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Research in Veterinary Science Mar 2022Proteomic analysis is having a rapid development as a method for the detection of biomarkers of diseases in dogs. Dogs in addition to their importance as companion...
Proteomic analysis is having a rapid development as a method for the detection of biomarkers of diseases in dogs. Dogs in addition to their importance as companion animals, serve as important animal models for research. This study aims to systematically review evidence regarding the studies performed in proteomics in dogs, and specifically those made in serum, saliva, urine and/or plasma. Information searched in October 2020, January 2021 and August 2021, for English language publications of the last decade (2010-2020) were obtained from electronic databases. Screening, data extraction and risk of bias assessment were undertaken by two investigators. The risk of bias was evaluated using the Review Manager (RevMan 5) tool. Meta-analysis and case report studies were not included in this review. Through the screening process a total of 557 publications were identified after the removal of duplicates. Out of these, 65 were fully evaluated and 44 of these were included in the review. Most studies evaluated the proteome of disease and compared it with a healthy population, and most of the articles included were made on serum, followed by saliva. The overall risk of bias for all studies was high, due to an absence in the generation of random sequence. Overall proteomic analysis has allowed the discovery of new physiopathological pathways of diseases and potential biomarkers in the dog, which are addressed in this review.
Topics: Animals; Biomarkers; Databases, Factual; Dogs; Proteome; Proteomics; Saliva
PubMed: 35007798
DOI: 10.1016/j.rvsc.2021.12.026 -
Frontiers in Endocrinology 2023Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity....
INTRODUCTION
Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.
METHODS
We applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022.
RESULTS
135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies).
CONCLUSION
Artificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.
Topics: Female; Humans; Artificial Intelligence; Polycystic Ovary Syndrome; Proteomics; Machine Learning; Cluster Analysis
PubMed: 37790605
DOI: 10.3389/fendo.2023.1106625 -
Journal of Diabetes and Metabolic... Jun 2022Due to growing concerns about the obesity pandemic as a worldwide phenomenon, a global effort has been made for managing it and associated disorders. Accordingly,... (Review)
Review
PURPOSE
Due to growing concerns about the obesity pandemic as a worldwide phenomenon, a global effort has been made for managing it and associated disorders. Accordingly, metabolomics as a promising field of "OMICS" is presented for investigating different molecular pathways in obesity and related disorders through the evaluation of specific metabolites in both animal and human subjects. Herein, the aim of the present study as the first systematic review is to evaluate all available studies about different mechanisms and their biomarkers discovery using metabolomics approaches.
METHOD
The study was designed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Using a comprehensive search strategy we searched in databases including; Web of Science, PubMed, and Scopus using specific keywords. Based on predefined inclusion/exclusion criteria study selection has been conducted considering the type of studies, participant, and outcome measures. Quality assessment was done using CASP (Critical Appraisal Skills Programme) checklist followed by data extraction according to a predefined data extraction sheet.
RESULTS
Among the articles that resulted from electronic search, a total of 74 articles met our inclusion criteria. The most prevalent studied metabolites were amino acids and lipid derivatives and both targeted and non-targeted approaches were applied for metabolomics studies.
CONCLUSION
This systematic review summarized a wide range of studies regardless of the age, history, language, and type of the study. Further studies are needed to compare the application of emerging methods in the treatment of obesity and related disorders.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s40200-021-00917-w.
PubMed: 35673462
DOI: 10.1007/s40200-021-00917-w -
Molecular & Cellular Proteomics : MCP Aug 2023Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of...
Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology.
Topics: Humans; Cartilage, Articular; Knee Joint; Osteoarthritis, Knee
PubMed: 37356495
DOI: 10.1016/j.mcpro.2023.100606 -
Nature Communications Sep 2023COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be... (Meta-Analysis)
Meta-Analysis
COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.
Topics: Humans; COVID-19; Proteome; Proteomics; SARS-CoV-2; Cytoplasm
PubMed: 37739942
DOI: 10.1038/s41467-023-41159-z -
Frontiers in Oral Health 2023Some salivary proteins seem to be differently abundant among caries-free (CF) and caries-affected (CA) individuals, but previous results are contradictory precluding... (Review)
Review
OBJECTIVE
Some salivary proteins seem to be differently abundant among caries-free (CF) and caries-affected (CA) individuals, but previous results are contradictory precluding that definitive conclusion be drawn. A pooled analysis of the available evidence may provide more robust data on identifying oral cavity protein patterns among CF and CA individuals. This systematic review and meta-analysis (PROSPERO CRD42021269079) aimed to compare the oral cavity protein abundance among caries-free and caries-affected individuals.
