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BMC Oral Health Mar 2024Understanding the distinct proteomics profiles in dogs' oral biofluids enhances diagnostic and therapeutic insights for canine oral diseases, fostering cross-species...
BACKGROUND
Understanding the distinct proteomics profiles in dogs' oral biofluids enhances diagnostic and therapeutic insights for canine oral diseases, fostering cross-species translational research in dentistry and medicine. This study aimed to conduct a systematic review to investigate the similarities and differences between the oral biofluids' proteomics profile of dogs with and without oral diseases.
METHODS
PubMed, Web of Science, and Scopus were searched with no restrictions on publication language or year to address the following focused question: "What is the proteome signature of healthy versus diseased (oral) dogs' biofluids?" Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analyses of the most abundant proteins were performed. Moreover, protein-protein interaction analysis was conducted. The risk of bias (RoB) among the included studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data.
RESULTS
In healthy dogs, the proteomic analysis identified 5,451 proteins, with 137 being the most abundant, predominantly associated with 'innate immune response'. Dogs with oral diseases displayed 6,470 proteins, with distinct associations: 'defense response to bacterium' (periodontal diseases), 'negative regulation of transcription' (dental calculus), and 'positive regulation of transcription' (oral tumors). Clustering revealed significant protein clusters in each case, emphasizing the diverse molecular profiles in health and oral diseases. Only six studies were provided to the JBI tool, as they encompassed case-control evaluations that compared healthy dogs to dogs with oral disease(s). All included studies were found to have low RoB (high quality).
CONCLUSION
Significant differences in the proteomics profiles of oral biofluids between dogs with and without oral diseases were found. The synergy of animal proteomics and bioinformatics offers a promising avenue for cross-species research, despite persistent challenges in result validation.
Topics: Animals; Dogs; Proteomics; Mass Spectrometry; Periodontal Diseases; Bacteria; Mouth Neoplasms
PubMed: 38519930
DOI: 10.1186/s12903-024-04096-x -
Metabolism: Clinical and Experimental Jan 2022The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date.
METHOD
23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity.
FINDINGS
Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81-0.96) and specificity 0.88 (interquartile range 0.82-0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application.
CONCLUSIONS
This systematic review and meta-analysis demonstrates the potential for mass spectrometry and 'omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.
Topics: COVID-19; COVID-19 Testing; Humans; Mass Spectrometry; Sensitivity and Specificity
PubMed: 34715115
DOI: 10.1016/j.metabol.2021.154922 -
Heliyon Jun 2020Quantitative proteomic workflow based on mass spectrometry (MS) is recently developed by the researchers to screen for biomarkers in periodontal diseases comprising... (Review)
Review
Quantitative proteomic workflow based on mass spectrometry (MS) is recently developed by the researchers to screen for biomarkers in periodontal diseases comprising periodontitis. Periodontitis is known for chronic inflammatory disease characterized by progressive destruction of the tooth-supporting apparatus, yet has a lack of clear pathobiology based on a discrepancy between specified categories and diagnostic vagueness. The objective of this review was to outlined the accessible information related to proteomics studies on periodontitis. The Preferred Reporting Items for Systematical Reviews and Meta-Analysis (PRISMA) statement guides to acquaint proteomic analysis on periodontal diseases was applied. Three databases were used in this study, such as Pubmed, ScienceDirect and Biomed Central from 2009 up to November 2019. Proteomics analysis platforms that used in the studies were outlined. Upregulated and downregulated proteins findings data were found, in which could be suitable as candidate biomarkers for this disease.
PubMed: 32529063
DOI: 10.1016/j.heliyon.2020.e04022 -
Cancer Medicine Jul 2022Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.
METHODS
We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.
RESULTS
Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.
CONCLUSION
Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.
Topics: Adult; Biomarkers; Breast Neoplasms; Female; Humans; Middle Aged; Odds Ratio; ROC Curve; Sensitivity and Specificity
PubMed: 35315584
DOI: 10.1002/cam4.4640 -
Biomolecules & Therapeutics Nov 2021Researchers have endeavored to identify the etiology of inflammatory bowel diseases, including Crohn's disease and ulcerative colitis. Though the pathogenesis of... (Review)
Review
Researchers have endeavored to identify the etiology of inflammatory bowel diseases, including Crohn's disease and ulcerative colitis. Though the pathogenesis of inflammatory bowel diseases remains unknown, dysregulation of the immune system in the host gastrointestinal tract is believed to be the major causative factor. Omics is a powerful methodological tool that can reveal biochemical information stored in clinical samples. Lipidomics is a subset of omics that explores the lipid classes associated with inflammation. One objective of the present systematic review was to facilitate the identification of biochemical targets for use in future lipidomic studies on inflammatory bowel diseases. The use of high-resolution mass spectrometry to observe alterations in global lipidomics might help elucidate the immunoregulatory mechanisms involved in inflammatory bowel diseases and discover novel biomarkers for them. Assessment of the characteristics of previous clinical trials on inflammatory bowel diseases could help researchers design and establish patient selection and analytical method criteria for future studies on these conditions. In this study, we curated literature exclusively from four databases and extracted lipidomics-related data from literature, considering criteria. This paper suggests that the lipidomics approach toward research in inflammatory bowel diseases can clarify their pathogenesis and identify clinically valuable biomarkers to predict and monitor their progression.
PubMed: 34565718
DOI: 10.4062/biomolther.2021.125 -
BMC Ophthalmology Dec 2023Age-related macular degeneration (AMD) is a significant cause of severe vision loss. The main purpose of this study was to identify mass spectrometry proteomics-based... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Age-related macular degeneration (AMD) is a significant cause of severe vision loss. The main purpose of this study was to identify mass spectrometry proteomics-based potential biomarkers of AMD that contribute to understanding the mechanisms of disease and aiding in early diagnosis.
METHODS
This study retrieved studies that aim to detect differences relate to proteomics in AMD patients and healthy control groups by mass spectrometry (MS) proteomics approaches. The search process was accord with PRISMA guidelines (PROSPERO database: CRD42023388093). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes Pathway Analysis (KEGG) were performed on differentially expressed proteins (DEPs) in the included articles using the DAVID database. DEPs were included in a meta-analysis when their effect size could be computed in at least two research studies. The effect size of measured proteins was transformed to the log2-fold change. Protein‒protein interaction (PPI) analysis was conducted on proteins that were statistically significant in the meta-analysis using the String online database.
RESULTS
Eleven studies fulfilled the inclusion criteria, and 161 DEPs were identified. The GO analysis showed that AMD is significantly related to proteolysis, extracellular exosome and protein binding. In KEGG, the most significant pathway was the complement and coagulation cascades. Meta-analysis results suggested that eight proteins were statistically significant, and according to PPI results, the most significant four proteins were serotransferrin (TF), apolipoprotein A1 (APOA1), complement C3 (C3) and lipocalin-1 (LCN1).
CONCLUSIONS
Four possible biomarkers, TF, APOA1, C3 and LCN1, were found to be significant in the pathogenesis of AMD and need to be further validated. Further studies should be performed to evaluate diagnostic and therapeutic value of these proteins.
Topics: Humans; Proteomics; Macular Degeneration; Biomarkers; Proteins; Mass Spectrometry
PubMed: 38087257
DOI: 10.1186/s12886-023-03237-0 -
Journal of Cachexia, Sarcopenia and... Jun 2024Proliferating cancer cells shift their metabolism towards glycolysis, even in the presence of oxygen, to especially generate glycolytic intermediates as substrates for...
BACKGROUND
Proliferating cancer cells shift their metabolism towards glycolysis, even in the presence of oxygen, to especially generate glycolytic intermediates as substrates for anabolic reactions. We hypothesize that a similar metabolic remodelling occurs during skeletal muscle hypertrophy.
METHODS
We used mass spectrometry in hypertrophying C2C12 myotubes in vitro and plantaris mouse muscle in vivo and assessed metabolomic changes and the incorporation of the [U-C]glucose tracer. We performed enzyme inhibition of the key serine synthesis pathway enzyme phosphoglycerate dehydrogenase (Phgdh) for further mechanistic analysis and conducted a systematic review to align any changes in metabolomics during muscle growth with published findings. Finally, the UK Biobank was used to link the findings to population level.
RESULTS
The metabolomics analysis in myotubes revealed insulin-like growth factor-1 (IGF-1)-induced altered metabolite concentrations in anabolic pathways such as pentose phosphate (ribose-5-phosphate/ribulose-5-phosphate: +40%; P = 0.01) and serine synthesis pathway (serine: -36.8%; P = 0.009). Like the hypertrophy stimulation with IGF-1 in myotubes in vitro, the concentration of the dipeptide l-carnosine was decreased by 26.6% (P = 0.001) during skeletal muscle growth in vivo. However, phosphorylated sugar (glucose-6-phosphate, fructose-6-phosphate or glucose-1-phosphate) decreased by 32.2% (P = 0.004) in the overloaded muscle in vivo while increasing in the IGF-1-stimulated myotubes in vitro. The systematic review revealed that 10 metabolites linked to muscle hypertrophy were directly associated with glycolysis and its interconnected anabolic pathways. We demonstrated that labelled carbon from [U-C]glucose is increasingly incorporated by ~13% (P = 0.001) into the non-essential amino acids in hypertrophying myotubes, which is accompanied by an increased depletion of media serine (P = 0.006). The inhibition of Phgdh suppressed muscle protein synthesis in growing myotubes by 58.1% (P < 0.001), highlighting the importance of the serine synthesis pathway for maintaining muscle size. Utilizing data from the UK Biobank (n = 450 243), we then discerned genetic variations linked to the serine synthesis pathway (PHGDH and PSPH) and to its downstream enzyme (SHMT1), revealing their association with appendicular lean mass in humans (P < 5.0e-8).
CONCLUSIONS
Understanding the mechanisms that regulate skeletal muscle mass will help in developing effective treatments for muscle weakness. Our results provide evidence for the metabolic rewiring of glycolytic intermediates into anabolic pathways during muscle growth, such as in serine synthesis.
