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A great deal of progress has recently been made in the discovery and understanding of the genetics of familial dilated cardiomyopathy (FDC). A consensus has emerged that with a new diagnosis of idiopathic dilated cardiomyopathy (IDC), the clinical screening of 1st degree family members will reveal FDC in at least 20-35% of cases. Point mutations in 31 autosomal and 2 X-linked genes representing diverse gene ontogeny have been implicated in causing FDC, but account for only 30-35% of genetic cause. Next generation sequencing (NGS) methods have dramatically decreased sequencing costs, making clinical genetic testing feasible for extensive panels of DCM genes. NGS also provides opportunities to discover additional genetic cause of FDC and IDC. Guidelines for evaluation and testing of FDC and IDC are now available, and when combined with FDC genetic testing and counseling will bring FDC/IDC genetics to the forefront of cardiovascular genetic medicine.
Since our 2005 review of familial dilated cardiomyopathy (FDC) genetics in this Journal (1), a great deal of additional progress has been made. We note other valuable dilated cardiomyopathy (DCM) reviews, consensus documents and guidelines since 2005 (2-17). We review key concepts of genetic research and provide recent updates in FDC genetics. We also note the dramatic innovation in sequencing technologies that are revolutionizing clinical and research genetic studies. Much of this is broadly applicable to all of cardiovascular genetics.
In our prior review (1) we cited 19 DCM phenotype studies published between 1981 and 2003, principally focused on estimating the fraction of those patients with idiopathic dilated cardiomyopathy (IDC) who were found to have FDC using family history (FH) or clinical screening of family members. FDC is defined most conservatively as DCM meeting criteria for IDC in at least two closely related family members (1). Large retrospective studies in the 1980's estimated that 2-10% of individuals with IDC had FDC. In the 1990's studies involving larger cohorts of patients with IDC and prospective cardiovascular screening in their close relatives estimated that 20-48% of individuals with IDC could be shown to have FDC (18-20). A consensus has emerged that FDC will be found in at least 20-35% of those with IDC with clinical screening of first-degree family members, where clinical screening includes ECG and echocardiography or some other measure of LV size and function. Notably, a family history without clinical screening is much less sensitive to detect FDC (18).
In 2005 we listed 19 genes shown to cause nonsyndromic DCM in humans (1). We now list 33 genes, 31 autosomal and 2 X-linked (Table 1) associated with DCM covering significant gene ontogeny (Table 2). Notably, the frequencies of DCM mutations in any one gene are low (<<1% to 6-8%), and a genetic cause is identified in only 30-35% of familial DCM cases (Table 1). In contrast, in HCM genetic cause can be found in 50-75% of familial cases, and in those cases when a mutation is identified, >80% can be found in one of two genes (MYH7, MYBPC3) (13). By inference from HCM (and LQTS, ARVD/C (13, 16)), FDC genetics are inherently more complex.
The number of DCM genes will continue to increase with ongoing discovery efforts. Also ‘crossover’ DCM phenotypes of desmosomal genes usually associated with ARVD/C present as DCM with low frequency (84); DCM phenotypes have also been observed for genes principally observed in HCM or the long QT syndrome, as previously reviewed (12, 13). We and others have recently shown that rare variant genetics are at play in some cases of peripartum cardiomyopathy (85-87).
The core approach to human genetic studies remains the same: the careful and comprehensive phenotyping of subjects and their family members, and then correlating those phenotypes with genetic information. The challenge of this approach is to assure oneself that the genetic variation identified is causative of the phenotype of interest.
The term ‘mutation’ is most commonly applied in Mendelian disease to one or a short string of variants in coding DNA (Table 3). The most common are missense mutations, but less common types include nonsense, splice site, and short insertion or deletion mutations (Table 3). Synonymous variants do not change the amino acid of that codon, while nonsynonymous variants do change the amino acid of that codon.
