Journal
BMC MEDICAL GENETICS
Volume 16, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12881-015-0230-x
Keywords
APOB; Diagnostic tools; Genetics; LDL; LDLR; LDLRAP1; Next-generation sequencing; PCSK9
Categories
Funding
- European Regional Development Fund (ERDF), the project Research and Development of Novel Diagnostic Methods for Genetic and Immunologic Testing [2013/0042/2DP/2.1.1.1.0/13/APIA/VIAA/002]
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Background: Familial hypercholesterolemia (FH) is one of the commonest monogenic disorders, predominantly inherited as an autosomal dominant trait. When untreated, it results in early coronary heart disease. The vast majority of FH remains undiagnosed in Latvia. The identification and early treatment of affected individuals remain a challenge worldwide. Most cases of FH are caused by mutations in one of four genes, APOB, LDLR, PCSK9, or LDLRAP1. The spectrum of disease-causing variants is very diverse and the variation detection panels usually used in its diagnosis cover only a minority of the disease-causing gene variants. However, DNA-based tests may provide an FH diagnosis for FH patients with no physical symptoms and with no known family history of the disease. Here, we evaluate the use of targeted next-generation sequencing (NGS) to identify cases of FH in a cohort of patients with coronary artery disease (CAD) and individuals with abnormal low-density lipoprotein-cholesterol (LDL-C) levels. Methods: We used targeted amplification of the coding regions of LDLR, APOB, PCSK9, and LDLRAP1, followed by NGS, in 42 CAD patients (LDL-C, 4.1-7.2 mmol/L) and 50 individuals from a population-based cohort (LDL-C, 5.1-9.7 mmol/L). Results: In total, 22 synonymous and 31 nonsynonymous variants, eight variants in close proximity (10 bp) to intron-exon boundaries, and 50 other variants were found. We identified four pathogenic mutations (p.(Arg3527Gln) in APOB, and p.(Gly20Arg), p.(Arg350*), and c.1706-10G > A in LDLR) in seven patients (7.6 %). Three possible pathogenic variants were also found in four patients. Conclusion: NGS-based methods can be used to detect FH in high-risk individuals when they do not meet the defined clinical criteria.
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