Role for interleukin-6 in COPD-related pulmonary hypertension.

International audienceBACKGROUND: Pulmonary artery remodeling triggered by alveolar hypoxia is considered the main mechanism of pulmonary hypertension (PH) in COPD patients. We hypothesized that the risk for PH in COPD is increased by an elevation in the proinflammatory cytokines interleukin (IL)-6, monocyte chemoattractant protein-1 (MCP-1), and IL-1beta, as well as by specific genetic polymorphisms of these cytokines. METHODS: We assessed cytokine plasma levels and the polymorphisms G(-174)C IL-6, C(-511)T IL-1beta, and A(-2518)G MCP-1 in 148 COPD patients (recruited at two centers) with right heart catheterization data and 180 control subjects including smokers and nonsmokers. Human pulmonary artery smooth muscle cells (PA-SMCs) were cultured for IL-6 messenger RNA assays under normoxic and hypoxic conditions. RESULTS: Patients with PH (mean pulmonary artery pressure [PAP], >or= 25 mm Hg) had lower Pao(2) and higher plasma IL-6 values than those without PH; there were no differences in terms of pulmonary function test results or CT scan emphysema scores. Plasma IL-6 correlated with mean PAP (r = 0.39; p < 0.001) and was included in a multiple stepwise regression analysis, with mean PAP as the dependent variable. In patients with the IL-6 GG genotype, the mean PAP value was significantly higher and PH was more common than in CG or CC patients (adjusted odds ratio, 4.32; 95% confidence interval, 1.96 to 9.54). Exposure to 4 h of hypoxia led to an about twofold increase in IL-6 messenger RNA in cultured human PA-SMCs. CONCLUSIONS: Inflammation, most likely involving IL-6, may contribute substantially to PH complicating COPD

The H2020 VERTIGO project towards tbit/s optical feeder links

ISSN:0277-786

Clinical phenotypes and outcomes of precapillary pulmonary hypertension of sickle cell disease

International audienc

Genetics of the connectome

Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods-such as genome-wide association studies (GWAS), linkage and candidate gene studies-that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity