Genetic susceptibility to coronary heart disease in type 2 diabetes: 3 independent studies

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D).

METHODS

We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.

RESULTS

Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort.

CONCLUSIONS

Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

A Missense Variation in PHACTR2 Associates with Impaired Actin Dynamics, Dilated Cardiomyopathy, and Left Ventricular Non-Compaction in Humans

Dilated cardiomyopathy (DCM) with left ventricular non-compaction (LVNC) is a primary myocardial disease leading to contractile dysfunction, progressive heart failure, and excessive risk of sudden cardiac death. Using whole-exome sequencing to investigate a possible genetic cause of DCM with LVNC in a consanguineous child, a homozygous nucleotide change c.1532G>A causing p.Arg511His in PHACTR2 was found. The missense change can affect the binding of PHACTR2 to actin by eliminating the hydrogen bonds between them. The amino acid change does not change PHACTR2 localization to the cytoplasm. The patient’s fibroblasts showed a decreased globular to fibrillary actin ratio compared to the control fibroblasts. The re-polymerization of fibrillary actin after treatment with cytochalasin D, which disrupts the actin filaments, was slower in the patient’s fibroblasts. Finally, the patient’s fibroblasts bridged a scar gap slower than the control fibroblasts because of slower and indirect movement. This is the first report of a human variation in this PHACTR family member. The knock-out mouse model presented no significant phenotype. Our data underscore the importance of PHACTR2 in regulating the monomeric actin pool, the kinetics of actin polymerization, and cell movement, emphasizing the importance of actin regulation for the normal function of the human heart.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture

BACKGROUND

Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.

METHOD

A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.

RESULTS

We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).

CONCLUSION

The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets

Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.

Epigenetic Modifications and Non-Coding RNA in Diabetes-Mellitus-Induced Coronary Artery Disease: Pathophysiological Link and New Therapeutic Frontiers

Diabetes mellitus (DM) is a glucose metabolism disorder characterized by chronic hyperglycemia resulting from a deficit of insulin production and/or action. DM affects more than 1 in 10 adults, and it is associated with an increased risk of cardiovascular morbidity and mortality. Cardiovascular disease (CVD) accounts for two thirds of the overall deaths in diabetic patients, with coronary artery disease (CAD) and ischemic cardiomyopathy as the main contributors. Hyperglycemic damage on vascular endothelial cells leading to endothelial dysfunction represents the main initiating factor in the pathogenesis of diabetic vascular complications; however, the underlying pathophysiological mechanisms are still not entirely understood. This review addresses the current knowledge on the pathophysiological links between DM and CAD with a focus on the role of epigenetic modifications, including DNA methylation, histone modifications and noncoding RNA control. Increased knowledge of epigenetic mechanisms has contributed to the development of new pharmacological treatments ("epidrugs") with epigenetic targets, although these approaches present several challenges. Specific epigenetic biomarkers may also be used to predict or detect the development and progression of diabetes complications. Further studies on diabetes and CAD epigenetics are needed in order to identify possible new therapeutic targets and advance personalized medicine with the prediction of individual drug responses and minimization of adverse effects.

Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes

OBJECTIVE

Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD), calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers, and investigates its performance according to the age and pharmacological treatment.

RESEARCH DESIGN AND METHODS

This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) used three risk scores: a GRS, a validated clinical score, and their combined score. Hazard ratios (HR) were calculated with Cox regression, and model performances were compared with the Harrell C-index (C-index).

RESULTS

A HR of 6.7 for CAD was observed between the highest and the lowest 5th percentile of the GRS (P = 1.8 × 10-6). The performance of GRS (C-index = 0.562) was similar to HbA1c (C-index = 0.563, P = 0.96 for difference), HDL (C-index = 0.571, P = 0.6), and total cholesterol (C-index = 0.594, P = 0.1). The GRS was not correlated with the clinical score (r = -0.013, P = 0.5). The combined score outperformed the clinical score (C-index = 0.813 vs. C-index = 0.820, P = 0.003). The GRS performed better in individuals below the median age (38.6 years) compared with those above (C-index = 0.637 vs. C-index = 0.546).

CONCLUSIONS

A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD, with a predictive power comparable to that of HbA1c and HDL and total cholesterol, and when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD.

CDKN2B-AS1 gene rs4977574 A/G polymorphism and coronary heart disease: A meta-analysis of 40,979 subjects

It has been implied that there is a possible relationship between cyclin‐dependent protein kinase inhibitors antisense RNA 1 (CDKN2B‐AS1) gene rs4977574 A/G polymorphism and coronary heart disease (CHD) susceptibility. However, as the research results are discrepant, no distinct consensus on this issue has been reached so far. In order to further elaborate the latent association of the CDKN2B‐AS1 gene rs4977574 A/G polymorphism and CHD, this present meta‐analysis was conducted. There were 40,979 subjects of 17 individual studies in the present meta‐analysis. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were estimated to determine the association strength. Considering the significant heterogeneity among the individual studies, the random‐effect models were used. In the current meta‐analysis, a significant association between CDKN2B‐AS1 gene rs4977574 A/G polymorphism and CHD was found under allelic (OR: 1.18, 95% CI: 1.08–1.29, p = 4.83×10⁻⁴), recessive (OR: 1.36, 95% CI: 1.11–1.67, p = 0.003), dominant (OR: 0.71, 95% CI: 0.58–0.86, p = 6.26×10⁻⁴), heterozygous (OR:1.210, 95% CI: 1.076–1.360, p = 0.001), homozygous (OR: 1.394, 95% CI: 1.163–1.671, p = 3.31×10⁻⁴) and additive (OR: 1.180, 95% CI: 1.075–1.295, p = 4.83×10⁻⁴) genetic models. A more significant association between them was found in the Asian population than that in the whole population under these genetic models (p < 0.05). However, no significant association between them was found in the Caucasian population (p > 0.05). CDKN2B‐AS1 gene rs4977574 A/G polymorphism was associated with CHD susceptibility, especially in the Asian population. G allele of CDKN2B‐AS1 gene rs4977574 A/G polymorphism is the risk allele for CHD.

