Evaluation of a proteomic signature coupled with the kidney failure risk equation in predicting end stage kidney disease in a chronic kidney disease cohort.

BACKGROUND: The early identification of patients at high-risk for end-stage renal disease (ESRD) is essential for providing optimal care and implementing targeted prevention strategies. While the Kidney Failure Risk Equation (KFRE) offers a more accurate prediction of ESRD risk compared to static eGFR-based thresholds, it does not provide insights into the patient-specific biological mechanisms that drive ESRD. This study focused on evaluating the effectiveness of KFRE in a UK-based advanced chronic kidney disease (CKD) cohort and investigating whether the integration of a proteomic signature could enhance 5-year ESRD prediction. METHODS: Using the Salford Kidney Study biobank, a UK-based prospective cohort of over 3000 non-dialysis CKD patients, 433 patients met our inclusion criteria: a minimum of four eGFR measurements over a two-year period and a linear eGFR trajectory. Plasma samples were obtained and analysed for novel proteomic signals using SWATH-Mass-Spectrometry. The 4-variable UK-calibrated KFRE was calculated for each patient based on their baseline clinical characteristics. Boruta machine learning algorithm was used for the selection of proteins most contributing to differentiation between patient groups. Logistic regression was employed for estimation of ESRD prediction by (1) proteomic features; (2) KFRE; and (3) proteomic features alongside KFRE. RESULTS: SWATH maps with 943 quantified proteins were generated and investigated in tandem with available clinical data to identify potential progression biomarkers. We identified a set of proteins (SPTA1, MYL6 and C6) that, when used alongside the 4-variable UK-KFRE, improved the prediction of 5-year risk of ESRD (AUC = 0.75 vs AUC = 0.70). Functional enrichment analysis revealed Rho GTPases and regulation of the actin cytoskeleton pathways to be statistically significant, inferring their role in kidney function and the pathogenesis of renal disease. CONCLUSIONS: Proteins SPTA1, MYL6 and C6, when used alongside the 4-variable UK-KFRE achieve an improved performance when predicting a 5-year risk of ESRD. Specific pathways implicated in the pathogenesis of podocyte dysfunction were also identified, which could serve as potential therapeutic targets. The findings of our study carry implications for comprehending the involvement of the Rho family GTPases in the pathophysiology of kidney disease, advancing our understanding of the proteomic factors influencing susceptibility to renal damage.

Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women.

BACKGROUND: A non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls. METHODS: This was a prospective case-control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression. RESULTS: The top discriminatory proteins individually showed moderate accuracy (AUC > 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs > 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96-0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86-0.9)). CONCLUSION: A patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted.

Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.

BACKGROUND: Halting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking. METHODS: Plasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m2/year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m2/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses. RESULTS: The resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin-proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched. CONCLUSIONS: The in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis.

Proteomic analysis identifies subgroups of patients with active systemic lupus erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is a clinically and biologically heterogenous autoimmune disease. We aimed to investigate the plasma proteome of patients with active SLE to identify novel subgroups, or endotypes, of patients. METHOD: Plasma was collected from patients with active SLE who were enrolled in the British Isles Lupus Assessment Group Biologics Registry (BILAG-BR). The plasma proteome was analysed using a data-independent acquisition method, Sequential Window Acquisition of All theoretical mass spectra mass spectrometry (SWATH-MS). Unsupervised, data-driven clustering algorithms were used to delineate groups of patients with a shared proteomic profile. RESULTS: In 223 patients, six clusters were identified based on quantification of 581 proteins. Between the clusters, there were significant differences in age (p = 0.012) and ethnicity (p = 0.003). There was increased musculoskeletal disease activity in cluster 1 (C1), 19/27 (70.4%) (p = 0.002) and renal activity in cluster 6 (C6) 15/24 (62.5%) (p = 0.051). Anti-SSa/Ro was the only autoantibody that significantly differed between clusters (p = 0.017). C1 was associated with p21-activated kinases (PAK) and Phospholipase C (PLC) signalling. Within C1 there were two sub-clusters (C1A and C1B) defined by 49 proteins related to cytoskeletal protein binding. C2 and C6 demonstrated opposite Rho family GTPase and Rho GDI signalling. Three proteins (MZB1, SND1 and AGL) identified in C6 increased the classification of active renal disease although this did not reach statistical significance (p = 0.0617). CONCLUSIONS: Unsupervised proteomic analysis identifies clusters of patients with active SLE, that are associated with clinical and serological features, which may facilitate biomarker discovery. The observed proteomic heterogeneity further supports the need for a personalised approach to treatment in SLE.

