Mendelian randomization analyses reveal mediating factors of the causal effect of height on coronary artery disease

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested evidence that this association may be causal. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized the largest set of genetic instruments for human stature to date, comprising >2,000 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 2.1x10-2). We observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest that height does not add meaningful clinical impact on CAD risk prediction beyond established risk factors.

Associations of m.5178C>A variant with serum lipids levels: A systematic review and meta-analysis

Background: Emerging evidence shows that m.5178C>A variant is associated with a lower risk of coronary artery disease (CAD). However, the specific mechanisms remain elusive. Since dyslipidemia is one of the most critical risk factors for CAD and accounts for at least 50% of the population-attributable risk, it is tempting to speculate that the reduced CAD risk caused by the m.5178C>A variant may stem from an improved lipid profile. In order to verify this hypothesis, we conducted this study to clarify the associations of m.5178C>A variant with lipid levels.  Methods: By searching ten databases for studies published before June 30, 2021. Thirteen East Asian populations (7,587 individuals) were included for the analysis.</p>  Results: The present study showed that m.5178C>A variant was associated with higher high-density lipoprotein cholesterol (HDL-C) [standard mean difference (SMD) = 0.12, 95% CI = 0.06—0.17, P< 0.001] and total cholesterol (TC) (SMD = 0.08, 95% CI = 0.02—0.14, P= 0.01) levels. In subgroup analysis, the association of m.5178C>A variant with higher HDL-C levels were observed in Japanese (SMD = 0.09, 95% CI = 0.01—0.17, P= 0.03) and Chinese populations (SMD = 0.13, 95% CI = 0.07—0.20, P< 0.001). However, the association of m.5178C>A variant with lower low-density lipoprotein cholesterol (LDL-C) levels were only observed in Japanese populations (SMD = -0.11, 95% CI = -0.22—-0.00, P= 0.04).</p>  Conclusions: The m.5178C>A variant was associated with higher HDL-C and lower LDL-C levels in Japanese populations, which may contribute to decreased CAD risk and longevity of Japanese.

Detecting Coronary Artery Disease Using Rest Seismocardiography and Gyrocardiography

In this study, we present a non-invasive solution to identify patients with coronary artery disease (CAD) defined as ⩾50% stenosis in at least one coronary artery. The solution is based on the analysis of linear acceleration (seismocardiogram, SCG) and angular velocity (gyrocardiogram, GCG) of the heart recorded in the x, y, and z directional axes from an accelerometer/gyroscope sensor mounted on the sternum. The database was collected from 310 individuals through a multicenter study. The time-frequency features extracted from each SCG and GCG data channel were fed to a one-dimensional Convolutional Neural Network (1D CNN) to train six separate classifiers. The results from different classifiers were later fused to estimate the CAD risk for each participant. The predicted CAD risk was validated against related results from angiography. The SCG z and SCG y classifiers showed better performance relative to the other models (p < 0.05) with the area under the curve (AUC) of 91%. The sensitivity range for CAD detection was 92–94% for the SCG models and 73–87% for the GCG models. Based on our findings, the SCG models achieved better performance in predicting the CAD risk compared to the GCG models; the model based on the combination of all SCG and GCG classifiers did not achieve higher performance relative to the other models. Moreover, these findings showed that the performance of the proposed 3-axial SCG/GCG solution based on recordings obtained during rest was comparable, or better than stress ECG. These data may indicate that 3-axial SCG/GCG could be used as a portable at-home CAD screening tool.

Polygenic risk for coronary artery disease in the Scottish and English population

Background Epidemiological studies have repeatedly observed a markedly higher risk for coronary artery disease (CAD) in Scotland as compared to England. Up to now, it is unclear whether environmental or genetic factors might explain this phenomenon. Methods Using UK Biobank (UKB) data, we assessed CAD risk, based on the Framingham risk score (FRS) and common genetic variants, to explore the respective contribution to CAD prevalence in Scotland (n = 31,963) and England (n = 317,889). We calculated FRS based on sex, age, body mass index (BMI), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), antihypertensive medication, smoking status, and diabetes. We determined the allele frequency of published genome-wide significant risk CAD alleles and a weighted genetic risk score (wGRS) for quantifying genetic CAD risk. Results Prevalence of CAD was 16% higher in Scotland as compared to England (8.98% vs. 7.68%, P < 0.001). However, the FRS only predicted a marginally higher CAD risk (less than 1%) in Scotland (12.5 ± 10.5 vs.12.6 ± 10.6, P = 0.03). Likewise, the overall number of genome-wide significant variants affecting CAD risk (157.6 ± 7.7 and 157.5 ± 7.7; P = 0.12) and a wGRS for CAD (2.49 ± 0.25 in both populations, P = 0.14) were remarkably similar in the English and Scottish population. Interestingly, we observed substantial differences in the allele frequencies of individual risk variants. Of the previously described 163 genome-wide significant variants studied here, 35 variants had higher frequencies in Scotland, whereas 37 had higher frequencies in England (P < 0.001 each). Conclusions Neither the traditional risk factors included in the FRS nor a genetic risk score (GRS) based on established common risk alleles explained the higher CAD prevalence in Scotland. However, we observed marked differences in the distribution of individual risk alleles, which emphasizes that even geographically and ethnically closely related populations may display relevant differences in the genetic architecture of a common disease.

The Clinical Utility of Genetic Risk Scores Following Myocardial Infarction

<p>Current risk assessment for the development of coronary artery disease (CAD) in an individual relies on a combination of clinical characteristics. These well-established CAD risk factors include consideration of age, gender, hypertension, dyslipidemia, diabetes, smoking and obesity. However there are a proportion of patients that experience an acute coronary syndrome (ACS) event despite being deemed as low risk based on the current New Zealand risk model. These patients present with an absence of the traditional risk factors, or they fall below the age threshold where CAD screening is initiated. The lack of association with disease development and presence of the traditional risk factors in these patients has led to the hypothesis that genetics play a significant role in the etiology of their disease. The conduction of family-based hereditary studies has supported the hypothesis that CAD risk is associated with genetic markers. A method of analyzing this genetic risk has been developed in the form of calculating a genetic risk score (GRS). The GRS is comprised of a panel of single nucleotide polymorphisms (SNPs) discovered through genome wide association studies in CAD patients. Currently, there is controversy in the clinical utility of different GRS calculation methods, and as yet, there has been no research conducted on the potential benefits of a GRS in a New Zealand setting. Our study measured genetic risk through a weighted GRS calculated from a 27 SNP panel in 420 patients in a New Zealand based population. In looking at whether we could determine a difference in GRS values between premature (young) MI patients and older control patients, we found that the mean GRS was not significantly elevated in the premature MI cohort (p = 0.156). However, in assessing GRS differences between ethnicities and in relation to specific risk factors we saw that mean GRS was higher in patients with a family history of coronary disease (p = 0.003), in Māori patients (p = 0.013) and in patients with fewer than 2 traditional risk features (p = 0.001). GRS was not associated with individual traditional risk factors, including dyslipidaemia, hypertension, diabetes, obesity or gender. Our results showed that genetic risk for CAD is identifiable with this GRS, and indicates that further research into ethnic differences and identifying genetic risk in young CAD patients with low traditional risk would provide interesting insights.</p>

The Clinical Utility of Genetic Risk Scores Following Myocardial Infarction

<p>Current risk assessment for the development of coronary artery disease (CAD) in an individual relies on a combination of clinical characteristics. These well-established CAD risk factors include consideration of age, gender, hypertension, dyslipidemia, diabetes, smoking and obesity. However there are a proportion of patients that experience an acute coronary syndrome (ACS) event despite being deemed as low risk based on the current New Zealand risk model. These patients present with an absence of the traditional risk factors, or they fall below the age threshold where CAD screening is initiated. The lack of association with disease development and presence of the traditional risk factors in these patients has led to the hypothesis that genetics play a significant role in the etiology of their disease. The conduction of family-based hereditary studies has supported the hypothesis that CAD risk is associated with genetic markers. A method of analyzing this genetic risk has been developed in the form of calculating a genetic risk score (GRS). The GRS is comprised of a panel of single nucleotide polymorphisms (SNPs) discovered through genome wide association studies in CAD patients. Currently, there is controversy in the clinical utility of different GRS calculation methods, and as yet, there has been no research conducted on the potential benefits of a GRS in a New Zealand setting. Our study measured genetic risk through a weighted GRS calculated from a 27 SNP panel in 420 patients in a New Zealand based population. In looking at whether we could determine a difference in GRS values between premature (young) MI patients and older control patients, we found that the mean GRS was not significantly elevated in the premature MI cohort (p = 0.156). However, in assessing GRS differences between ethnicities and in relation to specific risk factors we saw that mean GRS was higher in patients with a family history of coronary disease (p = 0.003), in Māori patients (p = 0.013) and in patients with fewer than 2 traditional risk features (p = 0.001). GRS was not associated with individual traditional risk factors, including dyslipidaemia, hypertension, diabetes, obesity or gender. Our results showed that genetic risk for CAD is identifiable with this GRS, and indicates that further research into ethnic differences and identifying genetic risk in young CAD patients with low traditional risk would provide interesting insights.</p>

