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Dissecting autism and schizophrenia through neuroimaging genomics

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  • معلومة اضافية
    • Contributors:
      Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)); Institut Pasteur Paris -Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP); Université de Montréal (UdeM); Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM); National Institute of Mental Health (NIMH); Centre de recherche de l'Institut universitaire de gériatrie de Montreal (CRIUGM); Douglas Mental Health University Institute; McGill University = Université McGill Montréal, Canada; Laboratory of Neuro Imaging Los Angeles (LONI); University of California Los Angeles (UCLA); University of California-University of California; This research was supported by the Brain Canada Multi investigator research initiative (MIRI), funds from the Institute of Data Valorization (IVADO). S.J. is supported by the Canadian Institute of Health Research CIHR_400528 and the The Institute of Data Valorization (IVADO) through the Canada First Research Excellence Fund, Healthy Brains for Healthy Lives through the Canada First Research Excellence Fund. P.B. is a fellow (‘Chercheur boursier Junior 2’) of the ‘Fonds de recherche du Québec—Santé’.
    • بيانات النشر:
      HAL CCSD
      Oxford University Press (OUP)
    • الموضوع:
      2021
    • Collection:
      Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
    • نبذة مختصرة :
      International audience ; Neuroimaging genomic studies of autism spectrum disorder and schizophrenia have mainly adopted a ‘top-down’ approach, beginning with the behavioural diagnosis, and moving down to intermediate brain phenotypes and underlying genetic factors. Advances in imaging and genomics have been successfully applied to increasingly large case-control studies. As opposed to diagnostic-first approaches, the bottom-up strategy begins at the level of molecular factors enabling the study of mechanisms related to biological risk, irrespective of diagnoses or clinical manifestations. The latter strategy has emerged from questions raised by top-down studies: why are mutations and brain phenotypes over-represented in individuals with a psychiatric diagnosis? Are they related to core symptoms of the disease or to comorbidities? Why are mutations and brain phenotypes associated with several psychiatric diagnoses? Do they impact a single dimension contributing to all diagnoses? In this review, we aimed at summarizing imaging genomic findings in autism and schizophrenia as well as neuropsychiatric variants associated with these conditions. Top-down studies of autism and schizophrenia identified patterns of neuroimaging alterations with small effect-sizes and an extreme polygenic architecture. Genomic variants and neuroimaging patterns are shared across diagnostic categories suggesting pleiotropic mechanisms at the molecular and brain network levels. Although the field is gaining traction; characterizing increasingly reproducible results, it is unlikely that top-down approaches alone will be able to disentangle mechanisms involved in autism or schizophrenia. In stark contrast with top-down approaches, bottom-up studies showed that the effect-sizes of high-risk neuropsychiatric mutations are equally large for neuroimaging and behavioural traits. Low specificity has been perplexing with studies showing that broad classes of genomic variants affect a similar range of behavioural and cognitive dimensions, which may be ...
    • Relation:
      info:eu-repo/semantics/altIdentifier/pmid/33704401; pasteur-03503367; https://hal-pasteur.archives-ouvertes.fr/pasteur-03503367; https://hal-pasteur.archives-ouvertes.fr/pasteur-03503367/document; https://hal-pasteur.archives-ouvertes.fr/pasteur-03503367/file/awab096.pdf; PUBMED: 33704401; PUBMEDCENTRAL: PMC8370419
    • الرقم المعرف:
      10.1093/brain/awab096
    • Rights:
      http://creativecommons.org/licenses/by-nc/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.5A078758