Successful pharmacological management of a child with compound heterozygous familial hypercholesterolemia and review of the recent literature

Sreedharan, Aravind Venkatesh; Pek, Sharon Li Ting; Tan, Teng Hong; Tavintharan, Subramaniam; Yap, Fabian

doi:10.1016/j.jacl.2020.07.006

Cited by 1 publication

(2 citation statements)

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“…Combined computational analysis based on 10 predictor tools (BayesDel_addAF, DANN, DEOGEN2, EIGEN, FATHMM-MKL, LIST-S2, M-CAP, MVP, MutationTaster and SIFT) on Varsome ( , accessed on 6 June 2022) classified the above variant as pathogenic. This variant was previously reported to be one of the most common in FH patients in Singapore, Hong Kong, Taiwan and China [ 23 ]. In vitro research data, based on radioactive method, indicated that LDL receptor activity decreased by 60% due to c.1747C>T variant [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

“…This variant was previously reported to be one of the most common in FH patients in Singapore, Hong Kong, Taiwan and China [ 23 ]. In vitro research data, based on radioactive method, indicated that LDL receptor activity decreased by 60% due to c.1747C>T variant [ 23 ]. Based on the available reports, the detected variant should be considered as potentially pathogenic, disrupting the normal function of the LDL receptor.…”

Section: Discussionmentioning

confidence: 99%

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Identification of New Copy Number Variation and the Evaluation of a CNV Detection Tool for NGS Panel Data in Polish Familial Hypercholesterolemia Patients

Rutkowska

Pinkier

Sałacińska

et al. 2022

Genes

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Familial hypercholesterolemia (FH) is an inherited, autosomal dominant metabolic disorder mostly associated with disease-causing variant in LDLR, APOB or PCSK9. Although the dominant changes are small-scale missense, frameshift and splicing variants, approximately 10% of molecularly defined FH cases are due to copy number variations (CNVs). The first-line strategy is to identify possible pathogenic SNVs (single nucleotide variants) using multiple PCR, Sanger sequencing, or with more comprehensive approaches, such as NGS (next-generation sequencing), WES (whole-exome sequencing) or WGS (whole-genome sequencing). The gold standard for CNV detection in genetic diagnostics are MLPA (multiplex ligation-dependent amplification) or aCGH (array-based comparative genome hybridization). However, faster and simpler analyses are needed. Therefore, it has been proposed that NGS data can be searched to analyze CNV variants. The aim of the study was to identify novel CNV changes in FH patients without detected pathogenic SNVs using targeted sequencing and evaluation of CNV calling tool (DECoN) working on gene panel NGS data; the study also assesses its suitability as a screening step in genetic diagnostics. A group of 136 adult and child patients were recruited for the present study. The inclusion criteria comprised at least “possible FH” according to the Simon Broome diagnostic criteria in children and the DLCN (Dutch Lipid Clinical Network) criteria in adults. NGS analysis revealed potentially pathogenic SNVs in 57 patients. Thirty selected patients without a positive finding from NGS were subjected to MLPA analysis; ten of these revealed possibly pathogenic CNVs. Nine patients were found to harbor exons 4–8 duplication, two harbored exons 6–8 deletion and one demonstrated exon 9–10 deletion in LDLR. To test the DECoN program, the whole study group was referred for bioinformatic analysis. The DECoN program detected duplication of exons 4–8 in the LDLR gene in two patients, whose genetic analysis was stopped after the NGS step. The integration of the two methods proved to be particularly valuable in a five-year-old girl presenting with extreme hypercholesterolemia, with both a pathogenic missense variant (c.1747C>T) and exons 9–10 deletion in LDLR. This is the first report of a heterozygous deletion of exons 9 and 10 co-occurring with SNV. Our results suggest that the NGS-based approach has the potential to identify large-scale variation in the LDLR gene and could be further applied to extend CNV screening in other FH-related genes. Nevertheless, the outcomes from the bioinformatic approach still need to be confirmed by MLPA; hence, the latter remains the reference method for assessing CNV in FH patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%