Haptoglobin Phenotype Modifies the Effect of Fenofibrate on Risk of Coronary Event: ACCORD Lipid Trial

Objective: The haptoglobin (Hp)2-2 phenotype (~35-40% of people) is associated with increased oxidation and dysfunctional high-density lipoprotein (HDL) in hyperglycemia and may explain why drugs designed to pharmacologically raise HDL-cholesterol and lower triglycerides have not reliably prevented cardiovascular disease (CVD) in diabetes. We aimed to determine whether the effect of adding fenofibrate versus placebo to simvastatin on the risk of coronary artery disease (CAD) events depends on Hp phenotype in the ACCORD lipid trial (NCT00000620). <p>Research Design and Methods: Cox proportional hazards regression models quantitfied the relationship between fenofibrate therapy and CAD events in the ACCORD lipid trial in participants with the Hp2-2 phenotype (n=1,795) separately from those without (n=3,201). </p> <p>Results: Fenofibrate therapy successfully lowered the risk of CAD events in participants without the Hp2-2 phenotype (multivariable-adjusted hazard ratio: 0.74, 95% CI: 0.60-0.90, compared to no fenofibrate therapy) but not in participants with the Hp2-2 phenotype (1.16, 0.87-1.56, p, interaction=0.009). Subgroup analyses revealed that this protective effect of fenofibrate against CAD events among the non-Hp2-2 phenotype group was most effective in participants with severe dyslipidemia (p, interaction=0.01), and and in males (p, interaction= 0.02) with an increased CAD risk from fenofibrate treatment observed in females with the Hp2-2 phenotype (p, interaction= 0.002). </p> <p>Conclusions: The effect of fenofibrate added to simvastatin on risk of CAD events depends on Hp phenotype in the ACCORD lipid trial. </p>

Haptoglobin Phenotype Modifies the Effect of Fenofibrate on Risk of Coronary Event: ACCORD Lipid Trial

Objective: The haptoglobin (Hp)2-2 phenotype (~35-40% of people) is associated with increased oxidation and dysfunctional high-density lipoprotein (HDL) in hyperglycemia and may explain why drugs designed to pharmacologically raise HDL-cholesterol and lower triglycerides have not reliably prevented cardiovascular disease (CVD) in diabetes. We aimed to determine whether the effect of adding fenofibrate versus placebo to simvastatin on the risk of coronary artery disease (CAD) events depends on Hp phenotype in the ACCORD lipid trial (NCT00000620). <p>Research Design and Methods: Cox proportional hazards regression models quantitfied the relationship between fenofibrate therapy and CAD events in the ACCORD lipid trial in participants with the Hp2-2 phenotype (n=1,795) separately from those without (n=3,201). </p> <p>Results: Fenofibrate therapy successfully lowered the risk of CAD events in participants without the Hp2-2 phenotype (multivariable-adjusted hazard ratio: 0.74, 95% CI: 0.60-0.90, compared to no fenofibrate therapy) but not in participants with the Hp2-2 phenotype (1.16, 0.87-1.56, p, interaction=0.009). Subgroup analyses revealed that this protective effect of fenofibrate against CAD events among the non-Hp2-2 phenotype group was most effective in participants with severe dyslipidemia (p, interaction=0.01), and and in males (p, interaction= 0.02) with an increased CAD risk from fenofibrate treatment observed in females with the Hp2-2 phenotype (p, interaction= 0.002). </p> <p>Conclusions: The effect of fenofibrate added to simvastatin on risk of CAD events depends on Hp phenotype in the ACCORD lipid trial. </p>