A.A.M. Wilde

The use of genotype-phenotype correlations in mutation analysis for the long QT syndrome

The autosomal dominant form of the congenital long QT syndrome (LQTS or Romano-Ward syndrome) is a disease of disturbance of repolarisation of cardiac myocytes secondary to malfunctioning ion channels, potentially leading to ventricular arrhythmias. The estimated prevalence is 1 in 5000-7000.1 LQTS is diagnosed by analysis of surface electrocardiograms, clinical presentation, and family history.2 Cardiac events in first and second degree relatives of LQTS patients occur in 6-13% of cases.3 Thirty percent of mutation carriers do not have a prolonged QT interval, but are still at risk for complications.4,5 Beta blockers and adjustments in life style are effective in most LQTS patients.6 Up to now, five LQTS genes (and one locus on chromosome 4) have been identified: KCNH2 , KCNQ1 , SCN5A , KCNE1 , and KCNE2 on chromosomes 7, 11, 3, 21, and 21, respectively. At present, the genotype has been identified in 50-70% of patients. Most patients have a private (missense) mutation in KCNH2 or KCNQ1 .7 Diagnostic screening of all five LQTS associated genes at once potentially leads to relatively fast mutation detection but is very labour intensive and costly. Sequential mutational analysis, starting with the gene that accounts for the largest percentage of mutations based on published gene prevalences ( KCNH2 , 45%), has the same disadvantages, albeit to a lesser extent.7 In most patients, a mutation will not be detected at the first attempt, so in most cases at least two genes have to be screened to detect the disease causing mutation. This is a major drawback for diagnosis of mutations in LQTS.8–10 Nevertheless, several commercial diagnostic services exist.11 Distinct genotype-phenotype correlations have been reported in LQTS. Age of onset, symptom related triggers, the ST-T segment morphology of the ECG, and the response to drugs …

Family and population strategies for screening and counselling of inherited cardiac arrhythmias

Family screening in inherited cardiac arrhythmias has been performed in The Netherlands since 1996, when diagnostic DNA testing in long QT syndrome (LQTS) and hypertrophic cardiomyopathy (HCM) became technically possible. In multidisciplinary outpatient academic clinics, an adjusted protocol for genetic counselling, originally derived from predictive testing in Huntingtons disease, is being used. 1110 Individuals, including 842 relatives of index patients, were informed about their risks, and most were tested molecularly and/or clinically for carriership of the disease present in their family. Of 345 relatives who were referred for cardiologic follow‐up, 189 are being treated, because of an increased risk of life‐threatening arrhythmias. Evaluation of the psychological and social consequences of family screening for inherited arrhythmias can be performed by using the adapted criteria of Wilson and Jüngner, i.e., from a point of view of public health. Preliminary results of psychological research show that parents of children at risk for LQTS show high levels of distress. Many other aspects have to be evaluated yet, making final conclusions about the feasibility of family screening difficult, particularly in HCM. Clinical guidelines are urgently needed. Population screening by molecular testing, for instance in athletic preparticipation screening, will become possible in the future and has its own prerequisites for success.

Founder mutations in hypertrophic cardiomyopathy patients in the Netherlands

In this part of a series on cardiogenetic founder mutations in the Netherlands, we review the Dutch founder mutations in hypertrophic cardiomyopathy (HCM) patients. HCM is a common autosomal dominant genetic disease affecting at least one in 500 persons in the general population. Worldwide, most mutations in HCM patients are identified in genes encoding sarcomeric proteins, mainly in the myosin-binding protein C gene (MYBPC3, OMIM #600958) and the beta myosin heavy chain gene (MYH7, OMIM #160760). In the Netherlands, the great majority of mutations occur in the MYBPC3, involving mainly three Dutch founder mutations in the MYBPC3 gene, the c.2373_2374insG, the c.2864_2865delCT and the c.2827C>T mutation. In this review, we describe the genetics of HCM, the genotype-phenotype relation of Dutch founder MYBPC3 gene mutations, the prevalence and the geographic distribution of the Dutch founder mutations, and the consequences for genetic counselling and testing. (Neth Heart J 2010;18:248-54.)

High Distress in Parents Whose Children Undergo Predictive Testing for Long QT Syndrome

Objectives: To assess the psychological effect of predictive testing in parents of children at risk for long QT syndrome (LQTS) in a prospective study.Methods: After their child was clinically screened by electrocardiography and blood was taken for DNA analysis, and shortly after delivery of the DNA test result, 36 parents completed measures of psychological distress. Results: 24 parents were informed that at least one of their children is a mutation carrier. Up to 50% of the parents of carrier children showed clinically relevant high levels of distress. Parents who were familiar with the disease for a longer time, who had more experiences with the disease in their family and who received positive test results for all their children were most distressed. Conclusions: Predictive ECG testing together with DNA testing has a profound impact on parents whose minors undergo predictive testing for LQTS.