Ascertaining whether any one specific variant is causing the phenotype of interest requires weighing several types of evidence, and achieving a high level of certainty for any one variant is challenging, especially if that variant is novel (1, 88-90) (Table 3). In most cases, the sum of all of the evidence is required to decide if the identified variants are relevant (Table 3). As noted below, with next generation sequencing (NGS) approaches, the unique genetic variants identified in an individual affected with a specific phenotype can be many – hundreds to thousands – creating new challenges.
The term ‘Mendelian disease’ has been applied to heritable genetic disease, usually familial, with identifiable inheritance patterns (dominant or recessive, and autosomal, X-linked or mitochondrial) (1). Many Mendelian diseases are uncommon to rare, with population frequencies well below 1%. For Mendelian disease demonstrating autosomal dominant inheritance (which is the case in most FDC families) (1), the most powerful evidence that a putative mutation is indeed disease-causing is segregation of the variant of interest with the disease phenotype in at least one large, multigenerational family with multiple affected individuals who carry the variant and multiple unaffected individuals who do not carry the variant (Table 3). Multiple large families available to assess segregation increases the strength of evidence. While this concept is superficially simple, certain features of adult-onset Mendelian disease commonly observed with FDC complicates this approach.
One feature is incomplete penetrance, which refers to individuals who carry a mutation but do not manifest any evidence of the disease phenotype. Thus, in gene discovery studies, the absence of a DCM phenotype in someone carrying a putative disease-causing variant can never be considered absolute evidence that the variant is not relevant: the individual in question may simply be manifesting incomplete penetrance. A key corollary for clinicians caring for at-risk family members is that a negative clinical cardiovascular evaluation at any age does not rule out the possibility that the family member may develop later disease. This provides the rationale for the periodic rescreening of at-risk family members who have normal evaluations.
A related concept, ‘age-dependent’ or ‘age-related’ penetrance, is also observed with FDC, where a disease-causing mutation usually manifests a disease phenotype only in the adult years, most commonly in the 4th to 6th decades or later.
Another feature that complicates FDC assessment is variable expressivity, which means that only some aspects of the DCM phenotype are present. For example, only mild left ventricular enlargement (LVE) without systolic dysfunction, or the onset of arrhythmia or conduction system disease with only borderline DCM may be observed. Also, age of onset can vary significantly, with variable severity of disease progression. Thus, within a large FDC family a wide range of clinical findings may be present without fully developed DCM. Reliance on endophenotypes (partial or sub-phenotypes) as an indication of genetic DCM/FDC also has been problematic, in part because subtle clinical changes may result from other more common causes of CV disease, making it difficult to decipher genetic from non-genetic cause.
While usually nonsyndromic, DCM can be included in syndromic disease involving various organ systems, but most commonly skeletal muscle disease (muscular dystrophy) (12).
Other criteria to assign causality (Table 3), in addition to segregation of the variant with the phenotype, include its relative rarity in control DNAs (commonly <<1%). The rationale for this is that if it were common in the population, it would be unlikely to cause a rare genetic disease. Nevertheless, how rare is rare (<0.01, <0.005, < 0.001, <0.0001)? Some analyses have suggested that the majority of rare alleles (0.001 – 0.003) may be injurious (91). The caveat with control DNAs is that they should be representative of the race and/or ethnicity of the DCM family, as variants observed to be common (>1%) in one population can be rare in a different population.
Conservation of the amino acid or nucleotide (i.e., lack of variation in the protein structure or specific nucleotide sequence (92, 93) of lower species) is also used to assess variants, with the rationale that an amino acid or a nucleotide position with greater variation in lower species may have increased tolerance to variants at that position and are therefore less likely to be disease-causing. Other features are also relevant (Table 3).
Much of this, vital for discovery efforts, is also relevant for FDC clinical genetics. These fundamental principles of human genetics investigations have not changed, but with NGS the quantity of data to which they are applied has changed dramatically.
