基因型/表型关系:从 137 名 PMM2-CDG 患者身上汲取的教训

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-03 DOI:10.1155/2024/8813121
Sander Pajusalu, Mari-Anne Vals, Mercedes Serrano, Peter Witters, Anna Cechova, Tomáš Honzik, Andrew C. Edmondson, Can Ficicioglu, Rita Barone, Pascale De Lonlay, Claire-Marine Bérat, Sandrine Vuillaumier-Barrot, Christina Lam, Marc C. Patterson, Mirian C. H. Janssen, Esmeralda Martins, Dulce Quelhas, Jolanta Sykut-Cegielska, Jehan Mousa, Roser Urreizti, Peter McWilliams, Frederique Vernhes, Horacio Plotkin, Eva Morava, Katrin Õunap
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引用次数: 0

摘要

我们报告了参加一项正在进行的国际多中心自然史研究的 PMM2-CDG 患者的最大单个数据集,该研究收集了遗传、临床和生物学信息,以评估与以往研究的相似性,报告新发现,并检查潜在的基因型/表型相关性。共有 137 名参与者有完整的基因型信息,代表 60 个独特的变异,其中最常见的变异是 p.Arg141His,占 58.4%(n = 80),其次是 p.Pro113Leu(21.2%,n = 29)和 p.Phe119Leu(12.4%,n = 17),与之前的研究一致。有趣的是,还报告了 6 个新变异,其中包括 5 个错义变异(p.Pro20Leu、p.Tyr64Ser、p.Phe68Cys、p.Tyr76His 和 p.Arg238His)和 1 个框变(c.696del p.Ala233Argfs∗100)。通过奈梅亨 CDG 进展评定量表(NPCRS)和生化参数对患者的表型进行了描述,其中最常出现失调的是凝血因子,特别是抗凝血酶(117 例中有 93 例,占 79.5%),此外还有因子 XI 和蛋白 C 活性。根据预测的疾病相关突变的致病机制对患者基因型进行分类,其中大多数突变出现在 PMM2 酶的催化/激活、折叠或二聚化区域。我们采用了两种不同的方法来揭示基因型与表型之间的关系。第一种方法仅通过预测的致病机制来描述基因型,并发现了生化参数的相关变化,而仅使用 NPCRS 则无法发现这些变化,这些变化涉及催化/激活、二聚化、折叠以及无蛋白质变异。第二种方法通过预测的致病机制和/或与严重无功能变异子集配对的单个变异来描述基因型,发现了与 NPCRS 和生化参数的相关性,表明 p.Cys241Ser 与较轻的疾病相关,而 p.Val231Met、二聚化和折叠变异与较严重的疾病相关。虽然确定PMM2-CDG的全面基因型/表型关系之前已被证明具有挑战性,但本次研究的样本量更大,而且纳入了生化参数,这为了解遗传与疾病的相互作用提供了新的视角。
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Genotype/Phenotype Relationship: Lessons From 137 Patients With PMM2-CDG

We report on the largest single dataset of patients with PMM2-CDG enrolled in an ongoing international, multicenter natural history study collecting genetic, clinical, and biological information to evaluate similarities with previous studies, report on novel findings, and, additionally, examine potential genotype/phenotype correlations. A total of 137 participants had complete genotype information, representing 60 unique variants, of which the most common were found to be p.Arg141His in 58.4% (n = 80) of participants, followed by p.Pro113Leu (21.2%, n = 29), and p.Phe119Leu (12.4%, n = 17), consistent with previous studies. Interestingly, six new variants were reported, comprised of five missense variants (p.Pro20Leu, p.Tyr64Ser, p.Phe68Cys, p.Tyr76His, and p.Arg238His) and one frameshift (c.696del p.Ala233Argfs∗100). Patient phenotypes were characterized via the Nijmegen Progression CDG Rating Scale (NPCRS), together with biochemical parameters, the most consistently dysregulated of which were coagulation factors, specifically antithrombin (below normal in 79.5%, 93 of 117), in addition to Factor XI and protein C activity. Patient genotypes were classified based upon the predicted pathogenetic mechanism of disease-associated mutations, of which most were found in the catalysis/activation, folding, or dimerization regions of the PMM2 enzyme. Two different approaches were used to uncover genotype/phenotype relationships. The first characterized genotype only by the predicted pathogenic mechanisms and uncovered associated changes in biochemical parameters, not apparent using only NPCRS, involving catalysis/activation, dimerization, folding, and no protein variants. The second approach characterized genotype by the predicted pathogenic mechanism and/or individual variants when paired with a subset of severe nonfunctioning variants and uncovered correlations with both NPCRS and biochemical parameters, demonstrating that p.Cys241Ser was associated with milder disease, while p.Val231Met, dimerization, and folding variants with more severe disease. Although determining comprehensive genotype/phenotype relationships has previously proven challenging for PMM2-CDG, the larger sample size, plus inclusion of biochemical parameters in the current study, has provided new insights into the interplay of genetics with disease.

Trial Registration:NCT03173300.

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