Genetics of macrovascular complications in type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a metabolic disorder that currently affects more than 400 million worldwide and is projected to cause 552 million cases by the year 2030. Long-term vascular complications, such as coronary artery disease, myocardial infarction, stroke, are the leading causes of morbidity and mortality among diabetic patients. The recent advances in genome-wide technologies have given a powerful impetus to the study of risk markers for multifactorial diseases. To date, the role of genetic and epigenetic factors in modulating susceptibility to T2DM and its vascular complications is being successfully studied that provides the accumulation of genomic knowledge. In the future, this will provide an opportunity to reveal the pathogenetic pathways in the development of the disease and allow to predict the macrovascular complications in T2DM patients. This review is focused on the evidence of the role of genetic variants and epigenetic changes in the development of macrovascular pathology in diabetic patients.

Effect of metabolic genetic variants on long-term disease comorbidity in patients with type 2 diabetes

Underlying genetic determinants contribute to developing type 2 diabetes (T2D) future diseases. The present study aimed to identify which genetic variants are associated with the incident of the major T2D co-morbid disease. First, we conducted a discovery study by investigating the genetic associations of comorbid diseases within the framework of the Utrecht Cardiovascular Pharmacogenetic studies by turning information of > 25 years follow-up data of 1237 subjects whom were genotyped and included in the discovery study. We performed Cox proportional-hazards regression to examine associations between genetic variants and comorbid diseases including cardiovascular diseases (CVD), chronic eye disease, cancer, neurologic diseases and chronic kidney disease. Secondly, we replicated our findings in two independent cohorts consisting of 1041 subjects. Finally, we performed a meta-analysis by combining the discovery and two replication cohorts. We ascertained 390 (39.7%) incident cases of CVD, 182 (16.2%) of chronic eye disease, 155 (13.8%) of cancer, 31 (2.7%) of neurologic disease and 13 (1.1%) of chronic kidney disease during a median follow-up of 10.2 years. In the discovery study, we identified a total of 39 Single Nucleotide Polymorphisms (SNPs) associated with comorbid diseases. The replication study, confirmed that rs1870849 and rs8051326 may play a role in the incidence of chronic eye disease in T2D patients. Half of patients developed at least one comorbid disease, with CVD occurring most often and earliest followed by chronic eye disease. Further research is needed to confirm the associations of two associated SNPs with chronic eye disease in T2D.

The Liability Threshold Model for Predicting the Risk of Cardiovascular Disease in Patients with Type 2 Diabetes: A Multi-Cohort Study of Korean Adults

Personalized risk prediction for diabetic cardiovascular disease (DCVD) is at the core of precision medicine in type 2 diabetes (T2D). We first identified three marker sets consisting of 15, 47, and 231 tagging single nucleotide polymorphisms (tSNPs) associated with DCVD using a linear mixed model in 2378 T2D patients obtained from four population-based Korean cohorts. Using the genetic variants with even modest effects on phenotypic variance, we observed improved risk stratification accuracy beyond traditional risk factors (AUC, 0.63 to 0.97). With a cutoff point of 0.21, the discrete genetic liability threshold model consisting of 231 SNPs (GLT₂₃₁) correctly classified 87.7% of 2378 T2D patients as high or low risk of DCVD. For the same set of SNP markers, the GLT and polygenic risk score (PRS) models showed similar predictive performance, and we observed consistency between the GLT and PRS models in that the model based on a larger number of SNP markers showed much-improved predictability. In silico gene expression analysis, additional information was provided on the functional role of the genes identified in this study. In particular, HDAC4, CDKN2B, CELSR2, and MRAS appear to be major hubs in the functional gene network for DCVD. The proposed risk prediction approach based on the liability threshold model may help identify T2D patients at high CVD risk in East Asian populations with further external validations.

Genetic risk score constructed from common genetic variants is associated with cardiovascular disease risk in type 2 diabetes mellitus

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) experience a two-fold increased risk of cardiovascular diseases. Genome-wide association studies (GWAS) have identified T2DM susceptibility genetic variants. Interestingly, the genetic variants associated with cardiovascular disease risk in T2DM Han Chinese remain to be elucidated. The present study aimed to investigate the genetic variants associated with cardiovascular disease risk in T2DM.

METHODS

We performed bootstrapping, GWAS and an investigation of genetic variants associated with cardiovascular disease risk in a discovery T2DM cohort and in a replication cohort. The discovery cohort included 326 cardiovascular disease patients and 1209 noncardiovascular disease patients. The replication cohort included 68 cardiovascular disease patients and 317 noncardiovascular disease patients. The main outcome measures were genetic variants for genetic risk score (GRS) in cardiovascular disease risk in T2DM.

RESULTS

In total, 35 genetic variants were associated with cardiovascular disease risk. A GRS was generated by combining risk alleles from these variants weighted by their estimated effect sizes (log odds ratio [OR]). T2DM patients with weighted GRS ≥ 12.63 had an approximately 15-fold increase in cardiovascular disease risk (odds ratio = 15.67, 95% confidence interval [CI] = 10.33-24.00) compared to patients with weighted GRS < 10.39. With the addition of weighted GRS, receiver-operating characteristic curves showed that area under the curve with conventional risk factors was improved from 0.719 (95% CI = 0.689-0.750) to 0.888 (95% CI = 0.866-0.910).

CONCLUSIONS

These 35 genetic variants are associated with cardiovascular disease risk in T2DM, alone and cumulatively. T2DM patients with higher levels of weighted genetic risk score have higher cardiovascular disease risks.

Diabetes and cardiovascular disease: inter-relation of risk factors and treatment

Background

The diabetes mellitus prevalence is still advancing and increasingly becoming one of the globally most severe and expensive chronic illnesses. The strong correlation between diabetes as well as the most prominent reason for diabetes and death in diabetic patients is cardiovascular disorders. Health conditions like dyslipidemia, hypertension, obesity, and other factors of risk like the risk of cardiovascular are frequent in diabetic persons and raise the likelihood of heart attacks.

Main text

In particular, several researchers have found diabetes mellitus-related biochemical pathways that raise the likelihood of cardiovascular disorder in people with diabetes individually. This review describes diabetes-cardiovascular disorder relationships, explores potential therapeutic mechanisms, addresses existing treatment, care, and describes the directions for the future for study.

