Dataset Information

Improvement of Definite Diagnosis of Familial Hypercholesterolemia Using an Expanding Genetic Analysis.

ABSTRACT:

Background

The deeper understanding of the complex hereditary basis of familial hypercholesterolemia (FH) has raised the rationale of genetic testing, which has been underutilized in clinical practice.

Objectives

The present study aimed to explore the variant spectrum of FH in an expanding manner and compare its diagnostic performance.

Methods

A total of 169 Chinese individuals (124 index cases and 45 relatives) with clinical definite/probable FH were consecutively enrolled. Next-generation sequencing was performed for genetic analysis of 9 genes associated with hypercholesterolemia (major genes: LDLR, APOB, and PCSK9; minor genes: LDLRAP1, LIPA, STAP1, APOE, ABCG5, and ABCG8) including the evaluations of small-scale variants and large-scale copy number variants (CNVs).

Results

Among the 169 clinical FH patients included, 98 (58.0%) were men. A total of 85 (68.5%) index cases carried FH-associated variants. The proportion of FH caused by small-scale variants in LDLR, APOB, and PCSK9 genes was 62.1% and then increased by 6.5% when other genes and CNVs were further included. Furthermore, the variants in LDLR, APOB, and PCSK9 genes occupied 75% of all FH-associated variants. Of note, there were 8 non-LDLR CNVs detected in the present study.

Conclusions

LDLR, APOB, and PCSK9 genes should be tested in the initial genetic screening, although variants in minor genes also could explain phenotypic FH, suggesting that an expanding genetic testing may be considered to further explain phenotypic FH.

SUBMITTER: Cao YX

PROVIDER: S-EPMC9627923 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improvement of Definite Diagnosis of Familial Hypercholesterolemia Using an Expanding Genetic Analysis.

Cao Ye-Xuan YX Sun Di D Liu Hui-Hui HH Jin Jing-Lu JL Li Sha S Guo Yuan-Lin YL Wu Na-Qiong NQ Zhu Cheng-Gang CG Liu Geng G Dong Qian Q Sun Jing J Chen Xie-Hui XH Li Jian-Jun JJ

JACC. Asia 20210421 1

<h4>Background</h4>The deeper understanding of the complex hereditary basis of familial hypercholesterolemia (FH) has raised the rationale of genetic testing, which has been underutilized in clinical practice.<h4>Objectives</h4>The present study aimed to explore the variant spectrum of FH in an expanding manner and compare its diagnostic performance.<h4>Methods</h4>A total of 169 Chinese individuals (124 index cases and 45 relatives) with clinical definite/probable FH were consecutively enrolled ...[more]

PMID: 36338372

Similar Datasets

Project description:ImportanceFamilial hypercholesterolemia (FH) is the most common inherited cardiovascular disease and carries significant morbidity and mortality risks. Genetic testing can identify affected individuals, but some array-based assays screen only a small subset of known pathogenic variants.ObjectiveTo identify the number of clinically significant variants associated with FH that would be missed by an array-based, limited-variant screen when compared with next-generation sequencing (NGS)-based comprehensive testing.Design, setting, and participantsThis cross-sectional study compared comprehensive genetic test results for clinically significant variants associated with FH with results for a subset of 24 variants screened by a limited-variant array. Data were deidentified next-generation sequencing results from indication-based or proactive gene panels. Individuals receiving next-generation sequencing-based genetic testing, either for an FH indication between November 2015 and June 2020 or as proactive health screening between February 2016 and June 2020 were included. Ancestry was reported by clinicians who could select from preset options or enter free text on the test requisition form.Main outcomes and measuresNumber of pathogenic or likely pathogenic (P/LP) variants identified.ResultsThis study included 4563 individuals who were referred for FH diagnostic testing and 6482 individuals who received next-generation sequencing of FH-associated genes as part of a proactive genetic test. Among individuals in the indication cohort, the median (interquartile range) age at testing was 49 (32-61) years, 55.4% (2528 of 4563) were female, and 63.6% (2902 of 4563) were self-reported White/Caucasian. In the indication cohort, the positive detection rate would have been 8.4% (382 of 4563) for a limited-variant screen compared with the 27.0% (1230 of 4563) observed with the next-generation sequencing-based comprehensive test. As a result, 68.9% (848 of 1230) of individuals with a P/LP finding in an FH-associated gene would have been missed by the limited screen. The potential for missed findings in the indication cohort varied by ancestry; among individuals with a P/LP finding, 93.7% (59 of 63) of self-reported Black/African American individuals and 84.7% (122 of 144) of Hispanic individuals would have been missed by the limited-variant screen, compared with 33.3% (4 of 12) of Ashkenazi Jewish individuals. In the proactive cohort, the prevalence of clinically significant FH variants was approximately 1:191 per the comprehensive test, and 61.8% (21 of 34) of individuals with an FH-associated P/LP finding would have been missed by a limited-variant screen.Conclusions and relevanceLimited-variant screens may falsely reassure the majority of individuals at risk for FH that they do not carry a disease-causing variant, especially individuals of self-reported Black/African American and Hispanic ancestry.

Project description:Purpose of reviewFamilial hypercholesterolemia (FH) is a hereditary condition characterized by elevated levels of low-density lipoprotein cholesterol (LDL-C), which increases the risk of cardiovascular disease if left untreated. This review aims to discuss the role of bioinformatics tools in evaluating the pathogenicity of missense variants associated with FH. Specifically, it highlights the use of predictive models based on protein sequence, structure, evolutionary conservation, and other relevant features in identifying genetic variants within LDLR, APOB, and PCSK9 genes that contribute to FH.Recent findingsIn recent years, various bioinformatics tools have emerged as valuable resources for analyzing missense variants in FH-related genes. Tools such as REVEL, Varity, and CADD use diverse computational approaches to predict the impact of genetic variants on protein function. These tools consider factors such as sequence conservation, structural alterations, and receptor binding to aid in interpreting the pathogenicity of identified missense variants. While these predictive models offer valuable insights, the accuracy of predictions can vary, especially for proteins with unique characteristics that might not be well represented in the databases used for training. This review emphasizes the significance of utilizing bioinformatics tools for assessing the pathogenicity of FH-associated missense variants. Despite their contributions, a definitive diagnosis of a genetic variant necessitates functional validation through in vitro characterization or cascade screening. This step ensures the precise identification of FH-related variants, leading to more accurate diagnoses. Integrating genetic data with reliable bioinformatics predictions and functional validation can enhance our understanding of the genetic basis of FH, enabling improved diagnosis, risk stratification, and personalized treatment for affected individuals. The comprehensive approach outlined in this review promises to advance the management of this inherited disorder, potentially leading to better health outcomes for those affected by FH.

Dataset Information

Improvement of Definite Diagnosis of Familial Hypercholesterolemia Using an Expanding Genetic Analysis.

Background

Objectives

Methods

Results

Conclusions

Publications

Improvement of Definite Diagnosis of Familial Hypercholesterolemia Using an Expanding Genetic Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets