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Objectives: Greater vulnerability of Black vs. White individuals to cardiovascular disease (CVD) and chronic kidney disease (CKD) is well charted in the United States, but studies involving sub-Saharan blacks are scarce., Methods: Baseline data (2021-2024) were collected in 168 sub-Saharan Blacks and 93 European Whites in an ongoing clinical trial (NCT04299529), using standardized patient selection criteria. Data included clinical and biochemical risk factors, ECG and echocardiographic traits, Framingham CVD risk, CKD grades (KDIGO 2024), self-assessed symptoms (WHO questionnaire), and urinary proteomic profiles predictive of left ventricular dysfunction (LVD) and CKD, HF1, and CKD273, respectively. Racial comparisons rested on unadjusted and multivariable-adjusted analyses., Results: Despite being younger (60.4 vs. 68.3 years), blacks had a worse risk profile, as evidenced by higher diabetes prevalence, higher BMI, faster heart rate, unfavourable serum cholesterol fractions, lower estimated glomerular filtration rate, microalbuminuria, and sedentary lifestyle. This resulted in blacks having higher 10-year CVD risk, higher heart age (index of vascular ageing with chronological age as reference), and a worse CKD grades. In both races, CKD273 increased with CKD grade, but CKD273 and HF1 were not different by race. These observations were robust in subgroup and adjusted analyses., Conclusion: This study did not differentiate host (genetic, molecular, and pathogenic) from environmental drivers of disease. Nonetheless, the findings call for a multipronged and comprehensive implementation of innovative health policies in sub-Saharan countries. Education, research, empowerment of stakeholders, and international learned societies connecting experts from a wide array of disciplines should vigorously sustain this effort., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

The field of clinical proteomics has seen enormous growth in the past 20 years, with over 40,000 scientific manuscripts published to date. At the same time, actual clinical application of the reported findings is obviously scarce. In this viewpoint article, we discuss the key issues that may be responsible for this apparent lack of success. We conclude that success must not be assessed based on the number of publications, but via the impact on patient management and treatment. We proceed with specific suggestions for potential solutions, which include keeping a strict focus on potential patient benefit. We hope this article can help shape the field, so it can in fact deliver on its realistic promise to bring significant improvement in management and care to patients., (© 2025 The Author(s). PROTEOMICS published by Wiley‐VCH GmbH.)

Aims: This study aimed to explore the effect of discontinuation of long-term spironolactone treatment on markers of kidney function in individuals with type 2 diabetes (T2D) at high risk of kidney disease enrolled in the Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria (PRIORITY) study., Materials and Methods: An observational study following the nested randomised part of the PRIORITY study was conducted. A total of 115 individuals with T2D and normoalbuminuria but high risk for progression based on urinary proteomics, randomised to daily spironolactone (n = 50) or placebo (n = 65) for a median of 2.5 years, were re-examined approximately 6 weeks after the final visit in the PRIORITY study. Primary endpoint was relative change in geometric mean of urinary albumin-creatinine ratio (UACR) between the final visit in PRIORITY (baseline) and follow-up. Secondary endpoints were change in estimated glomerular filtration rate (eGFR), systolic blood pressure (SBP) and serum potassium., Results: No change in UACR was observed in neither the spironolactone (geometric mean change: 17%; 95% CI -12, 55; p = 0.28) nor the placebo (5%; 95% CI -13, 26; p = 0.63) group at follow-up. No difference in UACR between the groups was observed at follow-up (relative difference in geometric mean: 11%, 95% CI -26, 67; p = 0.60). For eGFR and SBP, an increase after discontinuation of spironolactone was observed, as well as for SBP after placebo discontinuation. Potassium levels were lower after discontinuation of spironolactone, but higher after placebo discontinuation (all p < 0.05)., Conclusions: UACR did not change after discontinuation of long-term treatment with spironolactone. However, an increase in eGFR was observed supporting a haemodynamic effect of spironolactone in the kidneys., (© 2024 John Wiley & Sons Ltd.)

Naturally occurring fragments of collagen type I alpha 1 chain (COL1A1) have been previously associated with chronic kidney disease (CKD), with some fragments showing positive and others negative associations. Using urinary peptidome data from healthy individuals (n = 1131) and CKD patients (n = 5585) this aspect was investigated in detail. Based on the hypothesis that many collagen peptides are derived not from the full, mature collagen molecule, but from (larger) collagen degradation products, relationships between COL1A1 peptides containing identical sequences were investigated, with the smaller (offspring) peptide being a possible degradation product of the larger (parent) one. The strongest correlations were found for relationships where the parent differed by a maximum of three amino acids from the offspring, indicating an exopeptidase-regulated stepwise degradation process. Regression analysis indicated that CKD affects this degradation process. A comparison of matched CKD patients and control individuals (n = 612 each) showed that peptides at the start of the degradation process were consistently downregulated in CKD, indicating an attenuation of COL1A1 endopeptidase-mediated degradation. However, as these peptides undergo further degradation, likely mediated by exopeptidases, this downregulation can become less significant or even reverse, leading to an upregulation of later-stage fragments and potentially explaining the inconsistencies observed in previous studies., (© 2024 The Author(s). Proteomics published by Wiley‐VCH GmbH.)

Introduction: Prostate cancer (PCa) is the most frequently diagnosed cancer among men. A major clinical need is to accurately predict clinically significant PCa (csPCa). A proteomics-based 19-biomarker model (19-BM) was previously developed using capillary electrophoresis-mass spectrometry (CE-MS) and validated in close to 1,000 patients at risk for PCa. This study aimed to validate 19-BM in a multicenter prospective cohort of 101 biopsy-naive patients using current diagnostic pathways., Methods: Urine samples from 101 patients with suspicious of PCa were analyzed using CE-MS. All patients underwent multiparametric or magnetic resonance imaging (mpMRI) using a 3-T system. The 19-BM score was estimated using support vector machine-based software (MosaCluster v1.7.0), employing the previously published cut-off criterion of -0.07. Diagnostic nomograms were investigated along with mpMRI., Results: Independent validation of 19-BM yielded a sensitivity of 77% and a specificity of 85% (AUC:0.81). This performance surpassed those of prostate-specific antigen (PSA; AUC:0.56) and PSA density (AUC:0.69). For PI-RADS≤ 3 patients, 19-BM showed a sensitivity of 86% and a specificity of 88%. Integrating 19-BM with mpMRI resulted in significantly better accuracy (AUC:0.90) compared to individual investigations alone (AUC19BM = 0.81; p = 0.004 and AUCmpMRI: 0.79; p = 0.001). Examining the decision curve analysis, 19-BM with mpMRI surpassed other approaches for the prevailing risk interval from a 30% cut-off., Conclusions: 19-BM exhibited favorable reproducibility for the prediction of csPCa. In patients with PI-RADS ≤3, 19-BM correctly classified 88% of the patients with insignificant PCa at the cost of 1 missed csPCa patient. Utilizing the 19-BM test could prove valuable in complementing mpMRI and reducing the need for unnecessary biopsies., (© 2024 S. Karger AG, Basel.)

With urinary proteomics profiling (UPP) as exemplary omics technology, this review describes a workflow for the analysis of omics data in large study populations. The proposed workflow includes: (i) planning omics studies and sample size considerations; (ii) preparing the data for analysis; (iii) preprocessing the UPP data; (iv) the basic statistical steps required for data curation; (v) the selection of covariables; (vi) relating continuously distributed or categorical outcomes to a series of single markers (e.g., sequenced urinary peptide fragments identifying the parental proteins); (vii) showing the added diagnostic or prognostic value of the UPP markers over and beyond classical risk factors, and (viii) pathway analysis to identify targets for personalized intervention in disease prevention or treatment. Additionally, two short sections respectively address multiomics studies and machine learning. In conclusion, the analysis of adverse health outcomes in relation to omics biomarkers rests on the same statistical principle as any other data collected in large population or patient cohorts. The large number of biomarkers, which have to be considered simultaneously requires planning ahead how the study database will be structured and curated, imported in statistical software packages, analysis results will be triaged for clinical relevance, and presented., (© 2023 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd.)

Peptides carry important functions in normal physiological and pathophysiological processes and can serve as clinically useful biomarkers. Given the ability to diffuse passively across endothelial barriers, endogenous peptides can be examined in several body fluids, including among others urine, blood, and cerebrospinal fluid. This review article provides an update on the recently published literature that reports on investigating native peptides in body fluids using mass spectrometry-based platforms, specifically those studies that focus on the application of peptides as biomarkers to improve clinical management. We emphasize on the critical evaluation of their clinical value, how close they are to implementation, and the associated challenges and potential solutions to facilitate clinical implementation. During the last 5 years, numerous studies have been published, demonstrating the increased interest in mass spectrometry for the assessment of endogenous peptides as potential biomarkers. Importantly, the presence of few successful examples of implementation in patients' management and/or in the context of clinical trials indicates that the peptide biomarker field is evolving. Nevertheless, most studies still report evidence based on small sample size, while validation phases are frequently missing. Therefore, a gap between discovery and implementation still exists., (© 2023 John Wiley & Sons Ltd.)

Objective: Heart failure (HF) is characterised by collagen deposition. Urinary proteomic profiling (UPP) followed by peptide sequencing identifies parental proteins, for over 70% derived from collagens. This study aimed to refine understanding of the antifibrotic action of spironolactone., Methods: In this substudy (n=290) to the Heart 'Omics' in Ageing Study trial, patients were randomised to usual therapy combined or not with spironolactone 25-50 mg/day and followed for 9 months. The analysis included 1498 sequenced urinary peptides detectable in ≥30% of patients and carboxyterminal propeptide of procollagen I (PICP) and PICP/carboxyterminal telopeptide of collagen I (CITP) as serum biomarkers of COL1A1 synthesis. After rank normalisation of biomarker distributions, between-group differences in their changes were assessed by multivariable-adjusted mixed model analysis of variance. Correlations between the changes in urinary peptides and in serum PICP and PICP/CITP were compared between groups using Fisher's Z transform., Results: Multivariable-adjusted between-group differences in the urinary peptides with error 1 rate correction were limited to 27 collagen fragments, of which 16 were upregulated (7 COL1A1 fragments) on spironolactone and 11 downregulated (4 COL1A1 fragments). Over 9 months of follow-up, spironolactone decreased serum PICP from 81 (IQR 66-95) to 75 (61-90) µg/L and PICP/CITP from 22 (17-28) to 18 (13-26), whereas no changes occurred in the control group, resulting in a difference (spironolactone minus control) expressed in standardised units of -0.321 (95% CI 0.0007). Spironolactone did not affect the correlations between changes in urinary COL1A1 fragments and in PICP or the PICP/CITP ratio., Conclusions: Spironolactone decreased serum markers of collagen synthesis and predominantly downregulated urinary collagen-derived peptides, but upregulated others. The interpretation of these opposite UPP trends might be due to shrinking the body-wide pool of collagens, explaining downregulation, while some degree of collagen synthesis must be maintained to sustain vital organ functions, explaining upregulation. Combining urinary and serum fibrosis markers opens new avenues for the understanding of the action of antifibrotic drugs., Trial Registration Number: NCT02556450., Competing Interests: Competing interests: JS and AL are employees of Mosaiques-Diagnostics, Hanover, Germany. HM is the co-founder and co-owner of Mosaiques-Diagnostics. The other authors declare no conflict of interest., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background/objectives: Survival prospects following SARS-CoV-2 infection may extend beyond the acute phase, influenced by various factors including age, health conditions, and infection severity; however, this topic has not been studied in detail. Therefore, within this study, the mortality risk post-acute COVID-19 in the CRIT-COV-U cohort was investigated., Methods: Survival data from 651 patients that survived an acute phase of COVID-19 were retrieved and the association between urinary peptides and future death was assessed. Data spanning until December 2023 were collected from six countries, comparing mortality trends with age- and sex-matched COVID-19-negative controls. A death prediction classifier was developed and validated using pre-existing urinary peptidomic datasets., Results: Notably, 13.98% of post-COVID-19 patients succumbed during the follow-up, with mortality rates significantly higher than COVID-19-negative controls, particularly evident in younger individuals (<65 years). These data for the first time demonstrate that SARS-CoV-2 infection highly significantly increases the risk of mortality not only during the acute phase of the disease but also beyond for a period of about one year. In our study, we were further able to identify 201 urinary peptides linked to mortality. These peptides are fragments of albumin, alpha-2-HS-glycoprotein, apolipoprotein A-I, beta-2-microglobulin, CD99 antigen, various collagens, fibrinogen alpha, polymeric immunoglobulin receptor, sodium/potassium-transporting ATPase, and uromodulin and were integrated these into a predictive classifier (DP201). Higher DP201 scores, alongside age and BMI, significantly predicted death., Conclusions: The peptide-based classifier demonstrated significant predictive value for mortality in post-acute COVID-19 patients, highlighting the utility of urinary peptides in prognosticating post-acute COVID-19 mortality, offering insights for targeted interventions. By utilizing these defined biomarkers in the clinic, risk stratification, monitoring, and personalized interventions can be significantly improved. Our data also suggest that mortality should be considered as one possible symptom or a consequence of post-acute sequelae of SARS-CoV-2 infection, a fact that is currently overlooked.

The extracellular matrix (ECM) is composed of collagens, ECM glycoproteins, and proteoglycans (also named core matrisome proteins) that are critical for tissue structure and function, and matrisome-associated proteins that balance the production and degradation of the ECM proteins. The identification and quantification of core matrisome proteins using mass spectrometry is often hindered by their low abundance and their propensity to form macromolecular insoluble structures. In this study, we aimed to investigate the added value of decellularization in identifying and quantifying core matrisome proteins in mouse kidney. The decellularization strategy combined freeze-thaw cycles and sodium dodecyl sulphate treatment. We found that decellularization preserved 95% of the core matrisome proteins detected in non-decellularized kidney and revealed few additional ones. Decellularization also led to an average of 59 times enrichment of 96% of the core matrisome proteins as the result of the successful removal of cellular and matrisome-associated proteins. However, the enrichment varied greatly among core matrisome proteins, resulting in a misrepresentation of the native ECM composition in decellularized kidney. This should be brought to the attention of the matrisome research community, as it highlights the need for caution when interpreting proteomic data obtained from a decellularized organ., (© 2024 The Author(s). PROTEOMICS published by Wiley‐VCH GmbH.)

Objectives: Hypertension is a common condition worldwide; however, its underlying mechanisms remain largely unknown. This study aimed to identify urinary peptides associated with hypertension to further explore the relevant molecular pathophysiology., Methods: Peptidome data from 2876 individuals without end-organ damage were retrieved from the Human Urinary Proteome Database, belonging to general population (discovery) or type 2 diabetic (validation) cohorts. Participants were divided based on systolic blood pressure (SBP) and diastolic BP (DBP) into hypertensive (SBP ≥140 mmHg and/or DBP ≥90 mmHg) and normotensive (SBP <120 mmHg and DBP <80 mmHg, without antihypertensive treatment) groups. Differences in peptide abundance between the two groups were confirmed using an external cohort ( n  = 420) of participants without end-organ damage, matched for age, BMI, eGFR, sex, and the presence of diabetes. Furthermore, the association of the peptides with BP as a continuous variable was investigated. The findings were compared with peptide biomarkers of chronic diseases and bioinformatic analyses were conducted to highlight the underlying molecular mechanisms., Results: Between hypertensive and normotensive individuals, 96 (mostly COL1A1 and COL3A1) peptides were found to be significantly different in both the discovery (adjusted) and validation (nominal significance) cohorts, with consistent regulation. Of these, 83 were consistently regulated in the matched cohort. A weak, yet significant, association between their abundance and standardized BP was also observed., Conclusion: Hypertension is associated with an altered urinary peptide profile with evident differential regulation of collagen-derived peptides. Peptides related to vascular calcification and sodium regulation were also affected. Whether these modifications reflect the pathophysiology of hypertension and/or early subclinical organ damage requires further investigation., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Screening for and prevention of osteoporosis and osteoporotic fractures is imperative, given the high burden on individuals and society. This study constructed and validated an aging-related biomarker derived from the urinary proteomic profile (UPP) indicative of osteoporosis (UPPost-age). In a prospective population study done in northern Belgium (1985-2019), participants were invited for a follow-up examination in 2005-2010 and participants in the 2005-2010 examination again invited in 2009-2013. Participants in both the 2005-2010 and 2009-2013 examinations (n = 519) constituted the derivation (2005-2016 data) and time-shifted validation (2009-2013 data) datasets; 187 participants with only 2005-2010 data formed the synchronous validation dataset. The UPP was assessed by capillary electrophoresis coupled with mass spectrometry. Analyses focused on 2372 sequenced urinary peptides (101 proteins) with key roles in maintaining the integrity of bone tissue. In multivariable analyses with correction for multiple testing, chronological age was associated with 99 urinary peptides (16 proteins). Peptides derived from IGF2 and MGP were upregulated in women compared to men, whereas COL1A2, COL3A1, COL5A2, COL10A1 and COL18A1 were downregulated. Via application of a 1000-fold bootstrapped elastic regression procedure, finally, 29 peptides (10 proteins) constituted the UPPost-age biomarker, replicated across datasets. In cross-sectional analyses of 2009-2013 data (n = 706), the body-height-to-arm-span ratio, an osteoporosis marker, was negatively associated with UPPost-age (p&;lt0.0001). Over 4.89 years (median), the 10-year risk of osteoporosis associated with chronological age and UPPost-age (53 cases including 37 fractures in 706 individuals) increased by 21% and 36% (p ≤ 0.044). Among 357 women, the corresponding estimates were 55% and 60% for incident osteoporosis (37 cases; p ≤ 0.0003) and 42% and 44% for osteoporotic fractures (25 cases; p ≤ 0.017). In conclusion, an aging-related UPP signature with focus on peptide fragments derived from bone-related proteins is associated with osteoporosis risk and available for clinical and trial research.