Conclusion

Thus, in individuals with diabetes, it is important to concentrate on cardiovascular threat variables to reduce the illness’s lasting cardiovascular complications. Further work to enhance knowledge of the disease state and its impact on cardiovascular function is required to boost medical treatment and cardiovascular disorders result in people with diabetes.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

Analyzing Functional Pathways and constructing gene-gene network for Narcolepsy based on candidate genes

Aims: To investigate the interactions among narcolepsy-associated genes and reveal the pathways these genes involved through bioinformatics analyses. Methods: The study was performed with the following steps: 1) Selected the previously discovered narcolepsy risk genes through literature review, 2) pathway enrichment analysis, and construction of gene-gene and protein-protein interaction (PPI) networks for narcolepsy. Results: 1) GO analysis revealed the positive regulation of interferon-gamma production as the most enriched terms in biological process, and C-C chemokine receptor activity as the most enriched term in molecular function, 2) KEGG pathway enrichment analysis revealed selective enrichment of genes in cytokine-cytokine receptor interaction signaling pathways, and 3) five hub genes were identified (IFNAR1, IL10RB, DNMT1, TNFSF4 and NFATC2). Conclusion: The bioinformatics results provide new insights into the molecular pathogenesis of narcolepsy and the identification of potential therapeutic targets for narcolepsy treatment.

Nutritional genomics, inflammation and obesity

The Human Genome Project has significantly broadened our understanding of the molecular aspects regulating the homeostasis and the pathophysiology of different clinical conditions. Consequently, the field of nutrition has been strongly influenced by such improvements in knowledge - especially for determining how nutrients act at the molecular level in different conditions, such as obesity, type 2 diabetes, cardiovascular disease, and cancer. In this manner, characterizing how the genome influences the diet and vice-versa provides insights about the molecular mechanisms involved in chronic inflammation-related diseases. Therefore, the present review aims to discuss the potential application of Nutritional Genomics to modulate obesity-related inflammatory responses. Arch Endocrinol Metab. 2020;64(3):205-22.

Genome-wide association study on coronary artery disease in type 1 diabetes suggests beta-defensin 127 as a risk locus

AIMS

Diabetes is a known risk factor for coronary artery disease (CAD). There is accumulating evidence that CAD pathogenesis differs for individuals with type 1 diabetes (T1D). However, the genetic background has not been extensively studied. We aimed to discover genetic loci increasing CAD susceptibility, especially in T1D, to examine the function of these discoveries and to study the role of the known risk loci in T1D.

METHODS AND RESULTS

We performed the largest genome-wide association study to date for CAD in T1D, comprising 4869 individuals with T1D (cases/controls: 941/3928). Two loci reached genome-wide significance, rs1970112 in CDKN2B-AS1 [odds ratio (OR) = 1.32, P = 1.50 × 10-8], and rs6055069 on DEFB127 promoter (OR = 4.17, P = 2.35 × 10-9), with consistent results in survival analysis. The CDKN2B-AS1 variant replicated (P = 0.04) when adjusted for diabetic kidney disease in three additional T1D cohorts (cases/controls: 434/3123). Furthermore, we explored the function of the lead discoveries with a cardio-phenome-wide analysis. Among the eight suggestive loci (P < 1 × 10-6), rs70962766 near B3GNT2 associated with central blood pressure, rs1344228 near CNTNAP5 with intima media thickness, and rs2112481 on GRAMD2B promoter with serum leucocyte concentration. Finally, we calculated genetic risk scores for individuals with T1D with the known susceptibility loci. General population risk variants were modestly but significantly associated with CAD also in T1D (P = 4.21 × 10-7).

CONCLUSION

While general population CAD risk loci had limited effect on the risk in T1D, for the first time, variants at the CDKN2B-AS1 locus were robustly associated with CAD in individuals with T1D. The novel finding on β-defensin DEFB127 promoter provides a link between diabetes, infection susceptibility, and CAD, although pending on future confirmation.

Leveraging Genetics to Improve Cardiovascular Health in Diabetes: The 2018 Edwin Bierman Award Lecture

The past decade has witnessed an exponential increase in our ability to search the genome for genetic factors predisposing to cardiovascular disease (CVD) and in particular coronary heart disease (CHD). Identifying these genes could lead to the development of innovative strategies to prevent the cardiovascular complications of diabetes by allowing us to 1) create predictive algorithms for the identification of patients at especially high risk of CVD so that these individuals can undergo preventive interventions early in the natural history of the disease; 2) discover as yet unknown disease pathways linking diabetes to atherosclerosis, which can be used as targets for the development of new CVD-preventing drugs specifically directed at subjects with diabetes; and 3) devise personalized programs increasing the cost-effectiveness of preventive interventions by tailoring them to the genetic background of each patient. Substantial progress has been made in each of these three areas as exemplified by the recent development of a CHD genetic risk score improving CHD prediction among subjects with type 2 diabetes, the discovery of a diabetes-specific CHD locus on 1q25 pointing to glutamine synthase (GLUL) and the γ-glutamyl cycle as key regulators of CHD risk in diabetes, and the identification of two genetic loci allowing the selection of patients with type 2 diabetes who may especially benefit from intensive glycemic control. Translating these discoveries into clinical practice will not be without challenges, but the potential rewards, from the perspective of public health as well as that of persons with diabetes, make this goal worth pursuing.

SLC22A3 is associated with lipoprotein (a) concentration and cardiovascular disease in familial hypercholesterolemia

BACKGROUND AND AIMS

Several clinical and genetic factors have been shown to modulate the cardiovascular risk in subjects affected by familial hypercholesterolemia (FH). Genome wide association studies (GWAS) in the general population have identified several single nucleotide polymorphisms (SNPs) significantly associated with the risk of cardiovascular disease (CVD). This include the rs2048327 variant in the SLC22A3 gene. However, the effect of this SNP in FH subjects is unknown. The objectives of this study are to investigate the association between rs2048327 and the prevalence of CVD as well as with the concentration of lipoprotein (a) (Lp (a)), in a cohort of genetically-confirmed heterozygous FH patients.

METHODS

An enzyme-linked immunoassay kit was used to assess the Lp (a) concentration, whereas an exome chip genotyping method was used to impute the rs2048327 genotype.

RESULTS

The cohort comprised 287 non-carriers (TT), 305 heterozygous carriers (TC) and 76 homozygous carriers of the rs2048327 variant. In a model corrected for traditional cardiovascular risk factors, rs2048327 was significantly associated with Lp (a) level (median value of 12, 16 and 29 mg/dL in TT, TC and CC carriers, respectively, p < .0001). In a model corrected for cardiovascular risk factors and Lp(a) value, carrying the C allele was associated with a 2-fold increased risk of CVD (OR 1.96, 95%CI 1.21-3.19, p = .007).

