Search

Recent literature suggests that markers of neuroaxonal damage, such as neurofilaments and tau protein, might serve as potential biomarkers for ALS. We conducted this systematic review and meta-analysis study to compare cerebrospinal fluid (CSF) and blood levels of total tau (t-tau), phosphorylated tau (p-tau), amyloid beta peptide 42 (Abeta-42), and neurofilaments in ALS patients and controls. A systematic search of Cochrane Library, PubMed, Embase, and ISI Web of Science was conducted on March 18, 2022, and updated on January 26, 2023. Observational studies that compared the concentrations of neurofilament light chain (NfL), neurofilament heavy chain (NFH), t-tau, p-tau, or Abeta-42 in CSF or peripheral blood of ALS patients and controls were included. Data from relevant studies were independently extracted and screened for quality using a standard tool, by at least two authors. Meta-analysis was conducted when a minimum of 3 studies reported the same biomarker within the same biofluid. A total of 100 studies were eligible for at least one meta-analysis. CSF and blood levels of NfL (standardized mean difference (SMD) [95% CI]; CSF: 1.46 [1.25–1.68]; blood: 1.35 [1.09–1.60]) and NFH (CSF: 1.32 [1.13–1.50], blood: 0.90 [0.58–1.22]) were significantly higher in ALS patients compared with controls. The pooled differences between ALS patients and controls were not significant for CSF t-tau, blood t-tau, and CSF Abeta-42, but CSF p-tau was lower in ALS patients (-0.27 [-0.47- -0.07]). Significantly decreased p-tau/t-tau ratios were found in ALS patients compared with controls (-0.84 [-1.16- -0.53]). Heterogeneity was considerable in most of our meta-analyses. CSF and blood neurofilament levels, as well as the CSF p-tau/t-tau ratio, might be potential candidates for improving ALS diagnosis. Further research is warranted to better understand the underlying mechanisms and the clinical implications of these biomarker alterations. [ABSTRACT FROM AUTHOR]

Background: BI 836880 is a humanized bispecific nanobody® that binds to and blocks vascular endothelial growth factor (VEGF) and angiopoietin-2 (Ang-2). A comprehensive biomarker and modeling approach is presented here that supported dose finding for BI 836880. Methods: Two Phase I dose-escalation studies (1336.1 [NCT02674152], 1336.6 [NCT02689505]) assessed BI 836880 in adults with confirmed locally advanced or metastatic solid tumors, refractory to standard therapy or for which standard therapy was not reliably effective. Two dosing schedules were investigated, 3 weeks (q3w) or once weekly (qw), starting at a dose of 40 mg. In a comprehensive biomarker approach, soluble pharmacodynamic markers (free and total plasma VEGF-A and Ang-2), as well as circulating angiogenic factors (soluble VEGF3, soluble Tie2 and placenta growth factor, amongst others) were analyzed to assess target engagement in peripheral blood for q3w doses. A Population based pharmacokinetics/pharmacodynamics (PopPK/PD) model was built using the limited Phase I dataset to support dose finding by simulations. In order to demonstrate drug activity in the tumor, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was applied. Results: DCE-MRI scans supported target engagement in the tumor. Free VEGF-A was depleted at all doses, whereas free Ang-2 decreased dose-dependently, reaching depletion in most patients from 360 mg q3w onwards. While total VEGF-A levels increased in a dose-dependent manner, reaching saturation at 360 mg q3w, total Ang-2 levels increased, but did not plateau. Angiogenic biomarkers showed changes from doses ≥ 360 mg q3w. PopPK/PD modeling showed that doses ≥ 360 mg q3w led to > 90% inhibition of free Ang-2 at steady-state in most patients. By increasing the dose to ≥ 500 mg q3w, > 90% of patients are expected to achieve this level. Conclusions: The comprehensive analyses of multiple target engagement markers support BI 836880 720 mg q3w as a biologically relevant monotherapy dose schedule. Trial registration: NCT02674152 and NCT02689505. [ABSTRACT FROM AUTHOR]

