Validated context-dependent associations of coronary heart disease risk with genotype variation in the chromosome 9p21 region: the Atherosclerosis Risk in Communities study

Polygenic and Network-Based Studies in Risk Identification and Demystification of cancer

INTRODUCTION

Diseases were initially thought to be the consequence of a single gene mutation. Advances in DNA sequencing tools and our understanding of gene behavior have revealed that complex diseases, such as cancer, are the product of genes cooperating with each other and with their environment in orchestrated communication networks. Seeing that the function of individual genes is still used to analyze cancer, the shift to using functionally interacting groups of genes as a new unit of study holds promise for demystifying cancer.

AREAS COVERED

The literature search focused on three types of cancer, namely breast, lung, and prostate, but arguments from other cancers were also included. The aim was to prove that multigene analyses can accurately predict and prognosticate cancer risk, subtype cancer for more personalized and effective treatments, and discover anti-cancer therapies. Computational intelligence is being harnessed to analyze this type of data and is proving indispensable to scientific progress.

EXPERT OPINION

In the future, comprehensive profiling of all kinds of patient data (e.g., serum molecules, environmental exposures) can be used to build universal networks that should help us elucidate the molecular mechanisms underlying diseases and provide appropriate preventive measures, ensuring lifelong health and longevity.

Case-Control Study on the Interaction Effects of rs10757278 Polymorphisms at 9p21 Locus and Traditional Risk Factors on Coronary Heart Disease in Xinjiang, China

OBJECTIVE

To study the interaction effects of rs10757278 polymorphisms at 9p21 locus and traditional risk factors on coronary heart disease (CHD) in Xinjiang, China.

METHODS

This case-control study consecutively enrolled 310 unrelated consecutive CHD patients aged 18-70 years old. All study participants were recruited between January and December 2017 from The Heart Center of The First Affiliated Hospital of Xinjiang Medical University. CHD patients were confirmed by coronary angiography (≥50% diameter stenosis in at least one of the major coronary arteries) according to the American Heart Association criteria for the confirmation of CHD. Healthy subjects were randomly selected from the occupational population, who received physical examination in our hospital and matched to cases on the basis of age (±3 years) and sex, those without medical history of cardiovascular diseases, and 536 subjects were selected as the control group after medical history inquiry, physical examination, cardiac ultrasound, electrocardiogram, and other blood biochemical examinations in the hospital. The occupational stress was evaluated by an effort-reward imbalance questionnaire. An epidemiological survey was conducted to collect clinical data. Chi-squared test, analysis of variance, and binary logistic regression analysis were adopted.

RESULTS

Both the case and the control groups showed significant difference in smoking, drinking, physical activity, hypertension, diabetes mellitus, family history of CHD, and body mass index (BMI) (all P < 0.05); prevalence of CHD was not related to occupational stress. There was no significant difference in occupational stress level between the 2 groups (P > 0.05); Differences in rs10757278 genotype between the case group and the control groups were statistically significant; binary logistic regression analysis was used to evaluate the risk factors of CHD. After adjustment for age and sex, significant increased risk effects for CHD were found to be associated with smoking [odds ratio (OR) = 2.311; 95% confidence interval (CI): 1.04-2.499; P < 0.001], physical exercise (OR = 1.365; 95% CI: 1.137-1.639; P < 0.001), hypertension (OR = 4.627; 95% CI: 2.165-10.764; P < 0.001), family history of CHD (OR = 4.103; 95% CI: 3.169-6.892; P < 0.001), BMI (OR = 2.484; 95% CI: 2.036-3.03; P < 0.001), and GG genotype at rs10757278 (OR = 1.978; 95% CI: 1.413-2.769; P < 0.001); We noted that a significant interaction association between GG genotype at rs10757278 and CHD differs across categories of smoking, hypertension, family history of CHD, and BMI.

CONCLUSION

GG genotype at rs10757278 may be a risk factor for CHD. And there are interaction effects between GG genotype of rs10757278 in region 9p21 gene and traditional risk factors.

Effects of CDKN2B-AS1 polymorphisms on the susceptibility to coronary heart disease

Background

Coronary heart disease (CHD) is one of the most severe cardiovascular diseases. Cyclin‐dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B‐AS1) is a significant susceptibility locus for cardiovascular disease by regulating inflammation response and cell cycle. The aim of this study was to assess whether CDKN2B‐AS1 polymorphisms are associated with CHD risk in the Chinese Han population.

Methods

A total of 501 CHD patients and 496 healthy controls were recruited from Central South University Xiangya School of Medicine Affiliated Haikou Hospital, five CDKN2B‐AS1 polymorphisms (rs10115049, rs75227345, rs2383205, rs10738606, and rs1333049) were analyzed by the Agena MassARRAY platform. The association of CDKN2B‐AS1 polymorphisms and CHD risk was determined by odd ratios (OR) and 95% confidence intervals (CI) using logistic regression.