METHODS
This study was conducted following PRISMA guidelines. PubMed, Embase, and Web of Science databases were systematically assessed (up to February 2023) to retrieve clinical studies written in English, German, or in Latin-based languages that compared the oral cavity protein abundance among CF and CA individuals. Data extraction and methodological quality assessment (NIH guidelines) were independently performed by two investigators. Qualitative synthesis was performed from all included studies and meta-analysis was performed using a random-effects model with inverse variance for studies that reported the concentration of proteins or enzymatic activity. Standardized mean difference (SMD) with respective 95% confidence interval (CI) were calculated for each outcome.
RESULTS
A total of 90 studies (two cohort and 88 cross-sectional designs) of more than 6,000 participants were selected for data extraction, being the quality of evidence graded as "fair" for most of them. The oral cavity of CF individuals presented lower total protein concentration [SMD = 0.37 (95% CI: 0.07-0.68; 18 studies)], lower total antioxidant capacity [SMD = 1.29 (95% CI: 0.74-1.85); 17 studies], and lower carbonic anhydrase activity [SMD = 0.83 (95% CI: 0.58-1.09); three studies], whereas CA individuals presented lower carbonic anhydrase concentration [SMD = -0.66 (95% CI: -1.00 to -0.32); three studies], urease [SMD = -0.95 (IC 95%: -1.72 to -0.17); four studies], and arginine deiminase system [SMD = -2.07 (95% CI: -3.53 to -0.62); three studies] activities. Antimicrobial peptides, secretory immunoglobulin-A concentrations and alpha-amylase activity were similar among individuals.
CONCLUSION
Differences on oral cavity protein abundance were observed among CF and CA individuals. These data indicate some protein patterns for the oral health and dental caries conditions. Even when statistically significant, some of the results were not very consistent. Cohort studies need to be conducted to validate these results.
PubMed: 37780687
DOI: 10.3389/froh.2023.1265817 -
Frontiers in Immunology 2022Tryptophan (TRP) is an essential amino acid that must be provided in the diet. The kynurenine pathway (KP) is the main route of TRP catabolism into nicotinamide... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Tryptophan (TRP) is an essential amino acid that must be provided in the diet. The kynurenine pathway (KP) is the main route of TRP catabolism into nicotinamide adenosine dinucleotide (NAD), and metabolites of this pathway may have protective or degenerative effects on the nervous system. Thus, the KP may be involved in neurodegenerative diseases.
OBJECTIVES
The purpose of this systematic review and meta-analysis is to assess the changes in KP metabolites such as TRP, kynurenine (KYN), kynurenic acid (KYNA), Anthranilic acid (AA), 3-hydroxykynurenine (3-HK), 5-Hydroxyindoleacetic acid (5-HIAA), and 3-Hydroxyanthranilic acid (3-HANA) in Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD) patients compared to the control group.
METHODS
We conducted a literature search using PubMed/Medline, Scopus, Google Scholar, Web of Science, and EMBASE electronic databases to find articles published up to 2022. Studies measuring TRP, KYN, KYNA, AA, 3-HK, 5-HIAA, 3-HANA in AD, PD, or HD patients and controls were identified. Standardized mean differences (SMDs) were used to determine the differences in the levels of the KP metabolites between the two groups.
RESULTS
A total of 30 studies compromising 689 patients and 774 controls were included in our meta-analysis. Our results showed that the blood levels of TRP was significantly lower in the AD (SMD=-0.68, 95% CI=-0.97 to -0.40, p=0.000, I2 = 41.8%, k=8, n=382), PD (SMD=-0.77, 95% CI=-1.24 to -0.30, p=0.001, I2 = 74.9%, k=4, n=352), and HD (SMD=-0.90, 95% CI=-1.71 to -0.10, p=0.028, I2 = 91.0%, k=5, n=369) patients compared to the controls. Moreover, the CSF levels of 3-HK in AD patients (p=0.020) and the blood levels of KYN in HD patients (p=0.020) were lower compared with controls.
CONCLUSION
Overall, the findings of this meta-analysis support the hypothesis that the alterations in the KP may be involved in the pathogenesis of AD, PD, and HD. However, additional research is needed to show whether other KP metabolites also vary in AD, PD, and HD patients. So, the metabolites of KP can be used for better diagnosing these diseases.
Topics: Humans; Kynurenine; Kynurenic Acid; Tryptophan; Hydroxyindoleacetic Acid; Alzheimer Disease; Parkinson Disease; Huntington Disease; 3-Hydroxyanthranilic Acid; NAD; Adenosine; Niacinamide
PubMed: 36263032
DOI: 10.3389/fimmu.2022.997240 -
Biomolecules Nov 2023Mitochondria are ancient endosymbiotic double membrane organelles that support a wide range of eukaryotic cell functions through energy, metabolism, and cellular... (Review)
Review
Mitochondria are ancient endosymbiotic double membrane organelles that support a wide range of eukaryotic cell functions through energy, metabolism, and cellular control. There are over 1000 known proteins that either reside within the mitochondria or are transiently associated with it. These mitochondrial proteins represent a functional subcellular protein network (mtProteome) that is encoded by mitochondrial and nuclear genomes and significantly varies between cell types and conditions. In neurons, the high metabolic demand and differential energy requirements at the synapses are met by specific modifications to the mtProteome, resulting in alterations in the expression and functional properties of the proteins involved in energy production and quality control, including fission and fusion. The composition of mtProteomes also impacts the localization of mitochondria in axons and dendrites with a growing number of neurodegenerative diseases associated with changes in mitochondrial proteins. This review summarizes the findings on the composition and properties of mtProteomes important for mitochondrial energy production, calcium and lipid signaling, and quality control in neural cells. We highlight strategies in mass spectrometry (MS) proteomic analysis of mtProteomes from cultured cells and tissue. The research into mtProteome composition and function provides opportunities in biomarker discovery and drug development for the treatment of metabolic and neurodegenerative disease.