Background: Endometriosis is one of the most common gynaecological diseases, yet it lacks efficient biomarkers for early detection and unravels disease mechanisms. Proteomic profiling has revealed diverse patterns of protein changes in various clinical samples. Integrating and systematically analysing proteomics data can facilitate the development of biomarkers, expediting diagnosis and providing insights for potential clinical and therapeutic applications. Hence, this systematic review and meta-analysis aimed to explore potential non-invasive diagnostic biomarkers in various biological samples and therapeutic targets for endometriosis. Methods: Online databases, including Scopus, PubMed, Web of Science, MEDLINE, Embase via Ovid, and Google Scholar, were searched using MeSH terms. Two independent authors screened the articles, extracted the data, and assessed the methodological quality of the included studies. GO and KEGG analyses were performed to identify the pathways that were significantly enriched. Protein‑protein interaction and hub gene selection analyses were also conducted to identify biomarker networks for endometriosis. Results: Twenty-six observational studies with a total of 2,486 participants were included. A total of 644 differentially expressed proteins (180 upregulated and 464 downregulated) were identified from 9 studies. Proteins in peripheral blood exhibited a sensitivity and specificity of 38-100% and 59-99%, respectively, for detecting endometriosis, while proteins in urine had a sensitivity of 58-91% and specificity of 76-93%. Alpha-1-antitrypsin, albumin, and vitamin D binding proteins were significantly DEPs in both serum and urine. Complement C3 is commonly expressed in serum, menstrual blood, and cervical mucus. Additionally, S100-A8 is commonly expressed in both menstrual blood and cervical mucus. Haptoglobin is commonly detected in both serum and plasma, whereas cathepsin G is found in urine, serum, and plasma. GO and KEGG enrichment analyses revealed that proteoglycans in cancer pathways, which regulate cell-to-cell interactions, modulate the extracellular matrix, and promote the proliferation and invasion of endometrial cells, are commonly enriched in serum and urine. Conclusion: This comprehensive study revealed potential proteomes that were significantly differentially expressed in women with endometriosis utilizing various non-invasive clinical samples. Exploring common differentially expressed proteins in various biological samples provides insights into the diagnosis and pathophysiology of endometriosis, as well as potential clinical and therapeutic applications. [ABSTRACT FROM AUTHOR]

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, the entire medical oncology field has been revolutionized by the introduction of immune checkpoints inhibitors. Despite success in a variety of malignancies, responses typically only occur in a small percentage of patients for any given histology or treatment regimen. There are also concerns that immunotherapies are associated with immune-related toxicity as well as high costs. As such, identifying biomarkers to determine which patients are likely to derive clinical benefit from which immunotherapy and/or be susceptible to adverse side effects is a compelling clinical and social need. In addition, with several new immunotherapy agents in different phases of development, and approved therapeutics being tested in combination with a variety of different standard of care treatments, there is a requirement to stratify patients and select the most appropriate population in which to assess clinical efficacy. The opportunity to design parallel biomarkers studies that are integrated within key randomized clinical trials could be the ideal solution. Sample collection (fresh and/or archival tissue, PBMC, serum, plasma, stool, etc.) at specific points of treatment is important for evaluating possible biomarkers and studying the mechanisms of responsiveness, resistance, toxicity and relapse. This white paper proposes the creation of a network to facilitate the sharing and coordinating of samples from clinical trials to enable more in-depth analyses of correlative biomarkers than is currently possible and to assess the feasibilities, logistics, and collated interests. We propose a high standard of sample collection and storage as well as exchange of samples and knowledge through collaboration, and envisage how this could move forward using banked samples from completed studies together with prospective planning for ongoing and future clinical trials. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that autonomic dysfunction and persistent systemic inflammation are common clinical features in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID. However, there is limited knowledge regarding their potential association with circulating biomarkers and illness severity in these conditions. Methods: This single-site, prospective, cross-sectional, pilot cohort study aimed to distinguish between the two patient populations by using self-reported outcome measures and circulating biomarkers of endothelial function and systemic inflammation status. Thirty-one individuals with ME/CFS, 23 individuals with long COVID, and 31 matched sedentary healthy controls were included. All study participants underwent non-invasive cardiovascular hemodynamic challenge testing (10 min NASA lean test) for assessment of orthostatic intolerance. Regression analysis was used to examine associations between outcome measures and circulating biomarkers in the study participants. Classification across groups was based on principal component and discriminant analyses. Results: Four ME/CFS patients (13%), 1 with long COVID (4%), and 1 healthy control (3%) presented postural orthostatic tachycardia syndrome (POTS) using the 10-min NASA lean test. Compared with matched healthy controls, ME/CFS and long COVID subjects showed higher levels of ET-1 (p < 0.05) and VCAM-1 (p < 0.001), and lower levels of nitrites (NOx assessed as NO2- + NO3-) (p < 0.01). ME/CFS patients also showed higher levels of serpin E1 (PAI-1) and E-selectin than did both long COVID and matched control subjects (p < 0.01 in all cases). Long COVID patients had lower TSP-1 levels than did ME/CFS patients and matched sedentary healthy controls (p < 0.001). As for inflammation biomarkers, both long COVID and ME/CFS subjects had higher levels of TNF-α than did matched healthy controls (p < 0.01 in both comparisons). Compared with controls, ME/CFS patients had higher levels of IL-1β (p < 0.001), IL-4 (p < 0.001), IL-6 (p < 0.01), IL-10 (p < 0.001), IP-10 (p < 0.05), and leptin (p < 0.001). Principal component analysis supported differentiation between groups based on self-reported outcome measures and biomarkers of endothelial function and inflammatory status in the study population. Conclusions: Our findings revealed that combining biomarkers of endothelial dysfunction and inflammation with outcome measures differentiate ME/CFS and Long COVID using robust discriminant analysis of principal components. Further research is needed to provide a more comprehensive characterization of these underlying pathomechanisms, which could be promising targets for therapeutic and preventive strategies in these conditions. [ABSTRACT FROM AUTHOR]

