Zhuo Yongjie, Weng Mengjie, Lin Jiaqun, Wu Xiaoting, Nie Kun, Yang Liyan, Cui Jiong, Wan Jianxin
Department of Nephrology, Blood Purification Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Fujian Clinical Research Center for Metabolic Chronic Kidney Disease, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
J Diabetes Res. 2025 Aug 13;2025:6916580. doi: 10.1155/jdr/6916580. eCollection 2025.
Chronic inflammation plays a key role in diabetic nephropathy (DN), yet the impact of tertiary lymphoid structures (TLSs) on disease progression remains poorly understood. This study explored the relationship between TLS maturity and renal outcomes in patients with DN. This study included 117 biopsy-confirmed DN patients from the First Affiliated Hospital of Fujian Medical University. Patients were grouped based on TLS maturity, as determined by immunohistochemical staining. Clinical, laboratory, and pathological data were gathered, and Cox regression models were applied to assess renal outcome risk factors. Kaplan-Meier curves were constructed to compare renal survival among groups. A web-based model integrating TLS maturity, urinary albumin-to-creatinine ratio (UACR), and renal pathology classification was developed. Mature TLSs were associated with worse renal prognosis, with greater disease progression in the TLS+ group (75.4% vs. 53.3%, = 0.006). Multivariate Cox regression analysis identified TLS maturity (HR = 1.819, 95% CI: 1.144-2.893, = 0.011), DN glomerular classification (HR = 1.511, 95% CI: 1.057-2.160, = 0.024), and UACR (HR = 1.121, 95% CI: 1.038-1.210, = 0.004) as independent risk factors. The dynamic nomogram demonstrated strong predictive performance. TLS maturity independently predicts renal function decline in DN and may support personalized risk assessment through a web-based model.
慢性炎症在糖尿病肾病(DN)中起关键作用,然而三级淋巴结构(TLSs)对疾病进展的影响仍知之甚少。本研究探讨了DN患者TLS成熟度与肾脏结局之间的关系。本研究纳入了福建医科大学附属第一医院117例经活检确诊的DN患者。根据免疫组织化学染色确定的TLS成熟度对患者进行分组。收集临床、实验室和病理数据,并应用Cox回归模型评估肾脏结局危险因素。构建Kaplan-Meier曲线比较各组间的肾脏生存率。开发了一个整合TLS成熟度、尿白蛋白与肌酐比值(UACR)和肾脏病理分类的网络模型。成熟的TLSs与更差的肾脏预后相关,TLS+组的疾病进展更严重(75.4%对53.3%,P = 0.006)。多变量Cox回归分析确定TLS成熟度(HR = 1.819,95%CI:1.144 - 2.893,P = 0.011)、DN肾小球分类(HR = 1.511,95%CI:1.057 - 2.160,P = 0.024)和UACR(HR = 1.121,95%CI:1.038 - 1.210,P = 0.004)为独立危险因素。动态列线图显示出强大的预测性能。TLS成熟度可独立预测DN患者的肾功能下降,并可能通过基于网络的模型支持个性化风险评估。