Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines’ PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

预测功能丧失 (pLoF) 变异通常非常有害，并在疾病生物学中发挥重要作用，但许多 pLoF 变异可能不会导致功能丧失 (LoF)。在这里，我们提出了一个框架，通过考虑三类 LoF 逃避，推进研究和临床环境中 pLoF 变异的解释：（1）通过二级序列特性预测救援，（2）不确定的生物学相关性，以及（3）潜在的技术假象。我们还提供有关调整 ACMG/AMP 指南的 PVS1 标准的建议。将此框架应用于基因组聚合数据库 (gnomAD v.2.1.1) 中与常染色体隐性遗传病相关的 22 个基因中的所有高置信度 pLoF 变体，揭示了 27.3% (304/1,113) 变体中预测的 LoF 逃避或潜在伪影。主要原因是位于最后一个外显子、同聚物重复中、转录本 (pext) 评分区域中表达比例较低，或者存在神秘的框内剪接救援。预测逃避 LoF 或潜在伪影的变体被丰富为 ClinVar 良性变体。在预测为可能不是 LoF/非 LoF 的 pLoF 变体中，PVS1 的 99.4% (162/163) 被降级，其中 17.2% (28/163) 由于我们的框架而降级，增加了之前的指南。这 28 个变体中有 20 个（71.4%）变体致病性受到影响（主要是从可能致病性到 VUS）。该框架指导对标准注释流程之外的 pLoF 变异进行评估，并大幅降低假阳性率，这是确保研究和临床环境中准确的 LoF 变异预测的关键。