Using multiomic integration to improve blood biomarkers of major depressive disorder: a case-control studyResearch in context
Amazigh Mokhtari,
El Chérif Ibrahim,
Arnaud Gloaguen,
Claire-Cécile Barrot,
David Cohen,
Margot Derouin,
Hortense Vachon,
Guillaume Charbonnier,
Béatrice Loriod,
Charles Decraene,
Ipek Yalcin,
Cynthia Marie-Claire,
Bruno Etain,
Raoul Belzeaux,
Andrée Delahaye-Duriez,
Pierre-Eric Lutz
Affiliations
Amazigh Mokhtari
Université Paris Cité, Inserm, NeuroDiderot, UMR-1141, 75019, Paris, France
El Chérif Ibrahim
Aix-Marseille Univ, CNRS, INT, Inst Neurosci Timone, 13005, Marseille, France
Arnaud Gloaguen
Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, 91000, Evry, France
Claire-Cécile Barrot
Université Paris Cité, Inserm, NeuroDiderot, UMR-1141, 75019, Paris, France
David Cohen
Université Paris Cité, Inserm, NeuroDiderot, UMR-1141, 75019, Paris, France
Margot Derouin
Université Paris Cité, Inserm, NeuroDiderot, UMR-1141, 75019, Paris, France
Hortense Vachon
Aix-Marseille Université, INSERM, TAGC, 13009, Marseille, France
Guillaume Charbonnier
Aix-Marseille Université, INSERM, TAGC, 13009, Marseille, France
Béatrice Loriod
Aix-Marseille Université, INSERM, TAGC, 13009, Marseille, France
Charles Decraene
Centre National de la Recherche Scientifique, Université de Strasbourg, Institut des Neurosciences Cellulaires et Intégratives UPR 3212, F-67000, Strasbourg, France
Ipek Yalcin
Centre National de la Recherche Scientifique, Université de Strasbourg, Institut des Neurosciences Cellulaires et Intégratives UPR 3212, F-67000, Strasbourg, France; Department of Psychiatry and Neuroscience, Université Laval, Québec, QC, G1V 0A6, Canada
Cynthia Marie-Claire
Université Paris Cité, INSERM UMR-S 1144, Optimisation thérapeutique en neuropsychopharmacologie, OTeN, F-75006, Paris, France
Bruno Etain
Université Paris Cité, INSERM UMR-S 1144, Optimisation thérapeutique en neuropsychopharmacologie, OTeN, F-75006, Paris, France; Assistance Publique des Hôpitaux de Paris, GHU Lariboisière-Saint Louis-Fernand Widal, DMU Neurosciences, Département de psychiatrie et de Médecine Addictologique, F-75010, Paris, France
Raoul Belzeaux
Aix-Marseille Univ, CNRS, INT, Inst Neurosci Timone, 13005, Marseille, France; Département de psychiatrie, CHU de Montpellier, Montpellier, France
Andrée Delahaye-Duriez
Université Paris Cité, Inserm, NeuroDiderot, UMR-1141, 75019, Paris, France; Unité fonctionnelle de médecine génomique et génétique clinique, Hôpital Jean Verdier, Assistance Publique des Hôpitaux de Paris, F-93140, Bondy, France; Université Sorbonne Paris Nord, F-93000, Bobigny, France; Corresponding author. Neurodiderot, Inserm U1141, Hôpital Robert Debré, 48 boulevard Sérurier, 75019, Paris, France.
Pierre-Eric Lutz
Centre National de la Recherche Scientifique, Université de Strasbourg, Institut des Neurosciences Cellulaires et Intégratives UPR 3212, F-67000, Strasbourg, France; Douglas Mental Health University Institute, McGill University, QC, H4H 1R3, Montréal, Canada; Corresponding author. INCI UPR 3212, 8 allée du général Rouvillois, 67000, Strasbourg, France.
Summary: Background: Major depressive disorder (MDD) is a leading cause of disability, with a twofold increase in prevalence in women compared to men. Over the last few years, identifying molecular biomarkers of MDD has proven challenging, reflecting interactions among multiple environmental and genetic factors. Recently, epigenetic processes have been proposed as mediators of such interactions, with the potential for biomarker development. Methods: We characterised gene expression and two mechanisms of epigenomic regulation, DNA methylation (DNAm) and microRNAs (miRNAs), in blood samples from a cohort of individuals with MDD and healthy controls (n = 169). Case-control comparisons were conducted for each omic layer. We also defined gene coexpression networks, followed by step-by-step annotations across omic layers. Third, we implemented an advanced multiomic integration strategy, with covariate correction and feature selection embedded in a cross-validation procedure. Performance of MDD prediction was systematically compared across 6 methods for dimensionality reduction, and for every combination of 1, 2 or 3 types of molecular data. Feature stability was further assessed by bootstrapping. Findings: Results showed that molecular and coexpression changes associated with MDD were highly sex-specific and that the performance of MDD prediction was greater when the female and male cohorts were analysed separately, rather than combined. Importantly, they also demonstrated that performance progressively increased with the number of molecular datasets considered. Interpretation: Informational gain from multiomic integration had already been documented in other medical fields. Our results pave the way toward similar advances in molecular psychiatry, and have practical implications for developing clinically useful MDD biomarkers. Funding: This work was supported by the Centre National de la Recherche Scientifique (contract UPR3212), the University of Strasbourg, the Université Sorbonne Paris Nord, the Université Paris Cité, the Fondation de France (FdF N° Engt:00081244 and 00148126; ECI, IY, RB, PEL), the French National Research Agency (ANR-18-CE37-0002, BE, CMC, ADD, PEL, ECI; ANR-18-CE17-0009, ADD; ANR-19-CE37-0010, PEL; ANR-21-RHUS-009, ADD, BE, CMC, CCB; ANR-22-PESN-0013, ADD), the Fondation pour la Recherche sur le Cerveau (FRC 2019, PEL), Fondation de France (2018, BE, CMC, ADD) and American Foundation for Suicide Prevention (AFSP YIG-1-102-19; PEL).