Validation of high-resolution DNA melting analysis for mutation scanning of the LMNA gene

Available online at www.sciencedirect.com

Clinical Biochemistry 42 (2009) 892 – 898

Validation of high-resolution DNA melting analysis for mutation scanning of the LMNA gene Gilles Millat a,b,⁎, Valérie Chanavat a , Sophie Julia c , Hervé Crehalet a,b , Patrice Bouvagnet b,d,e , Robert Rousson a,b a

Laboratoire de Cardiogénétique Moléculaire, Centre de Biologie et Pathologie Est, Hospices Civils de Lyon, Bron, France b Université de Lyon, Lyon, F-69003, France; Université Lyon 1, Lyon, F-69003, France c Service de Génétique Médicale, Hôpital Purpan, CHU Toulouse, Toulouse, France d Service de Cardiologie C, Groupe Hospitalier Est, Hospices Civils de Lyon, Bron, France e EA4171, Methodologie du Traitement de l'Information en Cardiologie, Université Lyon 1, Lyon, F-69003, France Received 3 November 2008; received in revised form 13 January 2009; accepted 24 January 2009 Available online 6 February 2009

Abstract Objectives: LMNA mutations lead to a wide spectrum of disorders now called laminopathies. Due to large cohorts to investigate, mutational screening must be performed using an extremely sensitive and specific scanning method. Design and methods: High Resolution Melting (HRM) analysis was developed for LMNA mutation detection. A cohort of 64 patients with dilated cardiomyopathy was prospectively screened using both HRM and DHPLC methodologies. Results: All gene variants detected by DHPLC or by direct sequencing were also readily identified as abnormal by HRM analysis. Mutations were identified in 7 patients (~ 11%). Complete molecular LMNA 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 identify LMNA genetic variants. The discovery of novel LMNA mutations will provide new insights into the pathophysiology of dilated cardiomyopathy and in all other laminopathies. © 2009 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. Keywords: Mutations; Laminopathies; Dilated cardiomyopathy; High resolution melting; DHPLC; LMNA

Introduction Lamins are structural protein components of the nuclear lamina, a protein network underlying the inner nuclear membrane that determines nuclear shape and size. Three types of lamins, A, B, and C, have been described in mammalian cells. The LMNA gene [LMNA; MIM#: 150330, Swiss-Prot: P02545], located on chromosome 1q21.2, encodes the nucleo-

Abbreviations: DCM, Dilated Cardiomyopathy; HRMA, High Resolution Melting Analysis; DHPLC, Denaturing High-Performance Liquid Chromatography. ⁎ Corresponding author. Laboratoire de Cardiogénétique Moléculaire, Centre de Biologie Est, F-69677 BRON Cedex, France. Fax: +33(0)472357246. E-mail address: [email protected] (G. Millat).

philic A-type lamins, lamin A and lamin C [1]. These isoforms are generated by different splicing within exon 10 of LMNA. The coding region of the lamin A/C gene spans approximately 24 kb and contains 12 exons. Since the first mutation identified in the LMNA gene responsible for the autosomal dominant Emery–Dreifuss muscular dystrophy [2], numerous other mutations were identified leading to a wide spectrum of various disorders now called laminopathies (Table 1) [3,4]. Consequently, in medical practice, LMNA mutational screening in patients with syndromes listed in Table 1 is crucial for proper management of probands and relatives. To date, more than 230 different LMNA mutations have been reported with a large majority (~ 80%) of missense mutations (http://www.dmd.nl/ lmna_seqvar.html; http://www.umd.be:2000/). These mutations are scattered through the LMNA gene.

0009-9120/$ - see front matter © 2009 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.clinbiochem.2009.01.016

G. Millat et al. / Clinical Biochemistry 42 (2009) 892–898 Table 1 List of laminopathies LMNA linked-diseases

Inheritance

Hutchinson–Gilford progeria syndrome Atypical Werner syndrome Emery–Dreifuss muscular dystrophy type 2 Emery–Dreifuss muscular dystrophy type 3 Limb girdle muscular dystrophy Dilated cardiomyopathy, type 1A Charcot–Marie–Tooth disease, type 2 Familial partial lipodystrophy, Dunnigan type Mandibuloacral dysplasia Restrictive dermopathy Generalized lipoatrophy/lipodystrophy

