Presentation is loading. Please wait.

Presentation is loading. Please wait.

Kate Thomson Molecular Genetics Laboratory, Oxford

Similar presentations

Presentation on theme: "Kate Thomson Molecular Genetics Laboratory, Oxford"— Presentation transcript:

1 Kate Thomson Molecular Genetics Laboratory, Oxford
Clinical sensitivity of molecular genetic testing in hypertrophic cardiomyopathy. Kate Thomson Molecular Genetics Laboratory, Oxford

2 Overview Hypertrophic Cardiomyopathy
Clinical features Genetics Clinical sensitivity in our cohort Factors affecting clinical sensitivity

3 Hypertrophic cardiomyopathy
Characterised by thickening of the heart muscle, most commonly of the left ventricle, with no obvious cause (e.g. high blood pressure, athletes heart) Autosomal Dominant Prevalence of 1/500 Most common cause of heart related sudden death in people under 35 and athletes The most common of these is Hypertrophic Cardiomyopathy (HCM). The main feature of HCM is an excessive thickening of the heart muscle. First clinical description of HCM was reported in 1869, and it was recognised to be a genetic disorder in the late 1950s. It is estimated to have a prevalence of ~1/500 and thought to be the most common cause of SCD in people under 35 and athletes. Equates to ~ 12 young people dying each week in the UK.

4 The hypertrophic heart
In the normal heart of an average sized man the muscle is about 1cm thick. A diagnosis of HCM is made when the muscle is over 1.3 cm thick. Thickening can be anywhere in the left ventricle, most commonly its seen in the septum, between the left and right ventricles, but it can occur in the apex and occasionally it’s diffuse involving all the segments of the left ventricle. This thickening may be up to 3-4cm! The thickened muscle usually contracts well, and ejects most of the blood from the heart, however it is often stiff and relaxes poorly, requiring higher pressure than normal to expand. So the problem isn’t actually getting blood out of the heart, it’s getting the blood into the heart. Examination of the heart muscle under the microscope shows that the normal parallel alignment of muscle cells has been lost and the cells appear disorganised. This abnormality is called myocyte disarray. This disarray can sometimes interfere with the normal electrical activity in the hear and predispose to irregularities of the heartbeat.

5 Clinical Features Clinically heterogeneous
-No symptoms -Shortness of breath -Chest pain -Fainting -Dizziness -Palpitations -Exercise intolerance -Sudden death Variable presentation, age of onset and clinical course Differential diagnoses: -Cardiac amyloidosis -Hypertensive heart disease -Aortic stenosis -Athletes heart -Metabolic disease (Fabry’s disease, Danon disease) -Mitochondrial myopathy Clinically heterogeneous. Symptoms and severity can vary from person to person. They may begin in infancy, childhood or in middle or elderly life. Some patients never have any symptoms of HCM, in others the initial presentation may occasionally be with sudden death from HCM, but overall this is actually not common. Reduced penetrance and variable expression are the rule more than the exception. Clinical expression is probably influenced by several factors including age, sex, and environmental factors such as lifestyle, exercise and blood pressure. Genetic modifiers are also expected to be involved. Because the symptoms are close to those of other conditions it is not always easy or possible to make the differential diagnosis. These related conditions include the glycogen storage diseases and certain mitochondrial diseases, which usually have a different clinical profile and natural history and require different treatments. NB. Fabry’s disease is a rare X-linked AR metabolic storage disorder caused by a lack of lysosomal alpha galactosidase A, leading to an accumulation of glyco-sphingolipid in various tissues. Studies suggest a prevalence of 3% in males who present with LVH. Caused by mutations in GLA gene. Danon disease, is an extremely rare, X-linked, glycogen storage disease, caused by mutations in the LAMP-2 gene.Associated with severe cardiomyopathy, variable skeletal muscle weakness, and mental retardation. Both sexes can be affected but females generally present later.

