Exploring the neuropsychiatric spectrum using high-content functional analysis of single-cell signaling networks

Santiago G. Lago, Jakub Tomasik, Geertje F. van Rees, Jordan M Ramsey, Frieder Haenisch, Jason D Cooper, Jantine A. Broek, Paula Suarez-Pinilla, Tillmann Ruland, Bonnie Auyeung, Olya Mikova, Nikolett Kabacs, Volker Arolt, Simon Baron-Cohen, Benedicto Crespo-Facorro, Sabine Bahn

Research output: Contribution to journalArticlepeer-review

Abstract

Neuropsychiatric disorders overlap in symptoms and share genetic risk factors, challenging diagnostic classification and efficacious treatment. While genomic profiling has afforded multiple hypotheses, there is an urgent need to provide a substrate for functional interpretation of disease mechanisms at the cellular level. To address this, we apply high-content functional screening to characterize signaling network responses (n=1764) at the single-cell level in primary patient blood cells from four major neuropsychiatric disorders: autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD) and schizophrenia (SCZ; n=25 each), alongside healthy controls (n=100). We identified 25 disease nodes (individual cell subtype-epitope-ligand combinations) which were heterogeneously expressed in each patient and revealed an overlapping functional spectrum extending from MDD, through BD and SCZ, to ASD. Network analysis in key immune cell subsets revealed discrete alterations in functional connectivity, including antigen/integrin receptor and Akt pathways in ASD and SCZ and the JAK-STAT pathway in BD and MDD. Our results support the ‘dimensional’ approach to neuropsychiatric disease classification and suggest potential drug targets along the neuropsychiatric spectrum.
Original languageEnglish
Pages (from-to)1-18
JournalMolecular Psychiatry
Early online date23 Jul 2018
DOIs
Publication statusE-pub ahead of print - 23 Jul 2018

Keywords

  • neuropsychiatric disorders
  • spectrum
  • high-content
  • functional analysis
  • single-cell
  • signaling networks
  • ex vivo
  • drug targets

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