CONCLUSIONS

In this study, we demonstrated that the rs2048327 SNP of the SLC22A3 gene was significantly associated with Lp(a) as well as with CVD events in FH subjects. Further studies are required in order to investigate the mechanisms behind these associations.

Common Polymorphisms Linked to Obesity and Cardiovascular Disease in Europeans and Asians are Associated with Type 2 Diabetes in Mexican Mestizos

Background and objectives: Type 2 diabetes (T2D) is a major problem of public health in Mexico. We investigated the influence of five polymorphisms, previously associated with obesity and cardiovascular disease in Europeans and Asians, on T2D in Mexican Mestizos. Materials and Methods: A total of 1358 subjects from 30 to 85 years old were genotyped for five loci: CXCL12 rs501120; CDNK2A/B rs1333049; HNF-1α rs2259816; FTO rs9939609; and LEP rs7799039. We used logistic regressions to test the effect of each locus on T2D in two case⁻control groups with obesity and without obesity. Also, linear regression models on glucose and glycated hemoglobin (HbA1c) were carried out on the whole sample, adjusted by age, gender, and body mass index. Results: The CXCL12 rs501120 C allele (OR = 1.96, p = 0.02), the FTO rs9939609 A allele (OR = 2.20, p = 0.04) and the LEP rs7799039 A allele (OR = 0.6, p = 0.03) were significantly associated with T2D in obesity case⁻control group. No significant association was found in the non-obesity case⁻control group. The linear regression model showed that CDNK2A/B rs1333049 C allele (β = 0.4, p = 0.03) and FTO rs9939609 A allele (β = 0.5, p = 0.03), were significantly associated with HbA1c, but no association was found among the loci with the glucose levels. Conclusions: Polymorphisms previously linked with obesity and cardiovascular events were also associated with T2D and high levels of HbA1c. Furthermore, we must point at the fact that this is the first report where polymorphisms CXCL12 rs501120 and LEP rs7799039 are associated with T2D in subjects with obesity.

Expression and purification of human phosphatase and actin regulator 1 (PHACTR1) in plant-based systems

Cardiovascular diseases are a prevalent cause of morbidity and mortality especially in industrialized countries. The human phosphatase and actin regulator 1 (PHACTR1) may be involved in such diseases, but its precise regulatory function remains unclear due to the large number of potential interaction partners. The same phenomenon makes this protein difficult to express in mammalian cells, but it is also an intrinsically disordered protein that likely aggregates when expressed in bacteria due to the absence of chaperones. We therefore used a design of experiments approach to test the suitability of three plant-based systems for the expression of satisfactory quantities of recombinant PHACTR1, namely transient expression in tobacco (Nicotiana tabacum) BY-2 plant cell packs (PCPs), whole N. benthamiana leaves and BY-2 cell lysate (BYL). The highest yield was achieved using the BYL: up to 120 mg product kg-1 biomass equivalent within 48 h of translation. This was 1.3-fold higher than transient expression in N. benthamiana together with the silencing inhibitor p19, and 6-fold higher than the PCP system. The presence of Triton X-100 in the extraction buffer increased the recovery of PHACTR1 by 2-200-fold depending on the conditions. PHACTR1 was incompatible with biomass blanching and was stable for less than 16 h in raw plant extracts. Purification using a DDK-tag proved inefficient whereas 15% purity was achieved by immobilized metal affinity chromatography.

Genetic Tools for Coronary Risk Assessment in Type 2 Diabetes: A Cohort Study From the ACCORD Clinical Trial

OBJECTIVE

We evaluated whether the increasing number of genetic loci for coronary artery disease (CAD) identified in the general population could be used to predict the risk of major CAD events (MCE) among participants with type 2 diabetes at high cardiovascular risk.

RESEARCH DESIGN AND METHODS

A weighted genetic risk score (GRS) derived from 204 variants representative of all the 160 CAD loci identified in the general population as of December 2017 was calculated in 5,360 and 1,931 white participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Outcome Reduction With Initial Glargine Intervention (ORIGIN) studies, respectively. The association between GRS and MCE (combining fatal CAD events, nonfatal myocardial infarction, and unstable angina) was assessed by Cox proportional hazards regression.

RESULTS

The GRS was associated with MCE risk in both ACCORD and ORIGIN (hazard ratio [HR] per SD 1.27, 95% CI 1.18-1.37, P = 4 × 10-10, and HR per SD 1.35, 95% CI 1.16-1.58, P = 2 × 10-4, respectively). This association was independent from interventions tested in the trials and persisted, though attenuated, after adjustment for classic cardiovascular risk predictors. Adding the GRS to clinical predictors improved incident MCE risk classification (relative integrated discrimination improvement +8%, P = 7 × 10-4). The performance of this GRS was superior to that of GRS based on the smaller number of CAD loci available in previous years.

CONCLUSIONS

When combined into a GRS, CAD loci identified in the general population are associated with CAD also in type 2 diabetes. This GRS provides a significant improvement in the ability to correctly predict future MCE, which may increase further with the discovery of new CAD loci.

ANRIL polymorphism rs4977574 is associated with increased risk of coronary artery disease in Asian populations: A meta-analysis of 12,005 subjects

BACKGROUND

Several studies have shown that ANRIL polymorphism may be associated with the risk of coronary artery disease (CAD). However, these studies do not provide a clear consensus in Asian population. Thus, this meta-analysis was aimed to evaluate the relationship between the common variant rs4977574 in ANRIL and CAD risk in Asian population.

METHODS

We conducted a systematic literature search of PubMed, Embase and the Cochrane Library and 2 Chinese databases. A total of 12,005 subjects from 6 independent studies were included. The pooled odds ratio (OR) and their corresponding 95% confidence intervals (CIs) were used to assess the association between rs4977574 and CAD using random effects model.

RESULTS

A significant association was observed between rs4977574 and CAD risk under the allelic (OR: 1.18, 95% CI: 1.04-1.34, P = .010), recessive (OR: 1.27, 95% CI: 1.01-1.60, P = .04), dominant (OR: 1.28, 95% CI: 1.13-1.44, P = .002), homozygous (OR: 1.46, 95% CI: 1.15-1.86, P = .002), and heterozygous model (OR: 1.17, 95% CI: 1.07-1.28, P = .0004), especially in the Chinese subgroup and the myocardial infarction (MI) subgroup (P < .05).

