Extracellular matrix proteins matrix metallopeptidase 9 (MMP9) and soluble intercellular adhesion molecule 1 (sICAM-1) and correlations with clinical staging in euthymic bipolar disorder.

OBJECTIVES: Matrix metallopeptidase 9 (MMP9) and soluble intercellular adhesion molecule 1 (sICAM-1) are both involved in the restructuring of connective tissues. Evidence also implicates MMP9 and sICAM in cardiovascular and neoplastic diseases, where blood levels may be a marker of disease severity or prognosis. In individuals with bipolar disorder (BD), higher risk for cardiovascular illness has been extensively reported. METHODS: The aim of this investigation was to measure and compare peripheral levels of serum MMP9 and sICAM in adults with euthymic BD and healthy controls (HC). Furthermore, we focussed on correlations with illness severity and metabolic parameters. RESULTS: MMP9 levels among the BD sample (n = 112) were significantly higher than among the HC (n = 80) (MMP9: F = 9.885, p = 0.002, η(2)  = 0.058) after controlling for confounding factors. Patients with BD in a later, progressive stage of disease showed significantly higher MMP9 as well as sICAM-1 levels compared to patients with BD in an earlier stage of disease (MMP9: F = 5.8, p = 0.018, η(2)  = 0.054; sICAM-1: F = 5.6, p = 0.020, η(2)  = 0.052). Correlation analyses of cognitive measures revealed a negative association between performance on the d2 Test of Attention and MMP9 (r = -0.287, p = 0.018) in the BD sample. Despite the sample being euthymic (i.e., according to conventional criteria) at the time of analysis, we found significant correlations between MMP9 as well as sICAM-1 and subthreshold depressive/hypomanic symptoms. CONCLUSIONS: A collection of disparate findings herein point to a role of MMP9 and cICAM-1 in the patho-progressive process of BD: the increased levels of serum MMP9 and sICAM-1, the correlation between higher levels of these parameters, progressive stage, and cognitive dysfunction in BD, and the positive correlation with subthreshold symptoms. As sICAM-1 and MMP9 are reliable biomarkers of inflammatory and early atherosclerotic disease, these markers may provide indications of the presence of occult cardiovascular disease in this highly at-risk population.

The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research.

Introduction: Treatment of severe mental illness (SMI) symptoms, especially negative symptoms and cognitive dysfunction in schizophrenia, remains a major unmet need. There is good evidence that SMIs have a strong genetic background and are characterized by multiple biological alterations, including disturbed brain circuits and connectivity, dysregulated neuronal excitation-inhibition, disturbed dopaminergic and glutamatergic pathways, and partially dysregulated inflammatory processes. The ways in which the dysregulated signaling pathways are interconnected remains largely unknown, in part because well-characterized clinical studies on comprehensive biomaterial are lacking. Furthermore, the development of drugs to treat SMIs such as schizophrenia is limited by the use of operationalized symptom-based clusters for diagnosis. Methods: In line with the Research Domain Criteria initiative, the Clinical Deep Phenotyping (CDP) study is using a multimodal approach to reveal the neurobiological underpinnings of clinically relevant schizophrenia subgroups by performing broad transdiagnostic clinical characterization with standardized neurocognitive assessments, multimodal neuroimaging, electrophysiological assessments, retinal investigations, and omics-based analyzes of blood and cerebrospinal fluid. Moreover, to bridge the translational gap in biological psychiatry the study includes in vitro investigations on human-induced pluripotent stem cells, which are available from a subset of participants. Results: Here, we report on the feasibility of this multimodal approach, which has been successfully initiated in the first participants in the CDP cohort; to date, the cohort comprises over 194 individuals with SMI and 187 age and gender matched healthy controls. In addition, we describe the applied research modalities and study objectives. Discussion: The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive dysfunction, and treatment-resistant symptoms in general are still difficult to treat.