In this study of three CHD case-control series, we found that five of twelve loci previously identified as predictors of CHD in GWAS of the general population also affected CHD risk in the presence of type 2 diabetes. We also showed that the genetic determinants of cardiovascular risk in diabetic patients might be different from the general population.
At all the five loci associated with CHD, the association went in the same direction in the three series of diabetic subjects and was consistent with that previously reported in the general population (5
). Some variability was observed in the strength of the associations among the three samples, although no significant evidence of heterogeneity was detected at any of the five loci, indicating that such differences were compatible with chance. At two of the CHD loci (rs4977574 and rs646776), the effect estimates obtained by a meta-analysis of our three studies were similar to those previously reported in the general population (8
), whereas at the other three loci (rs12526453, rs2259816, and rs11206510) effects appeared to be stronger ( and Supplementary Table 1
Our data indicate that these genetic markers, when considered jointly, may exert sizable influence on CHD risk, even though the individual genetic effects appear to be moderate. Individuals with more than eight risk alleles had almost a two-fold increase in CHD risk as compared to individuals with less than five risk alleles. Considering the relatively high proportion of the two extreme groups (19% vs 30%) in the diabetic population, screening the genetic susceptibility may provide important information to discriminate diabetic individuals at high-risk for cardiovascular complications from those at lower risk. An added value of the genetic markers is that it can offer information on CHD risk early in life when other cardiovascular risk factors such as hypertension, hypercholesterolemia, or poor glycemic control have yet to emerge. Such feature is especially attractive if we consider that type 2 diabetes is being diagnosed at an increasingly young age (26
The genetic markers significantly improved CHD risk prediction when added to conventional risk factors such as age, BMI, sex, smoking, degree of glycemic control, HDL, and history of hypertension and hypercholesterolemia. This effect, however, was modest. These results are in line with the previous observations that currently identified genetic variants might contribute modestly to the prediction of common disorders such as type 2 diabetes and cancer (27
). However, our data suggest that adding the genetic information to the model may lead to a 28% net gain with respect to moving the risk estimates towards the correct direction.
Our data suggest that the architecture of genetic susceptibility to CHD may be different in diabetic patients from that in the general population. Across all the three studies, two loci MRAS
consistently showed associations with CHD risk that went in the opposite direction than that in the general population, although such effects did not reach statistical significance in the combined analyses. Some other loci such as the haplotype system at the SLC22A3-LPAL2-LPA
) identified in the general population were not associated with CHD risk in diabetes. However, the frequencies of the previously reported predisposing haplotypes at the SLC22A3-LPAL2-LPA
locus were low in the study samples, ~0.02 for CCTC and 0.13–0.14 for CTTG, and the failure to replicate the associations might have been partly due to the inadequate power. The mechanisms underlying the different genetic effects in diabetic and non-diabetic populations are not clear. Our previous findings suggest hyperglycemia or other metabolic abnormalities of the diabetic milieu might modulate the genetic effects on cardiovascular risk in diabetes (18
). However, we cannot exclude the possibility that the observed differences between the diabetic patients in our study and those in the general population may be due to chance or to differences in study designs. Future adequately powered studies including both diabetic and non-diabetic subjects are warranted to verify our findings.
The differences in genetic effects between diabetic subjects and the general population, raise the hypothesis that genetic predictors of CHD might exist that are specific to diabetes. Identification of these genes will require GWAS that are specifically targeted to the diabetic population. The existence of other, as yet unidentified genetic predictors of CHD is supported by the fact that the currently identified genetic markers did not explain the predisposing effect of family history on CHD observed in our study. A similar pattern has been observed for other common disorders, such as type 2 diabetes itself (27
), prompting an assessment in the literature of the reasons that may account for such “missing heritability” (29
). In addition to the existence of as yet unidentified genetic factors, part of the familial clustering of CHD may be due to the sharing of environmental risk factors among family members. Such putative shared environment, however, if it plays a role, should act through mechanisms other than those of known risk factors, such as smoking, BMI, or dyslipidemia, since the predictive effect of family history was unaffected by adjustment for these variables.
Our study has several main strengths, namely the replication design with three independent cohorts of diabetic patients, a rigorous definition of CHD, and a sample size that was adequate for the detection of additive genetic effects of the magnitude reported in the literature. Some limitations, however, should be acknowledged. One limitation concerns the generalizability of our findings. The NHS and HPFS cohorts consist of health professionals and the JHS consists of patients receiving their care in an academic environment. Whether our findings can be extended to the general population of diabetic subjects remains to be determined. However, our previous genetic analyses in these cohorts are highly consistent with the observations in other populations (15
). Our study was also restricted to non-Hispanic Whites to avoid the possible confounding effect of race. Based on the known differences in LD patterns among races, other genetic markers may be more effective in capturing the predisposing effect of the loci described in this paper in other racial groups. Different loci might also be involved in the modulation of CHD risk in other races.
In conclusion, five loci recently found to be associated with CHD in GWAS of the general population were also associated with CHD among diabetic subjects. Our findings demonstrate similarities in the genetic susceptibility to CHD between the diabetic and non-diabetic populations, but also highlight possible peculiarities in the genetic architecture of susceptibility to CHD in diabetes.