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Address reprint requests and correspondence: Dr Morten Krogh Christiansen, Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Blvd 99, 8200 Aarhus N, Denmark.
Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, DenmarkDepartment of Biomedicine, Aarhus University, Aarhus C, DenmarkDepartment of Clinical Medicine, Health, Aarhus University, Aarhus N, Denmark
First Department of Medicine, University Medical Centre Mannheim (UMM), Faculty of Medicine Mannheim, University of Heidelberg, European Center for AngioScience (ECAS), and DZHK (German Center for Cardiovascular Research) partner site Heidelberg/Mannheim, Mannheim, Germany
First Department of Medicine, University Medical Centre Mannheim (UMM), Faculty of Medicine Mannheim, University of Heidelberg, European Center for AngioScience (ECAS), and DZHK (German Center for Cardiovascular Research) partner site Heidelberg/Mannheim, Mannheim, Germany
Department of Cardiology, Aarhus University Hospital, Aarhus N, DenmarkDepartment of Clinical Medicine, Health, Aarhus University, Aarhus N, DenmarkERN Reference Center GUARD-Heart, Aarhus, Denmark
A variant in the SLC4A3 anion exchanger has been identified as a novel cause of short QT syndrome (SQTS), but the clinical importance of SLC4A3 as a cause of SQTS or sudden cardiac death remains unknown.
Objective
The purpose of this study was to investigate the prevalence of potential disease-causing variants in SQTS patients using gene panels including SLC4A3.
Methods
In this multicenter study, genetic testing was performed in 34 index patients with SQTS. The pathogenicity of novel SLC4A3variants was validated in a zebrafish embryo heart model.
Results
Potentially disease-causing variants were identified in 9 (26%) patients and were mainly (15%) located in SLC4A3: 4 patients heterozygous for novel nonsynonymous SLC4A3 variants—p.Arg600Cys, p.Arg621Trp, p.Glu852Asp, and p.Arg952His—and 1 patient with the known p.Arg370His variant. In other SQTS genes, potentially disease-causing variants were less frequent (2× in KCNQ1, 1× in KCNJ2, and CACNA1C each). SLC4A3 variant carriers (n = 5) had a similar heart rate but shorter QT and J point to T wave peak intervals than did noncarriers (n = 29). Knockdown of slc4a3 in zebrafish resulted in shortened heart rate–corrected QT intervals (calculated using the Bazett formula) that could be rescued by overexpression of the native human SLC4A3-encoded protein (AE3), but neither by the mutated AE3 variants p.Arg600Cys, p.Arg621Trp, p.Glu852Asp nor by p.Arg952His, suggesting pathogenicity of these variants. Dysfunction in slc4a3/AE3 was associated with alkaline cytosol and shortened action potential of cardiomyocytes.
Conclusion
In about a quarter of patients with SQTS, a potentially disease-causing variant can be identified. Nonsynonymous variants in SLC4A3 represent the most common cause of SQTS, underscoring the importance of including SLC4A3 in the genetic screening of patients with SQTS or sudden cardiac death.
Short QT syndrome (SQTS) is a rare inherited cardiac disease associated with a high risk of ventricular and atrial arrhythmias and sudden cardiac death (SCD).
This indicates that yet undetected causal genetic variants exist. Variants causing SQTS have been located in genes encoding cardiac cation channels. This is considered to cause an accentuated potassium efflux,
Loss-of-function mutations in the cardiac calcium channel underlie a new clinical entity characterized by ST-segment elevation, short QT intervals, and sudden cardiac death.
which results in a shortening of the ventricular action potential as reflected by the shortening of the QT interval. We have recently identified a variant in the SLC4A3 anion exchanger gene as a cause of SQTS.
SLC4A3 encodes the Cl−/HCO3− exchanger 3 (AE3), which transports Cl− into the cardiomyocyte in exchange for HCO3−. The identified SLC4A3 variant p.Arg370His reduces the Cl−/HCO3− exchange over the cell membrane, leading to an increase in intracellular pH (pHi), which in combination with a decrease in [Cl−]i shortens the heart rate–corrected QT interval.
