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Subtle killers and sudden death: Genetic variants modulating ventricular fibrillation in
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Pazoki, R.
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Pazoki, R. (2015). Subtle killers and sudden death: Genetic variants modulating ventricular fibrillation in the
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Download date: 18 Jun 2017
Chapter
3
Complex inheritance for susceptibility
to sudden cardiac death
Curr Pharm Des. 2013;19(39):6864-72.
Raha Pazoki, Michael W.T. Tanck, Arthur A.M. Wilde, Connie R. Bezzina
34 Chapter 3
Abstract
Sudden cardiac death (SCD) from ventricular fibrillation during myocardial infarction
is a leading cause of total and cardiovascular mortality. It has a multifactorial, complex
nature and aggregates in families, implicating the involvement of heritable factors in
the determination of risk. During the last few years, genome-wide association studies
have uncovered common genetic variants modulating risk of SCD. We here review
the current insight on genetic determinants of SCD in the community and describe
the genome-wide association approaches undertaken thus far in uncovering genetic
determinants of SCD risk.
Complex inheritance for susceptibility to sudden cardiac death
35
Sudden death (SD) is defined as natural, unexpected death within an hour of the
onset of symptoms and can be due to cardiac or non-cardiac causes (e.g. stroke or
aneurysm) 1. The annual incidence of SD in the general population (20-75 years of
age) is 1 per 1000 individuals, accounting for 18.5% of total mortality 1,2. SD is a rare
event in young individuals 3,4; the incidence is 1.3-8.5 per 100,000 individuals younger
than 40 years of age 1,3. The major proportion of SD is considered to be sudden cardiac
death (SCD).
In Europe and North America, SCD accounts for 50-100 deaths each year per
100,000 individuals in the general population 5,6. The incidence of SCD is 1 in 100,000
individuals in the young population (age < 35-40) and 1 in 1,000 in the older segment
(age > 35-40) of the population 6. Overall mortality of patients with sudden cardiac arrest, even in regions of the world with an advanced first responder system and resuscitation methodology, is more than 95% 6,7 Survival to hospital discharge for those cases
who present with witnessed ventricular fibrillation (VF) or ventricular tachycardia
(VT) is around 29% 8.
SCD accounts for a major proportion of all cardiovascular deaths (up to 50%) 9.
In fact, SCD is the fatal manifestation of a group of cardiac arrhythmias including
VT, VF or severe bradyarrhythmia 7. The most common electrophysiological disorder
underlying SCD is VF (Figure 1), which subsequently and ultimately degenerates to
asystole 10. Ventricular arrhythmia present with various symptoms including palpitations, chest pain, or syncope and can lead to SCD within a few minutes 7. The underlying cardiac disorder is often not diagnosed before the event and in 40-50% of all SCD
cases no symptoms precede the death 7,8,11.
SCD may occur in a broad range of pathological settings such as coronary artery
disease (CAD), cardiomyopathy, congenital heart disease, inflammatory myocardial
Figure 1 | Three lead ECG (II, I and III) displaying acute ischemia-related VF. The patient concerned
Figure 1 | Three-lead ECG (II, I and III) displaying acute ischemia-related VF. The patient conhas an acute inferior wall MI (ST elevation in leads II and III). An R-on-T extrasystole in the third ST-T
cerned has
anrise
acute
inferior wall
segment
gives
to immediate
VF.MI (ST elevation in leads II and III). An R-on-T extrasystole in the
third ST-T segment gives rise to immediate VF.
SCD may occur in a broad range of pathological settings such as coronary artery disease
(CAD), cardiomyopathy, congenital heart disease, inflammatory myocardial disease, or
even, sudden unexplained death, in the structurally normal heart. However, the
Chapter 3
Introduction
3
36 Chapter 3
• LVEF <30–35%
• LVH
• Aortic stenosis
Non-modifiable
factors
Modifiable
factors
• HTN
• Diabetes
• Prolonged QT interval
SCD
• Structural disorders of the
heart (HCM, ARVC, etc.)
• Primary electrical disorders
(LQTs,BrS, SSS, etc.)
