Targeted Assessment of Mucosal Immune Gene Expression Predicts Clinical Outcomes in Children with Ulcerative Colitis.

BACKGROUND AND AIMS: We aimed to determine whether a targeted gene expression panel could predict clinical outcomes in paediatric ulcerative colitis [UC] and investigated putative pathogenic roles of predictive genes. METHODS: In total, 313 rectal RNA samples from a cohort of newly diagnosed paediatric UC patients (PROTECT) were analysed by a real-time PCR microfluidic array for expression of type 1, 2 and 17 inflammation genes. Associations between expression and clinical outcomes were assessed by logistic regression. Identified prognostic markers were further analysed using existing RNA sequencing (RNA-seq) data sets and tissue immunostaining. RESULTS: IL13RA2 was associated with a lower likelihood of corticosteroid-free remission (CSFR) on mesalamine at week 52 (p = .002). A model including IL13RA2 and only baseline clinical parameters was as accurate as an established clinical model, which requires week 4 remission status. RORC was associated with a lower likelihood of colectomy by week 52. A model including RORC and PUCAI predicted colectomy by 52 weeks (area under the receiver operating characteristic curve 0.71). Bulk RNA-seq identified IL13RA2 and RORC as hub genes within UC outcome-associated expression networks related to extracellular matrix and innate immune response, and lipid metabolism and microvillus assembly, respectively. Adult UC single-cell RNA-seq data revealed IL13RA2 and RORC co-expressed genes were localized to inflammatory fibroblasts and undifferentiated epithelial cells, respectively, which was supported by protein immunostaining. CONCLUSION: Targeted assessment of rectal mucosal immune gene expression predicts 52-week CSFR in treatment-naïve paediatric UC patients. Further exploration of IL-13Rɑ2 as a therapeutic target in UC and future studies of the epithelial-specific role of RORC in UC pathogenesis are warranted.

Free drug samples in the United States: characteristics of pediatric recipients and safety concerns.

OBJECTIVES: Free drug samples frequently are given to children. We sought to describe characteristics of free sample recipients, to determine whether samples are given primarily to poor and uninsured children, and to examine potential safety issues. METHODS: We analyzed data on 10295 US residents <18 years of age from the 2004 Medical Expenditure Panel Survey, a nationally representative survey that includes questions on receipt of free drug samples. We performed bivariate and multivariate analyses to evaluate characteristics associated with receipt of >or=1 free drug sample in 2004. We identified the most frequently reported sample medications and reviewed potential safety issues. RESULTS: Ten percent of children who received prescription medications and 4.9% of all children received >or=1 free drug sample in 2004. In bivariate analyses, poor children (family incomes of <200% of the federal poverty level) were no more likely to receive free samples than were those with incomes of >or=400% of the poverty level (3.8% vs 5.9%). Children who were uninsured for part or all of the year were no more likely to receive free samples than were those who were insured all year (4.5% vs 5.1%); 84.3% of all sample recipients were insured. In multivariate analyses, routine access to health care (>or=3 provider visits in 2004) was associated with free sample receipt. The 15 most frequently distributed pediatric free samples in 2004 included 2 schedule II controlled medication, Adderall (amphetamine/dextroamphetamine) [corrected] and 4 medications that received new or revised black box warnings between 2004 and 2007, Elidel (pimecrolimus), Advair (fluticasone/salmeterol), Strattera (atomoxetine), and Adderall (amphetamine/dextroamphetamine). CONCLUSIONS: Poor and uninsured children are not the main recipients of free drug samples. Free samples do not target the neediest children selectively, and they have significant safety considerations.

Energy expenditure in critically ill children.

OBJECTIVE: To assess the measured resting energy expenditure pattern over time in a group of critically ill children who were admitted to a pediatric intensive care unit and to determine whether a hypermetabolic response, i.e., >10% above predicted, occurred in a pattern similar to that observed in adults. A secondary aim was to compare the accuracy of a newly derived prediction equation specific to the pediatric intensive care unit and the measured resting energy expenditure. DESIGN: A prospective, clinical, observational study. SETTING: A pediatric intensive care unit of a tertiary care medical center. PATIENTS: Forty-four children (29 males, 15 females) ages 2 wks to 17 yrs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: During the course of their stay in the pediatric intensive care unit, 44 patients' measured resting energy expenditure was assessed using indirect calorimetry 94 times at up to three time points. The first measurement was at a mean time of 25 +/- 10 (+/-sd) hrs after admission, the second at 73 +/- 16 hrs, and the third immediately before discharge, which occurred at a mean of 193 +/- 93 hrs after admission. Measured energy expenditure varied only slightly (7% to 10%) from the first to second and the second to third measurements. Evidence for hypermetabolism was not apparent. Generally, the prediction equations performed well. Mean measured resting energy expenditure for all measurements was 821 +/- 653 kcals/24 hrs. The Schofield equation estimate was 798 +/- 595 kcals/24 hrs and the White equation estimate was 815 +/- 564 kcals/24 hrs (p = not significant). Nineteen (20%) measurements were >110% above the age-appropriate Schofield-predicted equation, and 30 measurements (32%) were <90% below that predicted by Schofield. Consequently, 45% of measured resting energy expenditure measurements were within 90% to 110% of that predicted by the Schofield equation. The White equation was inaccurate (not within 10% of measured resting energy expenditure) in 66 of 94 measurements (70%). The discrepancy was greatest (100%) in children with measured resting energy expenditure <450 kcal/24 hrs. CONCLUSION: The hypermetabolic response apparent in adults was not evident in these critically ill children. Currently available prediction equations cannot substitute for indirect calorimetry measurement of energy expenditure in guiding nutritional support in pediatric intensive care units.