Since the discovery of SLC4A3 as a cause of SQTS, genome-wide association studies have further linked SLC4A3 to QT interval length as well as QT dynamics in response to exercise.
However, to date the prevalence of pathogenic variants in SLC4A3 has not been reported and therefore the clinical importance of SLC4A3 variants as a cause of SQTS or SCD remains unknown. We hypothesized that variants in the SLC4A3 anion exchanger might be a previously overlooked cause of SQTS. To address this, we investigated the prevalence of potential disease-causing variants using gene panels including SLC4A3 in a uniquely large German-Danish cohort of unrelated patients with SQTS and further investigated potentially disease-causing SLC4A3 variants in a zebrafish embryo heart model.
Methods
Patient population with SQTS
This was a cross-sectional study from national tertiary centers in Germany (Münster) and Denmark (Aarhus and Copenhagen) with specialized functions in inherited cardiac diseases. We identified patients with suspected SQTS in our clinics and included all index patients fulfilling a clinical diagnosis of SQTS according to the European Society of Cardiology 2015 guideline criteria.
2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC). Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC).
Thus, all included patients had a QTc interval of ≤340 ms or a QTc interval of ≤360 ms combined with at least one of the following criteria: (1) presence of a SQTS gene variant previously established as pathogenic, (2) a family history of SCD, or (3) a documented episode of ventricular tachycardia or ventricular fibrillation.
A 12-lead resting electrocardiogram (ECG) was obtained in all patients, and the R-R interval, QT interval, and J point to T wave peak interval were recorded. The QT interval was measured using the tangent method in the precordial lead presenting the highest T-wave amplitude, and the QTc interval was calculated using the Bazett formula.
AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: Part IV: the ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society: endorsed by the International Society for Computerized Electrocardiology.
AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: Part IV: the ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society: endorsed by the International Society for Computerized Electrocardiology.
Patient information was obtained from medical records.
The study complies with the Declaration of Helsinki. All study patients gave informed consent for genetic sequencing. The study was approved by the ethics committee in the Central Denmark Region (record no. 1-10-72-189-16) and local ethics committees. The zebrafish studies were performed in accordance with institutional guidelines.
Bioinformatic analysis
The DNA sequencing process is provided in the Online Supplement. Genes of interest were filtered and analyzed using the MOMA Heart Panel v4 (https://moma.dk/files/MOMA_Heartpanel.v4.2018-08-15.pdf) (n = 23 patients), the TruSight Cardio Sequencing Panel + SLC4A3 (https://www.illumina.com/content/dam/illumina-marketing/documents/clinical/rgh/gene-list.xlsx) (n = 6 patients), or a customized SQTS gene panel comprising KCNQ1, KCNH2, KCNJ2, and SLC4A3 (n = 5 patients) according to the clinical practice at each of the centers. Established (ie, disease-validated) genes for SQTS in the TruSight Cardio Sequencing Panel include KCNH2, KCNQ1, KCNJ2, and some genes suggested to be implicated in SQTS, although they have recently been disputed as being causative (CACNA1C, CACNB2, and CACNA2D1).
The MOMA NGS Heart Panel v4 includes all of the above plus SLC4A3. All variants were manually assessed and classified according to the American College of Medical Genetics (ACMG) criteria.
Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.
Variants were classified as potentially disease causing when scored as pathogenic or likely pathogenic according to the ACMG criteria, but variants of uncertain significance in any of the SQTS genes were also considered as potentially disease causing despite the absence of additional information (eg, familial inheritance) that may upgrade those.
Zebrafish embryo experiments
All zebrafish experiments were performed at early developmental stages before they become recognized as experimental animals in agreement with EU Directive 2010/63/EU and according to the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines. Zebrafish were housed in accordance with published recommendations.
Details on animal housing and husbandry, animal model generation and validation, as well as phenotypic analyses are provided in the Online Supplement including Online Supplemental Figure S1.
