Double trouble: T2DM genetic risk factors play a causal role in CAD.

Abstract

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide [[1]Finegold J.A. Asaria P. Francis D.P. Mortality from ischaemic heart disease by country, region, and age: statistics from World Health Organisation and United Nations.Int. J. Cardiol. 2013 Sep 30; 168: 934-945Abstract Full Text Full Text PDF PubMed Scopus (590) Google Scholar]. A major risk factor for CAD that has long been recognised is type 2 diabetes mellitus (T2DM). In addition, obesity, sedentary lifestyle and stress are common shared risk factors that contribute to the close association between T2DM and CAD. It is not yet obvious whether and to what degree this close association between the two conditions can be attributed to shared genetic risk factors. In contrast to other risk factors shared between T2DM and CAD, genetic risk factors offer the advantage of being unaffected by the various confounders affecting the association between these two conditions. T2DM and CAD both have polygenic inheritance and genetic studies have identified numerous distinct loci for both diseases. For CAD, over 50 single nucleotide polymorphisms (SNPs) have been identified in genome-wide association studies (GWAS), but only a few of these also associated with traditional CAD risk factors (lipid and blood pressure traits) and none of these were associated with glyco-metabolic traits at a genome-wide significant level (p < 5 × 10−8) [2Deloukas P. Kanoni S. Willenborg C. Farrall M. Assimes T.L. Thompson J.R. et al.Large-scale association analysis identifies new risk loci for coronary artery disease.Nat. Genet. 2013 Jan; 45: 25-33Crossref PubMed Scopus (1202) Google Scholar, 3Lieb W. Vasan R.S. Genetics of coronary artery disease.Circulation. 2013 Sep 3; 128: 1131-1138Crossref PubMed Scopus (42) Google Scholar, 4Schunkert H. Konig I.R. Kathiresan S. Reilly M.P. Assimes T.L. Holm H. et al.Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.Nat. Genet. 2011 Apr; 43: 333-338Crossref PubMed Scopus (1388) Google Scholar]. In the setting of T2DM, some components of the genetic predisposition to CAD appear to differ from those found in the general population. A variant related to the γ-glutamyl cycle of amino acid transport that had not been previously identified in the general population was found to be associated with CAD at a genome wide-level of significance in T2DM, representing a novel genetic risk factor for CAD in T2DM [[5]Qi L. Qi Q. Prudente S. Mendonca C. Andreozzi F. di P.N. et al.Association between a genetic variant related to glutamic acid metabolism and coronary heart disease in individuals with type 2 diabetes.JAMA. 2013 Aug 28; 310: 821-828Crossref PubMed Scopus (96) Google Scholar]. In this issue of Atherosclerosis, Jansen and colleagues used genetic markers as proxies for diabetes status to investigate whether T2DM – associated SNPs are also associated with increased risk of CAD in Caucasians, using the CARDIoGRAM Consortium dataset comprising ∼22,000 CAD cases and ∼65,000 controls [2Deloukas P. Kanoni S. Willenborg C. Farrall M. Assimes T.L. Thompson J.R. et al.Large-scale association analysis identifies new risk loci for coronary artery disease.Nat. Genet. 2013 Jan; 45: 25-33Crossref PubMed Scopus (1202) Google Scholar, 6Jansen H. et al.Genetic variants primarily associated with type 2 diabetes also affect coronary artery disease risk.Atherosclerosis. 2015; 241: 419-426Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar, 7Preuss M. Konig I.R. Thompson J.R. Erdmann J. Absher D. Assimes T.L. et al.Design of the Coronary ARtery DIsease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) Study: a Genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls.Circ. Cardiovasc. Genet. 2010 Oct; 3: 475-483Crossref PubMed Scopus (144) Google Scholar]. They argued that if T2DM is a causal risk factor for CAD, then genetic variants associated with T2DM would consequently be expected to be associated with CAD. They investigated whether the risk alleles of T2DM - associated SNPs previously identified in GWAS also increase the risk of CAD. A systematic literature search identified 48 variants currently known to be robustly associated with T2DM, of which 4 were excluded (on technical grounds or because of statistically – defined pleiotropy) and the remaining 44 were included in the study. For 29 of these variants, the T2DM risk allele gave an effect in the expected direction, (i.e. increased risk of CAD) and for ten SNPs this was statistically significant (p < 0.05). Of these, only