Background and Objective: While collagen density has been associated with poor outcomes in various cancers, its role in prostate cancer (PCa) remains elusive. Our aim was to analyze collagen-related transcriptomic, proteomic, and urinome alterations in the context of detection of clinically significant PCa (csPCa, International Society of Urological Pathology [ISUP] grade group ≥2)., Methods: Comprehensive analyses for PCa transcriptome (n = 1393), proteome (n = 104), and urinome (n = 923) data sets focused on 55 collagen-related genes. Investigation of the cellular source of collagen-related transcripts via single-cell RNA sequencing was conducted. Statistical evaluations, clustering, and machine learning models were used for data analysis to identify csPCa signatures., Key Findings and Limitations: Differential expression of 30 of 55 collagen-related genes and 34 proteins was confirmed in csPCa in comparison to benign prostate tissue or ISUP 1 cancer. A collagen-high cancer cluster exhibited distinct cellular and molecular characteristics, including fibroblast and endothelial cell infiltration, intense extracellular matrix turnover, and enhanced growth factor and inflammatory signaling. Robust collagen-based machine learning models were established to identify csPCa. The models outcompeted prostate-specific antigen (PSA) and age, showing comparable performance to multiparametric magnetic resonance imaging (mpMRI) in predicting csPCa. Of note, the urinome-based collagen model identified four of five csPCa cases among patients with Prostate Imaging-Reporting and Data System (PI-IRADS) 3 lesions, for which the presence of csPCa is considered equivocal. The retrospective character of the study is a limitation., Conclusions and Clinical Implications: Collagen-related transcriptome, proteome, and urinome signatures exhibited superior accuracy in detecting csPCa in comparison to PSA and age. The collagen signatures, especially in cases of ambiguous lesions on mpMRI, successfully identified csPCa and could potentially reduce unnecessary biopsies. The urinome-based collagen signature represents a promising liquid biopsy tool that requires prospective evaluation to improve the potential of this collagen-based approach to enhance diagnostic precision in PCa for risk stratification and guiding personalized interventions., Patient Summary: In our study, collagen-related alterations in tissue, and urine were able to predict the presence of clinically significant prostate cancer at primary diagnosis., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Catheter-based renal denervation (RDN) reduces blood pressure in hypertension. Urinary peptides are associated with cardiovascular and renal disease and provide prognostic information. We aimed to investigate the effect of RDN on urinary peptide-based classifiers associated with chronic kidney and heart disease and to identify urinary peptides affected by RDN., Methods: This single-arm, single-center study included patients undergoing catheter-based RDN. Urine samples were collected before and 24 months after RDN and were analyzed using capillary electrophoresis coupled with mass spectrometry. Predefined urinary peptide-based classifiers for chronic kidney disease (CKD273), coronary artery disease (CAD238), and heart failure (HF1) were applied., Results: This study included 48 patients (33% female) with uncontrolled hypertension. At 24 months after RDN, systolic blood pressure (165±17 versus 148±20 mm Hg; P <0.0001), diastolic blood pressure (90±17 versus 81±13 mm Hg; P <0.0001), and mean arterial pressure (115±15 versus 103±13 mm Hg; P <0.0001) decreased significantly. A total of 103 urinary peptides from 37 different proteins, mostly collagens, altered following RDN. CAD238, a 238 coronary artery-specific polypeptide-based classifier, significantly improved following RDN (Cohen's d , -0.632; P =0.0001). The classification scores of HF1 ( P =0.8295) and CKD273 ( P =0.6293) did not change significantly., Conclusions: RDN beneficially affected urinary peptides associated with coronary artery disease., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01888315., Competing Interests: Disclosures L. Lauder reports speaker honoraria from AstraZeneca, Medtronic, Pfizer, and ReCor Medical. J. Siwy and E. Mavrogeorgis are employees of the Mosaiques Diagnostics GmbH. I.E. Emrich has received speaker honoraria/consulting fees from Pharmacosmos, Astellas, Bristol Myers Squibb, AstraZeneca, and Novartis. M. Böhm is supported by the Deutsche Forschungsgemeinschaft (German Research Foundation; TTR 219, project No. 322900939) and reports personal fees from Abbott, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Cytokinetics, Edwards, Medtronic, Novartis, ReCor Medical, Servier, and Vifor during the conduct of the study. H. Mischak is cofounder and a shareholder of Mosaiques Diagnostics GmbH. F. Mahfoud is supported by Deutsche Gesellschaft für Kardiologie, Deutsche Forschungsgemeinschaft (SFB TRR219, project ID 322900939), and Deutsche Herzstiftung. His institution (Saarland University) has received scientific support from Ablative Solutions, Medtronic, and ReCor Medical, and speaker honoraria/consulting fees from Ablative Solutions, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Inari, Medtronic, Merck, ReCor Medical, Servier, and Terumo. The other authors report no conflicts.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by abnormal protein aggregation in the motor neurons. Present and earlier proteomic studies to characterize peptides in cerebrospinal fluid (CSF) associated with motoneuron pathology did not target low molecular weight proteins and peptides. We hypothesized that specific changes in CSF peptides or low molecular weight proteins are significantly altered in ALS, and that these changes may support deciphering molecular pathophysiology and even guide approaches towards therapeutic interventions., Methods: Cerebrospinal fluid (CSF) from 50 ALS patients and 50 non-ALS controls was collected, centrifuged immediately after collection, aliquoted into polypropylene test tubes, frozen within 30-40 min after the puncture, and stored at -80°C until use. Peptides were sequenced using capillary electrophoresis or liquid chromatography/mass spectrometry (CE-MS/MS or LC-MS/MS)., Findings: In the CSF of 50 patients and 50 non-ALS controls 33 peptides were found, of which 14 could be sequenced using a non-lytic single-pot proteomic detection method, CE/MS. ALS deregulated peptides vs. controls included Integral membrane protein 2B, Neurosecretory protein VGF, Osteopontin, Neuroendocrine protein 7B2 (Secretogranin-V), EGF-containing fibulin-like extracellular matrix protein 1, Xylosyltransferase 1 XT-1, Chromogranin-A, Superoxide dismutase SOD-1, Secretogranin-1 (Chromogranin B), NR2F2 Nuclear Receptor Subfamily 2 Group F Member 2 and Collagen alpha-1(VII) chain., Interpretation: Most striking deregulations in CSF from ALS patients were found in VGF, Osteopontin, SOD-1 and EFEMP1 peptides. No associations of disease severity, duration and region of onset with sequenced peptides were found., Competing Interests: S. Petri received honoraria as speaker/consultant from Biogen GmbH, Roche, Novartis, Teva, Cytokinetics Inc., Desitin, Italfarmaco, Ferrer, Amylyx, and Zambon; and grants from DGM e.V, Federal Ministry of Education and Research, German Israeli Foundation for Scientific Research and Development, EU Joint Program for Neurodegenerative Disease Research. J. Beige received funding from GSK and German Federal Ministries of Research and Health. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Lumi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The risk of diabetic kidney disease (DKD) progression is significant despite treatment with renin-angiotensin system (RAS) blocking agents. Current clinical tools cannot predict whether or not patients will respond to treatment with RAS inhibitors (RASi). We aimed to investigate whether proteome analysis could identify urinary peptides as biomarkers that could predict the response to angiotensin-converting enzyme inhibitor and angiotensin-receptor blockers treatment to avoid DKD progression. Furthermore, we investigated the comparability of the estimated glomerular filtration rate (eGFR), calculated using four different GFR equations, for DKD progression., Methods: We evaluated urine samples from a discovery cohort of 199 diabetic patients treated with RASi. DKD progression was defined based on eGFR percentage slope results between visits (∼1 year) and for the entire period (∼3 years) based on the eGFR values of each GFR equation. Urine samples were analysed using capillary electrophoresis-coupled mass spectrometry. Statistical analysis was performed between the uncontrolled (patients who did not respond to RASi treatment) and controlled kidney function groups (patients who responded to the RASi treatment). Peptides were combined in a support vector machine-based model. The area under the receiver operating characteristic curve was used to evaluate the risk prediction models in two independent validation cohorts treated with RASi., Results: The classification of patients into uncontrolled and controlled kidney function varies depending on the GFR equation used, despite the same sample set. We identified 227 peptides showing nominal significant difference and consistent fold changes between uncontrolled and controlled patients in at least three methods of eGFR calculation. These included fragments of collagens, alpha-1-antitrypsin, antithrombin-III, CD99 antigen and uromodulin. A model based on 189 of 227 peptides (DKDp189) showed a significant prediction of non-response to the treatment/DKD progression in two independent cohorts., Conclusions: The DKDp189 model demonstrates potential as a predictive tool for guiding treatment with RASi in diabetic patients., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Millions of people worldwide currently suffer from chronic kidney disease (CKD), requiring kidney replacement therapy at the end stage. Endeavors to better understand CKD pathophysiology from an omics perspective have revealed major molecular players in several sample sources. Focusing on non-invasive sources, gut microbial communities appear to be disturbed in CKD, while numerous human urinary peptides are also dysregulated. Nevertheless, studies often focus on isolated omics techniques, thus potentially missing the complementary pathophysiological information that multidisciplinary approaches could provide. To this end, human urinary peptidome was analyzed and integrated with clinical and fecal microbiome (16S sequencing) data collected from 110 Non-CKD or CKD individuals (Early, Moderate, or Advanced CKD stage) that were not undergoing dialysis. Participants were visualized in a three-dimensional space using different combinations of clinical and molecular data. The most impactful clinical variables to discriminate patient groups in the reduced dataspace were, among others, serum urea, haemoglobin, total blood protein, urinary albumin, urinary erythrocytes, blood pressure, cholesterol measures, body mass index, Bristol stool score, and smoking; relevant variables were also microbial taxa, including Roseburi a, Butyricicoccus , Flavonifractor , Burkholderiales , Holdemania , Synergistaceae , Enterorhabdus , and Senegalimassilia ; urinary peptidome fragments were predominantly derived from proteins of collagen origin; among the non-collagen parental proteins were FXYD2, MGP, FGA, APOA1, and CD99. The urinary peptidome appeared to capture substantial variation in the CKD context. Integrating clinical and molecular data contributed to an improved cohort separation compared to clinical data alone, indicating, once again, the added value of this combined information in clinical practice., Competing Interests: H.M. is the founder and co-owner of Mosaiques Diagnostics (Hannover, Germany). E.M., J.S. and A.L. are employed by Mosaiques Diagnostics.