Statistical analyses
Data are presented as mean ± SD, median (interquartile range), or number (percentage), and figure data are shown as individual data points with mean ± 1 standard error of the mean. All continuous variables were tested for normality, and the significance of difference between groups was tested using the Wilcoxon rank-sum test, Student t test, one-way analysis of variance with the Tukey posttest, χ2 test, or Fisher exact test, as appropriate. Statistical analyses were performed using Stata/IC 13.1 (StataCorp LLC, College Station, TX) and GraphPad Prism 9 (GraphPad Software, San Diego, CA).
Results
Clinical data on patients with SQTS
We identified 47 index patients with suspected SQTS. Eleven patients had a “borderline” clinical presentation and did not meet the full European Society of Cardiology 2015 guideline criteria for SQTS and were therefore excluded. Furthermore, 2 patients were excluded because they have previously been reported in the discovery study of SLC4A3.
Among the remaining 34 index patients with SQTS, the mean QTc interval was 333 ± 19 ms and 20 patients (59%) had a QTc interval of ≤340 ms (Table 1). One patient with SQTS had an ECG with signs of early repolarization but no pathogenic variants were identified (sequenced using the MOMA NGS Heart Panel v4). All patients had normal echocardiograms except 1 patient with a secundum atrial septum defect and reduced left ventricular function.
Table 1Characteristics of patients with SQTS
Characteristic
All patients (N = 34)
SLC4A3 variant present (n = 5)
SLC4A3 variant absent (n = 29)
P
Age (y)
31 ± 12
30 ±9
31 ± 12
.88
Male sex
30 (88)
4 (80)
26 (90)
.49
Family history of sudden cardiac death
8 (25)
2 (40)
6 (22)
.58
Documented ventricular arrhythmia
19 (56)
3 (60)
16 (55)
>.99
ICD implanted
22 (65)
3 (60)
19 (66)
>.99
Heart rate (beats/min)
57 ± 12
63 ± 9
56 ± 12
.25
QT interval (ms)
346 ± 40
312 ± 11
352 ± 40
.0043
QTc interval (ms)
333 ± 19
319 ± 20
335 ± 18
.075
Jp-Tp interval (ms)
217 ± 38
178 ± 26
224 ± 36
.022
NGS with coverage ≥30× (%)
99.5 (99.4–99.5)
99.3 (99.3–99.5)
99.5 (99.4–99.5)
.52
Values are presented as mean ± SD, median (interquartile range), or n (%).
Family history of sudden cardiac death <40 y was unknown in 2 patients. The Jp-Tp interval was missing in 6 patients. NGS with coverage ≥30× was missing in 2 patients.
ICD = implantable cardioverter-defibrillator; Jp-Tp = J point to T wave peak; NGS = next-generation sequencing; QTc interval = heart rate–corrected QT interval (calculated using the Bazett formula); SQTS = short QT syndrome.
A potentially disease-causing variant was identified in 9 patients (26%). Five variants were localized in SLC4A3 (15% of patients) including 4 novel variants (c.1798C>T (p.Arg600Cys), c.1861C>T (p.Arg621Trp), c.2556G>C (p.Glu852Asp), and c.2855G>A (p.Arg952His)), which were classified as variants of uncertain significance according to the ACMG criteria. A detailed list of the 5 patients and corresponding variants is provided in Table 2 and Online Supplemental Table S1 (ECGs are provided in Online Supplemental Figures S2–S6). In the case of the Danish proband (Table 2, case 34), information from a brother was also available. This brother had a QTc interval of 320 ms, atrial fibrillation and was found also to harbor the same c.2855G>A (p.Arg952His) variant. None of the patients with a potentially disease-causing variant carried ≥1 potentially disease-causing variant. Since rare missense variants are relatively common in SLC4A3 (599 high-quality missense variants reported in the gnomAD (v2.1.1) allele frequency database at a frequency rate of ≤0.004%), we compared the rate of SLC4A3 missense variants among patients with SQTS to 3528 in-house samples previously analyzed in our laboratory for hereditary diseases including various heart (≈5%), liver, kidney, neurological, and cancer diseases. There were 63 missense variants (1.7%) with an in-house allele frequency of <0.01, which was significantly lower than the rate of 5 (15%) observed in patients with SQTS (P < .001). Patients with SLC4A3 variants had shorter QT and J point to T wave peak intervals than the remaining patients with SQTS. Other patient characteristics were comparable between patients with and without SLC4A3 variants (Table 1).