CONCLUSION

The ANRIL polymorphism rs4977574 is associated with CAD risk in Asian population. The rs4977574 with G allele may confer to a higher risk of CAD, especially MI.

Precision medicine in diabetes prevention, classification and management

Diabetes has become a major burden of healthcare expenditure. Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of diabetic complications. Recent advances in our understanding of the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In the present review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications. From a clinician's perspective, we attempted to provide a balanced perspective on the utility of genomic medicine in the field of diabetes. Using genetic information to guide management of monogenic forms of diabetes represents the best-known examples of genomic medicine for diabetes. Although major strides have been made in genetic research for diabetes, its complications and pharmacogenetics, ongoing efforts are required to translate these findings into practice by incorporating genetic information into a risk prediction model for prioritization of treatment strategies, as well as using multi-omic analyses to discover novel drug targets with companion diagnostics. Further research is also required to ensure the appropriate use of this information to empower individuals and healthcare professionals to make personalized decisions for achieving the optimal outcome.

Genetic Markers for Coronary Artery Disease

Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting.

Genetic basis of diabetic kidney disease and other diabetic complications

Diabetic kidney disease and other long-term complications are common in diabetes, and comprise the main cause of co-morbidity and premature mortality in individuals with diabetes. While familial clustering and heritability have been reported for all diabetic complications, the genetic background and the molecular mechanisms remain poorly understood. In recent years, genome-wide association studies have identified a few susceptibility loci for the renal complications as well as for diabetic retinopathy, diabetic cardiovascular disease and mortality. As for many complex diseases, the genetic factors increase the risk of complications in concert with the environment, and certain associations seem specific for particular conditions, for example, SP3-CDCA7 associated with end-stage renal disease only in women, or MGMT and variants on chromosome 5q13 associated with cardiovascular mortality only under tight glycaemic control. The characterization of the phenotypes is one of the main challenges for genetic research on diabetic complications, in addition to an urgent need to increase the number of individuals with diabetes with high quality phenotypic data to be included in future genetic studies.

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.

CDKN2A and CDKN2B methylation in coronary heart disease cases and controls

The aim of the present study was to investigate the association between cyclin-dependent kinase inhibitor 2A (CDKN2A) and cyclin-dependent kinase inhibitor 2B (CDKN2B) methylation, and coronary heart disease (CHD), and to explore the interaction between methylation status and CHD clinical characteristics in Han Chinese patients. A total of 189 CHD (96 males, 93 females) and 190 well-matched non-CHD controls (96 males, 94 females) were recruited for the study. Methylation-specific polymerase chain reaction technology was used to examine gene promoter methylation status. Comparisons of methylation frequencies between CHD and non-CHD patients were carried out using the Chi-square test. Methylation levels of CDKN2A and CDKN2B genes were not found to be associated with the risk of CHD. However, the mean age of CDKN2A-hypermethylated participants was significantly lower than CDKN2A-unmethylated participants (58.73±5.88 vs. 62.62±5.36 years, adjusted P<0.001). Conversely, the mean age of CDKN2B-hypermethylated participants was significantly higher compared with CDKN2B-unmethylated participants (62.26±5.48 vs. 58.33±7.47 years, adjusted P=0.048). In addition, CDKN2B methylation frequencies were significantly increased in female participants compared with males (99.47 vs. 11.98%, P=0.032). In conclusion, the results indicated that CDKN2A and CDKN2B promoter methylation frequencies were significantly associated with age, and there was a gender dimorphism in CDKN2B methylation.

Mediterranean Diet Adherence and Genetic Background Roles within a Web-Based Nutritional Intervention: The Food4Me Study

Mediterranean Diet (MedDiet) adherence has been proven to produce numerous health benefits. In addition, nutrigenetic studies have explained some individual variations in the response to specific dietary patterns. The present research aimed to explore associations and potential interactions between MedDiet adherence and genetic background throughout the Food4Me web-based nutritional intervention. Dietary, anthropometrical and biochemical data from volunteers of the Food4Me study were collected at baseline and after 6 months. Several genetic variants related to metabolic risk features were also analysed. A Genetic Risk Score (GRS) was derived from risk alleles and a Mediterranean Diet Score (MDS), based on validated food intake data, was estimated. At baseline, there were no interactions between GRS and MDS categories for metabolic traits. Linear mixed model repeated measures analyses showed a significantly greater decrease in total cholesterol in participants with a low GRS after a 6-month period, compared to those with a high GRS. Meanwhile, a high baseline MDS was associated with greater decreases in Body Mass Index (BMI), waist circumference and glucose. There also was a significant interaction between GRS and the MedDiet after the follow-up period. Among subjects with a high GRS, those with a high MDS evidenced a highly significant reduction in total carotenoids, while among those with a low GRS, there was no difference associated with MDS levels. These results suggest that a higher MedDiet adherence induces beneficial effects on metabolic outcomes, which can be affected by the genetic background in some specific markers.

Progress in Defining the Genetic Basis of Diabetic Complications

PURPOSE OF REVIEW

Diabetic complications affecting the kidneys, retina, nerves, and the cardiovasculature are the major causes of morbidity and mortality in diabetes. This paper aims to review the current understanding of the genetic basis of these complications, based on recent findings especially from genome-wide association studies.

RECENT FINDINGS

Variants in or near AFF3, RGMA-MCTP2, SP3-CDCA7, GLRA3, CNKSR3, and UMOD have reached genome-wide significance (p value <5 × 10^-8) for association with diabetic kidney disease, and recently, GRB2 was reported to be associated at genome-wide significance with diabetic retinopathy. While some loci affecting cardiovascular disease in the general population have been replicated in diabetes, GLUL affects the risk of cardiovascular disease specifically in diabetic subjects. Genetic findings are emerging for diabetic complications, although the studies remain relatively small compared to those for type 1 and type 2 diabetes. In addition to pinpointing specific loci, the studies also reveal biological information on correlated traits and pathways.

The Genetics of Ischemic Heart Disease: From Current Knowledge to Clinical Implications

Ischemic heart disease continues to cause high morbidity and mortality. Its prevalence is expected to increase due to population aging, and its prevention is a major goal of health policies. The risk of developing ischemic heart disease is related to a complex interplay between genetic, environmental, and lifestyle factors. In the last decade, considerable progress has been made in knowledge of the genetic architecture of this disease. This narrative review provides an overview of current knowledge of the genetics of ischemic heart disease and of its translation to clinical practice: identification of new therapeutic targets, assessment of the causal relationship between biomarkers and disease, improved risk prediction, and identification of responders and nonresponders to specific drugs (pharmacogenomics).