De novo mutations Autosomal dominant Autosomal dominant Autosomal recessive Autosomal dominant Autosomal dominant Autosomal recessive Autosomal dominant Autosomal recessive De novo mutations Autosomal dominant

Dilated cardiomyopathy (DCM) is the most common cause of heart failure, resulting in considerable morbidity and mortality. DCM is characterized by dilatation and impaired contraction of the left ventricle. More than 20 known genes could cause autosomal dominant DCM, each accounting for only a few percentages of cases. LMNA mutations represent

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the leading genetic cause of DCM as LMNA genetic variants were observed with frequency varying from 6 to 9% in DCM probands [5–11]. To date, most of the mutational screening in DCM patients was performed either by direct sequencing [9,11], or by DHPLC/sequencing [5–8,12], or by DGGE/ sequencing strategy [10]. These methods for large-scale detection of mutations are expensive and technically timeconsuming. High Resolution Melting (HRM) analysis has been successful in overcoming many of these limitations and constitutes a detection method with a nearly 100% detection sensitivity [13]. No processing, reagent additions or separations after PCR are required. After PCR amplification, amplicons are readily subjected to melting curves with a fluorescence monitoring 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 the LMNA gene by HRM analysis using the Rotor-Gene 6000 (QIAGEN). A cohort of 64 DCM cases was blindly screened

Table 2 HRM conditions for mutation scanning of LMNA gene Exon

1

Forward primer (5′ to N3′)

Reverse primer (5′ to N3′)

Size (pb)

T°a (°C)

MgCl2 (mM)

1a

tccgagcagtctctgtcctt

ctgaccacctcttcagactcg

297

65–55

3

1b

ctcgctggaaacggagaac

ccctctcactcccttcctg

205

70–60

3

2

cctgggagcctggcactgtct

tgagtgtacatgtgttaggtg

282

70–60

2.5

3

tgttctgtgaccccttttcc

agcccaagtctgtcatcacc

228

70–60

3

4

ggcctcccaggaactaattctg

ctccctgccaccatctgc

334

70–65

2

5

ctcccagtcaccacagtcct

actctaggcccctggagaga

208

70–60

3

6

gtccctccttccccatactt

ggtctagtcaagggcagttg

350

70–60

3.2

7a

ggcaactggccttgactaga

cgtgcgtgctgtgagaag

193

70–60

3

7b

gtcaccaaaaagcgcaaact

gcagctgtatccccttagacc

175

70–60

3

8

gaggcctcaattgcaggcaggc

acccaaggcctccccagag

252

70–60

1.5

9

ggagcgctggggtaagtgtc

ctcgtccagcaagcagccag

192

70–60

3

10

ctgacccttggacctggtt

agggaggagagagaagaaagg

281

70–60

2

11a

agtggtcagtcccagactcg

gacactggaggcagaagagc

214

70–60

2.5

11b

ggctcaggagcccaggtg

acctcgtcctacccctcgat

234

70–60

2.5

agggctggagtgtgagggat

atgaggtgaggaggacgcaggaa

199

70–60

3

7

11

12

HRM conditions Melting T° ranges Leading range

Trailing range

83.7–84.4 83.9–84.3 86.3–86.6 86.9–87.8 85.6–87.3 80–80.9 80.5–81.2 87.6–88.5 84.4–85.2 82.7–84.4 84.3–85.2 83.3–85.1 85.1–86 84.3–86 87.6–88.4 86.9–88.3 86.4–87.5 84.8–86.5 84.1–85 83.9–85.6 82.6–83.7 81.7–83.7 86.3–87.2 85.6–87 85.6–86.7 85.9–86.6 90–90.4 89.2–90.2 88.4–90 85.5–86.7 85.1–86.9 83.1–84.1 82.2–84.1

91–91.6 86.1–86.4 90–90.5 93.3–94.3 93–94.8 93–94 86.1–86.8 92.5–93.3 89–90 89–90.5 89.3–90.3 89.6–91.5 91.8–92.8 92–93.5 92.3–93.1 92.2–93.7 91.6–92.8 91.6–93 91–92 91–92.8 89.8–90.9 89.3–91.3 91.6–92.6 91.3–92.9 93.5–94.6 90–90.3 92.9–93.4 94.3–95.2 94–95.8 92.3–93.4 92–93.6 87.8–88.8 88.1–90

