Identification of novel ABCB4 variants and genotype-phenotype correlation in progressive familial intrahepatic cholestasis type 3

被引:0
|
作者
Wang, Senyan [1 ,2 ]
Liu, Qi [2 ]
Sun, Xiaoyan [3 ]
Wei, Wenjuan [1 ]
Ding, Leilei [4 ]
Zhao, Xiaofang [1 ]
机构
[1] Zhengzhou Univ, Affiliated Hosp 1, Translat Med Ctr, Zhengzhou 450000, Peoples R China
[2] Zhengzhou Univ, Affiliated Hosp 1, Dept Hepatobiliary & Pancreat Surg, Zhengzhou, Peoples R China
[3] Zhengzhou Univ, Henan Canc Hosp, Affiliated Canc Hosp, Dept Oncol, Zhengzhou, Peoples R China
[4] Chinese Acad Med Sci, Peking Union Med Coll Hosp, Peking Union Med Coll, Natl Clin Res Ctr Obstet & Gynecol Dis,Dept Obstet, Beijing 100730, Peoples R China
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
基金
中国国家自然科学基金;
关键词
PFIC3; ABCB4; gene; Liver transplantation; machine learning; Mutation spectrum; LIVER-DISEASE; TRANSPORT DEFECTS; MUTATIONS; CHILDREN; SPECTRUM; THERAPY; BILE;
D O I
10.1038/s41598-024-79123-6
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:13
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