1
|
Endres D, von Zedtwitz K, Matteit I, Bünger I, Foverskov-Rasmussen H, Runge K, Feige B, Schlump A, Maier S, Nickel K, Berger B, Schiele MA, Cunningham JL, Domschke K, Prüss H, Tebartz van Elst L. Spectrum of Novel Anti-Central Nervous System Autoantibodies in the Cerebrospinal Fluid of 119 Patients With Schizophreniform and Affective Disorders. Biol Psychiatry 2022; 92:261-274. [PMID: 35606187 DOI: 10.1016/j.biopsych.2022.02.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 02/09/2022] [Accepted: 02/10/2022] [Indexed: 12/17/2022]
Abstract
BACKGROUND Autoimmune psychosis may be caused by well-characterized anti-neuronal autoantibodies, such as those against the NMDA receptor. However, the presence of additional anti-central nervous system (CNS) autoantibodies in these patients has not been systematically assessed. METHODS Serum and cerebrospinal fluid (CSF) from patients with schizophreniform and affective syndromes were analyzed for immunoglobulin G anti-CNS autoantibodies using tissue-based assays with indirect immunofluorescence on unfixed murine brain tissue as part of an extended routine clinical practice. After an initial assessment of patients with red flags for autoimmune psychosis (n = 30), tissue-based testing was extended to a routine procedure (n = 89). RESULTS Based on the findings from all 119 patients, anti-CNS immunoglobulin G autoantibodies against brain tissue were detected in 18% (n = 22) of patients (serum 9%, CSF 18%) following five principal patterns: 1) against vascular structures, most likely endothelial cells (serum 3%, CSF 8%); 2) against granule cells in the cerebellum and/or hippocampus (serum 4%, CSF 6%); 3) against myelinated fibers (serum 2%, CSF 2%); 4) against cerebellar Purkinje cells (serum 0%, CSF 2%); and 5) against astrocytes (serum 1%, CSF 1%). The patients with novel anti-CNS autoantibodies showed increased albumin quotients (p = .026) and white matter changes (p = .020) more frequently than those who tested negative for autoantibodies. CONCLUSIONS The study demonstrates five novel autoantibody-binding patterns on brain tissue of patients with schizophreniform and affective syndromes. CSF yielded positive findings more frequently than serum analysis. The frequency and spectrum of autoantibodies in these patient groups may be broader than previously thought.
Collapse
Affiliation(s)
- Dominique Endres
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katharina von Zedtwitz
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Isabelle Matteit
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Isabel Bünger
- Department of Neurology and Experimental Neurology, Universitätsmedizin Berlin, Berlin, Germany; German Center for Neurodegenerative Diseases Berlin, Berlin, Germany
| | - Helle Foverskov-Rasmussen
- Department of Neurology and Experimental Neurology, Universitätsmedizin Berlin, Berlin, Germany; German Center for Neurodegenerative Diseases Berlin, Berlin, Germany
| | - Kimon Runge
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bernd Feige
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Andrea Schlump
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Simon Maier
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Kathrin Nickel
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Benjamin Berger
- Clinic of Neurology and Neurophysiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Miriam A Schiele
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Janet L Cunningham
- Department of Neuroscience, Psychiatry, Uppsala University, Uppsala, Sweden
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Harald Prüss
- Department of Neurology and Experimental Neurology, Universitätsmedizin Berlin, Berlin, Germany; German Center for Neurodegenerative Diseases Berlin, Berlin, Germany.