Text limitations do not permit a reiteration of the components and importance of skilled genetic counseling, especially for difficult, confusing or syndromic cases, supported by geneticist consultations as needed (1). Unlike most cardiologists, genetic counselors are trained to deal with the family as a unit of inquiry rather than the individual patient, an essential quality for genetic medicine. Genetic counselors are also trained to emphasize disease prevention in contrast to the focus on disease treatment taken by most cardiovascular specialists. Both of these qualities are particularly relevant for facilitating genetic risk assessment. The availability of genetic counselors with cardiovascular training or experience can provide the support needed to initiate the practice of cardiovascular genetic medicine. We refer the reader to several citations that deal with these important points (1, 12, 15, 16, 94-96).
The most significant change is the dramatic improvement in efficiency and speed of gene sequencing methods. Next generation sequencing (NGS) is the term used to describe several diverse methods that improve sequencing throughput by several magnitudes, resulting in markedly reduced sequencing costs per nucleotide. This has led recently to sequencing the human exome routinely for research applications (97-99). The exome is defined as the protein coding portion (the exons) of the 18,000 – 19,000 genes, estimated at 1-2% of the human genome. NGS is also used to sequence the entire human genome (coding and non-coding regions of DNA), referred to as whole genome sequencing (WGS) (100). Because Mendelian disease typically affects the protein coding portions of the genome, exome sequencing is particularly relevant for rare variant Mendelian disease. As of 2010, typical costs of exome sequencing for research purposes are approximately $2000 per DNA sample. New instruments and new methods for multiplexing DNAs on NGS instruments are being developed that will improve throughput and decrease cost, making <$1000, or even <$500 exome sequences likely in the near future. WGS charges on the open market now range from $10,000 to $20,000; these costs are also expected to decrease dramatically (10- to 20-fold) in the next few years, which will bring even WGS into the realm of clinical genetic testing, as well as within the domain of the NIH research budgets of many cardiovascular genetics studies. NGS, whether for exome or WGS, is dramatically transforming the experimental possibilities – study designs unthinkable even 1-2 years ago can now be proposed and attained (97-99).
Along with this rapidly expanding universe of opportunity from NGS will come monstrous quantities of human DNA sequence data, challenging the hardware and software of informatics platforms, and necessitating novel approaches to data assembly, storage and analysis. Computational budgets for even modest exome projects now (terabytes of data) cost tens of thousands of dollars; larger projects containing hundreds to thousands of terabytes of data will require more robust outlays. These realities will require new ‘pipelines’ to be developed to efficiently analyze these massive data sets and reduce the cost of storage. This will also require new control DNA data sets to be generated, some of which is now underway (101).
NGS is directly related to the emergence of clinical genetic testing for FDC. As recently as 2-3 years ago, clinical genetic testing costing thousands of dollars was available only for a few HCM genes. Now panels of dozens of genes at reduced cost, incorporating many or all reported for any of the genetic cardiomyopathies (DCM, HCM, RCM, ARVD/C, and LVNC), are rapidly emerging using NGS methods. While this increase in data comes with a host of limitations and complications in interpretation, FDC testing sensitivity (the probability of finding a genetic cause with the genetic testing) now ranges from 15-25%, making pre-symptomatic testing feasible. Testing laboratories for DCM genes are catalogued at GeneTests (102), an online service hosted by NCBI.
After many years of effort, a new federal law using the eponym of GINA now protects individuals from genetic discrimination in health care or employment. Further information is available at the National Genome Research Institute website (103).
Despite the evidence supporting a genetic basis of IDC/FDC, the implementation of guidelines (13) by practitioners has been tepid. Adherence to such guidelines will require a shift in focus from strictly therapeutic measures for a single patient presenting with advanced disease to the consideration and assessment of DCM risk for an entire family (1, 13, 16) (Figure 1).
The rationale for these recommendations is that most IDC/DCM presents late in its causal pathway (advanced disease, usually with heart failure or sudden cardiac death), but early detection of asymptomatic DCM through screening enables presymptomatic intervention that may prevent or ameliorate the progression to advanced disease (95).