Topics: Glucose; Muscle, Skeletal; Animals; Mice; Humans; Hypertrophy; Muscle Fibers, Skeletal; Insulin-Like Growth Factor I; Metabolomics
PubMed: 38742477
DOI: 10.1002/jcsm.13468 -
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 -
International Journal of Molecular... Jul 2023The Alcohol Use Disorders Identification Test (AUDIT) and its short form, the AUDIT-C, the main clinical instruments used to identify unhealthy drinking behaviors, are... (Review)
Review
The Alcohol Use Disorders Identification Test (AUDIT) and its short form, the AUDIT-C, the main clinical instruments used to identify unhealthy drinking behaviors, are influenced by memory bias and under-reporting. In recent years, phosphatidylethanol (PEth) in blood has emerged as a marker of unhealthy alcohol use. This systematic review aims to investigate the molecular characteristics of PEth and summarize the last ten years of published literature and its use compared to structured questionnaires. A systematic search was performed, adhering to PRISMA guidelines, through "MeSH" and "free-text" protocols in the databases PubMed, SCOPUS, and Web of Science. The inclusion criteria were as follows: PEth was used for detecting unhealthy alcohol consumption in the general population and quantified in blood through liquid chromatography coupled to mass spectrometry, with full texts in the English language. Quality assessment was performed using the JBI critical appraisal checklist. Twelve papers were included (0.79% of total retrieved records), comprising nine cross-sectional studies and three cohort studies. All studies stratified alcohol exposure and quantified PEth 16:0/18:1 through liquid chromatography coupled to mass spectrometry (LC-MS) in liquid blood or dried blood spots (DBS) with lower limits of quantitation (LLOQ) ranging from 1.7 ng/mL to 20 ng/mL. A correlation between blood PEth level and the amount of alcohol ingested in the previous two weeks was generally observed. PEth interpretative cut-offs varied greatly among the included records, ranging from 4.2 ng/mL to 250 ng/mL, with sensitivity and specificity in the ranges of 58-100% and 64-100%, respectively. Although the biomarker seems promising, further research elucidating the variability in PEth formation and degradation, as well as the molecular mechanisms behind that variability, are necessary.
Topics: Humans; Alcoholism; Cross-Sectional Studies; Alcohol Drinking; Glycerophospholipids; Ethanol; Biomarkers
PubMed: 37569551
DOI: 10.3390/ijms241512175 -
Frontiers in Endocrinology 2022Diabetic nephropathy (DN) is a major microvascular complication of both type 1 and type 2 diabetes mellitus and is the most frequent cause of end-stage renal disease... (Meta-Analysis)
Meta-Analysis
Diabetic nephropathy (DN) is a major microvascular complication of both type 1 and type 2 diabetes mellitus and is the most frequent cause of end-stage renal disease with an increasing prevalence. Presently there is no non-invasive method for differential diagnosis, and an efficient target therapy is lacking. Extracellular vesicles (EV), including exosomes, microvesicles, and apoptotic bodies, are present in various body fluids such as blood, cerebrospinal fluid, and urine. Proteins in EV are speculated to be involved in various processes of disease and reflect the original cells' physiological states and pathological conditions. This systematic review is based on urinary extracellular vesicles studies, which enrolled patients with DN and investigated the proteins in urinary EV. We systematically reviewed articles from the PubMed, Embase, Web of Science databases, and China National Knowledge Infrastructure (CNKI) database until January 4, 2022. The article quality was appraised according to the Newcastle-Ottawa Quality Assessment Scale (NOS). The methodology of samples, isolation and purification techniques of urinary EV, and characterization methods are summarized. Molecular functions, biological processes, and pathways were enriched in all retrievable urinary EV proteins. Protein-protein interaction analysis (PPI) revealed pathways of potential biomarkers. A total of 539 articles were retrieved, and 13 eligible records were enrolled in this systematic review and meta-analysis. And two studies performed mass spectrometry to obtain the proteome profile. Two of them enrolled only T1DM patients, two studies enrolled both patients with T1DM and T2DM, and other the nine studies focused on T2DM patients. In total 988 participants were enrolled, and DN was diagnosed according to UACR, UAER, or decreased GFR. Totally 579 urinary EV proteins were detected and 28 of them showed a potential value to be biomarkers. The results of bioinformatics analysis revealed that urinary EV may participate in DN through various pathways such as angiogenesis, biogenesis of EV, renin-angiotensin system, fluid shear stress and atherosclerosis, collagen degradation, and immune system. Besides that, it is necessary to report results compliant with the guideline of ISEV, in orderto assure repeatability and help for further studies. This systematic review concordance with previous studies and the results of meta-analysis may help to value the methodology details when urinary EV proteins were reported, and also help to deepen the understanding of urinary EV proteins in DN.
Topics: Biomarkers; Diabetes Mellitus, Type 1; Diabetes Mellitus, Type 2; Diabetic Nephropathies; Extracellular Vesicles; Humans; Proteome
PubMed: 36034457
DOI: 10.3389/fendo.2022.866252