Results

CDKN2B‐AS1 rs10738606 was significantly associated with CHD under codominant (p = .03), dominant (p = .019), recessive (p = .010), additive (p = .003), and allele (p = .003) models. Gender‐based subgroup tests showed that four polymorphisms (rs75227345, rs2383205, rs10738606 and rs1333049) were associated with CHD in males (p < .05). And age‐based subgroup tests indicated that rs2383205 and rs10738606 were associated with CHD among individuals, respectively (p < .05). For CHD patients, rs1333049 decreased the risk of diabetes under heterozygote (p = .014) and dominant (p = .024) models.

Conclusions

In conclusion, CDKN2B‐AS1 polymorphisms were associated with CHD risk in the combined or subgroup tests, suggesting an important role of CDKN2B‐AS1 in CHD susceptibility.

Genetic analysis of the relation of telomere length-related gene (RTEL1) and coronary heart disease risk

BACKGROUND

Regulator of telomere elongation helicase 1 (RTEL1), a telomere length-related gene, is closely linked to cancer and age-related diseases. The aim of this study was to investigate the association between genetic polymorphisms in the RTEL1 gene and coronary heart disease (CHD) risk.

METHODS

In this case-control study, which includes samples from 596 CHD patients and 603 healthy controls, five SNPs in RTEL1 were selected. The genotypes were studied using the Agena MassARRAY platform, and the statistical analyses were performed using the chi-square and Fisher's exact tests, genetic model analysis, and haplotype analysis.

RESULTS

In the allele model, using the chi-square test, we found that the patients with the "G" allele of rs6010620 and the "C" allele of rs4809324 in the RTEL1 gene showed a decreased risk of CHD once the results were adjusted for age and gender. In the genetic model, logistic regression analyses revealed that the rs6010620 polymorphism conferred a decreased risk of CHD in the codominant model (OR = 0.52, 95% CI: 0.31-0.88, p = 0.007 for the "G/G" genotype) and the recessive model (OR = 0.49, 95% CI: 0.30-0.80, p = 0.004 for the "G/G" genotype). In addition, the haplotype "G_rs6010620 T_rs6010621 T_rs4809324 " of RTEL1 was associated with a 0.03-fold decreased risk of CHD once the results were adjusted for age and gender (OR = 0.03, 95% CI: 0.01-0.12, p < 0.001).

CONCLUSION

Our findings have demonstrated that the genetic variants of RTEL1 may have a protective role against CHD risk.

Implementing genome-driven personalized cardiology in clinical practice

Genomics designates the coordinated investigation of a large number of genes in the context of a biological process or disease. It may be long before we attain comprehensive understanding of the genomics of common complex cardiovascular diseases (CVDs) such as inherited cardiomyopathies, valvular diseases, primary arrhythmogenic conditions, congenital heart syndromes, hypercholesterolemia and atherosclerotic heart disease, hypertensive syndromes, and heart failure with preserved/reduced ejection fraction. Nonetheless, as genomics is evolving rapidly, it is constructive to survey now pertinent concepts and breakthroughs. Today, clinical multimodal electronic medical/health records (EMRs/EHRs) incorporating genomic information establish a continuously-learning, vast knowledge-network with seamless cycling between clinical application and research. It can inform insights into specific pathogenetic pathways, guide biomarker-assisted precise diagnoses and individualized treatments, and stratify prognoses. Complex CVDs blend multiple interacting genomic variants, epigenetics, and environmental risk-factors, engendering progressions of multifaceted disease-manifestations, including clinical symptoms and signs. There is no straight-line linkage between genetic cause(s) or causal gene-variant(s) and disease phenotype(s). Because of interactions involving modifier-gene influences, (micro)-environmental, and epigenetic effects, the same variant may actually produce dissimilar abnormalities in different individuals. Implementing genome-driven personalized cardiology in clinical practice reveals that the study of CVDs at the level of molecules and cells can yield crucial clinical benefits. Complementing evidence-based medicine guidelines from large ("one-size fits all") randomized controlled trials, genomics-based personalized or precision cardiology is a most-creditable paradigm: It provides customizable approaches to prevent, diagnose, and manage CVDs with treatments directly/precisely aimed at causal defects identified by high-throughput genomic technologies. They encompass stem cell and gene therapies exploiting CRISPR-Cas9-gene-editing, and metabolomic-pharmacogenomic therapeutic modalities, precisely fine-tuned for the individual patient. Following the Human Genome Project, many expected genomics technology to provide imminent solutions to intractable medical problems, including CVDs. This eagerness has reaped some disappointment that advances have not yet materialized to the degree anticipated. Undoubtedly, personalized genetic/genomics testing is an emergent technology that should not be applied without supplementary phenotypic/clinical information: Genotype≠Phenotype. However, forthcoming advances in genomics will naturally build on prior attainments and, combined with insights into relevant epigenetics and environmental factors, can plausibly eradicate intractable CVDs, improving human health and well-being.

