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Heliyon Oct 2021Cyclophosphamide (CPA) is a cytotoxic prodrug that needs to be metabolized by cytochrome P450 enzymes, like CYP2B6. Unfortunately, CYP2B6 is a very polymorphic enzyme... (Review)
Review
The correlation between the level of 3-hydroxypropyl mercapturic acid, CYP2B6 polymorphisms, and hematuria occurrences after cyclophosphamide administration and its bioanalytical methods: A systematic review.
BACKGROUND
Cyclophosphamide (CPA) is a cytotoxic prodrug that needs to be metabolized by cytochrome P450 enzymes, like CYP2B6. Unfortunately, CYP2B6 is a very polymorphic enzyme and can cause a change in 3-hydroxypropyl mercapturic acid (3-HPMA), the most found CYP metabolite in urine levels. Change in 3-HPMA levels can also indicate the level change in its precursor, acrolein, which is responsible for the hematuria incidence after CPA administration.This review's purpose is to obtain a conclusion about the optimal 3-HPMA analysis method in urine after the administration of cyclophosphamide using liquid chromatography-tandem mass spectrometry (LC-MS/MS) through literature review from previous studies. Also, this review was written to examine the relationship between levels of 3-HPMA in urine, polymorphisms of CYP2B6 enzymes, and the incidence of hematuria after cyclophosphamide administration in cancer patients.
METHODS
Major databases, such as Universitas Indonesia's library database ScienceDirect, PubMed/Medline, Frontiers Media, and Google Scholar database, were used to find both published and unpublished studies without a time limit until 2020. Studies on pharmacokinetics, pharmacodynamics, drug therapy monitoring of cyclophosphamide, bioanalysis, and polymerase chain reaction (PCR) published in Indonesian and English were included. Meanwhile, non-related studies or studies written in other languages besides Indonesian and English were excluded. Two independent reviewers screened the titles, abstracts, and full-text manuscripts. Data obtained from eligible sources were used to answer the purpose of this review in a narrative form.
RESULTS
The authors found 436 related studies from various databases and websites. Then, the authors narrowed it down into 62 pieces of literature by removing the duplicates and reviewing the abstracts and full-text manuscripts. Out of 62 sources, the authors found 30 studies that explained 3-HPMA analysis using LC/MS-MS, CYP2B6 polymorphisms, and hematuria occurrences. The authors used those 30 studies to build a conclusion regarding the purpose of this study. We strengthened the results with some additional information from the other 32 eligible sources.
CONCLUSIONS
The authors conclude that according to literature searches from previous studies, the optimal 3-HPMA analysis method in urine after cyclophosphamide administration using LC-MS/MS is using triple quadrupole LC-MS/MS; source of positive ion electrospray ionization (ESI); mobile phase combination of 0.1% formic acid in water (A) - 0.1% formic acid in acetonitrile (90:10 v/v) (B); the Acquity® BEH C18 column (2.1 × 100 mm; 1.7 μm); injection volume of 10 μl; flow rate of 0.2 ml/minute; gradient elution method. Detection was carried out using mass spectrometry with m/z ratio of 222.10 > 90 for 3-HPMA and m/z 164.10 > 122 for n-acetylcysteine (NAC). The optimum sample preparation method is acidification and dilution ratio of 1:5 v/v. Also, there is a relationship between 3-HPMA levels, CYP2B6 polymorphisms, and the occurrences of hematuria after the administration of cyclophosphamide, which is a type of CYP2B6 polymorph, namely CYP2B6∗6, can increase cyclophosphamide hydroxylation so that it can increase the levels of acrolein and 3-HPMA, as its metabolites, and risk of hematuria.
ETHICS AND DISSEMINATION
This research does not use human participants, human data, or human tissue for being directly studied for the review. Therefore, ethics approval and consent to participate are not applicable.
REGISTRATION
This research has not been registered yet.
