Individual and cumulative effect of type 2 diabetes genetic susceptibility variants on risk of coronary heart disease

Radiomics analysis of pericoronary adipose tissue based on plain CT for preliminary screening of coronary artery disease in patients with type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with a markedly increased prevalence of coronary artery disease (CAD). Radiomics features of pericoronary adipose tissue (PCAT) were correlated with inflammation, which may have potential value in the prediction of CAD.

PURPOSE

To determine whether radiomics analysis of PCAT captured by plain computed tomography (CT) could predict obstructive CAD in patients with T2DM.

MATERIAL AND METHODS

The study included 155 patients with T2DM with suspected CAD between January 2020 and December 2021. Volumes of right coronary artery of 10-50 mm were delineated in the plain CT to extract radiomics features and PCAT CT attenuation (PCATa). Least absolute shrinkage and selection operator was used to select the useful radiomics features to calculate the radiomics score (Rad-score). Univariate and multivariable logistic regression were applied to select independent predictors. The predictive performance was evaluated by the area under the receiver operating characteristics curve (AUC).

RESULTS

Rad-score (per 0.1 increments: odds ratio [OR] = 1.297; P < 0.001), coronary artery calcium score (CACS) (OR = 1.003; P = 0.037), and sex (OR = 3.245; P = 0.026) were identified as independent predictors for obstructive CAD. Rad-score (AUC = 0.835) outperformed CACS (AUC = 0.780), sex (AUC = 0.665), and PCATa (AUC = 0.550) in predicting obstructive CAD (P = 0.017 and 0.003 for Rad-score vs. sex and PCATa, respectively); however, the improvement between Rad-score and CACS had no statistical significance (P = 0.490).

CONCLUSION

Plain CT-derived Rad-score may be used as a preliminary screening tool for obstructive CAD in patients with T2DM.

Non-contrast CT-based radiomics nomogram of pericoronary adipose tissue for predicting haemodynamically significant coronary stenosis in patients with type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) patients have a higher incidence of coronary artery disease than the general population. The aim of this study was to develop a radiomics nomogram of pericoronary adipose tissue (PCAT) based on non-contrast CT to predict haemodynamically significant coronary stenosis in T2DM patients.

METHODS

The study enrolled 215 T2DM patients who underwent non-contrast CT and coronary computed tomography angiography (CCTA). CCTA derived fractional flow reserve (FFR_CT) ≤ 0.80 was defined as hemodynamically significant stenosis.1691 radiomics features were extracted from PCAT on non-contrast CT. Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to select useful radiomics features to construct Radscore. Logistic regression was applied to select significant factors among Radscore, fat attenuation index (FAI) and coronary artery calcium score (CACS) to construct radiomics nomogram.

RESULTS

Radscore [odds ratio (OR) = 2.84; P < 0.001] and CACS (OR = 1.00; P = 0.023) were identified as independent predictors to construct the radiomics nomogram. The radiomics nomogram showed excellent performance [training cohort: area under the curve (AUC) = 0.81; 95% CI: 0.76-0.86; validation cohort: AUC = 0.83; 95%CI: 0.76-0.90] to predict haemodynamically significant coronary stenosis in patients with T2DM. Decision curve analysis demonstrated high clinical value of the radiomics nomogram.

CONCLUSION

The non-contrast CT-based radiomics nomogram of PCAT could effectively predict haemodynamically significant coronary stenosis in patients with T2DM, which might be a potential noninvasive tool for screening of high-risk patients.

A diabetes-associated genetic variant is associated with diastolic dysfunction and cardiovascular disease

Aims

Although the epidemiological association between Type 2 diabetes and congestive heart failure (CHF) as well as cardiovascular disease (CVD) is well established, associations between diabetes‐related single‐nucleotide polymorphisms (SNPs), CHF, and CVD have been surprisingly inconclusive. Our aim is to examine if 43 diabetes‐related SNPs were associated with prevalent diastolic dysfunction assessed by echocardiography and incident CVD and/or CHF.