| | - Ludger Tebartz van Elst
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| |
Collapse
|
2
|
Hansen N, Lipp M, Vogelgsang J, Vukovich R, Zindler T, Luedecke D, Gingele S, Malchow B, Frieling H, Kühn S, Denk J, Gallinat J, Skripuletz T, Moschny N, Fiehler J, Riedel C, Wiedemann K, Wattjes MP, Zerr I, Esselmann H, Bleich S, Wiltfang J, Neyazi A. Autoantibody-associated psychiatric symptoms and syndromes in adults: A narrative review and proposed diagnostic approach. Brain Behav Immun Health 2021; 9:100154. [PMID: 34589896 PMCID: PMC8474611 DOI: 10.1016/j.bbih.2020.100154] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 09/26/2020] [Indexed: 12/13/2022] Open
Abstract
Background Autoimmune-mediated encephalitis is a disease that often encompasses psychiatric symptoms as its first clinical manifestation’s predominant and isolated characteristic. Novel guidelines even distinguish autoimmune psychosis from autoimmune encephalitis. The aim of this review is thus to explore whether a wide range of psychiatric symptoms and syndromes are associated or correlate with autoantibodies. Methods We conducted a PubMed search to identify appropriate articles concerning serum and/or cerebrospinal fluid (CSF) autoantibodies associated with psychiatric symptoms and syndromes between 2000 and 2020. Relying on this data, we developed a diagnostic approach to optimize the detection of autoantibodies in psychiatric patients, potentially leading to the approval of an immunotherapy. Results We detected 10 major psychiatric symptoms and syndromes often reported to be associated with serum and/or CSF autoantibodies comprising altered consciousness, disorientation, memory impairment, obsessive-compulsive behavior, psychosis, catatonia, mood dysfunction, anxiety, behavioral abnormalities (autism, hyperkinetic), and sleeping dysfunction. The following psychiatric diagnoses were associated with serum and/or CSF autoantibodies: psychosis and schizophrenia spectrum disorders, mood disorders, minor and major neurocognitive impairment, obsessive-compulsive disorder, autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), anxiety disorders, eating disorders and addiction. By relying on these symptom clusters and diagnoses in terms of onset and their duration, we classified a subacute or subchronic psychiatric syndrome in patients that should be screened for autoantibodies. We propose further diagnostics entailing CSF analysis, electroencephalography and magnetic resonance imaging of the brain. Exploiting these technologies enables standardized and accurate diagnosis of autoantibody-associated psychiatric symptoms and syndromes to deliver early immunotherapy. Conclusions We have developed a clinical diagnostic pathway for classifying subgroups of psychiatric patients whose psychiatric symptoms indicate a suspected autoimmune origin. Autoantibodies are associated with a broad spectrum of psychiatric syndromes. More systematic studies are needed to elucidate the significance of autoantibodies. We developed a pathway to identify autoantibody-associated psychiatric syndromes.
Collapse
Affiliation(s)
- Niels Hansen
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Von-Siebold-Str. 5, 37075, Goettingen, Germany
| | - Michael Lipp
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Jonathan Vogelgsang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Von-Siebold-Str. 5, 37075, Goettingen, Germany
| | - Ruth Vukovich
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Von-Siebold-Str. 5, 37075, Goettingen, Germany
| | - Tristan Zindler
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Daniel Luedecke
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Stefan Gingele
- Department of Neurology, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Von-Siebold-Str. 5, 37075, Goettingen, Germany
| | - Helge Frieling
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Simone Kühn
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Johannes Denk
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Thomas Skripuletz
- Department of Neurology, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Nicole Moschny
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Jens Fiehler
- Department of Neuroradiology, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Christian Riedel
- Department of Neuroradiology, University of Goettingen, Robert-Koch Str. 40, 37075, Goettingen, Germany
| | - Klaus Wiedemann
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20251, Hamburg, Germany
| | - Mike P Wattjes
- Department of Neuroradiology, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Inga Zerr
- Department of Neurology, University of Goettingen, Robert-Koch Str. 40, 37075, Goettingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075, Goettingen, Germany
