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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 -
Genes & Nutrition Apr 2023The predominant source of alcohol in the diet is alcoholic beverages, including beer, wine, spirits and liquors, sweet wine, and ciders. Self-reported alcohol intakes... (Review)
Review
The predominant source of alcohol in the diet is alcoholic beverages, including beer, wine, spirits and liquors, sweet wine, and ciders. Self-reported alcohol intakes are likely to be influenced by measurement error, thus affecting the accuracy and precision of currently established epidemiological associations between alcohol itself, alcoholic beverage consumption, and health or disease. Therefore, a more objective assessment of alcohol intake would be very valuable, which may be established through biomarkers of food intake (BFIs). Several direct and indirect alcohol intake biomarkers have been proposed in forensic and clinical contexts to assess recent or longer-term intakes. Protocols for performing systematic reviews in this field, as well as for assessing the validity of candidate BFIs, have been developed within the Food Biomarker Alliance (FoodBAll) project. The aim of this systematic review is to list and validate biomarkers of ethanol intake per se excluding markers of abuse, but including biomarkers related to common categories of alcoholic beverages. Validation of the proposed candidate biomarker(s) for alcohol itself and for each alcoholic beverage was done according to the published guideline for biomarker reviews. In conclusion, common biomarkers of alcohol intake, e.g., as ethyl glucuronide, ethyl sulfate, fatty acid ethyl esters, and phosphatidyl ethanol, show considerable inter-individual response, especially at low to moderate intakes, and need further development and improved validation, while BFIs for beer and wine are highly promising and may help in more accurate intake assessments for these specific beverages.
PubMed: 37076809
DOI: 10.1186/s12263-023-00726-1 -
Metabolites Jul 2023Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with five-year survival rates around 10%. The only curative option remains complete surgical... (Review)
Review
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with five-year survival rates around 10%. The only curative option remains complete surgical resection, but due to the delay in diagnosis, less than 20% of patients are eligible for surgery. Therefore, discovering diagnostic biomarkers for early detection is crucial for improving clinical outcomes. Metabolomics has become a powerful technology for biomarker discovery, and several metabolomic-based panels have been proposed for PDAC diagnosis, but these advances have not yet been translated into the clinic. Therefore, this review focused on summarizing metabolites identified for the early diagnosis of PDAC in the last five years. Bibliographic searches were performed in the PubMed, Scopus and WOS databases, using the terms "Biomarkers, Tumor", "Pancreatic Neoplasms", "Early Diagnosis", "Metabolomics" and "Lipidome" (January 2018-March 2023), and resulted in the selection of fourteen original studies that compared PDAC patients with subjects with other pancreatic diseases. These investigations showed amino acid and lipid metabolic pathways as the most commonly altered, reflecting their potential for biomarker research. Furthermore, other relevant metabolites such as glucose and lactate were detected in the pancreas tissue and body fluids from PDAC patients. Our results suggest that the use of metabolomics remains a robust approach to improve the early diagnosis of PDAC. However, these studies showed heterogeneity with respect to the metabolomics techniques used and further studies will be needed to validate the clinical utility of these biomarkers.
PubMed: 37512579
DOI: 10.3390/metabo13070872 -
The Journal of Nutrition Mar 2024The projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and...
BACKGROUND
The projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and progression. Identifying novel biomarkers in the preclinical or prodromal phase of dementia may be important for predicting early disease risk. Applying metabolomic techniques to prediagnostic samples in prospective studies provides the opportunity to identify potential disease biomarkers.
OBJECTIVE
The objective of this systematic review was to summarize the evidence on the associations between metabolite markers and risk of dementia and related dementia subtypes in human studies with a prospective design.
DESIGN
We searched PubMed, PsycINFO, and Web of Science databases from inception through December 8, 2023. Thirteen studies (mean/median follow-up years: 2.1-21.0 y) were included in the review.
