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Systemic cell-adhesion molecules (CAM) in severe mental illness-potential role of intracellular CAM-1 in linking peripheral and neuro-inflammation.

  • Author Footnotes
    ∗ Equal contribution
    Mashhood A. Sheikh
    Footnotes
    ∗ Equal contribution
    Affiliations
    Research Institute of Internal Medicine, Oslo University Hospital, Oslo, Norway
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  • Author Footnotes
    ∗ Equal contribution
    Kevin S. O`Connell
    Footnotes
    ∗ Equal contribution
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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  • Tove Lekva
    Affiliations
    Research Institute of Internal Medicine, Oslo University Hospital, Oslo, Norway
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  • Attila Szabo
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
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  • Ibrahim A. Akkouh
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
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  • Jordi Requena Osete
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
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  • Ingrid Agartz
    Affiliations
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden

    Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway

    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • John A. Engh
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Vestfold Hospital Trust, Division of Mental health and Addiction, Tønsberg, Norway
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  • Dimitrios Andreou
    Affiliations
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden

    Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway

    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Birgitte Boye
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Erlend Bøen
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Torbjørn Elvsåshagen
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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  • Sigrun Hope
    Affiliations
    Department of Neuro Habilitation, Oslo University Hospital Ullevål, Oslo, Norway
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  • Maren Caroline Frogner Werner
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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  • Inge Joa
    Affiliations
    Network for Clinical Psychosis Research, Division of Psychiatry, Stavanger University Hospital, Norway

    Network for Medical Sciences, Faculty of Health, University of Stavanger, Norway
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  • Erik Johnsen
    Affiliations
    Division of Psychiatry, Haukeland University Hospital, 5021 Bergen, Norway

    University of Bergen, Bergen, Norway

    The Norwegian Centre for Mental Disorders Research Centre of Excellence, Bergen, Norway
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  • Rune A. Kroken
    Affiliations
    Division of Psychiatry, Haukeland University Hospital, 5021 Bergen, Norway

    University of Bergen, Bergen, Norway

    The Norwegian Centre for Mental Disorders Research Centre of Excellence, Bergen, Norway
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  • Trine Vik Lagerberg
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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  • Ingrid Melle
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Ole Kristian Drange
    Affiliations
    Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway

    Department of Østmarka, Division of Mental Health, St. Olavs University Hospital, Trondheim, Norway

    Sørlandet Hospital, Kristiansand, Norway
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  • Gunnar Morken
    Affiliations
    Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
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  • Terje Nærland
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Kjetil Sørensen
    Affiliations
    Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
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  • Arne E. Vaaler
    Affiliations
    Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway

    Department of Østmarka, Division of Mental Health, St. Olavs University Hospital, Trondheim, Norway
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  • Melissa Authen Weibell
    Affiliations
    Network for Clinical Psychosis Research, Division of Psychiatry, Stavanger University Hospital, Norway

    Network for Medical Sciences, Faculty of Health, University of Stavanger, Norway
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  • Lars T. Westlye
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Faculty of Medicine, University of Oslo, Oslo, Norway
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  • Pål Aukrust
    Affiliations
    Research Institute of Internal Medicine, Oslo University Hospital, Oslo, Norway

    Faculty of Medicine, University of Oslo, Oslo, Norway

    Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
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  • Srdjan Djurovic
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

    K.G. Jebsen Center for Neurodevelopmental disorders, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Nils Eiel Steen
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Ole A. Andreassen
    Affiliations
    Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    Norwegian Centre for Mental Disorders Research, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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  • Thor Ueland
    Correspondence
    Address for correspondence: Thor Ueland, Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, P.B. 4959 Nydalen 0424 Oslo, Norway; Phone: 47-23070000; Fax: 47-23073630;
    Affiliations
    Research Institute of Internal Medicine, Oslo University Hospital, Oslo, Norway

    Faculty of Medicine, University of Oslo, Oslo, Norway

    K.G. Jebsen Thrombosis Research and Expertise Center, University of Tromsø, Tromsø, Norway
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  • Author Footnotes
    ∗ Equal contribution
Open AccessPublished:July 02, 2022DOI:https://doi.org/10.1016/j.biopsych.2022.06.029

      ABSTRACT

      Background

      Cell adhesion molecules (CAM) orchestrate leukocyte trafficking and could link peripheral and neuro-inflammation in patients with severe mental illness (SMI), by promoting inflammatory and immune mediated responses and mediating signals across blood-brain-barrier (BBB). We hypothesized that CAMs would be dysregulated in SMI and evaluated if plasma levels of different vascular and neural CAMs. Dysregulated CAMs in plasma were further evaluated in vivo in leukocytes and brain tissue and in vitro in iPSC cells.

      Methods

      We compared plasma soluble (s) levels in circulating leukocytes of different vascular (VCAM-1, ICAM-1, P-SEL) and neural (JAM-A, N-CAD) CAMs in a large SMI sample of schizophrenia spectrum disorders (SCZ, n=895) and affective disorders (AFF, n=737) and heathy controls (HC, n=1070) controlling for age, sex, BMI, CRP and freezer storage time. We also evaluated mRNA expression of ICAM1 and related genes encoding ICAM-1 receptors in leukocytes by microarray (n=842) and in available RNAseq from the CommonMind Consortium on post-mortem samples from the dorsolateral prefrontal cortex (n=474). The regulation of sICAM-1 in iPSC-derived neurons and astrocytes was assessed in SCZ patients and HC (n=8 of each).

      Results

      Our major findings: (1) increased sICAM-1 in SMI patients vs. HC; (2) increased ITGB2 mRNA, encoding the beta chain of the ICAM-1 receptor, in circulating leukocytes from SMI patients and increased prefrontal cortex mRNA expression of ICAM1 in SCZ; and (3) enhanced sICAM-1 release in iPSC-derived neurons from SCZ patients.

      Conclusion

      Our results support a systemic and cerebral dysregulation of sICAM-1 expression in SMI and especially in SCZ patients.