Background: Due to their complexity and to the presence of common clinical features, differentiation between asthma and chronic obstructive pulmonary disease (COPD) can be a challenging task, complicated in such cases also by asthma–COPD overlap syndrome. The distinct immune/inflammatory and structural substrates of COPD and asthma are responsible for significant differences in the responses to standard pharmacologic treatments. Therefore, an accurate diagnosis is of central relevance to assure the appropriate therapeutic intervention in order to achieve safe and effective patient care. Induced sputum (IS) accurately mirrors inflammation in the airways, providing a more direct picture of lung cell metabolism in comparison to those specimen that reflect analytes in the systemic circulation. Methods: An integrated untargeted metabolomics and lipidomics analysis was performed in IS of asthmatic (n = 15) and COPD (n = 22) patients based on Ultra-High-Pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and UHPLC–tandem MS (UHPLC-MS/MS). Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to resulting dataset. The analysis of main enriched metabolic pathways and the association of the preliminary metabolites/lipids pattern identified to clinical parameters of asthma/COPD differentiation were explored. Multivariate ROC analysis was performed in order to determine the discriminatory power and the reliability of the putative biomarkers for diagnosis between COPD and asthma. Results: PLS-DA indicated a clear separation between COPD and asthmatic patients. Among the 15 selected candidate biomarkers based on Variable Importance in Projection scores, putrescine showed the highest score. A differential IS bio-signature of 22 metabolites and lipids was found, which showed statistically significant variations between asthma and COPD. Of these 22 compounds, 18 were decreased and 4 increased in COPD compared to asthmatic patients. The IS levels of Phosphatidylethanolamine (PE) (34:1), Phosphatidylglycerol (PG) (18:1;18:2) and spermine were significantly higher in asthmatic subjects compared to COPD. Conclusions: This is the first pilot study to analyse the IS metabolomics/lipidomics signatures relevant in discriminating asthma vs COPD. The role of polyamines, of 6-Hydroxykynurenic acid and of d-rhamnose as well as of other important players related to the alteration of glycerophospholipid, aminoacid/biotin and energy metabolism provided the construction of a diagnostic model that, if validated on a larger prospective cohort, might be used to rapidly and accurately discriminate asthma from COPD. [ABSTRACT FROM AUTHOR]

Background: Idiopathic Pulmonary Fibrosis (IPF) is a type of chronic interstitial pneumonia, often fatal, with elusive causes and a bleak prognosis. Its treatment options are limited and largely ineffective. Early detection and precise diagnosis are pivotal in managing the disease effectively and enhancing patient survival rates. Recently, the quest for trustworthy biomarkers for IPF has gained momentum. Notably, emerging studies indicate that circular RNAs (circRNAs) found in exosomes may hold significant potential as valuable diagnostic markers. Methods: In this study, we initially explored the expression profile of circRNAs in exosomes sourced from the blood of IPF patients and healthy volunteers, employing a human circRNA microarray. We then utilized RT-qPCR to corroborate the dysregulated circRNAs identified by the microarray during the training phase. Next, the circRNAs that displayed a significant increase during the training phase were selected for further validation in a larger cohort encompassing 113 IPF patients and 76 healthy volunteers. Ultimately, the expression level and function of hsa_circ_0044226 were substantiated through a series of in vivo and in vitro experiments. Results: Utilizing a human circRNA microarray, we identified 11 dysregulated circRNAs in the exosomes derived from the blood of IPF patients and control volunteers. Subsequent RT-qPCR analysis revealed significant increases in three circRNAs (hsa_circ_0044226, hsa_circ_0004099, hsa_circ_0008898) within the IPF patients. Notably, hsa_circ_0044226 was markedly elevated in patients experiencing acute exacerbation of IPF (AE-IPF) compared to those with stable IPF (S-IPF). Additionally, an upregulation of hsa_circ_0044226 was observed in the blood exosomes derived from a bleomycin-induced IPF mouse model. Conclusion: The expression levels of hsa_circ_0044226, hsa_circ_0004099, and hsa_circ_0008898 in plasma exosomes introduce a new paradigm of biomarkers for the diagnosis and progression of IPF. [ABSTRACT FROM AUTHOR]

