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

Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders

In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets.

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.

Phase-and disorder-specific differences in peripheral metabolites of the kynurenine pathway in major depression, bipolar affective disorder and schizophrenia

OBJECTIVES

Kynurenine, kynurenic and quinolinic acid are important metabolites in tryptophan metabolism. Due to an involvement in glutamatergic neurotransmission and immune response, previous studies have investigated this pathway in mental disorders such as major depressive disorder (MDD), bipolar disorder (BD) or schizophrenia (SCZ). Tryptophan and kynurenine have been shown to be decreased across disorders, hinting at the missing link how inflammation causes neurotoxicity and psychiatric symptoms. The main aim of our study was to investigate if individual catabolites could serve as diagnostic biomarkers for MDD, BD and SCZ.

METHODS

We measured plasma levels of tryptophan, kynurenine, kynurenic acid, quinolinic acid and ratio of quinolinic acid/kynurenic acid using mass spectrometry in n = 175 participants with acute episodes and after remission, compared with controls.

RESULTS

Decreased levels of all tryptophan catabolites were found in the whole patient group, driven by the difference between BD and HC. Manic and mixed phase BD individuals displayed significantly lower kynurenine and kynurenic acid levels. We could not find significant differences between disorders. Upon reaching remission, changes in catabolite levels partially normalised.

CONCLUSIONS

Our data suggests an involvement of the kynurenine pathway in mental disorders, especially BD but disqualifying those metabolites as biomarkers for differential diagnosis.

Assessing the impact of meta-genomic tools on current cutting-edge genome engineering and technology

Metagenomics is defined as the study of the genome of the total microbiota found in nature and is often referred to as microbial environmental genomics because it entails the examination of a group of genetic components (genomes) from a diverse community of organisms in a particular setting. It is a sub-branch of omics technology that encompasses Deoxyribonucleic Acid (DNA), Ribonucleic acid (DNA), proteins, and various components associated with comprehensive analysis of all aspects of biological molecules in a system-wide manner. Clustered regularly interspaced palindromic repeats and its endonuclease, CRISPR-associated protein which forms a complex called CRISPR-cas9 technology, though it is a different technique used to make precise changes to the genome of an organism, it can be used in conjunction with metagenomic approaches to give a better, rapid, and more accurate description of genomes and sequence reads. There have been ongoing improvements in sequencing that have deepened our understanding of microbial genomes forever. From the time when only a small amount of gene could be sequenced using traditional methods (e.g., "the plus and minus" method developed by Allan and Sanger and the "chemical cleavage" method that is known for its use in the sequencing the phiX174 bacteriophage genome via radio-labeled DNA polymerase-primer in a polymerization reaction aided by polyacrylamide gel) to the era of total genomes sequencing which includes "sequencing-by-ligation" and the "sequencing-by-synthesis" that detects hydrogen ions when new DNA is synthesized (Second Generation) and then Next Generation Sequencing technologies (NGS). With these technologies, the Human Genome Project (HGP) was made possible. The study looks at recent advancements in metagenomics in plants and animals by examining findings from randomly selected research papers. All selected case studies examined the functional and taxonomical analysis of different microbial communities using high-throughput sequencing to generate different sequence reads. In animals, five studies indicated how Zebrafish, Livestock, Poultry, cattle, niches, and the human microbiome were exploited using environmental samples, such as soil and water, to identify microbial communities and their functions. It has also been used to study the microbiome of humans and other organisms, including gut microbiomes. Recent studies demonstrated how these technologies have allowed for faster and more accurate identification of pathogens, leading to improved disease diagnostics. They have also enabled the development of personalized medicine by allowing for the identification of genetic variations that can impact drug efficacy and toxicity. Continued advancements in sequencing techniques and the refinement of CRISPR-Cas9 tools offer even greater potential for transformative breakthroughs in scientific research and applications. On the other hand, metagenomic data are always large and uneasy to handle. The complexity of taxonomical profiling, functional annotation, and mechanisms of complex interaction still needs better bioinformatics tools. Current review focuses on better (e.g., AI-driven algorithms) tools that can predict metabolic pathways and interactions, and manipulate complex data to address potential bias for accurate interpretation.

The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia

The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries.

Validation and reliability test of Chinese language patient-reported impact of symptoms in schizophrenia scale

Background

Patient-reported outcomes, or subjective evaluations directly reflecting the patient's views, feelings, and judgments, are now being used to evaluate the outcomes of care and treatment of people with schizophrenia. In this study, we used an updated tool, the patient-reported impact of symptoms in schizophrenia scale (PRISS), translated into Chinese languages to assess the subjective experiences of schizophrenia patients.