Multi-Omics Reveals Mechanisms of Partial Modulation of COVID-19 Dysregulation by Glucocorticoid Treatment.

Treatments for COVID-19 infections have improved dramatically since the beginning of the pandemic, and glucocorticoids have been a key tool in improving mortality rates. The UK's National Institute for Health and Care Excellence guidance is for treatment to be targeted only at those requiring oxygen supplementation, however, and the interactions between glucocorticoids and COVID-19 are not completely understood. In this work, a multi-omic analysis of 98 inpatient-recruited participants was performed by quantitative metabolomics (using targeted liquid chromatography-mass spectrometry) and data-independent acquisition proteomics. Both 'omics datasets were analysed for statistically significant features and pathways differentiating participants whose treatment regimens did or did not include glucocorticoids. Metabolomic differences in glucocorticoid-treated patients included the modulation of cortisol and bile acid concentrations in serum, but no alleviation of serum dyslipidemia or increased amino acid concentrations (including tyrosine and arginine) in the glucocorticoid-treated cohort relative to the untreated cohort. Proteomic pathway analysis indicated neutrophil and platelet degranulation as influenced by glucocorticoid treatment. These results are in keeping with the key role of platelet-associated pathways and neutrophils in COVID-19 pathogenesis and provide opportunity for further understanding of glucocorticoid action. The findings also, however, highlight that glucocorticoids are not fully effective across the wide range of 'omics dysregulation caused by COVID-19 infections.

Results of a UK National Cancer Research Institute Phase II study of brentuximab vedotin using a response-adapted design in the first-line treatment of patients with classical Hodgkin lymphoma unsuitable for chemotherapy due to age, frailty or comorbidity (BREVITY).

Standard treatment for classical Hodgkin lymphoma (cHL) is poorly tolerated in older patients and results disappointing. We assessed safety and efficacy of brentuximab vedotin (BV), in previously untreated patients with cHL unfit for standard treatment due to age, frailty or comorbidity. The primary outcome was complete metabolic response (CMR) by positron emission tomography/computed tomography after four BV cycles (PET4). The secondary outcomes included progression-free survival (PFS), overall survival (OS), and toxicity. In all, 35 patients with a median age of 77 years and median total Cumulative Illness Rating Scale for Geriatrics (CIRS-G) score of 6 were evaluable for toxicity and 31 for response. A median of four cycles were given (range one-16). In all, 14 patients required dose reduction due to toxicity and 11 patients stopped treatment due to adverse events (AEs). A total of 716 AEs were reported, of which 626 (88%) were Grade 1/2 and 27 (77%) patients had at least one AE Grade ≥3. At PET4, CMR was 25·8% [95% confidence interval (CI) 13·7-42.2%] and objective response rate 83·9% (95% CI 63·7-90·8%). Median PFS was 7·3 months (95% CI 5·2-9·0), and OS 19·5 months. Our results suggest that BV monotherapy is tolerable but suboptimal in the front-line therapy of elderly or comorbid patients with cHL. Combining BV with other agents may be more effective. Trial Registration: Clinicaltrials.gov identifier: NCT02567851.

The use of missing values in proteomic data-independent acquisition mass spectrometry to enable disease activity discrimination.

MOTIVATION: Data-independent acquisition mass spectrometry allows for comprehensive peptide detection and relative quantification than standard data-dependent approaches. While less prone to missing values, these still exist. Current approaches for handling the so-called missingness have challenges. We hypothesized that non-random missingness is a useful biological measure and demonstrate the importance of analysing missingness for proteomic discovery within a longitudinal study of disease activity. RESULTS: The magnitude of missingness did not correlate with mean peptide concentration. The magnitude of missingness for each protein strongly correlated between collection time points (baseline, 3 months, 6 months; R = 0.95-0.97, confidence interval = 0.94-0.97) indicating little time-dependent effect. This allowed for the identification of proteins with outlier levels of missingness that differentiate between the patient groups characterized by different patterns of disease activity. The association of these proteins with disease activity was confirmed by machine learning techniques. Our novel approach complements analyses on complete observations and other missing value strategies in biomarker prediction of disease activity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RadBone: bone toxicity following pelvic radiotherapy - a prospective randomised controlled feasibility study evaluating a musculoskeletal health package in women with gynaecological cancers undergoing pelvic radiotherapy.

INTRODUCTION: Patients receiving radiotherapy are at risk of developing radiotherapy-related insufficiency fractures, which are associated with increased morbidity and pose a significant burden to patients' quality of life and to the health system. Therefore, effective preventive techniques are urgently required. The RadBone randomised controlled trial (RCT) aims to determine the feasibility and acceptability of a musculoskeletal health package (MHP) intervention in women undergoing pelvic radiotherapy for gynaecological malignancies and to preliminary explore clinical effectiveness of the intervention. METHODS AND ANALYSIS: The RadBone RCT will evaluate the addition to standard care of an MHP consisting of a physical assessment of the musculoskeletal health, a 3-month prehabilitation personalised exercise package, as well as an evaluation of the fracture risk and if required the prescription of appropriate bone treatment including calcium, vitamin D and-for high-risk individuals-bisphosphonates. Forty participants will be randomised in each group (MHP or observation) and will be followed for 18 months. The primary outcome of this RCT will be feasibility, including the eligibility, screening and recruitment rate, intervention fidelity and attrition rates; acceptability and health economics. Clinical effectiveness and bone turnover markers will be evaluated as secondary outcomes. ETHICS AND DISSEMINATION: This study has been approved by the Greater Manchester East Research Ethics Committee (Reference: 20/NW/0410, November 2020). The results will be published in peer-reviewed journals, will be presented in national and international conferences and will be communicated to relevant stakeholders. Moreover, a plain English report will be shared with the study participants, patients' organisations and media. TRIAL REGISTRATION NUMBER: NCT04555317.

Changes in the Proteome Profile of People Achieving Remission of Type 2 Diabetes after Bariatric Surgery.

Bariatric surgery (BS) results in metabolic pathway recalibration. We have identified potential biomarkers in plasma of people achieving type 2 diabetes mellitus (T2DM) remission after BS. Longitudinal analysis was performed on plasma from 10 individuals following Roux-en-Y gastric bypass (n = 7) or sleeve gastrectomy (n = 3). Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was done on samples taken at 4 months before (baseline) and 6 and 12 months after BS. Four hundred sixty-seven proteins were quantified by SWATH-MS. Principal component analysis resolved samples from distinct time points after selection of key discriminatory proteins: 25 proteins were differentially expressed between baseline and 6 months post-surgery; 39 proteins between baseline and 12 months. Eight proteins (SHBG, TF, PRG4, APOA4, LRG1, HSPA4, EPHX2 and PGLYRP) were significantly different to baseline at both 6 and 12 months post-surgery. The panel of proteins identified as consistently different included peptides related to insulin sensitivity (SHBG increase), systemic inflammation (TF and HSPA4-both decreased) and lipid metabolism (APOA4 decreased). We found significant changes in the proteome for eight proteins at 6- and 12-months post-BS, and several of these are key components in metabolic and inflammatory pathways. These may represent potential biomarkers of remission of T2DM.

Relationship between the Plasma Proteome and Changes in Inflammatory Markers after Bariatric Surgery.