PubMed: 34746455
DOI: 10.1016/j.heliyon.2021.e08126 -
Nutrients Sep 2022Necrotizing enterocolitis (NEC) is the most devastating gastrointestinal emergency in preterm neonates. Research on early predictive biomarkers is fundamental. This is a... (Review)
Review
Necrotizing enterocolitis (NEC) is the most devastating gastrointestinal emergency in preterm neonates. Research on early predictive biomarkers is fundamental. This is a systematic review of studies applying untargeted metabolomics and gut microbiota analysis to evaluate the differences between neonates affected by NEC (Bell’s stage II or III), and/or by spontaneous intestinal perforation (SIP) versus healthy controls. Five studies applying metabolomics (43 cases, 95 preterm controls) and 20 applying gut microbiota analysis (254 cases, 651 preterm controls, 22 term controls) were selected. Metabolomic studies utilized NMR spectroscopy or mass spectrometry. An early urinary alanine/histidine ratio >4 showed good sensitivity and predictive value for NEC in one study. Samples collected in proximity to NEC diagnosis demonstrated variable pathways potentially related to NEC. In studies applying untargeted gut microbiota analysis, the sequencing of the V3−V4 or V3 to V5 regions of the 16S rRNA was the most used technique. At phylum level, NEC specimens were characterized by increased relative abundance of Proteobacteria compared to controls. At genus level, pre-NEC samples were characterized by a lack or decreased abundance of Bifidobacterium. Finally, at the species level Bacteroides dorei, Clostridium perfringens and perfringens-like strains dominated early NEC specimens, whereas Clostridium butyricum, neonatale and Propionibacterium acnei those at disease diagnosis. Six studies found a lower Shannon diversity index in cases than controls. A clear separation of cases from controls emerged based on UniFrac metrics in five out of seven studies. Importantly, no studies compared NEC versus SIP. Untargeted metabolomics and gut microbiota analysis are interrelated strategies to investigate NEC pathophysiology and identify potential biomarkers. Expression of quantitative measurements, data sharing via biorepositories and validation studies are fundamental to guarantee consistent comparison of results.
Topics: Alanine; Biomarkers; Enterocolitis, Necrotizing; Gastrointestinal Microbiome; Histidine; Humans; Infant, Newborn; Infant, Newborn, Diseases; Intestinal Perforation; Metabolome; RNA, Ribosomal, 16S
PubMed: 36145235
DOI: 10.3390/nu14183859 -
Metabolism: Clinical and Experimental Sep 2022Several anticancer agents have been associated with cardiac toxic effects. The currently proposed mechanisms to explain cardiotoxicity differ among anticancer agents,... (Review)
Review
Several anticancer agents have been associated with cardiac toxic effects. The currently proposed mechanisms to explain cardiotoxicity differ among anticancer agents, but in fact, the specific modulation is not completely elucidated. Thus, this systematic review aims to provide an integrative perspective of the molecular mechanisms underlying the toxicity of anticancer agents on heart muscle while using a high-throughput technology, mass spectrometry (MS)-based proteomics. A literature search using PubMed database led to the selection of 27 studies, of which 13 reported results exclusively on animal models, 13 on cardiomyocyte-derived cell lines and only one included both animal and a cardiomyocyte line. The reported anticancer agents were the proteasome inhibitor carfilzomib, the anthracyclines daunorubicin, doxorubicin, epirubicin and idarubicin, the antimicrotubule agent docetaxel, the alkylating agent melphalan, the anthracenedione mitoxantrone, the tyrosine kinase inhibitors (TKIs) erlotinib, lapatinib, sorafenib and sunitinib, and the monoclonal antibody trastuzumab. Regarding the MS-based proteomic approaches, electrophoretic separation using two-dimensional (2D) gels coupled with tandem MS (MS/MS) and liquid chromatography-MS/MS (LC-MS/MS) were the most common. Overall, the studies highlighted 1826 differentially expressed proteins across 116 biological processes. Most of them were grouped in larger processes and critically analyzed in the present review. The selection of studies using proteomics on heart muscle allowed to obtain information about the anticancer therapy-induced modulation of numerous proteins in this tissue and to establish connections that have been disregarded in other studies. This systematic review provides interesting points for a comprehensive understanding of the cellular cardiotoxicity mechanisms of different anticancer drugs.