Interactions between vitamin D receptor (VDR) gene and Interleukin-6 gene and environment factors on coronary heart disease risk in a Chinese Han population

AIMS

To investigate the association of several single nucleotide polymorphisms (SNPs) within Interleukin-6 (IL- 6) and vitamin D receptor (VDR) gene, and additional gene- gene and gene- smoking interaction with coronary heart disease (CHD) risk in a Chinese population.

METHODS

Hardy-Weinberg equilibrium (HWE) examination was used by SNPstats (http://bioinfo.iconcologia.net/SNPstats). Generalized multifactor dimensionality reduction (GMDR) was used to screen the best interaction combination among SNPs and smoking. Stratified analysis for gene- smoking interaction was investigated by logistic regression.

RESULTS

CHD risk was significantly higher in carriers with the C allele of rs1800796 within IL-6 gene than those with GG genotype (GC+ CC versus GG), adjusted OR (95%CI) =1.62 (1.19-2.23); CHD risk was also higher in carriers with the T allele of rs2228570 within VDR gene than those with CC genotype (CT+ TT versus CC), adjusted OR (95%CI) = 1.68 (1.26-2.17). However, we did not find any direct associations of the others SNPs in IL- 6 and VDR gene with CHD risk. We also found a significant interaction between rs1800796 and smoking, the cross-validation consistency of this two- locus model was 10/ 10, and the testing accuracy was 60.11%. Current smokers with rs1800796- GC or CC genotype have the highest CHD risk, compared to never- smokers with rs1800796- GG genotype within IL- 6 gene, OR (95%CI) = 2.57 (1.74 -3.46).

CONCLUSIONS

We found that the C allele of rs1800796 within IL-6 and T allele of rs2228570 within VDR gene, interaction between rs1800796 and smoking were all associated with increased CHD risk.

Socioeconomic Status Interacts with the Genetic Effect of a Chromosome 9p21.3 Common Variant to Influence Coronary Artery Calcification and Incident Coronary Events in the Heinz Nixdorf Recall Study (Risk Factors, Evaluation of Coronary Calcium, and Lifestyle)

Background—

Genetic variants of a locus within the chromosome 9p21.3 region are consistently associated with coronary artery disease and coronary artery calcification (CAC). The aim of this study was to examine whether a 9p21.3 common variant interacts with socioeconomic status (SES) to influence CAC and incident coronary events in a population-based cohort.

Methods and Results—

9p21.3 single nucleotide polymorphism rs2891168 was genotyped in 4116 participants of the Heinz Nixdorf Recall study. SES indicators (education and income) and CAC were assessed at baseline. Incident coronary events were ascertained over a median follow-up of 9.3 years. Multiple regression models were fitted to estimate genetic effects on log e (CAC+1) and incident coronary events. Genetic effects were highest in the lower income tertile with a 53.1% (95% confidence interval, 30.6%–79.6%; P =1.8×10 – 7 ) increase in CAC and a hazard ratio of 1.44 (95% confidence interval, 1.01–2.07; P =0.049) for incident coronary events per additional risk allele. After including genotype×SES interaction terms in the regression models, genotype×income interactions were observed for CAC (exp[β g×income ]=0.85 [95% confidence interval, 0.74–0.98; P g×income =0.02] per 1000€/mo increase and additional risk allele) and for incident coronary events (hazard ratio g×income =0.69 [95% confidence interval, 0.48–0.98; P g×income =0.04] per 1000€/mo increase and additional risk allele). No interaction was observed using education as SES indicator.

Conclusions—

A 9p21.3 common variant seems to interact with SES to influence CAC and incident coronary events in a population-based cohort. This supports the hypothesis that better material, psychosocial, and lifestyle conditions enable higher SES groups to reduce the expression of their genetic susceptibility to coronary artery disease.