| | - Hermann Esselmann
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Von-Siebold-Str. 5, 37075, Goettingen, Germany
| | - Stefan Bleich
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Von-Siebold-Str. 5, 37075, Goettingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075, Goettingen, Germany.,Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Alexandra Neyazi
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Carl-Neuberg Str. 1, 30625, Hannover, Germany
| | | |
Collapse
|
3
|
Autoantibody profiles associated with clinical features in psychotic disorders. Transl Psychiatry 2021; 11:474. [PMID: 34518517 PMCID: PMC8438048 DOI: 10.1038/s41398-021-01596-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 08/12/2021] [Accepted: 08/26/2021] [Indexed: 11/23/2022] Open
Abstract
Autoimmune processes are suspected to play a role in the pathophysiology of psychotic disorders. Better understanding of the associations between auto-immunoglobulin G (IgG) repertoires and clinical features of mental illness could yield novel models of the pathophysiology of psychosis, and markers for biological patient stratification. We undertook cross-sectional detection and quantification of auto-IgGs in peripheral blood plasma of 461 people (39% females) with established psychotic disorder diagnoses. Broad screening of 24 individuals was carried out on group level in eight clinically defined groups using planar protein microarrays containing 42,100 human antigens representing 18,914 proteins. Autoantibodies indicated by broad screening and in the previous literature were measured using a 380-plex bead-based array for autoantibody profiling of all 461 individuals. Associations between autoantibody profiles and dichotomized clinical characteristics were assessed using a stepwise selection procedure. Broad screening and follow-up targeted analyses revealed highly individual autoantibody profiles. Females, and people with family histories of obesity or of psychiatric disorders other than schizophrenia had the highest overall autoantibody counts. People who had experienced subjective thought disorder and/or were treated with clozapine (trend) had the lowest overall counts. Furthermore, six autoantibodies were associated with specific psychopathology symptoms: anti-AP3B2 (persecutory delusions), anti-TDO2 (hallucinations), anti-CRYGN (initial insomnia); anti-APMAP (poor appetite), anti-OLFM1 (above-median cognitive function), and anti-WHAMMP3 (anhedonia and dysphoria). Future studies should clarify whether there are causal biological relationships, and whether autoantibodies could be used as clinical markers to inform diagnostic patient stratification and choice of treatment.
Collapse
|
4
|
Just D, Månberg A, Mitsios N, Stockmeier CA, Rajkowska G, Uhlén M, Mulder J, Feuk L, Cunningham JL, Nilsson P, Carlström EL. Exploring autoantibody signatures in brain tissue from patients with severe mental illness. Transl Psychiatry 2020; 10:401. [PMID: 33208725 PMCID: PMC7676257 DOI: 10.1038/s41398-020-01079-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 09/20/2020] [Accepted: 10/06/2020] [Indexed: 01/17/2023] Open
Abstract
In recent years, studies have shown higher prevalence of autoantibodies in patients with schizophrenia compared to healthy individuals. This study applies an untargeted and a targeted affinity proteomics approach to explore and characterize the autoantibody repertoire in brain tissues from 73 subjects diagnosed with schizophrenia and 52 control subjects with no psychiatric or neurological disorders. Selected brain tissue lysates were first explored for IgG reactivity on planar microarrays composed of 11,520 protein fragments representing 10,820 unique proteins. Based on these results of ours and other previous studies of autoantibodies related to psychosis, we selected 226 fragments with an average length of 80 amino acids, representing 127 unique proteins. Tissue-based analysis of IgG reactivities using antigen suspension bead arrays was performed in a multiplex and parallel fashion for all 125 subjects. Among the detected autoantigens, higher IgG reactivity in subjects with schizophrenia, as compared to psychiatrically healthy subjects, was found against the glutamate ionotropic receptor NMDA type subunit 2D (anti-GluN2D). In a separate cohort with serum samples from 395 young adults with a wider spectrum of psychiatric disorders, higher levels of serum autoantibodies targeting GluN2D were found when compared to 102 control individuals. By further validating GluN2D and additional potential autoantigens, we will seek insights into how these are associated with severe mental illnesses.
Collapse
Affiliation(s)
- David Just
- Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Department of Neuroscience, Psychiatry - Uppsala University, Uppsala, Sweden
| | - Anna Månberg
- Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Nicholas Mitsios
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Craig A Stockmeier
- Department of Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS, USA
| | - Grazyna Rajkowska
- Department of Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS, USA
| | - Mathias Uhlén
- Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Jan Mulder
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Lars Feuk
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Janet L Cunningham
- Department of Neuroscience, Psychiatry - Uppsala University, Uppsala, Sweden
| | - Peter Nilsson
- Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden.
| | - Eva Lindholm Carlström
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
| |
Collapse
|
5
|
Murrie B, Lappin J, Large M, Sara G. Transition of Substance-Induced, Brief, and Atypical Psychoses to Schizophrenia: A Systematic Review and Meta-analysis. Schizophr Bull 2020; 46:505-516. [PMID: 31618428 PMCID: PMC7147575 DOI: 10.1093/schbul/sbz102] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Some people who experience substance-induced psychosis later develop an enduring psychotic disorder such as schizophrenia. This study examines the proportion of people with substance-induced psychoses who transition to schizophrenia, compares this to other brief and atypical psychoses, and examines moderators of this risk. A search of MEDLINE, PsychINFO, and Embase identified 50 eligible studies, providing 79 estimates of transition to schizophrenia among 40 783 people, including 25 studies providing 43 substance-specific estimates in 34 244 people. The pooled proportion of transition from substance-induced psychosis to schizophrenia was 25% (95% CI 18%-35%), compared with 36% (95% CI 30%-43%) for brief, atypical and not otherwise specified psychoses. Type of substance was the primary predictor of transition from drug-induced psychosis to schizophrenia, with highest rates associated with cannabis (6 studies, 34%, CI 25%-46%), hallucinogens (3 studies, 26%, CI 14%-43%) and amphetamines (5 studies, 22%, CI 14%-34%). Lower rates were reported for opioid (12%), alcohol (10%) and sedative (9%) induced psychoses. Transition rates were slightly lower in older cohorts but were not affected by sex, country of the study, hospital or community location, urban or rural setting, diagnostic methods, or duration of follow-up. Substance-induced psychoses associated with cannabis, hallucinogens, and amphetamines have a substantial risk of transition to schizophrenia and should be a focus for assertive psychiatric intervention.
Collapse
Affiliation(s)
- Benjamin Murrie
- St George Hospital and Sutherland Hospital, South Eastern Sydney Local Health District, Kogarah, Australia
| | - Julia Lappin
- School of Psychiatry, University of NSW, Sydney, Australia,National Drug and Alcohol Research Centre, University of NSW, Sydney, Australia
| | - Matthew Large
- School of Psychiatry, University of NSW, Sydney, Australia
| | - Grant Sara
- InforMH, System Information and Analytics Branch, NSW Ministry of Health, North Ryde, Australia,Northern Clinical School, Sydney Medical School, University of Sydney, St Leonards, Australia,To whom correspondence should be addressed; PO Box 169, North Ryde NSW 1670, Australia; tel: 61-2-88775132, fax: 61-2-98875722, e-mail:
| |
Collapse
|
6
|
Moritz CP, Paul S, Stoevesandt O, Tholance Y, Camdessanché JP, Antoine JC. Autoantigenomics: Holistic characterization of autoantigen repertoires for a better understanding of autoimmune diseases. Autoimmun Rev 2020; 19:102450. [DOI: 10.1016/j.autrev.2019.102450] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 10/16/2019] [Indexed: 12/13/2022]
|
7
|
Chiricosta L, Gugliandolo A, Diomede F, Pizzicannella J, Trubiani O, Iori R, Tardiolo G, Guarnieri S, Bramanti P, Mazzon E. Moringin Pretreatment Inhibits the Expression of Genes Involved in Mitophagy in the Stem Cell of the Human Periodontal Ligament. Molecules 2019; 24:molecules24183217. [PMID: 31487916 PMCID: PMC6767209 DOI: 10.3390/molecules24183217] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 08/28/2019] [Accepted: 09/03/2019] [Indexed: 12/14/2022] Open