Topics: Animals; Antineoplastic Agents; Cardiotoxicity; Chromatography, Liquid; Proteomics; Tandem Mass Spectrometry
PubMed: 35809654
DOI: 10.1016/j.metabol.2022.155250 -
Technology in Cancer Research &... Apr 2014Numbers of studies used surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) to find novel serum biomarkers for non-small cell... (Meta-Analysis)
Meta-Analysis Review
Numbers of studies used surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) to find novel serum biomarkers for non-small cell lung cancer (NSCLC). It is arguable whether the SELDI technique has its value of diagnostic accuracy for NSCLC. The purpose of our study is to determine the diagnostic accuracy of SELDI-TOF-MS for diagnosing NSCLC. The Cochrane Central Register of Controlled Trials, MEDLINE, Pub Med, EMBASE, the Chinese Biomedical Literature Database, the China Academic Journals Full-text Database, and the Chinese Scientific Journals Database were searched systematically for potential studies. Reference lists of included studies and review articles were also reviewed. All studies that reported data on patients with a confirmed diagnosis of NSCLC and that compared the measurement of SELDI-TOF-MS with pathology standard were considered for inclusion. 11 studies were included in the systematic review. The ranges of the diagnostic value of SELDI-TOF-MS for NSCLC were as follows: sensitivity (SEN) was 0.70~1.00; specificity (SPE) was 0.68~1.00; positive likelihood ratio (PLR) was 2.23~23.14; negative likelihood ratio (NLR) was 0.04~0.43; and diagnostic odds ratio (DOR) was 5.17~621.0, respectively. SELDI-TOF-MS showed high accuracy in identifying NSCLC, and could be a potential screening tool for diagnosing NSCLC patients.
Topics: Biomarkers, Tumor; Carcinoma, Non-Small-Cell Lung; Humans; Lung Neoplasms; Odds Ratio; Proteomics; ROC Curve; Reproducibility of Results; Sensitivity and Specificity; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
PubMed: 23862745
DOI: 10.7785/tcrt.2012.500360 -
Toxics Mar 2022Oxidative stress has been associated with various inflammation-related human diseases. It is defined as an imbalance between the production and elimination of reactive... (Review)
Review
Oxidative stress has been associated with various inflammation-related human diseases. It is defined as an imbalance between the production and elimination of reactive oxygen species (ROS). ROS can oxidize proteins, lipids, and DNA, and some of these oxidized products are excreted in urine, such as malondialdehyde (MDA), which is considered a biomarker for oxidative damage of lipids. To interpret changes of this biomarker as a measure of oxidative species overproduction in humans, a background range for urinary MDA concentration in the general population is needed. We sought to establish urinary MDA concentration ranges for healthy adult populations based on reported values in the available scientific literature. We conducted a systematic review and meta-analysis using the standardized protocol registered in PROSPERO (CRD42020146623). EMBASE, PubMed, Web of Science, and Cochrane library databases were searched from journal inception up to October 2020. We included 35 studies (divided into 47 subgroups for the quantitative analysis). Only studies that measured creatinine-corrected urinary MDA with high-performance liquid chromatography (HPLC) with mass spectrometry (MS), fluorescence detection, or UV photometry were included. The geometric mean (GM) of urinary MDA concentration was 0.10 mg/g creatinine and 95% percentile confidence interval (CI) 0.07-0.12. Age, geographical location but not sex, and smoking status had a significant effect on urinary MDA concentrations. There was a significant increasing trend of urinary MDA concentrations with age. These urinary MDA values should be considered preliminary, as they are based on mostly moderate to some low-quality evidence studies. Although urinary MDA can reliably reflect excessive oxidative stress in a population, the influence of physiological parameters that affect its meaning needs to be addressed as well as harmonizing the chemical analytical methods.
PubMed: 35448421
DOI: 10.3390/toxics10040160 -
Journal of Ovarian Research Jan 2020To evaluate the diagnostic performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for ovarian cancer. (Meta-Analysis)
Meta-Analysis
Performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in diagnosis of ovarian cancer: a systematic review and meta-analysis.
BACKGROUND
To evaluate the diagnostic performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for ovarian cancer.
