Cytokine responses in nonlesional psoriatic skin as clinical predictor to anti-TNF agents,Journal of Allergy and Clinical Immunology

当前位置： X-MOL 学术 › J. Allergy Clin. Immunol. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Cytokine responses in nonlesional psoriatic skin as clinical predictor to anti-TNF agents
Journal of Allergy and Clinical Immunology ( IF 14.2 ) Pub Date : 2021-07-31 , DOI: 10.1016/j.jaci.2021.07.024
Lam C Tsoi ₁ , Matthew T Patrick ₂ , Shao Shuai ₃ , Mrinal K Sarkar ₂ , Sunyi Chi ₄ , Bethany Ruffino ₂ , Allison C Billi ₂ , Xianying Xing ₂ , Ranjitha Uppala ₂ , Cheng Zang ₂ , Joseph Fullmer ₂ , Zhi He ₅ , Emanual Maverakis ₆ , Nehal N Mehta ₇ , Bethany E Perez White ₈ , Spiro Getsios ₈ , Yolanda Helfrich ₂ , John J Voorhees ₂ , J Michelle Kahlenberg ₉ , Stephan Weidinger ₁₀ , Johann E Gudjonsson ₂

Affiliation

Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Mich; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Mich.
Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich.
Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Department of Dermatology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shannxi, China.
Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Mich.
Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Mich.
Department of Dermatology, School of Medicine, UC-Davis Medical Center, Sacramento, Calif.
Section of Inflammation and Cardiometabolic Diseases, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Md.
Department of Dermatology, Northwestern University, Chicago, Ill.
Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich.
Department of Dermatology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany.

Background

A major issue with the current management of psoriasis is our inability to predict treatment response.

Objective

Our aim was to evaluate the ability to use baseline molecular expression profiling to assess treatment outcome for patients with psoriasis.

Methods

We conducted a longitudinal study of 46 patients with chronic plaque psoriasis treated with anti-TNF agent etanercept, and molecular profiles were assessed in more than 200 RNA-seq samples.

Results

We demonstrated correlation between clinical response and molecular changes during the course of the treatment, particularly for genes responding to IL-17A/TNF in keratinocytes. Intriguingly, baseline gene expressions in nonlesional, but not lesional, skin were the best marker of treatment response at week 12. We identified USP18, a known regulator of IFN responses, as positively correlated with Psoriasis Area and Severity Index (PASI) improvement (P = 9.8 × 10⁻⁴) and demonstrate its role in regulating IFN/TNF responses in keratinocytes. Consistently, cytokine gene signatures enriched in baseline nonlesional skin expression profiles had strong correlations with PASI improvement. Using this information, we developed a statistical model for predicting PASI75 (ie, 75% of PASI improvement) at week 12, achieving area under the receiver-operating characteristic curve value of 0.75 and up to 80% accurate PASI75 prediction among the top predicted responders.

Conclusions

Our results illustrate feasibility of assessing drug response in psoriasis using nonlesional skin and implicate involvement of IFN regulators in anti-TNF responses.

中文翻译：

非损伤性银屑病皮肤中的细胞因子反应作为抗 TNF 药物的临床预测因子

背景

当前银屑病管理的一个主要问题是我们无法预测治疗反应。

客观的

我们的目的是评估使用基线分子表达谱来评估银屑病患者治疗结果的能力。

方法

我们对 46 名接受抗 TNF 药物依那西普治疗的慢性斑块状银屑病患者进行了纵向研究，并在 200 多个 RNA-seq 样本中评估了分子特征。

结果

我们证明了治疗过程中临床反应和分子变化之间的相关性，特别是对于角质形成细胞中对 IL-17A/TNF 有反应的基因。有趣的是，非损伤而非损伤皮肤的基线基因表达是第 12 周治疗反应的最佳标志。我们发现USP18是一种已知的 IFN 反应调节因子，与银屑病面积和严重程度指数 (PASI) 改善呈正相关 ( P = 9.8 × 10 ^-4) 并证明其在调节角质形成细胞中的 IFN/TNF 反应中的作用。一致地，在基线非损伤皮肤表达谱中富集的细胞因子基因特征与 PASI 改善有很强的相关性。利用这些信息，我们开发了一个统计模型，用于预测第 12 周的 PASI75（即 75% 的 PASI 改善），实现了 0.75 的接受者操作特征曲线下面积值和最高预测响应者中高达 80% 的 PASI75 预测准确度.