Christopher J Rhodes1, Pablo Otero-Núñez1, John Wharton1, Emilia M Swietlik2, Sokratis Kariotis3,4, Lars Harbaum1, Mark J Dunning5, Jason M Elinoff6, Niamh Errington3,4, A A Roger Thompson4, James Iremonger4, J Gerry Coghlan7, Paul A Corris8, Luke S Howard1, David G Kiely4, Colin Church9, Joanna Pepke-Zaba10, Mark Toshner2,10, Stephen J Wort1, Ankit A Desai11, Marc Humbert12,13,14, William C Nichols15, Laura Southgate16, David-Alexandre Trégouët17, Richard C Trembath18, Inga Prokopenko19, Stefan Gräf2,20, Nicholas W Morrell2, Dennis Wang3,5, Allan Lawrie4, Martin R Wilkins1. 1. National Heart and Lung Institute, Imperial College London, London, United Kingdom. 2. Department of Medicine, University of Cambridge, Cambridge, United Kingdom. 3. Sheffield Institute for Translational Neuroscience. 4. Department of Infection, Immunity & Cardiovascular Disease, and. 5. Sheffield Bioinformatics Core, The University of Sheffield, Sheffield, United Kingdom. 6. Critical Care Medicine Department, NIH Clinical Center, Bethesda, Maryland. 7. University College London, London, United Kingdom. 8. Newcastle University, Newcastle upon Tyne, United Kingdom. 9. University of Glasgow, Glasgow, United Kingdom. 10. Royal Papworth Hospital, Cambridge, United Kingdom. 11. Indiana University, Indianapolis, Indiana. 12. Université Paris-Sud, Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France. 13. Service de Pneumologie, Hôpital Bicêtre, Assistance Publique - Hôpitaux de Paris, Le Kremlin-Bicêtre, France. 14. INSERM UMR_S 999, Hôpital Marie Lannelongue, Le Plessis Robinson, France. 15. Division of Human Genetics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio. 16. Molecular and Clinical Sciences Research Institute, St. George's University of London, London, United Kingdom. 17. INSERM UMR_S 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France. 18. Division of Genetics and Molecular Medicine, King's College London, London, United Kingdom. 19. Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom; and. 20. NIHR BioResource for Translational Research, Cambridge, United Kingdom.
Abstract
Rationale: Idiopathic and heritable pulmonary arterial hypertension (PAH) are rare but comprise a genetically heterogeneous patient group. RNA sequencing linked to the underlying genetic architecture can be used to better understand the underlying pathology by identifying key signaling pathways and stratify patients more robustly according to clinical risk. Objectives: To use a three-stage design of RNA discovery, RNA validation and model construction, and model validation to define a set of PAH-associated RNAs and a single summarizing RNA model score. To define genes most likely to be involved in disease development, we performed Mendelian randomization (MR) analysis. Methods: RNA sequencing was performed on whole-blood samples from 359 patients with idiopathic, heritable, and drug-induced PAH and 72 age- and sex-matched healthy volunteers. The score was evaluated against disease severity markers including survival analysis using all-cause mortality from diagnosis. MR used known expression quantitative trait loci and summary statistics from a PAH genome-wide association study.Measurements and Main Results: We identified 507 genes with differential RNA expression in patients with PAH compared with control subjects. A model of 25 RNAs distinguished PAH with 87% accuracy (area under the curve 95% confidence interval: 0.791-0.945) in model validation. The RNA model score was associated with disease severity and long-term survival (P = 4.66 × 10-6) in PAH. MR detected an association between SMAD5 levels and PAH disease susceptibility (odds ratio, 0.317; 95% confidence interval, 0.129-0.776; P = 0.012).Conclusions: A whole-blood RNA signature of PAH, which includes RNAs relevant to disease pathogenesis, associates with disease severity and identifies patients with poor clinical outcomes. Genetic variants associated with lower SMAD5 expression may increase susceptibility to PAH.
Rationale: Idiopathic and heritable pulmonary arterial hypertension (PAH) are rare but comprise a genetically heterogeneous patient group. RNA sequencing linked to the underlying genetic architecture can be used to better understand the underlying pathology by identifying key signaling pathways and stratify patients more robustly according to clinical risk. Objectives: To use a three-stage design of RNA discovery, RNA validation and model construction, and model validation to define a set of PAH-associated RNAs and a single summarizing RNA model score. To define genes most likely to be involved in disease development, we performed Mendelian randomization (MR) analysis. Methods: RNA sequencing was performed on whole-blood samples from 359 patients with idiopathic, heritable, and drug-induced PAH and 72 age- and sex-matched healthy volunteers. The score was evaluated against disease severity markers including survival analysis using all-cause mortality from diagnosis. MR used known expression quantitative trait loci and summary statistics from a PAH genome-wide association study.Measurements and Main Results: We identified 507 genes with differential RNA expression in patients with PAH compared with control subjects. A model of 25 RNAs distinguished PAH with 87% accuracy (area under the curve 95% confidence interval: 0.791-0.945) in model validation. The RNA model score was associated with disease severity and long-term survival (P = 4.66 × 10-6) in PAH. MR detected an association between SMAD5 levels and PAH disease susceptibility (odds ratio, 0.317; 95% confidence interval, 0.129-0.776; P = 0.012).Conclusions: A whole-blood RNA signature of PAH, which includes RNAs relevant to disease pathogenesis, associates with disease severity and identifies patients with poor clinical outcomes. Genetic variants associated with lower SMAD5 expression may increase susceptibility to PAH.
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