      Key words

      Introduction

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      ]. These CAMs may shed from the cell surface by different mechanisms and their soluble (s) form released into the circulation. As shown in Supplemental Table 1, many previous studies have evaluated circulating CAMs showing quite consistent upregulation of proteins such as sICAM-1 in SMI [
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      ] and sP-SEL [
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      ], possibly due to differences in sample material and controlling for different demographics. To our knowledge, systemic levels of sJAM-A and sN-CAD, have not been evaluated in SMI. In addition
      Based on the role of CAMs in promoting inflammatory and immune responses and mediating signals across BBB, we hypothesized that evaluation of a range of circulating CAM reflecting leukocyte/vascular interactions such as sICAM-1, sVCAM-1 and sP-SEL, as well as neural CAMs such as sJAM-A and sN-CAD, could identify a novel pattern of dysregulation with clinical relevance for SMI. We focused on CAMs increased beyond the generalized systemic inflammation and metabolic distress in SMI as reflected by CRP and BMI, controlling for these factors. To test this hypothesis, we adopted a multi-step approach. Step 1: we evaluated plasma levels of different vascular and neural CAMs in patients with SMI (n=1632) and healthy controls (HC, n=1070) and associations with symptom severity. Step 2: among the observed regulated CAMs in step 1, we assessed microarray mRNA expression of the CAM and relevant receptors in leukocytes in a subset including 579 SMI patients and 263 HC. Step 3: we assessed dysregulated CAMs and corresponding receptors by estimating cell type-specific gene expression through computational deconvolution in leukocytes and RNA-seq data of dorsolateral prefrontal cortex (DLPFC) post mortem samples from the CommonMind Consortium (CMC, n=474). Step 4: we studied the regulation of dysregulated CAMs and their receptors in human induced pluripotent stem cell (iPSC)-derived neurons and astrocytes from SCZ and HC donors (n=8).

      Materials and methods

      Setting and participants

      The current study is part of the ongoing Thematically Organized Psychosis (TOP) Study including clinically stable patients 18-65 years, able to give a written informed consent, with a diagnosis of SCZ spectrum disorder (schizophrenia, schizoaffective disorder, schizophreniform disorder, delusional disorder, brief psychotic disorder and psychosis NOS) included in the diagnostic group “Schizophrenia” (SCZ), and affective disorder (bipolar I, bipolar II, bipolar NOS and major depressive disorder with psychotic features) included in the diagnostic group “Affective” (AFF) according to DSM-IV as described [
      • Dieset I.
      • Djurovic S.
      • Tesli M.
      • Hope S.
      • Mattingsdal M.
      • Michelsen A.
      • et al.
      Up-regulation of NOTCH4 gene expression in bipolar disorder.
      ]. See the supplemental file for details. All participants gave written consent and the study was approved by the Regional Committees for Medical and Health Research Ethics (REC) in Norway and the Norwegian Data Protection Agency. Participants with C-reactive protein (CRP) >10 mg/L for any reason were excluded from the study.

      Clinical assessments and medication

      We evaluated patients with the Positive and Negative Syndrome Scale (PANSS)[
      • Kay S.R.
      • Fiszbein A.
      • Opler L.A.
      The positive and negative syndrome scale (PANSS) for schizophrenia.
      ], Young Mania Rating scale (YMRS)[
      • Young R.C.
      • Biggs J.T.
      • Ziegler V.E.
      • Meyer D.A.
      A rating scale for mania: reliability, validity and sensitivity.
      ] and the Global Assessment of Functioning Scale (GAF-S)[
      • Pedersen G.
      • Hagtvet K.A.
      • Karterud S.
      Generalizability studies of the Global Assessment of Functioning-Split version.
      ]. All participants including HC were screened for medical history, physical examination and routine blood tests in addition to isolation of plasma for CAM analysis. Information regarding prescribed antipsychotics were obtained by clinical interviews and hospital records. We calculated “defined daily dose” (dddAP) according to the World Health Organization (WHO) principles, as described [
      • Morch R.H.
      • Dieset I.
      • Faerden A.
      • Hope S.
      • Aas M.
      • Nerhus M.
      • et al.
      Inflammatory evidence for the psychosis continuum model.
      ].

      Analysis plan

      We first assessed plasma CAMs in 1632 patients with SMI (SCZ=895, AFF=737) and 1070 HC, recruited between 2002 and 2017. As shown in Table 1, the groups were not well matched, as patients with AFF were older than HC and patients with SCZ, and BMI was higher in AFF and SCZ compared with HC. SCZ patients had more males compared to AFF and HC, while AFF had more females compared to HC. In CAMs dysregulated in plasma we proceeded with i) microarray mRNA analysis in leukocytes ii) cell type-specific gene expression through computational deconvolution of microarray blood expression data and RNA-seq data of dorsolateral prefrontal cortex (DLPFC) and iii) regulation in human induced pluripotent stem cell (iPSC)-derived neurons and astrocytes. Methods are detailed below.
      Table 1Demographics and clinical information in patients with severe mental illness and healthy control participants
      SCZAFFHCANOVASCZ vs HCAFF vs HCSCZ vs AFF
      nmean±SD or %nmean±SD or %nmean±SD or %pppp
      Age, yrs89532.8±13.373738.6±13.7107032.5±10<2e-160.92<2e-16<2e-16
      Sex (Male)42557.7 %36340.6 %55952.2 %7.0E-120.033.0E-078.3E-12
      BMI, kg/m245526±5.377925.9±4.884924.7±3.91.1E-085.1E-063.0E-070.98
      PANSS total55563.6±16.642145.4±10.2-----<2e-16
      PANSS neg56115.8±6.242110.0±3.4-----<2e-16
      PANSS pos55915.3±5.44239.8±3.4-----<2e-16
      PANSS gen55832.5±8.442225.6±5.9-----<2e-16
      YMRS4725.2±5.14163.1±4.4-----1.6E-10
      GAF-S60242.7±11.743758.1±11.6-----<2e-16
      CRP, mg/L5093.5±3.63763.2±3.49682.3±2.61.3E-14<2e-165.3E-060.14
      AP use52571.2 %22324.9 %00.0 %---<2e-16
      ddd AP5251.18±0.822230.87±0.64-----9.1E-07
      HC, healthy control participants; SCZ, Schizophrenia; AFF, affective disorders; BMI, body mass index; PANSS, Positive and Negative Syndrome Scale; YMRS, Young Mania Rating Scale; GAF-S, Global Assessment of Functioning Scale; CRP, C-reactive protein; AP, antipsychotics; ddd, defined daily dose. Categorical data are given as percent while continuous data are given as mean±SD

      Protein measurements

      Plasma levels of sICAM-1, sVCAM-1, sP-selectin (sP-SEL), sJAM-A and sN-CAD were measured in duplicate by enzyme immunoassays (EIA) using commercially available antibodies (R&D Systems, Minneapolis, MN, USA) as described in detail in the Supplemental file. Intra- and inter-assay coefficients of variation were <10% for all EIAs. For immunoassays, blood was taken using EDTA vials and the plasma was isolated within the next working day and stored at -80°C. Blood sampling was performed between 8 AM and 5 PM with some variation between patients and HC. A validation of the immune-assays with regard to performance, diurnal and post-prandial variation and effect bench/fridge time is presented in Supplemental Table 2.

