Michael A. Iacocca

Recent advances in genetic testing for familial hypercholesterolemia

ABSTRACT Introduction: Familial hypercholesterolemia (FH) is a common genetic cause of premature coronary heart disease that is widely underdiagnosed and undertreated. To improve the identification of FH and initiate timely and appropriate treatment strategies, genetic testing is becoming increasingly offered worldwide as a central part of diagnosis. Areas covered: Recent advances have been propelled by an improved understanding of the genetic determinants of FH together with substantially reduced costs of appropriate screening strategies. Here we review the various methods available for obtaining a molecular diagnosis of FH, and highlight the particular advantages of targeted next-generation sequencing (NGS) platforms as the most robust approach. Furthermore, we note the importance of screening for copy number variants and common polymorphisms to aid in molecularly defining suspected FH cases. Expert commentary: The need for genetic analysis of FH will increase, both for diagnosis and reimbursement of new therapies. An effective molecular diagnostic method must detect: 1) molecular and gene locus heterogeneity; 2) a wide range of mutation types; and 3) the polygenic component of FH. As availability of genetic testing for FH expands, standardization of variant curation, maintenance of clinical databases and registries, and wider health care provider education all assume greater importance.

Use of next-generation sequencing to detectLDLRgene copy number variation in familial hypercholesterolemia

Familial hypercholesterolemia (FH) is a heritable condition of severely elevated LDL cholesterol, caused predominantly by autosomal codominant mutations in the LDL receptor gene (LDLR). In providing a molecular diagnosis for FH, the current procedure often includes targeted next-generation sequencing (NGS) panels for the detection of small-scale DNA variants, followed by multiplex ligation-dependent probe amplification (MLPA) in LDLR for the detection of whole-exon copy number variants (CNVs). The latter is essential because ∼10% of FH cases are attributed to CNVs in LDLR; accounting for them decreases false negative findings. Here, we determined the potential of replacing MLPA with bioinformatic analysis applied to NGS data, which uses depth-of-coverage analysis as its principal method to identify whole-exon CNV events. In analysis of 388 FH patient samples, there was 100% concordance in LDLR CNV detection between these two methods: 38 reported CNVs identified by MLPA were also successfully detected by our NGS method, while 350 samples negative for CNVs by MLPA were also negative by NGS. This result suggests that MLPA can be removed from the routine diagnostic screening for FH, significantly reducing associated costs, resources, and analysis time, while promoting more widespread assessment of this important class of mutations across diagnostic laboratories.

ClinVar database of global familial hypercholesterolemia-associated DNA variants

Accurate and consistent variant classification is imperative for incorporation of rapidly developing sequencing technologies into genomic medicine for improved patient care. An essential requirement for achieving standardized and reliable variant interpretation is data sharing, facilitated by a centralized open‐source database. Familial hypercholesterolemia (FH) is an exemplar of the utility of such a resource: it has a high incidence, a favorable prognosis with early intervention and treatment, and cascade screening can be offered to families if a causative variant is identified. ClinVar, an NCBI‐funded resource, has become the primary repository for clinically relevant variants in Mendelian disease, including FH. Here, we present the concerted efforts made by the Clinical Genome Resource, through the FH Variant Curation Expert Panel and global FH community, to increase submission of FH‐associated variants into ClinVar. Variant‐level data was categorized by submitter, variant characteristics, classification method, and available supporting data. To further reform interpretation of FH‐associated variants, areas for improvement in variant submissions were identified; these include a need for more detailed submissions and submission of supporting variant‐level data, both retrospectively and prospectively. Collaborating to provide thorough, reliable evidence‐based variant interpretation will ultimately improve the care of FH patients.

Large-scale deletions of the ABCA1 gene in patients with hypoalphalipoproteinemia

Copy-number variations (CNVs) have been studied in the context of familial hypercholesterolemia but have not yet been evaluated in patients with extreme levels of HDL cholesterol. We evaluated targeted, next-generation sequencing data from patients with very low levels of HDL cholesterol (i.e., hypoalphalipoproteinemia) with the VarSeq-CNV® caller algorithm to screen for CNVs that disrupted the ABCA1, LCAT, or APOA1 genes. In four individuals, we found three unique deletions in ABCA1: a heterozygous deletion of exon 4, a heterozygous deletion that spanned exons 8 to 31, and a heterozygous deletion of the entire ABCA1 gene. Breakpoints were identified with Sanger sequencing, and the full-gene deletion was confirmed by using exome sequencing and the Affymetrix CytoScan HD array. Previously, large-scale deletions in candidate HDL genes had not been associated with hypoalphalipoproteinemia; our findings indicate that CNVs in ABCA1 may be a previously unappreciated genetic determinant of low levels of HDL cholesterol. By coupling bioinformatic analyses with next-generation sequencing data, we can successfully assess the spectrum of genetic determinants of many dyslipidemias, including hypoalphalipoproteinemia.

Whole-gene duplication of PCSK9 as a novel genetic mechanism for severe familial hypercholesterolemia

BACKGROUND Familial hypercholesterolemia (FH) is a common genetic disorder of severely elevated low-density lipoprotein (LDL) cholesterol, characterized by premature atherosclerotic cardiovascular disease. Although copy number variations (CNVs) are a large-scale mutation-type capable of explaining FH cases, they have been, to date, assessed only in the LDLR gene. Here, we performed novel CNV screening in additional FH-associated genes using a next-generation sequencing-based approach. METHODS In 704 patients with FH, we sequenced FH-associated genes APOB, PCSK9, LDLRAP1, APOE, STAP1, LIPA, and ABCG5/8 using our LipidSeq targeted next-generation sequencing panel. Bioinformatic tools were applied to LipidSeq data for CNV screening, and identified CNVs were validated using whole-exome sequencing and microarray-based copy number analyses. RESULTS We identified a whole-gene duplication of PCSK9 in 2 unrelated Canadian FH index cases; this PCSK9 CNV was also found to cosegregate with affected status in family members. Features in affected individuals included severely elevated LDL cholesterol levels that were refractory to intensive statin therapy, pronounced clinical stigmata, premature cardiovascular events, and a plasma PCSK9 of approximately 5000 ng/mL in 1 index case. We found no CNVs in APOB, LDLRAP1, APOE, STAP1, LIPA, and ABCG5/8 in our cohort of 704 FH individuals. CONCLUSIONS Here, we report the first description of a CNV affecting the PCSK9 gene in FH. This finding is associated with a profound FH phenotype and the highest known plasma PCSK9 level reported in a human. This finding also has therapeutic relevance, as elevated PCSK9 levels may limit the efficacy of high-dose statin therapy and also PCSK9 inhibition.