Mendelian
Inheritance
Complex
Inheritance
• CVD/CAD/ MI
• Family history of SCD
Figure 2 | Predisposing factors to sudden cardiac death. SCD, sudden cardiac death; LVH, left
ventricular hypertrophy; LVEF, left ventricular ejection fraction; HTN, hypertension; HCM, hyperthrophic cardiomyopathy; ARVC, arrhythmogenic right ventricular cardiomyopathy; LQTS, long QT
syndrome; BrS, Brugada syndrome; SSS, sick sinus syndrome; CVD, cardiovascular diseases; CAD,
coronary artery disease; MI, myocardial infarction.
disease, or even, sudden unexplained death, in the structurally normal heart. However, the overwhelming majority (~80%) 11 of SCDs occur in older individuals and are
largely caused by sequela of CAD, namely in the setting of acute or previous myocardial ischemia / infarction and heart failure 12. Acute myocardial infarction (MI) is the
most important source for ventricular arrhythmias 13 including VF, VT, and ventricular
premature depolarization.
Several factors have been mentioned to be associated with SCD in the setting of
CAD (Figure 2). These factors include left ventricular ejection fraction (LVEF), left
ventricular hypertrophy, prolonged QTc interval, Diabetes, and hypertension 7. Up
until now, LVEF is the only factor that is used for risk stratification of SCD. Patients
with LVEF of less than 30–35% are considered to be at high risk for SCD and eligible for
prophylactic implantation of a cardiac defibrillator 7,14.
Mechanism of arrhythmia in the setting of acute myocardial ischemia
In animal models, ventricular arrhythmias mainly occur during the first 30 minutes
of the experimental ischemia and in two distinct periods 13. The early phase (phase
1a) occurs from 2 to 10 minutes after the coronary occlusion and the delayed phase
(phase 1b) occurs between the minutes 12 and 30. There is no information whether
this bimodal distribution of ischemia-induced arrhythmias during the first 30 min-
utes of occlusion also occurs in human, but it is considered likely to be with a retarded
time course. It has been proposed that during phase 1a, two different mechanisms
are involved in development of arrhythmias. A reentrant excitation causes VF and
VT while a non-reentrant mechanism causes premature ventricular depolarizations
which subsequently lead to generation of reentry 13.
Different factors influence the induction of arrhythmias during the acute phase
of myocardial ischemia. One such factor is the current flow across the ischemic and
normal myocardial tissue (i.e. the ‘injury current’). The membrane potential is different for ischemic myocardium (less negative) compared with the normal cells. This
intercellular electrical imbalance causes current to flow between the depolarized and
polarized muscle fibers and induce abnormal activity 13.
Another important factor which facilitates VF during acute regional ischemia is
the cardiac subendocardial Purkinje fibers 15. During the early phase of acute myocardial ischemia, the electrophysiological properties of the cardiac Purkinje fibers are
changed 13. In patients with MI and rapid polymorphic ventricular tachycardia, premature depolarizations and arrhythmias could be suppressed by ablation of Purkinje
regions 16. It is suggested that early or delayed afterdepolarizations, sub threshold depolarizations caused by injury currents and the stretch caused by loss of contractility
and systolic bulging of the ischemic myocardium could initiate reentry in the Purkinje
network 13. During acute myocardial ischemia, the mechanical stretch due to left ventricular malfunction reduces the maximal diastolic potential of the Purkinje fibers and
therefore, abnormal activity is induced or accelerated. Stretch can additionally trigger
early or delayed afterdepolarizations. The ischemia and injury in the anterior wall
seems to play a more prominent role than in the inferior wall in producing stretch and
initiation of arrhythmias. Ischemia in the anterior wall causes a greater excursion than
ischemia in the inferior wall and thus produces more stretch in the fibers neighboring
the ischemic border 13.
Heart rate is another important parameter for arrhythmia induction during the
acute phase of MI. Changes in heart rate precede the onset of arrhythmia and patients
with increased heart rate tend to have higher risk to develop VF during myocardial
ischemia. Sequentially, increased heart rate gives rise to severity of ischemic damage
and the size of ischemic area 13.
Lastly, reperfusion of blood into the ischemic area can trigger the so called reperfusion arrhythmias. The likelihood for reperfusion arrhythmias increases from 5 to 30
minutes after the occlusion in animal models and decreases after 30 minutes. This is
due to the fact that arrhythmias must occur in viable cells. During a sudden reperfusion, a very rapid restoration of action potentials occurs in the ischemic myocardium.