Transdisciplinary approaches enhance the production of translational knowledge

The primary goal of translational research is to generate and apply knowledge that can improve human health. Although research conducted within the confines of a single discipline has helped us to achieve this goal in many settings, this unidisciplinary approach may not be optimal when disease causation is complex and health decisions are pressing. To address these issues, we suggest that transdisciplinary approaches can facilitate the progress of translational research, and we review publications that demonstrate what these approaches can look like. These examples serve to (1) demonstrate why transdisciplinary research is useful, and (2) stimulate a conversation about how it can be further promoted. While we note that open-minded communication is a prerequisite for germinating any transdisciplinary work and that epidemiologists can play a key role in promoting it, we do not propose a rigid protocol for conducting transdisciplinary research, as one really does not exist. These achievements were developed in settings where typical disciplinary and institutional barriers were surmountable, but they were not accomplished with a single predetermined plan. The benefits of cross-disciplinary communication are hard to predict a priori and a detailed research protocol or process may impede the realization of novel and important insights. Overall, these examples demonstrate that enhanced cross-disciplinary information exchange can serve as a starting point that helps researchers frame better questions, integrate more relevant evidence, and advance translational knowledge more effectively. Specifically, we discuss examples where transdisciplinary approaches are helping us to better explore, assess, and intervene to improve human health.

9p21 locus rs10757278 is associated with advanced carotid atherosclerosis in a gender-specific manner

Single nucleotide polymorphisms from the chromosome locus 9p21 are reported to carry a risk for various cardiovascular diseases. One of the lead single nucleotide polymorphisms, rs10757278, was mostly investigated in association with coronary artery disease but rarely with carotid atherosclerosis. In this study, we aimed to analyze the association of rs10757278 A/G polymorphism with carotid plaque presence in advanced carotid atherosclerosis. The study included 803 participants, 486 patients with high-grade stenosis (>70%) who were undergoing carotid endarterectomy and 317 controls from Serbian population. Genotypes were determined using the real-time polymerase chain reaction. According to the recessive model of inheritance, GG genotype was significantly and independently associated with carotid plaque in females only (odds ratio 2.42, CI = 1.20-4.90, P = 0.013). Odds ratio was adjusted for age, body mass index, hypertension, TC, LDLC, HDLC and TG, and P value was corrected for multiple comparisons. Our preliminary findings suggest a gender-specific association of rs10757278 polymorphism with carotid plaque. Further studies on larger sample and in genetically and environmentally similar populations are needed.

Genome-wide significant loci: how important are they? Systems genetics to understand heritability of coronary artery disease and other common complex disorders

Genome-wide association studies (GWAS) have been extensively used to study common complex diseases such as coronary artery disease (CAD), revealing 153 suggestive CAD loci, of which at least 46 have been validated as having genome-wide significance. However, these loci collectively explain <10% of the genetic variance in CAD. Thus, we must address the key question of what factors constitute the remaining 90% of CAD heritability. We review possible limitations of GWAS, and contextually consider some candidate CAD loci identified by this method. Looking ahead, we propose systems genetics as a complementary approach to unlocking the CAD heritability and etiology. Systems genetics builds network models of relevant molecular processes by combining genetic and genomic datasets to ultimately identify key "drivers" of disease. By leveraging systems-based genetic approaches, we can help reveal the full genetic basis of common complex disorders, enabling novel diagnostic and therapeutic opportunities.

The CAA repeat polymorphism in the ZFHX3 gene is associated with risk of coronary heart disease in a Chinese population

Coronary heart disease (CHD) is a disease resulting from the interaction between genetic variations and environmental factors. Zinc finger homeobox 3 (ZFHX3) is a transcription factor and contains a poly-glutamine tract in a compositionally biased region that is encoded by exon 9, containing a cluster of CAG and CAA triplets followed by the polymorphic CAA repeats: (CAG)2(CAA)2(CAG)3CAACAG(CAA)nGCA. Thus, nine successive glutamine residues precede the poly-glutamine tract, encoded by the polymorphic CAA repeats. The aim of this study was to investigate the association of the CAA repeat polymorphism in exon 9 of the ZFHX3 gene with the risk of CHD in a Chinese population. The CAA repeat polymorphism was determined by polymerase chain reaction followed by DNA sequencing in 321 CHD patients. Genotype frequencies were compared using the non-parametric mood median test. Four alleles of CAG(CAA)10GCA, CAG(CAA)8GCA, CAG(CAA)9GCA, and CAG(CAA)11GCA were found in Chinese CHD patients in exon 9 of the ZFHX3 gene. The CAG(CAA)10GCA was a major allele (95.95%), and the CAG(CAA)8GCA was a minor allele (3.58%). The CAG(CAA)9GCA and CAG(CAA)11GCA were rare alleles (0.31% and 0.16%). The CAG(CAA)10GCA allele encodes a poly-glutamine tract of 19 residues. Importantly, the CHD patients homozygous for the CAG(CAA)10GCA allele had a higher risk of CHD, compared to the heterozygous patients carrying a CAG(CAA)8GCA allele. Moreover, the CAG(CAA)10GCA allele was significantly associated with hypertension, diabetes mellitus, or dyslipidemia (P < 0.05). Thus, the CAA repeat polymorphism in exon 9 of the ZFHX3 gene contributes to the CHD susceptibility in the Chinese population.