Background: Bioactive lipids involved in the progression of various diseases. Nevertheless, there is still a lack of biomarkers and relative regulatory targets. The lipidomic analysis of the samples from platinum-resistant in gastric cancer patients is expected to help us further improve our understanding of it. Methods: We employed LC–MS based untargeted lipidomic analysis to search for potential candidate biomarkers for platinum resistance in GC patients. Partial least squares discriminant analysis (PLS-DA) and variable importance in projection (VIP) analysis were used to identify differential lipids. The possible molecular mechanisms and targets were obtained by metabolite set enrichment analysis and potential gene network screened. Finally, verified them by immunohistochemical of a tissue microarray. Results: There were 71 differential lipid metabolites identified in GC samples between the chemotherapy-sensitivity group and the chemotherapy resistance group. According to Foldchange (FC) value, VIP value, P values (FC > 2, VIP > 1.5, p < 0.05), a total of 15 potential biomarkers were obtained, including MGDG(43:11)-H, Cer(d18:1/24:0) + HCOO, PI(18:0/18:1)-H, PE(16:1/18:1)-H, PE(36:2) + H, PE(34:2p)-H, Cer(d18:1 + hO/24:0) + HCOO, Cer(d18:1/23:0) + HCOO, PC(34:2e) + H, SM(d34:0) + H, LPC(18:2) + HCOO, PI(18:1/22:5)-H, PG(18:1/18:1)-H, Cer(d18:1/24:0) + H and PC(35:2) + H. Furthermore, we obtained five potential key targets (PLA2G4A, PLA2G3, DGKA, ACHE, and CHKA), and a metabolite-reaction-enzyme-gene interaction network was built to reveal the biological process of how they could disorder the endogenous lipid profile of platinum resistance in GC patients through the glycerophospholipid metabolism pathway. Finally, we further identified PLA2G4A and ACHE as core targets of the process by correlation analysis and tissue microarray immunohistochemical verification. Conclusion: PLA2G4A and ACHE regulated endogenous lipid profile in the platinum resistance in GC patients through the glycerophospholipid metabolism pathway. The screening of lipid biomarkers will facilitate earlier precision medicine interventions for chemotherapy-resistant gastric cancer. The development of therapies targeting PLA2G4A and ACHE could enhance platinum chemotherapy effectiveness. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

Background: Bone is one of the major target tissues for Insulin-like Growth Factor I (IGF-I). Low doses of IGF-I were able to improve liver-associated osteopenia. In the present work, a model of partial IGF-I deficiency was used in order to provide insight into the mechanisms of the beneficial actions of IGF-I replacement therapy in bone., Methods: Several proteins involved in osteoblastic/osteocyte and osteoclastic differentiation and activity were studied in the three experimental groups: control (CO) group (wild type mice, Igf+/+, n=10), heterozygous Igf+/- group with partial IGF-I deficiency (Hz, n=10), and heterozygous Igf+/- mice treated with IGF-I for 10 days (Hz+IGF-I, n=10)., Results: Data in this paper confirm that the simple partial IGF-I deficiency is responsible for osteopenia, determined by densitometry and histopathology. These findings are associated with a reduced gene expression of osteoprotegerin, sclerostin, calcitonin receptor (CTR), insulin-like growth factor binding protein 5 and RUNX2. IGF-I replacement therapy normalized CTR gene expression and reduced markers of osteoclastic activity., Conclusions: Low doses of IGF-I constituted a real replacement therapy that normalized IGF-I serum levels improving the expression of most of these proteins closely involved in bone-forming, and reducing bone resorption by mechanisms related to osteoprotegerin, RANKL and PTH receptor.