Electrolytes and metabolites wash out of the ischemic area and change electrophysiological properties of the normal cells close to the ischemic area. This remarkable
37
Chapter 3
Complex inheritance for susceptibility to sudden cardiac death
38 Chapter 3
inhomogeneity in the ischemic myocardium and the border increases the likelihood
of reentry and subsequent fibrillation 13.
Genetic susceptibility to sudden cardiac death
A strong Mendelian hereditary component determines risk of SCD in young individuals 17,18. The genetic underpinnings of the Mendelian disorders associated with
increased risk of SCD have been brought into focus during the last two decades
leading to an enormous impact on patient care. This Mendelian form of SCD can be
caused by underlying electrical (primary electrical disorders) or structural (cardiomyopathies) disturbances (Figure 2). The primary electrical disorders (including
long QT syndrome, Brugada syndrome and sick sinus syndrome) are often associated
with characteristic abnormal features on the electrocardiogram (ECG). Arrhythmias
in these disorders are caused by abnormal intrinsic cardiac electrophysiological
properties mainly due to mutations in genes encoding ion channel subunits 19. The
most common of these disorders is probably the Long QT Syndrome associated with
prolonged cardiomyocyte repolarization. Mutations in a total of 13 genes have so far
been linked to this disorder. The genetic underpinnings of the Brugada syndrome on
the other hand remain largely unknown. Mutations in the SCN5A gene account for
about 20% of probands and while other genes have been implicated in the disorder,
between them they account for less than 5% of cases 20. Structural alteration of the
myocardium forms the substrate for arrhythmia in the cardiomyopathies, the most
common of which is hypertrophic cardiomyopathy, in most cases caused by mutations in MYH7 gene, encoding the β-myosin heavy chain, and in MYBPC3 gene, encoding cardiac myosin-binding protein C (cMyBP‑C) 21. Another rare cardiomyopathy
associated with SCD in the young and in athletes is arrhythmogenic right ventricular
cardiomyopathy (ARVC). The pathological hallmark of ARVC consists of progressive
loss of cardiac myocytes that are replaced by fibrofatty tissue, leading to electric instability. Five of the 8 causative genes thus far associated with the disorder encode major
components of the cardiac desmosomes 19.
Epidemiological studies have demonstrated that heritable factors also determine
variability in susceptibility to SCD in the old age groups (age > 35-40) 22-24 where CAD is
the most common underlying pathology. In a population-based case-control study by
Friedlander et al. 22, a family history of MI or SCD was associated with more than 50%
increased risk of SCD (relative risk [RR] = 1.57). This risk estimation was independent
of all common risk factors. A few years later, the same investigators re-analyzed their
case-control data. This time, they differentiated between family history of MI and family history of SCD and demonstrated that a positive family history of early-onset SCD
(< 65 years of age) independent of parental history of MI contributed to a greater risk
of SCD (RR = 2.7) 25. Similarly, in the Paris Prospective Study, selectively performed in
men, among whom 118 cases of sudden death occurred, SCD of one parent was found
to be an independent risk factor for sudden death (RR = 1.8). There was a remarkable
increase in risk if both parents had a history of SCD (RR = 9.4) 23.
Although these initial studies highlighted a heritable component in the determination of risk of SCD in the community, they did not differentiate between the different cardiac pathologies in which SCD occurred. Our group has investigated familial
aggregation of SCD in the setting of acute myocardial ischemia in the Arrhythmia
Genetics in the Netherlands Study (AGNES), conducted specifically in patients with
a first acute ST- segment elevation MI 24. This case-control study demonstrated that
patients with familial SCD were at higher risk of developing VF during a first acute MI
(odds ratio [OR] = 2.72) 24. Within the same year, a study from Finland uncovered similar findings. Kaikkonen et al. 26 showed that patients with SCD in the setting of a first
acute MI were more likely to have a family history of SCD compared with survivors of
acute MI (OR = 1.6) or compared with healthy controls (OR = 2.2). The presence of SCD
in two or more first degree relatives increased risk of SCD remarkably compared with
survivors of MI (OR = 3.3) or compared with healthy controls (OR = 11.3). These studies
clearly demonstrate familial aggregation of SCD pointing to a heritable component
in the determination of risk. Importantly, since these studies control for the presence
of acute MI, they show that genetic susceptibility specific for the arrhythmic event
exists and is unrelated to, for example, the genetic susceptibility to the hemodynamic
consequences of the MI itself.
