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ERJ Open Research Jul 2023Asthma and COPD are among the most common respiratory diseases. To improve the early detection of exacerbations and the clinical course of asthma and COPD new biomarkers... (Review)
Review
BACKGROUND
Asthma and COPD are among the most common respiratory diseases. To improve the early detection of exacerbations and the clinical course of asthma and COPD new biomarkers are needed. The development of noninvasive metabolomics of exhaled air into a point-of-care tool is an appealing option. However, risk factors for obstructive pulmonary diseases can potentially introduce confounding markers due to altered volatile organic compound (VOC) patterns being linked to these risk factors instead of the disease. We conducted a systematic review and presented a comprehensive list of VOCs associated with these risk factors.
METHODS
A PRISMA-oriented systematic search was conducted across PubMed, Embase and Cochrane Libraries between 2000 and 2022. Full-length studies evaluating VOCs in exhaled breath were included. A narrative synthesis of the data was conducted, and the Newcastle-Ottawa Scale was used to assess the quality of included studies.
RESULTS
The search yielded 2209 records and, based on the inclusion/exclusion criteria, 24 articles were included in the qualitative synthesis. In total, 232 individual VOCs associated with risk factors for obstructive pulmonary diseases were found; 58 compounds were reported more than once and 12 were reported as potential markers of asthma and/or COPD in other studies. Critical appraisal found that the identified studies were methodologically heterogeneous and had a variable risk of bias.
CONCLUSION
We identified a series of exhaled VOCs associated with risk factors for asthma and/or COPD. Identification of these VOCs is necessary for the further development of exhaled metabolites-based point-of-care tests in these obstructive pulmonary diseases.
PubMed: 37650089
DOI: 10.1183/23120541.00143-2023 -
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 -
European Journal of Medical Research Sep 2022Intrahepatic cholestasis of pregnancy (ICP) is a severe idiopathic disorder of bile metabolism; however, the etiology and pathogenesis of ICP remain unclear. (Review)
Review
BACKGROUND
Intrahepatic cholestasis of pregnancy (ICP) is a severe idiopathic disorder of bile metabolism; however, the etiology and pathogenesis of ICP remain unclear.
AIMS
This study comprehensively reviewed metabolomics studies related to ICP, to help in identifying the pathophysiological changes of ICP and evaluating the potential application of metabolomics in its diagnosis.
METHODS
Relevant articles were searched through 2 online databases (PubMed and Web of Science) from January 2000 to March 2022. The metabolites involved were systematically examined and compared. Pathway analysis was conducted through the online software MetaboAnalyst 5.0.
RESULTS
A total of 14 papers reporting 212 metabolites were included in this study. There were several highly reported metabolites: bile acids, such as glycocholic acid, taurochenodeoxycholic acid, taurocholic acid, tauroursodeoxycholic acid, and glycochenodeoxycholic acid. Dysregulation of metabolic pathways involved bile acid metabolism and lipid metabolism. Metabolites related to lipid metabolism include phosphatidylcholine, phosphorylcholine, phosphatidylserine, sphingomyelin, and ceramide.
CONCLUSIONS
This study provides a systematic review of metabolomics of ICP and deepens our understanding of the etiology of ICP.
Topics: Bile Acids and Salts; Cholestasis, Intrahepatic; Female; Humans; Metabolomics; Pregnancy; Pregnancy Complications
PubMed: 36104763
DOI: 10.1186/s40001-022-00802-z -
Cancers Aug 2023Cancer is the leading cause of death worldwide, with the most frequent being breast cancer in women, prostate cancer in men and colon cancer in both sexes. The use of... (Review)
Review
INTRODUCTION
Cancer is the leading cause of death worldwide, with the most frequent being breast cancer in women, prostate cancer in men and colon cancer in both sexes. The use of metabolomics to find new biomarkers can provide knowledge about possible interventions based on the presence of oncometabolites in different cancer types.
OBJECTIVES
The primary purpose of this review is to analyze the characteristic metabolome of three of the most frequent cancer types. We further want to identify the existence and success rate of metabolomics-based intervention in patients suffering from those cancer types. Our conclusions are based on the analysis of the methodological quality of the studies.