      RNA microarray analysis and gene expression imputation

      Leukocyte mRNA expression was evaluated in 842: SCZ=338, AFF=241, HC=263, described in Supplemental Table 3. Blood samples were collected in Tempus Blood RNA Tubes (Life Technologies Corporation) and processed as described previously [
      • Akkouh I.A.
      • Ueland T.
      • Andreassen O.A.
      • Brattbakk H.R.
      • Steen V.M.
      • Hughes T.
      • et al.
      Expression of TCN1 in Blood is Negatively Associated with Verbal Declarative Memory Performance.
      ]. Briefly 200 ng of total RNA was biotin labelled and amplified using the Illumina TotalPrep-96 RNA Amplification Kit (Thermo Fisher, Waltham, MA, USA) and global gene expression quantification was performed with Illumina HumanHT-12 v4 Expression BeadChip (Illumina, Inc.). Multidimensional scaling and hierarchical clustering were used for regular quality control and removal of multiple batch effects (RNA extraction batch, RNA extraction method, DNase treatment batch, cRNA labelling batch, and chip hybridization). The “detectOutlier” function in the R package lumi identified 84 samples as outliers. Further details are in the Supplemental file.
      The computational deconvolution tool CIBERSORTx [
      • Newman A.M.
      • Steen C.B.
      • Liu C.L.
      • Gentles A.J.
      • Chaudhuri A.A.
      • Scherer F.
      • et al.
      Determining cell type abundance and expression from bulk tissues with digital cytometry.
      ] imputed cell type-specific gene expression for 10 major blood cell populations (see Figure 2A) as defined by the LM22 reference data set available through the web-based version of the tool (https://cibersortx.stanford.edu/). The “Group Mode” analysis type was used to impute cell expression, and differential expression (DE) analyses were carried out according to the guidelines recommended by the developers [
      • Steen C.B.
      • Liu C.L.
      • Alizadeh A.A.
      • Newman A.M.
      Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx.
      ].
      Figure thumbnail gr2
      Figure 2Expression of leukocyte ICAM-1, JAM-A and integrin genes in SMI. A) Microarray mRNA expression of ICAM1 and F11R (encoding JAM-A) in circulating leukocytes. B) data were deconvoluted with CIBERSORTx. Heatmap showing imputed cell expression of genes encoding β2-integrins, LFA-1 (CD11a/CD18 encoded by the ITGAL/ITGB2 genes) and Mac-1 (CD11b/CD18 encoded by ITGAM/ITGB2) according to cell type. C) Imputed mRNA expression of ITGB2 across diagnostic groups. *p<0.05, **p<0.001 in FDR adjusted t-tests.

      RNA-seq of brain samples from the CMC

      RNA-seq data of DLPFC post-mortem brain samples was obtained from the CMC [
      • Hoffman G.E.
      • Bendl J.
      • Voloudakis G.
      • Montgomery K.S.
      • Sloofman L.
      • Wang Y.C.
      • et al.
      CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder.
      ]. A subset of 474 samples (SCZ=214, AFF=45, HC=215) was used, including only donors with Caucasian ethnicity. Details on extraction procedures, yield and quality control are given in the Supplemental file as are details on the RNAseq. All cases had a read count of >25 million reads (mean: 39.2 million). A pre-filtering step excluded all lowly expressed and non-expressed genes (<1 count per million in > 50% of cases), retaining 16895 genes for analysis. DE analyses were carried out with the DESeq2 package [
      • Love M.I.
      • Huber W.
      • Anders S.
      Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
      ], controlling for age, sex, post-mortem interval, and biobank repository (laboratory batch effects). Associations with FDR<0.05 were considered significant. For cell type-specific imputation of gene expression, CIBERSORTx was used [
      • Steen C.B.
      • Liu C.L.
      • Alizadeh A.A.
      • Newman A.M.
      Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx.
      ], selecting the “High Resolution” data analysis mode. Gene expression reference profiles for human neurons, astrocytes, and endothelial cells were obtained from Zhang et al. [
      • Zhang Y.
      • Sloan S.A.
      • Clarke L.E.
      • Caneda C.
      • Plaza C.A.
      • Blumenthal P.D.
      • et al.
      Purification and Characterization of Progenitor and Mature Human Astrocytes Reveals Transcriptional and Functional Differences with Mouse.
      ] and used as input for imputation of cell type-specific expression.

      Generation, differentiation and stimulation of astrocytes and neurons from donor iPSCs

      For reprogramming and astrocyte and neuron iPSC differentiation, fibroblast/skin biopsies were isolated from 4 HC (mean age 45.5±13.9 years, 2 male) and 4 SCZ patients (mean age 25.0±3.6 years, 2 male). We differentiated and thoroughly characterized astrocytes and neurons from patient and control iPSCs following previously published glial and neuron differentiation and phenotyping protocols with small modifications (see Supplemental methods). Culture pellets and supernatants were collected after 0, 4, 7, 11 and 14 days of incubation for qPCR and EIA analysis as described above. Harvested samples were stored at −80 °C. Extraction procedure, RT-PCR reaction and qPCR analysis are detailed in the Supplemental file.

      Statistical Analyses

      Statistical analyses were performed in R using the base statistical package. Associations between diagnosis (HC, SCZ, AFF, SCZ+AFF) and circulating levels CAM’s were assessed using linear regression, controlled for freezer storage time, age, sex, BMI and circulating levels of CRP. Similarly, associations between diagnosis and bulk mRNA levels of ICAM-1 receptors were also assessed using linear regression with the same covariates. Release of sICAM-1 from in vitro cultures were assessed by a univariate general linear model applying group (HC or SCZ) and time as fixed factors, ID number as random factor and the interaction time*group.

