Molecular and Clinical Data Integration Identifies an Association Between Decreased Colectomy Rates and Atorvastatin Exposure in Ulcerative Colitis Patients: A Retrospective Cohort Study

Background: Ulcerative colitis (UC) is a chronic inflammatory disorder of the gastrointestinal tract with limited effective therapeutic options for long-term treatment and disease maintenance. We hypothesized that multi-cohort analysis of independent cohorts representing real-world heterogeneity of patients with UC would identify a robust transcriptomic signature to improve identification of FDA-approved drugs that can be repurposed to treat patients with UC.  Methods: We performed a multi-cohort analysis of transcriptome profiles of 272 colon biopsies across 11 publicly available datasets to identify a robust UC gene signature. We compared the gene signature with in vitro transcriptomic profiles induced by 781 FDA-approved small-molecule drugs to identify potential drug targets. We used a retrospective cohort study design modeled after a target trial to evaluate the protective effect of atorvastatin on colectomy risk in patients with UC from the Stanford Research Repository (STARR) database and Optum Clinformatics DataMart.  Findings: The transcriptomic profile of atorvastatin treatment had the highest inverse-correlation with the UC gene signature among any non-oncolytic therapy. In both the STARR(n=827) and Optum(n=7821) cohorts, atorvastatin use was significantly associated with a decreased risk of colectomy, a marker of treatment-refractory disease in patients with UC, compared to patients prescribed a comparator drug (STARR: HR=0.47, p=0.03; Optum: HR=0.66, p=0.03), irrespective of age and length of atorvastatin treatment.  Interpretations: These findings suggest that atorvastatin might 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 similarly heterogeneous clinical data at a large scale to repurpose existing FDA-approved drugs for a wide range of human diseases.  Funding Statement: LB is funded by the Stanford Bio-X Graduate Fellowship. MKDS is funded in part by the National Heart, Lung, and Blood Institute (F30:HL149252) and The Stanford University Medical Scientist Training Program (T32GM007365). PK is funded in part by the Bill and Melinda Gates Foundation (OPP1113682); the National Institute of Allergy and Infectious Diseases (NIAID) grants 1U19AI109662, U19AI057229, and 5R01AI125197; Department of Defense contracts W81XWH-18-1-0253 and W81XWH1910235; and the Ralph & Marian Falk Medical Research Trust, outside of this work. Declaration of Interests: Authors declare no conflicts of interest. Ethics Approval Statement: Access was permitted through a previously approved IRB.