However, despite this evidence, advances in uncovering genetic factors underlying
susceptibility to arrhythmias in the setting of complex cardiac pathologies, affecting a
much greater proportion of the population, has been very limited 27-29. To date only a
few genetic variants modulating risk in this setting have been uncovered. We here review the current insight on genetic determinants of SCD in the community and mainly
describe genome-wide association approaches undertaken thus far in uncovering the
genetic determinants of SCD risk.
Genome-wide association studies (GWAS)
GWAS test millions of common variants (variants present in more than 5% of the
population) across the genome to identify those variants that are significantly associated with complex diseases 30.
Conducting genetic studies for SCD in large scale is extremely challenging. Most
cases of cardiac arrest occur early after the onset of symptoms. The majority of such
39
Chapter 3
Complex inheritance for susceptibility to sudden cardiac death
40 Chapter 3
early onset SCD cases that do not undergo resuscitation or are not witnessed are consequently not included in the analysis 11. DNA of individuals with the SCD phenotype
is difficult to obtain due to the natural course of the event. Moreover, ethical issues
related to collection of DNA from SCD victims limit inclusion of patients. In addition,
the lack of homogeneity of the underlying cardiac pathology (and consequently the
mechanism of the attendant arrhythmia) complicates the interpretation of findings
across different genetic studies. However, large samples of homogeneous SCD phenotype are challenging to collect for various reasons. The SD cases in the community
must have a cardiac origin to be defined as SCD. However, that is not always the case
and other underlying pathologies (e.g. stroke or aneurysm) may be the cause. In addition, SCD may not always be mediated by VF. Even a documented VF may not always
be in the setting of a first MI. Previous MI or structural disturbances of the heart (cardiomyopathies) may also be associated with VF and ultimately SCD. Detailed clinical
information regarding the event (including previous medical history, drug use, etc.)
or autopsies are the only methods to obtain sufficient information concerning the
underlying cardiac pathology in SCD. However, obtaining information about previous
medical and medication history of SCD victims, which would provide information
about the underlying cardiac substrate, is largely restricted and autopsy is conducted
only sporadically 31.
Up to now, three genome wide association studies on SCD and one on VF have investigated the role of common genetic variants in occurrence of these traits 32-35. Only
two studies were able to reach the genome-wide significant threshold of P < 5 × 10−8
and replicate the findings 33,35. Table 1 summarizes genetic variants that have been
found in the studies for SCD/VF.
The first GWAS for VF in MI was conducted in the AGNES case-control set 35 aiming to identify single nucleotide polymorphisms (SNPs) associated with risk of VF in
the setting of acute MI. The AGNES study comprises Dutch individuals with a first
ST-segment elevation acute MI where survivors of VF (n = 457) are compared with
patients without VF (n = 515). The high specification of the phenotype in the AGNES
study increases the chance to detect genetic variants that are associated with VF rather
than other arrhythmias through which SCD may occur. The control set is collected
Table 1 | Genetic variants that have been found associated with SCD
SNP
Location
Nearest
gene
Risk allele
Effect
size
P-value
rs2824292
Intergenic
CXADR
G
1.78
3.3 × 10−10
VF
rs4665058
Intronic
BAZ2B
A
1.92
1.8 × 10−10
SD/SCD
SCD phenotype
SNP, single nucleotide polymorphism; SCD, sudden cardiac death; VF, ventricular fibrillation; SD,
sudden death
from the same patient population as the VF patients. This similarly-exposed control
set increases the statistical power for detection of variants and reduces the chance of
confounding.
The AGNES study identified (chapter 4 of this thesis) a genetic variant at chromosome 21q21 (lead SNP rs2824292) in a non-coding region in the vicinity of the CXADR
gene, which encodes the coxsackie and adenovirus receptor. The association was
replicated in a similar population consisting of 146 out of hospital cardiac arrest cases
(in the setting of acute MI) and 391 controls (i.e. MI without VF).
CXADR encodes the coxsackievirus and adenovirus receptor (CAR) and is expressed in the heart (http://www.genecards.org). CAR is long known to play a role
in mediating viral myocarditis and its sequelum dilated cardiomyopathy 36,37. Two
studies have uncovered a physiologic role for CAR in localization of connexin 45 at
the intercalated disks of cardiomyocytes in the atrioventricular node, and a role in
conduction of the cardiac impulse within this cardiac compartment 38,39. Whether CAR
plays a role in ventricular conduction is yet unknown as is the mechanism whereby it
could impact on risk of VF during acute MI.