Abstract
Moringin [4-(α-L-rhamnosyloxy) benzyl isothiocyanate] is an isothiocyanate extracted from Moringa oleifera seeds. It is an antioxidant known for several biological properties useful in the treatment of neurodegenerative diseases. Several neurodegenerative disorders such as Parkinson’s and Alzheimer’s diseases are linked to dysfunctional mitochondria due to the resulting increase of Reactive Oxygen Species (ROS). Stem cell-based therapeutic treatments in neurodegenerative diseases provide an alternative strategy aimed to replace the impaired tissue. In this study were investigated the deregulated genes involved in mitophagy in the human periodontal ligament stem cells pretreated with moringin. The RNA-seq study reveals the downregulation of PINK1, with a fold change (FC) of −0.56, such as the genes involved in the phagophore formation (MAP1LC3B FC: −0.73, GABARAP FC: −0.52, GABARAPL1 FC: −0.70, GABARAPL2 FC: −0.39). The moringin pretreatment downregulates the pro−apoptotic gene BAX (−0.66) and upregulates the anti-apoptotic genes BCL2L12 (FC: 1.35) and MCL1 (FC: 0.36). The downregulation of the most of the caspases (CASP1 FC: −1.43, CASP4 FC: −0.18, CASP6 FC: −1.34, CASP7 FC: −0.46, CASP8 FC: −0.65) implies the inactivation of the apoptotic process. Our results suggest that mitochondrial dysfunctions induced by oxidative stress can be inhibited by moringin pretreatment in human periodontal ligament stem cells (hPDLSCs).
Collapse
Affiliation(s)
- Luigi Chiricosta
- IRCCS Centro Neurolesi "Bonino-Pulejo", Via Provinciale Palermo, Contrada Casazza, 98124 Messina, Italy.
| | - Agnese Gugliandolo
- IRCCS Centro Neurolesi "Bonino-Pulejo", Via Provinciale Palermo, Contrada Casazza, 98124 Messina, Italy.
| | - Francesca Diomede
- Department of Medical, Oral and Biotechnological Sciences, University "G. d'Annunzio" Chieti-Pescara, 66100 Chieti, Italy.
| | - Jacopo Pizzicannella
- Department of Medical, Oral and Biotechnological Sciences, University "G. d'Annunzio" Chieti-Pescara, 66100 Chieti, Italy.
| | - Oriana Trubiani
- Department of Medical, Oral and Biotechnological Sciences, University "G. d'Annunzio" Chieti-Pescara, 66100 Chieti, Italy.
| | - Renato Iori
- Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria, Centro di ricerca Agricoltura e Ambiente (CREA-AA), Via di Corticella 133, 40128 Bologna, Italy.
| | - Giuseppe Tardiolo
- IRCCS Centro Neurolesi "Bonino-Pulejo", Via Provinciale Palermo, Contrada Casazza, 98124 Messina, Italy.
| | - Simone Guarnieri
- Department of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio", Chieti-Pescara, 66100 Chieti, Italy.
- Center on Aging Science and Translational Medicine (Ce.S.I.-Me.T.), University "G. d'Annunzio", Chieti-Pescara, 66100 Chieti, Italy.
| | - Placido Bramanti
- IRCCS Centro Neurolesi "Bonino-Pulejo", Via Provinciale Palermo, Contrada Casazza, 98124 Messina, Italy.
| | - Emanuela Mazzon
- IRCCS Centro Neurolesi "Bonino-Pulejo", Via Provinciale Palermo, Contrada Casazza, 98124 Messina, Italy.
| |
Collapse
|
8
|
Morie KP, Wu J, Landi N, Potenza MN, Mayes LC, Crowley MJ. Oscillatory Dynamics of Feedback Processing in Adolescents with Prenatal Cocaine Exposure. Dev Neuropsychol 2019; 44:429-442. [PMID: 31353953 PMCID: PMC6690776 DOI: 10.1080/87565641.2019.1645143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 07/01/2019] [Accepted: 07/06/2019] [Indexed: 12/31/2022]
Abstract
Prenatal cocaine exposure (PCE) has ramifications for feedback processing. Measuring neural oscillatory dynamics (during electroencephalography) provides insight into the time signatures and neural processes of feedback processing in adolescents with PCE. We measured spectral power in alpha and theta frequency bands while 49 adolescents with PCE and 34 non-drug exposed (NDE) performed a task with win/no-win feedback. Compared to NDE individuals, those with PCE showed reduced alpha power and increased theta power in response to no-win feedback. These findings suggest altered reactivity in PCE adolescents.
