Improved cardiovascular risk prediction in patients with end-stage renal disease on hemodialysis using machine learning modeling and circulating microribonucleic acids

Autor: Faiez Zannad, Roland E. Schmieder, Ziad A. Massy, Bengt Fellström, Kevin Duarte, David de Gonzalo-Calvo, Nicolas Girerd, Alan G. Jardine, Pablo Martínez-Camblor, Patrick Rossignol, Christian Bär, Thomas Thum, Hallvard Holdaas
Přispěvatelé: Institute of Molecular and Translational Therapeutic Strategies (IMTTS), Hannover Medical School [Hannover] (MHH), Arnau de Vilanova University Hospital [Lleida, Spain], Institute of Health Carlos III, Geisel School of Medicine at Dartmouth, Centre d'investigation clinique plurithématique Pierre Drouin [Nancy] (CIC-P), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Défaillance Cardiovasculaire Aiguë et Chronique (DCAC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Cardiovascular and Renal Clinical Trialists [Vandoeuvre-les-Nancy] (INI-CRCT), Institut Lorrain du Coeur et des Vaisseaux Louis Mathieu [Nancy], French-Clinical Research Infrastructure Network - F-CRIN [Paris] (Cardiovascular & Renal Clinical Trialists - CRCT ), Uppsala University Hospital, Friedrich–Alexander University Erlangen–Nürnberg (FAU), University of Glasgow, Service Néphrologie/Dialyse [AP-HP Ambroise-Paré], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Ambroise Paré [AP-HP], Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Oslo University Hospital [Oslo], TT received funding the Federal Ministry of Education and Research (BMBF, Germany, research grant ERA-CVD JTC2016 EXPERT, 01KL1711).CIBERES (CB07/06/2008 to DdGC) is a project from Carlos III Health Institute. PR, FZ, NG and KD are supported by a grant by the RHU Fight-HF, apublic grant overseen by the French National Research Agency (ANR) as part of the second 'Investissements d’Avenir' program (reference:ANR-15-RHUS-0004), by the French PIA project 'Lorraine Université d’Excellence' (reference: ANR-15-IDEX-04-LUE), the ANR FOCUS-MR (reference: ANR-15-CE14-0032-01), ERA-CVD EXPERT (reference: ANR-16-ECVD-0002-02), Contrat de Plan Etat Lorraine IT2MP and FEDER Lorraine., IMPACT GEENAGE, ANR-16-ECVD-0002,EXPERT,Exploring new pathways in age-related heart diseases(2016), ANR-15-CE14-0032,MR-focus,Régulation, Diagnostique et Thérapeutique ciblée du récepteur minéralocorticoïde dans le remodelage cardiaque(2015), ANR-15-RHUS-0004,FIGHT-HF,Combattre l'insuffisance cardiaque(2015), ANR-15-IDEX-0004,LUE,Isite LUE(2015), DE CARVALHO, Philippe, Exploring new pathways in age-related heart diseases - - EXPERT2016 - ANR-16-ECVD-0002 - ERA-CVD - VALID, Régulation, Diagnostique et Thérapeutique ciblée du récepteur minéralocorticoïde dans le remodelage cardiaque - - MR-focus2015 - ANR-15-CE14-0032 - AAPG2015 - VALID, Combattre l'insuffisance cardiaque - - FIGHT-HF2015 - ANR-15-RHUS-0004 - RHUS - VALID, ISITE - Isite LUE - - LUE2015 - ANR-15-IDEX-0004 - IDEX - VALID
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Male
0301 basic medicine
Oncology
[SDV]Life Sciences [q-bio]
medicine.medical_treatment
Medicine (miscellaneous)
Disease
030204 cardiovascular system & hematology
[SDV.MHEP.UN]Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology
0302 clinical medicine
AURORA trial
Urologi och njurmedicin
Medicine
Pharmacology
Toxicology and Pharmaceutics (miscellaneous)
Aged
80 and over
[SDV.MHEP] Life Sciences [q-bio]/Human health and pathology
microRNA
Reverse Transcriptase Polymerase Chain Reaction
Confounding
Middle Aged
Kidney disease
[SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
3. Good health
[SDV] Life Sciences [q-bio]
Cardiovascular Diseases
Hemodialysis
Regression Analysis
Biomarker (medicine)
Female
Research Paper
Cart
medicine.medical_specialty
End stage renal disease
03 medical and health sciences
[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
Renal Dialysis
Internal medicine
Machine learning
Humans
Urology and Nephrology
Aged
Sequence Analysis
RNA
business.industry
Biomarker
medicine.disease
Cardiovascular risk
[SDV.MHEP.UN] Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology
MicroRNAs
030104 developmental biology
Case-Control Studies
Kidney Failure
Chronic
business
Biomarkers
[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Zdroj: Theranostics
Theranostics, Ivyspring International Publisher, 2020, 10 (19), pp.8665-8676. ⟨10.7150/thno.46123⟩
ISSN: 1838-7640
DOI: 10.7150/thno.46123⟩
Popis: International audience; Rationale: To test whether novel biomarkers, such as microribonucleic acids (miRNAs), and nonstandard predictive models, such as decision tree learning, provide useful information for medical decision-making in patients on hemodialysis (HD). Methods: Samples from patients with end-stage renal disease receiving HD included in the AURORA trial were investigated (n=810). The study included two independent phases: phase I (matched cases and controls, n=410) and phase II (unmatched cases and controls, n=400). The composite endpoint was cardiovascular death, nonfatal myocardial infarction or nonfatal stroke. miRNA quantification was performed using miRNA sequencing and RT-qPCR. The CART algorithm was used to construct regression tree models. A bagging-based procedure was used for validation. Results: In phase I, miRNA sequencing in a subset of samples (n=20) revealed miR-632 as a candidate (fold change=2.9). miR-632 was associated with the endpoint, even after adjusting for confounding factors (HR from 1.43 to 1.53). These findings were not reproduced in phase II. Regression tree models identified eight patient subgroups with specific risk patterns. miR-186-5p and miR-632 entered the tree by redefining two risk groups: patients older than 64 years and with hsCRP
Databáze: OpenAIRE
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