6 Benefits of Genetic Diagnosis
Confirm clinical diagnosis/familial disorder Offer testing to at risk family members to enable early diagnosis and treatment Future Risk stratification and prognosis Patient management Making a genetic diagnosis helps clinicians to differentiate between “pure” HCM and phenocopy conditions that have similar clinical features. Due to the familial nature of the disease, when a diagnosis of HCM is made in an individual, clinical evaluation of first-degree relatives is recommended annually during adolescence and subsequently every 5 years. Identification of a familial pathogenic variant will allow for cascade screening of the family, identifying those individuals who require ongoing clinical evaluation and excluding others from annual cardiac evaluation. Studies ongoing to determine whether genotype can reliably be used to identify high risk cases and prognosis and whether patient management may be tailored to genotype.

7 Genetics >20 genes known to be associated
Majority of genes encode components of the sarcomere (contractile apparatus of the heart) Four genes commonly associated sarcomeric genes account for ~80% of mutations. Double/compound variants reported in 5-10% Genetically heterogeneous Over 20 genes are now known to be associated. Majority encode components of the cardiac sarcomere. 4 sarcomeric genes appear to be the most commonly associated. A significant no. of patients have been found to have > 1 mutation.

8 Cardiac muscle cell & sarcomere
So what is the sarcomere and how do mutations in sarcomeric genes lead to HCM? The sarcomere is the basic contractile unit of the cardiac myocyte. This slide shows the anatomy of a cardiac muscle cell and the sarcomere units that lie along its length.

9 Figure 2 J. Clin. Invest. Hiroyuki Morita, et al. 115:518 doi:10
Figure 2 J. Clin. Invest. Hiroyuki Morita, et al. 115:518 doi: /JCI24351 The sarcomere is comprised of thick and thin filaments. The thick filaments are composed predominantly of myosin. The thin filaments are composed of cardiac actin, a-tropomysin and troponins C, I and T. Each sarcomere is bounded by two membranes (Z lines). During muscle contraction the actin and myosin filaments slide over each other and the length of the sarcomere shortens drawing the Z lines closer together leading to contraction of the muscle cells.

10 Commonly associated sarcomeric genes
Protein % of HCM MYH7 Beta Myosin heavy chain 25-35% MYBPC3 Myosin-binding protein C 20-30% TNNT2 Troponin T 3-5% TNNI3 Troponin I <5% TPM1 Tropomyosin 1 alpha <2% MYL3 Regulatory myosin light chain <1% MYL2 Essential myosin light chain Rare ACTC1 Actin This slides shows the most commonly associated sarcomeric genes. MYH7 and MYBPC3 are the most commonly associated genes, accounting for up to 35% each, followed by TNNT2 and TNNI3 genes which account for approx 5% each. Mutations in the other sarcomeric genes are less commonly associated. Spectrum of pathogenic variants have been reported( missense, nonsense, frameshift, splice site) Precise mechanisms by which sarcomeric gene mutations lead to HCM remain incompletely understood. Data to support dominant negative effects (e.g. in MYH7), halpoinsufficiency (MYBPC3), and loss and gain of protein function (MYBPC3, TNNt2). Widely proposed that the overall effect of these mutant proteins is sarcomere dysfunction and that left ventricular hypertophy develops as compensatory response to sarcomere dysfunction.

11 Clinical Sensitivity in HCM
HCM service introduced 2003 Gene dossier submitted 2006 Clinical sensitivity estimated to be 60% Review clinical sensitivity in cohort ( ) Determine clinical sensitivity in our cohort (>700 probands) Comparison with published data Identify factors affecting clinical sensitivity “The probability of a positive test result when the disease is known to be present”

12 Clinical Sensitivity in our cohort
737 probands screened 346/737 variant detected Clinical sensitivity 47% Since 2003 we have screened over 700 probands. And detected variants in approx. 47% of these. In MYBPC3 and MYH7 variants =total is 363 (so not even counting TNNT2 or TNNI3). However 346 HCM screen positive. 17 variants unaccounted for (double/compound patients, would be ~14 patients) what about tnnt2 (>12) and tnni3 (>12)

