Abstract P258: Traditional Risk Factors and a Genetic Risk Score Are Associated with Age of First Acute Coronary Syndrome

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Christopher Labos ◽  
Leo Rui Wang ◽  
Louise Pilote ◽  
Peter Bogaty ◽  
James M Brophy ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Acute Coronary Syndrome ◽  
Risk Score ◽  
Genetic Risk ◽  
Association Studies ◽  
Genetic Risk Score ◽  
Genome Wide Association Studies ◽  
Coronary Syndrome ◽  
Traditional Risk Factors

Background: Early onset myocardial infarction (MI) is frequently attributed to genetic factors that may accelerate the atherosclerotic process. However, early MI may also occur due to a high burden of traditional risk factors. We sought to examine the association between traditional risk factors as well as a genetic risk score on the age of a first acute coronary syndrome (ACS). Methods and Results: We included 460 participants (mean age 59 +/- 12 years, 22.4% female) with a first ACS enrolled in the Recurrence and Inflammation in the Acute Coronary Syndromes (RISCA) cohort. Participants were genotyped for 30 single nucleotide polymorphisms identified from prior myocardial infarction genome-wide association studies to construct a multilocus genetic risk score (GRS). Linear regression models were fit to estimate the association between traditional risk factors (TRFs) and the GRS with age of first ACS. Several TRFs were significantly associated with earlier age of first ACS (all β coefficients in years; p<0.05 for all) : male sex [β=-6.9 (95%CI -9.7,-4.1)], current cigarette smoking [β=-8.1 (95% confidence interval [CI] -10.0, -6.1)], overweight (BMI>25) [β=-2.6 (95%CI -4.8, -0.3)] and obesity (BMI>30) [β=-5.24 (95%CI -7.9, -2.6)]. Use of hormone replacement therapy [β=-4.3 (95%CI -8.4, -0.3) ] and aspirin use were also associated with age of first ACS [β=3.7 (95%CI 0.3, 7.0)]. After multivariable adjustment for TRFs, a one standard deviation increment in the GRS was associated with a 1.0 (95%CI 0.1-2.0) year earlier age of first ACS. Conclusion: Among individuals with a first ACS, a GRS composed of 30 SNPs is associated with a younger age of presentation. Although common genetic predisposition modestly contributes to earlier ACS, a heavy burden of traditional risk factors is strongly associated with markedly earlier ACS.

scholarly journals The Clinical Utility of Genetic Risk Scores Following Myocardial Infarction

2021 ◽  
Author(s):  
◽  
Hadley Northcott
Keyword(s):  
Risk Factors ◽  
New Zealand ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Association Studies ◽  
Genetic Risk Score ◽  
Genome Wide Association Studies ◽  
Coronary Syndrome ◽  
Traditional Risk Factors ◽  
Cad Risk

<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>

scholarly journals The Clinical Utility of Genetic Risk Scores Following Myocardial Infarction

2021 ◽  
Author(s):  
◽  
Hadley Northcott
Keyword(s):  
Risk Factors ◽  
New Zealand ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Association Studies ◽  
Genetic Risk Score ◽  
Genome Wide Association Studies ◽  
Coronary Syndrome ◽  
Traditional Risk Factors ◽  
Cad Risk

<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>

Traditional risk factors and a Genetic Risk Score are associated with age of first acute coronary syndrome

Heart ◽  
2014 ◽  
Vol 100 (20) ◽  
pp. 1620-1624 ◽  
Author(s):  
Christopher Labos ◽  
Rui Hao Leo Wang ◽  
Louise Pilote ◽  
Peter Bogaty ◽  
James M Brophy ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Coronary Syndrome ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Coronary Syndrome ◽  
Traditional Risk Factors

P6188Predicting type 2 diabetes mellitus: combining a genetic risk score with traditional risk factors

2018 ◽  
Vol 39 (suppl_1) ◽  
Author(s):  
J Ponte Monteiro ◽  
M I Mendonca ◽  
A Pereira ◽  
A C Sousa ◽  
R Rodrigues ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Traditional Risk Factors

Abstract P259: Genetic Risk Score, Lifestyle Cardiovascular Risk Score, and Myocardial Infarction in Hispanics