the T2DM SNP at the chromosome 2q36.3 locus, which contains the insulin receptor substrate 1 (IRS1) and LOC64673 genes, remained significantly associated with CAD after correcting for multiple testing (p = 3.4 × 10−5, Bonferroni corrected threshold p value 0.0011). Interestingly, for two of the remaining 15 variants (CILP2 and ADAMTS9), the T2DM risk allele was significantly associated with a decreased risk of CAD. The expected T2DM SNP effects on CAD were then calculated from both the previously reported effect of each SNP upon risk of T2DM and the effect of T2DM on CAD risk, derived from the Framingham Heart Study data [8Dawber T.R. Kannel W.B. Revotskie N. Stokes III, J. Kagan A. Gordon T. Some factors associated with the development of coronary heart disease: six years' follow-up experience in the Framingham study.Am. J. Public Health Nations Health. 1959 Oct; 49: 1349-1356Crossref PubMed Google Scholar, 9Kannel W.B. McGee D.L. Diabetes and cardiovascular disease. The Framingham study.JAMA. 1979 May 11; 241: 2035-2038Crossref PubMed Scopus (3684) Google Scholar, 10Splansky G.L. Corey D. Yang Q. Atwood L.D. Cupples L.A. Benjamin E.J. et al.The Third Generation Cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: design, recruitment, and initial examination.Am. J. Epidemiol. 2007 Jun 1; 165: 1328-1335Crossref PubMed Scopus (583) Google Scholar]. This expected average odds ratio (OR) was calculated as 1.067 per risk allele. In contrast, the observed average increase in CAD risk per T2DM risk allele was modest with OR = 1.0076 (95% confidence intervals (CI): 1.0027 – 1.018), significantly lower than the authors had expected. Sensitivity analyses, which excluded all potentially pleiotropic SNPs, or included all SNPs, gave broadly similar results, suggesting that the SNPs were not acting in a pleiotropic manner through recognized risk factors other than diabetes mellitus. All 44 SNPs were then combined into a weighted risk score. The score was found to be associated with CAD in the German MI Family Studies I & II and the Wellcome Trust Case Control CAD Consortium (using individual level data from a total of 9,856 participants), where the highest quintile of the risk score distribution had 11% (95% CI: -2 – 26%) greater odds of CAD than the lowest quintile, with a linear increase in risk from bottom to top quintile. The risk score results calculated from summary CARDIoGRAM data were significantly associated with CAD risk: p = 5.8 × 10−5 for a one standard deviation increase in the risk score (OR 1.083, 95% CI: 1.042 – 1.126). As before however, the effect size was smaller than expected. These results differed from those seen with other risk factors for CAD, where SNPs which associate with CAD through a risk factor (e.g. LDL cholesterol) were observed to show a greater association with CAD than would have been expected on the basis of their effect on that risk factor. The association between the gene score and other relevant traits was investigated using the data from the KORA4 study [[11]Wichmann H.E. Gieger C. Illig T. KORA-gen–resource for population genetics, controls and a broad spectrum of disease phenotypes.Gesundheitswesen. 2005 Aug; 67: S26-S30Crossref PubMed Scopus (359) Google Scholar]. Intriguingly, the gene score was found to be associated with T2DM and BMI > 30 (a causal factor for T2DM) but not with lipid measures, smoking or hypertension, which are traditional risk factors for CAD. The study identified a modest but significant association of T2DM SNPs and of T2DM genetic risk score with CAD, consistent with T2DM SNPs being a weak factor contributing to the cause of CAD in Caucasians. In the prediction of T2DM itself, the addition of a 65 T2DM SNP weighted gene score to the phenotypic risk model has recently been shown to give an improvement of potential clinical relevance [[12]Talmud P.J. Cooper J.A. Morris R.W. Dudbridge F. Shah T. Engmann J. et al.Sixty-five common genetic variants and prediction of type 2 diabetes.Diabetes. 2014 Dec 4; (PMID: 25475436)https://doi.org/10.2337/db14-1504Crossref PubMed Scopus (74) Google Scholar]. However, the lower ORs and significance of T2DM SNPs for CAD mean that the T2DM genetic data are unlikely to be immediately helpful in CAD prediction. Rather they may highlight pathogenetic mechanisms leading to CAD. The T2DM SNPs associated with CAD were deduced to cause T2DM through a number of distinct metabolic processes, influencing beta cell function, insulin secretion, insulin sensitivity, obesity or acting through as yet unknown mechanisms (Fig. 1) [[6]Jansen H. et al.Genetic variants primarily associated with type 2 diabetes also affect coronary artery disease risk.Atherosclerosis. 