With a new IDC diagnosis, genetic risk evaluation should be initiated, including taking a 3-4 generation family history and recommending that 1st degree family members undergo clinical cardiovascular screening (Figure 1). Clinical genetic testing may also be warranted, including the competent interpretation of genetic results with appropriate counseling (1, 16). All of this may require a referral of patients to centers providing expertise in cardiovascular genetics and guidance on implementation of gene and/or mutation-specific therapies if indicated (13), ideally in centers with geneticists or genetic counselors working in collaboration with cardiologists in cardiovascular genetic medicine clinics (95).
Even though rare variants have been identified in >30 genes, we estimate that this accounts for only one-third of genetic cause of FDC. We predict this number will expand significantly. Discovery of additional genetic cause of DCM is still key to further understanding DCM genetics.
We have only scratched the surface in understanding DCM genetics. We have almost no insight into the causes of the marked variation in age of onset, disease penetrance, or clinical severity observed even for the same mutation within a large extended family, or between families with the same variant. Gene-enviroment interactions may explain some of this, but additional genetic variation may also explain a portion of this variability. Most of the FDC genetic data thus far supports a ‘one gene’ Mendelian model with marked locus (many genes) and marked allelic heterogeneity (many private mutations within any one gene). The impact of multiple mutations in the same individual has been recognized for HCM (104-109) and the long QT syndrome (108, 110), where two or more mutations have been shown to be associated with earlier onset and more severe disease in 3-7% of subjects. However, considerable additional genetic variation may be at play. Such genetic variation could include ‘less common’ common variants (e.g., allele frequencies 0.5 – 5%), additional rare variants (including the bi-allelic models as shown in HCM and ARVD/C (111, 112)), epigenetic factors, gene promoter site variants, or alterations in other genetically-driven regulatory processes such as microRNAs or their target sites. All of these remain to be evaluated for genetic DCM.
A related issue involves the genetics of IDC, or DCM after all known causes (except genetic) have been ruled out, and its relationship to FDC. This is important because understanding the genetic basis of IDC could have a major public health impact, as non-ischemic DCM makes up a significant proportion of all forms of cardiomyopathy, and IDC is by far the largest component of nonischemic DCM. Here we differentiate a ‘true’ IDC as a patient with IDC who has had their first-degree family members clinically screened (history, exam, echocardiogram, ECG) to rule out FDC versus a ‘presumptive’ IDC – one who is negative for familial disease by a careful 3-4 generation family history but has not had family members screened beyond the FH. Preliminary data from our resequencing studies suggested that the frequency of possibly or likely disease-causing rare variants in a cohort of FDC and IDC probands (>300 in total) was similar (39, 113). However, in those studies the family members of the IDC probands were not systematically screened beyond FH, making it difficult to accurately assess the familial nature of disease in the ‘apparently sporadic’ IDC portion of our cohort. Therefore, whether ‘true’ sporadic IDC differs from FDC in gene composition, penetrance or expressivity remains untested in a large prospective study,
Recent progress for DCM genetics has been significant, although much remains to be learned. Clinical genetic testing is rapidly emerging, and NGS technology now permits patients to undergo clinical genetic testing for many genes at reduced cost. However, enthusiasm for DCM genetic testing remains tempered in 2011 in large part due to the testing sensitivity of 15-25%, and the plethora of DCM genes that makes the rare variants ‘established as disease-causing’ in any one gene only a very few. The discovery of new DCM genes and other DCM genetic cause, accelerated now by exome sequencing and soon by WGS, will lead to knowledge of the remainder of the genetic makeup of FDC and IDC. The careful and systematic phenotyping of DCM probands and family members, whether sporadic or familial, when combined with the cataloging of many DCM rare variants, will enable DCM genetics to move into the mainstream of cardiovascular genetic medicine.
This work was supported by NIH award RO1-HL58626 (Dr. Hershberger).
No relationships with industry of any kind are present.
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