多基因与癌症孟德尔模型的统计方法
Statistical methods for Mendelian models with multiple genes and cancers
摘要：
风险评估，以确定个人谁是在更大的风险癌症的结果，遗传性致病变异是一个有价值的组成部分，个性化的临床管理。利用孟德尔遗传学原理、贝叶斯概率论和变异特异性知识，孟德尔模型基于家族史推导出携带致病性变异和未来发展癌症的概率。现有的孟德尔模型被广泛采用，但通常限于特定的基因和综合征。然而，多基因组生殖细胞检测的兴起促使人们发现了许多新的基因-癌症关联，这些关联目前在这些模型中还没有得到解释。我们开发了PanelPRO，这是一种灵活、高效的孟德尔风险预测框架，可以整合任意数量的基因和癌症，克服了由于模型复杂性增加而带来的计算挑战。我们实现了一个11基因，11癌症模型，迄今为止最大的孟德尔模型，基于这个框架。使用模拟和临床队列与生殖系面板测试数据，我们评估模型性能，验证我们的方法与现有孟德尔模型的反向兼容性，并说明其使用。我们的实现可在PanelPRO R包中免费获得，用于研究。
英文摘要：
Risk evaluation to identify individuals who are at greater risk of cancer as a result of heritable pathogenic variants is a valuable component of individualized clinical management. Using principles of Mendelian genetics, Bayesian probability theory, and variant-specific knowledge, Mendelian models derive the probability of carrying a pathogenic variant and developing cancer in the future, based on family history. Existing Mendelian models are widely employed, but are generally limited to specific genes and syndromes. However, the upsurge of multi-gene panel germline testing has spurred the discovery of many new gene-cancer associations that are not presently accounted for in these models. We have developed PanelPRO, a flexible, efficient Mendelian risk prediction framework that can incorporate an arbitrary number of genes and cancers, overcoming the computational challenges that arise because of the increased model complexity. We implement an eleven-gene, eleven-cancer model, the largest Mendelian model created thus far, based on this framework. Using simulations and a clinical cohort with germline panel testing data, we evaluate model performance, validate the reverse-compatibility of our approach with existing Mendelian models, and illustrate its usage. Our implementation is freely available for research use in the PanelPRO R package.
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