Fever-triggered ventricular arrhythmias in Brugada syndrome and type 2 long-Qt syndrome

The risk for lethal ventricular arrhythmias is increased in individuals who carry mutations in genes that encode cardiac ion channels. Loss-of-function mutations in SCN5A, the gene encoding the cardiac sodium channel, are linked to Brugada syndrome (BrS). Arrhythmias in BrS are often preceded by coved-type ST-segment elevation in the right-precordial leads V1 and V2. Loss-of-function mutations in KCNH2, the gene encoding the cardiac ion channel that is responsible for the rapidly activating delayed rectifying potassium current, are linked to long-QT syndrome type 2 (LQT-2). LQT-2 is characterised by delayed cardiac repolarisation and rate-corrected QT interval (QTc) prolongation. Here, we report that the risk for ventricular arrhythmias in BrS and LQT-2 is further increased during fever. Moreover, we demonstrate that fever may aggravate coved-type ST-segment elevation in BrS, and cause QTc lengthening in LQT-2. Finally, we describe molecular mechanisms that may underlie the proarrhythmic effects of fever in BrS and LQT-2. (Neth Heart J 2010;18:165-9.)

Preferences of cardiologists and clinical geneticists for the future organization of genetic care in hypertrophic cardiomyopathy: A survey

In view of the increasing demands for genetic counselling and DNA diagnostics in cardiogenetics, the roles of cardiologists and clinical geneticists in the delivery of care need to be redefined. We investigated the preferences of both groups of professionals with regard to the future allocation of six cardiogenetic responsibilities in counselling and testing, using hypertrophic cardiomyopathy (HCM) as a prevalent model disease. In this cross‐sectional survey, the participants were Dutch cardiologists (n = 643) and clinical geneticists (n = 60), all members of professional societies. Response rates were 33 and 82%, respectively. In both groups, the majority preferred to perform most of the tasks described above in collaboration. Informing HCM patients about the genetics of HCM and requesting DNA testing in symptomatic patients was viewed by 43 and 35% of cardiologists, respectively, as their sole responsibility, however, and 39 and 59% of clinical geneticists did not object to these views. Both groups felt that the task of discussing the consequences of HCM for offspring and that of discussing the results of DNA diagnostics should be shared or performed by clinical geneticists. Both groups considered co‐ordination of family screening the sole responsibility of clinical geneticists. Opinions on who should request DNA diagnostics in asymptomatic relatives were divided: 86% of clinical geneticists considered it their exclusive responsibility, 10% of cardiologists believed that this task could be performed individually by either group and 30% preferred to collaborate. Most professionals said that they would appreciate education programmes and clinical guidelines. Both cardiologists and clinical geneticists prefer to share rather than divide most cardiogenetic responsibilities in caring for HCM patients. Consequently, capacity problems in both groups are to be expected. To safeguard current professional standards in genetic counselling and testing, deployment of non‐medical personnel might be essential.

Towards a better risk stratification for sudden cardiac death in patients with structural heart disease.

With the introduction of the implantable cardioverter defibrillator (ICD), patients can be protected against sudden cardiac death (SCD) due to ventricular arrhythmia (VA). Guidelines have been drawn up for selecting patients for primary and secondary prophylaxis. However, most ICD recipients today who receive an ICD for primary prevention will not experience a life-threatening VA requiring antitachypacing or shock therapy. Better risk stratification is desirable with efficacy, costs and complication rate in mind. An overview is presented of widely accepted and potentially valuable risk markers and the role they may play in better identifying candidates for ICD therapy. (Neth Heart J 2009;17:101–6.)

Diversity in cardiac sodium channel disease phenotype in transgenic mice carrying a single SCN5A mutation.

Lethal ventricular arrhythmias are increasingly considered an important cause of sudden death in relatively young individuals. A genetic predisposition has been recognised in many cases, and research in the last decade has focused on underlying inherited mutations in cardiac ion channels.

First experience with the wearable cardioverter defibrillator in the Netherlands

The implantable cardioverter defibrillator (ICD) has significantly improved survival in patients with an increased risk of sudden cardiac death (SCD). The wearable cardioverter defibrillator (WCD) is an alternative to the ICD in patients with a transient ICD indication or those in whom an ICD temporarily cannot be implanted. We describe here the technical details of the WCD and report three patients who were treated with a WCD in an outpatient setting. The WCD allowed the cardiac condition of two patients to improve to such an extent that permanent ICD implantation was deemed unnecessary. This new form of therapy may result in significant cost reduction, avoidance of unnecessary ICD implantation, and increased patient satisfaction.