Methods and results

We genotyped 43 SNPs that previously reported genome‐wide significant associations with Type 2 diabetes, in 1444 subjects from the population‐based Malmö Preventive Project‐Re‐examination Study (MPP‐RES) (mean age 68 years; 29% women, 36% prevalent diabetes) (discovery cohort) and in 996 subjects from the VARA cohort (mean age 51 years, 52% women, 7% prevalent diabetes) (replication cohort). Multivariable logistic regression was assessed. Genetic variants that reached significant association with diastolic dysfunction in both cohorts were then analysed for association with incident CVD/CHF in a larger sample of the MPP‐RES cohort (3,407 cases and 11,776 controls, median follow up >30 years) using Cox regression analysis. A common variant at the HNF1B [major allele (T) coded, also the risk allele for diabetes] was the only SNP associated with increased risk of prevalent diastolic dysfunction in both the discovery [MPP‐RES; odds ratio (OR) 1.21, P = 0.024), and the replication cohort (VARA; OR 1.38, P = 0.042]. Cox regression analysis showed that carriers of the T‐allele of rs757210 had an increased risk of future CVD (HR 1.05, P = 0.042). No significant association was seen for incident CHF.

Conclusions

The diabetes susceptibility locus HNF1B is associated with prevalent diastolic dysfunction in two independent Swedish cohorts as well as incident cardiovascular disease.

Coagulatory Defects in Type-1 and Type-2 Diabetes

Diabetes (both type-1 and type-2) affects millions of individuals worldwide. A major cause of death for individuals with diabetes is cardiovascular diseases, in part since both types of diabetes lead to physiological changes that affect haemostasis. Those changes include altered concentrations of coagulatory proteins, hyper-activation of platelets, changes in metal ion homeostasis, alterations in lipid metabolism (leading to lipotoxicity in the heart and atherosclerosis), the presence of pro-coagulatory microparticles and endothelial dysfunction. In this review, we explore the different mechanisms by which diabetes leads to an increased risk of developing coagulatory disorders and how this differs between type-1 and type-2 diabetes.

Genetic predisposition to type 2 diabetes is associated with severity of coronary artery disease in patients with acute coronary syndromes

Background

Accumulating evidence has shown that type 2 diabetes (T2D) and coronary artery disease (CAD) may stem from a ‘common soil’. The aim of our study was to examine the association between genetic predisposition to T2D and the risk of severe CAD among patients with acute coronary syndromes (ACS) undergoing angiography.

Methods

The current case–control study included 1414 ACS patients with at least one major epicardial vessel stenosis > 50% enrolled in the ACS Genetic Study. The severity of CAD was quantified by the number of coronary arteries involved. Genetic risk score (GRS) was calculated using 41 common variants that robustly associated with increased risk of T2D in East Asians. Logistic regression models were used to estimate the association between GRS and the severity of CAD.

Results

In the age-, sex- and BMI-adjusted model, each additional risk allele was associated with a 6% increased risk of multi-vessel disease (OR = 1.06, 95% CI 1.02–1.09). The OR was 1.43 (95% CI 1.08–1.89) for the risk of severe CAD when comparing the extreme tertiles of T2D-GRS. The association was not reduced after further adjustment for conventional cardiovascular risk factors. Additional adjustment for T2D status in our regression model attenuated the association by approximately one quarter. In subgroup analysis, the strengths of the associations between GRS and the severity of CAD were broadly similar in terms of baseline demographic information and disease characteristics.

Conclusions

Our data indicated that genetic predisposition to T2D is associated with elevated risk of severe CAD. This association revealed a possible causal relationship and is partially mediated through diabetic status.

Type 2 Diabetes Mellitus and Cardiovascular Disease: Genetic and Epigenetic Links

Type 2 diabetes mellitus (DM) is a common metabolic disorder predisposing to diabetic cardiomyopathy and atherosclerotic cardiovascular disease (CVD), which could lead to heart failure through a variety of mechanisms, including myocardial infarction and chronic pressure overload. Pathogenetic mechanisms, mainly linked to hyperglycemia and chronic sustained hyperinsulinemia, include changes in metabolic profiles, intracellular signaling pathways, energy production, redox status, increased susceptibility to ischemia, and extracellular matrix remodeling. The close relationship between type 2 DM and CVD has led to the common soil hypothesis, postulating that both conditions share common genetic and environmental factors influencing this association. However, although the common risk factors of both CVD and type 2 DM, such as obesity, insulin resistance, dyslipidemia, inflammation, and thrombophilia, can be identified in the majority of affected patients, less is known about how these factors influence both conditions, so that efforts are still needed for a more comprehensive understanding of this relationship. The genetic, epigenetic, and environmental backgrounds of both type 2 DM and CVD have been more recently studied and updated. However, the underlying pathogenetic mechanisms have seldom been investigated within the broader shared background, but rather studied in the specific context of type 2 DM or CVD, separately. As the precise pathophysiological links between type 2 DM and CVD are not entirely understood and many aspects still require elucidation, an integrated description of the genetic, epigenetic, and environmental influences involved in the concomitant development of both diseases is of paramount importance to shed new light on the interlinks between type 2 DM and CVD. This review addresses the current knowledge of overlapping genetic and epigenetic aspects in type 2 DM and CVD, including microRNAs and long non-coding RNAs, whose abnormal regulation has been implicated in both disease conditions, either etiologically or as cause for their progression. Understanding the links between these disorders may help to drive future research toward an integrated pathophysiological approach and to provide future directions in the field.

Association of a 62 Variants Type 2 Diabetes Genetic Risk Score With Markers of Subclinical Atherosclerosis: A Transethnic, Multicenter Study

BACKGROUND

Type 2 diabetes mellitus (T2D) and cardiovascular disease share risk factors and subclinical atherosclerosis (SCA) predicts events in those with and without diabetes mellitus. T2D genetic risk may predict both T2D and SCA. We hypothesized that greater T2D genetic risk is associated with higher extent of SCA.

METHODS AND RESULTS

In a cross-sectional analysis, including ≤9210 European Americans, 3773 African Americans, 1446 Hispanic Americans, and 773 Chinese Americans without known cardiovascular disease and enrolled in the Framingham Heart Study, Coronary Artery Risk Development in Young Adults, Multi-Ethnic Study of Atherosclerosis, and Genetic Epidemiology Network of Arteriopathy studies, we tested a 62 T2D-loci genetic risk score for association with measures of SCA, including coronary artery or abdominal aortic calcium score, common and internal carotid artery intima-media thickness, and ankle-brachial index. We used ancestry-stratified linear regression models, with random effects accounting for family relatedness when appropriate, applying a genetic-only (adjusted for sex) and a full SCA risk factors-adjusted model (significance, P<0.01=0.05/5, number of traits analyzed). An inverse association with coronary artery calcium score in Multi-Ethnic Study of Atherosclerosis Europeans (fully-adjusted P=0.004) and with common carotid artery intima-media thickness in the Framingham Heart Study (P=0.009) was not confirmed in other study cohorts, either separately or in meta-analysis. Secondary analyses showed no consistent associations with β-cell and insulin resistance genetic risk sub-scores in the Framingham Heart Study and in the Coronary Artery Risk Development in Young Adults.

CONCLUSIONS

SCA does not have a major genetic component linked to a burden of 62 T2D loci identified by large genome-wide association studies. A shared T2D-SCA genetic basis, if any, might become apparent from better functional information about both T2D and cardiovascular disease risk loci.

Plasma extracellular superoxide dismutase concentration, allelic variations in the SOD3 gene and risk of myocardial infarction and all-cause mortality in people with type 1 and type 2 diabetes

BACKGROUND

Oxidative stress is involved in development of diabetes complications. Extracellular superoxide dismutase (EC-SOD, SOD3) is a major extracellular antioxidant enzyme and is highly expressed in arterial walls. Advanced oxidation protein products (AOPP) and 8-iso-prostaglandin (isoprostane) are markers of oxidative stress. We investigated association of SOD3 gene variants, plasma concentrations of EC-SOD, AOPP and isoprostane with myocardial infarction and mortality in diabetic patients.

METHODS

We studied three cohorts designed to evaluate the vascular complications of diabetes: the GENEDIAB study (469 participants with type 1 diabetes at baseline; follow-up data for 259 participants), the GENESIS study (603 participants with type 1 diabetes at baseline; follow-up data for 525 participants) and the DIABHYCAR study (3137 participants with type 2 diabetes at baseline and follow-up). Duration of follow-up was 9, 5, and 5 years, respectively. Main outcome measures were incidence of myocardial infarction, and cardiovascular and total mortality during follow-up. Six single nucleotide polymorphisms in the SOD3 locus were genotyped in the three cohorts. Plasma concentrations of EC-SOD, AOPP, and isoprostane were measured in baseline samples of GENEDIAB participants.

RESULTS

In GENEDIAB/GENESIS pooled cohorts, the minor T-allele of rs2284659 variant was inversely associated with the prevalence at baseline (Odds Ratio 0.48, 95% CI 0.29-0.78, p = 0.004) and the incidence during follow-up of myocardial infarction (Hazard Ratio 0.58, 95% CI 0.40-0.83, p = 0.003) and with cardiovascular (HR 0.33, 95% CI 0.08-0.74, p = 0.004) and all-cause mortality (HR 0.44, 95% CI 0.21-0.73, p = 0.0006). The protective allele was associated with higher plasma EC-SOD and lower plasma AOPP concentrations in GENEDIAB. It was also inversely associated with incidence of myocardial infarction (HR 0.75, 95% CI 0.59-0.94, p = 0.01) and all-cause mortality (HR 0.87, 95% CI 0.79-0.97, p = 0.008) in DIABHYCAR.

CONCLUSIONS

The T-allele of rs2284659 in the promoter of SOD3 was associated with a more favorable plasma redox status and with better cardiovascular outcomes in diabetic patients. Our results suggest that EC-SOD plays an important role in the mechanisms of vascular protection against diabetes-related oxidative stress.

Insights into the genetic basis of type 2 diabetes

Type 2 diabetes is one of the most common complex diseases, of which considerable efforts have been made to unravel the pathophysiological mechanisms. Recently, large‐scale genome‐wide association (GWA) studies have successfully identified genetic loci robustly associated with type 2 diabetes by searching susceptibility variants across the entire genome in an unbiased, hypothesis‐free manner. The number of loci has climbed from just three in 2006 to approximately 70 today. For the common type 2 diabetes‐associated variants, three features have been noted. First, genetic impacts of individual variants are generally modest; mostly, allelic odds ratios range between 1.06 and 1.20. Second, most of the loci identified to date are not in or near obvious candidate genes, but some are often located in the intergenic regions. Third, although the number of loci is limited, there might be some population specificity in type 2 diabetes association. Although we can estimate a single or a few target genes for individual loci detected in GWA studies by referring to the data for experiments in vitro, biological function remains largely unknown for a substantial part of such target genes. Nevertheless, new biology is arising from GWA study discoveries; for example, genes implicated in β‐cell dysfunction are over‐represented within type 2 diabetes‐associated regions. Toward translational advances, we have just begun to face new challenges – elucidation of multifaceted (i.e., molecular, cellular and physiological) mechanistic insights into disease biology by considering interaction with the environment. The present review summarizes recent advances in the genetics of type 2 diabetes, together with its realistic potential.

Genetic risk score associations with cardiovascular disease and mortality in the Diabetes Heart Study

OBJECTIVE Given the high rates of cardiovascular disease (CVD) and associated mortality in individuals with type 2 diabetes, identifying and understanding predictors of CVD events and mortality could help inform clinical management in this high-risk group. Recent large-scale genetic studies may provide additional tools in this regard. RESEARCH DESIGN AND METHODS Genetic risk scores (GRSs) were constructed in 1,175 self-identified European American (EA) individuals comprising the family-based Diabetes Heart Study based on 1) 13 single nucleotide polymorphisms (SNPs) and 2) 30 SNPs with previously documented associations with CVD in genome-wide association studies. Associations between each GRS and a self-reported history of CVD, coronary artery calcified plaque (CAC) determined by noncontrast computed tomography scan, all-cause mortality, and CVD mortality were examined using marginal models with generalized estimating equations and Cox proportional hazards models. RESULTS The weighted 13-SNP GRS was associated with prior CVD (odds ratio [OR] 1.51 [95% CI 1.22-1.86]; P = 0.0002), CAC (β-coefficient [β] 0.22 [0.02-0.43]; P = 0.04) and CVD mortality (hazard ratio [HR] 1.35 [1.10-1.81]; P = 0.04) when adjusting for the other known CVD risk factors: age, sex, type 2 diabetes affection status, BMI, current smoking status, hypertension, and dyslipidemia. The weighted 30-SNP GRS was also associated with prior CVD (OR 1.33 [1.08-1.65]; P = 0.008), CAC (β 0.29 [0.08-0.50]; P = 0.006), all-cause mortality (HR 1.28 [1.05-1.56]; P = 0.01), and CVD mortality (HR 1.46 [1.08-1.96]; P = 0.01). CONCLUSIONS These findings support the utility of two simple GRSs in examining genetic associations for adverse outcomes in EAs with type 2 diabetes.

Diabetes genetic predisposition score and cardiovascular complications among patients with type 2 diabetes

OBJECTIVE

To examine the association between genetic predisposition to type 2 diabetes (T2D) and risk of cardiovascular disease (CVD) among patients with T2D.

RESEARCH DESIGN AND METHODS

The current study included 1,012 men and 1,310 women with T2D from the Health Professionals Follow-up Study and Nurses' Health Study, including 677 patients with CVD and 1,645 non-CVD control subjects. A genetic predisposition score (GPS) was calculated on the basis of 36 established independent diabetes-predisposing variants.

