Altered apolipoprotein C expression in association with cognition impairments and hippocampus volume in schizophrenia and bipolar disorder

APOE Genotype, ApoE Plasma Levels, Lipid Metabolism, and Cognition in Monozygotic Twins with, at Risk of, and without Affective Disorders

Background: Lipids influence brain function and mental health. Understanding the role of apolipoproteins in affective disorders could provide valuable insights and potentially pave the way for novel therapeutic approaches. Methods: We examined the apolipoprotein E genotype and ApoE-levels, lipid profiles, and the correlation with cognition in 204 monozygotic (MZ) twins with unipolar or bipolar disorder in remission or partial remission (affected, AT), their unaffected co-twins (high-risk, HR), and twins with no personal or family history of affective disorder (low-risk, LR). Results: The APOE genotype was not associated with affective disorders. No significant group differences in ApoE levels were found between the three risk groups. Post hoc analysis group-wise comparisons showed higher ApoE levels in the AT than HR twins and in the concordant AT twin pairs relative to the discordant twin pairs. Within the discordant twin pairs, higher ApoE levels were observed in the affected twins (AT = 39.4 mg/L vs. HR = 36.8 mg/L, p = 0.037). Limitations: The present study could benefit from a larger sample size. We did not assess dietary habits. Conclusions: The results did not support our main hypothesis. However, exploratory post hoc analysis suggests a role for plasma ApoE and triglycerides in affective disorders. Future research is needed.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

Apolipoprotein D as a Potential Biomarker in Neuropsychiatric Disorders

Neuropsychiatric disorders (NDs) are a diverse group of pathologies, including schizophrenia or bipolar disorders, that directly affect the mental and physical health of those who suffer from them, with an incidence that is increasing worldwide. Most NDs result from a complex interaction of multiple genes and environmental factors such as stress or traumatic events, including the recent Coronavirus Disease (COVID-19) pandemic. In addition to diverse clinical presentations, these diseases are heterogeneous in their pathogenesis, brain regions affected, and clinical symptoms, making diagnosis difficult. Therefore, finding new biomarkers is essential for the detection, prognosis, response prediction, and development of new treatments for NDs. Among the most promising candidates is the apolipoprotein D (Apo D), a component of lipoproteins implicated in lipid metabolism. Evidence suggests an increase in Apo D expression in association with aging and in the presence of neuropathological processes. As a part of the cellular neuroprotective defense machinery against oxidative stress and inflammation, changes in Apo D levels have been demonstrated in neuropsychiatric conditions like schizophrenia (SZ) or bipolar disorders (BPD), not only in some brain areas but in corporal fluids, i.e., blood or serum of patients. What is not clear is whether variation in Apo D quantity could be used as an indicator to detect NDs and their progression. This review aims to provide an updated view of the clinical potential of Apo D as a possible biomarker for NDs.

Cognitive impairment in psychiatric diseases: Biomarkers of diagnosis, treatment, and prevention

Psychiatric diseases, such as schizophrenia, bipolar disorder, autism spectrum disorder, and major depressive disorder, place a huge health burden on society. Cognitive impairment is one of the core characteristics of psychiatric disorders and a vital determinant of social function and disease recurrence in patients. This review thus aims to explore the underlying molecular mechanisms of cognitive impairment in major psychiatric disorders and identify valuable biomarkers for diagnosis, treatment and prevention of patients.

Associations between BMI and brain structures involved in food intake regulation in first-episode schizophrenia spectrum disorders and healthy controls

Structural brain differences have been described in first-episode schizophrenia spectrum disorders (FES), and often overlap with those evident in the metabolic syndrome (MetS). We examined the associations between body mass index (BMI) and brain structures involved in food intake regulation in minimally treated FES patients (n = 117) compared to healthy controls (n = 117). The effects of FES diagnosis, BMI and their interactions on our selected prefrontal cortical thickness and subcortical gray matter volume regions of interest (ROIs) were investigated with hierarchical multivariate regressions, followed by post-hoc regressions for the individual ROIs. In a secondary analysis, we examined the relationships of other MetS risk factors and psychopathology with the brain ROIs. Both illness and BMI significantly predicted the grouped prefrontal cortical thickness ROIs, whereas only BMI predicted the grouped subcortical volume ROIs. For the individual ROIs, schizophrenia diagnosis predicted thinner left and right frontal pole and right lateral OFC thickness, and increased BMI predicted thinner left and right caudal ACC thickness. There were no significant main or interaction effects for diagnosis and BMI on any of the individual subcortical volume ROIs. Secondary analyses suggest associations between several brain ROIs and individual MetS risk factors, but not with psychopathology. Our findings indicate differential, independent effects for FES diagnosis and BMI on brain structures. Limited evidence suggests that the BMI effects are more prominent in FES. Exploratory analyses suggest associations between other MetS risk factors and some brain ROIs.

