Genomic and clinical predictors of cardiovascular disease in Familial dyslipidemia: risk stratification in Egyptian adolescents and young adults

家族性血脂异常患者心血管疾病的基因组和临床预测因子:埃及青少年和青年人群的风险分层

阅读:1

Abstract

Familial dyslipidemia (FD), particularly familial hypercholesterolemia (FH), is a major contributor to premature cardiovascular disease (CVD), especially in regions with high consanguinity and underutilized genetic screening, such as Egypt. This study aimed to assess clinical, biochemical, and genetic factors that differentiate FD patients with and without CVD, and to develop a composite risk score for individualized stratification. A cross-sectional study was conducted on 60 Egyptian patients aged 15-25 years with genetically confirmed FD, equally divided based on CVD status. All participants underwent detailed clinical assessment, lipid profiling, and targeted next-generation sequencing of LDLR, APOB, and PCSK9 genes. Missense variants were evaluated using SIFT, PolyPhen-2, CADD, and ΔΔG stability scores, and classified according to ACMG criteria. Compared to non-CVD patients, those with CVD had significantly higher triglyceride levels (median: 356.5 vs. 236.5 mg/dL; p < 0.001) and a higher frequency of heterozygous pathogenic LDLR variants (30.0% vs. 3.3%; p = 0.006), while homozygous variants were more common in non-CVD patients (26.7% vs. 0%; p = 0.002). Deleterious missense variants were notably more frequent in the CVD group (56.7% vs. 10.0%; p < 0.001). A 10-variable composite risk score integrating clinical, lipid, and bioinformatic predictors effectively distinguished high- and moderate-risk cases (AUC = 0.742; p = 0.022), with 89.5% sensitivity and 81.8% negative predictive value. The study highlights the importance of combining clinical and genomic data for early risk stratification and introduces a pragmatic tool for identifying high-risk youth in resource-limited, consanguineous populations.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。