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Identifying disease associations via genome-wide association studies

机译:通过全基因组关联研究确定疾病关联

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Background: Genome-wide association studies prove to be a powerful approach to identify the genetic basis of different human diseases. We studied the relationship between seven diseases characterized in a previous genome-wide association study by the Wellcorne Trust Case Control Consortium. Instead of doing a horizontal association of SNPs to diseases, we did a vertical analysis of disease associations by comparing the genetic similarities of diseases.Our analysis was carried out at four levels -the nucleotide level (SNPs), the gene level, the protein level (through protein-protein interaction network), and the phenotype level.Results: Our results show that Crohn's disease, rheumatoid arthritis, and type 1 diabetes share evidence of genetic associations at all levels of analysis, offering strong molecular support for the current grouping of the diseases. On the other hand, coronary artery disease,hypertension, and type 2 diabetes, despite being considered as a natural group with potential aetiological overlap, do not show any evidence of shared genetic basis at all levels.Conclusions: Our study is a first attempt on mining of GWA data to examine genetic associations between different diseases. The positive result is apparently not a coincidence and hence demonstrates the promising use of our approach.
机译:背景:全基因组关联研究证明是鉴定不同人类疾病遗传基础的有效方法。我们研究了Wellcorne Trust Case Control Consortium在先前的全基因组关联研究中表征的七种疾病之间的关系。通过与疾病的遗传相似性进行比较,我们没有对SNP与疾病进行水平关联,而是对疾病关联进行了垂直分析。我们的分析在四个水平上进行-核苷酸水平(SNPs),基因水平,蛋白质水平结果:我们的研究结果表明,克罗恩病,类风湿性关节炎和1型糖尿病在所有分析水平上均具有遗传关联的证据,为当前的分组研究提供了强有力的分子支持疾病。另一方面,尽管冠状动脉疾病,高血压和2型糖尿病被认为是具有潜在病因学重叠的自然人群,但并未显示出所有水平上都有共享遗传基础的证据。结论:我们的研究是首次尝试挖掘GWA数据以检查不同疾病之间的遗传关联。积极的结果显然不是巧合,因此证明了我们方法的前景广阔。

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  • 会议地点 Beijing(CN);Beijing(CN)
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    Department of Computer Science, Virginia Tech,2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA;

    Department of Computer Science, Virginia Tech,2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA;

    Department of Computer Science, Virginia Tech,2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA;

    Department of Computer Science, Virginia Tech,2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA Program in Genetics, Bioinforrnatics, and Computational Biology, Blacksburg, VA 24061-0106, USA;

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