Autism, affective disorder, severe dental enamel defects
Normal
Chinidine 600 mg/d
No
CACNA1C
NM_000719.6
c.2399A>C
p.(Lys800Thr)
9.60 × 10−6
Nonsynonynous
PS3 (moderate) PM2 (supporting)
VUS
Custom SQTS panel
33
German
M (20)
No
Yes (20)
66
300
315
None
Normal
Amiodarone 200 mg/d
Yes (20)
SLC4A3
NM_201574.2
c.1798C>T
p.(Arg600Cys)
0
Nonsynonynous
PM2 (moderate) PP3 (supporting)
VUS
TruSight Cardio Sequencing Panel
34
Danish
M (37)
Yes
No
71
320
349
None
Normal
None
No
SLC4A3
NM_201574.2
c.2855G>A
p.(Arg952His)
0
Nonsynonynous
PM2 (moderate) PP3 (supporting)
VUS
MOMA Heart Panel v4
ACMG = American College of Medical Genetics; F = female; FHx = family history of sudden cardiac death <40 y; HR = heart rate; ICD = implantable cardioverter-defibrillator; LP = likely pathogenic (according to the ACMG criteria); M = male; MAF = minor allele frequency; N/A = not available; P = pathogenic (according to the ACMG criteria); QTc interval = heart rate–corrected QT interval (calculated using the Bazett formula); SCD = sudden cardiac death; SQTS = short QT syndrome; VF = ventricular fibrillation; VT = ventricular tachycardia; VUS = variant of unknown significance (according to the ACMG criteria).
∗ ACMG criteria were applied on the basis of the published evidence and not including the functional studies presented in this study.
Loss of AE3 function by slc4a3 knockdown in zebrafish embryos was previously reported to result in shortened QTc interval and shortened systolic duration, which was rescued by overexpression of wild-type AE3 but not by the short QT interval–associated AE3 variant Arg370His.
We applied a similar strategy to determine the in vivo consequences of the 4 novel AE3 variants on cardiac function. Reverse transcription polymerase chain reaction analysis indicated efficient knockdown and similar in vivo stability of microinjected wild-type and variant AE3 messenger RNA 2 days postfertilization (Online Supplemental Figures S7A and S7B), suggesting that any potential loss of in vivo functionality compared to wild-type AE3 is not a result of impaired messenger RNA stability. All ECG recordings were blinded before analysis, and neither slc4a3 knockdown nor co-overexpression of wild-type or variant AE3 affected the heart rate (Online Supplemental Figures S7C and S7G). However, knockdown of slc4a3 resulted in shortened QTc interval, which was rescued from the level of knockdown by overexpression of human wild-type AE3 (P = .0008) (Figure 1A and Online Supplemental Figure S7G), whereas the Arg370His variant was unable to rescue the shortened QTc interval (P = .98) (Figure 1B and Online Supplemental Figure S7G) as previously reported.
Similarly, neither Arg952His (P = .34), Arg621Trp (P = .98), Glu852Asp (P = .98) nor Arg600Cys (P = .98) mutated AE3 variants rescued the short QT phenotype from the level of knockdown (Figure 1B and Online Supplemental Figure S7G). Action potential (AP) duration was reduced in slc4a3 knockdown embryos (AP50%: P = .0029; AP70%: P = .027) (Figures 1E and 1F and Online Supplemental Figure S8), substantiating the QTc duration phenotype. We previously reported increased pHi in slc4a3 knockdown zebrafish embryo hearts and that increased pHi caused shortening of action potential duration in rabbit hearts.
