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Updated: Jun 13, 2026
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Systematic evaluation of mobile element insertions in autosomal dominant hypercholesterolemia genes using short-read
Lisa Jeanpetit1, Corentin Molitor2, Alexandre Janin3
1Service de Biochimie et Biologie Moléculaire, Laboratoire de Biologie Médicale Multisites, Hospices Civils de Lyon, Lyon, France.
Background And Aims:
Autosomal dominant hypercholesterolemia (ADH) is a common monogenic disorder conferring markedly increased cardiovascular risk. While short-read next-generation sequencing (NGS) efficiently detects small nucleotide variants, it often misses mobile element insertions (MEIs), recently recognized as an additional pathogenic mechanism in LDLR-related ADH. This study aimed to systematically evaluate the contribution of MEIs to ADH in a large, well-characterized cohort.
Methods:
NGS data from 2393 unrelated probands were retrospectively screened for MEIs using MELT software. Candidate variants were confirmed by orthogonal sequencing, and their functional consequences on LDLR promoter activity were assessed through luciferase assays.
Results:
MELT initially identified LDLR MEIs in 2 out of 2393 subjects with suspicion of ADH (0.08%). Validation revealed one false-positive event corresponding to a 3.96 kb tandem duplication within an Alu-rich region (exons 13-14). The second variant, an AluYb8b1 insertion in the 5'UTR (c.-660_-659insAluYb8b1), was confirmed, leading to an adjusted prevalence of 1/2393 (0.04%). This second variant was not present in population databases, and segregation analysis remained inconclusive. Functional assays showed no measurable impact on transcriptional activity, classifying this MEI as a variant of uncertain significance.
Conclusions:
Although extremely rare, LDLR MEIs can occur in ADH and may be informative in patients negative after standard genetic testing. Optimized pipelines for MEI detection could refine molecular diagnosis.
