The Utility of Genome-Wide Association Studies in Inherited Arrhythmias and Cardiomyopathies

Authors, Journal, Affiliations, Type, DOI

• Saif Dababneh, Arya Ardehali, Jasleen Badesha, Zachary Laksman
• Genes 2025, 16, 1448 (published 3 December 2025)
• University of British Columbia — Department of Cellular and Physiological Sciences; BC Children's Hospital Research Institute; Heart Rhythm Services & Center for Cardiovascular Innovation; Centre for Heart Lung Innovation
• Type: Review article
• DOI: https://doi.org/10.3390/genes16121448

Overview

GWAS have transformed understanding of inherited arrhythmias and cardiomyopathies, shifting the view from purely monogenic Mendelian disorders toward complex polygenic inheritance where common variants modify susceptibility, penetrance, and severity. This review focuses on four conditions with meaningful GWAS datasets — HCM, DCM, Brugada syndrome, and LQTS — detailing novel loci discovered, biological pathways implicated, and the clinical utility of polygenic risk scores (PRS) derived from these studies. A pivotal finding is that HCM and DCM share inverse risk loci: SNPs in the same genes (MYBPC3, ALPK3, FHOD3) that increase HCM risk decrease DCM risk and vice versa, with direct therapeutic implications. PRSs for all four conditions independently predict disease risk, penetrance in rare-variant carriers, and clinical outcomes — but remain predominantly European-ancestry derived, limiting global applicability.

Keywords

Inherited arrhythmias; inherited cardiomyopathies; GWAS; polygenic risk score; hypertrophic cardiomyopathy; dilated cardiomyopathy; long QT syndrome; Brugada syndrome

Key Takeaways

Introduction

• Inherited arrhythmias (LQTS: KCNQ1/KCNH2/SCN5A; BrS: SCN5A; CPVT: RYR2) and cardiomyopathies (HCM: MYH7/MYBPC3; DCM: TTN/LMNA; ACM: PKP2) were classically monogenic
• Genetic testing yield is incomplete: HCM 30–40%, BrS 20–30% (SCN5A only), indicating large non-monogenic residual
• Variable expressivity and penetrance — TTN truncating variants in 0.5–1% of the population, but only a minority develop DCM — demand a polygenic explanatory framework
• NGS has expanded gene discovery (BAG3, FLNC, TMEM43) but yield gaps persist

2. GWAS Primer

• Surveys millions of common SNPs genome-wide; significance threshold p < 5×10⁻⁸ (Bonferroni corrected)
• Imputation against 1000 Genomes/HRC reference panels extends coverage to millions of additional SNPs
• Most GWAS hits lie in non-coding genome (enhancers, TF binding sites, chromatin loops), making functional validation resource-intensive
• Fine-mapping and colocalization narrow causal variants; MAGMA, FLAG, TWAS locate biologically meaningful genes
• Key limitation: early GWASs were European-only and underpowered; international biobank collaboration has improved statistical power for rare diseases

3. Polygenic Risk Scores — Derivation, Application, Utility

• PRS = sum of risk SNPs weighted by GWAS-derived effect sizes
• Performance metrics: AUC/C-statistic, OR per SD, C-index, net reclassification improvement (NRI)
• European-ancestry PRSs show reduced predictive accuracy in non-European populations (most significant current limitation)
• Cross-ancestry tools (PRS-CSx, CT-SLEB) partially mitigate but do not fully solve transferability
• Clinical readiness requires prospective outcome trials; current PRSs are research tools with emerging clinical potential

4.1 HCM — Novel GWAS Insights

• GWAS validates common variation in MYH7 and identifies novel sarcomeric loci: FHOD3 (actin filament formation/sarcomere assembly), validated in 5900 HCM cases meta-analysis
• Non-sarcomeric loci: ALPK3 (transcription factor regulation), PLN (calcium handling), ACTN2 and CSRP3 (structural proteins)
• GWAS highlights interplay of sarcomeric and non-sarcomeric pathways in HCM pathophysiology

4.1 HCM — Polygenic Risk Scores

• Ning 2023 (n=42,194 UK Biobank): 12 LVRWT trait PRSs; inferoseptal thickness at end-systole most predictive for HCM; HR 1.69 per SD; modest standalone power
• Harper 2021: 27-SNP mixed-ancestry PRS HCM; OR 1.73 per SD; predicts HCM and greater LV wall thickness in sarcomere variant carriers; performs similarly across ancestry groups
• Biddinger 2022 (using Harper PRS; n=184,511 UKB + 30,716 MGB): OR 1.18 per SD in general population; independent of age, sex, BMI, BP; did not predict DCM, arrhythmia, or HF in non-HCM subjects
• Zheng 2025 (5900 cases/68,359 controls; multi-trait GWAS incorporating CMR): OR 2.34 per SD in general population; also OR 2.35 in sarcomere-positive carriers and 2.15 in sarcomere-negative carriers; predicts adverse outcomes including death; correlates with HCM imaging features; inverse association with HF; cross-ancestry performance reduced outside European populations