Collapse
Affiliation(s)
- Kristen P. Morie
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06510, USA
- Child Study Center, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Jia Wu
- Child Study Center, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Nicole Landi
- Child Study Center, Yale University School of Medicine, New Haven, CT, 06510, USA
- Haskins Laboratories, New Haven, CT 06519, USA
| | - Marc N. Potenza
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06510, USA
- Child Study Center, Yale University School of Medicine, New Haven, CT, 06510, USA
- Connecticut Mental Health Center, New Haven, CT, 06519, USA
- Connecticut Council on Problem Gambling, Wethersfield, CT, 06109, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Linda C. Mayes
- Child Study Center, Yale University School of Medicine, New Haven, CT, 06510, USA
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, 06519, USA
- Department of Psychology, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Michael J. Crowley
- Child Study Center, Yale University School of Medicine, New Haven, CT, 06510, USA
| |
Collapse
|
9
|
Neiman M, Hellström C, Just D, Mattsson C, Fagerberg L, Schuppe-Koistinen I, Gummesson A, Bergström G, Kallioniemi O, Achour A, Sallinen R, Uhlén M, Nilsson P. Individual and stable autoantibody repertoires in healthy individuals. Autoimmunity 2019; 52:1-11. [PMID: 30835561 DOI: 10.1080/08916934.2019.1581774] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
In the era towards precision medicine, we here present the individual specific autoantibody signatures of 193 healthy individuals. The self-reactive IgG signatures are stable over time in a way that each individual profile is recognized in longitudinal sampling. The IgG autoantibody reactivity towards an antigen array comprising 335 protein fragments, representing 204 human proteins with potential relevance to autoimmune disorders, was measured in longitudinal plasma samples from 193 healthy individuals. This analysis resulted in unique autoantibody barcodes for each individual that were maintained over one year's time. The reactivity profiles, or signatures, are person specific in regards to the number of reactivities and antigen specificity. Two independent data sets were consistent in that each healthy individual displayed reactivity towards 0-16 antigens, with a median of six. Subsequently, four selected individuals were profiled on in-house produced high-density protein arrays containing 23,000 protein fragments representing 14,000 unique protein coding genes. Based on a unique, broad and deep longitudinal profiling of autoantibody reactivities, our results demonstrate a unique autoreactive profile in each analyzed healthy individual. The need and interest for broad-ranged and high-resolution molecular profiling of healthy individuals is rising. We have here generated and assessed an initial perspective on the global distribution of the self-reactive IgG repertoire in healthy individuals, by investigating 193 well-characterized healthy individuals. Highlights A unique longitudinal profiling of autoantibody repertoires in healthy individuals Autoantibody profiles are highly individual and stable over time All individuals display IgG binding to human protein fragments The specificity of disease associated autoantigens needs to be thoroughly characterized The identification of a small set of highly reactive autoantigens Importance of stringent antigen and sample specific cut-offs for defining reactivity.
