Titre : | Longitudinal MicroRNA Signature of Conversion to Psychosis |
Auteurs : | Anton Iftimovici, Aut. ; Qin He, Aut. ; Chuan Jiao, Aut. ; Edouard Duchesnay, Aut. ; Marie-Odile Krebs, Aut. ; Oussama Kebir, Aut. ; Boris Chaumette, Aut. |
Dans : | SCHIZOPHRENIA BULLETIN (In Press, 2023) |
Langues: | Anglais |
Mots-clés : |
SANTEPSY EPIGENETIQUE ; ETUDE LONGITUDINALE ; FACTEUR DE RISQUE ; MARQUEUR BIOLOGIQUE ; PHYSIOPATHOLOGIE ; PSYCHOSE |
Résumé : | Background and Hypothesis : The emergence of psychosis in ultra-high-risk subjects (UHR) is influenced by gene-environment interactions that rely on epigenetic mechanisms such as microRNAs. However, whether they can be relevant pathophysiological biomarkers of psychosis’ onset remains unknown. Study Design : We present a longitudinal study of microRNA expression, measured in plasma by high-throughput sequencing at baseline and follow-up, in a prospective cohort of 81 UHR, 35 of whom developed psychosis at follow-up (converters). We combined supervised machine learning and differential graph analysis to assess the relative weighted contribution of each microRNA variation to the difference in outcome and identify outcome-specific networks. We then applied univariate models to the resulting microRNA variations common to both strategies, to interpret them as a function of demographic and clinical covariates. Study Results : We identified 207 microRNA variations that significantly contributed to the classification. The differential network analysis found 276 network-specific correlations of microRNA variations. The combination of both strategies identified 25 microRNAs, whose gene targets were overrepresented in cognition and schizophrenia genome-wide association studies findings. Interpretable univariate models further supported the relevance of miR-150-5p and miR-3191-5p variations in psychosis onset, independent of age, sex, cannabis use, and medication. Conclusions : In this first longitudinal study of microRNA variation during conversion to psychosis, we combined 2 methodologically independent data-driven strategies to identify a dynamic epigenetic signature of the emergence of psychosis that is pathophysiologically relevant. [résumé d'auteur] |
Notes de contenus : | Fig. ; Tabl. ; 58 réf. bibliogr. |
En ligne : | https://go.openathens.net/redirector/ghu-paris.fr?url=https://academic.oup.com/schizophreniabulletin/advance-article/doi/10.1093/schbul/sbad080/7248532 |
Service de l'auteur du GHU : |
Pôle PEPIT |