Genome-wide association analyses identify new Brugada syndrome risk loci and highlight a new mechanism of sodium channel regulation in disease susceptibility

Abstract

Brugada syndrome (BrS) is a cardiac arrhythmia disorder associated with sudden death in young adults. With the exception of SCN5A, encoding the cardiac sodium channel Na_V1.5, susceptibility genes remain largely unknown. Here we performed a genome-wide association meta-analysis comprising 2,820 unrelated cases with BrS and 10,001 controls, and identified 21 association signals at 12 loci (10 new). Single nucleotide polymorphism (SNP)-heritability estimates indicate a strong polygenic influence. Polygenic risk score analyses based on the 21 susceptibility variants demonstrate varying cumulative contribution of common risk alleles among different patient subgroups, as well as genetic associations with cardiac electrical traits and disorders in the general population. The predominance of cardiac transcription factor loci indicates that transcriptional regulation is a key feature of BrS pathogenesis. Furthermore, functional studies conducted on MAPRE2, encoding the microtubule plus-end binding protein EB2, point to microtubule-related trafficking effects on Na_V1.5 expression as a new underlying molecular mechanism. Taken together, these findings broaden our understanding of the genetic architecture of BrS and provide new insights into its molecular underpinnings.

Extended Data Fig. 1

In support for the involvement of transcription factor genes, an enrichment in genes encoding DNA binding proteins was found at BrS GWAS loci by permutation testing (one-tailed permutation P = 1 × 10⁻⁴).

Extended Data Fig. 2

MAPRE2 overlaps the association signal tagged by rs476348 and its causal role is supported by chromatin interaction between its promoter region and the association signal and by a significant eQTL (P = 2.9 × 10-5246 , CLPP = 0.10) where the BrS risk allele is associated with lower MAPRE2 expression in left ventricular tissue compared to the non-risk allele. MAPRE2 encodes the microtubule plus-end binding protein EB2, a regulator of microtubule organization.

Extended Data Fig. 3

A small positive shift in voltage dependency of activation was observed, while voltage dependency of inactivation and recovery from inactivation were not different between control and KO cells.

Extended Data Fig. 4

PRSBrS was significantly higher in BrS cases that presented with a spontaneous type 1 BrS ECG compared to those with a type 1 BrS ECG after sodium channel blocker challenge (9.3 ± 1.1 vs. 9.1 ± 1.1; P = 1.7 × 10⁻⁵; Fig. 3b), an effect that seemed more pronounced in the subgroup of SCN5A– cases (9.2 ± 1.0 vs. 9.5 ± 1.1; P = 3.5 × 10⁻⁸.

Extended Data Fig. 5

The effects of each of the 21 BrS risk alleles in previously published GWAS of PQ₂₉, QRS₂₈, QT₃₀ and AF₃₁ are generally concordant with the aggregate effect of those alleles (PRSBrS) in the PheWAS (Fig. 4b, Extended Data Fig. 5 and Supplementary Tables 14–17). One exception is the BrS risk allele near MYO18B (rs133902-T), which was also associated with greater risk for AF (P = 9 × 10⁻¹⁰ in Nielsen et al.32, and P = 1 × 10⁻⁷ in Roselli et al.

Fig. 1 |. Manhattan plot of genome-wide association meta-analysis comprising 2,820 unrelated Brugada syndrome cases and 10,001 controls.

The association P values were derived from a meta-analysis of the 10 GWAS strata using a fixed effects model with an inverse-variance weighted approach. We performed logistic regression on the disease status under additive model of SNP’s genotype. P-values are two-sided and not adjusted for multiple testing. The y-axis has breaks to emphasize the novel loci. The red and blue lines indicate the genome-wide significance (P < 5 × 10⁻⁸) and suggestive significance (P < 1 × 10⁻⁶) thresholds, respectively. Genes at novel loci are depicted in red.

Fig. 2 |. Loss of MAPRE2 leads to lower conduction velocity, action potential upstroke velocity and sodium current.

