Rare coding variant architecture and gene discovery from 130,000 sequenced cases of atrial fibrillation

Q: What are the key findings of this study?

Rare coding variants in 15 genes were significantly associated with atrial fibrillation risk (OR 1.2-4.4, P<2.5x10-6), explaining at least 2% of disease susceptibility.

Q: What is the clinical evidence from this study?

Study design: Case-Control. Population: Atrial fibrillation (n=984221). Intervention: Rare coding genetic variants vs. Non-carriers / referents without atrial fibrillation. Primary outcome: Exome-wide significant gene-level association with atrial fibrillation risk (OR 1.2 to 4.4 across 14 risk-increasing genes, p=<2.5x10-6).

Q: What does this research mean for the field?

Rare coding variants across 15 genes are significantly associated with increased risk of atrial fibrillation (OR 1.2-4.4), with ultra-rare protein-disrupting variants explaining at least 2% of disease susceptibility. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

Q: What question did this study set out to answer?

To identify rare coding genetic variants with large effects on atrial fibrillation risk and define their contribution to disease architecture.

Sean Joseph Jurgens; Nobuyuki Enzan; Ian R. Dinsmore; Seung Hoan Choi; J Z Luo; Alex Lipov; C Hartle; Xin Wang; Nicholas Marston; Lu-Chen C Weng; Giorgio E. M. Melloni; Brandon Chalazan; Michael Gray; James P. Pirruccello; Annette Diaz; Mark D. Chaffin; Aylin Ornelas-Loredo; Owen Tang; Faisal A Darbar; Shinwan Kany; Aenne S. von Falkenhausen; Alanna Morrison; Andrea Natale; Arnljot Tveit; Bastiaan Geelhoed; Brian E. Cade; David R. Van Wagoner; Doreen Haase; Elsayed Z. Soliman; Giovanni Davogustto; Hugh G Calkins; Jeffrey L. Anderson; Jennifer A. Brody; John Barnard; John E. Hokanson; Jonathan D. Smith; Joshua C. Bis; Kendra A. Young; L S B Johnson; D. Leann Long; Lorenz Risch; Lorne Gula; Lydia Coulter Kwee; Michael Kühne; Michael Preuss; Namrata Gupta; Navid A. Nafissi; Nicholas L. Smith; Peter M. Nilsson; Pim van der Harst; Quinn S. Wells; Renae Judy; Renate B. Schnabel; Renee Johnson; Roelof A. J. Smit; Stacey Gabriel; Stacey Knight; Tetsushi Furukawa; Yuan-I Min; Zachary T. Yoneda; Zachary Laksman; Álvaro Alonso; Bruce M. Psaty; Christine M. Albert; Dan E. Arking; Dan M. Roden; Daniel I. Chasman; Daniel James Rader; David Conen; David D. McManus; Diane Fatkin; Eric Boerwinkle; Gregory M. Marcus; Ingrid Christophersen; J. Gustav Smith; Jason Roberts; Laura Raffield; M.B. Shoemaker; M. H. Cho; Michael Cutler; Mina Chung; MORTEN SALLING OLESEN; Moritz F. Sinner; Nona Sotoodehnia; Paulus F. Kirchhof; Ruth J. F. Loos; Saman Nazarian; Sanghamitra Mohanty; Scott M. Damrauer; Stefan Kääb; Susan R. Heckbert; Susan S Redline; Svati Shah; Toshihiro Tanaka; Yusuke Ebana; Steven A. Lubitz; Kathryn L. Lunetta; Emelia J. Benjamin; Michiel Rienstra

doi:10.21203/rs.3.rs-9191644/v1

May 4, 2026Open Access

Rare coding variant architecture and gene discovery from 130,000 sequenced cases of atrial fibrillation

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Key result

Rare coding variants across 15 genes linked to ~20% higher risk of AF.

OR 1.2 to 4.4 across 14 risk-increasing genes
P<2.5x10-6
n=984,221

Why the study?

Rare coding genetic variants may exert large effects on common disease risk, yet understanding their contribution to AF architecture and their utility in gene prioritization remained limited by inadequate sample sizes.