13 Comparison with published data
Yield ranged from 13-61% 8 most commonly associated genes ~47% MYBPC3,MYH7,TNNT2,TNNI3 ~44% ~3% increased sensitivity~30% more workload 62% family history vs. 29% sporadic Useful to compare this to a study undertaken in 2005 which pooled the results of sarcomeric gene screening across several international groups. From these pooled results they estimated that if a complete screen of the 8 most commonly associated genes were undertaken, would expect to find a pathogenic variant in 47%. From this we estimated that the analysis undertaken in our laboratory of the 4 most commonly associated genes MYBPC3, MYH7, TNNT2 and TNNI3 genes would be expected to have a clinical sensitivity of ~44%. Analysis of these genes accounts for ~70% of the total workload (88/124 exons). Therefore we estimated that expanding analysis to include the 4 less commonly associated genes would increase workload by ~30% and achieve ~3% increase in sensitivity. What was also interesting to note was that if you split the probands into those with or without family history the clinical sensitivity you got a significant increase in detection rate. Van Driest et al Mayo Clin Proc 2005

14 Factors affecting clinical sensitivity
Diagnosis Clinical sensitivity Analysis Strategy So we wanted to identify the main factors which are likely to have an impact on the clinical sensitivity of genetic analysis in HCM. The accuracy of the clinical diagnosis. The analysis strategy undertaken (including the number of genes analysed and the technology used) The interpretation of the results . Results interpretation

15 Clinical Diagnosis Exclusion of phenocopies Family History The future
Refining clinical criteria of “sarcomeric HCM” Define frequency of phenocopies in HCM cohorts Cost of clinical vs. genetic investigations So how does clinical diagnosis affect clinical sensitivity. As previously discussed it can be difficult to make the differential diagnosis in HCM. A large proportion of patients with unexplained LVH (~50%) have no mutations in sarcomeric genes, though that a proportion may be due to patients with phenocopies of HCM. Careful phenotyping should identify the majority of these. All our referrals have gone through cardiology and clinical genetics assessment and I think in the majority of cases the cases that are being sent to us for genetic analysis really are the ones where the HCM is largely unexplained, and not associated with other features, however there is no defined clinical strategy for exclusion of phenocopies and therefore not all will have been excluded. As shown in previous slide selecting individuals with a family history of HCM will increase clinical sensitivity, however given the nature of the disorder (variable penetrance and age of onset) there is often no known or obvious family history, often these are the cases where the clinician feels genetic analysis is most useful in aiding diagnosis. For this reason we do not discriminate against cases without FH. What about in the future? Several studies have been undertake to try and tease out the subtle clinical differences between cohorts of patients with and without sarcomeric mutations. E.g. looking at morphological shape of the cardiac septum. It may be that in time these studies will find more robust clinical association which will allow us to indentify individuals with sarcomeric HCM. It may be possible to determine the expected frequency of phenocopies within HCM cohorts. For example recent studies have suggested that the prevalence of FD populations of HCM is 1%. A proportion of cases can be detected by biochemical means (levels of plasma α-galactosidase A activity) and confirmed by detection of mutations in the GLA gene. In addition diagnosis is relevant, because it allows the identification of disease carriers that might benefit from enzyme replacement therapy. So more accurate estimates of frequency of phenocopies and methods of exclusion may enable a more targeted screen. However, as introduction of new gene screening technologies leads to increased throughput, expansion of gene screens and reduction of costs it may be that genetic analysis becomes more cost effective and more definitive than comprehensive clinical and biochemical screening.