RESULTS

Each additional diabetes-risk allele in the GPS was associated with a 3% increased risk of CVD (odds ratio [OR] 1.03 [95% CI 1.00-1.06]). The OR was 1.47 (1.11-1.95) for CVD risk by comparing extreme quartiles of the GPS (P for trend = 0.01). We also found that the GPS was positively associated with hemoglobin A(1c) levels (P = 0.009).

CONCLUSIONS

Genetic predisposition to T2D is associated with an increased risk of cardiovascular complications in patients with T2D.

Common genetic variants of the natriuretic peptide gene locus are not associated with heart failure risk in participants in the EPIC-Norfolk study

AIMS

BNP has important effects on haemodynamics and myocardial remodelling which are protective from development and progression of heart failure. The aim of this study was to examine whether three common genetic variants (rs198389, rs5068, and rs198358) within or adjacent to the BNP gene locus which were shown to be associated with BNP blood levels are associated with risk of heart failure in the pospective population-based EPIC-Norfolk cohort.

METHODS AND RESULTS

The hazard ratio on heart failure was calculated in 23 192 participants in the EPIC-Norfolk study with Cox proportional regression analyses. During a mean follow-up of 12.6 years, 1673 (7.2%) participants had a heart failure event. There was no significant association between genotypes of rs198389, rs5068, and rs198358 and heart failure risk. Results did not differ materially in analyses stratified by hypertension, obesity, and coronary heart disease.

CONCLUSIONS

Common genetic variants reported to be associated with BNP levels were not associated with a relevant risk of heart failure in our population-based cohort. However, we cannot exclude a small association with risk of heart failure or an association with individual subtypes of the heart failure syndrome.

Genetic variant SLC2A2 [corrected] Is associated with risk of cardiovascular disease – assessing the individual and cumulative effect of 46 type 2 diabetes related genetic variants

Aim

To assess the individual and combined effect of 46 type 2 diabetes related risk alleles on incidence of a composite CVD endpoint.

Methods

Data from the first Danish MONICA study (N = 3523) and the Inter99 study (N = 6049) was used. Using Cox proportional hazard regression the individual effect of each risk allele on incident CVD was analyzed. Risk was presented as hazard ratios (HR) per risk allele.

Results

During 80,859 person years 1441 incident cases of CVD (fatal and non-fatal) occurred in the MONICA study. In Inter99 942 incident cases were observed during 61,239 person years.

In the Danish MONICA study four gene variants were significantly associated with incident CVD independently of known diabetes status at baseline; SLC2A2 rs11920090 (HR 1.147, 95% CI 1.027–1.283 , P = 0.0154), C2CD4A rs7172432 (1.112, 1.027–1.205 , P = 0.0089), GCKR rs780094 (1.094, 1.007–1.188 , P = 0.0335) and C2CD4B rs11071657 (1.092, 1.007–1.183 , P = 0.0323). The genetic score was significantly associated with increased risk of CVD (1.025, 1.010–1.041, P = 0.0016). In Inter99 two gene variants were associated with risk of CVD independently of diabetes; SLC2A2 (HR 1.180, 95% CI 1.038–1.341 P = 0.0116) and FTO (0.909, 0.827–0.998, P = 0.0463). Analysing the two populations together we found SLC2A2 rs11920090 (HR 1.164, 95% CI 1.070–1.267, P = 0.0004) meeting the Bonferroni corrected threshold for significance. GCKR rs780094 (1.076, 1.010–1.146, P = 0.0229), C2CD4B rs11071657 (1.067, 1.003–1.135, P = 0.0385) and NOTCH2 rs10923931 (1.104 (1.001 ; 1.217 , P = 0.0481) were found associated with CVD without meeting the corrected threshold. The genetic score was significantly associated with increased risk of CVD (1.018, 1.006–1.031, P = 0.0043).

Conclusions

This study showed that out of the 46 genetic variants examined only the minor risk allele of SLC2A2 rs11920090 was significantly (P = 0.0005) associated with a composite endpoint of incident CVD below the threshold for statistical significance corrected for multiple testing. This potential pathway needs further exploration.

Genetic prediction of common diseases. Still no help for the clinical diabetologist!