Systematic Review and Meta-Analysis on MS-Based Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Bipolar Disorder

Bipolar disorder (BD) is a clinically heterogeneous condition, presenting a complex underlying etiopathogenesis that is not sufficiently characterized. Without molecular biomarkers being used in the clinical environment, several large screen proteomics studies have been conducted to provide valuable molecular information. Mass spectrometry (MS)-based techniques can be a powerful tool for the identification of disease biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids to assess BD biomarkers and identify relevant networks of biological pathways. Following PRISMA guidelines, we searched for studies using MS proteomics to identify proteomic differences between BD patients and healthy controls (PROSPERO database: CRD42021264955). Fourteen articles fulfilled the inclusion criteria, allowing the identification of 266 differentially expressed proteins. Gene ontology analysis identified complement and coagulation cascades, lipid and cholesterol metabolism, and focal adhesion as the main enriched biological pathways. A meta-analysis was performed for apolipoproteins (A-I, C-III, and E); however, no significant differences were found. Although the proven ability of MS proteomics to characterize BD, there are several confounding factors contributing to the heterogeneity of the findings. In the future, we encourage the scientific community to use broader samples and validation cohorts, integrating omics with bioinformatics tools towards providing a comprehensive understanding of proteome alterations, seeking biomarkers of BD, and contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.

Childhood adversities and bipolar disorder: a neuroimaging focus

Early-life adverse events or childhood adversities (CAs) are stressors and harmful experiences severely impacting on a child's wellbeing and development. Examples of CAs include parental neglect, emotional and physical abuse and bullying. Even though the prevalence of CAs and their psychological effects in both healthy and psychiatric populations is established, only a paucity of studies have investigated the neurobiological firms associated with CAs in bipolar disorder (BD). In particular, the exact neural mechanisms and trajectories of biopsychosocial models integrating both environmental and genetic effects are still debated. Considering the potential impact of CAs on BD, including its clinical manifestations, we reviewed existing literature discussing the association between CAs and brain alterations in BD patients. Results showed that CAs are associated with volume alterations of several grey matter regions including the hippocampus, thalamus, amygdala and frontal cortex. A handful of studies suggest the presence of alterations in the corpus callosum and the pre-fronto-limbic connectivity at rest. Alterations in these regions of the brain of patients with BD are possibly due to the effect of stress produced by CAs, being hippocampus part of the hypothalamus-pituitary-adrenal axis and thalamus together with amygdala filtering sensory information and regulating emotional responses. However, results are mixed possibly due to the heterogeneity of methods and study design. Future neuroimaging studies disentangling between different types of CAs or differentiating between BD sub-types are needed in order to understand the link between CAs and BD.

Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls

BACKGROUND

Schizophrenia (SZ) and bipolar disorder (BD) share many features: overlap in mood and psychotic symptoms, common genetic predisposition, treatment with antipsychotics (APs), and similar metabolic comorbidities. The pathophysiology of both is still not well defined, and no biomarkers can be used clinically for diagnosis and management. This study aimed to assess the plasma proteomics profile of patients with SZ and BD maintained on APs compared to those who had been off APs for 6 months and to healthy controls (HCs).

METHODS

We analyzed the data using functional enrichment, random forest modeling to identify potential biomarkers, and multivariate regression for the associations with metabolic abnormalities.

RESULTS

We identified several proteins known to play roles in the differentiation of the nervous system like NTRK2, CNTN1, ROBO2, and PLXNC1, which were downregulated in AP-free SZ and BD patients but were "normalized" in those on APs. Other proteins (like NCAM1 and TNFRSF17) were "normal" in AP-free patients but downregulated in patients on APs, suggesting that these changes are related to medication's effects. We found significant enrichment of proteins involved in neuronal plasticity, mainly in SZ patients on APs. Most of the proteins associated with metabolic abnormalities were more related to APs use than having SZ or BD. The biomarkers identification showed specific and sensitive results for schizophrenia, where two proteins (PRL and MRC2) produced adequate results.

CONCLUSIONS

Our results confirmed the utility of blood samples to identify protein signatures and mechanisms involved in the pathophysiology and treatment of SZ and BD.

