Quantitative proteomic analysis of human plasma using tandem mass tags to identify novel biomarkers for herpes zoster

Molecular Study of Varicella zoster virus in Cerebrospinal Fluid from Stroke Patients of Thi-Qar province

INTRODUCTION

Varicella zoster virus (VZV) is a type of alpha-herpesvirus that specifically targets the nervous system. The initial infection, typically occurring during childhood, results in varicella (commonly known as chickenpox), after which the virus enters a dormant state in cranial nerve ganglia, dorsal root ganglia, and autonomic ganglia throughout the entire neuroaxis.

AIM OF THE STUDY

Molecular and genetic studies of viruses are an important tool for virus development and identifying viral treatments to combat the diseases. The aim of the study was to determine the whole ORF4 sequence of the local VZV strains for phylogenetic analysis to determine the variability in the viral sequence.

MATERIAL AND METHODS

Ten samples of VZV DNA were subjected to the sequencing of the whole ORF4 region following identification using the PCR method.

RESULTS

Sequences from five samples have been successfully analyzed. All clinical strains were discovered to possess a genome with a length of 124,884 base pairs. The sequences exhibited the occurrence of two distinct mutations, one being a transversion and the other a transition, with the latter resulting in an alteration of the amino acid. A phylogenetic tree was constructed using the maximum likelihood method based on the sequences of five nucleotide sequences from clinical samples and nine reference VZV strains. The tree displayed the evolutionary distances between these sequences. The analysis of the phylogenetic tree revealed the presence of five primary clades, with four of them originating from India (isolates S1, S2, S4, S5), while S3 exhibited similarity to a strain from the United Kingdom.

Identification of potential biomarkers for neuromyelitis optica by quantitative proteomics

OBJECTIVE

Neuromyelitis optica (NMO) was a serious autoimmune inflammatory condition affecting the central nervous system. Currently, there was a lack of diagnostic biomarkers for AQP4-IgG-negative NMO patients.

METHODS

A comparative proteomic analysis was conducted on the CSF of 10 patients with NMO and 10 patients with non-inflammatory neurological disorders (NND) using tandem mass tagging technology. Differentially expressed proteins (DEPs) were analyzed using bioinformatic methods. The candidate proteins were then validated through ELISAs in a subsequent cohort of 160 samples, consisting of paired CSF and plasma samples from 50 NMO patients, CSF samples from 30 NND patients, and plasma samples from 30 healthy individuals.

RESULTS

We identified 389 proteins via proteomics, screening 79 DEPs. NCAM1, SST and AHSG were selected as candidate molecules for further validation. Compared to NND patients, there were decreased levels of AHSG in CSF and increased levels of NCAM1 and SST in NMO patients. The ELISA results revealed significantly higher levels of AHSG, SST and NCAM1 in the CSF of the NMO group compared to the NND group. Similarly, the serum levels of these three proteins were also higher in the NMO group compared to the healthy control group. It was found that serum NCAM1 levels significantly decreased in patients with non-relapsed NMO compared to patients with relapsed NMO and CSF NCAM1 level increased in patients with bilateral NMO compared to patients with unilateral NMO. Furthermore, CSF SST levels increased in AQP4 antibody-positive NMO patients compared to AQP4 antibody-negative patients.

INTERPRETATION

CSF NCAM1, serum NCAM1 and serum SST may serve as potential biomarkers for NMO patients and aid in the diagnosis of AQP4 antibody-negative NMO patients.

Cerebrospinal Fluid Proteomic Profiles in Patients with Postherpetic Neuralgia

The intrinsic mechanism of postherpetic neuralgia (PHN) remains unclear. Herein, we aimed to seek the hub proteins in the cerebrospinal fluid (CSF), which display significant changes between the PHN and nonpainful patients (Control). First, the proteomic results showed that compared with the Control-CSF, there were 100 upregulated and 50 downregulated differentially expressed proteins (DEPs) in the PHN-CSF. Besides, functional analyses including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) revealed that biological processes and pathways including complement activation, infection, coagulation, and lipid metabolism were activated, while synaptic organization was suppressed. Next, the protein-protein interaction (PPI) analysis indicated that increased PLG, F2, APOA1, APOA2, SERPINC1, and KNG1 and reduced APOE, which were all enriched in the top pathways according to the KEGG analysis, were defined as hub proteins. Finally, three of the hub proteins, such as PLG, APOA1, and APOE, were reconfirmed in a larger cohort using both enzyme-linked immunosorbent assay (ELISA) and Western blotting methods. Above all, the results indicated that PLG, APOA1, and APOE and their involved processes such as infection, inflammation, cholesterol metabolism, and coagulation shall be potential therapeutic approaches. (The raw mass spectrometry proteome data and search results have been deposited to the iProx-integrated Proteome Resources (http://www.iprox.cn) with the data set identifier IPX0007372000.).