4.2 DCM — Novel GWAS Insights

• BAG3 (co-chaperone in protein quality control/sarcomere maintenance): rare pathogenic variants cause high-penetrance DCM; common variant p.C151R acts as a modifier influencing penetrance even in TTNtv carriers
• HSPB7 (heat shock protein critical for intercalated disc integrity)
• Inverse HCM–DCM loci (Tadros et al.): SNPs in MYBPC3, ALPK3, FHOD3 show opposing associations — those increasing HCM risk decrease DCM risk and vice versa. This convergent biology suggests cardiac myosin activators (omecamtiv mecarbil) as a potential DCM disease-modifying therapy, paralleling mavacamten's mechanism in HCM

4.2 DCM — Polygenic Risk Scores

• Aung 2019: PRSs for 6 LV CMR traits (LVEDV/LVESV/LVEF/LVSV/LVM/LVMVR); LVEDV, LVESV, LVEF, LVMVR PRSs predict heart failure after adjustment for demographic/clinical factors; LVM PRS not predictive
• Pirruccello 2020 (n=36,041 UK Biobank): 28-SNP PRS LVESVi; HR 1.58 per SD for incident DCM; independent of age, sex, ancestry
• Pirruccello 2022 (n=41,135): RV trait GWAS (~1.1M SNPs); RVEF PRS most significant — HR 1.33 per SD for incident DCM, remains significant after LV PRS adjustment; replicated in MGB Biobank and BioBank Japan
• Garnier 2021: first DCM-specific PRS — 4 SNPs (BAG3/HSPB7/SLC6A6/SMARCB1); 8 risk alleles → OR 3.34; 1 risk allele → OR 0.21; European-only validation
• Jurgens 2024 (largest; n=955,733 discovery, 1,448,963 validation): GWAS+MTAG PRS DCM; OR 1.73 (European), 1.61 (African), 1.34 (Admixed-American) per SD; MTAG outperforms GWAS-only; predicts systolic HF after AF/HTN/MI; more predictive in genotype-negative cases (OR 2.14) vs genotype-positive (OR 1.48); improves discrimination over clinical models

4.3 Brugada Syndrome — Novel GWAS Insights

• SCN5A LOF variants explain only ~30% of BrS; largest GWAS (2820 cases/10,001 controls) identified 21 independent genome-wide significant SNPs across 12 loci, 10 previously unreported
• Most common hot spot: SCN5A–SCN10A locus (sodium channel predominance)
• Novel loci: HEY2 (cardiac transcription factor), MAPRE2 (microtubule/myofilament function) — both functionally validated in preclinical models as regulators of sodium current density
• BrS now reconceptualised as an oligogenic disease with polygenic risk-based inheritance as a common form

4.3 Brugada Syndrome — Polygenic Risk Scores

• Tadros 2019: 3-SNP PRS BrS; independently predicts ajmaline-induced Type I ECG (OR 1.14 per SD); C-statistic 0.68 alone → 0.741 with clinical variables (up to 99% sensitivity or 95% specificity at optimised thresholds)
• Wijeyeratne 2020: same 3-SNP PRS BrS in SCN5A-positive and negative families; OR per additional risk allele 1.46 total, 1.25 in SCN5A+, 2.71 in genotype-negative relatives; ≥4 risk alleles OR 22.29 in genotype-negative relatives; effect size highest for SCN5A LOF variants (OR 5.18)
• Barc 2022: 21-SNP PRS BrS; better predicts BrS in SCN5A genotype-negative; better predicts spontaneous vs drug-induced Type I ECG; does NOT predict lethal arrhythmic events; associated with AV conduction disorders (OR 1.16 per SD)
• Ishikawa 2024: 17-SNP cross-ancestry meta-analysis PRS; OR 2.12 per SD; top 2.5% have >6-fold greater odds vs middle quintile; European-based PRS robust in Japanese patients (shared polygenic underpinnings across ancestries)

4.4 LQTS — Novel GWAS Insights

• QT interval GWASs implicate KCNE1, KCNQ1, TBX5, and prominently NOS1AP (nitric oxide synthase 1 adaptor protein)
• NOS1AP variants: most prominent genetic modifiers of QTc prolongation and arrhythmic risk in both the general population and rare-variant LQTS carriers; confirmed mechanistically in hiPSC-CMs and mouse models via regulation of NOS1 activity
• Overlap with drug-induced LQTS (diLQT) — same loci modify susceptibility to QT-prolonging medications

