Myocardial infarction (MI) is the most common, acute manifestation of coronary artery disease (CAD), which is the most common cardiovascular disease [1]. Although MI incidence decreased slightly from 1999 to 2008 [2], 790,000 Americans have MI each year [3]. MI is associated with high mortality rate [4] and significant health care costs [5]. Thus, MI is a significant public health problem with a huge burden on society and the health care system. Traditional risk factors for CAD are well known and include hypertension, hyperlipidemia, diabetes, smoking, family history, age, and postmenopausal status [6]. Lately, novel risk factors for CAD have been identified, such as obesity, lack of physical activity, and stress [6]. Recognition of novel risk factors for MI can improve our understanding of the disease as well as offer new therapeutic targets, in addition to the currently effective strategies for primary and secondary prevention and treatment of MI.

Gout was associated with 3-fold higher prevalence of the metabolic syndrome [7]. Gout was also associated with a higher prevalence of risk factors for MI, namely hyperlipidemia, hypertension, obesity, and diabetes [8]. Gout was associated with a 1.6-fold higher risk of incident CAD, after adjusting for systolic blood pressure, total cholesterol, alcohol intake, body mass index, and diabetes [9]; but in a case–control study, gout was not significantly associated with incident CAD after matching for age, sex, and medical practice, and the relative risk (RR) of incident CAD was 0.98 [10]. In a study of a British Columbia linked database of people with no history of ischemic disease, gout was associated with significantly increased relative risk of MI in women (RR 1.39 (95% CI 1.20, 1.61)), but not in men (RR 1.11; 95% CI 0.99, 1.23; p for interaction = 0.003); these analyses were adjusted for age, comorbidities, and prescription drug use [11]. In men from the MRFIT study, gout was associated with an adjusted odds ratio (OR) of 1.26 for MI [12]. In a study of an all-England national linked dataset of hospital admissions and death records from 1999 to 2011, compared to people without gout, gout was associated with a RR of 1.82 (95% CI 1.78, 1.85) for MI; findings were replicated in a similar dataset in the Oxford Record Linkage Study spanning 1963–1998 [13]. In Taiwanese population, gout was associated with a hazard ratio (HR) of 1.23 for MI, after adjustment for age, sex, and history of diabetes mellitus, hypertension, coronary heart disease, stroke, and end-stage renal disease [14]. Thus, gout seems to be associated with a higher risk of MI, although two studies reported no association overall or in men [10, 11].

Very few data exist with regards to the risk of MI associated with gout in people aged 65 years or older. This is a population at high risk of MI and poor outcome from MI. More than a third of all MIs occur in people aged > 70 years [15, 16] and more than 80% of deaths from MI occur in those 65 years or older [17]. The US population that is aged 65 years or older is predicted to grow from 34.4 million in 2000 to > 70 million in 2030 [18]. Given the public health burden of MI and associated mortality in the adults aged 65 years and older, potential cardiac risk associated with gout needs to be examined. Therefore, we aimed to assess whether gout was associated independently with a higher risk of incident MI in the elderly, and whether this association varied by CAD risk factors, including hypertension, hyperlipidemia, and diabetes.

Sensitivity analyses additionally adjusting model 3 for obesity led to minimal/no attenuation of HR from 1.79 (95% CI 1.69, 1.91) to 1.80 (95% CI 1.69, 1.91). Sensitivity analyses expanding the ICD-9-CM code for incident MI to a more sensitive and less specific diagnostic code algorithm (code 410 or 412) revealed slightly lower HRs of incident CAD related to gout in models corresponding to the three models as shown in Table 2 above: 1.85 (95% CI 1.79, 1.92; model 4), 1.83 (95% CI 1.77, 1.89; model 5), and 1.59 (95% CI 1.54, 1.65; model 6).

We noted a strong, robust, independent association of gout with incident MI in adults aged 65 years or older, confirmed in multiple sensitivity analyses for the main analysis (models 2–3); confirmed further when we expanded the ICD-9 code from 410.x1 (models 1-3) to a more sensitive definition using ICD-9 codes 410 or 412 (models 4–6). This is an important finding that merits further discussion. In previous studies in the general population, gout was associated with a higher risk/hazard ratio of incident MI ranging from 1.23-fold to 1.82-fold in some studies [11–14], but not associated with higher risk in others [10, 25]. Studies differed in setting (cohort vs record-linkage), population (men vs women vs both), and confounders adjusted (cardiovascular risk factors included vs not). Our hazard ratio estimates in models 1–3 ranging from 1.79 to 2.08 for adults aged 65 years or older are slightly higher than previous estimates, since we were examining an older patient population.