      Results

      Demographics and clinical characteristics

      SCZ patients had more severe symptoms as reflected by PANSS and YMRS scores, and lower levels of functioning as reflected by GAF-S, compared to AFF. CRP levels were higher in AFF and SCZ compared to HC. As expected, use of AP was more frequent in SCZ compared to AFF, with a higher dddAP.

      Circulating sCAMs in severe mental disorders

      Differences in plasma sCAM levels between patients and HC and within diagnostic subgroups, controlled for age, sex, BMI, and CRP are shown in Figure 1, with coefficient estimates after shown in Supplemental Table 4. Patients with SMI were characterized by higher plasma sICAM-1 (p=3.0E-07), with the highest levels in SCZ (p=5.3E-08), although patients with AFF (p=6.7E-04) also had higher levels compared to HC. Patients with SMI as a whole also displayed higher levels of sJAM-A (2.4E-04) with a comparable increase in SCZ (2.4E-04) and AFF (p=0.009), while sVCAM-1, sP-SEL and sN-CAD showed no differences between diagnostic groups and HC.
      Figure thumbnail gr1
      Figure 1Circulating sCAMs in severe mental disorders Evaluation of sCAM levels between SMI patients (n=1632) and HC (n=1070) and within SCZ (n=895) and AFF (n=737) subgroups, controlled for age, sex, BMI, and CRP. **p<0.01, ***p<0.001 vs. HC

      Associations between sICAM-1, sJAM-A, symptoms scores and AP treatment

      sICAM1 and sJAM-A levels were not associated with AP treatment (p=0.77 and p=0.33) or dddAP (p=0.59 and p=0.28), and there were no strong associations between plasma sICAM-1 and symptom scores as reflected by PANSS, YMRS and GAF-S (Supplemental Table 5), in SMI. A modest positive association was seen between PANSS negative scores (p=0.038) in the SMI group, mainly driven by an association in SCZ (p=0.063). In addition, sICAM-1 correlated with both BMI (r=0.14, p<0.001) and CRP (r=0.12, p<0.001), while no correlation was seen between sJAM-A and BMI or CRP (p>0.2).

      Evaluation of ICAM1, F11R (JAM-A gene) and receptor genes in leukocytes

      As shown in Figure 2A, ICAM1 and F11R mRNA expression in circulating leukocytes was similar between all diagnostic groups and controls, and did not correlate with corresponding plasma levels of sICAM-1 (r=0.03, p=0.60) or sJAM-A (r=-0.01, p=0.86).
      ICAM-1 and JAM-A mediated transmigration is facilitated by the β2-integrins, LFA-1 (CD11a/CD18 encoded by the ITGAL/ITGB2 genes) and Mac-1 (CD11b/CD18 encoded by ITGAM/ITGB2). We evaluated mRNA expression of these integrins in circulating leukocytes. As shown in Table 2, ITGB2 was increased in SMI as a whole and in SCZ and AFF subgroups, controlled for age, sex and BMI. Further controlling for CRP attenuated these associations, suggesting that enhanced systemic inflammation could contribute to elevated ITGB2 expression in SMI. Imputation of cell type-specific gene expression of the receptors through computational deconvolution (Figure 2B) revealed that ITGB2 expression was higher in neutrophils and monocytes in SZC and AFF, respectively, while it was decreased in CD4+ T cells from AFF (Figure 2C).
      Table 2Associations between mRNA expression of ICAM-1 receptor genes in leukocytes and diagnosis, controlled for age, sex, BMI, CRP and clo
      ModelOutcomeSCZ+AFFpSCZpAFFp
      AgeITGAM0.042±0.0280.1340.056±0.0310.0700.014±0.0360.698
      ITGB20.048±0.0126.4E-050.046±0.0130.0010.044±0.0158.3E-04
      ITGAL-0.013±0.0010.402-0.011±0.0220.605-0.013±0.0250.617
      Age+SEX

      +BMI
      ITGAM-0.005±0.0270.8650.028±0.0300.349-0.058±0.0330.075
      ITGB20.050±0.0131.1E-040.049±0.0150.0010.052±0.0170.002
      ITGAL0.022±0.0200.2770.013±0.0220.5730.041±0.0260.119
      Age+sex+

      BMI+CRP
      ITGAM-0.011±0.0280.7060.013±0.0310.677-0.06±0.0340.078
      ITGB20.038±0.0130.0050.031±0.0160.0520.047±0.0180.009
      ITGAL0.022±0.0210.3070.002±0.0230.9400.059±0.0280.037
      The table shows coefficients±SD compared to healthy controls. BMI, body mass index; CRP, C-reactive protein; ITGAM, Integrin alpha M; ITGB2, Integrin beta 2.

      Evaluation of ICAM1, F11R and its receptors in the brain

      We next assessed RNA-seq data in a large sample (n=474) of dorsolateral prefrontal cortex (DLPFC) post mortem tissues from the CommonMind Consortium (CMC) [
      • Hoffman G.E.
      • Bendl J.
      • Voloudakis G.
      • Montgomery K.S.
      • Sloofman L.
      • Wang Y.C.
      • et al.
      CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder.
      ]. Differential expression analyses of the whole brain region (bulk RNA-seq) showed an elevated expression of ICAM1 and ITGAL, but not F11R in SCZ (Figure 3A) compared to HC, and for ITGAL also compared to AFF. ITGAM and ITGB2 were not regulated. To investigate whether this association was driven by a specific cell population, we imputed cell type-specific expression in neurons, astrocytes (the two most abundant cell types in the brain) and endothelial cells. While gene expression in neurons and endothelial cells could not be reliably imputed, likely due to inadequate statistical power for these cell types, we found that ICAM1 expression was significantly increased in SCZ in the astrocyte subpopulation (Figure 3B) while ITGAL was not regulated in subpopulations.
      Figure thumbnail gr3
      Figure 3Regulation of ICAM-1, JAM-A and integrins in brain tissue and brain cells in SMI. A) Expression of ICAM1, F11R (encoding JAM-A) and ITGAL in bulk RNA-seq data from 474 DLPFC donors (SCZ=214, AFF=45, HC=215). *FDR<0.05, **FDR<0.001 vs. HC; †FDR<0.05 vs. AFF. B) Imputed expression of ICAM1 in astrocytes. *p<0.05. Release of sICAM-1 at different time-points from iPSC-derived C) neurons and D) astrocytes from SCZ and HC (n=8 in each group). The insert shows estimated marginal means and 95% CIs from the mixed model regression with p-value reflecting the diagnostic group effect.
      To further investigate the potential association between ICAM-1 and SCZ in the brain, we finally assessed if iPSC-derived neurons and astrocytes generated from HC and patients with SCZ released sICAM-1 during long-term culturing. As shown in Figure 3C, neurons derived from patients with SCZ released increased levels of sICAM-1 over time compared to HC. Increasing sICAM-1 release was also observed in astrocytes during culture (Figure 3D), but with a similar temporal profile in SCZ and HC. We were not able to detect ICAM1 mRNA expression in pellets from these cultures due to low expression (CT values >38).

