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Updated: Jul 29, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Identification of pathogenic variants in the Brazilian cohort with Familial hypercholesterolemia using exon-targeted
Jéssica Bassani Borges1, Victor Fernandes Oliveira2, Carolina Dagli-Hernandez2
1Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo 05508-000 SP, Brazil; Department of Teaching and Research, Real and Benemerita Associação Portuguesa de Beneficiencia, Sao Paulo 01323-001, Brazil.
Abstract:
Familial hypercholesterolemia (FH) is a monogenic disease characterized by high plasma low-density lipoprotein cholesterol (LDL-c) levels and increased risk of premature atherosclerotic cardiovascular disease. Mutations in FH-related genes account for 40% of FH cases worldwide. In this study, we aimed to assess the pathogenic variants in FH-related genes in the Brazilian FH cohort FHBGEP using exon-targeted gene sequencing (ETGS) strategy. FH patients (n = 210) were enrolled at five clinical sites and peripheral blood samples were obtained for laboratory testing and genomic DNA extraction. ETGS was performed using MiSeq platform (Illumina). To identify deleterious variants in LDLR, APOB, PCSK9, and LDLRAP1, the long-reads were subjected to Burrows-Wheeler Aligner (BWA) for alignment and mapping, followed by variant calling using Genome Analysis Toolkit (GATK) and ANNOVAR for variant annotation. The variants were further filtered using in-house custom scripts and classified according to the American College Medical Genetics and Genomics (ACMG) guidelines. A total of 174 variants were identified including 85 missense, 3 stop-gain, 9 splice-site, 6 InDel, and 71 in regulatory regions (3'UTR and 5'UTR). Fifty-two patients (24.7%) had 30 known pathogenic or likely pathogenic variants in FH-related genes according to the American College Medical and Genetics and Genomics guidelines. Fifty-three known variants were classified as benign, or likely benign and 87 known variants have shown uncertain significance. Four novel variants were discovered and classified as such due to their absence in existing databases. In conclusion, ETGS and in silico prediction studies are useful tools for screening deleterious variants and identification of novel variants in FH-related genes, they also contribute to the molecular diagnosis in the FHBGEP cohort.
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