Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study. Issue 11 (November 2017)

• Record Type: Journal Article
• Authors: Herazo-Maya, Jose D; Sun, Jiehuan; Molyneaux, Philip L; Li, Qin; Villalba, Julian A; Tzouvelekis, Argyrios; Lynn, Heather; Juan-Guardela, Brenda M; Risquez, Cristobal; Osorio, Juan C; Yan, Xiting; Michel, George; Aurelien, Nachelle; Lindell, Kathleen O; Klesen, Melinda J; Moffatt, Miriam F; Cookson, William O; Zhang, Yingze; Garcia, Joe G N; Noth, Imre; Prasse, Antje; Bar-Joseph, Ziv; Gibson, Kevin F; Zhao, Hongyu; Herzog, Erica L; Rosas, Ivan O; Maher, Toby M; Kaminski, Naftali
• Is Part Of: Lancet. Volume 5:Issue 11(2017)
• Page Start: 857
• Page End: 868
• Publication Date: 2017-11
• Subjects: Respiratory organs -- Diseases -- Periodicals; 616.2005
• DOI: 10.1016/S2213-2600(17)30349-1
• Languages: English
• ISSNs: 2213-2600

Abstract

Summary: Background: The clinical course of idiopathic pulmonary fibrosis (IPF) is unpredictable. Clinical prediction tools are not accurate enough to predict disease outcomes. Methods: We enrolled patients with IPF diagnosis in a six-cohort study at Yale University (New Haven, CT, USA), Imperial College London (London, UK), University of Chicago (Chicago, IL, USA), University of Pittsburgh (Pittsburgh, PA, USA), University of Freiburg (Freiburg im Breisgau, Germany), and Brigham and Women's Hospital–Harvard Medical School (Boston, MA, USA). Peripheral blood mononuclear cells or whole blood were collected at baseline from 425 participants and from 98 patients (23%) during 4–6 years' follow-up. A 52-gene signature was measured by the nCounter analysis system in four cohorts and extracted from microarray data (GeneChip) in the other two. We used the Scoring Algorithm for Molecular Subphenotypes (SAMS) to classify patients into low-risk or high-risk groups based on the 52-gene signature. We studied mortality with a competing risk model and transplant-free survival with a Cox proportional hazards model. We analysed timecourse data and response to antifibrotic drugs with linear mixed effect models. Findings: The application of SAMS to the 52-gene signature identified two groups of patients with IPF (low-risk and high-risk), with significant differences in mortality or transplant-free survival in each of the six cohorts (hazard ratio [HR] range 2·03–4·37). Pooled data showed similar results for mortality (HR 2·18, 95% CI 1·53–3·09; p<0·0001) or transplant-free survival (2·04, 1·52–2·74; p<0·0001). Adding 52-gene risk profiles to the Gender, Age, and Physiology index significantly improved its mortality predictive accuracy. Temporal changes in SAMS scores were associated with changes in forced vital capacity (FVC) in two cohorts. Untreated patients did not shift their risk profile over time. A simultaneous increase in up score and decrease in down score was predictive of decreased transplant-free survival (3·18, 1·16–8·76; p=0·025) in the Pittsburgh cohort. A simultaneous decrease in up score and increase in down score after initiation of antifibrotic drugs was associated with a significant (p=0·0050) improvement in FVC in the Yale cohort. Interpretation: The peripheral blood 52-gene expression signature is predictive of outcome in patients with IPF. The potential value of the 52-gene signature in predicting response to therapy should be determined in prospective studies. Funding: The Pulmonary Fibrosis Foundation, the Harold Amos Medical Faculty Development Program of the Robert Wood Johnson Foundation, and the National Heart, Lung, and Blood Institute of the US National Institutes of Health.