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Using Full Genomic Information to Predict Disease: Breaking Down the Barriers Between Complex and Mendelian Diseases
Annual Review of Genomics and Human Genetics ( IF 8.7 ) Pub Date : 2018-08-31 00:00:00 , DOI: 10.1146/annurev-genom-083117-021136
Daniel M Jordan 1 , Ron Do 1
Affiliation  

While sequence-based genetic tests have long been available for specific loci, especially for Mendelian disease, the rapidly falling costs of genome-wide genotyping arrays, whole-exome sequencing, and whole-genome sequencing are moving us toward a future where full genomic information might inform the prognosis and treatment of a variety of diseases, including complex disease. Similarly, the availability of large populations with full genomic information has enabled new insights about the etiology and genetic architecture of complex disease. Insights from the latest generation of genomic studies suggest that our categorization of diseases as complex may conceal a wide spectrum of genetic architectures and causal mechanisms that ranges from Mendelian forms of complex disease to complex regulatory structures underlying Mendelian disease. Here, we review these insights, along with advances in the prediction of disease risk and outcomes from full genomic information.

中文翻译:


使用完整的基因组信息预测疾病:打破复杂疾病和孟德尔疾病之间的障碍

虽然基于序列的基因测试长期以来一直可用于特定基因座,尤其是孟德尔病,但全基因组基因分型阵列、全外显子组测序和全基因组测序的成本迅速下降,正推动我们走向一个完整的基因组信息的未来可能为包括复杂疾病在内的多种疾病的预后和治疗提供信息。同样,拥有完整基因组信息的大量人群的可用性使人们对复杂疾病的病因和遗传结构有了新的认识。来自最新一代基因组研究的见解表明,我们将疾病分类为复杂可能隐藏了广泛的遗传结构和因果机制,从复杂疾病的孟德尔形式到孟德尔疾病的复杂调控结构。这里,

更新日期:2018-08-31
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