Mutation detection threshold 90 95 90 90 90 90 95 95 90 90 90 90 95 95 90 90 90 90 90 90 90 90 95 95 92 95 90 90 90 94 94 90 90

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Table 3 Conditions for amplification and DHPLC analysis of LMNA gene Exon

MgSO4 (mM)

T°a (°C)

Amplicon length (pb)

Forward primer

Reverse primer

DHPLC analysis (°C)

1 2 3 4 5 6 7 8 9 10 11 12

1 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

70/60 65/55 65/55 65/55 70/60 70/60 65/55 70/60 70/60 70/60 65/55 70/60

574 267 250 334 432 350 293 252 192 459 357 199

cccagatcccgaggtccgac cagactccttctcttaaatctac ccttcaagttcttgtgttctgtgac ggcctcccaggaactaattctg gctgtagcagtgatgcccaac gtccctccttccccatactt ccccacttggtctccctctcc gaggcctcaattgcaggcaggc ggagcgctggggtaagtgtc gtaagcagcaggcgggacaaag ggtcagtcccagactcgcc agggctggagtgtgagggat

cctctccactccccgcca cctaggtagaagagtgagtgtac cctagcccagcccaagtctgtc ctccctgccaccatctgc ccaaagccctgagaagtgaag ggtctagtcaagggcagttg ccctgatgcagctgtatcccc acccaaggcctccccagag ctcgtccagcaagcagccag cacaggaatattccatggcatc cgcctgcaggatttggaagac atgaggtgaggaggacgcaggaa

64.8 59.2 61.2 61.9 61.2 64.4 63.4 62.4 62.4 59.2 63 61.2

using both HRM and DHPLC strategies in order to determine the most efficient technique in terms of sensibility, specificity, practicability and cost. Methods Subjects The study included 64 unrelated DCM probands and 6 control patients. Informed consent was obtained for all subjects. The study was conducted in accordance with the principles of the Declaration of Helsinki. The diagnosis of DCM was established according to international criteria [14]. DNA extraction Genomic DNA was extracted from whole blood using a WIZARD Genomic DNA Purification kit (Promega, Madison, WI). HRM analysis The coding exons of LMNA were amplified using intronic primers and PCR conditions reported in Table 2. All pre-PCR steps were performed using the CAS-1200 liquid handling Table 4 List of LMNA genetic variants identified by HRM analysis Exon LMNA genetic variant ⁎ 1 2 3 4 5 6 7 8 9 10 11 12

p.Ser17Ser, p.Leu92Phe IVS1-20 cNt, p.Arg119Arg, p.Ins 128–129 RVTLISSR, p.Glu161Lys IVS4+13gNt IVS4-13 TNA, p.Ala287Ala, p.Ala287fs p.Glu317Lys, p. Arg377His, IVS6+16 gNa p.Asp446Asp p.Gly523Arg p.His566His p.Leu587Leu, IVS11+26 aNg IVS12+27 gNa

⁎ Genetic variants indicated in bold correspond to mutations; others variants to SNPs.

67.5 64 62.2 63 62.6 65.4 65 62.9 63.4 62 64.4 62.2

69.5 65.8 62.8 65.7 63.6 66.2 65.5 63.9 64.4 63.1 65.4 63.2

65.4

66.5 67.5

system (QIAGEN, Courtaboeuf, Fra). Amplicon lengths were kept relatively short (175–354 bp) to improve discrimination between genotypes. Real-time PCR cycling of the genomic DNA samples were carried out on the Rotor-Gene 6000 analyzer (QIAGEN). The cycling profile was 10 min denaturation at 95 °C, followed by 40 cycles of denaturation at 95 °C for 10 s, annealing at the indicated temperature in Table 2 for 15 s, and extension at 72 °C for 15 s. The final PCR step was a denaturation–renaturation procedure with 1 min at 95 °C followed by a decrease of temperature to 40 °C at 1 °C/s. All amplifications were performed in a final volume of 20 μL containing 10 ng of genomic DNA. Most amplicons were obtained using LightCycler® 480 High Resolution Melting Master kit according to the manufacturer's instructions (Roche Applied Science, Meylan, Fra). Exon 6 was amplified using LightCycler® 480 Probes Master kit (Roche Applied Science) and SYTO-9 dye (Invitrogen Carlsbad, CA) at final concentration of 2.5 μM according to the manufacturer's instructions (Roche Applied Science). Exons 1b and 12 were amplified using SYBR® GreenER™ qPCR SuperMix according to the manufacturer's instructions (Invitrogen). Exon 1a was amplified using Platinum Taq DNA polymerase (Invitrogen), SYTO-9 dye at final concentration of 2.5 μM, 100 μM of each dNTP, 0.25 μM of each primer, and MgCl2 at indicated concentrations in Table 2. Amplification of exon 1a was successfully optimized with 10% DMSO. HRM analysis was also performed using the Rotor-Gene 6000 analyzer (QIAGEN). Melting curves are generated by ramping from 70 °C to 99 °C at 0.1 °C/s. Melting curves are normalised between two temperature ranges, the leading range and the trailing range. Optimized melting temperature ranges Table 5 Molecular data of identified LMNA mutations in DCM cases Exon