Association between chemokine CXC ligand 12 gene polymorphism (rs1746048) and coronary heart disease: A MOOSE-compliant meta-analysis

Recently a large number of investigations have implicated the association between the chemokine CXC ligand 12 gene polymorphism (rs1746048) and risk of coronary heart disease (CHD), but the results remain debatable. The aim of our study was to provide more compelling evidence for the relationship between rs1746048 and CHD risk. Studies eligible for this meta-analysis were identified through electronic search of PubMed, EMBASE, and CNKI. Two authors performed independent literature review and study quality assessment by using the Newcastle-Ottawa Scale checklist. The odds ratios (ORs) with 95% confidence intervals (CIs) were pooled in a specific genetic model to assess the association. The meta-analysis of 48,852 patients and 64,386 controls from 12 studies showed that patients with rs1746048 had 1.11 times of high risk in developing CHD (OR = 1.11; 95% CI = 1.09-1.14; P < .005; I = 35.8%). The increased risk of CHD was also found in both Asian (OR = 1.07; 95%CI = 1.02-1.12; P < .005; I = 40.6%) and Caucasian populations (OR = 1.14; 95% CI = 1.10-1.18; P < .005; I = 22.2%). The results of our meta-analysis suggested that chemokine CXC ligand 12 gene polymorphism (rs1746048) may be linked with susceptibility to CHD.

PCSK9 variant, long-chain n-3 PUFAs, and risk of nonfatal myocardial infarction in Costa Rican Hispanics

Background: Previous studies have indicated that the cardioprotective effects of long-chain (LC) n-3 (ω-3) polyunsaturated fatty acids (PUFAs) may vary across various ethnic populations. Emerging evidence has suggested that the gene-environment interaction may partly explain such variations. Proprotein convertase subtilisin/kexin type 9 (PCSK9) was shown to have a mutually regulating relation with LC n-3 PUFAs and also to reduce the risk of cardiovascular diseases (CVDs). Therefore, we hypothesized that certain PCSK9 genetic variants may modify the association between LC n-3 PUFA intake and CVD risk.Objective: We determined whether a PCSK9 variant (rs11206510), which has been identified for early onset myocardial infarction (MI), modified the association of LC n-3 PUFAs with nonfatal MI risk in Costa Rican Hispanics.Design: We analyzed cross-sectional data from 1932 case subjects with a first nonfatal MI and 2055 population-based control subjects who were living in Costa Rica to examine potential gene-environment interactions. Two-sided P values <0.05 were considered significant.Results: We observed a significant interaction between the PCSK9 rs11206510 genotype and LC n-3 PUFA intake on nonfatal MI risk (P-interaction = 0.012). The OR of nonfatal MI was 0.84 (95% CI: 0.72, 0.98) per 0.1% increase in total energy intake from LC n-3 PUFAs in protective-allele (C-allele) carriers, whereas the corresponding OR (95% CI) in non-C-allele carriers was 1.02 (95% CI: 0.95, 1.10). Similar results were observed when we examined the association between docosahexaenoic acid, which is one type of LC n-3 PUFA, and nonfatal MI risk (P-interaction = 0.003).Conclusion: LC n-3 PUFA intake is associated with a lower risk of nonfatal MI in C-allele carriers of PCSK9 rs11206510 (n = 799) but not in non-C-allele carriers (n = 3188).

Clinical worthlessness of genetic prediction of common forms of diabetes mellitus and related chronic complications: A position statement of the Italian Society of Diabetology

AIM

We are currently facing several attempts aimed at marketing genetic data for predicting multifactorial diseases, among which diabetes mellitus is one of the more prevalent. The present document primarily aims at providing to practicing physicians a summary of available data regarding the role of genetic information in predicting diabetes and its chronic complications.

DATA SYNTHESIS

Firstly, general information about characteristics and performance of risk prediction tools will be presented in order to help clinicians to get acquainted with basic methodological information related to the subject at issue. Then, as far as type 1 diabetes is concerned, available data indicate that genetic information and counseling may be useful only in families with many affected individuals. However, since no disease prevention is possible, the utility of predicting this form of diabetes is at question. In the case of type 2 diabetes, available data really question the utility of adding genetic information on top of well performing, easy available and inexpensive non-genetic markers. Finally, the possibility of using the few available genetic data on diabetic complications for improving our ability to predict them will also be presented and discussed. For cardiovascular complication, the addition of genetic information to models based on clinical features does not translate in a substantial improvement in risk discrimination. For all other diabetic complications genetic information are currently very poor and cannot, therefore, be used for improving risk stratification.

CONCLUSIONS

In all, nowadays the use of genetic testing for predicting diabetes and its chronic complications is definitively of little value in clinical practice.

Possible role of intronic polymorphisms in the PHACTR1 gene on the development of cardiovascular disease

Cardiovascular disease (CVD) is a complex multifactorial and polygenetic disease in which the interaction of numerous genes, genetic variants, and environmental factors plays a major role in its development. In an attempt to demonstrate the association between certain genetic variants and CVD, researchers have run large genomic wild association studies (GWAS) in recent decades. These studies have correlated several genomic variants with the presence of CVD. Recently, certain polymorphisms in the phosphatase and actin regulator 1 (PHACTR1) gene have been shown to be associated with CVD (i.e., coronary artery disease, coronary artery calcification, early onset myocardial infarction, cervical artery dissection and hypertension) in different ethnic groups. It is important to state that all of the described PHACTR1 genetic variants associated with CVD are located in non-translating gene regions known as introns. Thus, the purpose of this article is to hypothesize the effect of certain intronic polymorphisms in the PHACTR1 gene on pathological processes in the cardiovascular system. In addition, we present compelling evidence that supports this hypothesis as well as a methodology that could be used to assess the allelic effect using in vitro and in vivo models, which will ultimately demonstrate the pathophysiological contribution of PHACTR1 intronic polymorphisms to the development of CVD.

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids

AIMS

An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants.

METHODS

Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform.

RESULTS

The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects.

CONCLUSIONS

Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D.