Background: Before implementing individualized strategies to treat acute kidney injury (AKI), identifying clusters of patients with divergent pathophysiological mechanisms, diagnosis criteria or outcomes is of the utmost importance. Here we studied sex-related molecular mechanisms in cardiac bypass (CBP) surgery patients developing AKI., Methods: We compared the characteristics of 1170 patients referred for CBP surgery using multivariate logistic regression and propensity score-based analysis. Performances of the candidate urinary biomarkers at <4 h post-surgery, urinary neutrophil gelatinase-associated lipocalin (uNGAL), [IGFBP7]·[TIMP-2] product (NephroCheck) and a recently developed AKI signature of 204 urinary peptides (AKI204) to predict AKI were compared in both sexes., Results: Incidence (∼25%) and severity of AKI were similar in men and women, even after adjustment for the usual risk factors of AKI, including baseline estimated glomerular filtration rate, age, diabetes mellitus, length of CBP and red blood cell transfusion. However, at the molecular level, performances of uNGAL, NephroCheck and AKI204 to predict AKI strongly diverged between men and women. In the full cohort, as well as in subgroups of men and women, the multimarker AKI204 signature outperformed uNGAL and NephroCheck and predicted the development of AKI significantly better in women than in men. Analysis of AKI204 at the single-peptide level suggested divergences of AKI mechanisms between sexes due to increased kidney inflammation in women (increased abundance of urinary fragments of osteopontin and uromodulin)., Conclusions: In patients referred for CBP surgery, significant clinical and biological differences between men and women as well as sexual dimorphism of AKI biomarker performances were identified. The urinary peptide signature points to sex-related molecular mechanisms underlying AKI., Competing Interests: J.S. and I.A. are employees of Mosaiques Diagnostics, (© The Author(s) 2024. Published by Oxford University Press on behalf of the ERA.)

Effective management of chronic kidney disease (CKD), a major health problem worldwide, requires accurate and timely diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for evaluating specific aspects of CKD have been proposed in the literature, many of which are based on a small number of samples. Based on the evidence presented in relevant studies, a comprehensive overview of the different biomarkers applicable for clinical implementation is lacking. This review aims to compile information on the non-invasive diagnostic, prognostic, and predictive biomarkers currently available for the management of CKD and provide guidance on the application of these biomarkers. We specifically focus on biomarkers that have demonstrated added value in prospective studies or those based on prospectively collected samples including at least 100 subjects. Published data demonstrate that several valid non-invasive biomarkers of potential value in the management of CKD are currently available.

Effective management of glomerular kidney disease, one of the main categories of chronic kidney disease (CKD), requires accurate diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for the assessment of specific aspects of glomerular diseases have been reported in the literature. Though, the vast majority of these have not been implemented in clinical practice or are not available on a global scale due to limited access, missing medical infrastructure, or economical as well as political reasons. The aim of this review is to compile all currently available information on the diagnostic, prognostic, and predictive biomarkers currently available for the management of glomerular diseases, and provide guidance on the application of these biomarkers. As a result of the compiled evidence for the different biomarkers available, we present a decision tree for a non-invasive, biomarker-guided diagnostic path. The data currently available demonstrate that for the large majority of patients with glomerular diseases, valid biomarkers are available. However, despite the obvious disadvantages of kidney biopsy, being invasive and not applicable for monitoring, especially in the context of rare CKD etiologies, kidney biopsy still cannot be replaced by non-invasive strategies.

Previous studies have established the association of sex with gene and protein expression. This study investigated the association of sex with the abundance of endogenous urinary peptides, using capillary electrophoresis-coupled to mass spectrometry (CE-MS) datasets from 2008 healthy individuals and patients with type II diabetes, divided in one discovery and two validation cohorts. Statistical analysis using the Mann-Whitney test, adjusted for multiple testing, revealed 143 sex-associated peptides in the discovery cohort. Of these, 90 peptides were associated with sex in at least one of the validation cohorts and showed agreement in their regulation trends across all cohorts. The 90 sex-associated peptides were fragments of 29 parental proteins. Comparison with previously published transcriptomics data demonstrated that the genes encoding 16 of these parental proteins had sex-biased expression. The 143 sex-associated peptides were combined into a support vector machine-based classifier that could discriminate males from females in two independent sets of healthy individuals and patients with type II diabetes, with an AUC of 89% and 81%, respectively. Collectively, the urinary peptidome contains multiple sex-associated differences, which may enable a better understanding of sex-biased molecular mechanisms and the development of more accurate diagnostic, prognostic, or predictive classifiers for each individual sex., (© 2023 The Authors. Proteomics published by Wiley-VCH GmbH.)

Background and Hypothesis: Specific urinary peptides hold information on disease pathophysiology, which, in combination with artificial intelligence, could enable non-invasive assessment of chronic kidney disease (CKD) aetiology. Existing approaches are generally specific for the diagnosis of single aetiologies. We present the development of models able to simultaneously distinguish and spatially visualize multiple CKD aetiologies., Methods: The urinary peptide data of 1850 healthy control (HC) and CKD [diabetic kidney disease (DKD), immunoglobulin A nephropathy (IgAN) and vasculitis] participants were extracted from the Human Urinary Proteome Database. Uniform manifold approximation and projection (UMAP) coupled to a support vector machine algorithm was used to generate multi-peptide models to perform binary (DKD, HC) and multiclass (DKD, HC, IgAN, vasculitis) classifications. This pipeline was compared with the current state-of-the-art single-aetiology CKD urinary peptide models., Results: In an independent test set, the developed models achieved 90.35% and 70.13% overall predictive accuracies, respectively, for the binary and the multiclass classifications. Omitting the UMAP step led to improved predictive accuracies (96.14% and 85.06%, respectively). As expected, the HC class was distinguished with the highest accuracy. The different classes displayed a tendency to form distinct clusters in the 3D space based on their disease state., Conclusion: Urinary peptide data present an effective basis for CKD aetiology differentiation using machine learning models. Although adding the UMAP step to the models did not improve prediction accuracy, it may provide a unique visualization advantage. Additional studies are warranted to further validate the pipeline's clinical potential as well as to expand it to other CKD aetiologies and also other diseases., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Background: Immunosuppressive treatment in heart transplant (HTx) recipient causes osteoporosis. The urinary proteomic profile (UPP) includes peptide fragments derived from the bone extracellular matrix. Study aims were to develop and validate a multidimensional UPP biomarker for osteoporosis in HTx patients from single sequenced urinary peptides identifying the parent proteins., Methods: A single-center HTx cohort was analyzed. Urine samples were measured by capillary electrophoresis coupled with mass spectrometry. Cases with osteoporosis and matching controls were randomly selected from all available 389 patients. In derivation case-control dataset, 1576 sequenced peptides detectable in ≥30 % of patients. Applying statistical analysis on these, an 18-peptide multidimensional osteoporosis UPP biomarker (OSTEO18) was generated by support vector modeling. The 2 replication datasets included 118 and 94 patients. For further validation, the whole cohort was analyzed. Statistical methods included logistic regression and receiver operating characteristic curve (ROC) analysis., Results: In derivation dataset, the AUC, sensitivity and specificity of OSTEO18 were 0.83 (95 % CI: 0.76-0.90), 74.3 % and 87.1 %, respectively. In replication datasets, results were confirmatory. In the whole cohort (154 osteoporotic patients [39.6 %]), the ORs for osteoporosis increased ( p  < 0.0001) across OSTEO18 quartiles from 0.39 (95 % CI: 0.25-0.61) to 3.14 (2.08-4.75). With full adjustment for known osteoporosis risk factors, OSTEO18 improved AUC from 0.708 to 0.786 ( p  = 0.0003) for OSTEO18 categorized (optimized threshold: 0.095) and to 0.784 ( p  = 0.0004) for OSTEO18 as continuously distributed classifier., Conclusion: OSTEO18 is a clinically meaningful novel biomarker indicative of osteoporosis in HTx recipients and is being certified as in-vitro diagnostic., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: uPROPHET was supported by the European Research Council (Advanced Researcher Grant-2011-294713-EPLORE and Proof-of-Concept Grant-713601-uPROPHET awarded to JAS). OMRON Healthcare, Co., Ltd., Kyoto, Japan provided a non-binding grant to the Non-Profit Research Association Alliance for the Promotion of Preventive Medicine (APPREMED), Mechelen, Belgium. Dries S. Martens holds a postdoctoral grant by the Research Foundations Flanders (FWO grants 12X9623N)., (© 2024 The Author(s).)

