Metabolomic analysis of obesity, metabolic syndrome, and type 2 diabetes: amino acid and acylcarnitine levels change along a spectrum of metabolic wellness

Background Metabolic syndrome (MS) is a construct used to separate “healthy” from “unhealthy” obese patients, and is a major risk factor for type 2 diabetes (T2D) and cardiovascular disease. There is controversy over whether obese “metabolically well” persons have a higher morbidity and mortality than lean counterparts, suggesting that MS criteria do not completely describe physiologic risk factors or consequences of obesity. We hypothesized that metabolomic analysis of plasma would distinguish obese individuals with and without MS and T2D along a spectrum of obesity-associated metabolic derangements, supporting metabolomic analysis as a tool for a more detailed assessment of metabolic wellness than currently used MS criteria. Methods Fasting plasma samples from 90 adults were assigned to groups based on BMI and ATP III criteria for MS: (1) lean metabolically well (LMW; n = 24); (2) obese metabolically well (OBMW; n = 26); (3) obese metabolically unwell (OBMUW; n = 20); and (4) obese metabolically unwell with T2D (OBDM; n = 20). Forty-one amino acids/dipeptides, 33 acylcarnitines and 21 ratios were measured. Obesity and T2D effects were analyzed by Wilcoxon rank-sum tests comparing obese nondiabetics vs LMW, and OBDM vs nondiabetics, respectively. Metabolic unwellness was analyzed by Jonckheere-Terpstra trend tests, assuming worsening health from LMW → OBMW → OBMUW. To adjust for multiple comparisons, statistical significance was set at p < 0.005. K-means cluster analysis of aggregated amino acid and acylcarnitine data was also performed. Results Analytes and ratios significantly increasing in obesity, T2D, and with worsening health include: branched-chain amino acids (BCAAs), cystine, alpha-aminoadipic acid, phenylalanine, leucine + lysine, and short-chain acylcarnitines/total carnitines. Tyrosine, alanine and propionylcarnitine increase with obesity and metabolic unwellness. Asparagine and the tryptophan/large neutral amino acid ratio decrease with T2D and metabolic unwellness. Malonylcarnitine decreases in obesity and 3-OHbutyrylcarnitine increases in T2D; neither correlates with unwellness. Cluster analysis did not separate subjects into discreet groups based on metabolic wellness. Discussion Levels of 15 species and metabolite ratios trend significantly with worsening metabolic health; some are newly recognized. BCAAs, aromatic amino acids, lysine, and its metabolite, alpha-aminoadipate, increase with worsening health. The lysine pathway is distinct from BCAA metabolism, indicating that biochemical derangements associated with MS involve pathways besides those affected by BCAAs. Even those considered “obese, metabolically well” had metabolite levels which significantly trended towards those found in obese diabetics. Overall, this analysis yields a more granular view of metabolic wellness than the sole use of cardiometabolic MS parameters. This, in turn, suggests the possible utility of plasma metabolomic analysis for research and public health applications

Derivation and external validation of a prediction model for pneumococcal urinary antigen test positivity in patients with community-acquired pneumonia

Abstract Objective: Derive and externally validate a prediction model for pneumococcal urinary antigen test (pUAT) positivity. Methods: Retrospective cohort study of adults admitted with community-acquired pneumonia (CAP) to 177 U.S. hospitals in the Premier Database (derivation and internal validation samples) or 12 Cleveland Clinic hospitals (external validation sample). We utilized multivariable logistic regression to predict pUAT positivity in the derivation dataset, followed by model performance evaluation in both validation datasets. Potential predictors included demographics, comorbidities, clinical findings, and markers of disease severity. Results: Of 198,130 Premier patients admitted with CAP, 27,970 (14.1%) underwent pUAT; 1962 (7.0%) tested positive. The strongest predictors of pUAT positivity were history of pneumococcal infection in the previous year (OR 6.99, 95% CI 4.27–11.46), severe CAP on admission (OR 1.76, 95% CI 1.56–1.98), substance abuse (OR 1.57, 95% CI 1.27–1.93), smoking (OR 1.23, 95% CI 1.09–1.39), and hyponatremia (OR 1.35, 95% CI 1.17–1.55). Negative predictors included IV antibiotic use in past year (OR 0.65, 95% CI 0.52–0.82), congestive heart failure (OR 0.72, 95% CI 0.63–0.83), obesity (OR 0.71, 95% CI 0.60–0.85), and admission from skilled nursing facility (OR 0.60, 95% CI 0.45–0.78). Model c-statistics were 0.60 and 0.67 in the internal and external validation cohorts, respectively. Compared to guideline-recommended testing of severe CAP patients, our model would have detected 23% more cases with 5% fewer tests. Conclusion: Readily available data can identify patients most likely to have a positive pUAT. Our model could be incorporated into automated clinical decision support to improve test efficiency and antimicrobial stewardship

Direct contact with perivascular tumor cells enhances integrin αvβ3 signaling and migration of endothelial cells

The secretion of soluble pro-angiogenic factors by tumor cells and stromal cells in the perivascular niche promotes the aggressive angiogenesis that is typical of glioblastoma (GBM). Here, we show that angiogenesis also can be promoted by a direct interaction between brain tumor cells, including tumor cells with cancer stem-like properties (CSCs), and endothelial cells (ECs). As shown in vitro, this direct interaction is mediated by binding of integrin αvβ3 expressed on ECs to the RGD-peptide in L1CAM expressed on CSCs. It promotes both EC network formation and enhances directed migration toward basic fibroblast growth factor. Activation of αvβ3 and bone marrow tyrosine kinase on chromosome X (BMX) is required for migration stimulated by direct binding but not for migration stimulated by soluble factors. RGD-peptide treatment of mice with established intracerebral GBM xenografts significantly reduced the percentage of Sox2-positive tumor cells and CSCs in close proximity to ECs, decreased integrin αvβ3 and BMX activation and p130CAS phosphorylation in the ECs, and reduced the vessel surface area. These results reveal a previously unrecognized aspect of the regulation of angiogenesis in GBM that can impact therapeutic anti-angiogenic targeting

Abnormal thrombosis and neutrophil activation increase hospital-acquired sacral pressure injuries and morbidity in COVID-19 patients

Hospitalized patients have an increased risk of developing hospital-acquired sacral pressure injury (HASPI). However, it is unknown whether SARS-CoV-2 infection affects HASPI development. To explore the role of SARS-CoV-2 infection in HASPI development, we conducted a single institution, multi-hospital, retrospective study of all patients hospitalized for ≥5 days from March 1, 2020 to December 31, 2020. Patient demographics, hospitalization information, ulcer characteristics, and 30-day-related morbidity were collected for all patients with HASPIs, and intact skin was collected from HASPI borders in a patient subset. We determined the incidence, disease course, and short-term morbidity of HASPIs in COVID-19(+) patients, and characterized the skin histopathology and tissue gene signatures associated with HASPIs in COVID-19 disease. COVID-19(+) patients had a 63% increased HASPI incidence rate, HASPIs of more severe ulcer stage (OR 2.0, p&lt;0.001), and HASPIs more likely to require debridement (OR 3.1, p=0.04) compared to COVID-19(-) patients. Furthermore, COVID-19(+) patients with HASPIs had 2.2x increased odds of a more severe hospitalization course compared to COVID-19(+) patients without HASPIs. HASPI skin histology from COVID-19(+) patients predominantly showed thrombotic vasculopathy, with the number of thrombosed vessels being significantly greater than HASPIs from COVID-19(-) patients. Transcriptional signatures of a COVID-19(+) sample subset were enriched for innate immune responses, thrombosis, and neutrophil activation genes. Overall, our results suggest that immunologic dysregulation secondary to SARS-CoV-2 infection, including neutrophil dysfunction and abnormal thrombosis, may play a pathogenic role in development of HASPIs in patients with severe COVID-19

Making the grade in a portfolio-based system: student performance and the student perspective

Assessment is such an integral part of the educational system that we rarely reflect on its value and impact. Portfolios have gained in popularity, but much attention has emphasized the end-user and portfolio assessment. Here we focus on the portfolio creator (the student) and examine whether their educational needs are met with such an assessment method. This study aims to investigate how assessment practices influence classroom performance and the learning experience of the student in a graduate education setting. Studied were 33 medical students at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, a program utilizing a portfolio-based system. The students may elect to simultaneously enroll in a Masters program; however, these programs employ traditional letter grades. Thus creating a unique opportunity to assess 25 portfolio only (P) students and 8 portfolio and grade (PG) students concurrently taking a course that counts for both programs. Classroom performance was measured via a comprehensive evaluation where the PG students scored modestly better (median total scores, 72% P vs. 76% PG). Additionally, a survey was conducted to gain insight into student’s perspective on how assessment method impacts the learning experience. The students in the PG group (those receiving a grade) reported increased stress but greater affirmation and self-assurance regarding their knowledge and skill mastery. Incorporation of such affirmation remains a challenge for portfolio-based systems and an area for investigation and improvement

Adding propensity scores to pure prediction models fails to improve predictive performance

Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression) were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1) concordance indices; (2) Brier scores; and (3) calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling