Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers.

Metabolic disease is a significant risk factor for severe COVID-19 infection, but the contributing pathways are not yet fully elucidated. Using data from two randomized controlled trials across 13 U.S. academic centers, our goal was to characterize metabolic features that predict severe COVID-19 and define a novel baseline metabolomic signature. Individuals (n = 133) were dichotomized as having mild or moderate/severe COVID-19 disease based on the WHO ordinal scale. Blood samples were analyzed using the Biocrates platform, providing 630 targeted metabolites for analysis. Resampling techniques and machine learning models were used to determine metabolomic features associated with severe disease. Ingenuity Pathway Analysis (IPA) was used for functional enrichment analysis. To aid in clinical decision making, we created baseline metabolomics signatures of low-correlated molecules. Multivariable logistic regression models were fit to associate these signatures with severe disease on training data. A three-metabolite signature, lysophosphatidylcholine a C17:0, dihydroceramide (d18:0/24:1), and triacylglyceride (20:4_36:4), resulted in the best discrimination performance with an average test AUROC of 0.978 and F1 score of 0.942. Pathways related to amino acids were significantly enriched from the IPA analyses, and the mitogen-activated protein kinase kinase 5 (MAP2K5) was differentially activated between groups. In conclusion, metabolites related to lipid metabolism efficiently discriminated between mild vs. moderate/severe disease. SDMA and GABA demonstrated the potential to discriminate between these two groups as well. The mitogen-activated protein kinase kinase 5 (MAP2K5) regulator is differentially activated between groups, suggesting further investigation as a potential therapeutic pathway.

Effects of Carboxymethylcellulose Artificial Tears on Ocular Surface Microbiome Diversity and Composition, A Randomized Controlled Trial.

Purpose: Carboxymethylcellulose is an artificial tear ingredient known to decrease gut microbiome diversity when ingested. This study examines the effect of carboxymethylcellulose on ocular surface microbiome diversity and composition. Methods: Healthy adult participants without significant ophthalmic disease or concurrent carboxymethylcellulose artificial tear use were allocated randomly to take carboxymethylcellulose or control polyethylene glycol artificial tears for seven days. Conjunctival swabs were collected before and after artificial tear treatment. This trial is registered at clinicaltrials.gov (NCT05292755). Primary outcomes included abundance of bacterial taxa and microbiome diversity as measured by the Chao-1 richness estimate, Shannon's phylogenetic diversity index, and UniFrac analysis. Secondary outcomes included Ocular Surface Disease Index scores and artificial tear compliance. Results: Of the 80 enrolled participants, 66 completed the trial. Neither intervention affected Chao-1 richness (analysis of variance [ANOVA], P = 0.231) or Shannon's diversity index (ANOVA, P = 0.224). Microbiome samples did not separate by time point (permutation multivariate analysis of variance [PERMANOVA], P = 0.223) or intervention group (PERMANOVA, P = 0.668). LEfSe taxonomic analysis revealed that carboxymethylcellulose depleted several taxa including Bacteroides and Lachnoclostridium, but enriched Enterobacteriaceae, Citrobacter, and Gordonia. Both interventions decreased OSDI scores (Wilcoxon signed rank test, P < 0.05), but there was no significant difference between interventions (Mann-Whitney U, P = 0.54). Conclusions: Carboxymethylcellulose artificial tears increased Actinobacteriota but decreased Bacteroides and Firmicutes bacteria. Carboxymethylcellulose artificial tears do not affect ocular surface microbiome diversity and are not significantly more effective than polyethylene glycol artificial tears for dry eye treatment. Translational Relevance: The 16S microbiome analysis has revealed small changes in the ocular surface microbiome associated with artificial tear use.

Prognosis of Open Globe Injuries at a Tertiary Referral Center: The Modified Florida Ocular Trauma Score.

PURPOSE: To analyze vision outcomes after open globe injury and propose modifications to the ocular trauma score to offer more specific vision prognoses. DESIGN: Validity and reliability analysis. METHODS: Patients presenting to the University of Florida with a new open globe injury from October 2015 to January 2021 with subsequent follow-up were included in the study. Demographics, ophthalmic history, trauma details, timeline, imaging, operative findings, and ocular examinations were collected from the medical record. Z tests, χ2 test, Fisher exact test, receiver operating characteristic curve, and ordinal correlation were used. A weighted logistic model was optimized to predict vision outcomes. Measured outcomes included the best-corrected visual acuity, Ocular Trauma Score category, and performance of vision prognosis scores. RESULTS: A total of 162 eyes were identified from chart review. Eighty percent of the Ocular Trauma Score categories were accurate. Only the absence of orbital fractures was associated with a significant weight in the logistic model, which produced more accurate prognoses for 59 patients, and less accurate prognoses for 30 patients compared to the Ocular Trauma Score. Kendall Tau-B was 0.639 for the logistic model and 0.582 for the Ocular Trauma Score. CONCLUSIONS: The Ocular Trauma Score accurately estimates vision prognosis after open globe injury. We propose inclusion of orbital fracture status in our Modified Florida Ocular Trauma Score. This addended score is more correlated with final vision outcome and provides more specific prognoses for severe open globe injuries. Prospective, multicenter validation is needed to refine and confirm the use of this new scoring system.

Expression of DNA Mismatch Repair Proteins, PD1 and PDL1 in Barrett's Neoplasia.

BACKGROUND/AIM: Cancers with a microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) status respond to immune checkpoint inhibition (ICI). Regardless of the tumor type, MSI-H/dMMR status is a reliable biomarker for ICI responsiveness. This study aimed at determining the MSI-H status in precursor lesions to esophageal adenocarcinoma (EAC) such as Barrett's esophagus (BE) and BE with either low-grade dysplasia (LGD) or high-grade dysplasia (HGD). PATIENTS AND METHODS: We performed immunohistochemical staining (IHC) for PMS2, MSH6, PD1, and PD-L1. RESULTS: All cases of BE (50), LGD (48), and HGD (50) had intact PMS2 and MSH6 nuclear expression; were negative for PD1; and had a PD-L1 combined positive score (CPS) score <1. One EAC case (2%) was negative for PMS2 nuclear expression. One HGD case (2%) and two EAC cases (4%) were PD1 positive (CPS score <1 applied to PD1). One EAC case (2%) had a CPS score >1, and one EAC case (2%) was MSI-H. MSI-H tumors usually show PD-L1 expression, although the MSI-H EAC in this study had a PD-L1 CPS score of <1. CONCLUSION: Further studies investigating EAC and its precursor lesions for PD1, PD-L1, and dMMR status may be informative regarding the immunogenicity of the evolution of EAC.