNA and differential expression analysis. GO and KEGG analyses hinted at cancer involvement in both diseases. Machine learning models pinpointed five genes as strong diagnostic biomarkers for both pSS and CKD, with NUDT1 and COMMD2 validated in independent cohorts. Clinical prediction models were constructed based on these two genes. GSEA and immune infiltration analysis suggested immune processes, particularly T cell infiltration, were implicated in both diseases. Bidirectional MR analysis failed to establish a causal link between the two diseases, yet SMR analysis revealed associations between NUDT1 and COMMD2 expression and the development of pSS and CKD.</p><p><strong>Conclusion: </strong>This study uncovered crucial genes shared between pSS and CKD, shedding light on their co-morbidity mechanisms and possible diagnostic biomarkers. Key Points • This study unveils for the first time the immunological association between PSS and CKD. • NUDT1 and COMMD2 are identified as key molecules in the comorbidity mechanism of PSS and CKD. • A diagnostic model for the comorbidity of PSS and CKD is constructed.</p>","PeriodicalId":10482,"journal":{"name":"Clinical Rheumatology","volume":" ","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Rheumatology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10067-025-07623-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RHEUMATOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: The mechanisms linking primary Sjogren's syndrome (pSS) to chronic kidney disease (CKD) are obscure. Our study sought to uncover shared genetic connections and pathways between these conditions.

Methods: Datasets for pSS and CKD were sourced from GEO. WGCNA alongside differential expression assessment was employed to pinpoint common genes. GO and KEGG were applied for gene enrichment. Key genes were selected using LASSO, Random Forest, and SVM-RFE. Clinical prediction models were constructed using multi-factor logistic regression. GSEA and immune infiltration analyses explored the mechanisms linking key genes in pSS and CKD. MR analysis and SMR approach assessed the genetic link between pSS and CKD, evaluating the impact of co-shared genes on these conditions.

Result: We identified 104 common genes using WGCNA and differential expression analysis. GO and KEGG analyses hinted at cancer involvement in both diseases. Machine learning models pinpointed five genes as strong diagnostic biomarkers for both pSS and CKD, with NUDT1 and COMMD2 validated in independent cohorts. Clinical prediction models were constructed based on these two genes. GSEA and immune infiltration analysis suggested immune processes, particularly T cell infiltration, were implicated in both diseases. Bidirectional MR analysis failed to establish a causal link between the two diseases, yet SMR analysis revealed associations between NUDT1 and COMMD2 expression and the development of pSS and CKD.

Conclusion: This study uncovered crucial genes shared between pSS and CKD, shedding light on their co-morbidity mechanisms and possible diagnostic biomarkers. Key Points • This study unveils for the first time the immunological association between PSS and CKD. • NUDT1 and COMMD2 are identified as key molecules in the comorbidity mechanism of PSS and CKD. • A diagnostic model for the comorbidity of PSS and CKD is constructed.

原发性干燥综合征和慢性肾脏疾病之间的共同诊断生物标志物和潜在合并症机制的鉴定
背景:原发性干燥综合征(pSS)与慢性肾脏疾病(CKD)之间的联系机制尚不清楚。我们的研究试图揭示这些疾病之间的共同遗传联系和途径。方法:pSS和CKD数据来源于GEO。采用WGCNA和差异表达评估来确定常见基因。应用GO和KEGG进行基因富集。采用LASSO、Random Forest和SVM-RFE筛选关键基因。采用多因素logistic回归建立临床预测模型。GSEA和免疫浸润分析探讨了pSS和CKD关键基因之间的联系机制。MR分析和SMR方法评估了pSS和CKD之间的遗传联系,评估了共共享基因对这些疾病的影响。结果:通过WGCNA和差异表达分析,共鉴定出104个常见基因。GO和KEGG分析表明,这两种疾病都与癌症有关。机器学习模型确定了五个基因作为pSS和CKD的强诊断生物标志物,其中NUDT1和COMMD2在独立队列中得到验证。基于这两个基因构建临床预测模型。GSEA和免疫浸润分析提示免疫过程,特别是T细胞浸润与这两种疾病有关。双向MR分析未能建立两种疾病之间的因果关系,但SMR分析揭示了NUDT1和COMMD2表达与pSS和CKD的发展之间的关联。结论:本研究揭示了pSS和CKD之间共享的关键基因,揭示了它们的合并症机制和可能的诊断生物标志物。•本研究首次揭示了PSS与CKD之间的免疫学关联。•NUDT1和COMMD2被确定为PSS和CKD共病机制的关键分子。•建立PSS与CKD合并症的诊断模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Clinical Rheumatology
Clinical Rheumatology 医学-风湿病学
CiteScore
6.90
自引率
2.90%
发文量
441
审稿时长
3 months
期刊介绍: Clinical Rheumatology is an international English-language journal devoted to publishing original clinical investigation and research in the general field of rheumatology with accent on clinical aspects at postgraduate level. The journal succeeds Acta Rheumatologica Belgica, originally founded in 1945 as the official journal of the Belgian Rheumatology Society. Clinical Rheumatology aims to cover all modern trends in clinical and experimental research as well as the management and evaluation of diagnostic and treatment procedures connected with the inflammatory, immunologic, metabolic, genetic and degenerative soft and hard connective tissue diseases.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信