59 research outputs found

    Roadmap for implementation of genomics in healthcare: towards equity in access to genomics

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    As atividades do WP5 do projeto B1MG resultaram num documento intitulado "A Roadmap for genomics in healthcare", que se constitui como um guia e suporte para os sistemas de saúde que pretendam implementar a genómica nos cuidados de saúde, facilitando a utilização do Maturity Level Model e providenciando acesso a guidelines e documentos desenvolvidos no âmbito de outras iniciativas de medicina personalisada. Este poster apresenta o contexto, as atividades e os pontos essenciais que constituem o roadmap.Funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 951724N/

    Differential methylation of the TRPA1 promoter in pain sensitivity

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    Chronic pain is a global public health problem, but the underlying molecular mechanisms are not fully understood. Here we examine genome-wide DNA methylation, first in 50 identical twins discordant for heat pain sensitivity and then in 50 further unrelated individuals. Whole-blood DNA methylation was characterized at 5.2 million loci by MeDIP sequencing and assessed longitudinally to identify differentially methylated regions associated with high or low pain sensitivity (pain DMRs). Nine meta-analysis pain DMRs show robust evidence for association (false discovery rate 5) with the strongest signal in the pain gene TRPA1 (P=1.2 �? 10(-13)). Several pain DMRs show longitudinal stability consistent with susceptibility effects, have similar methylation levels in the brain and altered expression in the skin. Our approach identifies epigenetic changes in both novel and established candidate genes that provide molecular insights into pain and may generalize to other complex traits

    Large-Scale Evidence for the Effect of the COLIA1 Sp1 Polymorphism on Osteoporosis Outcomes: The GENOMOS Study.

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    Background Osteoporosis and fracture risk are considered to be under genetic control. Extensive work is being performed to identify the exact genetic variants that determine this risk. Previous work has suggested that a G/T polymorphism affecting an Sp1 binding site in the COLIA1 gene is a genetic marker for low bone mineral density (BMD) and osteoporotic fracture, but there have been no very-large-scale studies of COLIA1 alleles in relation to these phenotypes. Methods and Findings Here we evaluated the role of COLIA1 Sp1 alleles as a predictor of BMD and fracture in a multicenter study involving 20,786 individuals from several European countries. At the femoral neck, the average (95% confidence interval [CI]) BMD values were 25 mg/cm2 (CI, 16 to 34 mg/cm2) lower in TT homozygotes than the other genotype groups ( p < 0.001), and a similar difference was observed at the lumbar spine; 21 mg/cm2 (CI, 1 to 42 mg/cm2), ( p = 0.039). These associations were unaltered after adjustment for potential confounding factors. There was no association with fracture overall (odds ratio [OR] = 1.01 [CI, 0.95 to 1.08]) in either unadjusted or adjusted analyses, but there was a non-significant trend for association with vertebral fracture and a nominally significant association with incident vertebral fractures in females (OR = 1.33 [CI, 1.00 to 1.77]) that was independent of BMD, and unaltered in adjusted analyses. Conclusions Allowing for the inevitable heterogeneity between participating teams, this study—which to our knowledge is the largest ever performed in the field of osteoporosis genetics for a single gene—demonstrates that the COLIA1 Sp1 polymorphism is associated with reduced BMD and could predispose to incident vertebral fractures in women, independent of BMD. The associations we observed were modest however, demonstrating the importance of conducting studies that are adequately powered to detect and quantify the effects of common genetic variants on complex diseases

    Common variants in the ATM, BRCA1, BRCA2, CHEK2 and TP53 cancer susceptibility genes are unlikely to increase breast cancer risk

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    RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Introduction Certain rare, familial mutations in the ATM, BRCA1, BRCA2, CHEK2 or TP53 genes increase susceptibility to breast cancer but it has not, until now, been clear whether common polymorphic variants in the same genes also increase risk. Methods We have attempted a comprehensive, single nucleotide polymorphism (SNP)- and haplotype-tagging association study on each of these five genes in up to 4,474 breast cancer cases from the British, East Anglian SEARCH study and 4,560 controls from the EPIC-Norfolk study, using a two-stage study design. Nine tag SNPs were genotyped in ATM, together with five in BRCA1, sixteen in BRCA2, ten in CHEK2 and five in TP53, with the aim of tagging all other known, common variants. SNPs generating the common amino acid substitutions were specifically forced into the tagging set for each gene. Results No significant breast cancer associations were detected with any individual or combination of tag SNPs. Conclusion It is unlikely that there are any other common variants in these genes conferring measurably increased risks of breast cancer in our study population

    Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

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    Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity

    GA4GH: International policies and standards for data sharing across genomic research and healthcare.

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    The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits
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