The second GWAS, conducted by Arking et al 33 consisted of a large meta-analysis
of multiple genome-wide association studies for SD/SCD carried out in individuals
of European ancestry. In the first stage, this study compared 1,283 SD/SCD cases and
> 20,000 controls drawn from a combination of five case-control and population-based
studies conducted in Europe and the U.S. Various underlying pathologies causing SD
or SCD were included in this meta-analysis. The controls comprised both CAD controls and population-based controls. These investigators 33 identified a genetic variant
at chromosome 2q24.2 (lead SNP rs4665058) in an intron in the BAZ2B gene, which
encodes bromodomain adjacent zinc finger domain 2B and is expressed in the heart.
The BAZ2B gene was not previously known to play a role in cardiac arrhythmia or SCD.
BAZ2B which was first identified and described in 2000 by Jones et al. belongs to the
ZK783.4 subfamily in the BAZ gene family (bromodomain adjacent zinc finger). The
function of the ZK783.4 subfamily has yet to be elucidated. The finding was described
to be consistent in studies comparing SD/SCD cases with CAD controls (FinGesture
and Oregon-SUDS) 33 ensuring that the risk associated with rs4665058 may be specific
to the SCD phenotype rather than CAD. This association was replicated in 3119 SD/
SCD cases and 11,146 controls from 11 European ancestry populations which also
included the AGNES case-control set. When the AGNES case-control set was considered separately however, the BAZ2B locus did not demonstrate an effect on risk of VF.
Similarly, the CXADR signal detected in the AGNES GWAS was not detected in a small
case-control set (90 patients with acute MI and VF and 167 MI non-VF controls) from
Germany 40. These differences may be due to differences in phenotype definition and
study design, statistical power or pure chance.
41
Chapter 3
Complex inheritance for susceptibility to sudden cardiac death
42 Chapter 3
A pilot GWAS with a very small sample size 32 investigated genetic determinants of
SCD by comparing genetic differences of 89 cases with 520 healthy controls. The cases
were defined as patients suffering from sudden cardiac arrest due to documented
sustained VT or VF requiring cardioversion or defibrillator in presence (n = 36) or absence (n = 53) of acute myocardial ischemia 32. This study identified 14 non-replicated
variants associated with SCD at the genome wide significant level (see table 2 from
Aouizerat et al. 32). The most significant SNP (rs12429889; P-value = 5.28 × 10−20) was located at chromosome 13q22.1 in the vicinity of KLF12 gene, which encodes Kruppellike factor 12. KLF12 is a transcriptional silencer of adaptor-related protein complex
2, alpha 1 subunit (AP2A1) which has been implicated in vesicle trafficking (OMIM:
601026; 607531). In the study by Aouizerat et al; the number of cases was very small
and multiple SCD phenotypes were included. In addition, the study lacked replication
of the results in other independent populations.
In causal inference studies, it is important to keep in mind that the sentinel genetic
variant itself (i.e. the SNP displaying the strongest genetic association) may not necessarily be the causal variant. SNPs display linkage disequilibrium (LD, the non-random
association between alleles at two or more loci along a chromosomal segment) and
are inherited as haplotype blocks. Thus any variant within such a haplotype block
(displaying high LD with the sentinel SNP) could in principle be the causal variant 30.
Common genetic variants are expected to modify the risk of SCD through different
genetic mechanisms. However, the mechanism through which the identified variants
are associated with SCD is in most cases not immediately clear. Oftentimes the sentinel
variant does not commonly occur in strong LD with any missense or splice variants in
the coding regions of genes. Variants identified in GWAS are often located in the nonprotein coding regions of the genome. This suggests that the genetic variation affects a
regulatory element which modulates disease susceptibility through effects on the level
of expression of a gene; the regulated gene may be neighboring the association signal
but may also be further away in the genome. In this regard, studies investigating the
genetic regulation of gene expression, commonly referred to as expression quantitative trait locus (eQTL) analysis, in cardiac tissue as well as genome-wide identification
of regulatory regions by ChIP-Seq (chromatin immunoprecipitation sequencing) 41
are likely to aid causal inference.