METHODS
We searched for studies that investigated the metabolomic characteristics in patients suffering from breast cancer, prostate cancer or colon cancer in clinical trials. The data were analyzed, as well as the effects of specific interventions based on identified metabolomics and one or more oncometabolites. The used databases were PubMed, Virtual Health Library, Web of Science, EBSCO and Cochrane Library. Only nine studies met the selection criteria. Study bias was analyzed using the Cochrane risk of bias tool. This systematic review protocol was registered at the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023401474).
RESULTS
Only nine studies about clinical trials were included in this review and show a moderate quality of evidence. Metabolomics-based interventions related with disease outcome were conflictive with no or small changes in the metabolic characteristics of the different cancer types.
CONCLUSIONS
This systematic review shows some interesting results related with metabolomics-based interventions and their effects on changes in certain cancer oncometabolites. The small number of studies we identified which fulfilled our inclusion criteria in this systematic review does not allow us to draw definitive conclusions. Nevertheless, some results can be considered as promising although further research is needed. That research must focus not only on the presence of possible oncometabolites but also on possible metabolomics-based interventions and their influence on the outcome in patients suffering from breast cancer, prostate cancer or colon cancer.
PubMed: 37686573
DOI: 10.3390/cancers15174297 -
Seminars in Arthritis and Rheumatism Apr 2023Osteoarthritis (OA) is a joint disease that is clinically diagnosed using components of history, physical exam, and characteristic radiographic findings, such as joint... (Review)
Review
PURPOSE
Osteoarthritis (OA) is a joint disease that is clinically diagnosed using components of history, physical exam, and characteristic radiographic findings, such as joint space narrowing. Currently, there are no laboratory findings that are specific to a diagnosis of OA. The purpose of this systematic review is to evaluate the state of current studies of metabolomic biomarkers that can aid in the diagnosis and treatment of OA.
METHODS
Articles were gathered from PubMed and Web of Science using the search terms "osteoarthritis" and "biomarkers" and "metabolomics". Last search of databases took place December 3rd, 2022. Duplicates were manually screened, along with any other results that were not original journal articles. Only original reports involving populations with diagnosed primary or secondary OA (human participants) or surgically induced OA (animal participants) and a healthy control group for comparison were considered for inclusion. Metabolites and metabolic pathways reported in included articles were then manually extracted and evaluated for importance based on reported a priori p-values and/or area under the receiver-operator curve (AUC).
RESULTS
Of the 161 results that were returned in the database searches, 43 unique articles met the inclusion criteria. Articles were categorized based on body fluid analyzed: 6 studies on urine samples, 13 studies on plasma samples, 11 studies on synovial fluid (SF) samples, 11 studies on serum samples, 1 study on both synovial fluid and serum, and 1 study that involved both plasma and synovial fluid. To synthesize results, individual metabolites, as well as metabolic pathways that involve frequently reported metabolites, are presented for each study. Indications as to whether metabolite levels were increased or decreased are also included if this data was included in the original articles.
CONCLUSIONS
These studies clearly show that there are a wide range of metabolic pathways perturbed in OA. For this period, there was no consensus on a single metabolite, or panel of metabolites, that would be clinically useful in early diagnosis of OA or distinguishing OA from a healthy control. However, many common metabolic pathways were identified in the studies, including TCA cycle, fatty acid metabolism, amino acid metabolism (notably BCAA metabolism and tryptophan metabolism via kynurenine pathway), nucleotide metabolism, urea cycle, cartilage matrix components, and phospholipid metabolism. Future research is needed to define effective clinical biomarkers of osteoarthritis from metabolomic and other data.
Topics: Animals; Humans; Osteoarthritis; Metabolomics; Biomarkers; Synovial Fluid; Metabolic Networks and Pathways
PubMed: 36736024
DOI: 10.1016/j.semarthrit.2023.152163 -
Environment International Jun 2022Systematic evidence maps are increasingly used to develop chemical risk assessments. These maps can provide an overview of available studies and relevant study... (Review)
Review
BACKGROUND
Systematic evidence maps are increasingly used to develop chemical risk assessments. These maps can provide an overview of available studies and relevant study information to be used for various research objectives and applications. Environmental epidemiological studies that examine the impact of chemical exposures on various 'omic profiles in human populations provide relevant mechanistic information and can be used for benchmark dose modeling to derive potential human health reference values.