Introduction: Preterm infants are at risk for a variety of somatic and neurological disorders. In recent years, biofluid proteomics has emerged as a potential diagnostic tool for biomarker analysis. The aim of this study was to determine gestational age (GA)-related patterns of the urinary peptidome in preterm infants for researching potential novel prognostic biomarkers., Methods: We performed urinary peptidomics in longitudinal samples of 24 preterm (mean GA weeks 28 + 1 [24+1-31 + 6]) and 27 term born controls (mean GA weeks 39 + 2 [37+0-41 + 1]) using capillary electrophoresis combined with mass spectrometry (CE-MS). Peptides were sequenced using CE-MS/MS or LC-MS/MS analysis and were deposited, matched, and annotated in a Microsoft SQL database for statistical analysis. We compared their abundance in urine of preterm and term born infants and performed a validation analysis as well as correlations to GA and clinical risk scores., Results: Our results confirmed significant differences in the abundance of peptides and the hypothesis of age-dependent urinary peptidome changes in preterm and term infants. In preterm infants, SLC38A10 (solute carrier family 38 member 10) is one of the most abundant peptides. Combined urinary peptides correlated with clinical risk scores (p &lt; 0.05)., Conclusion: This is the first study reporting GA-related urinary peptidome changes of preterm infants detected by CE-MS and a modulation of the peptidome with GA. Further research is required to locate peptidome clusters correlated with specific clinical complications and long-term outcome. This may identify preterm infants at higher risk for adverse outcome who would benefit from early intervention., (© 2024 S. Karger AG, Basel.)

Background: Focal segmental glomerulosclerosis (FSGS) is divided into genetic, primary (p), uncertain cause, and secondary (s) forms. The subclasses differ in management and prognosis with differentiation often being challenging. We aimed to identify specific urine proteins/peptides discriminating between clinical and biopsy-proven pFSGS and sFSGS., Methods: Sixty-three urine samples were collected in two different centers (19 pFSGS and 44 sFSGS) prior to biopsy. Samples were analysed using capillary electrophoresis-coupled mass spectrometry. For biomarker definition, datasets of age-/sex-matched normal controls (NC, n  = 98) and patients with other chronic kidney diseases (CKDs, n  = 100) were extracted from the urinary proteome database. Independent specificity assessment was performed in additional data of NC ( n  = 110) and CKD ( n  = 170)., Results: Proteomics data from patients with pFSGS were first compared to NC ( n  = 98). This resulted in 1179 biomarker ( P  < 0.05) candidates. Then, the pFSGS group was compared to sFSGS, and in a third step, pFSGS data were compared to data from different CKD etiologies ( n  = 100). Finally, 93 biomarkers were identified and combined in a classifier, pFSGS93. Total cross-validation of this classifier resulted in an area under the receiving operating curve of 0.95. The specificity investigated in an independent set of NC and CKD of other etiologies was 99.1% for NC and 94.7% for CKD, respectively. The defined biomarkers are largely fragments of different collagens (49%)., Conclusion: A urine peptide-based classifier that selectively detects pFSGS could be developed. Specificity of 95%-99% could be assessed in independent samples. Sensitivity must be confirmed in independent cohorts before routine clinical application., Competing Interests: J.S. is employee of Mosaiques Diagnostics. H.M. is co-founder and a shareholder of Mosaiques Diagnostics. B.H., M.W., and I.P. are employees of Travere Therapeutics., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Background: A recently developed urinary peptidomics biological aging clock can be used to study accelerated human aging. From 1990 to 2019, exposure to airborne particulate matter (PM) became the leading environmental risk factor worldwide., Objectives: This study investigated whether air pollution exposure is associated with accelerated urinary peptidomic aging, independent of calendar age, and whether this association is modified by other risk factors., Methods: In a Flemish population, the urinary peptidomic profile (UPP) age (UPP-age) was derived from the urinary peptidomic profile measured by capillary electrophoresis coupled with mass spectrometry. UPP-age-R was calculated as the residual of the regression of UPP-age on chronological age, which reflects accelerated aging predicted by UPP-age, independent of chronological age. A high-resolution spatial-temporal interpolation method was used to assess each individual's exposure to PM 10 , PM 2.5 , black carbon (BC), and nitrogen dioxide ( NO 2 ). Associations of UPP-age-R with these pollutants were investigated by mixed models, accounting for clustering by residential address and confounders. Effect modifiers of the associations between UPP-age-R and air pollutants that included 18 factors reflecting vascular function, renal function, insulin resistance, lipid metabolism, or inflammation were evaluated. Direct and indirect (via UPP-age-R) effects of air pollution on mortality were evaluated by multivariable-adjusted Cox models., Results: Among 660 participants (50.2% women; mean age: 50.7 y), higher exposure to PM 10 , PM 2.5 , BC, and NO 2 was associated with a higher UPP-age-R. Studying effect modifiers showed that higher plasma levels of desphospho-uncarboxylated matrix Gla protein (dpucMGP), signifying poorer vitamin K status, steepened the slopes of UPP-age-R on the air pollutants. In further analyses among participants with dpucMGP ≥ 4.26 μ g / L (median), an interquartile range (IQR) higher level in PM 10 , PM 2.5 , BC, and NO 2 was associated with a higher UPP-age-R of 2.03 [95% confidence interval (CI): 0.60, 3.46], 2.22 (95% CI: 0.71, 3.74), 2.00 (95% CI: 0.56, 3.43), and 2.09 (95% CI: 0.77, 3.41) y, respectively. UPP-age-R was an indirect mediator of the associations of mortality with the air pollutants [multivariable-adjusted hazard ratios from 1.094 (95% CI: 1.000, 1.196) to 1.110 (95% CI: 1.007, 1.224)] in participants with a high dpucMGP, whereas no direct associations were observed., Discussion: Ambient air pollution was associated with accelerated urinary peptidomics aging, and high vitamin K status showed a potential protective effect in this population. Current guidelines are insufficient to decrease the adverse health effects of airborne pollutants, including healthy aging trajectories. https://doi.org/10.1289/EHP13414.

Background: Immunoglobulin A nephropathy (IgAN) frequently leads to kidney failure. The urinary proteomics-based classifier IgAN237 may predict disease progression at the time of kidney biopsy. We studied whether IgAN237 also predicts progression later in the course of IgAN., Methods: Urine from patients with biopsy-proven IgAN was analyzed using capillary electrophoresis-mass spectrometry at baseline (IgAN237-1, n = 103) and at follow-up (IgAN237-2, n = 89). Patients were categorized as "non-progressors" (IgAN237 ≤0.38) and "progressors" (IgAN237 >0.38). Estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio slopes were calculated., Results: Median age at biopsy was 44 years, interval between biopsy and IgAN237-1 was 65 months and interval between IgAN237-1 and IgAN237-2 was 258 days (interquartile range 71-531). IgAN237-1 and IgAN237-2 values did not differ significantly and were correlated (rho = 0.44, P < .001). Twenty-eight percent and 26% of patients were progressors based on IgAN237-1 and IgAN237-2, respectively. IgAN237 inversely correlated with chronic eGFR slopes (rho = -0.278, P = .02 for score-1; rho = -0.409, P = .002 for score-2) and with ±180 days eGFR slopes (rho = -0.31, P = .009 and rho = -0.439, P = .001, respectively). The ±180 days eGFR slopes were worse for progressors than for non-progressors (median -5.98 versus -1.22 mL/min/1.73 m2 per year for IgAN237-1, P < .001; -3.02 vs 1.08 mL/min/1.73 m2 per year for IgAN237-2, P = .0047). In multiple regression analysis baseline progressor/non-progressor according to IgAN237 was an independent predictor of eGFR180days-slope (P = .001)., Conclusion: The urinary IgAN237 classifier represents a risk stratification tool in IgAN also later in the course of the dynamic disease. It may guide patient management in an individualized manner., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Introduction: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have emerged as novel therapeutics to treat diabetic kidney disease (DKD). Although the beneficial effects of SGLT2i have been demonstrated, their target mechanisms on kidney function are unknown. The current study aimed to elucidate these mechanisms by studying SGLT2i-induced changes in the urinary proteome of persons with type 2 diabetes (T2D) and DKD., Methods: A total of 40 participants with T2D were enrolled in a double-blinded randomized cross-over trial at the Steno Diabetes Center Copenhagen, Denmark. They were treated with 10 mg of dapagliflozin for 12 weeks. Thirty-two participants with complete urinary proteomics measures before and after the trial were included. All participants received renin-angiotensin system blockade and had albuminuria, (urine albumin-to-creatinine ratio [UACR] ≥30 mg/g). A type 1 diabetes (T1D) cohort consisting of healthy controls and persons with DKD was included for validation. Urinary proteome changes were analyzed using Wilcoxon signed-rank test. Functional enrichment analysis was conducted to discover affected biological processes., Results: Dapagliflozin treatment significantly ( P adjusted  < 0.05) affected 36 urinary peptide fragments derived from 19 proteins. Eighteen proteins were correspondingly reflected in the validation cohort. A multifold change in peptide abundance was observed in many proteins (A1BG, urinary albumin [ALB], Caldesmon 1, COLCRNN, heat shock protein 90-β [HSP90AB1], IGLL5, peptidase inhibitor 16 [PI16], prostaglandin-H2-D-isomerase [PTGDS], SERPINA1). These also included urinary biomarkers of kidney fibrosis and function (type I and III collagens and albumin). Biological processes relating to inflammation, wound healing, and kidney fibrosis were enriched., Conclusion: The current study discovers the urinary proteome impacted by the SGLT2i, thereby providing new potential target sites and pathways, especially relating to wound healing and inflammation., (© 2023 International Society of Nephrology. Published by Elsevier Inc.)