      Discussion

      The present study evaluated previously investigated and novel sCAMs in a large sample of patients with SMI and HC. We confirm enhanced plasma sICAM-1 in patients with SMI, increased mRNA levels of ITGB2, encoding the beta chain of the ICAM-1 receptor, in circulating leukocytes from SMI patients and elevated DLPFC mRNA expression of ICAM1 in SCZ. Novel findings of our study are the dysregulation of ITGB2 in leukocytes in AFF, increased DLPFC mRNA expression of ITGAL in SCZ and enhanced release of sICAM-1 from neurons in SCZ. In addition, we report increased sJAM-A in SMI, but found no regulation in DLPFC samples.
      Plasma and serum levels of sICAM-1 have previously been evaluated in SMI (reviewed in [
      • Muller N.
      The Role of Intercellular Adhesion Molecule-1 in the Pathogenesis of Psychiatric Disorders.
      ] and summarized in Supplemental Table 1). Our finding of increased sICAM-1 supports most studies reporting higher levels in SCZ [
      • Cai H.Q.
      • Catts V.S.
      • Webster M.J.
      • Galletly C.
      • Liu D.
      • O'Donnell M.
      • et al.
      Increased macrophages and changed brain endothelial cell gene expression in the frontal cortex of people with schizophrenia displaying inflammation.
      ,
      • Nguyen T.T.
      • Dev S.I.
      • Chen G.
      • Liou S.C.
      • Martin A.S.
      • Irwin M.R.
      • et al.
      Abnormal levels of vascular endothelial biomarkers in schizophrenia.
      ,
      • Stefanovic M.P.
      • Petronijevic N.
      • Dunjic-Kostic B.
      • Velimirovic M.
      • Nikolic T.
      • Jurisic V.
      • et al.
      Role of sICAM-1 and sVCAM-1 as biomarkers in early and late stages of schizophrenia.
      ,
      • Beumer W.
      • Drexhage R.C.
      • De Wit H.
      • Versnel M.A.
      • Drexhage H.A.
      • Cohen D.
      Increased level of serum cytokines, chemokines and adipokines in patients with schizophrenia is associated with disease and metabolic syndrome.
      ] and bipolar disorders [
      • Pantovic-Stefanovic M.
      • Petronijevic N.
      • Dunjic-Kostic B.
      • Velimirovic M.
      • Nikolic T.
      • Jurisic V.
      • et al.
      sVCAM-1, sICAM-1, TNF-alpha and IL-6 levels in bipolar disorder type I: Acute, longitudinal and therapeutic implications.
      ,
      • Turan C.
      • Kesebir S.
      • Suner O.
      Are ICAM, VCAM and E-selectin levels different in first manic episode and subsequent remission?.
      ,
      • Reininghaus E.Z.
      • Lackner N.
      • Birner A.
      • Bengesser S.
      • Fellendorf F.T.
      • Platzer M.
      • et al.
      Extracellular matrix proteins matrix metallopeptidase 9 (MMP9) and soluble intercellular adhesion molecule 1 (sICAM-1) and correlations with clinical staging in euthymic bipolar disorder.
      ,
      • Schaefer M.
      • Sarkar S.
      • Schwarz M.
      • Friebe A.
      Soluble Intracellular Adhesion Molecule-1 in Patients with Unipolar or Bipolar Affective Disorders: Results from a Pilot Trial.
      ], while some studies report lower levels in SCZ [
      • Kronig H.
      • Riedel M.
      • Schwarz M.J.
      • Strassnig M.
      • Moller H.J.
      • Ackenheil M.
      • et al.
      ICAM G241A polymorphism and soluble ICAM-1 serum levels: evidence for an active immune process in schizophrenia.
      ,
      • Schwarz M.J.
      • Riedel M.
      • Ackenheil M.
      • Muller N.
      Decreased levels of soluble intercellular adhesion molecule-1 (sICAM-1) in unmedicated and medicated schizophrenic patients.
      ]. In these studies, higher sICAM-1 levels were related to stage of disease [
      • Pantovic-Stefanovic M.
      • Petronijevic N.
      • Dunjic-Kostic B.
      • Velimirovic M.
      • Nikolic T.
      • Jurisic V.
      • et al.
      sVCAM-1, sICAM-1, TNF-alpha and IL-6 levels in bipolar disorder type I: Acute, longitudinal and therapeutic implications.
      ,
      • Turan C.
      • Kesebir S.
      • Suner O.
      Are ICAM, VCAM and E-selectin levels different in first manic episode and subsequent remission?.
      ,
      • Stefanovic M.P.
      • Petronijevic N.
      • Dunjic-Kostic B.
      • Velimirovic M.
      • Nikolic T.
      • Jurisic V.
      • et al.
      Role of sICAM-1 and sVCAM-1 as biomarkers in early and late stages of schizophrenia.
      ,
      • Reininghaus E.Z.
      • Lackner N.
      • Birner A.
      • Bengesser S.
      • Fellendorf F.T.
      • Platzer M.
      • et al.
      Extracellular matrix proteins matrix metallopeptidase 9 (MMP9) and soluble intercellular adhesion molecule 1 (sICAM-1) and correlations with clinical staging in euthymic bipolar disorder.
      ,
      • Schaefer M.
      • Sarkar S.
      • Schwarz M.
      • Friebe A.
      Soluble Intracellular Adhesion Molecule-1 in Patients with Unipolar or Bipolar Affective Disorders: Results from a Pilot Trial.
      ], inflammatory and cardio-metabolic burden [
      • Cai H.Q.
      • Catts V.S.
      • Webster M.J.
      • Galletly C.
      • Liu D.
      • O'Donnell M.
      • et al.
      Increased macrophages and changed brain endothelial cell gene expression in the frontal cortex of people with schizophrenia displaying inflammation.
      ,
      • Beumer W.
      • Drexhage R.C.
      • De Wit H.
      • Versnel M.A.
      • Drexhage H.A.
      • Cohen D.
      Increased level of serum cytokines, chemokines and adipokines in patients with schizophrenia is associated with disease and metabolic syndrome.
      ], while lower levels were associated with ICAM-1 SNPs [
      • Kronig H.
      • Riedel M.
      • Schwarz M.J.
      • Strassnig M.
      • Moller H.J.
      • Ackenheil M.
      • et al.
      ICAM G241A polymorphism and soluble ICAM-1 serum levels: evidence for an active immune process in schizophrenia.
      ] and AP treatment [
      • Pantovic-Stefanovic M.
      • Petronijevic N.
      • Dunjic-Kostic B.
      • Velimirovic M.
      • Nikolic T.
      • Jurisic V.
      • et al.
      sVCAM-1, sICAM-1, TNF-alpha and IL-6 levels in bipolar disorder type I: Acute, longitudinal and therapeutic implications.
      ]. With some exceptions [
      • Stefanovic M.P.
      • Petronijevic N.
      • Dunjic-Kostic B.
      • Velimirovic M.
      • Nikolic T.
      • Jurisic V.
      • et al.
      Role of sICAM-1 and sVCAM-1 as biomarkers in early and late stages of schizophrenia.
      ], and similar to our findings, these studies present only marginal or no correlation with symptom scores. Based on the widespread vascular expression of ICAM-1 [
      • Hubbard A.K.
      • Rothlein R.
      Intercellular adhesion molecule-1 (ICAM-1) expression and cell signaling cascades.
      ] and role in atherosclerosis and metabolic disease [
      • Lim S.C.
      • Caballero A.E.
      • Smakowski P.
      • LoGerfo F.W.
      • Horton E.S.
      • Veves A.
      Soluble intercellular adhesion molecule, vascular cell adhesion molecule, and impaired microvascular reactivity are early markers of vasculopathy in type 2 diabetic individuals without microalbuminuria.
      ,
      • Luc G.
      • Arveiler D.
      • Evans A.
      • Amouyel P.
      • Ferrieres J.
      • Bard J.M.
      • et al.
      Circulating soluble adhesion molecules ICAM-1 and VCAM-1 and incident coronary heart disease: the PRIME Study.
      ], increased levels driven by potential cardio-metabolic risk could obscure associations with symptom severity in SMI. Indeed, increased BMI and CRP correlated with sICAM-1 levels in our patients suggesting that enhanced subclinical inflammation could contribute to increased sICAM-1 in SMI, but in contrast to the above studies, we controlled for CRP and BMI in our analyses. Regardless of demographic or comorbid factors contributing to elevated systemic levels, sICAM-1 could link systemic inflammation and immune activation and neuro-inflammation in SMI. Regarding potential effects of AP treatment, we found no significant associations, but this may be best assessed by a temporal design. Taken together, in by far the largest study of SMI patients, we show that elevated sICAM-1 levels in both SCZ and AFF disorders, beyond the subclinical inflammation as assessed by CRP and metabolic risk as assessed by BMI.
      Transmigration across the BBB is facilitated by the β2-integrins LFA-1 and Mac-1 [
      • Gorina R.
      • Lyck R.
      • Vestweber D.
      • Engelhardt B.
      beta2 integrin-mediated crawling on endothelial ICAM-1 and ICAM-2 is a prerequisite for transcellular neutrophil diapedesis across the inflamed blood-brain barrier.
      ], and our finding of increased ITGB2 mRNA levels encoding the common beta chain protein for these integrins in SMI leukocytes, as shown previously for mRNA [
      • Cai H.Q.
      • Weickert T.W.
      • Catts V.S.
      • Balzan R.
      • Galletly C.
      • Liu D.
      • et al.
      Altered levels of immune cell adhesion molecules are associated with memory impairment in schizophrenia and healthy controls.
      ] and protein levels [
      • Ormel P.R.
      • Bottcher C.
      • Gigase F.A.J.
      • Missall R.D.
      • van Zuiden W.
      • Fernandez Zapata M.C.
      • et al.
      A characterization of the molecular phenotype and inflammatory response of schizophrenia patient-derived microglia-like cells.
      ] in SCZ, further support that ICAM-1 mediated mechanisms could promote inflammatory cell trafficking across the BBB. Cai et al. demonstrated monocytes in the prefrontal cortex and brain tissue macrophages in close proximity to neurons in SCZ patients [
      • Cai H.Q.
      • Catts V.S.
      • Webster M.J.
      • Galletly C.
      • Liu D.
      • O'Donnell M.
      • et al.
      Increased macrophages and changed brain endothelial cell gene expression in the frontal cortex of people with schizophrenia displaying inflammation.
      ], and increased density of macrophages has been shown along the lateral ventricle [
      • North H.F.
      • Weissleder C.
      • Fullerton J.M.
      • Sager R.
      • Webster M.J.
      • Weickert C.S.
      A schizophrenia subgroup with elevated inflammation displays reduced microglia, increased peripheral immune cell and altered neurogenesis marker gene expression in the subependymal zone.
      ,
      • Weissleder C.
      • North H.F.
      • Bitar M.
      • Fullerton J.M.
      • Sager R.
      • Barry G.
      • et al.
      Reduced adult neurogenesis is associated with increased macrophages in the subependymal zone in schizophrenia.
      ] and in the midbrain [
      • Purves-Tyson T.D.
      • Robinson K.
      • Brown A.M.
      • Boerrigter D.
      • Cai H.Q.
      • Weissleder C.
      • et al.
      Increased Macrophages and C1qA, C3, C4 Transcripts in the Midbrain of People With Schizophrenia.
      ]. The imputed increased ITGB2 in monocytes, support infiltration of these cells also in AFF as suggested by deconvolution of RNAseq data from post mortem samples of the dorsal striatum, estimating more monocytes in BD compared to HC [
      • Batchu S.
      Transcriptomic Deconvolution of Dorsal Striata Reveals Increased Monocyte Fractions in Bipolar Disorder.
      ]. The increased ITGB2 on neutrophils in SCZ in our study, may suggest a role these cells in disruption of, or migration across, the BBB as seen in Alzheimer’s disease [
      • Zenaro E.
      • Pietronigro E.
      • Della Bianca V.
      • Piacentino G.
      • Marongiu L.
      • Budui S.
      • et al.
      Neutrophils promote Alzheimer's disease-like pathology and cognitive decline via LFA-1 integrin.
      ]. Neutrophil counts correlate with reductions in grey matter volume and enlarged ventricles in SCZ [
      • Nunez C.
      • Stephan-Otto C.
      • Usall J.
      • Bioque M.
      • Lobo A.
      • Gonzalez-Pinto A.
      • et al.
      Neutrophil Count Is Associated With Reduced Gray Matter and Enlarged Ventricles in First-Episode Psychosis.
      ]. Finally, the lower imputed ITGB2 in CD4+ T in AFF, suggest reduced migration of these cells following astrocyte-derived chemotaxis as shown in SCZ [