PHACTR1 Gene Polymorphism Is Associated with Increased Risk of Developing Premature Coronary Artery Disease in Mexican Population

Single-nucleotide polymorphisms (SNPs) in the protein phosphatase and actin regulator 1 gene (PHACTR1) have been associated with susceptibility to develop several diseases, including cardiovascular disease. The purpose of this study was to evaluate the role of two polymorphisms (rs2026458 and rs9349379) of the PHACTR1 gene in the susceptibility to the risk of developing premature coronary artery disease (CAD) in the Mexican population. The genotype analysis was performed using 5’exonuclease TaqMan genotyping assays in a group of 994 patients with premature CAD and 703 controls. A similar genotype distribution of rs2026458 was observed in both groups; however, under an additive model adjusted by age, body mass index, type 2 diabetes mellitus, smoking, dyslipidemia, and hypertension, the rs9349379 G allele was associated with a higher risk for developing premature CAD (odds ratio (OR) = 1.22, 95% confidence interval (CI) = 1.03–1.46, p-value (p) = 0.024). The two PHACTR1 polymorphisms were not in linkage disequilibrium. In summary, our results suggest that the PHACTR1 rs9349379 polymorphism plays an important role in the risk of developing premature CAD in the Mexican population.

Genetics of coronary artery disease and myocardial infarction

Atherosclerotic coronary artery disease (CAD) comprises a broad spectrum of clinical entities that include asymptomatic subclinical atherosclerosis and its clinical complications, such as angina pectoris, myocardial infarction (MI) and sudden cardiac death. CAD continues to be the leading cause of death in industrialized society. The long-recognized familial clustering of CAD suggests that genetics plays a central role in its development, with the heritability of CAD and MI estimated at approximately 50% to 60%. Understanding the genetic architecture of CAD and MI has proven to be difficult and costly due to the heterogeneity of clinical CAD and the underlying multi-decade complex pathophysiological processes that involve both genetic and environmental interactions. This review describes the clinical heterogeneity of CAD and MI to clarify the disease spectrum in genetic studies, provides a brief overview of the historical understanding and estimation of the heritability of CAD and MI, recounts major gene discoveries of potential causal mutations in familial CAD and MI, summarizes CAD and MI-associated genetic variants identified using candidate gene approaches and genome-wide association studies (GWAS), and summarizes the current status of the construction and validations of genetic risk scores for lifetime risk prediction and guidance for preventive strategies. Potential protective genetic factors against the development of CAD and MI are also discussed. Finally, GWAS have identified multiple genetic factors associated with an increased risk of in-stent restenosis following stent placement for obstructive CAD. This review will also address genetic factors associated with in-stent restenosis, which may ultimately guide clinical decision-making regarding revascularization strategies for patients with CAD and MI.

Disruption of phactr-1 pathway triggers pro-inflammatory and pro-atherogenic factors: New insights in atherosclerosis development

Significant interest has recently emerged for phosphatase and actin regulatory protein (PHACTR1) gene in heart diseases prognosis. However, the functional role of phactr-1 protein remains elusive in heart related-diseases such as atherosclerosis, coronary artery calcification, ischaemic stroke, coronary artery stenosis and early-onset myocardial infarction. Phactr-1 is directly regulated by vascular endothelial growth factor A165 (VEGF-A165) through VEGF receptor 1 (VEGR-1) and Neuropilin-1 (NRP-1). Using an antagonist peptide approach to inhibit the interaction of VEGF-A165 to NRP-1 and VEGF-R1, we highlighted the importance of both cysteine residues located at the end of VEGF-A165 exon-7 and at the exon-8 to generate functional peptides, which decreased Phactr-1 expression. Here, we report original data showing Phactr-1 down-expression induces the expression of Matrix Metalloproteinase (MMP) regulators such as Tissue inhibitor of metalloproteinase (TIMP-1/-2) and Reversion-inducing-cysteine-rich protein with kazal motifs (RECK). Furthermore, focal adhesion kinases (FAK/PYK2/PAXILLIN) and metabolic stress (AMPK/CREB/eNOS) pathways were inhibited in endothelial cells. Moreover, the decrease of phactr-1 expression induced several factors implicated in atherosclerotic events such as oxidized low-density lipoprotein receptors (CD36, Clusterin, Cadherin-13), pro-inflammatory proteins including Thrombin, Thrombin receptor 1 (PAR-1), A Disintegrin And Metalloprotease domain-9/-17 (ADAM-9/-17), Trombospondin-2 and Galectin-3. Besides, Phactr-1 down-expression also induces emerging atherosclerosis biomarkers such as semicarbazide-sensitive amine oxidase (SSAO) and TGF-beta-inducible gene h3 (βIG-H3). In this report, we show for the first time the direct evidence of the phactr-1 biological function in the regulation of pro-atherosclerotic molecules. This intriguing result strengthened heart diseases PHACTR-1 single-nucleotide polymorphisms (SNP) correlation. Taken together, our result highlighted the pivotal role of phactr-1 protein in the pathogenesis of atherosclerosis.

Genetics of cardiovascular and renal complications in diabetes

The development of debilitating complications represents a major heathcare burden associated with the treatment of diabetes. Despite advances in new therapies for controlling hyperglycemia, the burden associated with diabetic complications remains high, especially in relation to cardiovascular and renal complications. Furthermore, an increasing proportion of patients develop type 2 diabetes at a younger age, putting them at higher risk of developing complications as a result of the increased exposure to hyperglycemia. Diabetes has become the main contributing cause to end‐stage renal disease in most countries. Although there has been important breakthroughs in our understanding of the genetics of type 1 and type 2 diabetes, bringing important insights towards the pathogenesis of diabetes, there has been comparatively less progress in our understanding of the genetic basis of diabetic complications. Genome‐wide association studies are beginning to expand our understanding of the genetic architecture relating to diabetic complications. Improved understanding of the genetic basis of diabetic cardiorenal complications might provide an opportunity for improved risk prediction, as well as the development of new therapies.

Analysis of a cardiovascular disease genetic risk score in the Diabetes Heart Study

AIMS

It remains unclear whether the high cardiovascular disease (CVD) burden in people with type 2 diabetes (T2D) is associated with genetic variants that contribute to CVD in general populations. Recent studies have examined genetic risk scores of single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies for their cumulative contribution to CVD-related traits. Most analyses combined SNPs associated with a single phenotypic class, e.g., lipids. In the present analysis, we examined a more comprehensive risk score comprised of SNPs associated with a broad range of CVD risk phenotypes.