Genome-wide association studies (GWAS) have identified several loci associated with many common, multifactorial diseases which have been recently used to market genetic testing directly to the consumers. We here addressed the clinical utility of such GWAS-derived genetic information in predicting type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) in diabetic patients. In addition, the development of new statistical approaches, novel technologies of genome sequencing and ethical, legal and social aspects related to genetic testing have been also addressed. Available data clearly show that, similarly to what reported for most common diseases, genetic testing offered today by commercial companies cannot be used as predicting tools for T2DM and CAD. Further studies taking into account the complex interaction between genes as well as between genetic and non-genetic factors, including age, obesity and glycemic control which seem to modify genetic effects on the risk of T2DM and CAD, might mitigate such negative conclusions. Also, addressing the role of relatively rare variants by next generation sequencing may help identify novel and strong genetic markers with an important role in genetic prediction. Finally, statistical tools concentrated on reclassifying patients might be a useful application of genetic information for predicting many common diseases. By now, prediction of such diseases, including those of interest for the clinical diabetologist, have to be pursued by using traditional clinical markers which perform well and are not costly.

Association of the PPARG Pro12Ala polymorphism with type 2 diabetes and incident coronary heart disease in a Hong Kong Chinese population

AIMS

We examined the risk association between single nucleotide polymorphisms (SNPs) in eleven candidate genes with type 2 diabetes (T2D). T2D-associated polymorphisms were also examined for prediction of incident CHD.

METHODS

113 tagging SNPs were genotyped in stage 1 (467 T2D cases, 290 controls), and 15 SNPs were analyzed in the final cohort (1462 T2D cases, 600 controls). Three T2D-associated SNPs were further tested for prediction of CHD within a subset of 1417 T2D cases free of CHD at enrolment.

RESULTS

In the case-control analysis, PPARG rs1801282 (Pro12Ala) (OR=1.48 (1.02-2.16)), ADIPOQ rs1063539 (OR=1.17 (1.01-1.35)), and HNF4A rs1884614 (OR=1.16 (1.00-1.32) were associated with T2D (P(allelic)<0.05). Joint analysis of rs1801282-C, rs1063539-G, and rs1884614-T risk alleles showed an additive dosage effect (P for trend=0.001). Moreover, carriers with two PPARG rs1801282-C risk alleles were associated with an increased risk of incident CHD (HR=4.38 (1.03-18.57), P=0.045) in T2D patients in the prospective analysis.

CONCLUSIONS

Genetic variants of PPARG, ADIPOQ and HNF4A were individually and jointly associated with T2D in Hong Kong Chinese. The PPARG Pro12 risk allele contributed to increased risk for both T2D and CHD.

Genetic analysis of atherosclerosis and glucose homeostasis in an intercross between C57BL/6 and BALB/cJ apolipoprotein E-deficient mice

BACKGROUND

Diabetic patients have an increased risk of developing atherosclerosis and related complications compared with nondiabetic individuals. The increased cardiovascular risk associated with diabetes is due in part to genetic variations that influence both glucose homeostasis and atherosclerotic lesion growth. Mouse strains C57BL/6J (B6) and BALB/cJ (BALB) exhibit distinct differences in fasting plasma glucose and atherosclerotic lesion size when deficient in apolipoprotein E (Apoe(-/-)). Quantitative trait locus (QTL) analysis was performed to determine genetic factors influencing the 2 phenotypes.

METHODS AND RESULTS

Female F(2) mice (n=266) were generated from an intercross between B6.Apoe(-/-) and BALB.Apoe(-/-) mice and fed a Western diet for 12 weeks. Atherosclerotic lesions in the aortic root, fasting plasma glucose, and body weight were measured. 130 microsatellite markers across the entire genome were genotyped. Four significant QTLs, Ath1 on chromosome (Chr) 1, Ath41 on Chr2, Ath42 on Chr5, and Ath29 on Chr9, and 1 suggestive QTL on Chr4, were identified for atherosclerotic lesion size. Four significant QTLs, Bglu3 and Bglu12 on Chr1, Bglu13 on Chr5, Bglu15 on Chr12, and 2 suggestive QTLs on Chr9 and Chr15 were identified for fasting glucose levels on the chow diet. Two significant QTLs, Bglu3 and Bglu13, and 1 suggestive locus on Chr8 were identified for fasting glucose on the Western diet. One significant locus on Chr1 and 2 suggestive loci on Chr9 and Chr19 were identified for body weight. Ath1 and Ath42 coincided with Bglu3 and Bglu13, respectively, in the confidence interval.

CONCLUSIONS

We have identified novel QTLs that have major influences on atherosclerotic lesion size and glucose homeostasis. The colocalization of QTLs for atherosclerosis and diabetes suggests possible genetic connections between the 2 diseases.