Background: Clear cell renal cell carcinoma (ccRCC) represents the most invasive and common adult kidney neoplasm. Mounting evidence suggests that microRNAs (miRNAs) are important regulators of gene expression. But their function in tumourigenesis in this tumour type remains elusive. With the development of high throughput technologies such as microarrays and NGS, aberrant miRNA expression has been widely observed in ccRCC. Systematic and integrative analysis of multiple microRNA expression datasets may reveal potential mechanisms by which microRNAs contribute to ccRCC pathogenesis. Methods: We collected 5 public microRNA expression datasets in ccRCC versus non-matching normal renal tissues from GEO database and published literatures. We analyzed these data sets with an integrated bioinformatics framework to identify expression signatures. The framework incorporates a novel statistic method for abnormal gene expression detection and an in-house developed predictor to assess the regulatory activity of microRNAs. We then mapped target genes of DE-miRNAs to different databases, such as GO, KEGG, GeneGo etc, for functional enrichment analysis. Results: Using this framework we identified a consistent panel of eleven deregulated miRNAs shared by five independent datasets that can distinguish normal kidney tissues from ccRCC. After comparison with 3 RNA-seq based microRNA profiling studies, we found that our data correlated well with the results of next generation sequencing. We also discovered 14 novel molecular pathways that are likely to play a role in the tumourigenesis of ccRCC. Conclusions: The integrative framework described in this paper greatly improves the inter-dataset consistency of microRNA expression signatures. Consensus expression profile should be identified at pathway or network level to address the heterogeneity of cancer. The DE-miRNA signature and novel pathways identified herein could provide potential biomarkers for ccRCC that await further validation. [ABSTRACT FROM AUTHOR]

Background: Neuroendocrine tumors (NETs) early diagnosis is a clinical challenge that require a deep understanding of molecular and genetic features of this heterogeneous group of neoplasms. However, few biomarkers exist to aid diagnosis and to predict prognosis and treatment response. In the oncological field, tumor-educated platelets (TEPs) have been implicated as central players in the systemic and local responses to tumor growth, thereby altering tumor specific RNA profile. Although TEPs have been found to be enriched in RNAs, few studies have investigated the potential of a type of RNA, circular RNAs (circRNA), as platelet-derived biomarkers for cancer. In this proof-of-concept study, we aim to demonstrate whether the circRNAs signature of tumor educated platelets can be used as a liquid biopsy biomarker for the detection of gastroenteropancreatic (GEP)-NETs and the prediction of the early response to treatment. Methods: We performed a 24-months, prospective proof-of-concept study in men and women with histologically proven well-differentiated G1-G2 GEP-NET, aged 18–80 years, naïve to treatment. We performed a RNAseq analysis of circRNAs obtained from TEPs samples of 10 GEP-NETs patients at baseline and after 3 months from therapy (somatostatin analogs or surgery) and from 5 patients affected by non-malignant endocrinological diseases enrolled as a control group. Results: Statistical analysis based on p < 0.05 resulted in the identification of 252 circRNAs differentially expressed between GEP-NET and controls of which 109 were up-regulated and 143 were down-regulated in NET patients. Further analysis based on an FDR value ≤ 0.05 resulted in the selection of 5 circRNAs all highly significant downregulated. The same analysis on GEP-NETs at baseline and after therapy in 5 patients revealed an average of 4983 remarkably differentially expressed circRNAs between follow-up and baseline samples of which 2648 up-regulated and 2334 down-regulated, respectively. Applying p ≤ 0.05 and FDR ≤ 0.05 filters, only 3/5 comparisons gave statistically significant results. Conclusions: Our findings identified for the first time a circRNAs signature from TEPs as potential diagnostic and predictive biomarkers for GEP-NETs. [ABSTRACT FROM AUTHOR]