Increased arterial stiffness is related to early vascular aging and is an independent predictor for cardiovascular disease and mortality. Molecular mechanisms underlying increased arterial stiffness are largely unexplored, especially at the proteome level. We aimed to explore the relationship between pulse wave velocity and urinary proteomics. We included 919 apparently healthy (no chronic illnesses) Black and White men and women (equally distributed) between 20 and 30 years from the African-PREDICT study. Capillary electrophoresis time-of-flight mass spectrometry was used to analyze the urinary proteome. We measured the carotid-femoral pulse wave velocity to estimate arterial stiffness. In the total group, pulse wave velocity correlated positively with collagen-derived peptides including collagen types I, II, III, IV, V, and IX and inversely with collagen type XI (adjusted for mean arterial pressure). Regarding noncollagen-derived peptides, pulse wave velocity positively correlated with polymeric immunoglobulin receptor peptides ( n = 2) (all q -value ≤0.05). In multivariable adjusted analyses, pulse wave velocity associated positively and independently with seven urinary peptides (collagen type I, n = 5) (all p -value ≤0.05). We found significant positive and independent associations between pulse wave velocity and the collagen type I-derived peptides, suggesting that dysregulation of collagen type I in the extracellular matrix scaffold could lead to early onset of increased arterial stiffness.

Purpose: Acute kidney injury (AKI) is a frequent and severe condition in intensive care units (ICUs). In 2020, the Acute Dialysis Quality Initiative (ADQI) group proposed a new stage of AKI, referred to as stage 1S, which represents subclinical disease (sAKI) defined as a positive biomarker but no increase in serum creatinine (sCr). This study aimed to determine and compare the urinary peptide signature of sAKI as defined by biomarkers., Methods: This is an ancillary analysis of the prospective, observational, multinational FROG-ICU cohort study. AKI was defined according to the Kidney Disease Improving Global Outcome definition (AKI KDIGO ). sAKI was defined based on the levels of the following biomarkers, which exceeded the median value: neutrophil gelatinase-associated lipocalin (pNGAL, uNGAL), cystatin C (pCysC, uCysC), proenkephalin A 119-159 (pPENKID) and liver fatty acid binding protein (uLFABP). Urinary peptidomics analysis was performed using capillary electrophoresis-mass spectrometry. Samples were collected at the time of study inclusion., Results: One thousand eight hundred eighty-five patients had all biomarkers measured at inclusion, which included 1154 patients without AKI (non-AKI KDIGO subgroup). The non-AKI KDIGO subgroup consisted of individuals at a median age of 60 years [48, 71], among whom 321 (27.8%) died. The urinary peptide signatures of sAKI, regardless of the biomarkers used for its definition, were similar to the urinary peptide signatures of AKI KDIGO (inflammation, haemolysis, and endothelial dysfunction). These signatures were also associated with 1-year mortality., Conclusion: Biomarker-defined sAKI is a common and severe condition observed in patients within intensive care units with a urinary peptide signature that is similar to that of AKI, along with a comparable prognosis., (© 2023. Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: There is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, although the mechanisms causing this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to vulnerabilities that are already present. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides., Methods: Urinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated., Results: In the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death [adjusted HR 1.2 (95% CI 1.17-1.24)]. The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% [adjusted HR 1.61 (95% CI 1.47-1.76)], consistent with adjusted meta-analytic HR estimate of 1.55 [95% CI 1.39-1.73]. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I (I)., Conclusion: The COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. This prediction is mainly based on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as a basis for proteomics-guided intervention aiming towards manipulating/ improving collagen turnover, thereby reducing the risk of death., (© 2023. BioMed Central Ltd., part of Springer Nature.)

(1) Background: Kidney and cardiovascular diseases are responsible for a large fraction of population morbidity and mortality. Early, targeted, personalized intervention represents the ideal approach to cope with this challenge. Proteomic/peptidomic changes are largely responsible for the onset and progression of these diseases and should hold information about the optimal means of treatment and prevention. (2) Methods: We investigated the prediction of renal or cardiovascular events using previously defined urinary peptidomic classifiers CKD273, HF2, and CAD160 in a cohort of 5585 subjects, in a retrospective study. (3) Results: We have demonstrated a highly significant prediction of events, with an HR of 2.59, 1.71, and 4.12 for HF, CAD, and CKD, respectively. We applied in silico treatment, implementing on each patient's urinary profile changes to the classifiers corresponding to exactly defined peptide abundance changes, following commonly used interventions (MRA, SGLT2i, DPP4i, ARB, GLP1RA, olive oil, and exercise), as defined in previous studies. Applying the proteomic classifiers after the in silico treatment indicated the individual benefits of specific interventions on a personalized level. (4) Conclusions: The in silico evaluation may provide information on the future impact of specific drugs and interventions on endpoints, opening the door to a precision-based medicine approach. An investigation into the extent of the benefit of this approach in a prospective clinical trial is warranted.

Type II diabetes mellitus (T2DM) accounts for approximately 90% of all diabetes mellitus cases in the world. Glucagon-like peptide-1 receptor (GLP-1R) agonists have established an increased capability to target directly or indirectly six core defects associated with T2DM, while the underlying molecular mechanisms of these pharmacological effects are not fully known. This exploratory study was conducted to analyze the effect of treatment with GLP-1R agonists on the urinary peptidome of T2DM patients. Urine samples of thirty-two T2DM patients from the PROVALID study ("A Prospective Cohort Study in Patients with T2DM for Validation of Biomarkers") collected pre- and post-treatment with GLP-1R agonist drugs were analyzed by CE-MS. In total, 70 urinary peptides were significantly affected by GLP-1R agonist treatment, generated from 26 different proteins. The downregulation of MMP proteases, based on the concordant downregulation of urinary collagen peptides, was highlighted. Treatment also resulted in the downregulation of peptides from SERPINA1 , APOC3 , CD99 , CPSF6 , CRNN , SERPINA6 , HBA2 , MB , VGF , PIGR , and TTR , many of which were previously found to be associated with increased insulin resistance and inflammation. The findings indicate potential molecular mechanisms of GLP-1R agonists in the context of the management of T2DM and the prevention or delaying of the progression of its associated diseases.

Given the pathophysiological continuum of chronic kidney disease (CKD), different molecular determinants affecting progression may be associated with distinct disease phases; thus, identification of these players are crucial for guiding therapeutic decisions, ideally in a non-invasive, repeatable setting. Analyzing the urinary peptidome has been proven an efficient method for biomarker determination in CKD, among other diseases. In this work, after applying several selection criteria, urine samples from 317 early (stage 2) and advanced (stage 3b-5) CKD patients were analyzed using capillary electrophoresis coupled to mass spectrometry (CE-MS). The entire two groups were initially compared to highlight the respective pathophysiology between initial and late disease phases. Subsequently, slow and fast progressors were compared within each group in an attempt to distinguish phase-specific disease progression molecules. The early vs. late-stage CKD comparison revealed 929 significantly different peptides, most of which were downregulated and 268 with collagen origins. When comparing slow vs. fast progressors in early stage CKD, 42 peptides were significantly altered, 30 of which were collagen peptide fragments. This association suggests the development of structural changes may be reversible at an early stage. The study confirms previous findings, based on its multivariable-matched progression groups derived from a large initial cohort. However, only four peptide fragments differed between slow vs. fast progressors in late-stage CKD, indicating different pathogenic processes occur in fast and slow progressors in different stages of CKD. The defined peptides associated with CKD progression at early stage might potentially constitute a non-invasive approach to improve patient management by guiding (personalized) intervention.