PATIENTS AND METHODS
A thorough research was conducted in PubMed, Web of Science and Embase (until November 2018) to identify studies evaluating the accuracy of MALDI-TOF-MS for ovarian cancer. Using Meta-Disc1.4, Review Manager 5.3 and Stata 15.1 software to analyze the pooled results: sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and 95% confidence intervals (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) show the overall performance of MALDI-TOF-MS.
RESULTS
Eighteen studies were included in the meta-analysis. Methodological quality analysis of the included studies showed that these articles were at low risk of bias and applicability concerns in total. Summary estimates of the diagnostic parameters were as follows: sensitivity, 0.77 (95% CI: 0.73-0.80); specificity, 0.72 (95% CI: 0.70-0.74), PLR, 2.80 (95% CI: 2.41-3.24); NLR, 0.30 (95% CI: 0.22-0.40) and DOR, 10.71 (95% CI: 7.81-14.68). And the AUC was 0.8336. Egger's test showed no significant publication bias in this meta-analysis.
CONCLUSION
In conclusion, MALDI-TOF-MS shows a good ability for diagnosing ovarian cancer. Further evaluation and optimization of standardized procedures are necessary for complete relying on MALDI-TOF-MS to diagnose ovarian cancer.
Topics: Biomarkers, Tumor; CA-125 Antigen; Carcinoembryonic Antigen; Female; Humans; Membrane Proteins; Ovarian Neoplasms; ROC Curve; Reproducibility of Results; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
PubMed: 31924227
DOI: 10.1186/s13048-019-0605-2 -
Clinical Microbiology and Infection :... Oct 2020The matrix assisted laser desorption/ionization and time-of-flight mass spectrometry (MALDI-TOF MS) technology has revolutionized the field of microbiology by...
BACKGROUND
The matrix assisted laser desorption/ionization and time-of-flight mass spectrometry (MALDI-TOF MS) technology has revolutionized the field of microbiology by facilitating precise and rapid species identification. Recently, machine learning techniques have been leveraged to maximally exploit the information contained in MALDI-TOF MS, with the ultimate goal to refine species identification and streamline antimicrobial resistance determination.
OBJECTIVES
The aim was to systematically review and evaluate studies employing machine learning for the analysis of MALDI-TOF mass spectra.
DATA SOURCES
Using PubMed/Medline, Scopus and Web of Science, we searched the existing literature for machine learning-supported applications of MALDI-TOF mass spectra for microbial species and antimicrobial susceptibility identification.
STUDY ELIGIBILITY CRITERIA
Original research studies using machine learning to exploit MALDI-TOF mass spectra for microbial specie and antimicrobial susceptibility identification were included. Studies focusing on single proteins and peptides, case studies and review articles were excluded.
METHODS
A systematic review according to the PRISMA guidelines was performed and a quality assessment of the machine learning models conducted.
RESULTS
From the 36 studies that met our inclusion criteria, 27 employed machine learning for species identification and nine for antimicrobial susceptibility testing. Support Vector Machines, Genetic Algorithms, Artificial Neural Networks and Quick Classifiers were the most frequently used machine learning algorithms. The quality of the studies ranged between poor and very good. The majority of the studies reported how to interpret the predictors (88.89%) and suggested possible clinical applications of the developed algorithm (100%), but only four studies (11.11%) validated machine learning algorithms on external datasets.
CONCLUSIONS
A growing number of studies utilize machine learning to optimize the analysis of MALDI-TOF mass spectra. This review, however, demonstrates that there are certain shortcomings of current machine learning-supported approaches that have to be addressed to make them widely available and incorporated them in the clinical routine.
Topics: Anti-Bacterial Agents; Bacteria; Humans; Machine Learning; Microbial Sensitivity Tests; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
PubMed: 32217160
DOI: 10.1016/j.cmi.2020.03.014 -
Health Technology Assessment... Jun 2016Sepsis can lead to multiple organ failure and death. Timely and appropriate treatment can reduce in-hospital mortality and morbidity. (Review)
Review
Sepsis: the LightCycler SeptiFast Test MGRADE®, SepsiTest™ and IRIDICA BAC BSI assay for rapidly identifying bloodstream bacteria and fungi - a systematic review and economic evaluation.
