Elsevier

Clinica Chimica Acta

Volume 411, Issues 23–24, 14 December 2010, Pages 1983-1991
Clinica Chimica Acta

Development of a high resolution melting method for the detection of genetic variations in hypertrophic cardiomyopathy

https://doi.org/10.1016/j.cca.2010.08.017Get rights and content

Abstract

Background

Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiac disease affecting 1 in 500 people. Due to large cohorts to investigate, the number of disease-causing genes, the size of the 2 prevalent mutated genes, and the presence of a large spectrum of private mutations, mutational screening must be performed using an extremely sensitive and specific scanning method.

Methods

High Resolution Melting (HRM) analysis was developed for prevalent HCM-causing genes (MYBPC3, MYH7, TNNT2, and TNNI3) using control DNAs and DNAs carrying previously identified gene variants. A cohort of 34 HCM patients was further blindly screened. To evaluate HRM sensitivity, this cohort was also screened using an optimized DHPLC methodology.

Results

All gene variants detected by DHPLC were also readily identified as abnormal by HRM analysis. Mutational screening of a cohort of 34 HCM cases led to identification of 19 mutated alleles. Complete molecular investigation was completed two times faster and cheaper than using DHPLC strategy.

Conclusions

HRM analysis represents an inexpensive, highly sensitive and high-throughput method to allow identification of mutations in the coding sequences of prevalent HCM genes. Identification of more HCM mutations will provide new insights into genotype/phenotype relationships and will allow a better knowledge of the HCM physiopathology.

Introduction

Hypertrophic cardiomyopathy (HCM) is defined by unexplained hypertrophy of the ventricular myocardium in the absence of a detectable cause [1]. HCM, generally transmitted as an autosomal dominant trait, is the most prevalent genetic cardiac disease affecting 1 in 500 people [1]. HCM is caused by mutations in at least ten sarcomeric protein encoding genes and marked allelic heterogeneity has been seen with the majority of disease-causing genes [2], [3]. Over the past decade, molecular genetic approaches have allowed the identification of more than 1000 disease-causing defects scattered among these genes [2], [3]. The four most common genes involved in HCM are β-myosin heavy chain (MYH7, OMIM + 160760), cardiac myosin binding protein C (MYBPC3, OMIM *600958), cardiac troponin T (TNNT2, OMIM *191045) and cardiac troponin I (TNNI3, OMIM + 191044) [2], [3]. The majority of reported mutations (86%) are single nucleotide substitutions causing missense, nonsense, or splice mutations. The remaining 14% are small in-frame insertions or deletions, mainly in MYBPC3, or rare large deletions (for more informations, see the Human Gene Mutation Database; www.hgmd.cf.ac.uk). Although some recurrent mutations have been described in MYH7 and MYBPC3, most affected families segregate a unique private mutation. In addition, more than one genetic variant could be observed in approximately 5% of HCM patients [4], [5], [6], [7]. As a subgroup of patients carries multiple mutations, it is recommended to screen at least all coding sequences of the four most prevalent pathogenic HCM genes (MYBPC3, MYH7, TNNT2, and TNNI3).

In medical practice, mutational screening of HCM patients is crucial for proper management of patients and affected families. A molecular genetics approach (DNA testing and genetic counselling) can now help identify asymptomatic individuals who have inherited the disease causing allele within families segregating HCM. Genetic testing can also aid in the differential diagnosis of hypertrophic cardiomyopathy, more particularly in the differentiation of HCM from hypertensive or athlete's heart. Molecular analysis of HCM patients is however challenging owing to the number of disease-causing genes, the size of the 2 prevalent mutated genes (MYBPC3, MYH7), and the presence of a large spectrum of private mutations. To date, mutational screening in most of the HCM cohorts was performed either by direct sequencing or by using a scanning method such as DHPLC or SSCP [8], [9], [10], [11], [12], [13], [14], [15]. These methods for large-scale detection of mutations are expensive and technically time-consuming. High resolution melting (HRM) analysis has been successful in overcoming many of these limitations and constitutes a detection method with a nearly 100% detection [16], [17]. This scanning method does not require any processing, reagent additions or separations after PCR. Once amplicons obtained, melting curves are generated by monitoring the fluorescence of a saturating dye that does not inhibit PCR. When combined with real-time PCR, this approach allowed a simple, semi-automated, and cost-effective detection of single-base substitutions and small insertions/deletions.

In this study, we report an optimized protocol for scanning prevalent HCM-causing genes (MYH7, MYBPC3, TNNT2 and TNNI3) by HRM analysis using the Rotor-Gene 6000 (Corbett Life Science). A cohort of 34 HCM patients was blindly screened using both the HRM and DHPLC strategies in order to determine the most efficient technique in terms of sensibility, specificity, practicability and cost.

Section snippets

Subjects

Genomic DNA samples from control patients and from HCM patients with previously characterized genetic variants were used to determine the sensitivity of HRM analysis. Optimized HRM conditions were applied to further screen mutations in a panel of 34 additional unrelated HCM patients. HCM patients met the clinical diagnostic criterion for HCM: left ventricular wall thickness > 13 mm in the absence of another confounding diagnosis. The study was conducted in accordance with the principles of the

Optimization of HRM conditions

Mutational screening of MYH7, MYBPC3, TNNT2 and TNNI3 coding sequences by HRM analysis required the investigation of 95 coding exons. As sensitivity and specificity of mutation detection by HRM analysis could be affected by the length the amplicon but also by the presence of many melting domains, each exon was firstly tested using a DNA melting simulation software for in silico diagnostic assay design (www.biophys.uni-duesseldorf.de/local/POLAND /poland.html). Exons which were greater than 350 

Discussion

Many scanning methods, such as single-strand conformational polymorphism analysis (SSCP), denaturing gradient gel electrophoresis (DGGE), denaturing high-performance liquid chromatography (DHPLC), temperature gradient capillary electrophoresis (TGCE), PCR-RFLP, have been developed to screen for differences between the two copies of DNA within an individual. All of these methods require separation of the sample on a gel or other matrix. Many are manual and labor intensive, while others are

Acknowledgements

The full disclosure presents no conflict of interest. This work was supported by PHRC 97061 and by French Ministry of Research (Diagnosis Network on Neuromuscular Diseases).The authors thank Ms. C. Bulle, E. Froidefond, R. Perraudin and O. Vial for expert technical assistance.

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