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Modeling psychiatric disorders: From genomic findings to cellular phenotypes

  • A. Falk
  • , V. M. Heine
  • , A. J. Harwood
  • , P. F. Sullivan
  • , M. Peitz
  • , O. Brüstle
  • , S. Shen
  • , Y. M. Sun
  • , J. C. Glover
  • , D. Posthuma
  • , S. Djurovic*
  • *Corresponding author for this work
  • Karolinska Institutet
  • Cardiff University
  • University of North Carolina at Chapel Hill
  • University of Bonn and German Center for Neurodegenerative Diseases (DZNE)
  • University of Galway
  • Masaryk University
  • University of Oslo
  • University of Bergen

Research output: Contribution to journalReview articleAcademicpeer-review

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Abstract

Major programs in psychiatric genetics have identified >150 risk loci for psychiatric disorders. These loci converge on a small number of functional pathways, which span conventional diagnostic criteria, suggesting a partly common biology underlying schizophrenia, autism and other psychiatric disorders. Nevertheless, the cellular phenotypes that capture the fundamental features of psychiatric disorders have not yet been determined. Recent advances in genetics and stem cell biology offer new prospects for cell-based modeling of psychiatric disorders. The advent of cell reprogramming and induced pluripotent stem cells (iPSC) provides an opportunity to translate genetic findings into patient-specific in vitro models. iPSC technology is less than a decade old but holds great promise for bridging the gaps between patients, genetics and biology. Despite many obvious advantages, iPSC studies still present multiple challenges. In this expert review, we critically review the challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes.

Original languageEnglish
Pages (from-to)1167-1179
Number of pages13
JournalMolecular psychiatry
Volume21
Issue number9
DOIs
Publication statusPublished - 1 Sept 2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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