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

Overview of attention for article published in Molecular Psychiatry, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Exploring the neuropsychiatric spectrum using high-content functional analysis of single-cell signaling networks
Published in
Molecular Psychiatry, July 2018
DOI 10.1038/s41380-018-0123-4
Pubmed ID
Authors

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 Auyeug, Olya Mikova, Nikolett Kabacs, Volker Arolt, Simon Baron-Cohen, Benedicto Crespo-Facorro, Sabine Bahn

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.

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X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 20%
Student > Ph. D. Student 12 13%
Student > Bachelor 10 11%
Student > Master 6 6%
Student > Doctoral Student 5 5%
Other 14 15%
Unknown 29 31%
Readers by discipline Count As %
Neuroscience 11 12%
Biochemistry, Genetics and Molecular Biology 10 11%
Psychology 10 11%
Agricultural and Biological Sciences 8 8%
Medicine and Dentistry 7 7%
Other 16 17%
Unknown 33 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 February 2019.
All research outputs
#4,304,516
of 25,708,267 outputs
Outputs from Molecular Psychiatry
#2,454
of 4,656 outputs
Outputs of similar age
#75,587
of 341,864 outputs
Outputs of similar age from Molecular Psychiatry
#60
of 86 outputs
Altmetric has tracked 25,708,267 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,656 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.6. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,864 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.