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Mercedes Sotos-Prieto ◽  
Ana Baylin ◽  
Hannia Campos ◽  
Lu Qi ◽  
Josiemer Mattei
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Myocardial Infarction ◽  
Socioeconomic Status ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Lifestyle Risk Factors ◽  
Cardiovascular Risk Score ◽  
Lifestyle Risk

Background: A genetic risk score (GRS) and a lifestyle cardiovascular risk score (LCRS) have been independently associated with myocardial infarction (MI) in Hispanics. However, it is unknown if there is an interaction or a joint association between these scores. Objectives: To assess the interactive and joint associations between a GRS and a LCRS, as well as each individual lifestyle risk factor on the likelihood of MI. Methods: Data included 1534 Costa Rican adults with nonfatal acute MI and 1534 without MI participating in a case-control study. The GRS was calculated by summing the number of the top three MI-associated risk alleles. The LCRS was calculated using the estimated coefficients as weights for each lifestyle risk factors (diet, physical activity, smoking, waist:hip ratio, low or high alcohol intake, and low socioeconomic status). Conditional logistic regression was used to calculate odds ratios (OR), adjusting for age, sex, and area of residence (matching condition), and to test for interaction and joint association. Results: The multivariable OR for MI was 1.14 (95% CI 1.07, 1.22) per GRS unit and 2.72 (2.33, 3.91) per LCRS unit. Participants in the highest tertile of the GRS and highest tertile of the LCRS had higher odds of MI (5.43 [3.80, 7.76]) compared to those in the lowest category. A significant joint association was detected (p <0.0001), while the interaction term was non-significant (p=0.44). Similar results were found for the joint association between GRS and each individual lifestyle component: joint odds for highest risk category vs. lowest was 2.16 (1.53, 3.04) for diet, 1.85 (1.33, 2.59) for physical activity, 3.31 (2.45, 4.48) for smoking, 1.32 (0.92, 1.89) for alcohol, 2.84 (1.82, 4.42) for waist:hip ratio, and 1.86 (1.29, 2.69) for socioeconomic status. Conclusion: Although lifestyle risk factors and genetics contribute independently and in combination to the odds of MI, lifestyle risk factors were stronger among Costa Ricans. Efforts to improve lifestyle behaviors in this population, regardless of genetic susceptibility, may help prevent MI and related heart conditions.

Abstract 175: Performance of a Multilocus Genetic Risk Score Derived from Top Signals in the Cardiogram+C4d Consortium in Predicting Incident Coronary Disease in the Atherosclerosis Risk in Communities Study

2012 ◽  
Vol 32 (suppl_1) ◽  
Author(s):  
Themistocles L Assimes ◽  
Benjamin Goldstein ◽  
Keyword(s):  
Risk Prediction ◽  
Risk Score ◽  
Genetic Risk ◽  
Association Studies ◽  
Genetic Risk Score ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genotype Information ◽  
Atherosclerosis Risk

Genome wide association studies (GWAS) to date have identified 30 CAD susceptibility loci but the ability to use this information to improve risk prediction remains limited. A meta-analysis of the GWAS and Cardio Metabochip data produced by the CARDIoGRAM+C4D consortium representing 63,253 cases and 126,820 controls has identified 1885 SNPs passing a False Discovery Rate (FDR) threshold of 0.5%. We hypothesized that an expanded multi locus genetic risk score (GRS) incorporating genotype information at all loci below an FDR of 0.5% would perform better than a GRS restricted to 42 loci reaching genome wide significance and tested this hypothesis in subjects of European ancestry participating in the Atherosclerosis Risk in the Community (ARIC) study. Models testing the GRS were either minimally (age and sex) or fully adjusted for traditional risk factors (TRFs). The Figure shows the hazard ratio (HZ) and 95% CI for incident events comparing each quintile of GRS to the middle quintile. The GRS including genotype information at all loci with an FDR of 0.5% noticeably improves risk prediction over the GRS restricted to genome wide significant loci in both the minimally and fully adjusted models based on several metrics including i) HR per GRS quintile, ii) the HR per SD of the GRS, and iii) the logistic regression pseudo R2, and iv) the c statistic. The HR per GRS quintile and per SD of GRS were all lower in the fully adjusted models compared to the respective minimally adjusted models but the reduction of the HR was more striking for the models that tested the more expansive GRS. These findings suggest that a larger proportion of novel GWAS CAD loci are mediating their effects through TRFs. While these findings demonstrate some progress in risk prediction using GWAS loci, both the limited and the expanded GRS continues to explain a relatively small proportion of the overall variance compared to TRF. Thus, the clinical utility of a CAD GRS remains to be determined.