2015; 241: 419-426Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar]. Therefore, analysis of the underlying datasets may identify significant enrichment of genes and their predicted proteins in key metabolic pathways and protein – protein interaction networks pertinent to the pathogenesis of CAD, including CAD in the setting of T2DM and preclinical diabetes. These predictions may be tested using transcriptomic, proteomic and metabolomic approaches and, if validated, may ultimately help to inform potential therapeutic strategies. However, many of the SNPs associated with T2DM are located in a linkage disequilibrium block containing many SNPs and they are often positioned in non-coding regions of the genome. Therefore, there remains much scope for mechanistic research to identify the functional SNP underlying the association and to investigate the means whereby the single nucleotide sequence change influences T2DM risk, whether by influencing the binding of a transcription factor or other protein and so affecting gene expression, or by altering epigenetic regulation, or through other effects. The role of gene – gene and gene – environmental effects also remain to be fully investigated. Another possible future application of this approach is the investigation of the role of T2DM - associated SNPs in CAD genetics in non – Caucasian populations. T2DM was once regarded as a disease of Western populations, but with changes in diet and decreased physical activity, it has become a worldwide public health crisis alongside obesity: the World Health Organization estimated that over 300 million adults will be affected with diabetes by the year 2025 [[13]King H. Aubert R.E. Herman W.H. Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections.Diabetes Care. 1998 Sep; 21: 1414-1431Crossref PubMed Scopus (5045) Google Scholar]. While several SNPs associated with T2DM in Europeans have been replicated in Middle Eastern and Asian populations, population-specific loci have also been identified; hence comparison of the genetic basis of T2DM and CAD in non-Europeans may identify the common and distinct pathways and protein–protein interaction networks contributing to T2DM and CAD in different populations [14Cho Y.S. Chen C.H. Hu C. Long J. Ong R.T. Sim X. et al.Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians.Nat. Genet. 2012 Jan; 44: 67-72Crossref Scopus (477) Google Scholar, 15Tabassum R. Chauhan G. Dwivedi O.P. Mahajan A. Jaiswal A. Kaur I. et al.Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21.Diabetes. 2013 Mar; 62: 977-986Crossref PubMed Scopus (129) Google Scholar, 16Al-Daghri N.M. Alkharfy K.M. Alokail M.S. Alenad A.M. Al-Attas O.S. Mohammed A.K. et al.Assessing the contribution of 38 genetic loci to the risk of type 2 diabetes in the Saudi Arabian Population.Clin. Endocrinol. (Oxf). 2014 Apr; 80: 532-537Crossref PubMed Scopus (30) Google Scholar]. Considering the role of Africa in the evolution of man and of all present-day human genomes, consistent with the observed low linkage disequilibrium which is potentially advantageous for genetic studies, there is a deficiency of GWAS for T2DM in continental African populations [[17]Tekola-Ayele F. Adeyemo A.A. Rotimi C.N. Genetic epidemiology of type 2 diabetes and cardiovascular diseases in Africa.Prog. Cardiovasc. Dis. 2013 Nov; 56: 251-260Abstract Full Text Full Text PDF PubMed Scopus (25) Google Scholar]. In summary, while the observed effects were modest, in aggregate the power afforded by the use of genetic markers showed significant association, albeit weaker than predicted, of T2DM SNPs and T2DM risk score with increased risk of CAD. These findings support the role of T2DM genetic risk variants as a weak but causal factor for CAD. Studying the shared genetic architecture of complex conditions such as T2DM and CAD using this type of approach in multiple populations will help elucidate common, as well as possibly novel, pathways and pathogenic mechanisms. Supported by an Egyptian Educational and Cultural Bureau Channel Scheme scholarship (IAYH), MRC CASE award (1270920) with Randox Laboratories (KEB) and BHF scholar position on BHF Chair award CH1992025 held by Professor Steve Humphries (JLB). Genetic variants primarily associated with type 2 diabetes are related to coronary artery disease riskAtherosclerosisVol. 241Issue 2PreviewThe mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well. Full-Text PDF