Interpreting Genetic Variants of Uncertain Significance

描述(由申请人提供)：在某些临床情况下，个体人类基因组的测序可能很快就会成为常规--例如，诊断儿童患者的可疑孟德尔疾病，或指导癌症治疗的治疗决定。然而，即使其成本暴跌至1000美元或更少，“个人基因组”的价值仍将受到个别基因变异解释能力差的严重制约。例如，尽管BRCA1和BRCA2在出现功能丧失突变时在临床上是可以操作的，尽管这两个基因在过去10年里已经在5万名患者中进行了测序，但返回给患者的结果往往仍然是“意义不确定的变种”。随着临床测序的加速和临床可操作基因列表的增加，这一挑战将会深刻地加深。为了解决这一问题，我们建议开发一种新的方法来以前所未有的规模实验测量这种“不确定意义的变体”的功能后果，并开发一种创新的计算方法来估计整个人类基因组中任何可能的变体的相对致病性。对于临床相关的基因，我们将利用大规模并行的核酸合成和测序技术，朝着以饱和分辨率解剖功能的新范式迈进。这一范例的应用将为所有可能的单一残基变体的功能后果产生有实验依据的预测，从而为患者新观察到的变体的解释提供信息。对于人类基因组的其余部分，我们将开发一个框架，将不断增长的编码和非编码注释多样性集成到单个度量中。然后，我们将计算人类基因组中所有可能的单核苷酸变异的相对致病性的这一指标。我们预计，这些方法和由此产生的致病性的“预计计算”将广泛地使在不同的临床和研究环境中解释人类基因组序列成为可能。

DESCRIPTION (provided by applicant): The sequencing of individual human genomes may soon be routine in certain clinical contexts - for example, to diagnose suspected Mendelian disorders in pediatric patients, or to guide therapeutic decisions in cancer treatment. However, even as its cost plummets to $1,000 or less, the value of a "personal genome" will remain highly constrained by the poor interpretability of individual genetic variants. For example, although BRCA1 and BRCA2 are clinically actionable when loss-of-function mutations are present, and although both genes have been sequenced in >50,000 patients over the past decade, the result returned to patients is often still "variant of uncertain significance". This challenge will profoudly deepen as clinical sequencing accelerates and as the list of clinically actionable genes grows. To address this, we propose to develop a novel approach for experimentally measuring the functional consequences of such "variants of uncertain significance" at an unprecedented scale, as well as innovative computational approaches for estimating the relative pathogenicity of any possible variant in the entire human genome. For clinically relevant genes, we will exploit massively parallel technologies for nucleic acid synthesis and sequencing towards a new paradigm for dissecting function at saturating resolution. The application of this paradigm will yield experimentally grounded predictions for the functional consequences of all possible single residue variants, thereby informing the interpretation of variants newly observed in patients. For the remainder of the human genome, we will develop a framework for integrating a proliferating diversity of coding and non-coding annotations to a single metric. We will then calculate this metric of relative pathogenicity for all possible single nucleotide variants in the human genome. We anticipate that these methods and the resulting "pre-computations" of pathogenicity will broadly enable the interpretation of human genome sequences in diverse clinical and research settings.