Collapse
Affiliation(s)
- Maja Neiman
- a SciLifeLab, Division of Affinity Proteomics, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - Cecilia Hellström
- a SciLifeLab, Division of Affinity Proteomics, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - David Just
- a SciLifeLab, Division of Affinity Proteomics, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - Cecilia Mattsson
- a SciLifeLab, Division of Affinity Proteomics, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - Linn Fagerberg
- b SciLifeLab, Division of Systems Biology, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - Ina Schuppe-Koistinen
- b SciLifeLab, Division of Systems Biology, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - Anders Gummesson
- c Department of Clinical Pathology and Genetics , Sahlgrenska University Hospital , Gothenburg , Sweden
| | - Göran Bergström
- d Department of Clinical Physiology , Sahlgrenska University Hospital , Gothenburg , Sweden
| | - Olli Kallioniemi
- e Institute for Molecular Medicine Finland, FIMM , University of Helsinki , Helsinki , Finland.,f SciLifeLab, Department of Oncology and Pathology , Karolinska Institutet , Stockholm , Sweden
| | - Adnane Achour
- g SciLifeLab, Department of Medicine Solna, Karolinska Institute & Division of Infectious Diseases , Karolinska University Hospital , Stockholm , Sweden
| | - Riitta Sallinen
- e Institute for Molecular Medicine Finland, FIMM , University of Helsinki , Helsinki , Finland.,f SciLifeLab, Department of Oncology and Pathology , Karolinska Institutet , Stockholm , Sweden
| | - Mathias Uhlén
- b SciLifeLab, Division of Systems Biology, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| | - Peter Nilsson
- a SciLifeLab, Division of Affinity Proteomics, Department of Protein Science , KTH Royal Institute of Technology , Stockholm , Sweden
| |
Collapse
|
10
|
Pollak TA, Rogers JP, Nagele RG, Peakman M, Stone JM, David AS, McGuire P. Antibodies in the Diagnosis, Prognosis, and Prediction of Psychotic Disorders. Schizophr Bull 2019; 45:233-246. [PMID: 29474698 PMCID: PMC6293207 DOI: 10.1093/schbul/sby021] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Blood-based biomarker discovery for psychotic disorders has yet to impact upon routine clinical practice. In physical disorders antibodies have established roles as diagnostic, prognostic and predictive (theranostic) biomarkers, particularly in disorders thought to have a substantial autoimmune or infective aetiology. Two approaches to antibody biomarker identification are distinguished: a "top-down" approach, in which antibodies to specific antigens are sought based on the known function of the antigen and its putative role in the disorder, and emerging "bottom-up" or "omics" approaches that are agnostic as to the significance of any one antigen, using high-throughput arrays to identify distinctive components of the antibody repertoire. Here we review the evidence for antibodies (to self-antigens as well as infectious organism and dietary antigens) as biomarkers of diagnosis, prognosis, and treatment response in psychotic disorders. Neuronal autoantibodies have current, and increasing, clinical utility in the diagnosis of organic or atypical psychosis syndromes. Antibodies to selected infectious agents show some promise in predicting cognitive impairment and possibly other symptom domains (eg, suicidality) within psychotic disorders. Finally, infectious antibodies and neuronal and other autoantibodies have recently emerged as potential biomarkers of response to anti-infective therapies, immunotherapies, or other novel therapeutic strategies in psychotic disorders, and have a clear role in stratifying patients for future clinical trials. As in nonpsychiatric disorders, combining biomarkers and large-scale use of "bottom-up" approaches to biomarker identification are likely to maximize the eventual clinical utility of antibody biomarkers in psychotic disorders.
Collapse
Affiliation(s)
- Thomas A Pollak
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Joint first authors
| | - Jonathan P Rogers
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Joint first authors
| | - Robert G Nagele
- Biomarker Discovery Center, New Jersey Institute for Successful Aging, Rowan University School of Osteopathic Medicine, Stratford, NJ
| | - Mark Peakman
- Department of Immunobiology, Faculty of Life Sciences & Medicine, King’s College London, London, UK
| | - James M Stone
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Anthony S David
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| |
Collapse
|
11
|
Abstract
Protein profiling enabled through affinity proteomics represents a powerful strategy for analysis of complex samples such as human body fluids. Cerebrospinal fluid (CSF) is the proximal fluid of the central nervous system and is commonly analyzed in the context of neurological diseases. Through the presence of brain-derived proteins, this fluid can offer insight into the physiological state of the brain. Here, we describe multiplex and flexible protein and autoantibody profiling approaches using suspension bead arrays. Through minimal sample processing, these methods enable high-throughput analysis of hundreds of samples and proteins in one single assay and thereby provide powerful approaches for discovery of disease-associated proteins and autoantigens.