Topics: Humans; Proteome; Neurodegenerative Diseases; Proteomics; Mitochondria; Neurons; Mitochondrial Proteins
PubMed: 38002320
DOI: 10.3390/biom13111638 -
Frontiers in Immunology 2023Sjögren's syndrome (SS) is a systemic autoimmune disease, which affects the exocrine glands leading to glandular dysfunction and, particularly, symptoms of oral and...
INTRODUCTION
Sjögren's syndrome (SS) is a systemic autoimmune disease, which affects the exocrine glands leading to glandular dysfunction and, particularly, symptoms of oral and ocular dryness. The aetiology of SS remains unclear, and the disease lacks distinctive clinical features. The current diagnostic work-up is complex, invasive and often time-consuming. Thus, there is an emerging need for identifying disease-specific and, ideally, non-invasive immunological and molecular biomarkers that can simplify the diagnostic process, allow stratification of patients, and assist in monitoring the disease course and outcome of therapeutic intervention in SS.
METHODS
This systematic review addresses the use of proteomics and miRNA-expression profile analyses in this regard.
RESULTS AND DISCUSSION
Out of 272 papers that were identified and 108 reviewed, a total of 42 papers on proteomics and 23 papers on miRNA analyses in saliva, blood and salivary gland tissue were included in this review. Overall, the proteomic and miRNA studies revealed considerable variations with regard to candidate biomarker proteins and miRNAs, most likely due to variation in sample size, processing and analytical methods, but also reflecting the complexity of SS and patient heterogeneity. However, interesting novel knowledge has emerged and further validation is needed to confirm their potential role as biomarkers in SS.
Topics: Humans; Sjogren's Syndrome; MicroRNAs; Proteomics; Saliva; Biomarkers
PubMed: 37275849
DOI: 10.3389/fimmu.2023.1183195 -
International Journal of Molecular... May 2023Biomarker development, improvement, and clinical implementation in the context of kidney disease have been a central focus of biomedical research for decades. To this... (Review)
Review
Biomarker development, improvement, and clinical implementation in the context of kidney disease have been a central focus of biomedical research for decades. To this point, only serum creatinine and urinary albumin excretion are well-accepted biomarkers in kidney disease. With their known blind spot in the early stages of kidney impairment and their diagnostic limitations, there is a need for better and more specific biomarkers. With the rise in large-scale analyses of the thousands of peptides in serum or urine samples using mass spectrometry techniques, hopes for biomarker development are high. Advances in proteomic research have led to the discovery of an increasing amount of potential proteomic biomarkers and the identification of candidate biomarkers for clinical implementation in the context of kidney disease management. In this review that strictly follows the PRISMA guidelines, we focus on urinary peptide and especially peptidomic biomarkers emerging from recent research and underline the role of those with the highest potential for clinical implementation. The Web of Science database (all databases) was searched on 17 October 2022, using the search terms "marker *" OR biomarker * AND "renal disease" OR "kidney disease" AND "proteome *" OR "peptid *" AND "urin *". English, full-text, original articles on humans published within the last 5 years were included, which had been cited at least five times per year. Studies based on animal models, renal transplant studies, metabolite studies, studies on miRNA, and studies on exosomal vesicles were excluded, focusing on urinary peptide biomarkers. The described search led to the identification of 3668 articles and the application of inclusion and exclusion criteria, as well as abstract and consecutive full-text analyses of three independent authors to reach a final number of 62 studies for this manuscript. The 62 manuscripts encompassed eight established single peptide biomarkers and several proteomic classifiers, including CKD273 and IgAN237. This review provides a summary of the recent evidence on single peptide urinary biomarkers in CKD, while emphasizing the increasing role of proteomic biomarker research with new research on established and new proteomic biomarkers. Lessons learned from the last 5 years in this review might encourage future studies, hopefully resulting in the routine clinical applicability of new biomarkers.
Topics: Humans; Proteomics; Renal Insufficiency, Chronic; Kidney; Peptides; Biomarkers
PubMed: 37298105
DOI: 10.3390/ijms24119156