In addition to the future possibilities for risk stratification, an important motivation of carrying out genetic studies on SCD is to uncover novel molecular players that
could illuminate previously unsuspected pathways involved in the determination of
risk. Following GWAS, follow-on causal inference and functional studies in animal
models resembling the disorder in humans are therefore necessary and important to
reap the full benefit of GWAS efforts. This is a crucial step in order to translate the
Complex inheritance for susceptibility to sudden cardiac death
43
emerging scientific knowledge to patient management and development of new or
better targeted therapy for prevention of SCD.
An alternative approach to GWAS of SCD is to identify genetic variants associated with
phenotypes that are considered as risk factors for SCD 31. Such phenotypes are often
referred to as “intermediate phenotypes”. It is thought that genetic variants that are associated with an intermediate phenotype should have a similar relation to the disease
of interest if the intermediate phenotype is a causal factor for that disease 42.
A proper intermediate phenotype should be quantifiable and should display
heritability in order to be useful in gene discovery. Heart rate and ECG indices of
conduction and repolarization are considered important quantifiable intermediate
phenotypes for risk of developing cardiac arrhythmias (Table 2; reviewed in reference 31). For instance, we have previously shown that ECG indices measured during
the acute phase of a first MI were associated with risk of ensuing VF 43. Furthermore, a
number of studies have demonstrated that heart rate, PR interval, QRS duration and
Table 2 | Established SNPs affecting ECG indices of heart rate, conduction and repolarization
SNP
Coded/Non
Coded Allele
GWAS Beta
(ms per copy of
coded Allele)
Minor Allele
(Frequency)
Genea
RR SNPs
rs11154022
A/G
5.8
A (0.33)
8 kb from GJA1
rs12666989
C/G
−7.0
C (0.20)
UFSP1
rs17287293
G/A
8.6
G (0.14)
SOX5-BCAT1
rs174547
C/T
−6.2
C (0.31)
FADS1
rs223116
A/G
−7.4
A (0.24)
THTPA-NGDN-ZFHX2-MYH7
rs2745967
G/A
5.4
G (0.38)
CD34-PLXNA2
rs281868
G/A
−6.3
A (0.49)
SLC35F1
rs314370
C/T
−7.6
C (0.20)
SLC12A9
rs452036
A/G
−7.8
A (0.39)
MYH6
rs885389
A/G
−0.17
A (0.37)
GPR133
rs9398652
A/C
−12.6
A (0.12)
GJA1-HSF2
rs11047543
A/G
−2.09
A (0.14)
SOX5
rs11708996
C/G
3.04
C (0.16)
SCN5A
PR SNPs
a
According to the definition of the original publication where the association was first identified.
Chapter 3
Intermediate phenotypes in SCD
44 Chapter 3
Table 2 | Established SNPs affecting ECG indices of heart rate, conduction and repolarization
(continued)
Coded/Non
Coded Allele
GWAS Beta
(ms per copy of
coded Allele)
Minor Allele
(Frequency)
Genea
rs11897119
C/T
1.36
C (0.38)
MEIS1
rs1896312
C/T
1.95
C (0.29)
TBX5-TBX3
rs251253
C/T
−1.49
C (0.41)
NKX2-5
rs3807989
A/G
2.29
A (0.42)
CAV1-CAV2
rs3825214
G/A
7.35
G (0.20)
TBX5
rs4944092
G/A
−1.19
G (0.33)
WNT11
rs6795970
A/G
14.81
A (0.39)
SCN10A
rs7660702
T/C
8.46
C (0.30)
ARHGAP24
A/G
1.78
G (0.11)
ATP1B1
rs11970286
T/C
1.53
T (0.47)
PLN
rs12029454
A/G
0.17
A (0.14)
NOS1AP
SNP
QTc SNPs
rs10919071
rs12053903
C/T
−0.07
C (0.33)
SCN5A
rs12143842
T/C
0.18
T (0.24)
NOS1AP
rs12210810
C/G
0.06
C (0.04)
PLN
rs12296050
T/C
1.62
T (0.18)
KCNQ1
rs16857031
G/C
0.15
G (0.14)
NOS1AP
rs17779747
T/G
−1.10
T (0.34)
KCNJ2
rs1805128
A/G
0.05
T (0.05)
KCNE1
rs2074238
T/C
−0.45
T (0.05)
KCNQ1
rs2074518
T/C
−0.06
T (0.49)
LIG3
rs2968863
T/C
−1.37
T (0.26)
KCNH2
rs37062
G/A
−0.10
G (0.23)
CNOT1
rs4657178
T/C
0.3
T (0.25)
NOS1AP
rs4725982
T/C
0.09
T (0.19)
KCNH2
rs8049607
T/C
0.07
C (0.49)
LITAF
rs846111
C/C
0.10
C (0.29)
RNF207
rs10850409
A/G
−0.49
A (0.25)
TBX3
rs10865879
T/C
0.77
C (0.25)
SCN5A-EXOG
rs11153730
C/T
0.59
T (0.49)
C6orf204-SLC35F1PLN-BRD7P3
rs11708996
C/G
0.79
C (0.16)
SCN5A
rs11710077
T/A
−0.84
T (0.18)
SCN5A
QRS SNPs
a
According to the definition of the original publication where the association was first identified.
