Morphology and Progression in Primary Varicose Vein Disorder Due to 677C>T and 1298A>C Variants of MTHFR
Background: Clinical assessment and prognostic stratification of primary varicose veins have remained controversial and the molecular pathogenesis is unknown. Previous data have suggested a contribution of the MTHFR (methylenetetrahydrofolate reductase) polymorphism c.677C>T. Methods: We collected blood and vein specimens from 159 consecutive patients undergoing varicose vein surgery, or autologous vein reconstruction for arterial occlusive disease as controls. We compared the frequencies of c.677C>T and another polymorphism of MTHFR, c.1298A>C, with morphology and types of complicated disease. Morphology was recorded as a trunk or perforator type and peripheral congestive complication was …
Integrative Genome-Scale DNA Methylation Analysis of a Large and Unselected Cohort Reveals 5 Distinct Subtypes of Colorectal Adenocarcinomas
BACKGROUND & AIMS: Colorectal cancer is an epigenetically heterogeneous disease, however, the extent and spectrum of the CpG island methylator phenotype (CIMP) is not clear. METHODS: Genome-scale methylation and transcript expression were measured by DNA Methylation and RNA expression microarray in 216 unselected colorectal cancers, and findings were validated using The Cancer Genome Atlas 450K and RNA sequencing data. Mutations in epigenetic regulators were assessed using CIMP-subtyped Cancer Genome Atlas exomes. RESULTS: CIMP-high cancers dichotomized into CIMP-H1 and CIMP-H2 based on methylation profile. KRAS mutation was associated significantly with CIMP-H2 cancers, but not CIMP-H1 can…
Automatic variable selection for exposure-driven propensity score matching with unmeasured confounders.
Multivariable model building for propensity score modeling approaches is challenging. A common propensity score approach is exposure-driven propensity score matching, where the best model selection strategy is still unclear. In particular, the situation may require variable selection, while it is still unclear if variables included in the propensity score should be associated with the exposure and the outcome, with either the exposure or the outcome, with at least the exposure or with at least the outcome. Unmeasured confounders, complex correlation structures, and non-normal covariate distributions further complicate matters. We consider the performance of different modeling strategies in …