Beyond the One Gene-One Disease Paradigm: Complex Genetics and Pleiotropy in Inheritable Cardiac Disorders

Abstract

Inheritable cardiac disorders, which may be associated with cardiomyopathic changes, are often associated with increased risk of sudden death in the young. Early linkage analysis studies in Mendelian forms of these diseases, such as hypertrophic cardiomyopathy and long-QT syndrome, uncovered large-effect genetic variants that contribute to the phenotype. In more recent years, through genotype-phenotype studies and methodological advances in genetics, it has become evident that most inheritable cardiac disorders are not monogenic but, rather, have a complex genetic basis wherein multiple genetic variants contribute (oligogenic or polygenic inheritance). Conversely, studies on genes underlying these disorders uncovered pleiotropic effects, with a single gene affecting multiple and apparently unrelated phenotypes. In this review, we explore these 2 phenomena: on the one hand, the evidence that variants in multiple genes converge to generate one clinical phenotype, and, on the other, the evidence that variants in one gene can lead to apparently unrelated phenotypes. Although multiple conditions are addressed to illustrate these concepts, the experience obtained in the study of long-QT syndrome, Brugada syndrome, and arrhythmogenic cardiomyopathy, and in the study of functions related to SCN5A (the gene coding for the α-subunit of the most abundant sodium channel in the heart) and PKP2 (the gene coding for the desmosomal protein plakophilin-2), as well, is discussed in more detail.

Keywords: Brugada syndrome; genetic pleiotropy; genetics; long QT syndrome; mutation; plakophilins; sodium channels.

Figure 1:

Evolving model of genetic architecture of inherited arrhythmias and cardiomypathies. In the classic monogenic model, a single disease-causing variant is sufficient for phenotypic manifestation. In most families with a disease-causing variant (i.e. mutation-positive), additional common variants with small effect sizes are needed to reach the disease threshold (near-monogenic). In mutation-negative families, the genetic architecture may be more complex, comprising multiple genetic variants with different effect sizes that together determine disease risk (oligogenic/polygenic), in addition to non-genetic factors. (Reprinted with permission from.)

Figure 2:

Phenotypic expression is determined by genetic variation in addition to age, gender and environmental factors. The causal relation between genetic variation and disease could be either direct or through one or multiple endophenotypes.

Figure 3:

Assessing the role of endophenotype-related single nucleotide polymorphisms (SNPs) in disease susceptibility and risk prediction. Large-scale genome-wide association studies (GWAS) identify endophenotype-related SNPs. Polygenic risk scores (PRS) are then calculated for cases and controls by summing the number of alleles weighted by the allele-specific effect size (β) for all endophenotype-related SNPs. The association of PRS with disease not only confirms a role for the endophenotype in question in disease susceptibility, but also contribute to the development of genetic risk predictors.

Figure 4:

Screenshot of a gnomAD database search for the KCNE1 gene. The gnomAD database aggregates and harmonizes exome and genome sequencing data from a variety of large-scale sequencing projects, and provides summary data available for the wider scientific community. As of December 2018, the gnomAD data set comprised sequence data spanning 125,748 exomes and 15,708 genomes from unrelated individuals of different ethnicities that were sequenced as part of various disease-specific and population genetic studies, totalling 141,456 individuals. The low-frequency p.Asp85Asn variant that has been associated with QT-interval and susceptibility to LQTS and drug-induced long QT syndrome, is indicated by the red arrow. Through the browser, one can appreciate aspects such as the tolerance of the gene to different types of variant categories (in the form of an observed / expected (oe) metric), as well as the genomic position, allele count and allele frequency of detected variants. More details at^–.

Figure 5:

Regulatory variants as modifiers. Coding region variants on lower-expressed haplotypes are expected to lead to decreased penetrance whereas coding region variants on higher-expressed haplotypes are expected to increase penetrance (reprinted with permission from Springer Nature: Nature Genetics, reference).

Figure 6:

PKP2 as a pleiotropic gene. Deficiencies in PKP2 have been associated with at least four downstream effects: integrity of gap junctions and hence electrical coupling; function of the sodium channel complex and consequently, sodium current properties; cell adhesion to maintain mechanical integrity, and regulation of transcription which affects both, metabolic/mechanical function, as well as the regulation of intracellular calcium concentration -[Ca²⁺]_i. If disturbed (dotted line) each of the four arms can lead to either an electrical or a structural phenotype. A dysfunction along all four arms would yield the complete arrhythmogenic cardiomyopathy phenotype. But not all arms have to be affected in all cases and as such, a walk downstream of the “sodium channel complex” arm would lead to a BrS-like phenotype; downstream of transcription-[Ca²⁺]_i would yield a phenotype resembling CPVT, whereas a mechanical phenotype of dilated cardiomyopathy would also be possible. As such, a pleiotropic gene can result in one or more of multiple, seemingly unrelated phenotypes. (Reproduced with permission from reference. )

Figure 7:

SCN5A as a pleiotropic gene. As in the case of PKP2 (Figure 6), seemingly unrelated functions related to the expression of the SCN5A gene can, if impaired, cause a clinical phenotype consequent to the balance of endophenotypes that were affected by the mutation, ranging from purely electrical (blue) to structural (red) or a combination of both “Brugada syndrome/arrhythmogenic cardiomyopathy.”