Translational Medicine Centre, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Sci Rep. 2024 Nov 9;14(1):27381. doi: 10.1038/s41598-024-79123-6.
Progressive familial intrahepatic cholestasis type 3 (PFIC3) is a severe hepatic disorder characterized by cholestasis. Elucidating the genotype-phenotype correlations and expanding the mutational spectrum of the ABCB4 gene are crucial for enhancing diagnostic accuracy and therapeutic strategies.Clinical and genetic data from 2 original PFIC3 patients from our institution, along with 118 additional cases identified through a comprehensive literature review, were integrated for a comprehensive analysis. The study included statistical analysis of clinical information, genetic analysis, multi-species sequence alignment, protein structure modeling, and pathogenicity assessment. Machine learning techniques were applied to identify genotype-phenotype relationships. We identified three novel ABCB4 mutations: two missense mutations (c.904G > T and c.2493G > C) and one splicing mutation (c.1230 + 1G > A). Homozygous mutations were associated with significantly earlier disease onset compared to compound heterozygous mutations (p < 0.0001). Missense mutations were predominant (76.9%), with Exon 7 being the most frequently affected region. A random forest model indicated that Exon 10 had the highest feature importance score (9.9%). Liver transplantation remains the most effective treatment modality for PFIC3. This investigation broadens the known mutation spectrum of the ABCB4 gene and identifies key variant sites associated with clinical manifestations. These insights lay a foundation for early diagnosis, optimal treatment selection, and further research into PFIC3.
进行性家族性肝内胆汁淤积症 3 型(PFIC3)是一种严重的肝脏疾病,其特征为胆汁淤积。阐明 ABCB4 基因突变与表型的相关性并扩展其突变谱,对于提高诊断准确性和治疗策略至关重要。我们整合了来自本机构的 2 名原发性 PFIC3 患者的临床和遗传数据,以及通过全面文献回顾确定的 118 例额外病例,进行了综合分析。该研究包括对临床信息、遗传分析、多物种序列比对、蛋白质结构建模和致病性评估的统计分析。应用机器学习技术来识别基因型-表型关系。我们鉴定了三个新的 ABCB4 突变:两个错义突变(c.904G>T 和 c.2493G>C)和一个剪接突变(c.1230+1G>A)。与复合杂合突变相比,纯合突变与疾病更早发生相关(p<0.0001)。错义突变占主导地位(76.9%),其中第 7 外显子受影响最频繁。随机森林模型表明第 10 外显子具有最高的特征重要性评分(9.9%)。肝移植仍然是 PFIC3 最有效的治疗方式。该研究扩展了 ABCB4 基因突变的已知突变谱,并确定了与临床表现相关的关键变异位点。这些见解为 PFIC3 的早期诊断、最佳治疗选择以及进一步研究奠定了基础。