To assess the correlation of variant AE3 with pHi, we measured pHi in slc4a3 knockdown zebrafish hearts with and without overexpression of wild-type or Arg370His-mutated AE3 (Figure 1G). Whereas overexpression of wild-type AE3 decreased pHi from the level of slc4a3 knockdown (P = .0010), the Arg370His variant was unable to do so (P = .57), suggesting increased pHi as a cause of short QTc interval associated with this variant. Taken together, these data suggest impaired function and pathogenicity of the assessed variants.
Figure 1Short QT syndrome–associated SLC4A3 variants are unable to normalize short heart rate–corrected QT (QTc) interval in slc4a3 knockdown zebrafish embryos. A–D: QTc interval is shortened by slc4a3 knockdown and normalized by coinjected messenger RNA (mRNA) encoding wild-type but not variant human AE3. Plotted data represent QTc interval of individual zebrafish embryos microinjected with either standard control morpholino (Control), slc4a3 targeted morpholino (KD), or slc4a3 targeted morpholino in combination with mRNA encoding human wild-type or mutated AE3 as indicated. All electrocardiographic recordings were blinded before analysis. A: Control (n = 14; mean 0.5049 ± 0.0142), knockdown (n = 16; mean 0.4454 ± 0.0172), and knockdown + AE3 (n = 18; mean 0.5226 ± 0.0112). B: Knockdown (n = 7; mean 0.4305 ± 0.0163), knockdown + AE3 (n = 11; mean 0.5115 ± 0.0851); knockdown + AE3 Arg370His (n = 10; mean 0.4383 ± 0.0127), and knockdown + AE3 Arg952His (n = 15; mean 0.4622 ± 0.0121). C: Knockdown (n = 10; mean 0.4555 ± 0.0155), knockdown + AE3 (n = 8; mean 0.5288 ± 0.0088), knockdown + AE3 Arg621Trp (n = 10; mean 0.4497 ± 0.0114), and knockdown + AE3 Glu852Asp (n = 10; mean 0.4489 ± 0.0094). D: Knockdown (n = 12; mean 0.4342 ± 0.0146), knockdown + AE3 (n = 12; mean 0.5042 ± 0.0146), and knockdown + AE3 Arg600Cys (n = 10; mean 0.4380 ± 0.0124). E and F: Action potential (AP) duration is shortened by slc4a3 knockdown. Plotted data represent AP duration of individual isolated embryonic zebrafish hearts. All AP recordings were blinded before analysis. E: AP70%. Control (n = 9; mean 0.5010 ± 0.0226) and knockdown (n = 12; mean 0.4160 ± 0.0255). F: AP50%. Control (n = 9; mean 0.3954 ± 0.0206) and knockdown (n = 12; mean 0.3030 ± 0.0176). G: AE3 Arg370His is unable to reduce intracellular pH (pHi) in slc4a3 knockdown embryos. Knockdown (n = 14; mean 7.456 ± 0.0276), knockdown + AE3 (n = 13; mean 7.344 ± 0.0146), and knockdown + AE3 Arg370His (n = 13; mean 7.427 ± 0.0140). Data in each plot were compiled from 3–4 independent experiments, each including all experimental groups. ∗P < .05, ∗∗P < .01, ∗∗∗P < .001 as determined by one-way analysis of variance with the Tukey posttest. Data are presented including mean ± 1 standard error of the mean.
In the present study, we performed targeted next-generation sequencing in order to investigate the yield of genetic testing in patients fulfilling a diagnosis of SQTS according to the current European Society of Cardiology guideline criteria. First, within this large SQTS cohort (n = 34), we were capable of identifying a potentially disease-causing gene variant in about a quarter of patients (26%). With a focus on the recently identified SLC4A3 gene, we found a potentially disease-causing variant in this gene in 15% of all patients, including 4 novel nonsynonymous variants. Since rare SLC4A3 variants are relatively common in the population, we functionally investigated the novel variants. Using genetic modulation, we created zebrafish embryo heart models for all 4 variants and demonstrated their inability to normalize shortened QTc interval induced by lack of AE3, in contrast to the normalizing effect of injecting native AE3. Furthermore, increased pHi resulted not only from AE3 deficiency but also from the patient-derived AE3 Arg370His variant, substantiating altered pHi as a cause of the SQTS phenotype in agreement with previous observations.