Introduction: Kidney transplant recipients (KTRs) are at an increased risk of fractures. Total urinary hydroxyproline excretion served as marker for bone resorption (BR) but was replaced by β-CrossLaps (CTX), a C-terminal collagen α-1(I) chain (COL1A1) telopeptide. We investigated the low-molecular-weight urinary proteome for peptides associated with changes in bone metabolism after kidney transplantation., Methods: Clinical and laboratory data including serum levels of CTX in 96 KTR from two nephrology centers were correlated with signal intensities of urinary peptides identified by capillary electrophoresis mass spectrometry., Results: Eighty-two urinary peptides were significantly correlated with serum CTX levels. COL1A1 was the predominant peptide source. Oral bisphosphonates were administered for decreased bone density in an independent group of 11 KTR and their effect was evaluated on the aforementioned peptides. Study of the peptides cleavage sites revealed a signature of Cathepsin K and MMP9. Seventeen of these peptides were significantly associated with bisphosphonate treatment, all showing a marked reduction in their excretion levels compared to baseline., Discussion: This study provides strong evidence for the presence of collagen peptides in the urine of KTR that are associated with BR and that are sensitive to bisphosphonate treatment. Their assessment might become a valuable tool to monitor bone status in KTR., (© 2023 The Authors. Proteomics - Clinical Applications published by Wiley-VCH GmbH.)

The collagen family contains 28 proteins, predominantly expressed in the extracellular matrix (ECM) and characterized by a triple-helix structure. Collagens undergo several maturation steps, including post-translational modifications (PTMs) and cross-linking. These proteins are associated with multiple diseases, the most pronounced of which are fibrosis and bone diseases. This review focuses on the most abundant ECM protein highly implicated in disease, type I collagen (collagen I), in particular on its predominant chain collagen type I alpha 1 (COLα1 (I)). An overview of the regulators of COLα1 (I) and COLα1 (I) interactors is presented. Manuscripts were retrieved searching PubMed, using specific keywords related to COLα1 (I). COL1A1 regulators at the epigenetic, transcriptional, post-transcriptional and post-translational levels include DNA Methyl Transferases (DNMTs), Tumour Growth Factor β (TGFβ), Terminal Nucleotidyltransferase 5A (TENT5A) and Bone Morphogenic Protein 1 (BMP1), respectively. COLα1 (I) interacts with a variety of cell receptors including integrinβ, Endo180 and Discoidin Domain Receptors (DDRs). Collectively, even though multiple factors have been identified in association to COLα1 (I) function, the implicated pathways frequently remain unclear, underscoring the need for a more spherical analysis considering all molecular levels simultaneously.

Hypertension is one of the most important and complex risk factors for cardiovascular diseases (CVDs). By using urinary peptidomics analyses, we aimed to identify peptides associated with hypertension, building a framework for future research towards improved prediction and prevention of premature development of CVD. We included 78 hypertensive and 79 normotensive participants from the African-PREDICT study (aged 20-30 years), matched for sex (51% male) and ethnicity (49% black and 51% white). Urinary peptidomics data were acquired using capillary-electrophoresis-time-of-flight-mass-spectrometry. Hypertension-associated peptides were identified and combined into a support vector machine-based multidimensional classifier. When comparing the peptide data between the normotensive and hypertensive groups, 129 peptides were nominally differentially abundant (Wilcoxon p < 0.05). Nonetheless, only three peptides, all derived from collagen alpha-1(III), remained significantly different after rigorous adjustments for multiple comparisons. The 37 most significant peptides (all p ≤ 0.001) served as basis for the development of a classifier, with 20 peptides being combined into a unifying score, resulting in an AUC of 0.85 in the ROC analysis (p < 0.001), with 83% sensitivity at 80% specificity. Our study suggests potential value of urinary peptides in the classification of hypertension, which could enable earlier diagnosis and better understanding of the pathophysiology of hypertension and premature cardiovascular disease development., (© 2023 The Authors. Proteomics published by Wiley-VCH GmbH.)

High blood pressure (BP) and type-2 diabetes (T2DM) are forerunners of chronic kidney disease and left ventricular dysfunction. Home BP telemonitoring (HTM) and urinary peptidomic profiling (UPP) are technologies enabling risk stratification and personalized prevention. UPRIGHT-HTM (NCT04299529) is an investigator-initiated, multicenter, open-label, randomized trial with blinded endpoint evaluation designed to assess the efficacy of HTM plus UPP (experimental group) over HTM alone (control group) in guiding treatment in asymptomatic patients, aged 55-75 years, with ≥5 cardiovascular risk factors. From screening onwards, HTM data can be freely accessed by all patients and their caregivers; UPP results are communicated early during follow-up to patients and caregivers in the intervention group, but at trial closure in the control group. From May 2021 until January 2023, 235 patients were screened, of whom 53 were still progressing through the run-in period and 144 were randomized. Both groups had similar characteristics, including average age (62.0 years) and the proportions of African Blacks (81.9%), White Europeans (16.7%), women 56.2%, home (31.2%), and office (50.0%) hypertension, T2DM (36.4%), micro-albuminuria (29.4%), and ECG (9.7%) and echocardiographic (11.5%) left ventricular hypertrophy. Home and office BP were 128.8/79.2 mm Hg and 137.1/82.7 mm Hg, respectively, resulting in a prevalence of white-coat, masked and sustained hypertension of 40.3%, 11.1%, and 25.7%. HTM persisted after randomization (48 681 readings up to 15 January 2023). In conclusion, results predominantly from low-resource sub-Saharan centers proved the feasibility of this multi-ethnic trial. The COVID-19 pandemic caused delays and differential recruitment rates across centers., (© 2023 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC.)

Biomarker development, improvement, and clinical implementation in the context of kidney disease have been a central focus of biomedical research for decades. To this point, only serum creatinine and urinary albumin excretion are well-accepted biomarkers in kidney disease. With their known blind spot in the early stages of kidney impairment and their diagnostic limitations, there is a need for better and more specific biomarkers. With the rise in large-scale analyses of the thousands of peptides in serum or urine samples using mass spectrometry techniques, hopes for biomarker development are high. Advances in proteomic research have led to the discovery of an increasing amount of potential proteomic biomarkers and the identification of candidate biomarkers for clinical implementation in the context of kidney disease management. In this review that strictly follows the PRISMA guidelines, we focus on urinary peptide and especially peptidomic biomarkers emerging from recent research and underline the role of those with the highest potential for clinical implementation. The Web of Science database (all databases) was searched on 17 October 2022, using the search terms "marker *" OR biomarker * AND "renal disease" OR "kidney disease" AND "proteome *" OR "peptid *" AND "urin *". English, full-text, original articles on humans published within the last 5 years were included, which had been cited at least five times per year. Studies based on animal models, renal transplant studies, metabolite studies, studies on miRNA, and studies on exosomal vesicles were excluded, focusing on urinary peptide biomarkers. The described search led to the identification of 3668 articles and the application of inclusion and exclusion criteria, as well as abstract and consecutive full-text analyses of three independent authors to reach a final number of 62 studies for this manuscript. The 62 manuscripts encompassed eight established single peptide biomarkers and several proteomic classifiers, including CKD273 and IgAN237. This review provides a summary of the recent evidence on single peptide urinary biomarkers in CKD, while emphasizing the increasing role of proteomic biomarker research with new research on established and new proteomic biomarkers. Lessons learned from the last 5 years in this review might encourage future studies, hopefully resulting in the routine clinical applicability of new biomarkers., Competing Interests: J.S. is employee of Mosaiques Diagnostics. H.M. is co-founder and a shareholder of Mosaiques Diagnostics.

Background: This study aimed to assess the value of blood and urine biomarkers in addition to routine clinical variables in risk stratification of patients admitted to ICU., Methods: Multivariable prognostic models were developed in this post hoc analysis of the French and EuRopean Outcome ReGistry in Intensive Care Units study, a prospective observational study of patients admitted to ICUs. The study included 2087 patients consecutively admitted to the ICU who required invasive mechanical ventilation or a vasoactive agent for more than 24 h. The main outcome measures were in-ICU, in-hospital, and 1 year mortality., Results: Models including only SAPS II or APACHE II scores had c-indexes for in-hospital and 1 year mortality of 0.64 and 0.65, and 0.63 and 0.61, respectively. The c-indexes for a model including age and estimated glomerular filtration rate were higher at 0.69 and 0.67, respectively. Models utilizing available clinical variables increased the c-index for in-hospital and 1 year mortality to 0.80 and 0.76, respectively. The addition of biomarkers and urine proteomic markers increased c-indexes to 0.83 and 0.78., Conclusions: The commonly used scores for risk stratification in ICU patients did not perform well in this study. Models including clinical variables and biomarkers had significantly higher predictive values.

