MR is a tool used in causal inference, and its three core assumptions are prerequisites for reliable causal inference. The genetic variant used as an instrument is strongly associated with the exposure, is independent of any confounders, and only affects the outcome through its effect on the exposure. In this study, by using SNPs as the IVs and excluding the bias caused by confounding factors, we elucidated the bidirectional causal relationship between MI and AF using the MR methods. We extracted data on MI and AF from database and ensured that all SNPs selected as IVs were statistically correlated with the exposure factor and not in LD, and we conducted horizontal pleiotropy analysis to exclude SNPs that might be related to confounding factors and eliminated weak IVs. We then harmonized the effect alleles in the GWAS data of the exposure and outcome factors and used five analysis methods to conduct MR, while also testing for heterogeneity and pleiotropy in the IVs. Finally, the study results showed a good causal effect of MI on AF, as evidenced by the consistency and monotonicity of the scatter plot, one-by-one analysis, and distribution of SNPs in the funnel plot. The IVW analysis also found a causal effect of AF on MI but the effect performance is not as good as that of MI on AF.
Our findings are consistent with previous observational studies that have shown a positive association between MI and AF(26). The reasons for MI leading to AF may be related to the following aspects. Experimental studies have found that when the perfusion of the right coronary artery and the left circumflex branch is significantly reduced, the excitability of the atrial myocardium is increased, and the conduction velocity is accelerated, which can cause re-entry and fibrillation(27). After MI occurs, the atrium is excessively stretched which increases the excitement of atrial myocytes and prolongs the length of the electrical conduction pathway, which is conducive to the formation of re-entry and fibrillation(28). In addition, MI-induced myocardial fibrosis also favors the formation of re-entry and fibrillation. Inflammation plays an important role in the occurrence and maintenance of AF. When MI occurs, a large amount of inflammatory factors are released. In the non-infarct and non-ischemic areas, the expression of inflammatory factors also increases, indicating that AF under acute MI conditions may be a marker of widespread inflammation(29). ln addition, the reduced parasympathetic tone, increased sympathetic nerve output, and hormones including B-type natriuretic peptide after MI may be related to the occurrence of AF(30, 31).
The Atherosclerosis Risk in Communities study found that AF patients have a 63% increased risk of acute MI(32). MI The reasons for AF leading to MI may be related to the following aspects. AF is associated with systemic signs of inflammation that could promote a pro-thrombotic state and eventually MI(33). AF and its risk factors, such as hypertension, diabetes, and dyslipidemia, can lead to platelet activation, which is a critical step in the process of MI(34, 35). When the heart rate of AF patients is too fast, it can lead to increased myocardial oxygen consumption and decreased coronary blood flow, which can easily cause type 2 MI due to an imbalance between oxygen supply and demand(36). The traction of the atrial muscle can significantly enhance sympathetic nerve activity, stimulate the release of catecholamines in the heart, and activate adrenergic receptors to cause vasoconstriction(37). However, most of studies are based on laboratory data or observational results. Our study provides stronger evidence for a causal relationship between the two conditions using a MR approach. Additionally, our study is the first to demonstrate a bidirectional causal relationship between MI and AF. The mechanisms underlying the causal relationship between MI and AF remains unclear. Further studies are needed to elucidate the exact mechanisms underlying the causal relationship between MI and AF.
This study has several advantages. MR is used to elucidate the bidirectional causal relationship between MI and AF, providing important clinical implications(38). Clinicians should be aware of the increased risk of AF in patients with a history of MI and consider appropriate management strategies to reduce the risk of AF. Conversely, patients with AF should be screened for underlying cardiovascular diseases, including MI. Additionally, our study reminds the importance of primary prevention of both MI and AF. Moreover, the reliability of causal association evidence based on MR studies is between that of observational epidemiological studies and experimental epidemiological studies(12). In other words, the evidence level of MR studies is higher than that of cohort studies and only slightly lower than that of RCTs studies. However, the high cost of RCTs makes them less feasible. MR can provide powerful evidence when RCTs cannot be implemented, for example, due to ethical reasons. MR studies can effectively overcome biases caused by confounding and reverse causality issues, providing reliable evidence for inferring the causal relationship between exposure factors and outcomes(39). In the MR analysis process, selecting SNPs as IVs can directly infer a causal relationship between exposure and outcome, as SNPs are randomly distributed to individuals through genetic inheritance and are not affected by external environmental and other confounding factors(40).
There are several limitations to our study. First, our study was conducted in individuals of European descent, and the generalizability of our findings to other populations is unclear(41). Second, MR assumes that genetic variants are not associated with confounding factors, and our results could be biased if this assumption is violated. Third, our study only examined the relationship between MI and AF and did not investigate the effect of treatment on either condition. Finally, AF and MI have specific subtypes, such as paroxysmal atrial fibrillation, persistent atrial fibrillation, type 1 MI, and type 2 MI. Due to limitations in the data source, causal relationship analysis cannot be performed on these subtypes.
In future studies, it will be important to investigate the mechanism underlying the causal relationship between MI and AF and to explore potential therapeutic strategies for reducing the risk of both conditions. Additionally, studies in diverse populations are needed to determine the generalizability of our findings. Finally, investigating the effect of treatment on both MI and AF could provide important insights into the management of these conditions.