Tunis University

About: Tunis University is a education organization based out in Tunis, Tunisia. It is known for research contribution in the topics: Population & Thin film. The organization has 11745 authors who have published 15400 publications receiving 154900 citations. The organization is also known as: University of Tunis & UT.

The Val158Met COMT polymorphism is a modifier of the age at onset in Parkinson's disease with a sexual dimorphism

Abstract: The catechol-O-methyltranferase (COMT) is one of the main enzymes that metabolise dopamine in the brain. The Val158Met polymorphism in the COMT gene (rs4680) causes a trimodal distribution of high (Val/Val), intermediate (Val/Met) and low (Met/Met) enzyme activity. We tested whether the Val158Met polymorphism is a modifier of the age at onset (AAO) in Parkinson's disease (PD). The rs4680 was genotyped in a total of 16 609 subjects from five independent cohorts of European and North American origin (5886 patients with PD and 10 723 healthy controls). The multivariate analysis for comparing PD and control groups was based on a stepwise logistic regression, with gender, age and cohort origin included in the initial model. The multivariate analysis of the AAO was a mixed linear model, with COMT genotype and gender considered as fixed effects and cohort and cohort-gender interaction as random effects. COMT genotype was coded as a quantitative variable, assuming a codominant genetic effect. The distribution of the COMT polymorphism was not significantly different in patients and controls (p=0.22). The Val allele had a significant effect on the AAO with a younger AAO in patients with the Val/Val (57.1±13.9, p=0.03) than the Val/Met (57.4±13.9) and the Met/Met genotypes (58.3±13.5). The difference was greater in men (1.9 years between Val/Val and Met/Met, p=0.007) than in women (0.2 years, p=0.81). Thus, the Val158Met COMT polymorphism is not associated with PD in the Caucasian population but acts as a modifier of the AAO in PD with a sexual dimorphism: the Val allele is associated with a younger AAO in men with idiopathic PD.

Multiple imputation using chained equations for missing data in TIMSS: a case study

Abstract: In this paper, we document a study that involved applying a multiple imputation technique with chained equations to data drawn from the 2007 iteration of the TIMSS database. More precisely, we imputed missing variables contained in the student background datafile for Tunisia (one of the TIMSS 2007 participating countries), by using Van Buuren, Boshuizen, and Knook’s (SM 18:681-694,1999) chained equations approach. We imputed the data in a way that was congenial with the analysis model. We also carried out different diagnostics in order to determine if the imputations were reasonable. Our analysis of multiply imputed data confirmed that the power of multiple imputation lies in obtaining smaller standard errors and narrower confidence intervals in addition to allowing one to work with the entire dataset.