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Biomolecules May 2023Cluster of Differentiation (CD) 93 (also known as complement protein 1 q subcomponent receptor C1qR1 or C1qRp) is a transmembrane glycoprotein that can also be present... (Review)
Review
INTRODUCTION
Cluster of Differentiation (CD) 93 (also known as complement protein 1 q subcomponent receptor C1qR1 or C1qRp) is a transmembrane glycoprotein that can also be present in a soluble (sCD93) form. Recent studies have investigated the role of this protein in cardiovascular disease (CVD). The present systematic review aims to assess the associations between CD93 and cardiovascular (CV) risk factors and disease at both the proteomic and genomic levels.
METHODS
We conducted systematic searches in the PubMed, EMBASE, and Web of Science databases to identify all human studies since inception to February 2023 that investigated the role of CD93 in CV risk factors, CVD, and CV-associated outcomes. The data collection and analysis have been independently conducted by two reviewers. The search terms included: cardiovascular, heart failure, acute stroke, myocardial infarction, stroke, peripheral artery disease, cardiovascular death, MACE, hypertension, metabolic syndrome, hyperuricemia, diabetes, cd93, c1qr, C1qR1, complement protein 1 q subcomponent receptor.
RESULTS
A total of 182 references were identified, and 15 studies investigating the associations between CD93 protein levels or CD93 genetic polymorphisms and the development or prevalence of CV risk factors (i.e., hypertension, dyslipidemia, and obesity) and CVD (i.e., heart failure, coronary artery disease, and ischemic stroke) were included. Although promising, the quality and dimension of the analyzed studies do not allow for a definitive answer to the question of whether CD93 may hold diagnostic and prognostic value in CVD.
Topics: Humans; Cardiovascular Diseases; Complement System Proteins; Heart Failure; Hypertension; Prognosis; Proteomics
PubMed: 37371490
DOI: 10.3390/biom13060910 -
Journal of Clinical Medicine May 2022Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as...
Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM.
PubMed: 35628864
DOI: 10.3390/jcm11102737 -
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 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 -
BioMedicine 2023Glioblastoma multiforme, commonly known as GBM or glioblastoma is a grade IV astrocytoma. Brain tumors are difficult to treat and lead to poor prognosis and survival in... (Review)
Review
BACKGROUND
Glioblastoma multiforme, commonly known as GBM or glioblastoma is a grade IV astrocytoma. Brain tumors are difficult to treat and lead to poor prognosis and survival in patients. Gliomas are categorized into four different grades among which GBM is the worst grade primary brain tumor with a survival of less than a year. The genomic heterogeneity of the brain tumor results in different profiles for patients diagnosed with glioblastoma. Precision medicine focuses on this specific tumor type and suggests specialized treatment for better prognosis and overall survival (OS).
PURPOSE
With the recent advancements in Genome-Wide Studies (GWS) and various characterizations of brain tumors based on genetic, transcriptomic, proteomic, epigenetic, and metabolomics, this review discusses the advancements and opportunities of precision medicine therapeutics, drugs, and diagnosis methods based on the different profiles of glioblastoma.
METHODS
This review has exhaustively surveyed several pieces of works from various literature databases.
CONCLUSION
It is evident that most primary brain tumors including glioblastoma require specific and precision therapeutics for better prognosis and OS. In present and future, molecular understanding and discovering specific therapies are essential for treatment in the field of neurooncology.
PubMed: 37937301
DOI: 10.37796/2211-8039.1403 -
Journal of Nephrology Apr 2024Glomerulonephritis inherently leads to the development of chronic kidney disease. It is the second most common diagnosis in patients requiring renal replacement therapy... (Review)
Review
BACKGROUND
Glomerulonephritis inherently leads to the development of chronic kidney disease. It is the second most common diagnosis in patients requiring renal replacement therapy in the United Kingdom. Metabolomics and proteomics can characterise, identify and quantify an individual's protein and metabolite make-up. These techniques have been optimised and can be performed on samples including kidney tissue, blood and urine. Utilising omic techniques in nephrology can uncover disease pathophysiology and transform the diagnostics and treatment options for glomerulonephritis.
OBJECTIVES
To evaluate the utility of metabolomics and proteomics using mass spectrometry and nuclear magnetic resonance in glomerulonephritis.
METHODS
The systematic review was registered on PROSPERO (CRD42023442092). Standard and extensive Cochrane search methods were used. The latest search date was March 2023. Participants were of any age with a histological diagnosis of glomerulonephritis. Descriptive analysis was performed, and data presented in tabular form. An area under the curve or p-value was presented for potential biomarkers discovered.
RESULTS
Twenty-seven studies were included (metabolomics (n = 9)), and (proteomics (n = 18)) with 1818 participants. The samples analysed were urine (n = 19) blood (n = 4) and biopsy (n = 6). The typical outcome themes were potential biomarkers, disease phenotype, risk of progression and treatment response.
CONCLUSION
This review shows the potential of metabolomic and proteomic analysis to discover new disease biomarkers that may influence diagnostics and disease management. Further larger-scale research is required to establish the validity of the study outcomes, including the several proposed biomarkers.
