Platform to support clinical variant interpretation through probabilistic assessment of functional evidence

项目总结 现在，只需数百美元就可以对整个患者的基因组进行测序，而且价格仍在下降。内科医生 现在，作为诊断疾病和指导治疗的一种方式，人们通常会订购大的基因面板。而当 这些测试的广泛使用对患者护理是有益的，它也带来了大规模数据的挑战 释义。目前，通过基因测试发现的大多数独特的变异都没有足够的证据证明 分类。这些“意义未知的变种”(Vus)阻碍了致命疾病的及时诊断和治疗 心脏病和癌症等疾病。需要改进和积极主动的方法来减少 被归类为VU的变体数量。 在实验室进行的功能分析是用于基因分类的重要证据来源 变种。从历史上看，这些实验的吞吐量一直很低，一次只能为一个变种生成数据。 此外，这样的实验是反应性的，这意味着它们只有在给定的变种被 在临床上观察。为了积极扩大基因变异的表征，几个学术实验室 最近开发了变异效应多重分析(MAVES)，它收集了数千名 一次实验中的蛋白质变异。MAVE作为高通量函数的来源前景看好 证据。尽管如此，目前还没有商业平台来管理和有力地分析大型 学术实验室正在生成越来越多的MAVE数据集，以告知临床变异 解读。因此，这些数据为挽救生命的医疗决策提供信息的潜力尚未实现。 为了满足改进临床变体解释的需要，康斯坦蒂安生物科学公司正在开发VarifyTM， 首个此类平台，专门将MAVE数据转换为可操作的信息，以支持 临床变种解读。Varify为基因组解释领域带来了两项关键创新： 贝叶斯推理的应用，这是处理不确定性和概率的最好方法 编程，一种新的计算技术，使统计推理能够有效地在 准确反映数据生成条件的模型。支持第一阶段 计划，康斯坦蒂安生物科学公司已经开发了Varify的早期原型。该公司将建造 在这些初步努力的基础上，执行第一阶段SBIR计划，目标是开发和评估 Varify的变量效应推理框架。目标1的重点是增强现有的早期变异效应 推理框架，包括对MAVE中存在的信号破坏过程的影响进行建模的模块 可以扭曲和模糊不同效果的实验。将继续对扩大的框架进行评估 使用模拟数据(目标1)，并应用于BRCA1和PTEN的现有MAVE数据集(目标2)。成功 完成这些目标将为Varify的扩展框架提供关键的概念验证，并支持 第二阶段计划将更广泛地应用Varify并开发商业就绪的产品。

PROJECT SUMMARY Entire patient genomes can now be sequenced for hundreds of dollars, and the price is still falling. Physicians now routinely order large gene panels as a way of diagnosing disease and guiding treatment. While the widespread use of these tests is beneficial for patient care, it also introduces a challenge of large-scale data interpretation. Currently, most unique variants uncovered by genetic tests have insufficient evidence for confident classification. These “variants of unknown significance” (VUS) hinder timely diagnosis and treatment of deadly diseases such as heart disease and cancer. An improved and proactive approach is needed to decrease the number of variants that are classified as VUS. Functional assays performed in laboratories are important sources of evidence used for classification of gene variants. Historically, these experiments have been low-throughput, generating data for one variant at a time. Furthermore, such experiments are reactive, meaning they are performed only after a given variant has been observed in the clinic. To proactively expand genetic variant characterization, several academic laboratories have recently developed Multiplexed Assays of Variant Effect (MAVEs), which collect data on thousands of protein variants in a single experiment. MAVEs hold great promise as a source of high-throughput functional evidence. Nonetheless, there are currently no commercial platforms that curate and robustly analyze the large and growing number of MAVE datasets being generated by academic labs to inform clinical variant interpretations. As a result, the potential for these data to inform lifesaving medical decisions is unrealized. To address the need for improved clinical variant interpretation, Constantiam Biosciences is developing VarifyTM, a first of its kind platform specializing in the translation of MAVE data into actionable information to support clinical variant interpretation. Varify brings two key innovations to the field of genomic interpretation: the application of Bayesian inference, which is the best proven method for handling uncertainty, and probabilistic programming, a novel computational technique that allows statistical inference to be performed efficiently on models that accurately reflect the conditions under which the data were generated. To support the Phase I program, Constantiam Biosciences has developed an early-stage prototype of Varify. The company will build upon these preliminary efforts to execute the Phase I SBIR program with the goal of developing and assessing Varify’s variant effect inference framework. Aim 1 is focused on augmenting the existing early-stage variant effect inference framework to include modules that model the influence of signal-corrupting processes present in MAVE experiments that can distort and obscure variant effects. The expanded framework will be continuously evaluated using simulated data (Aim 1) and applied on existing MAVE data sets for BRCA1 and PTEN (Aim 2). Successful completion of these aims will provide critical proof-of-concept for Varify’s expanded framework and support a Phase II program that will apply Varify more broadly and develop a commercial-ready product.