Malfunctions of voltage-gated sodium and calcium channels (encoded by SCNxA and CACNA1x family genes, respectively) have been associated with severe neurologic, psychiatric, cardiac, and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) that often corresponds not only to clinical disease manifestations but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. On the basis of known gene-disease mechanisms of 19 different diseases, we inferred LOF (n = 518) and GOF (n = 309) likely pathogenic variants from the disease phenotypes of variant carriers. By training a machine learning model on sequence- and structure-based features, we predicted LOF or GOF effects [area under the receiver operating characteristics curve (ROC) = 0.85] of likely pathogenic missense variants. Our LOF versus GOF prediction corresponded to molecular LOF versus GOF effects for 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and was validated in exome-wide data from 21,703 cases and 128,957 controls. We showed respective regional clustering of inferred LOF and GOF nucleotide variants across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCNxA/CACNA1x family genes.

电压门控钠通道和钙通道（分别由SCNxA和CACNA1x家族基因编码）的功能障碍与严重的神经、精神、心脏和其他疾病有关。通道活性的改变通常分为离子通道功能的获得或丧失（分别为 GOF 或 LOF），这通常不仅与临床疾病表现相对应，而且还与药物反应的差异相对应。因此，通道功能的实验研究很重要，但很费力，而且通常一次只关注几个变体。在已知的19种不同疾病的基因疾病机制的基础上，我们从变异携带者的疾病表型推断出LOF（ n = 518）和GOF（ n = 309）可能的致病变异。通过基于基于序列和结构的特征训练机器学习模型，我们预测了可能致病性错义变异的 LOF 或 GOF 效应 [受试者工作特征曲线下面积 (ROC) = 0.85]。我们的 LOF 与 GOF 预测对应于SCN1/2/8A和CACNA1I中 87 个功能测试变体的分子 LOF 与 GOF 效应（ROC = 0.73），并在来自 21,703 例病例和 128,957 例对照的全外显子组数据中得到验证。我们在整个基因家族的比对中显示了推断的 LOF 和 GOF 核苷酸变异的各自区域聚类，表明SCNxA/CACNA1x家族基因具有共同的病理机制。