a, Left panel shows representative isochrone maps of hearts isolated from 5 day post-fertilization zebrafish larvae injected with tracrRNA/Cas9 and multiple gRNAs targeting mapre2 (mapre2 KO) or tracrRNA/Cas9 without gRNA (CTRL). The dotted squares reflect the main ventricular area in the hearts from which the various parameters are measured. Right panel shows average ventricular conduction velocity (CV) in CTRL and mapre2 KO hearts. b, Left panel shows representative maximum action potential (AP) upstroke velocity (V_max) maps from zebrafish hearts. Right panel shows average V_max in CTRL and mapre2 KO hearts. c, Left panel shows representative maps of AP duration at 80% repolarization (APD80) in isolated hearts paced at 100 bpm. Right panel shows average APD80 in CTRL and mapre2 KO hearts. d, Representative APs at 1 Hz pacing from single human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) with CRISPR/Cas9–mediated MAPRE2 knockout and isogenic control (CTRL) hiPSC-CMs. A constant ohmic current was injected to set the membrane potential just before the APs at approximately −80 mV to overcome the depolarized state of the hiPSC-CMs (see Online Methods). Inset shows first derivative of the AP upstroke velocity (Vmax). e, Average Vmax and APD at 30 and 90% repolarization (APD₃₀ and APD₉₀, respectively) in CTRL and MAPRE2 KO hiPSC-CMs. Vmax (P = 8.1 × 10⁻⁶), APD₃₀ (P = 4.8 × 10⁻⁶), and APD₉₀ (P = 6.0 × 10⁻⁷) differed significantly between CTRL and MAPRE2 KO hiPSC-CM (**P <0.01; unpaired two-tailed Student’s t-test). Maximal diastolic potential (−56.4 ± 1.5 mV (CTRL) vs. −55.6 ± 1.6 mV (MAPRE2 KO)) and AP amplitude (114.8 ± 6.7 mV (CTRL) vs. 121.8 ± 4.2 mV (MAPRE2 KO)) did not differ significantly between CTRL (n = 15) and MAPRE2 KO (n = 12) hiPSC-CMs (unpaired two-tailed Student’s t-test). f, Left panel shows average current-voltage relationships of the sodium current (I_Na). Right panel shows average repolarizing outward current (I_outward) in CTRL and MAPRE2 KO hiPSC-CMs. Insets show voltage protocol used. *P < 0.05, **P < 0.01 vs. CTRL (two-way ANOVA). Results are expressed as mean ± s.e.m. Numbers in the bar graph refer to the number of hearts or cells studied.

Fig. 3 |. Distribution of PRS_BrS in specific patient sub-groups.

a, Histograms displaying PRS_BrS distribution in BrS cases carrying a rare pathogenic or likely-pathogenic variant in SCN5A (SCN5A⁺; blue) compared to BrS cases without such variants (SCN5A⁻; red). b, Histograms displaying PRS_BrS distribution in BrS cases presenting with a spontaneous type 1 BrS ECG (blue) compared with those presenting with a type 1 BrS ECG only after sodium channel blocker challenge (drug-induced; red). PRS_BrS was calculated per individual based on the 21 BrS risk alleles and their corresponding effect sizes. Results were obtained after logistic regression, two sided p-value not corrected for multiple testing. Reported P values refer to the difference in PRS_BrS units between two groups. Dashed lines showing the mean PRS_BrS for each group.

Fig. 4 |. Associations between polygenic susceptibility to Brugada syndrome and common cardiovascular diseases and traits.

a, Results of the phenome-wide association analysis (PheWAS) for the Brugada syndrome (BrS) polygenic risk score (PRS_BrS) among individuals of European ancestry from the UK Biobank. Phenotypes significantly associated with PRS_BrS and phenotypes relevant to the heart are shown on the x-axis (five electrocardiographic traits are depicted on the right of the plot); the P values from multiple regression are depicted on the y-axis. Red circles indicate that polygenic predisposition to BrS is associated with a positive beta (e.g. increased risk of the condition or higher value for continuous traits), whereas blue circles indicate that polygenic predisposition to BrS is associated with a negative beta (e.g. decreased risk of the condition or lower value). We set the significance threshold to P < 0.0007 after Bonferroni correction (P < 0.05/70), shown as dotted colored lines. The grey dotted lines indicate the nominal significance threshold (P < 0.05). The complete PheWAS results are shown in Supplementary Tables 11 and 12 for dichotomous and continuous traits, respectively. b, Heat-map of associations between BrS risk alleles and atrial fibrillation/flutter (AF), PR-interval (PR), QRS-complex duration (QRS) and QT interval duration (QT) from previously published GWAS^–. The complete PheWAS results are shown in Supplementary Tables 14–17. Each row represents an independent BrS risk allele, while each column represents a phenotype. Red indicates that the BrS risk allele (or a proxy with r² > 0.8) is associated with higher risk of AF or prolongation of the electrocardiographic interval; blue indicates that the BrS risk increasing allele is associated with lower risk of AF or shortening of the interval. The darkest red and blue colors represent conventional genome-wide significance in the published GWAS (P < 5 × 10⁻⁸).