Genetic Testing and Risk Scores: Impact on Familial Hypercholesterolemia

被引:29
作者
Sarraju, Ashish [1 ,2 ]
Knowles, Joshua W. [1 ,2 ,3 ,4 ]
机构
[1] Stanford Univ, Div Cardiovasc Med, Stanford, CA 94305 USA
[2] Stanford Univ, Cardiovasc Inst, Stanford, CA 94305 USA
[3] FH Fdn, Pasadena, CA 91106 USA
[4] Stanford Univ, Stanford Diabet Res Ctr, Stanford, CA 94305 USA
关键词
polygenic risk scores; genetic testing; familial hypercholesterolemia; genome wide association studies; PCKS9; low-density lipoprotein; homozygous; heterozygous; CORONARY-ARTERY-DISEASE; CARDIOVASCULAR EVENTS; COST-EFFECTIVENESS; ATHEROSCLEROSIS; POPULATION; MUTATIONS; PREDICTION; DIAGNOSIS; ADULTS;
D O I
10.3389/fcvm.2019.00005
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Familial Hypercholesterolemia (FH) is an inherited lipid disorder affecting 1 in 220 individuals resulting in highly elevated low-density lipoprotein levels and risk of premature coronary disease. Pathogenic variants causing FH typically involve the LDL receptor (LDLR), apolipoprotein B-100 (APOB), and proprotein convertase subtulisin/kexin type 9 genes (PCSK9) and if identified convey a risk of early onset coronary artery disease (ASCVD) of 3- to 10-fold vs. the general population depending on the severity of the mutation. Identification of monogenic FH within a family has implications for family-based testing (cascade screening), risk stratification, and potentially management, and it has now been recommended that such testing be offered to all potential FH patients. Recently, robust genome wide association studies (GWAS) have led to the recognition that the accumulation of common, small effect alleles affecting many LDL-c raising genes can result in a clinical phenotype largely indistinguishable from monogenic FH (i.e., a risk of early onset ASCVD of similar to 3-fold) in those at the extreme tail of the distribution for these alleles (i.e., the top 8% of the population for a polygenic risk score). The incorporation of these genetic risk scores into clinical practice for non-FH patients may improve risk stratification but is not yet widely performed due to a less robust evidence base for utility. Here, we review the current status of FH genetic testing, potential future applications as well as challenges and pitfalls.
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页数:7
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