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2型糖尿病中的炎症与死亡预测:与色氨酸代谢存在交织联系的证据

Inflammation and Prediction of Death in Type 2 Diabetes. Evidence of an Intertwined Link With Tryptophan Metabolism.

作者信息

Menzaghi Claudia, Marucci Antonella, Mastroianno Mario, Di Ciaccia Giulio, Armillotta Maria Pia, Prehn Cornelia, Salvemini Lucia, Mangiacotti Davide, Adamski Jerzy, Fontana Andrea, De Cosmo Salvatore, Lamacchia Olga, Copetti Massimiliano, Trischitta Vincenzo

机构信息

Research Unit of Diabetes and Endocrine Diseases, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," 71013 San Giovanni Rotondo, Italy.

Scientific Direction, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza," 71013 San Giovanni Rotondo, Italy.

出版信息

J Clin Endocrinol Metab. 2025 Apr 22;110(5):e1323-e1333. doi: 10.1210/clinem/dgae593.

DOI:10.1210/clinem/dgae593
PMID:39193712
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12012783/
Abstract

CONTEXT

The role of inflammation in shaping death risk in diabetes is still unclear.

OBJECTIVE

To study whether inflammation is associated with and helps predict mortality risk in patients with type 2 diabetes. To explore the intertwined link between inflammation and tryptophan metabolism on death risk.

METHODS

There were 2 prospective cohorts: the aggregate Gargano Mortality Study (1731 individuals; 872 all-cause deaths) as the discovery sample, and the Foggia Mortality Study (490 individuals; 256 deaths) as validation sample. Twenty-seven inflammatory markers were measured. Causal mediation analysis and in vitro studies were carried out to explore the link between inflammatory markers and the kynurenine to tryptophan ratio (KTR) in shaping mortality risk.

RESULTS

Using multivariable stepwise Cox regression analysis, interleukin (IL)-4, IL-6, IL-8, IL-13, RANTES, and interferon gamma-induced protein-10 (IP-10) were independently associated with death. An inflammation score (I score) comprising these 6 molecules is strongly associated with death in both the discovery and the validation cohorts HR (95% CI) 2.13 (1.91-2.37) and 2.20 (1.79-2.72), respectively. The I score improved discrimination and reclassification measures (all P < .01) of 2 mortality prediction models based on clinical variables. The causal mediation analysis showed that 28% of the KTR effect on mortality was mediated by IP-10. Studies in cultured endothelial cells showed that 5-methoxy-tryptophan, an anti-inflammatory metabolite derived from tryptophan, reduces the expression of IP-10, thus providing a functional basis for the observed causal mediation.

CONCLUSION

Adding the I score to clinical prediction models may help identify individuals who are at greater risk of death. Deeply addressing the intertwined relationship between low-grade inflammation and imbalanced tryptophan metabolism in shaping mortality risk may help discover new therapies targeting patients characterized by these abnormalities.

摘要

背景

炎症在塑造糖尿病患者死亡风险中的作用仍不明确。

目的

研究炎症是否与2型糖尿病患者的死亡风险相关并有助于预测该风险。探讨炎症与色氨酸代谢在死亡风险上的相互关联。

方法

有2个前瞻性队列:汇总的加尔加诺死亡率研究(1731人;872例全因死亡)作为发现样本,以及福贾死亡率研究(490人;256例死亡)作为验证样本。测量了27种炎症标志物。进行了因果中介分析和体外研究,以探讨炎症标志物与犬尿氨酸与色氨酸比值(KTR)在塑造死亡风险中的联系。

结果

使用多变量逐步Cox回归分析,白细胞介素(IL)-4、IL-6、IL-8、IL-13、调节激活正常T细胞表达和分泌因子(RANTES)以及γ干扰素诱导蛋白10(IP-10)与死亡独立相关。由这6种分子组成的炎症评分(I评分)在发现队列和验证队列中均与死亡密切相关,风险比(HR)(95%置信区间)分别为2.13(1.91 - 2.37)和2.20(1.79 - 2.72)。I评分改善了基于临床变量的2种死亡率预测模型的辨别和重新分类指标(所有P < .01)。因果中介分析表明,KTR对死亡率的影响有28%由IP-10介导。在培养的内皮细胞中的研究表明,色氨酸衍生的抗炎代谢物5-甲氧基色氨酸可降低IP-10的表达,从而为观察到的因果中介提供了功能基础。

结论

将I评分添加到临床预测模型中可能有助于识别死亡风险更高的个体。深入探讨低度炎症与色氨酸代谢失衡在塑造死亡风险中的相互关系,可能有助于发现针对具有这些异常特征患者的新疗法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/868a6b91a273/dgae593f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/725bb9f4f87e/dgae593f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/b0c69e0e543c/dgae593f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/868a6b91a273/dgae593f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/725bb9f4f87e/dgae593f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/b0c69e0e543c/dgae593f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3dd/12012783/868a6b91a273/dgae593f3.jpg

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