Complex inheritance for susceptibility to sudden cardiac death
45
Coded/Non
Coded Allele
GWAS Beta
(ms per copy of
coded Allele)
Minor Allele
(Frequency)
Genea
rs11848785
G/A
−0.5
G (0.27)
SIPA1L1
rs13165478
A/G
−0.55
A (0.37)
HAND1-SAP30L
rs1321311
A/C
7.14
A (0.24)
CDKN1A
rs1362212
A/G
0.69
A (0.16)
TBX20
rs17020136
C/T
0.51
C (0.21)
HEATR5B-STRN
rs1733724
A/G
0.49
A (0.27)
DKK1
rs17391905
G/T
−1.35
G (0.02)
C1orf185-RNF11CDKN2C-FAF1
rs17608766
C/T
0.53
C (0.13)
GOSR2
SNP
rs1886512
A/T
−0.4
A (0.37)
KLF12
rs2051211
G/A
−0.44
G (0.26)
EXOG
rs2242285
A/G
0.37
A (0.43)
LRIG1-SLC25A26
rs4074536
C/T
−0.42
C (0.32)
CASQ2
rs4687718
A/G
−0.63
A (0.12)
TKT-PRKCD-CACNA1D
rs6795970
A/G
4.45
A (0.39)
SCN10A
rs7342028
T/G
0.48
T (0.25)
VTI1A
rs7562790
G/T
0.39
G (0.43)
CRIM1
rs7784776
G/A
0.39
G (0.41)
IGFBP3
rs883079
C/T
0.49
C (0.26)
TBX5
rs9436640
G/T
−0.59
G (0.48)
NFIA
rs9851724
C/T
−0.66
C (0.35)
SCN10A
rs991014
T/C
0.42
T (0.43)
SETBP1
rs9912468
G/C
0.39
G (0.40)
PRKCA
a
According to the definition of the original publication where the association was first identified.
QTc interval are strongly heritable traits 44-46. This implies that a strong genetic component determines the variation in these traits.
Following these findings, large-scale GWAS in large samples of the general
population have identified numerous SNPs modulating heart rate, and ECG indices
of conduction (PR interval, QRS duration) and repolarization (QTc interval) 47-53. SNPs
identified for each of these traits have recently been summarized by Kolder et al. 31. As
is typical for genetic variants with high population frequency, these variants explain a
very small portion of the population variance in the respective parameter. This translates to an effect of less than one or two milliseconds in the respective ECG parameter.
Even when these common variants with marginal effects on ECG traits are considered
Chapter 3
Table 2 | Established SNPs affecting ECG indices of heart rate, conduction and repolarization
(continued)
46 Chapter 3
in aggregate, they still explain only a very small percentage of the variation in these
traits. For instance, in a meta-analysis for identification of QTc-associating SNPs by
Pfeufer et al. 51, SNPs at 10 different loci in aggregate explained only around 3% of the
variance in this trait.