Collapse
|
12
|
Ocak U, Ocak PE, Wang A, Zhang JH, Boling W, Wu P, Mo J, Zhang T, Huang L. Targeting mast cell as a neuroprotective strategy. Brain Inj 2018; 33:723-733. [PMID: 30554528 DOI: 10.1080/02699052.2018.1556807] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background: Mast cells (MCs) are perivascularly located immune cells of haematopoietic origin. Emerging evidences suggest that the activation of MCs play important roles in the pathogenesis of blood brain barrier disruption, neuroinflammation, and neurodegeneration. Objectives: In this review, we aimed to discuss the detrimental effects of MCs in response to various types of brain injury, as well as the therapeutic potential and neuroprotective effects of targeting the activation and degranulation of MCs, particularly in the management of the acute phase. Methods: An extensive online literature search was conducted through Pubmed/Central on March 2018. Then, we comprehensively summarized the effects of the activation of brain MCs in acute brain injury along with current pharmacological strategies targeting at the activation of MCs. Results: The review of the current literature indicated that the activation and degranulation of brain MCs significantly contribute to the acute pathological process following different types of brain injury including focal and global cerebral ischaemia, intracerebral haemorrhage, subarachnoid haemorrhage, and traumatic brain injury. Conclusions: Brain MCs significantly contribute to the acute pathological processes following brain injury. In that regard, targeting brain MCs may provide a novel strategy for neuroprotection.
Collapse
Affiliation(s)
- Umut Ocak
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA
| | - Pinar Eser Ocak
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA
| | - Annie Wang
- b Department of Anesthesiology , Loma Linda University School of Medicine , Loma Linda , CA , USA
| | - John H Zhang
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA.,b Department of Anesthesiology , Loma Linda University School of Medicine , Loma Linda , CA , USA.,c Department of Neurosurgery , Loma Linda University School of Medicine , Loma Linda , CA , USA
| | - Warren Boling
- c Department of Neurosurgery , Loma Linda University School of Medicine , Loma Linda , CA , USA
| | - Pei Wu
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA.,d Department of Neurosurgery , The First Affiliated Hospital of Harbin Medical University , Harbin , Heilongjiang , China
| | - Jun Mo
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA.,e Department of Neurosurgery, The Fourth Affiliated Hospital , School of Medicine, Zhejiang University , Yiwu , Zhejiang , China
| | - Tongyu Zhang
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA.,d Department of Neurosurgery , The First Affiliated Hospital of Harbin Medical University , Harbin , Heilongjiang , China
| | - Lei Huang
- a Department of Basic Sciences, Division of Physiology , Loma Linda University School of Medicine , Loma Linda , CA , USA.,c Department of Neurosurgery , Loma Linda University School of Medicine , Loma Linda , CA , USA
| |
Collapse
|
13
|
Suvisaari J, Mantere O, Keinänen J, Mäntylä T, Rikandi E, Lindgren M, Kieseppä T, Raij TT. Is It Possible to Predict the Future in First-Episode Psychosis? Front Psychiatry 2018; 9:580. [PMID: 30483163 PMCID: PMC6243124 DOI: 10.3389/fpsyt.2018.00580] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 10/23/2018] [Indexed: 12/26/2022] Open
Abstract
The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features-like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis-are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.
Collapse
Affiliation(s)
- Jaana Suvisaari
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Outi Mantere
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Psychiatry, McGill University, Montreal, QC, Canada.,Bipolar Disorders Clinic, Douglas Mental Health University Institute, Montreal, QC, Canada.,Department of Psychiatry, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jaakko Keinänen
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Psychiatry, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Teemu Mäntylä
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, and Advanced Magnetic Imaging Center, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland.,Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Eva Rikandi
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, and Advanced Magnetic Imaging Center, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland.,Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Maija Lindgren
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Tuula Kieseppä
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Psychiatry, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Tuukka T Raij
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, and Advanced Magnetic Imaging Center, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland
| |
Collapse
|