Abstract

Objective

Ulcerative colitis (UC) is a chronic inflammatory disorder with limited effective therapeutic options for long-term treatment and disease maintenance. We hypothesized that a multi-cohort analysis of independent cohorts representing real-world heterogeneity of UC would identify a robust transcriptomic signature to improve identification of FDA-approved drugs that can be repurposed to treat patients with UC.

Materials and Methods

We performed a multi-cohort analysis of 272 colon biopsy transcriptome samples across 11 publicly available datasets to identify a robust UC disease gene signature. We compared the gene signature to in vitro transcriptomic profiles induced by 781 FDA-approved drugs to identify potential drug targets. We used a retrospective cohort study design modeled after a target trial to evaluate the protective effect of predicted drugs on colectomy risk in patients with UC from the Stanford Research Repository (STARR) database and Optum Clinformatics DataMart.

Results

Atorvastatin treatment had the highest inverse-correlation with the UC gene signature among non-oncolytic FDA-approved therapies. In both STARR (n = 827) and Optum (n = 7821), atorvastatin intake was significantly associated with a decreased risk of colectomy, a marker of treatment-refractory disease, compared to patients prescribed a comparator drug (STARR: HR = 0.47, P = .03; Optum: HR = 0.66, P = .03), irrespective of age and length of atorvastatin treatment.

Discussion & Conclusion

These findings suggest that atorvastatin may serve as a novel therapeutic option for ameliorating disease in patients with UC. Importantly, we provide a systematic framework for integrating publicly available heterogeneous molecular data with clinical data at a large scale to repurpose existing FDA-approved drugs for a wide range of human diseases.

中文翻译：

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阿托伐他汀治疗溃疡性结肠炎的计算药物重新定位

摘要

客观的

溃疡性结肠炎 (UC) 是一种慢性炎症性疾病，长期治疗和疾病维持的有效治疗选择有限。我们假设，对代表真实世界 UC 异质性的独立队列的多队列分析将确定一个强大的转录组特征，以改进 FDA 批准的药物的识别，这些药物可以重新用于治疗 UC 患者。

材料和方法

我们对 11 个公开可用的数据集的 272 个结肠活检转录组样本进行了多队列分析，以确定稳健的 UC 疾病基因特征。我们将基因特征与781 种 FDA 批准的药物诱导的体外转录组谱进行了比较，以确定潜在的药物靶点。我们使用了一项以目标试验为模型的回顾性队列研究设计，以评估来自斯坦福研究资料库 (STARR) 数据库和 Optum Clinformatics DataMart 的预测药物对 UC 患者结肠切除术风险的保护作用。

结果

在 FDA 批准的非溶瘤疗法中，阿托伐他汀治疗与 UC 基因特征的负相关性最高。在 STARR (n = 827) 和 Optum (n = 7821) 中，与开具对照药物的患者相比，阿托伐他汀摄入与结肠切除术风险降低显着相关，结肠切除术是治疗难治性疾病的标志物（STARR：HR = 0.47，P  = .03；Optum：HR = 0.66，P  = .03），与年龄和阿托伐他汀治疗时间无关。

讨论与结论

这些发现表明，阿托伐他汀可作为一种新的治疗选择，用于改善 UC 患者的疾病。重要的是，我们提供了一个系统框架，用于将公开可用的异构分子数据与大规模临床数据相结合，以重新利用 FDA 批准的现有药物来治疗广泛的人类疾病。