Quantitative planar array screen of 1000 proteins uncovers novel urinary protein biomarkers of lupus nephritis.

OBJECTIVE: The goal of these studies is to discover novel urinary biomarkers of lupus nephritis (LN). METHODS: Urine from systemic lupus erythematosus (SLE) patients was interrogated for 1000 proteins using a novel, quantitative planar protein microarray. Hits were validated in an independent SLE cohort with inactive, active non-renal (ANR) and active renal (AR) patients, in a cohort with concurrent renal biopsies, and in a longitudinal cohort. Single-cell renal RNA sequencing data from LN kidneys were examined to deduce the cellular origin of each biomarker. RESULTS: Screening of 1000 proteins revealed 64 proteins to be significantly elevated in SLE urine, of which 17 were ELISA validated in independent cohorts. Urine Angptl4 (area under the curve (AUC)=0.96), L-selectin (AUC=0.86), TPP1 (AUC=0.84), transforming growth factor-ß1 (TGFß1) (AUC=0.78), thrombospondin-1 (AUC=0.73), FOLR2 (AUC=0.72), platelet-derived growth factor receptor-ß (AUC=0.67) and PRX2 (AUC=0.65) distinguished AR from ANR SLE, outperforming anti-dsDNA, C3 and C4, in terms of specificity, sensitivity and positive predictive value. In multivariate regression analysis, urine Angptl4, L-selectin, TPP1 and TGFß1 were highly associated with disease activity, even after correction for demographic variables. In SLE patients with serial follow-up, urine L-selectin (followed by urine Angptl4 and TGFß1) were best at tracking concurrent or pending disease flares. Importantly, several proteins elevated in LN urine were also expressed within the kidneys in LN, either within resident renal cells or infiltrating immune cells, based on single-cell RNA sequencing analysis. CONCLUSION: Unbiased planar array screening of 1000 proteins has led to the discovery of urine Angptl4, L-selectin and TGFß1 as potential biomarker candidates for tracking disease activity in LN.

Learnings in Digital Health Design: Insights From a Pilot Web App for Structured Note-Taking for Patients With Rheumatoid Arthritis.

BACKGROUND: Patients fail to accurately remember 40% to 80% of medical information relayed during doctor appointments, and most standard after-visit summaries fail to effectively help patients comply with behaviors to manage their health conditions. The value of technology to empower and engage patients in their health management has been shown, and here we apply technology to help patients remember and act upon information communicated during their medical appointments. OBJECTIVE: We describe the development of WellNote, a digital notebook designed for patients to create a customized plan to manage their condition, plan for their appointments, track important actions (eg, medications and labs), and receive reminders for appointments and labs. METHODS: For this pilot, we chose to focus on rheumatoid arthritis, a chronic condition that relies on many of these features. The development of WellNote followed a structured method based on design thinking and co-design principles, with the app built in close collaboration with patients and a physician partner to ensure clinical relevance. Our design process consisted of 3 rounds: patient and physician interviews, visual prototypes, and a functional pilot app. RESULTS: Over the course of the design process, WellNote's features were refined, with the final version being a digital notebook designed for patients with rheumatoid arthritis to manage their health by helping them track medications and labs and plan for appointments. It features several pages, like a dashboard, patient profile, appointment notes, preplanning, medication management, lab tracking, appointment archives, reminders, and a pillbox for medication visualization. CONCLUSIONS: WellNote's active and structured note-taking features allow patients to clearly document the information from their physician without detracting from the conversation, helping the patient to become more empowered and engaged in their health management. The co-design process empowered these stakeholders to share their needs and participate in the development of a solution that truly solves pain points for these groups. This viewpoint highlights the role of digital health tools and the co-design of new health care innovations to empower patients and support clinicians.

Comprehensive aptamer-based screen of 1317 proteins uncovers improved stool protein markers of colorectal cancer.