Nucleotide change

Effect on protein

References

1 2 2 5 6 6 9

c.274 CNT c.383_384ins24bp c.481GNA c.859insC c.949GNA c.1130GNT c.1567 GNA

p.Leu92Phe p.Ile128-Ala129 insRVTLISSR p.Glu161Lys p Ala287fs p.Glu317Lys p.Arg377His p.Gly523Arg

15 Novel 9,16 Novel 12 7,10,16–20 Novel

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used to analzse PCR amplicons are given in Table 2. Fluorescence data were visualized using normalisation plotting, and then analyzed using the automated grouping functionality provided by the Rotor-Gene 6000 scanning software. DHPLC analysis Amplifications were performed in a final volume of 50 μL containing 100 ng of genomic DNA, 100 μM of each dNTP, 0.25 μM of each primer, 1.25 units of Optimase DNA polymerase (Transgenomic) and MgCl2 at indicated concentrations in Table 3. Prior to DHPLC analysis, the quality and quantity of PCR products were determined on 2% agarose gels by standard procedures. The temperature for heteroduplex detection was determined using the NAVIGATOR software (Transgenomic). Since some fragments showed distinct melting domains, additional analyzing temperatures were required. The optimized elution profiles and melting temperatures of the entire coding sequence of LMNA gene are shown in Table 3. Sequence analysis PCR products showing divergent DHPLC or HRM profiles were purified by using MultiScreen-PCR Plates (Millipore, Bedford, MA) and directly sequenced on both strands using the BigDye® Terminator v.3.1 Cycle Sequencing Kit (Applied Biosystems, Forster City, CA). Sequencing products were purified with Montage SEQ96 Sequencing Reaction Clean Up kit (Millipore) and applied onto an ABI 3730 automatic sequencer. Results Complete LMNA mutational screening required the investigation of 12 exons. HRM analysis was firstly optimized using a small cohort of 6 control DNAs. Exons and exon/intron junctions of control DNAs were directly sequenced on both strands in order to determine which genetic variations have to be detected by HRM analysis. To perform HRM analysis with a near 100% sensitivity, exons which were greater than 400 bp or with more than two melting domains were amplified in two overlapping segments (Table 2). Presence of melting domains was determined, in silico, using a DNA melting simulation software (www.biophys.uni-duesseldorf.de/local/POLAND/ poland.html). To avoid a variable amplification that may lead to an increased number of false positives, all analyzed DNAs were extracted using the same method and were subsequently adjusted to a concentration of 2.5 ng/μL. Presence of too many false positives could lead to misinterpretation of results as the data became too noisy to reliably discriminate wild type and mutated samples. PCR optimization also plays a critical role in successful HRM analysis. For best results, PCRs were optimized to produce specific product by using touchdown thermal cycling programs, by varying magnesium ion concen-

