| Literature DB >> 28669352 |
Thomas Bardin1,2,3,4, Pascal Richette5,6,7.
Abstract
Gout, the most prevalent inflammatory arthritis worldwide, is associated with cardiovascular and renal diseases, and is an independent predictor of premature death. The frequencies of obesity, chronic kidney disease (CKD), hypertension, type 2 diabetes, dyslipidaemias, cardiac diseases (including coronary heart disease, heart failure and atrial fibrillation), stroke and peripheral arterial disease have been repeatedly shown to be increased in gout. Therefore, the screening and care of these comorbidities as well as of cardiovascular risk factors are of outmost importance in patients with gout. Comorbidities, especially CKD, and drugs prescribed for their treatment, also impact gout management. Numerous epidemiological studies have shown the association of asymptomatic hyperuricaemia with the above-mentioned diseases and cardiovascular risk factors. Animal studies have also produced a mechanistic approach to the vascular toxicity of soluble urate. However, causality remains uncertain because confounders, reverse causality or common etiological factors might explain the epidemiological results. Additionally, these uncertainties remain unsolved despite recent studies using Mendelian randomisation or therapeutic approaches. Thus, large randomised placebo-controlled trials are still needed to assess the benefits of treating asymptomatic hyperuricaemia.Entities:
Keywords: Atrial fibrillation; Cardiovascular death; Colchicine; Coronary heart disease; Dyslipidaemia; Heart failure; Hypertension; Obesity; Type-2 diabetes; Urate-lowering drugs
Mesh:
Year: 2017 PMID: 28669352 PMCID: PMC5494879 DOI: 10.1186/s12916-017-0890-9
Source DB: PubMed Journal: BMC Med ISSN: 1741-7015 Impact factor: 8.775
Mendelian randomisation studies of the link between uricaemia and various cardiovascular diseases/risk factors with variants of SLCA9 as instrumental variables
| Author year [ref] | Instrumental variable | No. of participants | Population | Main results |
|---|---|---|---|---|
| McKeigues 2009 [ | SNP | 1017 | Orkney Islands Scottish | No effect on metabolic syndrome |
| Parsa 2012 [ | SNP | 516 | Amish | Increase in ambulatory SBP, with low- and high-salt diets |
| Palmer 2013 [ | SNP | >58,000 | Danes | No effect on BP or ischemic heart disease |
| Testa 2014 [ | SNP | 755 | Southern Italy | Prediction of CKD progression |
| Mallamaci 2015 [ | SNP | 449 | Southern Italy | Increase in office SBP and US carotid atherosclerosis features |
BP blood pressure, SBP systolic blood pressure, SNP single nucleotide polymorphism, CKD chronic kidney disease, US ultrasonography
Mendelian randomisation studies using genetic risk scores (GRSs) to explore causality between uricaemia and cardiovascular outcomes; positive studies
| Author year [ref] | GRS instrumental variable | No. of participants | Population | Account of pleiotropy | Main results |
|---|---|---|---|---|---|
| Kleber 2015 [ | 8 SNPs | 3315 | LURIC cohort German | No pleiotropy found | Association with cardiovascular mortality and sudden cardiac death |
| Yan 2016 [ | 17 SNPs | T2DM >3200 | China, Cross-sectional | Exclusion of 14 genes that are pleiotropic or in linkage disequilibrium | Association with diabetic macro-angiopathy |
GRS genetic risk score, SNP single nucleotide polymorphisms, T2DM type 2 diabetes mellitus
Mendelian randomisation studies using genetic risk scores (GRSs) to explore causality between uricaemia and cardiovascular outcomes; negative studies
| Author year (ref) | Instrumental variable (GRS) | Effect on SUA variance | No. of participants | Population | Accounted for pleiotropy | Main results |
|---|---|---|---|---|---|---|
| Stark 2009 [ | 10 SNPs | CAD: 1473; controls: 1241 | Germany | No | No association with CAD | |
| Yang 2010 [ | 8 SNPs | 6% | >50,000 | Europe and United States | No | Association with gout but not with BP, glucose level, CKD, CAD |
| Pfister 2011 [ | 8 SNPs | T2DM: 7504; | No association of the GRS SNPs with confounders | No association with diabetes | ||
| Hughes 2013 [ | 5 SNPs, urate transporters | 2% | >70,000 | ARIC and FIJS cohorts | Likely to explain the observation | Association with improved renal function |
| Rasheed 2014 [ | 5 SNPs, urate transporters | 2% | >70,000 | ARIC and FIJS cohorts | No | No causal link with triglycerides; triglycerides cause hyperuricaemia |
| Sedaghat 2015 [ | 30 SNPs | 2 mg/dL | 5791 | Rotterdam cohort | No | Negative association with SBP and DBP stronger in diuretic users |
| Sluijs 2015 [ | 24 loci | 4% | >41,500 | Europeans: EOIC interact and DIAGRAM cohorts | No pleiotropy except for triglycerides level | No association with diabetes |
| Yan 2016 [ | 17 SNPs | T2DM: >3200 | China | Exclusion of 14 pleiotropic genes or in linkage disequilibrium | Association with diabetic macro-angiopathy | |
| Keenan 2016 [ | 28 SNPs | T2DM: 65,000; controls: 68,000 | Europe | Exclusion of 14 pleiotropic genes | Association with gout | |
| White 2016 [ | 31 SNPs | >166,000 | 17 observational cohorts, mainly from the United Kingdom | Multivariate analysis | Multivariate OR 1–1.22; Egger OR 0.92–1.22 |
BP blood pressure, CAD cardiovascular disease, CHD cardiac heart disease, DBP diastolic blood pressure, GRS genetic risk score, HF heart failure, OR odds ratio, SBP systolic blood pressure, SNP single nucleotide polymorphism, SUA soluble uric acid IS ischemic stroke, T2DM type 2 diabetes mellitus