Therefore, we estimate that variants in SLC4A3 explain ≈15% of all SQTS cases (19% if the complete cohort of patients with SQTS was considered by including the 2 patients from the discovery study of SLC4A38), indicating that SLC4A3 is the gene most frequently involved in SQTS.
The majority of previous reports on genetic testing in SQTS have been published as case reports, but few studies have investigated the yield of genetic testing in smaller cohorts. Giustetto et al
studied 22 index patients with SQTS and reported a presumed disease-causing variant in 5 patients (23%), of whom 4 variants were located in KCNH2 and 1 in CACNB2b.
who found a presumed disease-causing variant in 6 of 45 patients (13%) (2 located in KCNH2, 2 in KCNJ2, 1 in KCNQ1, and 1 in CACNA1C). Whereas these studies sequenced primarily potassium ion channel genes (KCNH2, KCNJ2, and KCNQ1), and to a lesser extent the questioned SQTS-related calcium channel genes (CACNA1C and CACNB2b), the present study is the first to include the anion exchanger gene SLC4A3. We demonstrate that the yield of sequencing this gene is significantly higher than the yield obtained from sequencing other SQTS genes, which establishes SLC4A3 as the most common cause of SQTS to date and underscores the importance of including SLC4A3 in the genetic screening of patients with SQTS or SCD. It should be noted that the variant rate in potassium channel genes was somewhat lower in our study than what has previously been reported by Giustetto et al
However, Giustetto et al included already published discovery case reports in their study that might inflate the estimated yield and Villafane et al investigated a somewhat different population, which possibly contributes to the differences in estimates.
It is interesting to note that the QT interval was significantly shorter in SLC4A3 variant carriers than in SLC4A3 nonvariant carriers. The same observation has also been described in carriers of disease-causing SQTS gene variants in KCNH2.
One explanation may be a generally stronger contribution to QT interval length from Mendelian inherited disease-causing SQTS variants compared with a more polygenic contribution to QT interval length in noncarriers, a phenomenon that has been observed in other genetic conditions such as familial hypercholesterolemia.
Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study.
Another possible explanation may be that SLC4A3 causes SQTS through a different molecular mechanism where loss of protein function gives rise to a stronger impact on the QT interval. In prior reports, phenotypic variations have been observed among the SQTS subtypes, including a higher risk of atrial arrhythmias in KCNQ1 variant carriers and a marked response to hydroxychloroquine treatment in KCNH2 variant carriers,
and in that respect it is also interesting whether the SLC4A3 SQTS phenotype differs from other SQTS subtypes. However, future longitudinal studies are needed in order to shed light on the outcome.
Despite the significant incremental yield obtained from sequencing SLC4A3, the SQTS phenotype remains unexplained in the majority of patients. This stands in contrast to the fact that familial aggregation of SQTS, and thus a likely genetic component in the pathogenesis of the disease, has been reported in approximately half of patients with SQTS.
These findings indicate the existence of yet unidentified SQTS genes and/or the presence of a polygenic component contributing to SQTS development. Prior identifications of novel SQTS-related genes have primarily been candidate gene driven,
Loss-of-function mutations in the cardiac calcium channel underlie a new clinical entity characterized by ST-segment elevation, short QT intervals, and sudden cardiac death.
suggesting a need for a broader approach to unravel disease-causing variants in unexplained SQTS cases. Given the phenotypic overlap of SQTS with Brugada syndrome,
they may potentially share a common genetic background. Moreover, a large number of genes associated with long QT syndrome (LQTS) have been identified,
and variants in genes associated with LQTS may also exhibit opposite effects leading to SQTS, as is the case for the 3 SQTS-related potassium channel genes (KCNH2, KCNJ2, and KCNQ1), where loss-of-function variants have been associated with LQTS whereas gain-of-function variants have been associated with SQTS.