Background: Low- and middle-income countries experience an increasing burden of chronic kidney disease. Cardiovascular risk factors, including advancing age, may contribute to this phenomenon. We (i) profiled cardiovascular risk factors and different biomarkers of subclinical kidney function and (ii) investigated the relationship between these variables., Methods: We cross-sectionally analysed 956 apparently healthy adults between 20 and 30 years of age. Cardiovascular risk factors such as high adiposity, blood pressure, glucose levels, adverse lipid profiles and lifestyle factors were measured. Various biomarkers were used to assess subclinical kidney function, including estimated glomerular filtration rate (eGFR), urinary albumin, uromodulin and the CKD273 urinary proteomics classifier. These biomarkers were used to divide the total population into quartiles to compare extremes (25 th percentiles) on the normal kidney function continuum. The lower 25 th percentiles of eGFR and uromodulin and the upper 25 th percentiles of urinary albumin and the CKD273 classifier represented the more unfavourable kidney function groups., Results: In the lower 25 th percentiles of eGFR and uromodulin and the upper 25 th percentile of the CKD273 classifier, more adverse cardiovascular profiles were observed. In multi-variable adjusted regression analyses performed in the total group, eGFR associated negatively with HDL-C (β= -0.44; p < 0.001) and GGT (β= -0.24; p < 0.001), while the CKD273 classifier associated positively with age and these same risk factors (age: β = 0.10; p = 0.021, HDL-C: β = 0.23; p < 0.001, GGT: β = 0.14; p = 0.002)., Conclusion: Age, lifestyle and health measures impact kidney health even in the third decade., (© 2023. The Author(s).)

Aims: Baseline diabetic retinopathy (DR) and risk of development of microalbuminuria, kidney function decline, and cardiovascular events (CVEs) in type 2 diabetes., Methods: Post-hoc analysis of the PRIORITY study including 1758 persons with type 2 diabetes and normoalbuminuria followed for a median of 2.5 (IQR: 2.0-3.0) years. DR diagnosis included non-proliferative and proliferative abnormalities, macular oedema, or prior laser treatment. Cox models were fitted to investigate baseline DR presence with development of persistent microalbuminuria (urinary albumin-creatinine ratio > 30 mg/g); chronic kidney disease (CKD) G3 (eGFR <60 ml/min/1.73m 2 ); and CVE. Models were adjusted for relevant risk factors., Results: At baseline, 304 (17.3 %) had DR. Compared to persons without DR, they were older (mean ± SD: 62.7 ± 7.7 vs 61.4 ± 8.3 years, p = 0.019), had longer diabetes duration (17.9 ± 8.4 vs. 10.6 ± 7.0 years, p < 0.001), and higher HbA 1c (62 ± 13 vs. 56 ± 12 mmol/mol, p < 0.001). The adjusted hazard ratios of DR at baseline for development of microalbuminuria (n = 197), CKD (n = 166), and CVE (n = 64) were: 1.50 (95%CI: 1.07, 2.11), 0.87 (95%CI: 0.56, 1.34), and 2.61 (95%CI: 1.44, 4.72), compared to without DR., Conclusions: Presence of DR in normoalbuminuric type 2 diabetes was associated with an increased risk of developing microalbuminuria and CVE, but not with kidney function decline., Competing Interests: Declaration of competing interest NT is a full-time employee of Novo Nordisk A/S. TWH has equity in Novo Nordisk A/S. ML has received research support from Boehringer Ingelheim, Bayer and Merck Sharp & Dohme, and lecture fees from AstraZeneca, Bayer and Boehringer Ingelheim. All fees are given to Holbaek hospital. FP has served as a consultant, on advisory boards or as educator for AstraZeneca, Novo Nordisk, Boehringer Ingelheim, Sanofi, Mundipharma, MSD, Novartis, Amgen and has received research grants to institution from Novo Nordisk, Boehringer Ingelheim, Amgen and AstraZeneca. AO has received grants from Sanofi and consultancy or speaker fees or travel support from Advicciene, Astellas, Astrazeneca, Amicus, Amgen, Fresenius Medical Care, GSK, Bayer, Sanofi-Genzyme, Menarini, Mundipharma, Kyowa Kirin, Alexion, Freeline, Idorsia, Chiesi, Otsuka, Novo-Nordisk, Sysmex and Vifor Fresenius Medical Care Renal Pharma and is Director of the Catedra Mundipharma-UAM of diabetic kidney disease and the Catedra Astrazeneca-UAM of chronic kidney disease and electrolytes. HM is the cofounder and co-owner of Mosaiques Diagnostics GmbH. JS and PZ are employees of Mosaiques Diagnostics GmbH. MF-M has received speaker fees or support for medical meetings and research grants from AstraZeneca and Novo Nordisk and speaking fees from Boehringer Ingelheim, Eli Lilly, Novo Nordisk, Novartis, Baxter, and Sanofi-Aventis. IR has received honoraria for lectures of AstraZenec, Bayer, Boehringer Ingelheim, and Mundipharma. PR has received research support and personal fees from AstraZeneca, Bayer and Novo Nordisk, and personal fees from Astellas Pharma Inc., Bayer, Boehringer Ingelheim, Eli Lilly and Company, Gilead, Merck, Merck Sharp & Dohme, Mundipharma, Sanofi, and Vifor Pharma. All fees are given to Steno Diabetes Center Copenhagen. All other authors declare no competing interests that could be perceived as affecting the impartiality of the reported results., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Chronic kidney disease (CKD) is prevalent in 10% of world's adult population. The role of protein glycosylation in causal mechanisms of CKD progression is largely unknown. The aim of this study was to identify urinary O-linked glycopeptides in association to CKD for better characterization of CKD molecular manifestations. Urine samples from eight CKD and two healthy subjects were analyzed by CE-MS/MS and glycopeptides were identified by a specific software followed by manual inspection of the spectra. Distribution of the identified glycopeptides and their correlation with Age, eGFR and Albuminuria were evaluated in 3810 existing datasets. In total, 17 O-linked glycopeptides from 7 different proteins were identified, derived primarily from Insulin-like growth factor-II (IGF2). Glycosylation occurred at the surface exposed IGF2 Threonine 96 position. Three glycopeptides (DVStPPTVLPDNFPRYPVGKF, DVStPPTVLPDNFPRYPVG and DVStPPTVLPDNFPRYP) exhibited positive correlation with Age. The IGF2 glycopeptide (tPPTVLPDNFPRYP) showed a strong negative association with eGFR. These results suggest that with aging and deteriorating kidney function, alterations in IGF2 proteoforms take place, which may reflect changes in mature IGF2 protein. Further experiments corroborated this hypothesis as IGF2 increased plasma levels were observed in CKD patients. Protease predictions, considering also available transcriptomics data, suggest activation of cathepsin S with CKD, meriting further investigation.

(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.

Cardiovascular disease (CVD) affects individuals across the lifespan, with multiple cardiovascular (CV) risk factors increasingly present in young populations. The underlying mechanisms in early cardiovascular disease development are complex and still poorly understood. We therefore employed urinary proteomics as a novel approach to gain better insight into early CVD-related molecular pathways based on a CVD risk stratification approach. This study included 964 apparently healthy (no self-reported chronic illnesses, free from clinical symptoms of CVD) black and white men and women (aged 20-30 years old) from the African Prospective study on the Early Detection and Identification of Cardiovascular disease and Hypertension (African-PREDICT) study. Cardiovascular risk factors used for stratification included obesity, physical inactivity, tobacco use, high alcohol intake, hyperglycemia, dyslipidemia and hypertension. Participants were divided into low (0 risk factors), medium (1-2 risk factors) and high (≥3 risk factors) CV risk groups. We analyzed urinary peptidomics by capillary electrophoresis time-of-flight mass spectrometry. After adjusting for ethnicity, sex and age, 65 sequenced urinary peptides were differentially expressed between the CV risk groups (all q-values ≤ 0.01). These peptides included a lower abundance of collagen type I- and III-derived peptides in the high compared to the low CV risk group. With regard to noncollagen peptides, we found a lower abundance of alpha-1-antitrypsin fragments in the high compared to the low CV risk group (all q-values ≤ 0.01). Our findings indicate lower abundances of collagen types I and III in the high compared to the low CV risk group, suggesting potential early alterations in the CV extracellular matrix., (© 2022. The Author(s), under exclusive licence to The Japanese Society of Hypertension.)

Delivering better care for patients with bladder cancer (BC) necessitates the development of novel therapeutic strategies that address both the high disease heterogeneity and the limitations of the current therapeutic modalities, such as drug low efficacy and patient resistance acquisition. Drug repurposing is a cost-effective strategy that targets the reuse of existing drugs for new therapeutic purposes. Such a strategy could open new avenues toward more effective BC treatment. BC patients' multi-omics signatures can be used to guide the investigation of existing drugs that show an effective therapeutic potential through drug repurposing. In this book chapter, we present an integrated multilayer approach that includes cross-omics analyses from publicly available transcriptomics and proteomics data derived from BC tissues and cell lines that were investigated for the development of disease-specific signatures. These signatures are subsequently used as input for a signature-based repurposing approach using the Connectivity Map (CMap) tool. We further explain the steps that may be followed to identify and select existing drugs of increased potential for repurposing in BC patients., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)