Decreased serum apolipoprotein A4 as a potential peripheral biomarker for patients with schizophrenia

Recent evidence supports an association between lipid metabolism dysfunction and the pathology of schizophrenia which has led to the search for peripheral blood-based biomarkers. The purpose of this study was to investigate the proteins involved in lipid metabolism (especially apolipoprotein) and to explore their potential as biomarkers for schizophrenia. Using multiple reaction monitoring mass spectrometry (MRM-MS), we quantified 22 proteins in serum samples of 109 healthy controls (HCs) and 111 patients with schizophrenia (SCZ), who were divided into discovery and validation sets. We found serum apolipoprotein A4 (ApoA4) to be significantly decreased in SCZ patients compared to HCs (p=1.61E-05). Moreover, the serum ApoA4 level served as an effective diagnostic tool, achieving area under the receiver operating characteristic curves (AUROC) of 0.840 in the discovery set and 0.791 in the validation set. Additionally, apolipoprotein F (ApoF), angiotensinogen (AGT), and alpha1-antichymotrypsin (ACT) levels were significantly higher in patients with schizophrenia than in healthy controls. These proteins combined with ApoA4, provided higher diagnostic accuracy for schizophrenia in the discovery set (AUROC=0.901) and in the validation set (AUROC=0.879). Our results suggest that the serum level of ApoA4 is a novel potential biomarker for schizophrenia. The proteins identified in this study expand the pool of biomarker candidates for schizophrenia and may be linked to the underlying mechanism of the disease.

A pilot study indicating the dysregulation of the complement and coagulation cascades in treated schizophrenia and bipolar disorder patients

A better understanding of the proteome profile after bipolar disorder (BD) and schizophrenia (SCZ) treatment, besides monitoring disease progression, may assist on the development of novel therapeutic strategies with the ability to reduce or control possible side effects. In this pilot study, proteomics analysis employing nano liquid chromatography coupled to mass spectrometry (nLC-MS) and bioinformatic tools were applied to identify differentially abundant proteins in serum of treated BD and SCZ patients. In total, 10 BD patients, 10 SCZ patients, and 14 healthy controls (HC) were included in this study. 24 serum proteins were significantly altered (p < 0.05) in BD and SCZ treated patients and, considering log₂FC > 0.58, 8 proteins presented lower abundance in the BD group, while 7 proteins presented higher abundance and 2 lower abundance in SCZ group when compared against HC. Bioinformatics analysis based on these 24 proteins indicated two main altered pathways previously described in the literature; furthermore, it revealed that opposite abundances of the complement and coagulation cascades were the most significant biological processes involved in these pathologies. Moreover, we describe disease-related proteins and pathways associations suggesting the necessity of clinical follow-up improvement besides treatment, as a precaution or safety measure, along with the disease progression. Further biological validation and investigations are required to define whether there is a correlation between complement and coagulation cascade expression for BD and SCZ and cardiovascular diseases.

Proteomics for Target Identification in Psychiatric and Neurodegenerative Disorders

Psychiatric and neurodegenerative disorders such as schizophrenia (SCZ), Parkinson's disease (PD), and Alzheimer's disease (AD) continue to grow around the world with a high impact on health, social, and economic outcomes for the patient and society. Despite efforts, the etiology and pathophysiology of these disorders remain unclear. Omics technologies have contributed to the understanding of the molecular mechanisms that underlie these complex disorders and have suggested novel potential targets for treatment and diagnostics. Here, we have highlighted the unique and common pathways shared between SCZ, PD, and AD and highlight the main proteomic findings over the last 5 years using in vitro models, postmortem brain samples, and cerebrospinal fluid (CSF) or blood of patients. These studies have identified possible therapeutic targets and disease biomarkers. Further studies including target validation, the use of large sample sizes, and the integration of omics findings with bioinformatics tools are required to provide a better comprehension of pharmacological targets.

The Discovery of Clinically Applicable Biomarkers for Bipolar Disorder: A Review of Candidate and Proteomic Approaches

Bipolar disorder (BD) is a severe psychiatric condition which affects innumerable people across the globe. The etiopathogenesis of BD is multi-faceted with genetic, environmental and psychosocial factors playing a role. Hitherto, the diagnosis and management of BD are purely on empirical grounds as we lack confirmed biomarkers for this condition. In this regard, hypothesis-driven investigations have been unable to identify clinically applicable biomarkers, steering the field towards newer technologies. Innovative, state-of-the-art techniques like multiplex immunoassays and mass spectrometry can potentially investigate the entire proteome. By detecting up or down regulated proteins, novel biomarkers are identified and new postulates about the etiopathogenesis of BD are specified. Hence, biological pathways are uncovered which are involved in the initiation and advancement of the disease and new therapeutic targets are identified. In this manuscript, the extant literature is thoroughly reviewed and the latest findings on candidate BD biomarkers are provided, followed by an overview of the proteomic approaches. It was found that due to the heterogeneous nature of BD no single biomarker is feasible, instead a panel of tests is more likely to be useful. With the application of latest technologies, it is expected that validated biomarkers will be discovered which will be useful as diagnostic tools and help in the delivery of individually tailored therapies to the patients.

Applications of multiple reaction monitoring targeted proteomics assays in human plasma

Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.