PubMed: 38689160
DOI: 10.1007/s40620-024-01923-w -
Expert Reviews in Molecular Medicine Apr 2022Preterm birth (PTB) is one of the leading causes of deaths in infants under the age of five. Known risk factors of PTB include genetic factors, lifestyle choices or... (Review)
Review
Preterm birth (PTB) is one of the leading causes of deaths in infants under the age of five. Known risk factors of PTB include genetic factors, lifestyle choices or infection. Identification of omic biomarkers associated with PTB could aid clinical management of women at high risk of early labour and thereby reduce neonatal morbidity. This systematic literature review aimed to identify and summarise maternal omic and multi-omic (genomics, transcriptomics, proteomics and metabolites) biomarker studies of PTB. Original research articles were retrieved from three databases: PubMed, Web of Science and Science Direct, using specified search terms for each omic discipline. PTB studies investigating genomics, transcriptomics, proteomics or metabolomics biomarkers prior to onset of labour were included. Data were collected and reviewed independently. Pathway analyses were completed on the biomarkers from non-targeted omic studies using Reactome pathway analysis tool. A total of 149 omic studies were identified; most of the literature investigated proteomic biomarkers. Pathway analysis identified several cellular processes associated with the omic biomarkers reported in the literature. Study heterogeneity was observed across the research articles, including the use of different gestation cut-offs to define PTB. Infection/inflammatory biomarkers were identified across majority of papers using a range of targeted and non-targeted approaches.
PubMed: 35379367
DOI: 10.1017/erm.2022.13 -
Scientific Reports Dec 2016We aimed to comprehensively compare two compartmented oral proteomes, the salivary and the dental pellicle proteome. Systematic review and datamining was used to obtain... (Review)
Review
We aimed to comprehensively compare two compartmented oral proteomes, the salivary and the dental pellicle proteome. Systematic review and datamining was used to obtain the physico-chemical, structural, functional and interactional properties of 1,515 salivary and 60 identified pellicle proteins. Salivary and pellicle proteins did not differ significantly in their aliphatic index, hydrophaty, instability index, or isoelectric point. Pellicle proteins were significantly more charged at low and high pH and were significantly smaller (10-20 kDa) than salivary proteins. Protein structure and solvent accessible molecular surface did not differ significantly. Proteins of the pellicle were more phosphorylated and glycosylated than salivary proteins. Ion binding and enzymatic activities also differed significantly. Protein-protein-ligand interaction networks relied on few key proteins. The identified differences between salivary and pellicle proteins could guide proteome compartmentalization and result in specialized functionality. Key proteins could be potential targets for diagnostic or therapeutic application.
Topics: Animals; Data Mining; Dental Enamel Proteins; Dental Pellicle; Humans; Proteome; Salivary Proteins and Peptides
PubMed: 27966577
DOI: 10.1038/srep38882 -
Cancers Oct 2023The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to... (Review)
Review
The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to identify proteins differentially expressed in SCLC compared to normal lung tissue, evaluating their potential utility in diagnosing and prognosing the disease. Additionally, the study identifies proteins differentially expressed between SCLC and large cell neuroendocrine carcinoma (LCNEC), aiming to discover biomarkers distinguishing between these two subtypes of neuroendocrine lung cancers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/MEDLINE, Scopus, Embase, and Web of Science databases. Studies reporting proteomics information and confirming SCLC and/or LCNEC through histopathological and/or cytopathological examination were included, while review articles, non-original articles, and studies based on animal samples or cell lines were excluded. The initial search yielded 1705 articles, and after deduplication and screening, 16 articles were deemed eligible. These studies revealed 117 unique proteins significantly differentially expressed in SCLC compared to normal lung tissue, along with 37 unique proteins differentially expressed between SCLC and LCNEC. In conclusion, this review highlights the potential of proteomics technology in identifying novel biomarkers for diagnosing SCLC, predicting its prognosis, and distinguishing it from LCNEC.
PubMed: 37894372
DOI: 10.3390/cancers15205005 -
Frontiers in Immunology 2021Although proteomics has been employed in the study of several models of liver injury, proteomic methods have only recently been applied not only to biomarker discovery...
BACKGROUND
Although proteomics has been employed in the study of several models of liver injury, proteomic methods have only recently been applied not only to biomarker discovery and validation but also to improve understanding of the molecular mechanisms involved in transplantation.
METHODS
The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and the guidelines for performing systematic literature reviews in bioinformatics (BiSLR). The PubMed, ScienceDirect, and Scopus databases were searched for publications through April 2020. Proteomics studies designed to understand liver transplant outcomes, including ischemia-reperfusion injury (IRI), rejection, or operational tolerance in human or rat samples that applied methodologies for differential expression analysis were considered.
RESULTS
The analysis included 22 studies after application of the inclusion and exclusion criteria. Among the 497 proteins annotated, 68 were shared between species and 10 were shared between sample sources. Among the types of studies analyzed, IRI and rejection shared a higher number of proteins. The most enriched pathway for liver biopsy samples, IRI, and rejection was metabolism, compared to cytokine-cytokine receptor interactions for tolerance.
CONCLUSIONS
Proteomics is a promising technique to detect large numbers of proteins. However, our study shows that several technical issues such as the identification of proteoforms or the dynamic range of protein concentration in clinical samples hinder the successful identification of biomarkers in liver transplantation. In addition, there is a need to minimize the experimental variability between studies, increase the sample size and remove high-abundance plasma proteins.
Topics: Animals; Biomarkers; Computational Biology; Humans; Liver Transplantation; Proteomics
PubMed: 34381445
DOI: 10.3389/fimmu.2021.672829