Hao Wang1, Hang Yang1, Zhaohui Liu1, Kai Cui1, Yinhui Zhang1, Yujing Zhang1, Kun Zhao1, Kunlun Yin1, Wenke Li1, Zhou Zhou1. 1. State Key Laboratory of Cardiovascular Disease, Beijing Key Laboratory for Molecular Diagnostics of Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College.
Abstract
AIM: Familial hypercholesterolemia (FH) is the most commonly encountered genetic condition that predisposes individuals to severe autosomal dominant lipid metabolism dysfunction. Although more than 75% of the European population has been scrutinized for FH-causing mutations, the genetic diagnosis proportion among Chinese people remains very low (less than 0.5%). The aim of this study was to identify genetic mutations and help make a precise diagnosis in Chinese FH patients. METHODS: We designed a gene panel containing 20 genes responsible for FH and tested 208 unrelated Chinese possible/probable or definite FH probands. In addition, we called LDLR copy number variation (CNVs) with the panel data by panelcn.MOPS, and multiple ligation-dependent probe amplification (MLPA) was used to search for CNVs in LDLR, APOB, and PCSK9. RESULTS: A total of 79 probands (38.0%) tested positive for a (likely) pathogenic mutation, most of which were LDLR mutations, and three LDLR CNVs called from the panel data were all successfully confirmed by MLPA analysis. In total, 48 different mutations were identified, including 45 LDLR mutations, 1 APOB mutation, 1 ABCG5 mutation, and 1 APOE mutation. Among them, the five most frequent mutations (LDLR c.1879G＞A, c.1747C＞T, c.313＋1G＞A, c.400T＞C, and APOB c.10579C＞T) were detected. Moreover, we also found that patients with LDLR variants of CNVs and splicing and nonsense had increased low-density lipoprotein cholesterol levels when compared with those who carried missense variants. CONCLUSIONS: The spectrum of FH-causing mutations in the Chinese population is refined and expanded. Analyses of FH causal genes have been a great help in clinical diagnosis and have deep implications in disease treatment. These data can serve as a considerable dataset for next-generation sequencing analysis of the Chinese population with FH and contribute to the genetic diagnosis and counseling of FH patients.
AIM: Familial hypercholesterolemia (FH) is the most commonly encountered genetic condition that predisposes individuals to severe autosomal dominant lipid metabolism dysfunction. Although more than 75% of the European population has been scrutinized for FH-causing mutations, the genetic diagnosis proportion among Chinese people remains very low (less than 0.5%). The aim of this study was to identify genetic mutations and help make a precise diagnosis in Chinese FHpatients. METHODS: We designed a gene panel containing 20 genes responsible for FH and tested 208 unrelated Chinese possible/probable or definite FH probands. In addition, we called LDLR copy number variation (CNVs) with the panel data by panelcn.MOPS, and multiple ligation-dependent probe amplification (MLPA) was used to search for CNVs in LDLR, APOB, and PCSK9. RESULTS: A total of 79 probands (38.0%) tested positive for a (likely) pathogenic mutation, most of which were LDLR mutations, and three LDLR CNVs called from the panel data were all successfully confirmed by MLPA analysis. In total, 48 different mutations were identified, including 45 LDLR mutations, 1 APOB mutation, 1 ABCG5 mutation, and 1 APOE mutation. Among them, the five most frequent mutations (LDLR c.1879G＞A, c.1747C＞T, c.313＋1G＞A, c.400T＞C, and APOB c.10579C＞T) were detected. Moreover, we also found that patients with LDLR variants of CNVs and splicing and nonsense had increased low-density lipoprotein cholesterol levels when compared with those who carried missense variants. CONCLUSIONS: The spectrum of FH-causing mutations in the Chinese population is refined and expanded. Analyses of FH causal genes have been a great help in clinical diagnosis and have deep implications in disease treatment. These data can serve as a considerable dataset for next-generation sequencing analysis of the Chinese population with FH and contribute to the genetic diagnosis and counseling of FHpatients.
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