RESULTS
Several metabolites detected in biological samples, including amino acids, fatty acids, acylcarnitines, lipid and lipoprotein variations, hormones, and other related metabolites, were associated with risk of developing dementia. Our systematic review summarized the adjusted associations between metabolites and dementia risk; however, our findings should be interpreted with caution because of the heterogeneity across the included studies and potential sources of bias. Further studies are warranted with well-designed prospective cohort studies that have defined study populations, longer follow-up durations, the inclusion of additional diverse biological samples, standardization of techniques in metabolomics and ascertainment methods for diagnosing dementia, and inclusion of other related dementia subtypes.
CONCLUSIONS
This study contributes to the limited systematic reviews on metabolomics and dementia by summarizing the prospective associations between metabolites in prediagnostic biological samples with dementia risk. Our review discovered additional metabolite markers associated with the onset of developing dementia and may help aid in the understanding of dementia etiology. The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/prospero/; registration ID: CRD42022357521).
Topics: Humans; Biomarkers; Dementia; Prospective Studies; Metabolomics
PubMed: 38219861
DOI: 10.1016/j.tjnut.2024.01.012 -
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 -
Gut Microbes Dec 2023Loss of response to therapy in inflammatory bowel disease (IBD) has led to a surge in research focusing on precision medicine. Three systematic reviews have been... (Review)
Review
Loss of response to therapy in inflammatory bowel disease (IBD) has led to a surge in research focusing on precision medicine. Three systematic reviews have been published investigating the associations between gut microbiota and disease activity or IBD therapy. We performed a systematic review to investigate the microbiome predictors of response to advanced therapy in IBD. Unlike previous studies, our review focused on predictors of response to therapy; so the included studies assessed microbiome predictors before the proposed time of response or remission. We also provide an update of the available data on mycobiomes and viromes. We highlight key themes in the literature that may serve as future biomarkers of treatment response: the abundance of fecal SCFA-producing bacteria and opportunistic bacteria, metabolic pathways related to butyrate synthesis, and non-butyrate metabolomic predictors, including bile acids (BAs), amino acids, and lipids, as well as mycobiome predictors of response.
Topics: Humans; Gastrointestinal Microbiome; Inflammatory Bowel Diseases; Feces; Fecal Microbiota Transplantation; Biomarkers
PubMed: 38044504
DOI: 10.1080/19490976.2023.2287073 -
Frontiers in Plant Science 2022Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under...
Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.
PubMed: 36570904
DOI: 10.3389/fpls.2022.1062952 -
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 -
Journal of Affective Disorders Nov 2022Postpartum depression (PPD) is the most frequent psychiatric complication during the postnatal period and its mechanisms are not fully understood. Metabolomics, can... (Review)
Review
BACKGROUND
Postpartum depression (PPD) is the most frequent psychiatric complication during the postnatal period and its mechanisms are not fully understood. Metabolomics, can quantitatively measure metabolites in a high-throughput method, and thus uncover the underlying pathophysiology of disease.
OBJECTIVES
In this study, we reviewed metabolomics studies conducted on PPD, aiming to understand the changes of metabolites in PPD patients and analyze the potential application of metabolomics in PPD prediction and diagnosis.
METHODS
Relevant articles were searched in PubMed, Google scholar, and Web of Science databases from January 2011 to July 2022. The metabolites involved were systematically examined and compared. MetaboAnalyst online software was applied to analyze metabolic pathways.
RESULTS
A total of 14 papers were included in this study. There were several highly reported metabolites, such as kynurenine, kynurenic acid, and eicosapentaenoic acid. Dysregulation of metabolic pathways involved amino acids metabolism, fatty acids metabolism, and steroids metabolism.
LIMITATIONS
The included studies are relatively inadequate, and further work is needed.
CONCLUSIONS
This study summarized significant metabolic alterations that provided clues for the prediction, diagnosis, and pathogenesis of PPD.
Topics: Biomarkers; Depression, Postpartum; Eicosapentaenoic Acid; Female; Humans; Kynurenic Acid; Kynurenine; Metabolomics; Postpartum Period; Steroids
PubMed: 36031003
DOI: 10.1016/j.jad.2022.08.043 -
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