Plain language summary
Heart disease is a major cause of death worldwide. Individuals at risk are usually identified by the presence of diseases such as obesity and diabetes, and lifestyle factors such as smoking. However, there is a new understanding that when the body converts food into energy it creates by-products which might play an important role in the development of heart disease. Better understanding of these may be able to aid the identification of individuals at risk. This analysis of 7897 participants from 6 different cohort studies aimed to determine biomarkers associated with a heart attack. The results showed there were 56 metabolites associated with heart attack, some of which were associated with an increased occurrence and some a decreased occurrence. Most of the identified metabolites were lipids. Metabolites involved in bile acid production and amino acids were also identified. It was concluded that these metabolites may act as an indicator for individuals who are at risk of heart attack, however further research is needed. This study could be used by healthcare professionals to understand that the science behind the use of metabolites to indicate risk for heart attack is developing but still in its infancy.
Expert Review
Conflicts of interest:
None
Take Home Message:
- There are certain lipids and amino acids that are associated with the incidence of MI, but the use of these to identify people at risk of MI is still in its infancy
- Current proven strategies to identify those at risk should take precedence over the measurement, identification and use of metabolites. However, this area of research is of current interest.
Evidence Category:
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X
A: Meta-analyses, position-stands, randomized-controlled trials (RCTs)
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B: Systematic reviews including RCTs of limited number
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C: Non-randomized trials, observational studies, narrative reviews
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D: Case-reports, evidence-based clinical findings
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E: Opinion piece, other
Summary Review:
Introduction
Individuals at risk of cardiovascular disease are usually identified by the presence of comorbidities (e.g. obesity and diabetes), and lifestyle factors (e.g. smoking). However, there is a new understanding that certain metabolites may be associated with myocardial infarction (MI) and a better understanding of these may be able to aid the identification of individuals at risk. This meta-analysis aimed to determine metabolites associated with a MI.
Methods
- This meta-analysis of 6 cohort studies from the USA and Europe involved 7897 participants
- The primary outcome was the metabolites associated with incident MI
- The secondary outcome was the metabolites associated with prevalent MI
- A total of 1442 metabolites were measured.
Results
- There were 1373 MI cases from the studies
- The results showed that there were 56 metabolites associated with MI, 42 had a direct association and 14 had an inverse relationship
- Most of the identified metabolites were lipids (n=21) and amino acids (n=17)
- Of the lipids, 3-methyladipate and 1-palmitoyl-2-linoleoyl-glycerol (16:0/18:2) were associated with a higher risk of MI (HR estimates ranged from 1.28; 95% confidence interval (CI) = 1.13–1.44, P < 0.001 to 1.21; 95% CI = 1.08–1.35, P = <0.005 respectively)
- Of the amino acids, 4-hydroxyphenylacetate and cystathionine had the largest increase in risk (HR estimates 1.24; 95% CI = 1.11–1.38, P = <0.01 and 1.2; 95% CI = 1.07–1.35, P = <0.01 respectively)
- When the meta-analysis was stratified by race, it showed that out of the 56 metabolites identified, the majority were associated with white individuals (n=41), whereas only 18 were associated with black individuals. Of these, 3 were specific to individuals with an African ancestry.
Conclusion
- It was concluded that certain metabolites and their associated pathways may help to identify individuals at risk for MI before disease onset and lead to better prevention
Clinical practice applications:
- Research into metabolite association with increased risk of MI is still in its infancy and has little merit until we understand the mechanisms involved and the direction of causation
- It does however give an idea of the tools that may be developed in the future that will aid identification and help to develop prevention strategies
- The metabolites associated with MI may be racially specific and further understanding is needed on this. Hence the data should be interpreted with caution.
Considerations for future research:
- Whilst associations are indicative of relationships, they do not identify causation. Future research should focus on the pathways which may link the metabolites with MI
- Identifying these pathways will also help to develop prevention strategies pertinent to specific nutrients
- A better understanding of how metabolites may be racially distinct is also required.
Abstract
AIMS: Myocardial infarction (MI) is a major cause of death and disability worldwide. Most metabolomics studies investigating metabolites predicting MI are limited by the participant number and/or the demographic diversity. We sought to identify biomarkers of incident MI in the COnsortium of METabolomics Studies. METHODS AND RESULTS We included 7897 individuals aged on average 66 years from six intercontinental cohorts with blood metabolomic profiling (n = 1428 metabolites, of which 168 were present in at least three cohorts with over 80% prevalence) and MI information (1373 cases). We performed a two-stage individual patient data meta-analysis. We first assessed the associations between circulating metabolites and incident MI for each cohort adjusting for traditional risk factors and then performed a fixed effect inverse variance meta-analysis to pull the results together. Finally, we conducted a pathway enrichment analysis to identify potential pathways linked to MI. On meta-analysis, 56 metabolites including 21 lipids and 17 amino acids were associated with incident MI after adjusting for multiple testing (false discovery rate < 0.05), and 10 were novel. The largest increased risk was observed for the carbohydrate mannitol/sorbitol {hazard ratio [HR] [95% confidence interval (CI)] = 1.40 [1.26-1.56], P < 0.001}, whereas the largest decrease in risk was found for glutamine [HR (95% CI) = 0.74 (0.67-0.82), P < 0.001]. Moreover, the identified metabolites were significantly enriched (corrected P < 0.05) in pathways previously linked with cardiovascular diseases, including aminoacyl-tRNA biosynthesis. CONCLUSIONS In the most comprehensive metabolomic study of incident MI to date, 10 novel metabolites were associated with MI. Metabolite profiles might help to identify high-risk individuals before disease onset. Further research is needed to fully understand the mechanisms of action and elaborate pathway findings.
Methodological quality
Jadad score
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Allocation concealment
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