So far, studies have largely shown that SNPs that were previously implicated in
modulating ECG traits, do not exert an influence in determination of risk of SCD, both
when considered individually or in aggregate 33,47. Arking et al. 33 tested 49 SNPs which
are known to exert small effects on ECG traits for effects on modulation of SCD risk in
the general population. Only one SNP (rs4687718) showed association with the SD/
SCD phenotype in a large population consisting of 1,283 SD/SCD cases and more
than 20,000 controls of European ancestry. Noseworthy et al. 54 tested 15 common
variants that were previously found to be associated with QTc interval in GWAS. While
almost all of these variants showed association with QTc interval individually and in
aggregate, these SNPs did not display modulatory effects on SCD risk in a population
consisting of 116 SCD cases and 6808 controls. These variants in aggregate showed
a nonlinear association with SCD. However, Lahtinen et al. 55 from the same group
could not replicate this finding in a further larger meta-analysis. We recently tested
common variants that were previously found to be associated with RR interval, PR
interval, QRS duration, and QTc interval for effects on VF in the setting of a first acute
MI in the AGNES case-control set 56. Our findings were in line with those of previous
investigators as the SNPs did not display any marked effect on risk of VF.
In those few studies where an individual effect of a SNP on risk of SCD was shown,
the effect was at times counter-intuitive. For instance the QRS-shortening A-allele at
rs4687718 33,50 is a SNP that has been found in GWAS for QRS duration and each A allele
at rs4687718 was found to be associated with an increased risk of SCD (OR = 1.27) 33.
In another study by Chambers et al. 47, the PR interval-prolonging allele at rs6795970
was associated with decreased risk of VF during acute MI. It is clear that more work is
required to both validate these initial findings and eventually understand the underlying mechanism.
Obviously, genetic variants identified thus far as modulators of ECG traits cannot
be used for assessing genetic susceptibility to SCD. The findings so far highlights the
need for further studies with large sample sizes aiming to uncover additional genetic
variants, such as rare variants associated with larger effects, which would lead to a
more-complete representation of the allelic architecture of these ECG differences in
the general population.
Complex inheritance for susceptibility to sudden cardiac death
47
Understanding the genetic structure of complex traits as is cardiac arrhythmia is a
major challenge 57. The studies that have investigated the role of common genetic
variation in SCD risk have so far identified only few signals. Difficulty in collection
of SCD cases and the proper characterization of the underlying cardiac pathology for
strict definition of the phenotype represent major obstacles. Collaborations in large
scale have been initiated in order to increase the sample size and consequently the
statistical power to detect more variants; the current efforts to gain statistical power
are at the expense of phenotypic heterogeneity. Careful downstream epidemiological
studies as well as functional studies will be required to understand the exact cardiac
pathology where the variants exert their effect. The research in this field gets even
more challenging as the search for genetic predisposition to complex phenotypes
is shifting to encompass the role of rare variants in risk of SCD which consequently
necessitates even larger sample sizes to ensure statistical power.
Summary
SCD accounts for up to half of all cardiovascular deaths. In the young it occurs primarily in the setting of the primary electrical disorders and the cardiomyopathies,
disorders displaying Mendelian inheritance. Significant progress has been made in
the last 15 years in unraveling genes underlying these disorders. However, most SCD
cases occur due to VF in the setting of myocardial infarction/ischemia in the older
segment of the population.
During ischemia, multiple factors that can trigger arrhythmia include injury
current, changes in electrophysiological properties of the cardiac Purkinje fibers, mechanical stretch due to left ventricular malfunction, changes in the heart rate and
reperfusion of blood into the ischemic area.
Although unequivocal evidence exists for a genetic component in the determination of risk for VF in the setting of ischemia/infarction, the underlying genetic factors
remain largely unidentified. To date only a few genetic variants modulating VF risk in
this setting have been uncovered. So far, GWAS have identified two loci close to the
CXADR and within BAZ2B genes, respectively, as susceptibility loci for VF and SCD.
The molecular function through which these loci are associated with SCD has yet to
be elucidated.
Intermediate phenotypes such as ECG traits have been used as a surrogate in order
to identify genetic variants modulating risk of SCD. However, studies conducted thus
far demonstrate that, such variants do not have a marked effect on susceptibility. Fu-
Chapter 3
Future perspective for the genetics of SCD
48 Chapter 3
ture large scale collaborative studies on large patient sets might provide the statistical
power required to detect their effect.
Acknowledgement
The authors are supported by research grants from the Netherlands Heart Foundation
(grants 2001D019, 2003T302 and 2007B202), the Leducq Foundation (grant 05-CVD)
and the Netherlands Heart Institute. Dr. C.R. Bezzina is an Established Investigator of
the Netherlands Heart Foundation (grant 2005T024). We thank Jonas S. de Jong for
providing Figure 1.
Complex inheritance for susceptibility to sudden cardiac death
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