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Clostridioides difficile (C. difficile) is a global threat and has significant implications for individuals and health care systems. Little is known about host molecular mechanisms and transcriptional changes in peripheral immune cells. This is the first gene expression study in whole blood from patients with C. difficile infection. We took blood and stool samples from patients with toxigenic C. difficile infection (CDI), non-toxigenic C. difficile infection (GDH), inflammatory bowel disease (IBD), diarrhea from other causes (DC), and healthy controls (HC). We performed transcriptome-wide RNA profiling on peripheral blood to identify diarrhea common and CDI unique gene sets. Diarrhea groups upregulated innate immune responses with neutrophils at the epicenter. The common signature associated with diarrhea was non-specific and shared by various other inflammatory conditions. CDI had a unique 45 gene set reflecting the downregulation of humoral and T cell memory functions. Dysregulation of immunometabolic genes was also abundant and linked to immune cell fate during differentiation. Whole transcriptome analysis of white cells in blood from patients with toxigenic C. difficile infection showed that there is an impairment of adaptive immunity and immunometabolism.

Each year in the United States, Clostridioides difficile causes nearly 500,000 gastrointestinal infections that range from mild diarrhea to severe colitis and death. The ability to identify patients at increased risk for severe disease or mortality at the time of diagnosis of C. difficile infection (CDI) would allow clinicians to effectively allocate disease modifying therapies. In this study, we developed models consisting of only a small number of serum biomarkers that are capable of predicting both 30-day all-cause mortality and adverse outcomes of patients at time of CDI diagnosis. We were able to validate these models through experimental mouse infection. This provides evidence that the biomarkers reflect the underlying pathophysiology and that our mouse model of CDI reflects the pathogenesis of human infection. Predictive models can not only assist clinicians in identifying patients at risk for severe CDI but also be utilized for targeted enrollment in clinical trials aimed at reduction of adverse outcomes from severe CDI. Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after diagnosis of CDI in two cohorts. Biomarkers were measured with a custom multiplex bead array assay. Patients were classified using IDSA severity criteria and the development of disease-related complications (DRCs), which were defined as ICU admission, colectomy, and/or death attributed to CDI. Unadjusted and adjusted models were built using logistic and elastic net modeling. The best model for severity included procalcitonin (PCT) and hepatocyte growth factor (HGF) with an area (AUC) under the receiver operating characteristic (ROC) curve of 0.74 (95% confidence interval, 0.67 to 0.81). The best model for 30-day mortality included interleukin-8 (IL-8), PCT, CXCL-5, IP-10, and IL-2Rα with an AUC of 0.89 (0.84 to 0.95). The best model for DRCs included IL-8, procalcitonin, HGF, and IL-2Rα with an AUC of 0.84 (0.73 to 0.94). To validate our models, we employed experimental infection of mice with C. difficile . Antibiotic-treated mice were challenged with C. difficile and a similar panel of serum biomarkers was measured. Applying each model to the mouse cohort of severe and nonsevere CDI revealed AUCs of 0.59 (0.44 to 0.74), 0.96 (0.90 to 1.0), and 0.89 (0.81 to 0.97). In both human and murine CDI, models based on serum biomarkers predicted adverse CDI outcomes. Our results support the use of serum-based biomarker panels to inform Clostridioides difficile infection treatment. IMPORTANCE Each year in the United States, Clostridioides difficile causes nearly 500,000 gastrointestinal infections that range from mild diarrhea to severe colitis and death. The ability to identify patients at increased risk for severe disease or mortality at the time of diagnosis of C. difficile infection (CDI) would allow clinicians to effectively allocate disease modifying therapies. In this study, we developed models consisting of only a small number of serum biomarkers that are capable of predicting both 30-day all-cause mortality and adverse outcomes of patients at time of CDI diagnosis. We were able to validate these models through experimental mouse infection. This provides evidence that the biomarkers reflect the underlying pathophysiology and that our mouse model of CDI reflects the pathogenesis of human infection. Predictive models can not only assist clinicians in identifying patients at risk for severe CDI but also be utilized for targeted enrollment in clinical trials aimed at reduction of adverse outcomes from severe CDI.

Background and Objectives: Clostridioides difficile infection (CDI) poses a major public health problem worldwide. Materials and Methods: In this retrospective study, we included 274 patients with CDI, who were hospitalized in Internal Medicine Departments in Evangelismos General Hospital in Athens, Greece, during the past decade. Demographic, clinical and laboratory parameters of the patients were recorded. Statistical analysis revealed an association between older age and mortality as well as heart failure and mortality among patients with CDI. Results: Notably, WBC (white blood count), neutrophils, NLR (neutrophil-to-lymphocyte ratio), dNLR (derived NLR), SII (systemic immune–inflammation index) and hs-CRP (high-sensitivity C-reactive protein) demonstrated a positive association with mortality, whereas serum albumin levels and PNR (platelet-to-neutrophil ratio) exhibited an inverse relationship with mortality. We propose that the aforementioned biomarkers may be used as prognostic parameters regarding mortality from CDI. Conclusions: Large scale studies among patients with CDI with the advent of AI (artificial intelligence) may incorporate demographic, clinical and laboratory features into prognostic scores to further characterize the global CDI threat.

Background/AimsFinding differences in systemic inflammatory response in ulcerative colitis (UC), UC with Clostridium difficile infection (CDI), and CDI could lead to a better ability to differentiate between UC with symptomatic CDI and UC with C. difficile colonization, and could identify specific inflammatory pathways for UC or CDI, which could be therapeutic targets.MethodsWe prospectively collected sera from symptomatic UC patients whose stools were tested for toxigenic C. difficile, and from CDI patients who did not have UC (CDI-noUC). The UC patients with positive tests (UC-CDI) were further categorized into responders to CDI treatment (UC-CDI-R) and non-responders (UC-CDI-NR). We compared serum inflammatory mediators among groups using unadjusted and adjusted multivariable statistics.ResultsWe included 117 UC [27 UC-CDI, 90 UC without CDI (UC-noCDI)] and 16 CDI-noUC patients. Principal component analysis (PCA) did not reveal significant differences either between UC-CDI and UC-noCDI groups, or between UC-CDI-R and UC-CDI-NR groups. In contrast, the PCA showed significant separation between the UC and CDI-noUC groups (P = 0.002). In these two groups, hepatocyte growth factor (HGF) and chemokine (C-C motif) ligand 2 (CCL2) levels were significantly lower and IL-23 levels were higher in UC patients in multivariable analyses. The model to distinguish UC from CDI including IL-23, HGF, CCL2, age, gender, and HGB had an AuROC of 0.93.ConclusionInflammatory profiles could not distinguish UC-CDI from UC-noCDI, and UC-CDI-R from UC-CDI-NR. However, the UC and CDI-noUC groups were significantly different. Future work should examine whether therapeutic agents inhibiting IL-23 or stimulating HGF can treat UC.

Background. Current biomarkers have been routinely used noninvasive methods for assessing disease activity of inflammatory bowel disease (IBD), but none of them are specific. This study was aimed to determine the performance of the serological biomarkers for detecting disease activity in patients with IBD. Methods. A prospective study that included 73 ulcerative disease (UC) subjects, 141 Crohn’s disease (CD) subjects, and 30 of them complicated with C. difficile infection (CDI) were diagnosed at a single-institution IBD center. Disease activity was assessed using by Truelove and Witts criteria for UC and Harvey Bradshaw Simple Index for CD. Serological inflammatory biomarkers were compared in different severity groups. Receiver operator curve analyses assessed the performance of each biomarker in discriminating disease states. Results. For UC patients, elevated monocyte counts, C-reactive protein (CRP), and decreased lymphocyte counts and lymphocyte/monocyte ratio (LMR) significantly differed between subjects with active and inactive UC. LMR of 3.1 was 76% sensitive and had a specificity of 67% for active UC. For CD patients, higher values of neutrophils, monocytes, neutrophil/lymphocyte ratio, CRP, fibrinogen, and lower values of LMR and hemoglobin were significantly different between subjects with active and inactive CD. None of the biomarkers included had a good correlation with disease activity (area under the ROC Curve < 0.70). Conclusions. A low LMR represents an inexpensive, readily available test with a promising value to identify disease activity in UC patients, whereas none of the inflammatory biomarkers showed a discriminative value in disease activity of CD.

Clostridioides difficile ( C . difficile ) is a Gram-positive, spore-forming, toxin-producing anaerobic bacillus, which is one of the most common causes of health-care-associated infection developed mainly by elderly patients. The objective of this study was to assess mortality among the patients of the Hospital for Infectious Diseases in Warsaw related to C.difficile infection. Analysis was conducted of 1638 records reporting the medical histories of patients hospitalized for the first time due to Clostridioides difficile infection (CDI) in the Hospital for Infectious Diseases in Warsaw from 2010 to 2017. The inclusion criteria were any (principal or secondary) discharge diagnosis code for CDI according to ICD-10 and being an adult (≥ 18 years). 108 out of 1638 (7%) of the patients died. The median age in this group was 83 years. The largest number of deaths (90%) occurred in the group of patients aged 65 years or older and 81–90 years old (53% of all the deaths). In the multivariate logistic regression model relevant only to the age groups, not to sepsis—age over 80 and over 90 were independent predictors of death, increasing the risk of death by 3.4 and 1.8 times, respectively. The result of the receiver operating curve (ROC) analysis determined the age of 77 years as the threshold value, indicating the increased risk of death (AUC 0.727, standard error 0.025, 95% CI 0.678–0.776, p  < 0.0001). In addition, other quantitative variables, namely CRP, creatinine and leucocytes were studied and turned out to be independent death predictors as well. The diagnosis of sepsis increased the risk of death fourfold (OR = 4.042; 95% Cl 2.4–6.7; p  < 0.001). Increased inflammatory parameters, namely CRP and white blood cell count, advanced age, particularly over the age of 80, as well as a diagnosis of sepsis are independent risk factors for death and could be used as predictive markers of poor outcome in CDI.

To determine whether the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA) Clostridioides difficile infection (CDI) severity criteria adequately predicts poor outcomes. Retrospective validation study. Patients with CDI in the Veterans’ Affairs Health System from January 1, 2006, to December 31, 2016. For the 2010 criteria, patients with leukocytosis or a serum creatinine (SCr) value ≥1.5 times the baseline were classified as severe. For the 2018 criteria, patients with leukocytosis or a SCr value ≥1.5 mg/dL were classified as severe. Poor outcomes were defined as hospital or intensive care admission within 7 days of diagnosis, colectomy within 14 days, or 30-day all-cause mortality; they were modeled as a function of the 2010 and 2018 criteria separately using logistic regression. We analyzed data from 86,112 episodes of CDI. Severity was unclassifiable in a large proportion of episodes diagnosed in subacute care (2010, 58.8%; 2018, 49.2%). Sensitivity ranged from 0.48 for subacute care using 2010 criteria to 0.73 for acute care using 2018 criteria. Areas under the curve were poor and similar (0.60 for subacute care and 0.57 for acute care) for both versions, but negative predictive values were >0.80. Model performances across care settings and criteria versions were generally poor but had reasonably high negative predictive value. Many patients in the subacute-care setting, an increasing fraction of CDI cases, could not be classified. More work is needed to develop criteria to identify patients at risk of poor outcomes.

INTRODUCTION:Fecal microbiota transplantation (FMT) is effective for recurrent Clostridioides difficile infection (rCDI). Adverse reactions to FMT occur early, and cellular immune responses after FMT may contribute to effects and reactions. We compared early changes in peripheral immune cell subsets and clinical outcomes in patients with rCDI who received either FMT and antibiotics or antibiotics alone in a randomized trial.METHODS:Thirty-five patients with rCDI were randomized to vancomycin and FMT (n = 20) or vancomycin alone (n = 15). Blood samples were drawn before (wk0) and 1 week (wk1) after treatment. In 3 additional patients, blood samples were drawn before and 24 hours and wk1 after FMT. Adaptive and innate immune cell subsets and gut-homing memory (CD45RO+integrinβ7+) and effector (CD45RO-integrinβ7+) T cells were analyzed by flow cytometry.RESULTS:FMT induced subtle changes in immune cell subsets with no clear pattern from wk0 to wk1. The Treg fraction tended to decrease after FMT, and a similar decrease at 24 hours indicated rapid T regulatory cells dynamics. Natural killer T (NKT) cells increased during the first 24 hours and returned to baseline level at wk1. Regardless of FMT, patients with clinical resolution from rCDI had a decrease in nonclassical monocytes and a shift in gut-homing memory to effector cells at wk1.DISCUSSION:In rCDI, FMT induced subtle and transient dynamics in peripheral immune cell subsets. T regulatory cells and NKT cells seemed responsive and should be further studied. Cure of Clostridioides difficile infection may be associated with an increase in circulating gut-homing T cells.

The systemic inflammatory response to Clostridium difficile infection (CDI) is incompletely defined, particularly for patients with severe disease. Analysis of 315 blood samples from 78 inpatients with CDI (cases), 100 inpatients with diarrhea without CDI (inpatient controls), and 137 asymptomatic outpatient controls without CDI was performed. Serum or plasma was obtained from subjects at the time of CDI testing or shortly thereafter. Severe cases had intensive care unit admission, colectomy, or death due to CDI within 30 days after diagnosis. Thirty different circulating inflammatory mediators were quantified using an antibody-linked bead array. Principal component analysis (PCA), multivariate analysis of variance (MANOVA), and logistic regression were used for analysis. Based on MANOVA, cases had a significantly different inflammatory profile from outpatient controls but not from inpatient controls. In logistic regression, only chemokine (C-C motif) ligand 5 (CCL5) levels were associated with cases vs. inpatient controls. Several mediators were associated with cases vs. outpatient controls, especially hepatocyte growth factor, CCL5, and epithelial growth factor (inversely associated). Eight cases were severe and associated with elevations in IL-8, IL-6, and eotaxin. A broad systemic inflammatory response occurs during CDI and severe cases appear to differ from non-severe infections.

A 74-year-old man presented to the emergency department with jaundice. Three days earlier, his wife had noted yellow discoloration of his eyes and skin, followed by progressive lethargy and confusion.