Exome and genome sequencing are increasingly utilized in research studies and clinical care and can provide clinically relevant information beyond the initial intent for sequencing, including medically actionable secondary findings. Despite ongoing debate about sharing this information with patients and participants, a growing number of clinical laboratories and research programs routinely report secondary findings that increase the risk for selected diseases. Recently, there has been a push to maximize the potential benefit of this practice by implementing proactive genomic screening at the population level irrespective of medical history, but the feasibility of deploying population‐scale proactive genomic screening requires scaling key elements of the genomic data evaluation process. Herein, we describe the motivation, development, and implementation of a population‐scale variant‐first screening pipeline combining bioinformatics‐based filtering with a manual review process to screen for clinically relevant findings in research exomes generated through the DiscovEHR collaboration within Geisinger's MyCode® research project. Consistent with other studies, this pipeline yields a screen‐positive detection rate between 2.1 and 2.6% (depending on inclusion of those with prior indication‐based testing) in 130,048 adult MyCode patient‐participants screened for clinically relevant findings in 60 genes. Our variant‐first pipeline affords cost and time savings by filtering out negative cases, thereby avoiding analysis of each exome one‐by‐one, as typically employed in the diagnostic setting. While research is still needed to fully appreciate the benefits of population genomic screening, MyCode provides the first demonstration of a program at scale to help shape how population genomic screening is integrated into routine clinical care.

中文翻译：

---

利用基于人群的外显子组筛查影响临床护理：Geisinger MyCode 研究项目中变异评估的演变

外显子组和基因组测序越来越多地用于研究和临床护理，并且可以提供超出测序最初意图的临床相关信息，包括医学上可操作的次要发现。尽管关于与患者和参与者共享这些信息的争论仍在继续，但越来越多的临床实验室和研究项目经常报告次要发现，这些发现会增加特定疾病的风险。最近，通过在人群水平上实施主动基因组筛查而不考虑病史，一直在推动这种做法的潜在好处最大化，但部署人群规模主动基因组筛查的可行性需要扩展基因组数据评估过程的关键要素. 在这里，我们描述了动机、发展、并实施人口规模的变异优先筛选管道，将基于生物信息学的过滤与手动审查过程相结合，以筛选通过 Geisinger 的 MyCode® 研究项目中的 DiscovEHR 合作生成的研究外显子组中的临床相关发现。与其他研究一致，该管道在 130,048 名成人 MyCode 患者参与者中产生了 2.1% 到 2.6% 之间的筛查阳性检出率（取决于是否包含了先前基于适应症的检测），在 60 个基因中筛查了临床相关结果。我们的变体优先管道通过过滤掉负面案例来节省成本和时间，从而避免了诊断设置中通常采用的逐个分析每个外显子组。