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104: Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation
Episode 104: Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation
In this episode of PaperCast Base by Base, we explore a large cross-ancestry study that integrates genome-wide association results with plasma proteomics to map genetic architecture, nominate causal pathways and proteins, and boost risk prediction for atrial fibrillation (AF).
Study Highlights:
The authors meta-analyzed AF across ancestries—more than two million participants overall—and reported 525 genome-wide significant loci among 168,007 AF cases, with PITX2 and ZFHX3 emerging as shared signals across populations. Gene prioritization and pathway enrichment reinforced core roles in muscle contraction and cardiogenesis and highlighted additional mechanisms such as TGF-β signaling and electrical coupling. Mendelian randomization linked multiple modifiable traits—adiposity measures, LDL cholesterol, type 2 diabetes, blood pressure, smoking, alcohol use, sedentary behavior, and insomnia—to AF risk. Protein-wide Mendelian randomization nominated 28 circulating proteins with potential causal effects on AF, several of which already have drugs in other indications. Finally, combining a polygenic risk score with a protein score substantially improved incident AF prediction, achieving an AUC of 0.823 and outperforming either component alone.
Conclusion:
Together, cross-ancestry genetics plus proteomics sharpen AF biology, spotlight prevention targets, and move multi-omic risk stratification closer to clinical application.
Reference:
Yuan S, Chen J, Ruan X, Li Y, Abramowitz SA, Wang L, Jiang F, Xiong Y, Levin MG, Voight BF, Gill D, Burgess S, Åkesson A, Michaëlsson K, Li X, Damrauer SM, Larsson SC. Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation. Nature Communications. 2025;16:6426. doi:10.1038/s41467-025-61720-2
License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/
On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.
View all episodes
By Gustavo BarraEpisode 104: Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation
In this episode of PaperCast Base by Base, we explore a large cross-ancestry study that integrates genome-wide association results with plasma proteomics to map genetic architecture, nominate causal pathways and proteins, and boost risk prediction for atrial fibrillation (AF).
Study Highlights:
The authors meta-analyzed AF across ancestries—more than two million participants overall—and reported 525 genome-wide significant loci among 168,007 AF cases, with PITX2 and ZFHX3 emerging as shared signals across populations. Gene prioritization and pathway enrichment reinforced core roles in muscle contraction and cardiogenesis and highlighted additional mechanisms such as TGF-β signaling and electrical coupling. Mendelian randomization linked multiple modifiable traits—adiposity measures, LDL cholesterol, type 2 diabetes, blood pressure, smoking, alcohol use, sedentary behavior, and insomnia—to AF risk. Protein-wide Mendelian randomization nominated 28 circulating proteins with potential causal effects on AF, several of which already have drugs in other indications. Finally, combining a polygenic risk score with a protein score substantially improved incident AF prediction, achieving an AUC of 0.823 and outperforming either component alone.
Conclusion:
Together, cross-ancestry genetics plus proteomics sharpen AF biology, spotlight prevention targets, and move multi-omic risk stratification closer to clinical application.
Reference:
Yuan S, Chen J, Ruan X, Li Y, Abramowitz SA, Wang L, Jiang F, Xiong Y, Levin MG, Voight BF, Gill D, Burgess S, Åkesson A, Michaëlsson K, Li X, Damrauer SM, Larsson SC. Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation. Nature Communications. 2025;16:6426. doi:10.1038/s41467-025-61720-2
License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/
On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.