Plasma urate and coronary heart disease: fingerprint match, but no smoking gun

Abstract

In The Lancet Diabetes & Endocrinology, Jon White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar consider the causal role of plasma urate in coronary heart disease, using the technique known as mendelian randomisation. They assess the association between genetic predictors of the risk factor (plasma urate) and the disease outcome (coronary heart disease), noting a statistically robust association between a genetic score based on 31 variants associated with plasma urate and coronary heart disease risk, with a straightforward application of Mendelian randomisation estimating an 18% (95% CI 8-29) relative increase in coronary heart disease risk per 1 SD increase in plasma urate. This positive finding from the mendelian randomisation investigation was in line with the observational epidemiological analysis also reported by the investigators. However, the association of the genetic score with the outcome seems to be at least partly explained by pleiotropic (off-target) associations of the genetic score, and the pattern of associations of the individual genetic variants does not show the characteristic dose–response association that would be expected if the genetic associations were solely driven by the effect of the risk factor on the outcome. Mendelian randomisation is a relatively new, but well established epidemiological technique to assess whether a modifiable risk factor is a worthwhile target for clinical or pharmacological intervention.2Davey Smith G Ebrahim S ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?.Int J Epidemiol. 2003; 32: 1-22Crossref PubMed Scopus (2488) Google Scholar, 3Burgess S Thompson SG Mendelian randomization: methods for using genetic variants in causal estimation. Chapman & Hall, London2015Crossref Scopus (195) Google Scholar An association between a genetic predictor of the risk factor and the outcome is more likely to reflect that the risk factor has a causal relation with the outcome, compared with an association of the risk factor itself from a traditional epidemiological analysis, for several reasons. First, risk factors tend to be mutually correlated. It is difficult to distinguish whether the risk factor itself is the cause, or if a correlated risk factor is driving the identified association with an outcome. By contrast, most genetic variants tend to be uncorrelated with conventional epidemiological risk factors.4Davey Smith G Lawlor D Harbord R Timpson N Day I Ebrahim S Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology.PLoS Med. 2007; 4: e352Crossref PubMed Scopus (329) Google Scholar Second, genetic variants are fixed at conception. Hence, a genetic association cannot be affected by external factors that lead to confounded associations. Finally, the associations of genetic variants are not subject to reverse causation. The gene can only ever be the cause, and never the effect. In an ideal mendelian randomisation analysis, the genetic variants have a clear biological link with the risk factor (for example, genetic variants in the CRP gene region for the analysis of C-reactive protein5CRP CHD Genetics CollaborationAssociation between C reactive protein and coronary heart disease: Mendelian randomisation analysis based on individual participant data.BMJ. 2011; 342: d548Crossref PubMed Scopus (210) Google Scholar), and are associated with the risk factor, but not with alternative risk factors. The analysis proceeds analogously to a randomised trial,6Hingorani A Humphries S Nature's randomised trials.Lancet. 2005; 366: 1906-1908Summary Full Text Full Text PDF PubMed Scopus (141) Google Scholar and compares groups of individuals with (on average) genetically raised levels of the risk factor versus those with genetically lowered levels to assess whether the risk factor is a cause of the outcome, and therefore a promising target for prioritisation in drug development. White and colleagues' analysis1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar is far from an ideal mendelian randomisation investigation. This is not a criticism, but a consequence of their investigation of a risk factor that is not a protein biomarker, and so does not have a coding gene region, as in the case of C-reactive protein. However, the consideration of multiple gene regions gives some robustness in the analysis, in that the consistency of any causal finding can be assessed. If multiple independent genetic variants associated with the risk factor are all concordantly associated with the outcome (as in the case of LDL cholesterol with coronary heart disease7Ference BA Yoo W Alesh I et al.Effect of long-term exposure to lower low-density lipoprotein cholesterol beginning early in life on the risk of coronary heart disease: a Mendelian randomization analysis.J Am Coll Cardiol. 2012; 60: 2631-2639Summary Full Text Full Text PDF PubMed Scopus (544) Google Scholar), the separate genetic associations each provide independent evidence for a causal effect of the risk factor on the outcome, strengthening the evidence for a causal finding. Another deficiency is that the composite genetic instrument considered by White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar is not solely associated with urate concentrations, but also shows associations with other risk factors, including blood pressure and lipid fractions. This finding is not necessarily a problem provided that the genetic associations with these factors are mediated by urate concentrations, and so one single causal pathway is represented. However, these associations might reflect pleiotropy of the genetic variants, meaning that there are multiple causal pathways from gene to disease, thereby violating the assumption of mendelian randomisation that an association between gene and disease reflects a causal effect of the risk factor. White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar show a statistically robust association between their 31 variant composite instrument and disease risk. However, the authors are to be commended in not stopping here, as others have done previously, but instead seeking to assess whether potential violations of the instrumental variable assumptions invalidate a causal interpretation for their findings. They use two main statistical approaches: multivariable mendelian randomisation8Burgess S Thompson S Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects.Am J Epidemiol. 2015; 181: 251-260Crossref PubMed Scopus (434) Google Scholar and Egger regression.9Bowden J Davey Smith G Burgess S Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression.Int J Epidemiol. 2015; 44: 512-525Crossref PubMed Scopus (1958) Google Scholar In multivariable mendelian randomisation, alternative risk factors are accounted for by adjusting for the genetic associations with these risk factors in the analysis model. In Egger regression, the assessment is not simply of whether genetic variants that are associated with the risk factor are also associated with the outcome, but whether there is a dose–response relation in these associations—that is, are genetic variants that are more strongly associated with the risk factor also more strongly associated with the outcome? Egger regression also encompasses a test for directional pleiotropy—whether this dose–response relation suggests that a variant having zero association with the risk factor also has zero association with the outcome (as expected if there is no pleiotropy, or balanced pleiotropy). Although multivariable mendelian randomisation does not suggest that measured pleiotropy completely accounts for the causal finding, Egger regression detects pleiotropy among the genetic variants, and provides a weaker causal estimate (a 5% [95% CI −8 to 20] relative increase coronary heart disease risk per 1 SD increase in plasma urate) that is compatible with the null once this pleiotropy is accounted for. Additionally, the genetic associations with the outcome are more variable than would be expected by chance alone; this heterogeneity suggests that the genetic associations with coronary heart disease risk are not solely mediated via plasma urate concentrations. The overall finding is not unequivocal. There is an undeniable association between genetic predictors of plasma urate concentrations and risk of coronary heart disease. However, there are suggestions that the association might represent pleiotropic effects of genetic variants included in the model, rather than a causal effect of urate. In summary, the evidence presented honestly by White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar suggests that urate lowering should be prioritised as a potential mechanism to improve cardiovascular outcomes, but without providing a smoking gun that puts the question of causality beyond doubt. I declare no competing interests. Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysisConventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. Full-Text PDF Open Access