Exploring cellular markers of metabolic syndrome in peripheral blood mononuclear cells across the neuropsychiatric spectrum

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy.This work was supported by grants from the Stanley Medical Research Institute (SMRI); the Engineering and Physical Sciences Research Council UK (EPSRC); the Dutch Government-funded Virgo consortium (ref. FES0908); the Netherlands Genomics Initiative (ref. 050-060-452); the European Union FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (ref. 286334, PSYCH-AID project); SAF2016-76046-R and SAF2013-46292-R (MINECO) and PI16/00156 (isciii and FEDER)

The Dark Side of EGFP: Defective Polyubiquitination

Enhanced Green Fluorescent Protein (EGFP) is the most commonly used live cell reporter despite a number of conflicting reports that it can affect cell physiology. Thus far, the precise mechanism of GFP-associated defects remained unclear. Here we demonstrate that EGFP and EGFP fusion proteins inhibit polyubiquitination, a posttranslational modification that controls a wide variety of cellular processes, like activation of kinase signalling or protein degradation by the proteasome. As a consequence, the NF-κB and JNK signalling pathways are less responsive to activation, and the stability of the p53 tumour suppressor is enhanced in cell lines and in vivo. In view of the emerging role of polyubiquitination in the regulation of numerous cellular processes, the use of EGFP as a live cell reporter should be carefully considered

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

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

The coming decade of digital brain research: a vision for neuroscience at the intersection of technology and computing

In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales— from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, to identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research

Density measurements of different receptors for Area ifs1 (IFS) [human, v1.0]

This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifs1 (IFS) obtained by means of quantitative in vitro autoradiography. The receptor densities are visualized as fingerprints (fp), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. For exemplary samples, we also provide color-coded laminar autoradiography images (ar). The autoradiography images show an exemplary density distribution of a single receptor for one laminar cross-section in a single tissue sample. Information on the used tissue samples and corresponding subjects for the receptor fingerprints and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset

Density measurements of different receptors for Area ifs3 (IFS) [human, v1.0]

This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifs3 (IFS) obtained by means of quantitative in vitro autoradiography. The receptor densities are visualized as fingerprints (fp), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. For exemplary samples, we also provide color-coded laminar autoradiography images (ar). The autoradiography images show an exemplary density distribution of a single receptor for one laminar cross-section in a single tissue sample. Information on the used tissue samples and corresponding subjects for the receptor fingerprints and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset

Density measurements of different receptors for Area ifj1 (IFS,PreCS) [human, v1.0]

This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifj1 (IFS,PreCS) obtained by means of quantitative in vitro autoradiography. The receptor densities are visualized as fingerprints (fp), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. For exemplary samples, we also provide color-coded laminar autoradiography images (ar). The autoradiography images show an exemplary density distribution of a single receptor for one laminar cross-section in a single tissue sample. Information on the used tissue samples and corresponding subjects for the receptor fingerprints and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset

Density measurements of different receptors for Area ifs4 (IFS) [human, v1.0]

This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifs4 (IFS) obtained by means of quantitative in vitro autoradiography. The receptor densities are visualized as fingerprints (fp), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. For exemplary samples, we also provide color-coded laminar autoradiography images (ar). The autoradiography images show an exemplary density distribution of a single receptor for one laminar cross-section in a single tissue sample. Information on the used tissue samples and corresponding subjects for the receptor fingerprints and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset

Density measurements of different receptors for Area ifj2 (IFS,PreCS) [human, v1.0]

This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifj2 (IFS,PreCS) obtained by means of quantitative in vitro autoradiography. The receptor densities are visualized as fingerprints (fp), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. For exemplary samples, we also provide color-coded laminar autoradiography images (ar). The autoradiography images show an exemplary density distribution of a single receptor for one laminar cross-section in a single tissue sample. Information on the used tissue samples and corresponding subjects for the receptor fingerprints and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset