These include ABCA6, ARHGAP44, Wnt3, TCF4, ZBTB32, CDK14, KCNN4, and TCF4, which showed (except for Wnt3), consistency across both cohorts studied. Instead, and despite the limited number of CLL cases available, our analyses led to the identification of several strong signals associated with prospective CLL risk (more than 10 years before diagnosis). ], our results do not support the existence of genes whose change in expression is common to the pathogenesis of all or multiple histological subtypes of NHL. Hsa04662:B cell receptor signaling pathway GO:0048534∼hemopoietic or lymphoid organ development GO:0050870∼positive regulation of T cell activation GO:0050864∼regulation of B cell activation GO:0050867∼positive regulation of cell activation GO:0002684∼positive regulation of immune system process GO:0030888∼regulation of B cell proliferation GO:0002696∼positive regulation of leukocyte activation GO:0051251∼positive regulation of lymphocyte activation GO:0050863∼regulation of T cell activation GO:0070665∼positive regulation of leukocyte proliferation GO:0032946∼positive regulation of mononuclear cell proliferation GO:0050671∼positive regulation of lymphocyte proliferation GO:0032944∼regulation of mononuclear cell proliferation GO:0070663∼regulation of leukocyte proliferation GO:0050670∼regulation of lymphocyte proliferation GO:0002694∼regulation of leukocyte activation GO:0051249∼regulation of lymphocyte activation Table 3 Summary of the results of the gene-enrichment analyses Database Analyses were (i) carried out on the full population and (ii) stratified by major histological subtypes, and a series of sensitivity analyses were performed.įold-change (f) is derived from the regression coefficient estimate (β) by the mixed model: f = 2β. Model was fitted, using the R-statistical package lme4, on all 29 662 probes separately, and we accounted for multiple testing using a stringent Bonferroni correction, setting the family-wise error rate (FWER) to 5%. The dates of the three main steps of sample processing were used as random effect variables: RNA isolation, hybridization, and dye labeling. Nuisance variation was modeled through a random intercept model where uAi represents the shift associated to Ai, the value of the random effect variable(s) A observed for individual i. ]: body mass index (BMI, continuous), education (5 classes), physical activity (4 classes), smoking at enrollment (3 classes), and alcohol consumption at enrollment (continuous), and a binary variable indicating if the participant was a BC case or not.
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