BACKGROUND: To screen and validate novel stool protein biomarkers of colorectal cancer (CRC). METHODS: A novel aptamer-based screen of 1317 proteins was used to uncover elevated proteins in the stool of patients with CRC, as compared to healthy controls (HCs) in a discovery cohort. Selected biomarker candidates from the discovery cohort were ELISA validated in three independent cross-sectional cohorts comprises 76 CRC patients, 15 adenoma patients, and 63 healthy controls, from two different ethnicities. The expression of the potential stool biomarkers within CRC tissue was evaluated using single-cell RNA-seq datasets. RESULTS: A total of 92 proteins were significantly elevated in CRC samples as compared to HCs in the discovery cohort. Among Caucasians, the 5 most discriminatory proteins among the 16 selected proteins, ordered by their ability to distinguish CRC from adenoma and healthy controls, were MMP9, haptoglobin, myeloperoxidase, fibrinogen, and adiponectin. Except myeloperoxidase, the others were significantly associated with depth of tumor invasion. The 8 stool proteins with the highest AUC values were also discriminatory in a second cohort of Indian CRC patients. Several of the stool biomarkers elevated in CRC were also expressed within CRC tissue, based on the single-cell RNA-seq analysis. CONCLUSIONS: Stool MMP9, fibrinogen, myeloperoxidase, and haptoglobin emerged as promising CRC stool biomarkers, outperforming stool Hemoglobin. Longitudinal studies are warranted to assess the clinical utility of these novel biomarkers in early diagnosis of CRC.

A Systematic Review of Interpathologist Agreement in Histologic Classification of Lupus Nephritis.

INTRODUCTION: Lupus nephritis (LN) is one of the most severe manifestations of systemic lupus erythematosus (SLE), resulting in increased morbidity and mortality. The gold standard for diagnosis of LN is a renal biopsy. Considering the importance of the biopsy in determining long-term prognostication and treatment decisions, it is crucial to assess renal histopathology with utmost accuracy and precision. This review represents a systematic search of published literature to estimate the degree of interpathologist reproducibility in current assessment of LN. METHODS: Using the PubMed and Google Scholar search engines, studies analyzing the agreement of 4 or more pathologists assessing LN slides using the ISN/Renal Pathology Society (RPS) classification, activity index, and chronicity index were selected for analysis in this systematic review. RESULTS: In reviewing 6 qualifying studies (those analyzing the agreement of 4 or more pathologists using the ISN/RPS classification, activity index, and chronicity index) for the assignment of ISN/RPS class was 0.325 (interquartile range [IQR] 0.2405-0.425), which is "poor." The median interpathologist concordance values for the assigned activity index and chronicity index were "moderate": 0.52 (IQR 0.51-0.69) and 0.49 (IQR 0.36-0.58), respectively. CONCLUSION: Thus, the current scoring using the ISN/RPS classification system and activity and chronicity indices for LN exhibits poor interpathologist agreement, which limits its use in clinical practice. Given that this can have severe repercussions on a patient's treatment and prognosis, efforts to update pathology assessment guidelines, objectively measurable biomarkers, and deep learning approaches are strongly warranted.

Urine protein biomarkers for the detection, surveillance, and treatment response prediction of bladder cancer.

The "gold standard" diagnostic procedure for bladder cancer is cystoscopy, a technique that can be invasive, expensive, and a possible cause of urinary tract infection. Unlike techniques such as histology, PCR, and staining, assays for protein biomarkers lend themselves well to the creation of efficient point-of-care tests, which are easy to use and yield fast results. A couple of urine-based tests have been approved by the U.S. FDA, but these tests suffer from low sensitivity. Hence, there is clearly a need for more reliable non-invasive biomarkers of bladder cancer. Urinary biomarkers are particularly attractive due to the direct contact of the urine with the urothelial tumor and the ease of sample collection. With these considerations, this review aims to provide a comprehensive listing of the most promising protein biomarkers of bladder cancer in urine. Biomarkers are organized by their potential role in detection, surveillance, or monitoring of treatment response. The purpose of this review is to assess progress towards the goal of identifying ideal urinary proteins for use in each of the above three biomarker applications in bladder cancer.