16 Analysis strategy Analysis of less commonly associated genes
Assay sensitivity and specificity New technology (Roche 454) Expansion of screen Faster throughput Results interpretation Cost implications Clinical sensitivity is also affected by the analysis strategy employed. Systematic genotyping of the 8 most commonly associated sarcomeric genes has revealed that over 80% of pathogenic variants are in MYBPC3, MYH7, TNNT2 and TNNI3 genes. We wouldn’t expect expansion of the gene screen to include some of the less common genes would have a huge impact on clinical sensitivity, however,comprehensive mutation analysis remains the goal for all index cases. Assay sensitivity and specificity may also impact on clinical sensitivity. We are currently using a combination of LS technology and sequencing which we feel offers high sensitivity. In terms of specificity it may be looking at the right genes but missing a subset of variants, for example those in intronic or untranslated regions or larger exon insertions deletions. Certainly for some genes where loss of protein function is the suspected mechanism it may be appropriate to use MPLA to look for larger gene deletions/insertions. There isn’t a lot of data out there supporting this at the moment but this could be an ascertainment bias, and it would be certainly be interesting to look at. We are currently working with the University of Oxford to introduce Roche 454 technologies for our SCD service. This will enable us to provide a more comprehensive service and hopefully increase throughput and reduce costs. Think we do have to be aware that by expanding analysis to include lesser known genes we will detect more variants of unknown clinical significance, and we will undoubtedly identify more individuals compound/double heterozygote for variants in these genes. This will have an impact on results interpretation and reporting, which brings me to our next slide…..

17 Interpretation of results
Classification Family testing Highly likely /certain to be pathogenic. Testing available for unaffected family members (FMs). Likely to be pathogenic but cannot be formally proven. Recommend testing affected FMs prior to analysis of unaffected FMs. Intermediate-not possible to determine neutral/pathogenic. Recommend testing affected FMs. Testing unaffected FMs not indicated. Unlikely to be pathogenic but Testing FMs not indicated. Neutral polymorphism -certainly not pathogenic. We investigate pathogenicity of variants using a combination of biochemical data, literature/mutation databases searches, in silico analysis and segregation analysis, generally we attempt to classify variants into the following categories: Highly likely: Clear evidence for pathogenicity 2. Likely: Likely to be pathogenic but cannot be formally proven 3. Intermediate: 4. Unlikely: 5. Neutral Polymorphism: To give you an idea of what this classification actually means in terms of family testing: Highly likely-offer PST testing Likely-recommend segregation prior to PST testing Intermediate-in absence of further evidence PST testing not recommended

18 Issues with results interpretation -the usual suspects……..
High number of private missense mutations Functional domains of proteins not defined Limited functional studies Segregation studies confounded by: clinical heterogeneity variable penetrance & age of onset SCD of other affected FMs No clinically normal control cohort However as I’m sure many of you can sympathise with classification of variant pathogeneicity is Difficult and there is always an element of subjectivity. Particular issues we have being -High number of private missense mutations -Often functional domains of proteins not defined -Above means that limited functional studies -segregation studies would be most useful but these are often confounded by clinical heterogeneity/variable penetrance/age of onset/death of other affected FMs -No “normal” control cohort And actually when you look at reports in the literature few studies actually breakdown their positive results by likely pathogeneicity this obviously impacts on estimates of clinical sensitivity in the literature. In more optimism moments it seems possible that as knowledge of the genes/proteins involved and the spectrum of variants associated expands that classification of variants will become a less daunting task. We have certainly seen the benefit of communication with other testing centres and feel that submission to a common mutation databases would be a huge step forward. Also very important when family testing is undertaken in different centres that results are fed back!

19 Clinical sensitivity based on likely pathogenicity
All 47% Highly likely & Likely 37% Highly likely only 27% Few reports in the literature breakdown estimates of clinical sensitivity by likely pathogenicity but this can have a big impact. Our of clinical sensitivity takes into consideration variants in the highly likely, likely or intermediate categories. You can see from the above chart the % of variants in each class. If were only highly likely variants were included this would reduce clinical sensitivity by approx 20%-not quite so impressive!

20 In summary Clinical sensitivity in our cohort 47%
Several factors thought to impact clinical sensitivity: Clinical criteria for testing Analysis strategy chosen Results interpretation Introducing new technology (Roche 454) and techniques (MLPA) to ensure comprehensive analysis Hope that future studies will refine clinical criteria and overcome some of the issues with results interpretation

21 Acknowledgements Oxford SCD Team Dr Anneke Seller Karen McGuire
Melanie Proven Omer Mohammed Jessica Thistleton Ria Hipkiss John Taylor Sarah Reid Penny Clouston NHS Department of Clinical Genetics Dr E. Blair

Download ppt "Kate Thomson Molecular Genetics Laboratory, Oxford"

Similar presentations

Ads by Google