Early Diagnosis of Herpes Zoster Neuralgia: A Narrative Review

BACKGROUND

Early intervention reduces the incidence of postherpetic neuralgia (PHN). Typical shingles are easy to diagnose; however, there is no clear diagnostic method for neuralgia symptoms manifested before the onset of the rash, which can easily cause misdiagnosis. This not only increases the patient's pain, medical expenses, and mental burden, but more importantly, delays the valuable time for early treatment of shingles, and increases the probability of complications and PHN.

OBJECTIVE

In this paper, the diagnostic methods of preherpetic neuralgia were summarized and analyzed, and the current challenges were put forward to provide directions for the early diagnosis of herpes zoster (HZ) in the future.

METHODS

PubMed, and China National Knowledge Infrastructure (CNKI) libraries were searched using the terms "herpes zoster," "before the blistering," "diagnosis," and "neuralgia." Clinical trials, reviews, and case reports were collected and reviewed. The period of literature search is from 1 January 1980 to 1 October 2022.

RESULTS

The early diagnosis of herpes zoster neuralgia can reduce misdiagnosis and mistreatment, and timely and effective intervention can significantly reduce the incidence of PHN. The body may possess a mechanism that limits the local breakthrough of the virus in the skin, causing blistering later than the onset of pain. Changes in the plasma proteins of patients with varicella-zoster virus shingles neuralgia may be used as an early diagnostic indicator in patients with HZ neuralgia before eruption.

CONCLUSION

Early diagnosis of HZ neuralgia before eruption can facilitate timely targeted treatment, thereby reducing the incidence of PHN. Proteomic quantitative analysis and validation results can serve as a simple, micro, rapid, and accurate diagnostic method.

Characterization of plasma metabolites and proteins in patients with herpetic neuralgia and development of machine learning predictive models based on metabolomic profiling

Herpes zoster (HZ) is a localized, painful cutaneous eruption that occurs upon reactivation of the herpes virus. Postherpetic neuralgia (PHN) is the most common chronic complication of HZ. In this study, we examined the metabolomic and proteomic signatures of disease progression in patients with HZ and PHN. We identified differentially expressed metabolites (DEMs), differentially expressed proteins (DEPs), and key signaling pathways that transition from healthy volunteers to the acute or/and chronic phases of herpetic neuralgia. Moreover, some specific metabolites correlated with pain scores, disease duration, age, and pain in sex dimorphism. In addition, we developed and validated three optimal predictive models (AUC > 0.9) for classifying HZ and PHN from healthy individuals based on metabolic patterns and machine learning. These findings may reveal the overall metabolomics and proteomics landscapes and proposed the optimal machine learning predictive models, which provide insights into the mechanisms of HZ and PHN.

Using plasma proteomics to investigate viral infections of the central nervous system including patients with HIV-associated neurocognitive disorders

State-of-the-art liquid chromatography/mass spectrometry (LC/MS)-based proteomic technologies, using microliter amounts of patient plasma, can detect and quantify several hundred plasma proteins in a high throughput fashion, allowing for the discovery of clinically relevant protein biomarkers and insights into the underlying pathobiological processes. Using such an in-house developed high throughput plasma proteomics allowed us to identify and quantify > 400 plasmas proteins in 15 min per sample, i.e., a throughput of 100 samples/day. We demonstrated the clinical applicability of our method in this pilot study by mapping the plasma proteomes from patients infected with human immunodeficiency virus (HIV) or herpes virus, both groups with involvement of the central nervous system (CNS). We found significant disease-specific differences in the plasma proteomes. The most notable difference was a decrease in the levels of several coagulation-associated proteins in HIV vs. herpes virus, among other dysregulated biological pathways providing insight into the differential pathophysiology of HIV compared to herpes virus infection. In a subsequent analysis, we found several plasma proteins associated with immunity and metabolism to differentiate patients with HIV-associated neurocognitive disorders (HAND) compared to cognitively normal people with HIV (PWH), suggesting the presence of plasma-based biomarkers to distinguishing HAND from cognitively normal PWH. Overall, our high-throughput plasma proteomics pipeline enables the identification of distinct proteomic signatures of HIV and herpes virus, which may help illuminate divergent pathophysiology behind virus-associated neurological disorders.