4.4 LQTS — Polygenic Risk Scores

• Strauss 2017: 61-SNP PRS QT; explains up to 30% of diLQT; predicts drug-induced TdP
• Turkowski 2020: same 61-SNP PRS in LQT1/LQT2/LQT3 families; predicts higher QTc but NOT symptomatic status or serious arrhythmic events; resting QTc strongest predictor
• Lahrouchi 2020 (68-SNP PRS QT; European and Japanese): PRS higher in LQTS cases vs controls, notably higher in genotype-negative than genotype-positive patients — stronger polygenic basis in gene-negative LQTS
• Nauffal 2022 (1.1M SNP PRS QTc; 84,630 UK Biobank discovery; TOPMed multi-ancestry validation): each decile increase = 1.4 ms QTc prolongation; top decile = 8.7 ms longer QTc (similar magnitude to monogenic rare variants); lower predictive power in African-ancestry populations; ~75% of marked QTc prolongation lacks high PRS or rare pathogenic variant
• Lancaster 2024 (465,399-SNP PRS QTc-baseline): predicts magnitude of ΔQTc and likelihood of extreme response (≥60 ms) to sotalol challenge; independent after adjusting for age, sex, plasma sotalol, potassium, ancestry
• Simon 2024: OR 1.34 per SD for diLQT after high-risk drug exposure (significant in White patients; non-significant in African American/Asian subgroups, likely underpowered)

5. Conclusions and Future Directions

• Paradigm shift confirmed: inherited arrhythmias and cardiomyopathies exist on a spectrum influenced by rare variants, common variants, environmental exposures, and epigenetic regulation
• PRSs complement rare variant testing, particularly in gene-negative individuals and in carriers with variable expressivity
• Challenges: ancestry-specific performance (most training data European); absolute risk imprecision; non-coding GWAS hit functional validation; no prospective PRS-guided outcome trials yet
• Future: functional validation via hiPSC-CMs and CRISPR; diverse population inclusion in GWASs; longitudinal cohort studies to link polygenic risk with outcomes; multiancestry fine-mapping tools

Limitations of the document

• All four key GWAS/PRS datasets are predominantly European-ancestry; PRS performance is demonstrably reduced in African, East Asian, and Admixed-American populations
• No prospective RCTs testing whether PRS-guided management improves patient outcomes — all evidence is observational
• CPVT and ARVC/ACM excluded due to insufficient case numbers for GWAS; strongly monogenic diseases (e.g., CPVT) may have limited GWAS utility
• Most identified GWAS loci are in non-coding genome; functional validation remains challenging and resource-intensive
• PRS metrics continually evolve as GWAS sample sizes grow — reported ORs/HRs will change over time
• Industry relationships not disclosed for all studies cited

Key Concepts Mentioned

• concepts/Polygenic-Risk-Score — central focus; expanded to HCM/DCM/BrS/LQTS
• concepts/Modifier-Genes — NOS1AP and BAG3 common variants as GWAS-derived modifiers
• concepts/Cascade-Family-Screening — PRS complements genetic cascade in gene-negative relatives
• concepts/iPSC-Derived-Cardiomyocytes — functional validation of GWAS hits
• concepts/CRISPR-Cas9-in-Channelopathies — mentioned for validation of GWAS loci
• concepts/Pharmacological-Provocation-Testing — BrS PRS predicts ajmaline-induced Type I ECG

Key Entities Mentioned

• entities/HCM — GWAS novel loci (FHOD3/ALPK3/PLN) and PRS studies
• entities/DCM — GWAS loci (BAG3/HSPB7); inverse HCM-DCM loci; PRS validation across ancestries
• entities/Brugada-Syndrome — oligogenic reframing; 21 loci; HEY2/MAPRE2; PRS predicts phenotype not lethal events
• entities/Long-QT-Syndrome — NOS1AP as key modifier; diLQT PRS clinical utility
• entities/NOS1AP — most validated QTc modifier; mechanistically confirmed in hiPSC-CMs
• entities/MYBPC3 — HCM GWAS-validated; inverse DCM risk locus
• entities/MYH7 — common variation confirmed by HCM GWAS
• entities/SCN5A — BrS explains only 30%; SCN5A–SCN10A hotspot in GWAS
• entities/TTN — DCM; common variant modifiers interact with TTNtv penetrance
• entities/Mavacamten — mechanism context for inverse HCM-DCM therapeutic hypothesis

Wiki Pages Updated

• wiki/sources/gwas-arrhythmias-cmp-genes-2025 (created)
• wiki/sourceindex (updated)
• wiki/wikiindex (updated)