tration and by testing different saturating dyes and different DNA polymerases (Table 2). Using optimized HRM conditions reported in Table 2, all LMNA polymorphisms previously detected by sequencing on our control cohort were readily identified as abnormal HRM profiles. A cohort of 64 DCM patients was further blindly screened using both HRM and DHPLC strategies (Tables 2 and 3). Each abnormal HRM or DHPLC profile was sequenced. This mutational screening lead to the identification of 19 LMNA genetic variants: 7 pathogenic mutations and 12 polymorphisms (Tables 4 and 5, Fig. 1). All gene variants present in a heterozygous status were detected both by HRM and DHPLC analyses. Unlike DHPLC, for some DCM cases, HRM analysis was also able to detect polymorphisms which were present in a homozygous status. This molecular study allowed us to identify 7 mutations including 5 missense mutations, 1 1-bp insertion, 1 in-frame 24-bp deletion (Table 5 and Fig. 1). Missense mutations affect highly conserved amino acid residues and were not found in 200 control chromosomes of French origin. Insertion mutations and p.Gly523Arg correspond to new mutations. The p.Leu92Phe mutation was recently identified in a patient presenting with a severe metabolic syndrome [15]. The p.Glu161Lys mutation, localised in the rod domain of the lamin A and the lamin C, was previously identified in 2 DCM families [9,16]. The missense mutation p.Arg377His was previously identified in affected patients of families that were described with either DCM [5,17], or with DCM associated with a specific quadriceps restricted myopathy [16,18,19], or with Emery–Dreifuss muscular dystrophy [10] or with LGMD1B clinical features [20]. Functional consequence of this mutation is associated with a disorganisation of the lamin [18,21]. The p.Glu317Lys was previously reported in an Italian family with a dilated cardiomyopathy and an atrioventricular block [12]. Discussion Mutations in the LMNA gene are responsible for several laminopathies, including dilated cardiomyopathy, with complex genotype/phenotype relationships. Direct sequencing remains the gold standard methodology to detect LMNA genetic variations. This methodology provides both genotyping and scanning information. However due to the large number of private mutations and the large number of patients to explore, identification of LMNA mutations by direct sequencing remains expensive and time-consuming. Optimization of scanning methods with a nearly 100% detection could lead to a simple, semi-automated, and cost-effective detection of single-base substitutions and small insertions/deletions. Among them, HRM and DHPLC are known to offer discovery and detection of genetic variations at close to 100% sensitivity, making them among the most sensitive and accurate scanning method. The sensitivity of HRM has previously been evaluated extensively in the NRGL report (http://www.ngrl.org.uk/Wessex/downloads/

Fig. 1. Normalised high-resolution melting curves (A) and difference plots (B) of identified LMNA mutations. Green curves represent wild-type HRM profiles.

G. Millat et al. / Clinical Biochemistry 42 (2009) 892–898

pdf/NGRL_HRM_WebPP.pdf) which compared the sensitivity of HRM to the sensitivity of the “gold standard” methodology. This report evaluated 624 samples, with 11 amplicons varying in length, GC%, point mutations, insertions and deletions, positional location within the amplicon. Results on the RotorGene 6000 showed 100% sensitivity and 95.3% specificity. Moreover, HRM analysis differs from other gene scanning methods as any application of the PCR products onto a gel or other matrix is required to separate and detect the heteroduplexes. In our study, HRM analysis was firstly optimized using a small cohort of 6 control genomic DNAs that were previously completely sequenced. As PCR optimization plays a critical role in successful HRM analysis, meticulous optimization of PCR conditions were performed in order to avoid the presence of non-specific bands and primers–dimers that could significantly reduce HRM performance. Using these optimized PCR conditions, all LMNA polymorphisms previously detected by sequencing on our control cohort were readily identified as abnormal HRM profiles. A cohort of 64 DCM patients was further blindly screened using HRM and DHPLC strategies. Complete mutation identification was technically achieved in slightly less than 1 week whereas, using DHPLC strategy, this screening was technically achieved in approximately 2 weeks. Moreover, complete HRM LMNA investigation was completed two times cheaper than when using DHPLC strategy. All LMNA genetic variants detected by DHPLC were readily identified as abnormal HRM profiles. This molecular screening led to the identification of 19 LMNA variants including 7 pathogenic mutations (~ 11%) and 12 polymorphisms (Tables 4 and 5, Fig. 1). The prevalence of LMNA mutations observed in our cohort is slightly higher than previously reported frequencies [5,6,10,11]. Similar results were previously reported for other genes such as SCN5A, F8, NF2 or CFTR suggesting that our reported HRM conditions minimize the risk to obtain a false negative [22–25]. On the other hand, HRM analysis could induce some false positives. Even with good genomic DNA quality samples that were extracted with the same method, some amplicons produce melt curves with subtle differences which may result in increased false positive rates. This number of false positive calls was significantly decreased by testing each amplicon against a mean of 4 wild-type samples. In our experience [[22], this study], use of 4 selected wild-type samples instead of only one does not modify the sensitivity of the method but slightly increase the specificity. Although, this analysis was performed on a cohort of DCM patients, this method could be used to scan for LMNA mutations in other laminopathies since there are no specific gene domains or mutation types that are associated to any subtype of laminopathies. Our results support this view since mutations were scattered along the gene and of varying types. In summary, HRM is a mutation scanning method which presents a sensitivity comparable or superior to currently available prescreening techniques like DHPLC. HRM is a rapid, close-tube, highly efficient and cost effective post-PCR technique which fulfills all the conditions required for the systematic detection of

