Familial hypercholesterolemia (FH) is a heritable condition of severely elevated LDL cholesterol, characterized by premature atherosclerotic cardiovascular disease. FH affects an estimated 1 in 250 individuals worldwide, and is considered to be the most frequent monogenic disorder encountered in clinical practice. Although FH has multiple genetic etiologies, the large majority of defined cases result from 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 as ~10% of FH cases are attributed to CNVs in LDLR; accounting for them decreases false-negative findings. Here, we have determined the potential of replacing MLPA with bioinformatic analysis (VarSeq) 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 NGS + VarSeq, while 350 samples negative for CNVs by MLPA were also negative by NGS + VarSeq. This result suggests that MLPA is dispensable, significantly reducing costs, resources, and analysis time associated with the routine diagnostic screening for FH, while promoting more widespread assessment of this important class of mutations across diagnostic laboratories.
About the Presenter
Michael Iacocca is a research trainee at Robarts Research Institute, of the Schulich School of Medicine & Dentistry, Western University, London ON, Canada. Michael completed his BSc degree with an Honors Specialization in Genetics at Western University in 2016, and is currently completing his MSc degree in Biochemistry under the supervision of Dr. Robert Hegele. His research has so far focused on the genetic determinants of extreme LDL cholesterol levels in familial hypercholesterolemia (FH) and on expanding the routine diagnostic screening of FH to include both polygenic risk scores and copy number variation analysis. Michael is also working closely with the Clinical Genomics (ClinGen) Resource FH Variant Curation Committee in a collaboration that will soon establish guidelines to achieve globally standardized DNA variant interpretation in FH. Michael hopes to eventually attend medical school while maintaining a keen interest in the research space of clinical genetics.