Cross-sectional proteomic expression in Parkinson's disease-related proteins in drug-naïve patients vs healthy controls with longitudinal clinical follow-up

Plasmodium knowlesi infection is associated with elevated circulating biomarkers of brain injury and endothelial activation

Introduction

Malaria remains a major public health concern with substantial morbidity and mortality worldwide. In Malaysia, the emergence of Plasmodium knowlesi has led to a surge in zoonotic malaria cases and deaths in recent years. Signs of cerebral involvement have been observed in a non-comatose, fatal case of severe knowlesi infection, but the potential impact of this malaria species on the brain remains underexplored. To address this gap, we investigated circulating levels of brain injury, inflammation, and vascular biomarkers in a cohort of knowlesi-infected patients and controls.

Methods

Archived plasma samples from 19 patients with confirmed symptomatic knowlesi infection and 19 healthy, age-matched controls from Peninsular Malaysia were analysed. A total of 52 plasma biomarkers of brain injury, inflammation, and vascular activation were measured using Luminex and SIMOA assays. Wilcoxon tests were used to examine group differences, and biomarker profiles were explored through hierarchical clustering heatmap analysis.

Results

Bonferroni-corrected analyses revealed significantly elevated brain injury biomarker levels in knowlesi-infected patients, including S100B (p<0.0001), Tau (p=0.0007), UCH-L1 (p<0.0001), αSyn (p<0.0001), Park7 (p=0.0006), NRGN (p=0.0022), and TDP-43 (p=0.005). Compared to controls, levels were lower in the infected group for BDNF (p<0.0001), CaBD (p<0.0001), CNTN1 (p<0.0001), NCAM-1 (p<0.0001), GFAP (p=0.0013), and KLK6 (p=0.0126). Hierarchical clustering revealed distinct group profiles for circulating levels of brain injury and vascular activation biomarkers.

Conclusions

Our findings highlight for the first time the impact of Plasmodium knowlesi infection on the brain, with distinct alterations in cerebral injury and endothelial activation biomarker profiles compared to healthy controls. Further studies are warranted to investigate the pathophysiology and clinical significance of these altered surrogate markers, through both neuroimaging and long-term neurocognitive assessments.

Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images

Knowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, several studies have been conducted to analyze protein expression in mouse brains. However, labeling protein expression using biotechnology is costly and time-consuming. Therefore, automated models that can accurately recognize protein expression are needed. Here, we constructed machine learning models to automatically annotate the protein expression intensity and cellular location in different mouse brain regions from immunofluorescence images. The brain regions and sub-regions were segmented through learning image features using an autoencoder and then performing K-means clustering and registration to align with the anatomical references. The protein expression intensities for those segmented structures were computed on the basis of the statistics of the image pixels, and patch-based weakly supervised methods and multi-instance learning were used to classify the cellular locations. Results demonstrated that the models achieved high accuracy in the expression intensity estimation, and the F1 score of the cellular location prediction was 74.5%. This work established an automated pipeline for analyzing mouse brain images and provided a foundation for further study of protein expression and functions.

A top-down proteomic approach reveals a salivary protein profile able to classify Parkinson's disease with respect to Alzheimer's disease patients and to healthy controls

Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin β4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin β4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.

Inflammatory Blood Biomarkers Are Associated with Long-Term Clinical Disease Severity in Parkinson's Disease

An altered immune response has been identified as a pathophysiological factor in Parkinson's disease (PD). We aimed to identify blood immunity-associated proteins that discriminate PD from controls and that are associated with long-term disease severity in PD patients. Immune response-derived proteins in blood plasma were measured using Proximity Extension Technology by OLINK in a cohort of PD patients (N = 66) and age-matched healthy controls (N = 52). In a selection of 30 PD patients, we evaluated changes in protein levels 7-10 years after the baseline and assessed correlations with motor and cognitive assessments. Data from the Parkinson's Disease Biomarkers Program (PDBP) cohort and the Parkinson's Progression Markers Initiative (PPMI) cohort were used for independent validation. PD patients showed an altered immune response compared to controls based on a panel of four proteins (IL-12B, OPG, CXCL11, and CSF-1). The expression levels of five inflammation-associated proteins (CCL23, CCL25, TNFRSF9, TGF-alpha, and VEGFA) increased over time in PD and were partially associated with more severe motor and cognitive symptoms at follow-up. Increased CCL23 levels were associated with cognitive decline and the APOE4 genotype. Our findings provide further evidence for an altered immune response in PD that is associated with disease severity in PD over a long period of time.

The Role of IgLON Cell Adhesion Molecules in Neurodegenerative Diseases

In the brain, cell adhesion molecules (CAMs) are critical for neurite outgrowth, axonal fasciculation, neuronal survival and migration, and synapse formation and maintenance. Among CAMs, the IgLON family comprises five members: Opioid Binding Protein/Cell Adhesion Molecule Like (OPCML or OBCAM), Limbic System Associated Membrane Protein (LSAMP), neurotrimin (NTM), Neuronal Growth Regulator 1 (NEGR1), and IgLON5. IgLONs exhibit three N-terminal C2 immunoglobulin domains; several glycosylation sites; and a glycosylphosphatidylinositol anchoring to the membrane. Interactions as homo- or heterodimers in cis and in trans, as well as binding to other molecules, appear critical for their functions. Shedding by metalloproteases generates soluble factors interacting with cellular receptors and activating signal transduction. The aim of this review was to analyse the available data implicating a role for IgLONs in neuropsychiatric disorders. Starting from the identification of a pathological role for antibodies against IgLON5 in an autoimmune neurodegenerative disease with a poorly understood mechanism of action, accumulating evidence links IgLONs to neuropsychiatric disorders, albeit with still undefined mechanisms which will require future thorough investigations.

The application of Aptamer in biomarker discovery

Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.