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LMNA genetic variants. This molecular strategy allows the rapid mutation screening of LMNA, a better understanding of the pathophysiology of LMNA-linked diseases which could further lead to a better management of patients with LMNA pathogenic mutations. Acknowledgments The full disclosure presents no conflict of interest. This work was supported by PHRC 97061 and by the 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. References [1] Lin F, Worman HJ. Structural organization of the human gene encoding nuclear lamin A and nuclear lamin C. J Biol Chem 1993;268:16321–6. [2] Bonne G, Di Barletta MR, Varnous S, et al. Mutations in the gene encoding lamin A/C cause autosomal dominant Emery–Dreifuss muscular dystrophy. Nat Genet 1999;21:285–8. [3] Worman HJ, Bonne G. Laminopathies”: a wide spectrum of human diseases. Exp Cell Res 2007;313:2121–33. [4] Taylor MR, Carniel E, Mestroni L. Cardiomyopathy, familial dilated. Orphanet J Rare Dis 2006;13:1–27. [5] Taylor MR, Fain PR, Sinagra G, et al. Familial Dilated Cardiomyopathy Registry Research Group. Natural history of dilated cardiomyopathy due to lamin A/C gene mutations. J Am Coll Cardiol 2003;41:771–80. [6] Vytopil M, Benedetti S, Ricci E, et al. Mutation analysis of the lamin A/C gene (LMNA) among patients with different cardiomuscular phenotypes. J Med Genet 2003;40:e132. [7] Taylor MR, Robinson ML, Mestroni L. Analysis of genetic variations of lamin A/C gene (LMNA) by denaturing high-performance liquid chromatography. J Biomol Screen 2004;9:625–8. [8] Kärkkäinen S, Reissell E, Heliö T, et al. Novel mutations in the lamin A/C gene in heart transplant recipients with end stage dilated cardiomyopathy. Heart 2006;92:524–6. [9] Song K, Dubé MP, Lim J, Hwang I, Lee I, Kim JJ. Lamin A/C mutations associated with familial and sporadic cases of dilated cardiomyopathy in Koreans. Exp Mol Med 2007;39:114–20. [10] van Tintelen JP, Hofstra RM, Katerberg H, et al. High yield of LMNA mutations in patients with dilated cardiomyopathy and/or conduction disease referred to cardiogenetics outpatient clinics. Am Heart J 2007;154:1130–9. [11] Parks SB, Kushner JD, Nauman D, et al. Lamin A/C mutation analysis in a cohort of 324 unrelated patients with idiopathic or familial dilated cardiomyopathy. Am Heart J 2008;156:161–9. [12] Arbustini E, Pilotto A, Repetto A, et al. Autosomal dominant dilated cardiomyopathy with atrioventricular block: a lamin A/C defect-related disease. J Am Coll Cardiol 2002;39:981–90. [13] Reed GH, Kent JO, Wittwer CT. High-resolution DNA melting analysis for simple and efficient molecular diagnostics. Pharmacogenomics 2007;8:597–608. [14] Mestroni L, Maisch B, McKenna WJ, et al. Guidelines for the study of familial dilated cardiomyopathies. Collaborative Research Group of the European Human and Capital Mobility Project on Familial Dilated Cardiomyopathy. Eur Heart J 1999;20:93–102. [15] Decaudain A, Vantyghem MC, Guerci B, et al. New metabolic phenotypes in laminopathies: LMNA mutations in patients with severe metabolic syndrome. J Clin Endocrinol Metab 2007;92:4835–44. [16] Sébillon P, Bouchier C, Bidot LD, et al. Expanding the phenotype of LMNA mutations in dilated cardiomyopathy and functional consequences of these mutations. J Med Genet 2003;40:560–7. [17] Perrot A, Sigusch HH, Nägele H, et al. Genetic and phenotypic analysis of dilated cardiomyopathy with conduction system disease: demand for

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