Evidence of microglial activation following exposure to serum from first-onset drug-naïve schizophrenia patients

Abnormal activation of brain microglial cells is widely implicated in the pathogenesis of schizophrenia. Previously the pathophysiology of microglial activation was considered to be intrinsic to the central nervous system. We hypothesised that due to their perivascular localization, microglia can also be activated by factors present in circulating blood. Through application of high-content functional screening, we show that peripheral blood serum from first-onset drug-naïve schizophrenia patients is sufficient to provoke microglial cell signalling network responses in vitro which are indicative of proinflammatory activation. We further explore the composition of the serum for the presence of analytes, with the potential to activate microglia, and the utility of the resultant microglial cellular phenotype for novel drug discovery.

Schizophrenia-risk and urban birth are associated with proteomic changes in neonatal dried blood spots

In the present study, we tested whether there were proteomic differences in blood between schizophrenia patients after the initial onset of the disorder and controls; and whether those differences were also present at birth among neonates who later developed schizophrenia compared to those without a psychiatric admission. We used multiple reaction monitoring mass spectrometry to quantify 77 proteins (147 peptides) in serum samples from 60 first-onset drug-naive schizophrenia patients and 77 controls, and 96 proteins (152 peptides) in 892 newborn blood-spot (NBS) samples collected between 1975 and 1985. Both serum and NBS studies showed significant alterations in protein levels. Serum results revealed that Haptoglobin and Plasma protease C1 inhibitor were significantly upregulated in first-onset schizophrenia patients (corrected P < 0.05). Alpha-2-antiplasmin, Complement C4-A and Antithrombin-III were increased in first-onset schizophrenia patients (uncorrected P-values 0.041, 0.036 and 0.013, respectively) and also increased in newborn babies who later develop schizophrenia (P-values 0.0058, 0.013 and 0.044, respectively). We also tested whether protein abundance at birth was associated with exposure to an urban environment during pregnancy and found highly significant proteomic differences at birth between urban and rural environments. The prediction model for urbanicity had excellent predictive performance in both discovery (area under the receiver operating characteristic curve (AUC) = 0.90) and validation (AUC = 0.89) sample sets. We hope that future biomarker studies based on stored NBS samples will identify prognostic disease indicators and targets for preventive measures for neurodevelopmental conditions, particularly those with onset during early childhood, such as autism spectrum disorder.

Parallel changes in serum proteins and diffusion tensor imaging in methamphetamine-associated psychosis

Methamphetamine-associated psychosis (MAP) involves widespread neurocognitive and molecular deficits, however accurate diagnosis remains challenging. Integrating relationships between biological markers, brain imaging and clinical parameters may provide an improved mechanistic understanding of MAP, that could in turn drive the development of better diagnostics and treatment approaches. We applied selected reaction monitoring (SRM)-based proteomics, profiling 43 proteins in serum previously implicated in the etiology of major psychiatric disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurements from patients diagnosed with MAP (N = 12), methamphetamine dependence without psychosis (MA; N = 14) and healthy controls (N = 16). Protein analysis identified changes in APOC2 and APOH, which differed significantly in MAP compared to MA and controls. DTI analysis indicated widespread increases in mean diffusivity and radial diffusivity delineating extensive loss of white matter integrity and axon demyelination in MAP. Upon integration, several co-linear relationships between serum proteins and DTI measures reported in healthy controls were disrupted in MA and MAP groups; these involved areas of the brain critical for memory and social emotional processing. These findings suggest that serum proteomics and DTI are sensitive measures for detecting pathophysiological changes in MAP and describe a potential diagnostic fingerprint of the disorder.

Unbiased and targeted mass spectrometry for the HDL proteome

PURPOSE OF REVIEW

Mass spectrometry is an ever evolving technology that is equipped with a variety of tools for protein research. Some lipoprotein studies, especially those pertaining to HDL biology, have been exploiting the versatility of mass spectrometry to understand HDL function through its proteome. Despite the role of mass spectrometry in advancing research as a whole, however, the technology remains obscure to those without hands on experience, but still wishing to understand it. In this review, we walk the reader through the coevolution of common mass spectrometry workflows and HDL research, starting from the basic unbiased mass spectrometry methods used to profile the HDL proteome to the most recent targeted methods that have enabled an unprecedented view of HDL metabolism.

RECENT FINDINGS

Unbiased global proteomics have demonstrated that the HDL proteome is organized into subgroups across the HDL size fractions providing further evidence that HDL functional heterogeneity is in part governed by its varying protein constituents. Parallel reaction monitoring, a novel targeted mass spectrometry method, was used to monitor the metabolism of HDL apolipoproteins in humans and revealed that apolipoproteins contained within the same HDL size fraction exhibit diverse metabolic properties.

SUMMARY

Mass spectrometry provides a variety of tools and strategies to facilitate understanding, through its proteins, the complex biology of HDL.