Severe obesity is a disease associated with multiple adverse effects on health. Metabolic bariatric surgery (MBS) can have significant effects on multiple body systems and was shown to improve inflammatory markers in previous short-term follow-up studies. We evaluated associations between changes in inflammatory markers (CRP, IL6 and TNFα) and circulating proteins after MBS. METHODS: Sequential window acquisition of all theoretical mass spectra (SWATH-MS) proteomics was performed on plasma samples taken at baseline (pre-surgery) and 6 and 12 months after MBS, and concurrent analyses of inflammatory/metabolic parameters were carried out. The change in absolute abundances of those proteins, showing significant change at both 6 and 12 months, was tested for correlation with the absolute and percentage (%) change in inflammatory markers. RESULTS: We found the following results: at 6 months, there was a correlation between %change in IL-6 and fold change in HSPA4 (rho = -0.659; p = 0.038) and in SERPINF1 (rho = 0.714, p = 0.020); at 12 months, there was a positive correlation between %change in IL-6 and fold change in the following proteins-LGALS3BP (rho = 0.700, p = 0.036), HSP90B1 (rho = 0.667; p = 0.05) and ACE (rho = 0.667, p = 0.05). We found significant inverse correlations at 12 months between %change in TNFα and the following proteins: EPHX2 and ACE (for both rho = -0.783, p = 0.013). We also found significant inverse correlations between %change in CRP at 12 months and SHBG (rho = -0.759, p = 0.029), L1CAM (rho = -0.904, p = 0.002) and AMBP (rho = -0.684, p = 0.042). CONCLUSION: Using SWATH-MS, we identified several proteins that are involved in the inflammatory response whose levels change in patients who achieve remission of T2DM after bariatric surgery in tandem with changes in IL6, TNFα and/or CRP. Future studies are needed to clarify the underlying mechanisms in how MBS decreases low-grade inflammation.

Effects of peroral insulin and glucose on circulating insulin-like growth factor-1, its binding proteins and thyroid hormones in neonatal calves.

There is disagreement in the literature about the ability of neonatal calves to absorb perorally administered insulin. This study evaluated the absorption of a bolus of insulin administered alone or with an energy souce and its effects on the circulating insulin-like growth factor system and thyroid hormones in newborn Holstein-Friesian calves. Within 1 h of dosing, mean serum insulin and triiodothyronine (T3) concentrations had increased considerably, whether the insulin was applied alone (n = 4) or together with glucose (n = 4), accompanied by marked hypoglycemia. No significant changes were observed in control calves (n = 4) given the vehicle solution. Increased serum glucose and T3 concentrations with no change in insulinemia occurred in a 4th group of calves given glucose alone. At 32 h of age and after 3 meals of colostrum there were no differences in glycemia, insulinemia, or proteinemia among the 4 groups of calves examined. Mean serum insulin-like growth factor-I (IGF-I) tended to decrease over this period in the control group. The decrease was more pronounced in the insulin-treated group but absent in both groups that received glucose. These differences were associated with equivalent differences in abundance of the 40-45K IGF-binding protein-3 (IGFBP-3); however, lower molecular mass IGFBPs were not affected. The results show that a pharmacological peroral dose of insulin can lead to rapid systemic alterations in the IGF/IGFBP system in neonatal calves that can be modified by simultaneous administration of a small energy supply in the form of glucose.

Integrating Allergen Analysis Within a Risk Assessment Framework: Approaches to Development of Targeted Mass Spectrometry Methods for Allergen Detection and Quantification in the iFAAM Project.

Allergen analysis is central to implementing and monitoring food allergen risk assessment and management processes by the food industry, but current methods for the determination of allergens in foods give highly variable results. The European Union-funded "Integrated Approaches to Food Allergen and Allergy Risk Management" (iFAAM) project has been working to address gaps in knowledge regarding food allergen management and analysis, including the development of novel MS and immuno-based allergen determination methods. Common allergenic food ingredients (peanut, hazelnut, walnut, cow's milk [Bos domesticus], and hen's egg [Gallus domesticus]) and common food matrixes (chocolate dessert and cookie) have been used for both clinical studies and analytical method development to ensure that the new methods are clinically relevant. Allergen molecules have been used as analytical targets and allergenic ingredients incurred into matrixes at levels close to reference doses that may trigger the use of precautionary allergen labeling. An interlaboratory method comparison has been undertaken for the determination of peanut in chocolate dessert using MS and immuno-based methods. The iFAAM approach has highlighted the need for methods to report test results in allergenic protein. This will allow food business operators to use them in risk assessments that are founded on clinical study data in which protein has been used as a measure of allergenic potency.