Plasma Proteomics Characteristics of Subclinical Vitamin E Deficiency of Dairy Cows During Early Lactation

Vitamin E (VE) is an essential fat-soluble nutrient for dairy cows. Vitamin E deficiency leads to immune suppression and oxidative stress and increases the susceptibility of cows to reproductive disorders in the early post-partum period. However, studies on plasma proteomics of VE deficiency have not been reported so far. Therefore, the purpose of this study was to understand the changes of blood protein profile in cows with subclinical VE deficiency in the early post-partum period. In this study, plasma protein levels of 14 healthy cows (>4 μg/ml α-tocopherol) and 13 subclinical VE-deficient cows (2–3 μg/ml α-tocopherol) were analyzed by tandem mass tag (TMT). The results showed that there were 26 differentially expressed proteins (DEPs) in the plasma of cows with subclinical VE deficiency compared with healthy controls. Twenty-one kinds of proteins were downregulated, and five kinds were upregulated, among which eight proteins in protein–protein interactions (PPI) network had direct interaction. These proteins are mainly involved in the MAPK signaling pathway, pantothenic acid and coenzyme A (CoA) biosynthesis, PPAR signaling pathway, and glycosylphosphatidylinositol (GPI)-anchor biosynthesis. The top four DEPs in PPI (APOC3, APOC4, SAA4, PHLD) and one important protein (VNN1) by literature review were further verified by ELISA and Western blot. The expression levels of APOC3, VNN1, and SAA4 were significantly lower than those of healthy controls by ELISA. VNN1 was significantly lower than those of healthy controls by Western blot. VNN1 is closely related to dairy cow subclinical VE deficiency and can be a potential biomarker. It lays a foundation for further research on the lack of pathological mechanism and antioxidative stress of VE.

Potential biomarkers identified by tandem mass tags based quantitative proteomics for diagnosis and classification of Guillain-Barré syndrome

BACKGROUND AND PURPOSE

Guillain-Barré syndrome (GBS) is an acute inflammatory autoimmune and demyelinating disease of the peripheral nervous system. Currently, valid biomarkers are unavailable for the diagnosis of GBS.

METHODS

A comparative proteomics analysis was performed on the cerebrospinal fluid (CSF) from 10 patients with GBS and 10 patients with noninflammatory neurological disease (NND) using the tandem mass tags technique. The differentially expressed proteins were analyzed by bioinformatics, and then the candidate proteins were validated by the enzyme-linked immunosorbent assay method in another cohort containing 160 samples (paired CSF and plasma of 40 patients with GBS, CSF of 40 NND patients and plasma of 40 healthy individuals).

RESULTS

In all, 298 proteins were successfully identified in the CSF samples, of which 97 differentially expressed proteins were identified in the GBS and NND groups. Three key molecules were identified as candidate molecules for further validation. The CSF levels of TGOLN2 and NCAM1 decreased in GBS patients compared with NND patients, whereas the CSF levels of APOC3 increased. The enzyme-linked immunosorbent assay results were consistent with our proteomics analysis. Interestingly, in the validation cohort, serum APOC3 levels in the GBS group were consistent with those in the CSF samples and significantly higher than those in the healthy control group.

CONCLUSIONS

Our preliminary data suggest that the CSF protein expression profile of patients with GBS is different from that of patients with NND. Moreover, alterations of TGOLN2, NCAM1and APOC3 may be used as novel biomarkers for identifying patients with GBS.

Spleen proteome profiling of dairy goats infected with C. pseudotuberculosis by TMT-based quantitative proteomics approach