METHODS

The composite risk score was analyzed for potential associations with subclinical CVD, self-reported CVD events, and mortality in 983 T2D-affected individuals of European descent from 466 Diabetes Heart Study (DHS) families. Genetic association was examined using marginal models with generalized estimating equations for subclinical CVD and prior CVD events and Cox proportional hazards models with sandwich-based variance estimation for mortality; analyses were adjusted for age and sex.

RESULTS

An increase in genetic risk score was significantly associated with higher levels of coronary artery calcified plaque (p = 1.23 × 10(-4)); however, no significant associations with self-reported myocardial infarction and CVD events and all-cause and CVD mortality were observed.

CONCLUSIONS

These results suggest that a genetic risk score of SNPs associated with CVD events and risk factors does not significantly account for CVD risk in the DHS, highlighting the limitations of applying current genetic markers for CVD in individuals with diabetes.

Asparaginase treatment side-effects may be due to genes with homopolymeric Asn codons (Review-Hypothesis)

The present treatment of childhood T-cell leukemias involves the systemic administration of prokary-otic L-asparaginase (ASNase), which depletes plasma Asparagine (Asn) and inhibits protein synthesis. The mechanism of therapeutic action of ASNase is poorly understood, as are the etiologies of the side-effects incurred by treatment. Protein expression from genes bearing Asn homopolymeric coding regions (N-hCR) may be particularly susceptible to Asn level fluctuation. In mammals, N-hCR are rare, short and conserved. In humans, misfunctions of genes encoding N-hCR are associated with a cluster of disorders that mimic ASNase therapy side-effects which include impaired glycemic control, dislipidemia, pancreatitis, compromised vascular integrity, and neurological dysfunction. This paper proposes that dysregulation of Asn homeostasis, potentially even by ASNase produced by the microbiome, may contribute to several clinically important syndromes by altering expression of N-hCR bearing genes. By altering amino acid abundance and modulating ribosome translocation rates at codon repeats, the microbiomic environment may contribute to genome decoding and to shaping the proteome. We suggest that impaired translation at poly Asn codons elevates diabetes risk and severity.

Genetic Variant at the GLUL Locus Predicts All-Cause Mortality in Patients With Type 2 Diabetes

Single nucleotide polymorphism (SNP) rs10911021 at the glutamate-ammonia ligase (GLUL) locus has been associated with an increased risk of coronary heart disease in individuals with type 2 diabetes. The effect of this SNP on mortality was investigated among 1,242 white subjects with type 2 diabetes from the Joslin Kidney Study (JKS) (n = 416) and the Gargano Mortality Study (GMS) (n = 826). During a mean follow-up of 12.8 ± 5.8 and 7.5 ± 2.2 years, respectively, a total of 215 and 164 deaths were observed in the two studies. In both cohorts, the all-cause mortality rate significantly increased with the number of rs10911021 risk alleles, with allelic hazard ratios (HRs) of 1.32 (95% CI 1.07-1.64, P = 0.01), 1.30 (1.10-1.69, P = 0.04), and 1.32 (1.12-1.55, P = 0.0011), respectively, in the JKS, the GMS, and the two studies combined. These associations were not affected by adjustment for possible confounders. In the JKS, for which data on causes of death were available, the HR for cardiovascular mortality was 1.51 (1.12-2.04, P = 0.0077) as opposed to 1.15 (0.84-1.55, P = 0.39) for mortality from noncardiovascular causes. These findings point to SNP rs10911021 as an independent modulator of mortality in patients with type 2 diabetes and, together with the previous observation, suggest that this results from an effect of this variant on cardiovascular risk.

Associations of the uric acid related genetic variants in SLC2A9 and ABCG2 loci with coronary heart disease risk

Background

Multiple studies investigated the associations between serum uric acid and coronary heart disease (CHD) risk. However, further investigations still remain to be carried out to determine whether there exists a causal relationship between them. We aim to explore the associations between genetic variants in uric acid related loci of SLC2A9 and ABCG2 and CHD risk in a Chinese population.

Results

A case–control study including 1,146 CHD cases and 1,146 controls was conducted. Association analysis between two uric acid related variants (SNP rs11722228 in SLC2A9 and rs4148152 in ABCG2) and CHD risk was performed by logistic regression model. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Compared with subjects with A allele of rs4148152, those with G allele had a decreased CHD risk and the association remained significant in a multivariate model. However, it altered to null when BMI was added into the model. No significant association was observed between rs11722228 and CHD risk. The distribution of CHD risk factors was not significantly different among different genotypes of both SNPs. Among subjects who did not consume alcohol, the G allele of rs4148152 showed a moderate protective effect. However, no significant interactions were observed between SNP by CHD risk factors on CHD risk.

Conclusions

There might be no association between the two uric acid related SNPs with CHD risk. Further studies were warranted to validate these results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0162-7) contains supplementary material, which is available to authorized users.

A multilocus genetic risk score predicts coronary heart disease risk in a Chinese Han population

OBJECTIVE

Genome-wide association studies have identified multiple genetic loci associated with coronary heart disease (CHD) risk. However, whether these loci could improve the CHD risk prediction is unclear.

METHODS AND RESULTS

The present case-control study (1146 CHD cases and 1146 controls) genotyped 19 recently discovered SNPs that associated with CHD risk. As a result, 10 SNPs were successfully replicated with odds ratios (ORs) ranging from 1.16 to 1.78 (P = 4.6 × 10(-2) to 5.99 × 10(-6)). A genetic risk score was constructed to assess the combined effects of the susceptibility loci on CHD risk. Subject in the second tertile (OR = 1.32, 95% CI, 1.02-1.73, P = 3.84 × 10(-2)) and the third tertile (OR = 2.62, 95% CI, 2.00-3.43, P = 3.18 × 10(-12)) had an increased risk of CHD comparing with those in the first genetic risk score tertile after adjustment for traditional risk factors including family history of CHD. Addition of the genetic risk score to the traditional model significantly improved the net reclassification as measured by the net reclassification index (NRI) (4.82%, P = 0.0001), however, no significant improvement was observed in discrimination of CHD, the area under the receiver operating characteristic curve (AUC) increased from 0.811 to 0.822 (P = 0.18).

CONCLUSIONS

A multilocus genetic risk score was associated with CHD risk in a Chinese Han population. This genetic risk score improved the net reclassification but not improved the CHD discrimination. The potential clinical use of this variations remains to be defined.