Comparative proteomic profiling of uric acid, ammonium acid urate, and calcium-based kidney stones.

INTRODUCTION: Kidney stone matrix proteins may help explain cellular mechanisms of stone genesis. However, most existing proteomic studies have focused on calcium oxalate stones. Here, we present a comparative proteomic analysis of different kidney stone types. METHODS: Proteins were extracted from the stones of patients undergoing percutaneous nephrolithotomy (PCNL). Approximately 20 µg of protein was digested into tryptic peptides using filter aided sample preparation, followed by liquid chromatography tandem-mass-spectrometry using an EASY-nLC 1200 and Orbitrap Fusion Lumos mass spectrometer. A standard false discovery rate cutoff of 1% was used for protein identification. Stone analysis was used to organize stone samples into similar groups. We selected the top 5% of proteins based on total ion intensities and used DAVID and Ingenuity Pathway Analysis to identify and compare significantly enriched gene ontologies and pathways between groups. RESULTS: Six specimens were included and organized into the following four groups: 1) mixed uric acid (UA) and calcium-based, 2) pure UA, 3) pure ammonium acid urate (AAU), and 4) pure calcium-based. We identified 2,426 unique proteins (1,310-1,699 per sample), with 11-16 significantly enriched KEGG pathways identified per group and compared via heatmap. Based on number of unique proteins identified, this is the deepest proteomic study of kidney stones to date and the first such study of an AAU stone. CONCLUSIONS: The results indicate that mixed UA and calcium-based kidney stones are more similar to pure UA stones than pure calcium-based stones. AAU stones appear more similar to pure calcium-based stones than UA containing stones and may be related to parasitic infections. Further research with larger cohorts and histopathologic correlation is warranted.

An accessible, efficient, and accurate natural language processing method for extracting diagnostic data from pathology reports.

Context: Analysis of diagnostic information in pathology reports for the purposes of clinical or translational research and quality assessment/control often requires manual data extraction, which can be laborious, time-consuming, and subject to mistakes. Objective: We sought to develop, employ, and evaluate a simple, dictionary- and rule-based natural language processing (NLP) algorithm for generating searchable information on various types of parameters from diverse surgical pathology reports. Design: Data were exported from the pathology laboratory information system (LIS) into extensible markup language (XML) documents, which were parsed by NLP-based Python code into desired data points and delivered to Excel spreadsheets. Accuracy and efficiency were compared to a manual data extraction method with concordance measured by Cohen's κ coefficient and corresponding P values. Results: The automated method was highly concordant (90%-100%, P<.001) with excellent inter-observer reliability (Cohen's κ: 0.86-1.0) compared to the manual method in 3 clinicopathological research scenarios, including squamous dysplasia presence and grade in anal biopsies, epithelial dysplasia grade and location in colonoscopic surveillance biopsies, and adenocarcinoma grade and amount in prostate core biopsies. Significantly, the automated method was 24-39 times faster and inherently contained links for each diagnosis to additional variables such as patient age, location, etc., which would require additional manual processing time. Conclusions: A simple, flexible, and scaleable NLP-based platform can be used to correctly, safely, and quickly extract and deliver linked data from pathology reports into searchable spreadsheets for clinical and research purposes.

Baseline Histological Findings Do Not Predict the Risk of Subsequent Extension in Patients with Limited Ulcerative Colitis.

BACKGROUND: Among patients with limited ulcerative colitis (UC), 30% ultimately extend to pancolitis and are at increased risk of adverse clinical outcomes. Risk of endoscopic extension has been found to correlate with clinical features such as early age of onset. AIMS: We sought to determine whether histologic features correlate with disease extension. METHODS: The study population consisted of 40 patients with UC from two large academic centers diagnosed between 2006 and 2017. Eligible cases had a diagnosis of endoscopically limited UC (Montreal E1 or E2) at baseline and ≥ 2 subsequent endoscopic examinations with biopsies. Severity of inflammation was scored using both the Mount Sinai Activity Index and Nancy Histological Index. RESULTS: Patients were divided into two cohorts: those who progressed to pancolitis (Montreal E3) were defined as "Extenders" (n = 21), whereas "Non-extenders" (n = 19) were cases without progression in the follow-up period. The median follow-up time was 58.4 months. The histologic scores in the endoscopically involved mucosa of the index biopsies were not associated with subsequent extension of disease, overall. However, among extender cohort, the index histology scores correlated with biopsy scores at extension (r = 0.455, P = 0.044) and index severity was associated with a shorter time to extension (r = - 0.611, P = 0.003). Furthermore, female patients had a shorter time to extension (P = 0.013). CONCLUSIONS: Histological severity of limited UC is not an independent predictor of extension in UC. However, among patients who subsequently extend, severe inflammation at baseline correlates with shorter progression time and severe inflammation when extension occurs. Patients with limited UC but severe histologic inflammation may warrant more frequent endoscopic surveillance.

Development and characterization of a quantitative ELISA to detect anti-SARS-CoV-2 spike antibodies.

A novel clinical assay for the detection and quantitation of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was adapted from an in-house, research-based enzyme-linked immunosorbent assay (ELISA). Development and validation were performed under regulatory guidelines, and the test obtained emergency use authorization (EUA) from the New York State Department of Health (NYSDOH) and the Food and Drug Administration (FDA). The Mount Sinai coronavirus disease 2019 (COVID-19) antibody assay is an orthogonal, quantitative direct ELISA test which detects antibodies reactive to the receptor binding domain (RBD) and the spike protein of the novel SARS-CoV-2. The assay is performed on 96-well plates coated with either SARS-CoV-2 recombinant RBD or spike proteins. The test is divided into two stages, a qualitative screening assay against RBD and a quantitative assay against the full-length spike protein. The test uses pooled high titer serum as a reference standard. Negative pre-COVID-19 and positive post-COVID-19, PCR-confirmed specimens were incorporated in each ELISA test run, and the assays were performed independently at two different locations. The Mount Sinai COVID-19 serology performed with high sensitivity and specificity, 92.5% (95% CI: 0.785-0.980) and 100% (CI: 0.939-1.000) respectively. Between-run precision was assessed with a single run repeated over 22 days; and within-run precision was assessed with 10 replicates per day over 22 days. Both were within reported acceptance criteria (CV ≤ 20%). This population-based study reveals the applicability and reliability of this novel orthogonal COVID-19 serology test for the detection and quantitation of antibodies against SARS-CoV-2, allowing a broad set of clinical applications, including the broad evaluation of SARS-CoV-2 seroprevalence and antibody profiling in different population subsets.

Pathophysiology of SARS-CoV-2: the Mount Sinai COVID-19 autopsy experience.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated clinical syndrome COVID-19 are causing overwhelming morbidity and mortality around the globe and disproportionately affected New York City between March and May 2020. Here, we report on the first 100 COVID-19-positive autopsies performed at the Mount Sinai Hospital in New York City. Autopsies revealed large pulmonary emboli in six cases. Diffuse alveolar damage was present in over 90% of cases. We also report microthrombi in multiple organ systems including the brain, as well as hemophagocytosis. We additionally provide electron microscopic evidence of the presence of the virus in our samples. Laboratory results of our COVID-19 cohort disclose elevated inflammatory markers, abnormal coagulation values, and elevated cytokines IL-6, IL-8, and TNFα. Our autopsy series of COVID-19-positive patients reveals that this disease, often conceptualized as a primarily respiratory viral illness, has widespread effects in the body including hypercoagulability, a hyperinflammatory state, and endothelial dysfunction. Targeting of these multisystemic pathways could lead to new treatment avenues as well as combination therapies against SARS-CoV-2 infection.

An inflammatory cytokine signature predicts COVID-19 severity and survival.

Several studies have revealed that the hyper-inflammatory response induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major cause of disease severity and death. However, predictive biomarkers of pathogenic inflammation to help guide targetable immune pathways are critically lacking. We implemented a rapid multiplex cytokine assay to measure serum interleukin (IL)-6, IL-8, tumor necrosis factor (TNF)-α and IL-1ß in hospitalized patients with coronavirus disease 2019 (COVID-19) upon admission to the Mount Sinai Health System in New York. Patients (n = 1,484) were followed up to 41 d after admission (median, 8 d), and clinical information, laboratory test results and patient outcomes were collected. We found that high serum IL-6, IL-8 and TNF-α levels at the time of hospitalization were strong and independent predictors of patient survival (P < 0.0001, P = 0.0205 and P = 0.0140, respectively). Notably, when adjusting for disease severity, common laboratory inflammation markers, hypoxia and other vitals, demographics, and a range of comorbidities, IL-6 and TNF-α serum levels remained independent and significant predictors of disease severity and death. These findings were validated in a second cohort of patients (n = 231). We propose that serum IL-6 and TNF-α levels should be considered in the management and treatment of patients with COVID-19 to stratify prospective clinical trials, guide resource allocation and inform therapeutic options.

An inflammatory cytokine signature helps predict COVID-19 severity and death.

The COVID-19 pandemic caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to more than 100,000 deaths in the United States. Several studies have revealed that the hyper-inflammatory response induced by SARS-CoV-2 is a major cause of disease severity and death in infected patients. However, predictive biomarkers of pathogenic inflammation to help guide targetable immune pathways are critically lacking. We implemented a rapid multiplex cytokine assay to measure serum IL-6, IL-8, TNF-α, and IL-1ß in hospitalized COVID-19 patients upon admission to the Mount Sinai Health System in New York. Patients (n=1484) were followed up to 41 days (median 8 days) and clinical information, laboratory test results and patient outcomes were collected. In 244 patients, cytokine measurements were repeated over time, and effect of drugs could be assessed. Kaplan-Meier methods were used to compare survival by cytokine strata, followed by Cox regression models to evaluate the independent predictive value of baseline cytokines. We found that high serum IL-6, IL-8, and TNF-α levels at the time of hospitalization were strong and independent predictors of patient survival. Importantly, when adjusting for disease severity score, common laboratory inflammation markers, hypoxia and other vitals, demographics, and a range of comorbidities, IL-6 and TNF-α serum levels remained independent and significant predictors of disease severity and death. We propose that serum IL-6 and TNF-α levels should be considered in the management and treatment of COVID-19 patients to stratify prospective clinical trials, guide resource allocation and inform therapeutic options. We also propose that patients with high IL-6 and TNF-α levels should be assessed for combinatorial blockade of pathogenic inflammation in this disease.