Primary immunodeficiencies (PID) are a diverse group of genetic disorders caused by inadequate development and function of immune system. Identifying genetic etiology is important for genetic counselling and treatment decisions. Clinical relevance of genetic variants is a complex problem depending on gene-specific and variant specific genotype–phenotype interactions. To address this challenge, we aimed to characterize the pathogenic landscape of PID genes by combining the analysis of germline variations reported in ClinVar and HGMD^® and identification of damaging variations available in dbSNP. We generated a joint ClinVar/HGMD database, which included 111,940 variants, among them 32,452 were classified as pathogenic/likely pathogenic. From a total of 5,415,794 bi- or multiallelic variants in PID genes recorded in dbSNP, we retrieved 38,291 high impact (HI) biallelic variants with presumably disruptive impact in the protein, of them 25,500 variants were not present in ClinVar/HGMD. Using a functional prediction algorithm, we additionally identified 28,507 deleterious and 56,016 neutral missense variants among dbSNP variants and created a collection of damaging and neutral variations in PID genes, not currently present in ClinVar/HGMD, with their allele frequencies and mappings to protein domains. The distribution of pathogenic variants from ClinVar/HGMD, HI variants and deleterious missense variants from dbSNP was analyzed in the context of hereditary pattern and gene specific metrics, such as pLI and haploinsufficiency. Our report summarized data on complex gene-specific variability in PID genes and might be useful for the identification of the most promising variants and gene regions for further study.

原发性免疫缺陷 (PID) 是一组由免疫系统发育和功能不足引起的遗传性疾病。确定遗传病因对于遗传咨询和治疗决策很重要。遗传变异的临床相关性是一个复杂的问题，取决于基因特异性和变异特异性基因型-表型相互作用。为了应对这一挑战，我们旨在通过结合 ClinVar 和 HGMD ^{® 中}报告的种系变异分析来表征 PID 基因的致病情况 和识别 dbSNP 中可用的破坏性变异。我们生成了一个联合 ClinVar/HGMD 数据库，其中包括 111,940 个变异，其中 32,452 个被归类为致病性/可能致病性。从 dbSNP 中记录的 PID 基因中总共 5,415,794 个双或多等位基因变体中，我们检索了 38,291 个高影响 (HI) 双等位基因变体，可能对蛋白质具有破坏性影响，其中 25,500 个变体在 ClinVar/HGMD 中不存在。使用功能预测算法，我们另外在 dbSNP 变体中鉴定了 28,507 个有害和 56,016 个中性错义变体，并在 PID 基因中创建了一组破坏性和中性变异，目前在 ClinVar/HGMD 中不存在，其等位基因频率和映射到蛋白质域。ClinVar/HGMD 致病变异的分布，来自 dbSNP 的 HI 变体和有害错义变体在遗传模式和基因特异性指标（例如 pLI 和单倍体不足）的背景下进行分析。我们的报告总结了 PID 基因中复杂基因特异性变异的数据，可能有助于确定最有希望的变异和基因区域以供进一步研究。