BACKGROUND
Sepsis can lead to multiple organ failure and death. Timely and appropriate treatment can reduce in-hospital mortality and morbidity.
OBJECTIVES
To determine the clinical effectiveness and cost-effectiveness of three tests [LightCycler SeptiFast Test MGRADE(®) (Roche Diagnostics, Risch-Rotkreuz, Switzerland); SepsiTest(TM) (Molzym Molecular Diagnostics, Bremen, Germany); and the IRIDICA BAC BSI assay (Abbott Diagnostics, Lake Forest, IL, USA)] for the rapid identification of bloodstream bacteria and fungi in patients with suspected sepsis compared with standard practice (blood culture with or without matrix-absorbed laser desorption/ionisation time-of-flight mass spectrometry).
DATA SOURCES
Thirteen electronic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched from January 2006 to May 2015 and supplemented by hand-searching relevant articles.
REVIEW METHODS
A systematic review and meta-analysis of effectiveness studies were conducted. A review of published economic analyses was undertaken and a de novo health economic model was constructed. A decision tree was used to estimate the costs and quality-adjusted life-years (QALYs) associated with each test; all other parameters were estimated from published sources. The model was populated with evidence from the systematic review or individual studies, if this was considered more appropriate (base case 1). In a secondary analysis, estimates (based on experience and opinion) from seven clinicians regarding the benefits of earlier test results were sought (base case 2). A NHS and Personal Social Services perspective was taken, and costs and benefits were discounted at 3.5% per annum. Scenario analyses were used to assess uncertainty.
RESULTS
For the review of diagnostic test accuracy, 62 studies of varying methodological quality were included. A meta-analysis of 54 studies comparing SeptiFast with blood culture found that SeptiFast had an estimated summary specificity of 0.86 [95% credible interval (CrI) 0.84 to 0.89] and sensitivity of 0.65 (95% CrI 0.60 to 0.71). Four studies comparing SepsiTest with blood culture found that SepsiTest had an estimated summary specificity of 0.86 (95% CrI 0.78 to 0.92) and sensitivity of 0.48 (95% CrI 0.21 to 0.74), and four studies comparing IRIDICA with blood culture found that IRIDICA had an estimated summary specificity of 0.84 (95% CrI 0.71 to 0.92) and sensitivity of 0.81 (95% CrI 0.69 to 0.90). Owing to the deficiencies in study quality for all interventions, diagnostic accuracy data should be treated with caution. No randomised clinical trial evidence was identified that indicated that any of the tests significantly improved key patient outcomes, such as mortality or duration in an intensive care unit or hospital. Base case 1 estimated that none of the three tests provided a benefit to patients compared with standard practice and thus all tests were dominated. In contrast, in base case 2 it was estimated that all cost per QALY-gained values were below £20,000; the IRIDICA BAC BSI assay had the highest estimated incremental net benefit, but results from base case 2 should be treated with caution as these are not evidence based.
LIMITATIONS
Robust data to accurately assess the clinical effectiveness and cost-effectiveness of the interventions are currently unavailable.
CONCLUSIONS
The clinical effectiveness and cost-effectiveness of the interventions cannot be reliably determined with the current evidence base. Appropriate studies, which allow information from the tests to be implemented in clinical practice, are required.
STUDY REGISTRATION
This study is registered as PROSPERO CRD42015016724.
FUNDING
The National Institute for Health Research Health Technology Assessment programme.
Topics: Age Factors; Anti-Bacterial Agents; Bacteremia; Cost-Benefit Analysis; Cross Infection; Febrile Neutropenia; Fungemia; Germany; Hospital Mortality; Humans; Models, Econometric; Models, Economic; Polymerase Chain Reaction; Quality-Adjusted Life Years; Sensitivity and Specificity; Sepsis; Technology Assessment, Biomedical; United Kingdom
PubMed: 27355222
DOI: 10.3310/hta20460 -
Asian Journal of Urology Apr 2024Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various... (Review)
Review
OBJECTIVE
Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.
METHODS
A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.
RESULTS
The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.
CONCLUSION
The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.
PubMed: 38680576
DOI: 10.1016/j.ajur.2022.11.005 -
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