OBJECTIVES
To create a systematic evidence map of environmental epidemiological studies examining environmental contaminant exposures with 'omics in order to characterize the extent of available studies for future research needs.
METHODS
Systematic review methods were used to search and screen the literature and included the use of machine learning methods to facilitate screening studies. The Populations, Exposures, Comparators and Outcomes (PECO) criteria were developed to identify and screen relevant studies. Studies that met the PECO criteria after full-text review were summarized with information such as study population, study design, sample size, exposure measurement, and 'omics analysis.
RESULTS
Over 10,000 studies were identified from scientific databases. Screening processes were used to identify 84 studies considered PECO-relevant after full-text review. Various contaminants (e.g. phthalate, benzene, arsenic, etc.) were investigated in epidemiological studies that used one or more of the four 'omics of interest: epigenomics, transcriptomics, proteomics, and metabolomics . The epidemiological study designs that were used to explore single or integrated 'omic research questions with contaminant exposures were cohort studies, controlled trials, cross-sectional, and case-control studies. An interactive web-based systematic evidence map was created to display more study-related information.
CONCLUSIONS
This systematic evidence map is a novel tool to visually characterize the available environmental epidemiological studies investigating contaminants and biological effects using 'omics technology and serves as a resource for investigators and allows for a range of applications in chemical research and risk assessment needs.
Topics: Cross-Sectional Studies; Environmental Exposure; Epidemiologic Studies; Humans; Reference Values; Risk Assessment
PubMed: 35551006
DOI: 10.1016/j.envint.2022.107243 -
Diagnostics (Basel, Switzerland) Nov 2023Gastric cancer is the fourth most frequently diagnosed form of cancer and the third leading cause of cancer-related mortality worldwide. The aim of this review is to... (Review)
Review
INTRODUCTION
Gastric cancer is the fourth most frequently diagnosed form of cancer and the third leading cause of cancer-related mortality worldwide. The aim of this review is to identify individual metabolic biomarkers and their association with accurate diagnostic values, which can predict gastric cancer metastasis.
MATERIALS AND METHODS
After searching the keywords, 83 articles were found over a period of 13 years. One was eliminated because it was not written in English, and two were published outside the selected period. Seven scientific papers were qualified for this investigation after eliminating duplicates, non-related articles, systematic reviews, and restricted access studies.
RESULTS
New metabolic biomarkers with predictive value for gastric cancer metastasis and for elucidating metabolic pathways of the metastatic process have been found. The pathogenic processes can be outlined as follows: pro-oxidant capacity, T-cell inactivation, cell cycle arrest, energy production and mitochondrial enzyme impairment, cell viability and pro-apoptotic effect, enhanced degradation of collagen extracellular matrix, migration, invasion, structural protein synthesis, and tumoral angiogenesis.
CONCLUSION
Metabolic biomarkers have been recognized as independent risk factors in the molecular process of gastric cancer metastasis, with good diagnostic and prognostic value.
PubMed: 37998537
DOI: 10.3390/diagnostics13223401 -
Frontiers in Molecular Biosciences 2020Magnetic resonance imaging (MRI), cerebrospinal fluid (CSF) analysis, and the McDonald's clinical criteria are currently utilized tools in diagnosing multiple sclerosis.... (Review)
Review
BACKGROUND
Magnetic resonance imaging (MRI), cerebrospinal fluid (CSF) analysis, and the McDonald's clinical criteria are currently utilized tools in diagnosing multiple sclerosis. However, a more conclusive, consistent, and efficient way of diagnosing multiple sclerosis (MS) is yet to be discovered. A potential biomarker, discovered using advances in high-throughput sequencing such as nuclear magnetic resonance (NMR) spectroscopy and other "Omics"-based techniques, may make diagnosis and prognosis more reliable resulting in a more personalized and targeted treatment regime and improved outcomes. The aim of this review was to systematically search the literature for potential biomarkers from any bodily fluid that could consistently and accurately diagnose MS and/or indicate disease progression.
METHODS
A systematic literature review of EMBASE, PubMed (MEDLINE), The Cochrane Library, and CINAHL databases produced over a thousand potential studies. Inclusion criteria stated studies with potential biomarker outcomes for people with MS were to be included in the review. Studies were limited to those with human participants who had a clinically defined diagnosis of MS and published in English, with no limit placed on date of publication or the type of bodily fluid sampled.
