@article{10902/31631,
year = {2020},
url = {https://hdl.handle.net/10902/31631},
abstract = {Neuropsychiatric disorders overlap in symptoms and share genetic risk factors, challenging their current classification into distinct diagnostic categories. Novel cross-disorder approaches are needed to improve our understanding of the heterogeneous nature of neuropsychiatric diseases and overcome existing bottlenecks in their diagnosis and treatment. Here we employ high-content multi-parameter phospho-specific flow cytometry, fluorescent cell barcoding and automated sample preparation to characterize ex vivo signaling network responses (n?=?1764) measured at the single-cell level in B and T lymphocytes across patients diagnosed with four major neuropsychiatric disorders: autism spectrum condition (ASC), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ; n?=?25 each), alongside matched healthy controls (n?=?100). We identified 25 nodes (individual cell subtype?epitope?ligand combinations) significantly altered relative to the control group, with variable overlap between different neuropsychiatric diseases and heterogeneously expressed at the level of each individual patient. Reconstruction of the diagnostic categories from the altered nodes revealed an overlapping neuropsychiatric spectrum extending from MDD on one end, through BD and SCZ, to ASC on the other end. Network analysis showed that although the pathway structure of the epitopes was broadly preserved across the clinical groups, there were multiple discrete alterations in network connectivity, such as disconnections within the antigen/integrin receptor pathway and increased negative regulation within the Akt1 pathway in CD4+ T cells from ASC and SCZ patients, in addition to increased correlation of Stat1 (pY701) and Stat5 (pY694) responses in B cells from BD and MDD patients. Our results support the ?dimensional? approach to neuropsychiatric disease classification and suggest potential novel drug targets along the neuropsychiatric spectrum.},
organization = {We would like to thank clinicians and support staff at the affiliated institutions for patient recruitment and sample
collection, including Liliana Ruta and Stephanie Mok for the ASC cohort; Eva Brombacher for sample preparation; collaborators Joshua A. Bishop, Tracey Petryshen, and Steven J. Haggarty from Harvard Medical School (Boston, MA, USA) for contribution of the JB1121 compound; and PBMC donors for provision of biological samples.
This work was supported by grants to S.B. from the Stanley Medical Research Institute (SMRI) and the Engineering and Physical Sciences Research Council UK (EPSRC CASE studentship and Impact Acceleration Award). S.G.L. was supported an by EPSRC CASE studentship and Psynova Neurotech Ltd. J.T. was supported
through grants awarded t`o Psynova Neurotech Ltd. by the European Union FP7 funding scheme: Marie Curie Actions Industry-Academia Partnerships and Pathways (ref. 286334, PSYCH-AID project); by the Virgo consortium, funded by the Dutch Government (ref. FES0908); by the Netherlands Genomics Initiative (ref. 050-060); and by the S. G. Lago et al. Dutch Fund for Economic Structure Reinforcement, the NeuroBasic
PharmaPhenomics project (ref. 0908). S.B.-C. and B.A. were supported by the Autism Research Trust.},
publisher = {Nature Publishing Group},
publisher = {Molecular Psychiatry, 2020, 25(10), 2355-2372},
title = {Exploring the neuropsychiatric spectrum using high-content functional analysis of single-cell signaling networks},
author = {Lago, Santiago G. and Tomasik, Jakub and Rees, Geertje F. van and Ramsey, Jordan M. and Cooper, Jason D. and Broek, Jantine A. and Suárez Pinilla, Paula and Ruland, Tillmann and Auyeug, Bonnie and Mikova, Olya and Kabacs, Nikolett and Arolt, Volker and Baron-Cohen, Simon and Crespo Facorro, Benedicto and Bahn, Sabine},
}