8 research outputs found

    Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

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    Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10−4). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10−8), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals

    Integrative sediment quality assessment using a biomarker approach: review of 3 years of field research

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    14 páginas, 4 figuras, 2 tablas.Recent research efforts in sediment and dredged material assessment research have focused on the inclusion of sublethal endpoints (biomarkers) in acute and long-term bioassays for dredged material characterisation and management. The incorporation of biomarkers as a new line of evidence in a weight of evidence approach allows the determination of more sensitive, longer-term biological information for use in laboratory and in situ sediment/tissue quality guidelines.This work was conducted under the framework of the projects INTEGRAL (Spanish Ministry of Education and Science; CTM2005-07282-C03-C01/TECNO; PHB2005-0100-PC) and was partially financed by the Master Erasmus Mundus (UNESCO/UNITWIN/WiCop and Unidad Asociada CSIC). Dr. Laura Martín-Díaz would like to thank the Juan de la Cierva Program (Ministry of Education and Science).Peer reviewe
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