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1.
Genes Immun ; 15(2): 126-32, 2014 Mar.
Article in English | MEDLINE | ID: mdl-24430173

ABSTRACT

Genome-wide association studies (GWASs) perform per-SNP association tests to identify variants involved in disease or trait susceptibility. However, such an approach is not powerful enough to unravel genes that are not individually contributing to the disease/trait, but that may have a role in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted of ITGAL, ICAM1 and ICAM3 genes, could be of interest to develop novel therapeutic targets.


Subject(s)
Cell Adhesion Molecules/genetics , Multiple Sclerosis/genetics , Antigens, CD/genetics , Blood-Brain Barrier/cytology , Blood-Brain Barrier/immunology , Cell Adhesion Molecules/immunology , Genetic Predisposition to Disease , Genome-Wide Association Study , Humans , Integrin alpha Chains/genetics , Intercellular Adhesion Molecule-1/genetics , Multiple Sclerosis/immunology , Polymorphism, Single Nucleotide , Signal Transduction/genetics , T-Lymphocytes/immunology
2.
Eur J Clin Invest ; 40(2): 172-82, 2010 Feb.
Article in English | MEDLINE | ID: mdl-20050879

ABSTRACT

BACKGROUND: Most clinical trials on medical interventions are sponsored by the industry. The choice of comparators shapes the accumulated evidence. We aimed to assess how often major companies sponsor trials that involve only their own products. METHODS: Studies were identified by searching ClinicalTrials.gov for trials registered in 2006. We focused on randomized trials involving the 15 companies that had sponsored the largest number of registered trials in ClinicalTrials.gov in that period. RESULTS: Overall, 577 randomized trials were eligible for analysis and 82% had a single industry sponsor [89% (166/187) of the placebo-control trials, 87% (91/105) of trials comparing different doses or ways of administration of the same intervention, and 78% (221/285) of other active control trials]. The compared intervention(s) belonged to a single company in 67% of the trials (89%, 81% and 47% in the three categories respectively). All 15 companies strongly preferred to run trials where they were the only industry sponsor or even the only owner of the assessed interventions. Co-sponsorship typically reflected co-ownership of the same intervention by both companies. Head-to-head comparison of different active interventions developed by different companies occurred in only 18 trials with two or more industry sponsors. CONCLUSIONS: Each company generates a clinical research agenda that is strongly focused on its own products, while comparisons involving different interventions from different companies are uncommon. This diminishes the ability to understand the relative merits of different interventions for the same condition.


Subject(s)
Drug Industry/economics , Randomized Controlled Trials as Topic/economics , Research Support as Topic , Conflict of Interest
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