RESULTS
A total of 1,805 studies were recorded from the literature search. A total of 1,760 studies were removed based on their abstract, with a further 18 removed after considering the full text. A total of 30 studies were considered relevant and had their data retrieved and analyzed. Due to the heterogeneity of focus and results from the refined studies, a narrative synthesis was favored.
CONCLUSION
Several promising candidate biomarkers suitable for clinical application in MS have been studied. It is recommended follow-up studies with larger sample sizes be completed on several potential biomarkers.
PubMed: 33381517
DOI: 10.3389/fmolb.2020.574133 -
BMJ Open Apr 2022To determine the accuracy of metabolomics in predicting hypertensive disorders in pregnancy.
OBJECTIVE
To determine the accuracy of metabolomics in predicting hypertensive disorders in pregnancy.
DESIGN
Systematic review of observational studies.
DATA SOURCES AND STUDY ELIGIBILITY CRITERIA
An electronic literature search was performed in June 2019 and February 2022. Two researchers independently selected studies published between 1998 and 2022 on metabolomic techniques applied to predict the condition; subsequently, they extracted data and performed quality assessment. Discrepancies were dealt with a third reviewer. The primary outcome was pre-eclampsia. Cohort or case-control studies were eligible when maternal samples were taken before diagnosis of the hypertensive disorder.
STUDY APPRAISAL AND SYNTHESIS METHODS
Data on study design, maternal characteristics, how hypertension was diagnosed, metabolomics details and metabolites, and accuracy were independently extracted by two authors.
RESULTS
Among 4613 initially identified studies on metabolomics, 68 were read in full text and 32 articles were included. Studies were excluded due to duplicated data, study design or lack of identification of metabolites. Metabolomics was applied mainly in the second trimester; the most common technique was liquid-chromatography coupled to mass spectrometry. Among the 122 different metabolites found, there were 23 amino acids and 21 fatty acids. Most of the metabolites were involved with ammonia recycling; amino acid metabolism; arachidonic acid metabolism; lipid transport, metabolism and peroxidation; fatty acid metabolism; cell signalling; galactose metabolism; nucleotide sugars metabolism; lactose degradation; and glycerolipid metabolism. Only citrate was a common metabolite for prediction of early-onset and late-onset pre-eclampsia. Vitamin D was the only metabolite in common for pre-eclampsia and gestational hypertension prediction. Meta-analysis was not performed due to lack of appropriate standardised data.
CONCLUSIONS AND IMPLICATIONS
Metabolite signatures may contribute to further insights into the pathogenesis of pre-eclampsia and support screening tests. Nevertheless, it is mandatory to validate such methods in larger studies with a heterogeneous population to ascertain the potential for their use in clinical practice.
PROSPERO REGISTRATION NUMBER
CRD42018097409.
Topics: Case-Control Studies; Female; Humans; Hypertension, Pregnancy-Induced; Mass Spectrometry; Metabolomics; Pre-Eclampsia; Pregnancy
PubMed: 35470187
DOI: 10.1136/bmjopen-2021-054697 -
Metabolites Dec 2022Cancers are the leading cause of death worldwide. The most common cancers include breast, lung, and colorectum. Salivary metabolome profiling is a novel non-invasive... (Review)
Review
Cancers are the leading cause of death worldwide. The most common cancers include breast, lung, and colorectum. Salivary metabolome profiling is a novel non-invasive method in oncological diagnosis. This systematic review was designed to answer the question "Are salivary metabolites reliable for the diagnosis of systemic cancers?". Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). Changes in salivary metabolome were most commonly determined in patients with breast cancer, gastrointestinal cancers, and lung cancer. Most studies involved unstimulated whole saliva as the diagnostic material, evaluated by different spectroscopic methods. Among the found saliva metabolites, the alterations in the metabolic pathways of amino acids and polyamines were most frequently observed, which showed significant predictive values in oncological diagnostics. The most frequently encountered risks of bias were the absence of data regarding blinding, sample size justification, and randomisation. In conclusion, salivary metabolites seem to be potentially reliable for detecting the most common systemic cancers. However, further research is desirable to confirm these outcomes and to detect new potential metabolic biomarkers in saliva.
PubMed: 36676953
DOI: 10.3390/metabo13010028