Cancer remains the leading cause of death around the world. In cancer treatment, over 50% of cancer patients receive radiotherapy alone or in multimodal combinations with other therapies. One of the adverse consequences after radiation exposure is the occurrence of radiation-induced tissue fibrosis (RIF), which is characterized by the abnormal activation of myofibroblasts and the excessive accumulation of extracellular matrix. This phenotype can manifest in multiple organs, such as lung, skin, liver and kidney. In-depth studies on the mechanisms of radiation-induced fibrosis have shown that a variety of extracellular signals such as immune cells and abnormal release of cytokines, and intracellular signals such as cGAS/STING, oxidative stress response, metabolic reprogramming and proteasome pathway activation are involved in the activation of myofibroblasts. Tissue fibrosis is extremely harmful to patients' health and requires early diagnosis. In addition to traditional serum markers, histologic and imaging tests, the diagnostic potential of nuclear medicine techniques is emerging. Anti-inflammatory and antioxidant therapies are the traditional treatments for radiation-induced fibrosis. Recently, some promising therapeutic strategies have emerged, such as stem cell therapy and targeted therapies. However, incomplete knowledge of the mechanisms hinders the treatment of this disease. Here, we also highlight the potential mechanistic, diagnostic and therapeutic directions of radiation-induced fibrosis. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence suggests that hepatocellular carcinoma (HCC) stem cells (LCSCs) play an essential part in HCC recurrence, metastasis, and chemotherapy and radiotherapy resistance. Multiple studies have demonstrated that stemness-related genes facilitate the progression of tumors. However, the mechanism by which stemness-related genes contribute to HCC is not well understood. Here, we aim to construct a stemness-related score (SRscores) model for deeper analysis of stemness-related genes, assisting with the prognosis and individualized treatment of HCC patients.Further, we found that the gene LPCAT1 was highly expressed in tumor tissues by immunohistochemistry, and sphere-forming assay revealed that knockdown of LPCAT1 inhibited the sphere-forming ability of hepatocellular carcinoma cells. Methods: We used the TCGA-LIHC dataset to screen stemness-related genes of HCC from the MSigDB database. Prognosis, tumor microenvironment, immunological checkpoints, tumor immune dysfunction, rejection, treatment sensitivity, and putative biological pathways were examined. Random forest created the SRscores model. The anti-PD-1/anti-CTLA4 immunotherapy, tumor mutational burden, medication sensitivity, and cancer stem cell index were compared between the high- and low-risk score groups. We also examined risk scores for different cell types using single-cell RNA sequencing data and correlated transcription factor activity in cancer stem cells with SRscores genes. Finally, we tested core marker expression and biological functions. Results: Patients can be divided into two subtypes (Cluster1 and Cluster2) based on the TCGA-LIHC dataset's identification of 11 stemness-related genes. Additionally, a SRscores was developed based on subtypes. Cluster2 and the group with the lowest SRscores had superior survival and immunotherapy response than Cluster1 and the group with the highest SRscores. The group with a high SRscores was significantly more enriched in classical tumor pathways than the group with a low SRscores. Multiple transcription factors and SRscores genes are correlated. The core gene LPCAT1 is highly expressed in rat liver cancer tissues and promotes tumor cell sphere formation. Conclusion: A SRscores model can be utilized to predict the prognosis of HCC patients as well as their response to immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a multifactorial illness that affects many body systems including the immune, nervous, endocrine, cardiovascular, and urinary systems. There is currently no universal diagnostic marker or targeted treatment for ME/CFS. Urine is a non-invasive sample that provides biomarkers that may have the potential to be used in a diagnostic capacity for ME/CFS. While there are several studies investigating urine-based biomarkers for ME/CFS, there are no published systematic reviews to summarise existing evidence of these markers. The aim of this systematic review was to compile and appraise literature on urinary-based biomarkers in ME/CFS patients compared with healthy controls. Methods: Three databases: Embase, PubMed, and Scopus were searched for articles pertaining to urinary biomarkers for ME/CFS compared with healthy controls published between December 1994 to December 2022. The final articles included in this review were determined through application of specific inclusion and exclusion criteria. Quality and bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Case Control Studies. A meta-analysis according to Cochrane guidelines was conducted on select studies, in particular, those that investigate urinary free cortisol levels in ME/CFS patients compared to healthy controls using the program STATA 17. Results: Twenty-one studies were included in this review. All of the studies investigated urinary-based markers in ME/CFS patients compared with healthy controls. The reported changes in urinary outputs include urinary free cortisol (38.10%), carnitine (28.6%), iodine (4.76%), and the metabolome (42.86%). In most cases, there was minimal overlap in the main outcomes measured across the studies, however, differences in urinary free cortisol between ME/CFS patients and healthy controls were commonly reported. Seven studies investigating urinary free cortisol were included in the meta-analysis. While there were significant differences found in urinary free cortisol levels in ME/CFS patients, there was also substantial heterogeneity across the included studies that makes drawing conclusions difficult. Conclusions: There is limited evidence suggesting a consistent and specific potential urinary-based biomarker for ME/CFS. Further investigations using more standardised methodologies and more stringent case criteria may be able to identify pathophysiological differences with diagnostic potential in ME/CFS patients compared with healthy controls. [ABSTRACT FROM AUTHOR]