Objective

This study aimed to test the psychometrics of the Chinese languages PRISS (CL-PRISS).

Method

This study used the Chinese version of PRISS (CL-PRISS), acquired from the harmonized English-language version. A total of 280 patients enrolled in this study were asked to complete the CL-PRISS, the positive and negative syndrome scale (PANSS), and the World Health Organization Disability Assessment Schedule (WHO-DAS). Construct and concurrent validity was tested using the confirmatory factor analysis (CFA) and Spearman correlation coefficient, respectively. The reliability of CL-PRISS was tested using Cronbach's α coefficient and the internal correlation coefficient.

Results

Confirmatory factor analysis (CFA) analysis demonstrated three major factors in CL_PRISS: the first factor is productive experiences, the second factor is affective-negative, and the third factor experiences. The factor loadings between items and factors ranged from 0.436 to 0.899 (RMSEA = 0.029, TLI = 0.940, CFI = 0.921). The correlation coefficient between the CL_PRISS and PANSS was 0.845, and between the CL-PRISS and WHO-DAS was 0.886. The ICC of the total CL_PRISS was 0.913, and Cronbach's α was 0.903.

Conclusion

The Chinese version of the PRISS (CL_PRISS) can be effectively used for assessing the subjective experience of Chinese patients with schizophrenia.

Mass Spectrometry based identification of site-specific proteomic alterations and potential pathways underlying the pathophysiology of schizophrenia

BACKGROUND

Schizophrenia (SZ) is a complex multifactorial disorder that affects 1% of the population worldwide with no available effective treatment. Although proteomic alterations are reported in SZ however proteomic expression aberrations among different brain regions are not fully determined. Therefore, the present study aimed spatial differential protein expression profiling of three distinct regions of SZ brain and identification of associated affected biological pathways in SZ progression.

METHODS AND RESULTS

Comparative protein expression profiling of three distinct autopsied human brain regions (i.e., substantia nigra, hippocampus and prefrontal cortex) of SZ was performed with respective healthy controls. Using two-dimensional electrophoresis (2DE)-based nano liquid chromatography tandem mass spectrometry (Nano-LC MS /MS) analysis, 1443 proteins were identified out of which 58 connote to be significantly dysregulated, representing 26 of substantia nigra,14 of hippocampus and 18 of prefrontal cortex. The 58 differentially expressed proteins were further analyzed using Ingenuity pathway analysis (IPA). The IPA analysis provided protein-protein interaction networks of several proteins including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kb), extracellular signal regulated kinases 1/2 (ERK1/2), alpha serine / Threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53) and amyloid precursor protein (APP), holding prime positions in networks and interacts with most of the identified proteins and their closely interacting partners.

CONCLUSION

These findings provide conceptual insights of novel SZ related pathways and the cross talk of co and contra regulated proteins. This spatial proteomic analysis will further broaden the conceptual framework for schizophrenia research in future.

Proteomics as a tool to decipher plant responses in arbuscular mycorrhizal interactions: a meta-analysis

The beneficial symbiosis between plants and arbuscular mycorrhizal (AM) fungi leads to a deep reprogramming of plant metabolism, involving the regulation of several molecular mechanisms, many of which are poorly characterized. In this regard, proteomics is a powerful tool to explore changes related to plant-microbe interactions. This study provides a comprehensive proteomic meta-analysis conducted on AM-modulated proteins at local (roots) and systemic (shoots/leaves) level. The analysis was implemented by an in-depth study of root membrane-associated proteins and by a comparison with a transcriptome meta-analysis. A total of 4262 differentially abundant proteins were retrieved and, to identify the most relevant AM-regulated processes, a range of bioinformatic studies were conducted, including functional enrichment and protein-protein interaction network analysis. In addition to several protein transporters which are present in higher amounts in AM plants, and which are expected due to the well-known enhancement of AM-induced mineral uptake, our analysis revealed some novel traits. We detected a massive systemic reprogramming of translation with a central role played by the ribosomal translational apparatus. On one hand, these new protein-synthesis efforts well support the root cellular re-organization required by the fungal penetration, and on the other they have a systemic impact on primary metabolism.

Biological hypotheses, risk factors, and biomarkers of schizophrenia

Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.

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.