      • Akkouh I.A.
      • Ueland T.
      • Hansson L.
      • Inderhaug E.
      • Hughes T.
      • Steen N.E.
      • et al.
      Decreased IL-1beta-induced CCL20 response in human iPSC-astrocytes in schizophrenia: Potential attenuating effects on recruitment of regulatory T cells.
      ]. Since CD4+ Tregs are important anti-inflammatory regulators, their reduced ingress into the brain in SMI may contribute to a more inflammatory environment. Taken together, we hypothesize that an inflammatory systemic environment could increase β2-integrins in leukocytes in SMI, and exposure to elevated ICAM-1 could potentiate leukocyte arrest along the BBB vasculature and eventual migration into perivascular space, further promoting neuro-inflammation through secretion of inflammatory signals.
      Cai et al. demonstrated a 68% higher ICAM1 mRNA expression in DLPFC in 37 SCZ patients, in particular in a subgroup with high inflammation, with enrichment in the brain endothelium [
      • Cai H.Q.
      • Catts V.S.
      • Webster M.J.
      • Galletly C.
      • Liu D.
      • O'Donnell M.
      • et al.
      Increased macrophages and changed brain endothelial cell gene expression in the frontal cortex of people with schizophrenia displaying inflammation.
      ]. Herein we extend these findings showing increased ICAM1 mRNA expression in SCZ in a large DLPFC post mortem sample, with imputed expression primarily in astrocytes. Inflammatory challenge may induce ICAM1 mRNA and cell surface expression on cultured astrocytes [
      • Satoh J.
      • Kastrukoff L.F.
      • Kim S.U.
      Cytokine-induced expression of intercellular adhesion molecule-1 (ICAM-1) in cultured human oligodendrocytes and astrocytes.
      ,
      • Frohman E.M.
      • Frohman T.C.
      • Dustin M.L.
      • Vayuvegula B.
      • Choi B.
      • Gupta A.
      • et al.
      The induction of intercellular adhesion molecule 1 (ICAM-1) expression on human fetal astrocytes by interferon-gamma, tumor necrosis factor alpha, lymphotoxin, and interleukin-1: relevance to intracerebral antigen presentation.
      ,
      • Hery C.
      • Sebire G.
      • Peudenier S.
      • Tardieu M.
      Adhesion to human neurons and astrocytes of monocytes: the role of interaction of CR3 and ICAM-1 and modulation by cytokines.
      ], and the higher levels in post mortem samples could reflect a higher inflammatory environment in vivo as found by Cai et al. We were not able to detect any ICAM1 mRNA using qPCR from our iPSC derived cells suggesting low levels. Still, spontaneous sICAM1 correlates strongly with membrane bound expression on astrocytes [
      • Otto V.I.
      • Heinzel-Pleines U.E.
      • Gloor S.M.
      • Trentz O.
      • Kossmann T.
      • Morganti-Kossmann M.C.
      sICAM-1 and TNF-alpha induce MIP-2 with distinct kinetics in astrocytes and brain microvascular endothelial cells.
      ], and is detected in supernatants of resting cells [
      • Otto V.I.
      • Heinzel-Pleines U.E.
      • Gloor S.M.
      • Trentz O.
      • Kossmann T.
      • Morganti-Kossmann M.C.
      sICAM-1 and TNF-alpha induce MIP-2 with distinct kinetics in astrocytes and brain microvascular endothelial cells.
      ,
      • Lyons P.D.
      • Benveniste E.N.
      Cleavage of membrane-associated ICAM-1 from astrocytes: involvement of a metalloprotease.
      ]. Thus, the lack of difference between SCZ and HC in unstimulated cells support that increased astrocyte derived ICAM-1 in SCZ is due to a higher inflammatory environment. In contrast, the higher secretion of sICAM-1 from neurons in SCZ, without an inflammatory trigger, could point to some genotypic differences between SCZ patients and HC. Interestingly, enhanced oxidative stress is a feature of iPSC-derived neurons in SCZ [
      • Ahmad R.
      • Sportelli V.
      • Ziller M.
      • Spengler D.
      • Hoffmann A.
      Tracing Early Neurodevelopment in Schizophrenia with Induced Pluripotent Stem Cells.
      ], and it is tempting to hypothesize that ICAM-1 may promote oxidative-stress induced neuronal loss [
      • Calingasan N.Y.
      • Huang P.L.
      • Chun H.S.
      • Fabian A.
      • Gibson G.E.
      Vascular factors are critical in selective neuronal loss in an animal model of impaired oxidative metabolism.
      ]. Astrocytes express low levels of LFA-1, which are enhanced by IFNγ [
      • Weber F.
      • Meinl E.
      • Aloisi F.
      • Nevinny-Stickel C.
      • Albert E.
      • Wekerle H.
      • et al.
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      ], and we speculate that the increased ITGAV imputed in SCZ astrocytes could promote inflammatory signaling involving glial cells, neurons and infiltrating leukocytes. sICAM-1 may induce MIP-2 release in both mouse astrocytes and brain microvascular endothelial cells [
      • Otto V.I.
      • Heinzel-Pleines U.E.
      • Gloor S.M.
      • Trentz O.
      • Kossmann T.
      • Morganti-Kossmann M.C.
      sICAM-1 and TNF-alpha induce MIP-2 with distinct kinetics in astrocytes and brain microvascular endothelial cells.
      ], which could advance recruitment of leukocytes and inflammation in the brain [
      • Zwijnenburg P.J.
      • Polfliet M.M.
      • Florquin S.
      • van den Berg T.K.
      • Dijkstra C.D.
      • van Deventer S.J.
      • et al.
      CXC-chemokines KC and macrophage inflammatory protein-2 (MIP-2) synergistically induce leukocyte recruitment to the central nervous system in rats.
      ]. In addition to regulation of vascular permeability, ICAM-1-dependent adhesion to astrocytes induces TNF secretion, suggesting a direct role in inflammatory signal transduction [
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      ICAM-1-coupled signaling pathways in astrocytes converge to cyclic AMP response element-binding protein phosphorylation and TNF-alpha secretion.
      ]. Similar effects of sICAM-1 have shown in endothelial cells and macrophages, invoking a range of inflammatory responses [
