3 resultados para Multiple-model filter


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TRAIL and TRAIL Receptor genes have been implicated in Multiple Sclerosis pathology as well as in the response to IFN beta therapy. The objective of our study was to evaluate the association of these genes in relation to the age at disease onset (AAO) and to the clinical response upon IFN beta treatment in Spanish MS patients. We carried out a candidate gene study of TRAIL, TRAILR-1, TRAILR-2, TRAILR-3 and TRAILR-4 genes. A total of 54 SNPs were analysed in 509 MS patients under IFN beta treatment, and an additional cohort of 226 MS patients was used to validate the results. Associations of rs1047275 in TRAILR-2 and rs7011559 in TRAILR-4 genes with AAO under an additive model did not withstand Bonferroni correction. In contrast, patients with the TRAILR-1 rs20576-CC genotype showed a better clinical response to IFN beta therapy compared with patients carrying the A-allele (recessive model: p = 8.88×10(-4), pc = 0.048, OR = 0.30). This SNP resulted in a non synonymous substitution of Glutamic acid to Alanine in position 228 (E228A), a change previously associated with susceptibility to different cancer types and risk of metastases, suggesting a lack of functionality of TRAILR-1. In order to unravel how this amino acid change in TRAILR-1 would affect to death signal, we performed a molecular modelling with both alleles. Neither TRAIL binding sites in the receptor nor the expression levels of TRAILR-1 in peripheral blood mononuclear cell subsets (monocytes, CD4+ and CD8+ T cells) were modified, suggesting that this SNP may be altering the death signal by some other mechanism. These findings show a role for TRAILR-1 gene variations in the clinical outcome of IFN beta therapy that might have relevance as a biomarker to predict the response to IFN beta in MS.

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Gut mesodermal tissues originate from the splanchnopleural mesenchyme. However, the embryonic gastrointestinal coelomic epithelium gives rise to mesenchymal cells, whose significance and fate are little known. Our aim was to investigate the contribution of coelomic epithelium-derived cells to the intestinal development. We have used the transgenic mouse model mWt1/IRES/GFP-Cre (Wt1(cre)) crossed with the Rosa26R-EYFP reporter mouse. In the gastrointestinal duct Wt1, the Wilms' tumor suppressor gene, is specific and dynamically expressed in the coelomic epithelium. In the embryos obtained from the crossbreeding, the Wt1-expressing cell lineage produces the yellow fluorescent protein (YFP) allowing for colocalization with differentiation markers through confocal microscopy and flow cytometry. Wt1(cre-YFP) cells were very abundant throughout the intestine during midgestation, declining in neonates. Wt1(cre-YFP) cells were also transiently observed within the mucosa, being apparently released into the intestinal lumen. YFP was detected in cells contributing to intestinal vascularization (endothelium, pericytes and smooth muscle), visceral musculature (circular, longitudinal and submucosal) as well as in Cajal and Cajal-like interstitial cells. Wt1(cre-YFP) mesenchymal cells expressed FGF9, a critical growth factor for intestinal development, as well as PDGFRα, mainly within developing villi. Thus, a cell population derived from the coelomic epithelium incorporates to the gut mesenchyme and contribute to a variety of intestinal tissues, probably playing also a signaling role. Our results support the origin of interstitial cells of Cajal and visceral circular muscle from a common progenitor expressing anoctamin-1 and SMCα-actin. Coelomic-derived cells contribute to the differentiation of at least a part of the interstitial cells of Cajal.

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In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.