Corynebacterium pseudotuberculosis (C.pseudotuberculosis) is a zoonotic pathogen that can cause cheese lymphadenitis in goats. In order to obtain detailed information about the pathogenesis and host immune response of goats infected with C.pseudotuberculosis, we used tandem mass tag (TMT)-labeling proteomic analysis to detect differentially expressed proteins (DEPs) in dairy goats infected with C.pseudotuberculosis, and confirmed the altered proteins with western blot. A total of 6611 trusted proteins were identified, and 126 proteins were differentially abundant. Gene ontology (GO) analysis showed that all DEPs were annotated as biological processes, cell composition, and molecular functions. Biological processes mainly involve acute inflammation and immune response; cell components mainly involve extracellular areas and high-density lipoprotein particles; molecular functions are mainly antigen binding, ferric iron binding, and iron ion binding. KEGG analysis showed that a total of 102 pathways were significantly enriched, mainly lysosomes, phagosomes, and mineral absorption pathways. Our findings provided the relevant knowledge of spleen protein levels in goats infected with C.pseudotuberculosis and revealed the complex molecular pathways and immune response mechanisms in the process of C.pseudotuberculosis infection. SIGNIFICANCE: C.pseudotuberculosis is the most fatal infectious disease in dairy goats, causing huge economic losses. However, the molecular pathways and immune response mechanisms of C.pseudotuberculosis infection in goats remain unclear. Therefore, we conducted a comparative quantitative proteomics study on dairy goats infected with C.pseudotuberculosis. The results provide a basis for better understanding the complexity of C.pseudotuberculosis infection, reveal the complex molecular pathways and immune response mechanisms in C.pseudotuberculosis infection, and provide some clues for identifying potential therapeutic targets. This is the first report to show that C.pseudotuberculosis infection in dairy goats can disrupt the immune response mechanism and lead to massive immune cell death. The study provided new findings on the interaction between C.pseudotuberculosis and the host.

Circulating Level of Myelin Basic Protein Predicts Postherpetic Neuralgia: A Prospective Study

OBJECTIVES

Patients with herpes zoster (HZ) would benefit from accurate prediction of whether they are likely to develop postherpetic neuralgia (PHN). We investigated whether a circulating biomarker of neuronal damage could be a predictor of PHN in this nonmatched prospective, nested, case-control study.

MATERIALS AND METHODS

We included patients with HZ who were within 90 days after rash onset. Volunteers without a history of HZ were recruited as controls. We evaluated epidemiologic factors and circulating neuronal damage biomarkers, including cell-free DNA, myelin basic protein (MBP), and soluble protein-100B (S100B). We conducted logistic regression analyses to develop a prediction model of PHN.

RESULTS

We found that cell-free DNA and MBP levels were higher in patients with HZ (n=71) than in controls (n=37). However, only MBP level was higher in patients who developed PHN (n=25), in comparison with those who did not (n=46). MBP level and 3 clinical factors, age, acute pain severity, and response to treatment drugs were identified as independent predictors of PHN. Receiver operating characteristic (ROC) curve analysis showed that the prediction made using a combination of MBP level and clinical factors had an area under ROC curve of 0.853 (95% confidence interval: 0.764 to 0.943), which was better than prediction using clinical factors alone (area under ROC curve: 0.823, 95% confidence interval: 0.728 to 0.917).

DISCUSSION

Our results indicate that circulating MBP level in patients with HZ is a predictor for PHN. The combination of clinical predictors and MBP level enhanced the prediction performance.

Identification of Proteomic Signatures in Chronic Obstructive Pulmonary Disease Emphysematous Phenotype

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease. Emphysematous phenotype is the most common and critical phenotype, which is characterized by progressive lung destruction and poor prognosis. However, the underlying mechanism of this structural damage has not been completely elucidated. A total of 12 patients with COPD emphysematous phenotype (COPD-E) and nine patients with COPD non-emphysematous phenotype (COPD-NE) were enrolled to determine differences in differential abundant protein (DAP) expression between both groups. Quantitative tandem mass tag–based proteomics was performed on lung tissue samples of all patients. A total of 29 and 15 lung tissue samples from patients in COPD-E and COPD-NE groups, respectively, were used as the validation cohort to verify the proteomic analysis results using western blotting. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted for DAPs. A total of 4,343 proteins were identified, of which 25 were upregulated and 11 were downregulated in the COPD-E group. GO and KEGG analyses showed that wound repair and retinol metabolism–related pathways play an essential role in the molecular mechanism of COPD emphysematous phenotype. Three proteins, namely, KRT17, DHRS9, and FMO3, were selected for validation. While KRT17 and DHRS9 were highly expressed in the lung tissue samples of the COPD-E group, FMO3 expression was not significantly different between both groups. In conclusion, KRT17 and DHRS9 are highly expressed in the lung tissue of patients with COPD emphysematous phenotype. Therefore, these proteins might involve in wound healing and retinol metabolism in patients with emphysematous phenotype and can be used as phenotype-specific markers.

Why Inclusion Matters for Alzheimer's Disease Biomarker Discovery in Plasma

BACKGROUND

African American/Black adults have a disproportionate incidence of Alzheimer's disease (AD) and are underrepresented in biomarker discovery efforts.

OBJECTIVE

This study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults.

METHODS

We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates.

RESULTS

In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD.

CONCLUSION

These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.