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      ,
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      ICAM-1 signaling in endothelial cells.
      ]. Thus, ICAM-1-related mechanisms in SMI may not be restricted to transmigration of leukocytes across the BBB, but could both enhance and be enhanced by inflammation within the CNS.
      A novel finding in our study was the increased sJAM-A levels in SMI. JAM-A is expressed on endothelial cells, epithelial tight junctions and leukocytes [
      • Martin-Padura I.
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      ,
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      ] and mediate transmigration of leukocytes across the BBB in a LFA-1 dependent manner [
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      • Zernecke A.
      • Schroder A.
      • Weber C.
      JAM-1 is a ligand of the beta(2) integrin LFA-1 involved in transendothelial migration of leukocytes.
      ]. However, we observed no regulation of F11R in the DLPFC samples. A study evaluating sJAM-A as a BBB breakdown marker in human brain microvascular cells found no effects of inflammatory or hypoxic challenge and detected no upregulation in patients with clinically active multiple sclerosis [
      • Haarmann A.
      • Deiss A.
      • Prochaska J.
      • Foerch C.
      • Weksler B.
      • Romero I.
      • et al.
      Evaluation of soluble junctional adhesion molecule-A as a biomarker of human brain endothelial barrier breakdown.
      ]. As JAM-A is also expressed in atherosclerotic plaques [
      • Babinska A.
      • Azari B.M.
      • Salifu M.O.
      • Liu R.
      • Jiang X.C.
      • Sobocka M.B.
      • et al.
      The F11 receptor (F11R/JAM-A) in atherothrombosis: overexpression of F11R in atherosclerotic plaques.
      ] and increased soluble levels have been demonstrated in patients with atherosclerotic disease [
      • Cavusoglu E.
      • Kornecki E.
      • Sobocka M.B.
      • Babinska A.
      • Ehrlich Y.H.
      • Chopra V.
      • et al.
      Association of plasma levels of F11 receptor/junctional adhesion molecule-A (F11R/JAM-A) with human atherosclerosis.
      ], comorbid conditions could contribute to increased sJAM-A in SMI.
      A strength of our study was the large number of patients and controls. While previous studies on sICAM-1 have been relatively consistent, not requiring this statistical power, our study brings confidence to markers such as sP-SEL and sVCAM-1, where previous studies are highly inconsistent. P-SEL is abundantly expressed in platelets [
      • Tedder T.F.
      • Steeber D.A.
      • Chen A.
      • Engel P.
      The selectins: vascular adhesion molecules.
      ] and serum would therefore not reflect in vivo circulating levels but rather ex vivo release during platelet degranulation, which may be less relevant in SMI. Nonetheless, while we did not detect systemic dysregulation of P-selectin, VCAM-1 and NCAD, this does not necessarily imply that these proteins have no role in the progression of SMI, but merely that this was not reflected by circulating levels in our study.
      Limitations to our study include the blood sampling protocol, which was not optimal with differences between patients and HC in time of day when samples were obtained and with isolation of plasma the next day. However, our validation experiments found no systematic effects on the measured CAMs. Samples were collected and stored at -80°C over a period of 15 years, however controlling for this had no major impact on the results. The lack of smoking status in our control population is a limitation of our study. RIN was only determined in a subsample of our leukocyte mRNA samples, and quality control to remove samples with lower numbers of detected transcripts and low signal-noise ratio was performed with an R algorithm, resulting in removal of 84 samples. We were not able to impute gene expression for neurons or endothelial cell in the DLPFC post mortem samples, most probably due to low expression of the ICAM-related genes and low number of the cells compared to astrocytes in the cortex. Also, to ensure a more homogeneous study population, we a set of RNAseq data from the CMC collection due to technical differences with regard to strand specificity as described by the authors [
      • Hoffman G.E.
      • Bendl J.
      • Voloudakis G.
      • Montgomery K.S.
      • Sloofman L.
      • Wang Y.C.
      • et al.
      CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder.
      ], as well as non-Caucasian samples. While these strict criteria negatively impacted the sample size, our sample is still much larger than the sample size used in most similar studies. Patients were chronic with stable disease and results could be different in acute patients.
      Finally, the study had a cross-sectional design, making the causality described suggestive. We do not suggest sICAM-1 represents a clinically useful biomarker in these patients, as there was a large overlap in the sICAM-1 distributions of SMI patients and controls.
      In conclusion, our results support a systemic and cerebral dysregulation of sICAM-1 signaling in SMI and especially in SCZ, potentially contributing to CNS pathology in this patient group.

      Acknowledgements

      We would like to thank the participants of the study. We are also grateful for the financial support provided by South East Norway Health Authority (#2018-089,#2019-108), Research Council of Norway (#223273,#300309), for this study. We also acknowledge the technical support and service from the Genomics Core Facility at the Department of Clinical Science, the University of Bergen.
      OAA is a consultant to HealthLytix, and has received speaker’s honorarium from Sunovion and Lundbeck. All other authors report no biomedical financial interests or potential conflicts of interest.

      Supplementary Material

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