Comprehensive functional characterization of SGCB coding variants predicts pathogenicity in limb-girdle muscular dystrophy type R4/2E.
Comprehensive functional characterization of SGCB coding variants predicts pathogenicity in limb-girdle muscular dystrophy type R4/2E.
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DOI：
10.1172/jci168156
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发表时间：
2023-06-15
影响因子：
15.9
通讯作者：
Haller, Gabe
中科院分区：
文献类型：
--
作者：
Li, Chengcheng;Wilborn, Jackson;Pittman, Sara;Daw, Jil;Alonso-Perez, Jorge;Diaz-Manera, Jordi;Weihl, Conrad C.;Haller, Gabe
基因检测对疑似遗传性肌病的患者至关重要。超过50%的临床诊断为肌病的患者在肌病基因中携带未知意义的变异，通常使他们无法进行遗传诊断。R4/2E型肢带状肌营养不良症（LGMD）是由β-肌聚糖（SGCB）突变引起的。β-、α-、γ-和δ-肌聚糖共同形成定位于肌膜的4蛋白跨膜复合物（SGC）。任何亚基的双等位基因功能丧失突变都可能导致LGMD。为了提供错义变异致病性的功能证据，我们对SGC进行了深度突变扫描，并评估了SGC细胞表面定位中所有6340个可能的氨基酸变化。变异功能评分呈双峰分布，可以很好地预测已知变异的致病性。功能评分较轻的变异更常出现在疾病进展较慢的患者中，这意味着功能变异与疾病严重程度之间存在关系。不耐受变异的氨基酸位置映射到预测SGC相互作用的点，在硅结构模型中得到验证，并能够准确预测其他SGC基因的致病变异。这些结果将有助于临床解释SGCB变异和提高LGMD的诊断；我们希望他们能够更广泛地使用可能挽救生命的基因疗法。
Genetic testing is essential for patients with a suspected hereditary myopathy. More than 50% of patients clinically diagnosed with a myopathy carry a variant of unknown significance in a myopathy gene, often leaving them without a genetic diagnosis. Limb-girdle muscular dystrophy (LGMD) type R4/2E is caused by mutations in β-sarcoglycan (SGCB). Together, β-, α-, γ-, and δ-sarcoglycan form a 4-protein transmembrane complex (SGC) that localizes to the sarcolemma. Biallelic loss-of-function mutations in any subunit can lead to LGMD. To provide functional evidence for the pathogenicity of missense variants, we performed deep mutational scanning of SGCB and assessed SGC cell surface localization for all 6,340 possible amino acid changes. Variant functional scores were bimodally distributed and perfectly predicted pathogenicity of known variants. Variants with less severe functional scores more often appeared in patients with slower disease progression, implying a relationship between variant function and disease severity. Amino acid positions intolerant to variation mapped to points of predicted SGC interactions, validated in silico structural models, and enabled accurate prediction of pathogenic variants in other SGC genes. These results will be useful for clinical interpretation of SGCB variants and improving diagnosis of LGMD; we hope they enable wider use of potentially life-saving gene therapy.