Our study examined men and women 65 aged years or older in the USA, controlling for cardiovascular risk factors among other important factors. Estimates were robust in sensitivity analyses. The implications of our study are several. Using a representative US patient population, we provided estimates for gout and incident MI, which adds clarity to this important clinical question. An increased risk of incident MI in people with gout raises a question regarding the role of chronic inflammation and IL-1β pathways (via NLRP3 inflammasome activation) and CRP, hallmarks of gout [26, 27], in the pathogenesis of MI. The IL-1β pathway is shown to be important in the pathogenesis of MI [28–35] and as a downstream effect increases IL-6 levels, a potential causal pathway for atherothrombosis [36, 37]. Various pathogenic mechanisms common in people with CAD risk factors, such as cholesterol crystals, tissue hypoxia, and abnormal arterial flow patterns, can promote the activation of the NLRP3 inflammasome [38–41], which then activates IL-1β. CRP is elevated in CAD and contributes directly to atherosclerosis via leukocyte activation and endothelial dysfunction [42–44]. Our study findings generate the hypothesis that inflammatory pathways may be activated in the atherosclerotic plaque, which may then lead to MI. People with gout have upregulation of these inflammatory pathways, which might explain the increased risk of MI in gout, at least partially.  The role of key mechanisms of increased atherosclerosis in gout needs to be examined in basic and translational studies.

We noted that the association of gout with incident MI was stronger in people without each CAD risk factor (hypertension, hyperlipidemia, or diabetes) (HR 2.3–3.0) than in the presence of each CAD risk factor respectively (HR 1.6–1.7). This indicates that in patients with known CAD/MI risk factors, gout contributes much less to the risk of incident MI. Most differences were not only statistically significant, but also clinically meaningful. We also noted a similar trend in presence vs absence of heart failure and CAD. This observation is similar to that noted by Kuo et al. previously in a Taiwanese study [14]. We speculate two potential reasons for this observation: gout is associated with a 3-fold higher prevalence of the metabolic syndrome [7] that has features of hyperlipidemia, hyperglycemia, or obesity, and gout may be an early clinical manifestation of the metabolic syndrome; and episodic inflammation characteristic of gout flares may increase the MI risk, especially in those without other CAD risk factors.

In a subgroup analysis, we found that gender made little difference to the association of gout with incident MI in the elderly. Previous studies found higher risk of MI with gout in UK women compared to men (2.08 (95% CI 2.01, 2.16) vs 1.73 (95% CI 1.69, 1.77), respectively) [13], considering all age groups (mean age 70 years), or a trend of higher risk of MI with gout in Canadian women compared to men (1.11 (95% CI 0.99, 1.23); p = 0.003 for interaction by gender) [11] in the elderly with a mean age of 75 years. The mean age of people in our study is similar to these studies at 73 years. The reasons for differences in the findings is likely related to differences in country setting (USA vs UK vs Canada), confounders adjusted in the analyses (cardiovascular diseases, cardiovascular medications, and gout medications vs neither vs cardiovascular medications only), the outcome definition, the underlying conditions (none vs. none vs. musculoskeletal disease), study sample (all Medicare recipients vs. all hospital admissions for gout vs. all elderly) and the population examined in each study (limited to only people aged 65 years or older vs all ages vs. women 65 years or older).

Our study has several limitations, which must be considered while interpreting the findings. We used data from Americans aged 65 years or older, and therefore the generalizability of these findings to younger people is uncertain. Diagnostic misclassification may have occurred despite our use of validated algorithms; this would bias our study findings toward the null, making our findings conservative (i.e., we may have missed some associations). Residual confounding is still possible, given an observational study design, despite the fact that we controlled for several potential confounders. We adjusted for several potential confounders including cardiovascular drugs, but we did not adjust for aspirin, nonsteroidal anti-inflammatory drug (NSAID) use, alcohol use, smoking, or exercise, which may have led to some residual confounding. Adjustment for aspirin and NSAID use was considered but not done, since most NSAID and aspirin use in this age group is over the counter rather than prescription use [45, 46]. Over-the-counter medication use is not captured in the Medicare claims data, which would introduce misclassification bias. We are also unaware of the differential rate/pattern of the use of aspirin or NSAID by gout status, for primary or secondary prevention of CAD. Our study has several strengths. Inclusion of medications for cardiovascular disease and gout strengthens the analyses, since these medications might be imperfect surrogates of disease severity which Medicare data lack and have independent protective effects related to MI risk, but also in some cases may be indicative of the presence of a disease in the absence of an ICD-9-CM code and may reduce misclassification bias. We used a representative sample of US adults aged 65 years or older, had an adequate number of events for analyses, and conducted multiple sensitivity analyses to test the robustness of findings.

This study showed an association of gout with incident MI in adults aged 65 years or older, independent of the traditional CAD risk factors. The MI risk associated with gout was stronger in people without CAD risk factors compared to people with CAD risk factors, and the risk was increased 2-fold or higher in both groups. Chronic inflammation, a hallmark of gout, is implicated in the pathogenesis of incident MI [28]. Future studies should evaluate the mechanisms for this disease association, and evaluate to what extent this association is due to chronic inflammation versus other potential pathways.