Annals of Clinical Biochemistry > Annals of Clinical Biochemistry Online First > 10.1258/acb.2009.009076

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Original Article

Development of a high-resolution melting method for mutation detection in familial hypercholesterolaemia patients

R A Whittall¹, M Scartezini^1,2, KaWah Li¹, C Hubbart¹, Z Reiner³, A Abraha⁴, H A W Neil⁵, G Dedoussis⁶ and S E Humphries¹

¹ Centre for Cardiovascular Genetics, British Heart Foundation Laboratories, Royal Free and University College London Medical School, London WC1E 6JJ, UK; ² Department of Medical Pathology, Federal University of Paraná, Curitiba–Paraná, 80210–170, Brazil; ³ Department of Internal Medicine, University Hospital Center Zagreb, Zagreb 1000, Croatia; ⁴ Department of Clinical Biochemistry, Stoke Mandeville Hospital, Aylesbury HP21 8AL, UK; ⁵ Division Public Health & Primary Health Care, University of Oxford, Oxford OX3 7LF, UK; ⁶ Department of Dietetics-Nutrition, Harokopio University, Athens 17671, Greece

Corresponding author: S E Humphries, Centre for Cardiovascular Genetics, British Heart Foundation Laboratories, The Rayne Building, Royal Free and University College London Medical School, London WC1E 6JJ, UK. Email: rmhaseh{at}ucl.ac.uk

Aims: Current screening methods, such as single strand conformational polymorphism (SSCP) and denaturing high performance liquid chromatography (dHPLC) that are used for detecting mutations in familial hypercholesterolaemia (FH) subjects are time consuming, costly and only 80–90% sensitive. Here we have tested high-resolution melt (HRM) analysis for mutation detection using the Rotor-Gene⁶⁰⁰⁰ realtime rotary analyser.

Methods and subjects: Polymerase chain reaction and melt conditions (HRM) for 23 fragments of the LDL-receptor gene, a region of exon 26 in the APOB gene (including p.R3527Q) and exon 7 of the PCSK9 gene (including p.D374Y) were optimized. Two double stranded DNA saturating dyes, LC-Green and Syto9, were compared for sensitivity. Eighty-two samples with known mutations were used as positive controls. Twenty-eight Greek FH heterozygous patients and two homozygous patients from the UK and Croatia were screened.

Results: HRM was able to identify all the positive control mutations tested, with similar results with either dye. Eight different variations were found in 17 of the 28 Greek FH patients for an overall detection rate of 61%: c.41delT (1), p.W165X (1), p.C173R (3), p.S286R (2), p.V429M (4), p.G549D (4), p.V613I (1), and a previously unreported mutation p.F694V (1) which is predicted to be FH-causing by functional algorithms. Mutations were found in both the homozygous patients; p.Q92X (Croatia) and p.Y489C (UK); both patients were homozygous for their respective mutations.

Conclusions: HRM is a sensitive, robust technique that could significantly reduce the time and cost of screening for mutations in a clinical setting.

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