The Association Between Genetic Risk Factors and the Size of Intracranial Aneurysms at Time of Rupture

Neurosurgery ◽  
2013 ◽  
Vol 73 (4) ◽  
pp. 705-708 ◽  
Author(s):  
Rachel Kleinloog ◽  
Femke N.G. van 't Hof ◽  
Franciscus J. Wolters ◽  
Ingeborg Rasing ◽  
Irene C. van der Schaaf ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Intracranial Aneurysms ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Association Studies ◽  
Genetic Risk Score ◽  
Genetic Risk Factors ◽  
Genome Wide Association Studies ◽  
Aneurysm Size ◽  
Genome Wide

Abstract BACKGROUND: Genetic risk factors for intracranial aneurysms may influence the size of aneurysms. OBJECTIVE: To assess the association between genetic risk factors and the size of aneurysms at the time of rupture. METHODS: Genotypes of 7 independent single-nucleotide polymorphisms (SNPs) of the 6 genetic risk loci identified in genome-wide association studies of patients with intracranial aneurysms were obtained from 700 Dutch patients with an aneurysmal subarachnoid hemorrhage (1997-2007) previously genotyped in the genome-wide association studies; 255 additional Dutch patients with an aneurysmal subarachnoid hemorrhage (2007-2011) were genotyped for these SNPs. Aneurysms were measured on computerized tomography angiography or digital subtraction angiography. The mean aneurysm size (with standard error) was compared between patients with and without a genetic risk factor by the use of linear regression. The association between SNPs and size was assessed for single SNPs and for the combined effect of SNPs by using a weighted genetic risk score. RESULTS: Single SNPs showed no association with aneurysm size, nor did the genetic risk score. CONCLUSION: The 6 genetic risk loci have no major influence on the size of aneurysms at the time of rupture. Because these risk loci explain no more than 5% of the genetic risk, other genetic factors for intracranial aneurysms may influence aneurysm size and thereby proneness to rupture.

Abstract 13702: A Novel Genetic Risk Score Predicts Ischemic Stroke in Patients With Cardiometabolic Disease

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Parth N Patel ◽  
Nicholas A Marston ◽  
Frederick K Kamanu ◽  
Lu Chen Weng ◽  
Marc P Bonaca ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Trials ◽  
Ischemic Stroke ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
European Ancestry ◽  
Cardiometabolic Disease ◽  
Genome Wide Association Studies ◽  
Increased Risk

Introduction: Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) that are associated with an increased risk of stroke. We sought to determine whether a genetic risk score (GRS) could identify subjects at higher risk for first ischemic stroke after accounting for traditional risk factors in four clinical trials across the spectrum of cardiometabolic disease. Methods: Subjects who had consented for genetic testing, were of European ancestry, and had no prior history of stroke from the SOLID-TIMI 52, SAVOR-TIMI 53, PEGASUS-TIMI 54, and FOURIER trials were included in this analysis. A recently validated GRS composed of 36 SNPs associated with ischemic stroke was calculated in each patient. A Cox model was used to calculate hazard ratios for ischemic stroke across genetic risk groups, adjusted for age, sex, ancestry, hypertension, hyperlipidemia, smoking, diabetes mellitus, atrial fibrillation, coronary artery disease, and congestive heart failure. Results: In 23,089 subjects across the four trials, a total of 313 ischemic strokes occurred over a median follow-up of 3 years. Those with higher genetic risk were at significantly increased risk for ischemic stroke with an adjusted HR per 1-SD GRS of 1.12 (1.004-1.25; p=0.043). Individuals in the top 10% of genetic risk had a 42% greater hazard for ischemic stroke than those in the lower 90% of genetic risk (adjusted HR 1.42 [1.03-1.97]; p=0.034). The magnitude of risk conferred by high genetic risk was similar or greater than the risk provided by well-established clinical risk factors (Figure). Conclusions: Across four large clinical trials of subjects with cardiometabolic disease, a 36-SNP GRS was a strong, independent predictor of first ischemic stroke. The risk of stroke was particularly high in patients in the top 10% of genetic risk.

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