One more time: bibliometric analysis of scientific output remains complicated

Dear Sir, In the May issue of the Netherlands Heart Journal, we published an update [1] of a previous bibliometric analysis of the scientific work of Dutch professors in clinical cardiology [2]. The paper was accompanied by an editorial [3] in the same issue and another one in the subsequent June issue [4]. Van der Wall [3] summarises our paper and emphasises that we have stated ‘….that citation analysis should always be applied with great care in science policy.’ We indeed concluded that given the inhomogeneity in citation characteristics of the scientific output of an -at first sight- homogeneous group of clinical cardiologists, such analyses lack sufficient validation for application in a more complex network as a university medical centre. In his 2005 paper [5], Hirsch indeed proposed his well-known h-index for quality assessment of scientific output. At that time he emphasised that Nobel prize winners had h-indices of 30 and higher. In addition he mentioned that a h-index of 18 might be reasonable as an equivalent for a full-professorship, whereas a h-index of 10–12 might be reasonable to obtain ‘tenure’. It is important to underscore that Hirsch’s statements were restricted to the arena of physics, where h-indices are much lower than in the life sciences, as pointed out previously by us [2] and others [6]. Professor Doevendans’ contribution [4] focuses on the competitive aspects of science in relation with its financial system rather than on our paper [1]. We fully agree with Doevendans that the credibility of a funding system is very important. A system primarily based on grants heavily leans on the integrity of committees and individuals deciding on the fate of research proposals. With respect to this the literature is not very reassuring to put it mildly [7–9]. There is a trend towards decision-making at an early stage (within academic medical centres; i.e. before actual submission) and to decision-making without peer review after submission. Despite the understandable efforts to save time and energy both on the part of applicants and those in control of the system, we share the concerns of Professor Doevendans [4]. Therefore we can imagine that bibliometric analysis can be perceived as part of an armamentarium in a tombola with unequal chances and is therefore received with distrust. Having said that, we must take away from three of Doevendans’ suggestions. 1) Authors with an uncommon name had a disadvantage of up to 20%, whereas data of authors with ‘a more common name’ were polluted. It is suggested that we allocated citations or papers to professors that they did not receive, respectively write. In case of doubt, our data were checked on a per author/per paper base. Therefore our data stand! However, in general, Professor Doevendans is correct in emphasising that when an assessment is made by organisations/institutions that do not know the individuals/work under assessment, there is an increased risk for errors. This implies that an adversary approach is always wise. But again, this is not the case in our study. 2) Doevendans’ claim that the use of alternative databases as Scopus (or e.g. Google Scholar) instead of Thomson Reuters’ Web of Science (WoS) would lead to different rankings is not substantiated with data. However, it would certainly be interesting to see the effect on rankings. Some databases index more journals than others and with different time lags as well. To us it seems improbable that individuals in any top-10 based on the Thomson Reuters’ database would not score high in the other databases as well. But the onus to show this is not on us, but on those who criticise our study. 3) Doevendans states that ‘although the paper is accepted by a scientific journal, the reproducibility of the data has not been established.’ This is simply not true because a second count of several authors, using the same database (i.e. WoS), revealed identical results. Within one and the same database, the data are reproducible. It is a pity that Professor Doevendans focuses on differences between the databases without an effort to either measure or explain these. In addition, there is some juggling with the concept of ‘reproducibility’. This tends to obscure the quintessence of our paper: large differences in citations and also in h-indices occur within a relatively homogeneous group of clinical cardiologists. These differences cannot be interpreted as differences in scientific quality, because we have shown that there are large differences in citation frequency, e.g. between ‘sub-sub-fields’ as ‘Marfan syndrome’ and ‘Brugada syndrome’, but also between ‘subfields’ as ‘congenital heart disease’ and ‘arrhythmias’, just to mention a few. Thus, this type of citation analysis at the personal level should be discouraged, because it can damage the scientific status of individuals. It goes without saying that this advice is even more urgent when it comes to comparison of different specialisations within university medical centres, where these are meant to corroborate each other. We finish by summarising three important parameters that determine the total of citations of a scientist. First is the network. How many co-authors (and grants…) were involved? Second is the ‘citation culture’. In medicine, papers have many more references than in mathematics or computer science. We would not want to see a mathematics faculty closed down because the h-indices of its scientists are considered too low (compared with the medicine faculty). Third is the number of scientists publishing in a field. If an author publishes a paper and there are 10 other scientists active and publishing in the same field, whose papers all cite the work, the author under assessment obtains ‘only’ 10 citations, despite the fact that 100% of the citing authors have cited the work. If there are 100 other scientists of which 50 cite the work, the author under assessment obtains 50 citations (five times as many) although ‘only’ 50% of the citing authors have cited the work. These three issues, in particular the last one, have thus far not been fully addressed in the specialised literature in such a way that consensus resulted. There is an additional concern. When an identical paper is simultaneously published in two or more journals, the citations obtained are not identical, but strongly correlated with the impact factor of the publishing journal [10]. The difference can be substantial. How then can citations be taken as a parameter of scientific quality? For all these reasons we concluded that ‘citation analysis should be applied with great care in science policy’. And not because our data are incorrect or not reproducible.