However, this is not the explanation for the significant number of unexplained SQTS probands in our study since the majority of patients were sequenced using panels covering already established genes associated with Brugada syndrome and LQTS. Recent genome-wide association studies of QT interval length have identified a number of novel candidate genes related to sodium, potassium, and calcium ion regulation as well as autonomic control of the QT interval that may also be involved in the development of SQTS.
Furthermore, these studies highlight the influence of a polygenic contribution to QT interval length. Thus, it is possible that the accumulation in 1 individual of several genetic variants that each causes a small shortening of the QT interval could also account for a proportion of the remaining unexplained SQTS cases (ie, the extreme of a quantitative trait distribution).
Limitations
The present study constitutes one of the largest studies to date investigating the genetic yield in SQTS, a rare arrhythmia phenotype associated with SCD, but a number of limitations deserve attention. All patients were recruited from tertiary referral centers, which may have introduced selection bias since less clinically affected patients with SQTS may have been underdiagnosed or refrained from referral. Except for the Danish patient with a SLC4A3 variant, we only had access to index patient information, and therefore segregation data from affected family members were not available to support variant pathogenicity. However, our study has been strengthened by in vivo demonstration of the QTc-shortening effects of the 4 novel variants. We used different sequencing panels among the study patients including 5 patients who were sequenced for only 4 SQTS genes. Using a wider gene panel might lead to the identification of additional disease-causing variants. However, despite the fact that the majority of patients were sequenced using panels covering genes of potential interest, we found no patient with a pathogenic or likely pathogenic variant outside the established SQTS genes, suggesting a low additional yield of sequencing patients with SQTS by currently established cardiac sequencing panels.
We acknowledge that measurements of QT interval and action potential duration in zebrafish embryos are not universally validated methods and are technically challenging. However, on the basis of the mutually substantiating observations of QT interval and action potential duration obtained by technically independent phenotyping methods, we are confident in the soundness of the reported phenotypic observations. Furthermore, while our data show that increased pHi is a result not only of AE3 deficiency but also of the patient-derived AE3 Arg370His variant, this does not allow us to extend this conclusion to all AE3 variants included in this article. Additional studies are required to establish the molecular mechanism(s) of AE3 variants and associated SQTS.
Conclusion
We identified SCL4A3 as a major cause of SQTS (variant detection rate 15%) and further established an experimental zebrafish AE3 (−/−) model for SQTS in which the novel SLC4A3 variants showed a lack to normalize shortened QT interval. This takes the total proportion of patients with an identified genetic cause of SQTS to about a quarter and establishes SLC4A3 as the most common cause of SQTS to date. Thus, our findings highlight the importance of other than cation channel–driven mechanisms in SQTS and underscore the importance of including SLC4A3 in the genetic screening of patients with SQTS or SCD.
Acknowledgments
We thank the patients for study participation, Birgit Stallmeyer for bioinformatic advice, and Ellen Schulze-Bahr with her technical team for genotyping at Institut für Genetik von Herzerkrankungen and the bioimaging facilities at Department of Molecular Biology and Genetics, Aarhus University and Department of Biomedicine, Aarhus University, for support.
Loss-of-function mutations in the cardiac calcium channel underlie a new clinical entity characterized by ST-segment elevation, short QT intervals, and sudden cardiac death.
2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC). Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC).
AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: Part IV: the ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society: endorsed by the International Society for Computerized Electrocardiology.
Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.
Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study.
Funding Sources: This work was supported by unrestricted research grants from the Novo Nordisk Foundation, Denmark (NNF18OC0031258 and NNF20OC0065151 to Dr Jensen).
Disclosures: Dr Bundgaard was supported by grants from the Research Foundation at Rigshospitalet and Research Foundations of the Capital Region, the Innovation Fund Denmark (PM Heart), and NordForsk and received lecture fees from Amgen. Dr Jensen was supported by grants from the Novo Nordisk Foundation, Denmark (NNF18OC0031258 and NNF20OC0065151), and received lecture fees from Abbott Denmark and Biosense Webster, Europe. The remaining authors have nothing to disclose.
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