1. Director Medical Sciences Division, Ramos Law, Northglenn, CO 80260; 2. Chief Science Officer, Neuroganics, Northglenn, CO 80260
email: DrDon@neuroganicslabs.com
Synopsis: Miyazawa, K., Ito, K., Ito, M. et al. Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction. Nat Genet (2023).
Atrial fibrillation (AF) is a common cardiac arrhythmia that affects millions of people worldwide. It is characterized by an irregular and rapid heartbeat, which increases the risk of stroke, heart failure, and other complications. Despite its high heritability, our understanding of the genetic factors that contribute to AF is still incomplete. A recent genome-wide association study (GWAS) in the Japanese population has advanced our knowledge of the genetic architecture of AF and has identified new susceptibility loci and the development of a polygenic risk score (PRS) that can predict the risk of cardiovascular and stroke mortalities in AF patients.
Synopsis
The study involved 9,826 cases among 150,272 individuals and found that rare, East Asian-specific variants were associated with AF. A cross-ancestry meta-analysis of more than one million individuals, including 77,690 cases, identified 35 new loci associated with AF. The study also identified IL6R as a putative causal gene, suggesting that immune responses may be involved in the development of AF.
One of the most significant findings of the study was the development of a polygenic risk score (PRS) that can predict the risk of cardiovascular and stroke mortalities in AF patients. The PRS can also help identify individuals with undiagnosed AF who are at risk of cardioembolic stroke. This is particularly important because AF is often asymptomatic, and many people may not be aware that they have the condition.
The study identified several specific genes that are associated with AF, including SYNE1 and FGF13. SYNE1 is involved in the nuclear envelope protein complex, and mutations in this gene have been linked to muscle dystrophy and dilated cardiomyopathy. FGF13 is involved in cell survival and is a direct binding partner of the main cardiac sodium channel (NaV1.5). Defects in FGF13 have been linked to conduction disturbance in cardiomyocytes, which can lead to AF.
The study suggests that the genetic architecture of AF is complex, and multiple genes are involved in its development. However, it also provides new insights into the biological mechanisms underlying AF and has the potential to improve the diagnosis and treatment of the condition.
Health Implications
For individuals who are at risk of AF, there are several things that can be done to decrease the risk of stroke or clots. This includes taking medications to control blood pressure and cholesterol, maintaining a healthy diet and exercise routine, and avoiding alcohol and tobacco use. It is essential to be aware of the potential risk and monitor heart health closely and for those carrying the risk markers to be vigilant about their heart health. It would be prudent to practice regular check-ups with a cardiologist, healthy lifestyle choices, and closely monitor symptoms suggestive of AF. Lastly, it is important to discuss medications to reduce the risk of stroke and understand that having risk genes does not mean AF is certain because there are many other factors that contribute to AF.
In conclusion, Miyazawa et al., has advanced our understanding of novel genetic factors that contribute to AF and has developed a PRS that can predict the risk of cardiovascular and stroke mortalities in AF potential to improve the diagnosis and treatment of the condition.
| Variant | Gene | Effect Size | Frequency | Significance |
|---|---|---|---|---|
| rs6841049_G | LIN54 | -0.04 | 57% | 6.01 x 10-8 |
| rs4896104_T | ALDH8A1 | -0.04 | 56% | 7.51 x 10-8 |
| rs12209223_A | FILIP1 | 0.06 | 11% | 7.42 x 10-8 |
| rs8096658_G | NFATC1 | 0.04 | 49% | 1.33 x 10-7 |
| rs139557_G | MEI1 | 0.04 | 68% | 1.69 x 10-7 |
| rs517938_T | SESN3 | -0.04 | 67% | 1.80 x 10-7 |
| rs3746471_A | KIAA1755 | 0.03 | 47% | 2.30 x 10-7 |
| rs1886512_A | KLF12 | 0.04 | 36% | 2.81 x 10-7 |
| rs10500790_A | SPON1 | 0.03 | 38% | 3.45 x 10-7 |
| rs1933723_A | PALMD | 0.04 | 68% | 5.21 x 10-7 |
| rs11881441_C | NOP53 | 0.04 | 66% | 5.93 x 10-7 |
| rs9284324_A | MYH11 | -0.04 | 31% | 1.22 x 10-6 |
| rs12512502_C | DCK | -0.03 | 62% | 1.27 x 10-6 |
| rs17118812_C | PFDN1 | 0.04 | 28% | 1.86 x 10-6 |
| rs11527634_T | CCDC7 | 0.05 | 11% | 1.92 x 10-6 |
| rs10845620_A | GPR19 | 0.05 | 13% | 2.32 x 10-6 |
| rs75414548_A | NDUFS5 | 0.07 | 8% | 4.35 x 10-6 |
| rs17430357_T | EXT1 | 0.04 | 18% | 4.85 x 10-6 |
| rs7126870_T | STIM1 | -0.03 | 49% | 5.10 x 10-6 |
| rs17303101_A | TRIM32 | 0.03 | 29% | 5.27 x 10-6 |
| rs1769758_T | ZMIZ1 | 0.03 | 49% | 5.38 x 10-6 |
| rs4970418_C | PLEKHN1 | 0.04 | 17% | 7.54 x 10-6 |
| rs11841562_A | MICU2 | 0.03 | 40% | 8.82 x 10-6 |
| rs76460895_A | TMEM273 | 0.07 | 5% | 1.25 x 10-5 |
| rs7766436_T | HDGFL1 | 0.03 | 28% | 2.04 x 10-5 |
| rs2727757_G | CDHR3 | 0.03 | 27% | 5.49 x 10-5 |
| rs2629755_G | HCFC2 | -0.04 | 14% | 6.71 x 10-5 |
| rs9782984_C | SPEN | -0.06 | 88% | 8.40 x 10-5 |
| rs5754508_G | CCDC116 | 0.04 | 19% | 1.00 x 10-4 |
Table 1. Novel Gene Variant, Gene, Effect Size, Frequency, and Significance for variants associated with increased or decreased risk of Atrial Fibrillation. (Miyazawa, K., Ito, K., Ito, M. et al. 2023).
- References
Miyazawa, K., Ito, K., Ito, M. et al. Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction. Nat Genet (2023). https://doi.org/10.1038/s41588-022-01284-9