Key Points

To identify rare coding genetic variants with large effects on atrial fibrillation risk and define their contribution to disease architecture.
Conducted a rare variant association study across 8 sequencing cohorts, analyzing over 1.1 million participants including 123,106 atrial fibrillation cases and 861,115 referents.
Tested up to 60 rare variant masks per gene incorporating protein-truncating and predicted deleterious missense variants across multiple allele frequency cutoffs, combining mask results using Cauchy distribution tests across 19,841 genes.
Replicated candidate findings in independent datasets from the All of Us Research Program (6,513 cases; 96,848 referents) and the Genomics England 100,000 Genomes Program (3,387 cases; 72,716 referents).
Identified 15 genes associated with atrial fibrillation at exome-wide significance (P < 2.5×10−6), including 5 genes not previously identified at exome-wide significance: RBM20, ACTC1, FBN1, FNIP1, and ZFP36L2.
Most significant masks displayed odds ratios from 1.2 to 4.4, with 7 of 14 testable genes replicating at P < 0.0035, including FNIP1 (OR 8.4, P = 4.4×10−5) and PLEC (OR 3.2, P = 2.5×10−3).
Ultra-rare protein-disrupting variants concentrated in a small group of large-effect genes accounted for at least 2% of atrial fibrillation susceptibility across European and African ancestry groups.

Study Design

Type

Case-Control (n=984,221)

Multicenter

Yes

Structured PICO

P

Population

984,221 sequenced participants (123,106 atrial fibrillation cases and 861,115 referents) from 8 population-based, health-system, and clinical trial cohorts.

C

Comparator

Referents without atrial fibrillation (n=861,115 in discovery, n=169,564 in replication)

O

Outcome

Atrial fibrillation (AF) status and exome-wide significant gene-based rare variant burden associations (Bonferroni-corrected threshold α=2.5×10^-6 across 19,841 genes)hard clinical

Main Result

Effect estimate: OR 1.2 to 4.4 across 14 risk-increasing genes

p-value: p=<2.5x10-6

This massive-scale rare variant association study identifies 15 genes (including 5 novel genes: RBM20, ACTC1, FBN1, FNIP1, and ZFP36L2) associated with atrial fibrillation through rare coding variation, demonstrating that ultra-rare protein-disrupting variants explain at least 2% of AF heritability.

Limitations

Discovery sample was predominantly of European ancestry (106,239 of 123,106 cases).
ZFP36L2 had insufficient carrier counts (<20) to be tested in the replication cohorts.
Relatively limited detection power of rare variant testing
Burden Score Heritability Regression (BHR) assumes that variant effects are homogeneous within gene masks
Limitations of missense prediction tools and variability in phenotypic effects conferred by damaging missense variants likely make missense heritability estimates lower-bounds
Large confidence intervals for burden heritability estimates in African-ancestry individuals

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Implication

Rare variant associations in 15 AF genes support expanded prioritization efforts; leaves open clinical utility for risk stratification or therapy.

Abstract

Rare coding genetic variants may exert large effects on risk of common disease, yet their contribution to disease architecture and their utility in gene prioritization remain limited by inadequate sample sizes. Here, we performed a massive-scale rare variant association study (RVAS), analyzing over 1.1 million sequenced participants among which 130,000 had atrial fibrillation (AF). Through a multi-mask burden testing approach, we identified 15 genes significantly associated with AF through rare large-effect variation. Integrative analyses revealed strong convergence between genes implicated by rare and common variation, and highlighted instances where RVAS data may aid in GWAS prioritization. Nevertheless, several RVAS genes were not among GWAS loci ( FAM189A2 , ACTC1 , FNIP1 , FBN1 ), or were not nominated through contemporary GWAS prioritization ( KDM5B , ZFP36L2 ). Finally, we observed that ultra-rare protein-disrupting variants - concentrated in a small number of large-effect size genes - explained at least 2% of AF susceptibility across European and African ancestry groups. These findings refine the genetic architecture of AF, while highlighting the value and cost of RVAS for genomic discovery in common disease.

Discussion

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Cite This Study

Jurgens et al. (2026) conducted a case-control in Atrial fibrillation (n=984,221). Rare coding genetic variants vs. Non-carriers / referents without atrial fibrillation was evaluated on Exome-wide significant gene-level association with atrial fibrillation risk (OR 1.2 to 4.4 across 14 risk-increasing genes, p=<2.5x10-6). Rare coding variants in 15 genes were significantly associated with atrial fibrillation risk (OR 1.2-4.4, P<2.5x10-6), explaining at least 2% of disease susceptibility.

synapsesocial.com/papers/6aeab4ff7ffc2bac0cab8011 https://doi.org/10.21203/rs.3.rs-9191644/v1

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Rare coding variant architecture and gene discovery from 130,000 sequenced cases of atrial fibrillation

Key Points

Study Design

Structured PICO

Main Result

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Rare coding variant architecture and gene discovery from 130,000 sequenced cases of atrial fibrillation

Key Points

Study Design

Structured PICO

Main Result

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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