Prediction of Sudden Cardiac Death With Ultra-Short-Term Heart Rate Fluctuations.

BACKGROUND: Conventional measures of heart rate variability (HRV) have shown only modest associations with sudden cardiac death (SCD). Detrended fluctuation analysis (DFA), with novel methodological developments to evaluate the short-term scaling exponent, is a potentially superior method compared to conventional HRV tools. OBJECTIVES: In this study, the authors studied the analysis of the association between DFA and SCD. METHODS: The investigators studied the predictive value of ultra-short-term heart rate fluctuations (1-minute electrocardiogram samples) with DFA at rest and during different stages of physical exertion for incident SCD among 2,794 participants undergoing clinical exercise testing in the prospective FINCAVAS (Finnish Cardiovascular Study). The novel key DFA measure, the short-scale scaling exponent computed with second-order detrending (DFA2 α1), was the main exposure variable. SCDs were defined by American Heart Association/European Society of Cardiology criteria using death certificates with written accounts of the events. RESULTS: During a median follow-up of 8.3 years (Q1-Q3: 6.4-10.5), 83 SCDs occurred. DFA2 α1 measured at rest (but not in exercise) associated highly significantly with the risk of SCD, with 1-SD lower values associating with a 2.4-fold (Q1-Q3: 2.0-3.0) risk (P < 0.001). The results persisted when adjusting for other major risk factors for SCD, including age, cardiovascular morbidities, cardiorespiratory fitness, heart rate reduction, and left ventricular ejection fraction. Associations between conventional HRV parameters (measured at any stage of exercise or at rest) and SCD were substantially weaker and statistically nonsignificant after adjusting for other risk factors. CONCLUSIONS: Ultra-short-term DFA2 α1, when measured at rest, is a powerful and independent predictor of SCD. The association between DFA2 α1 and SCD is modified by physical exertion.

Psoas muscle quantified muscle status and long-term mortality after cardiovascular interventions.

RESULTS: In the meta-analysis, psoas muscle measurements were significantly associated with mortality among men (p < 0.05), with high heterogeneity in the associations across all cohorts. There was very little difference in the association between PMA and PMD and mortality (HR 0.83, 95% CI 0.69-0.99, p = 0.002; HR 0.85, 95% CI 0.77-0.94, p = 0.041 for one SD increase in PMA and PMD in the random effects model). Combining PMA and PMD into one composite variable by multiplying their values together showed the most robust association in terms of the magnitude of the effect size in men (HR, 0.77; 95% CI 0.73-0.87, p < 0.001). Indexing PMA to body size did not result in any significant differences in this association. Among women, psoas muscle measurements were not associated with long-term mortality in this meta-analysis. CONCLUSIONS: Different psoas muscle measurements were significantly and very similarly associated with mortality among men but not among women. No single measurement stands out, although combining PMA and PMD seems to be a slightly stronger estimate in terms of effect size and should be considered in further studies.

Significant sarcopenia affecting survival in patients undergoing heavy invasive operations may be preoperatively assessed using images of psoas muscle (PM) from routine computerized tomography but the optimal method for evaluation is unclear. A meta-analysis of individual participant data of over two thousand patients undergoing cardiovascular interventions shows that different PM measurements of surface area and density were significantly and very similarly associated with mortality among men but not among women. Combining PM area with PM density to one estimate of lean psoas muscle area seems to provide the strongest hazard estimate among men.

Influence of early-life body mass index and systolic blood pressure on left ventricle in adulthood - the Cardiovascular Risk in Young Finns Study.

BACKGROUND: Increased left ventricular mass (LVM) predicts cardiovascular events and mortality. The objective of this study was to determine whether early-life exposures to body mass index (BMI) and systolic blood pressure (SPB) affects the left ventricular structure in adulthood. METHODS: We used longitudinal data from a 31-year follow-up to examine the associations between early-life (between ages 6-18) BMI and SPB on LVM in an adult population (N = 1864, aged 34-49). The burden of early-life BMI and SBP was defined as area under the curve. RESULTS: After accounting for contemporary adult determinants of LVM, early-life BMI burden associated significantly with LVM (3.61 g/SD increase in early-life BMI; [1.94 - 5.28], p < 0.001). Overweight in early-life (age- and sex-specific BMI values corresponding to adult BMI > 25 kg/m2) associated with 4.7% (2.5-6.9%, p < 0.0001) higher LVM regardless of BMI status in adulthood. Overweight in early-life combined with obesity in adulthood (BMI > 30kg/m2) resulted in a 21% (17.3-32.9%, p < 0.0001) increase in LVM. Higher early-life BMI was associated with a risk of developing eccentric hypertrophy. The burden of early-life SPB was not associated with adult LVM or left ventricular remodeling. CONCLUSIONS: High BMI in early-life confers a sustained effect on LVM and the risk for eccentric hypertrophy independently of adulthood risk factors. KEY MESSAGES Excess in BMI in early-life has an independent effect on LVM and the risk of developing eccentric hypertrophy regardless of overweight status in adulthood. Systolic blood pressure levels in early-life did not have an independent effect on LVM or LV remodeling. The clinical implication of this study is that primary prevention of obesity in early-life may prevent the development of high LVM and eccentric hypertrophy.

Cardiorespiratory fitness and heart rate recovery predict sudden cardiac death independent of ejection fraction.

OBJECTIVE: To evaluate whether cardiorespiratory fitness (CRF) and heart rate recovery (HRR) associate with the risk of sudden cardiac death (SCD) independently of left ventricular ejection fraction (LVEF). METHODS: The Finnish Cardiovascular Study is a prospective clinical study of patients referred to clinical exercise testing in 2001-2008 and follow-up until December 2013. Patients without pacemakers undergoing first maximal or submaximal exercise testing with cycle ergometer were included (n=3776). CRF in metabolic equivalents (METs) was estimated by achieving maximal work level. HRR was defined as the reduction in heart rate 1 min after maximal exertion. Adjudication of SCD was based on death certificates. LVEF was measured for clinical indications in 71.4% of the patients (n=2697). RESULTS: Population mean age was 55.7 years (SD 13.1; 61% men). 98 SCDs were recorded during a median follow-up of 9.1 years (6.9-10.7). Mean CRF and HRR were 7.7 (SD 2.9) METs and 25 (SD 12) beats/min/min. Both CRF and HRR were associated with the risk of SCD in the entire study population (HRCRF0.47 (0.37-0.59), p<0.001 and HRHRR0.57 (0.48-0.67), p<0.001 with HR estimates corresponding to one SD increase in the exposure variables) and with CRF, HRR and LVEF in the same model (HRCRF0.60 (0.45-0.79), p<0.001, HRHRR0.65 (0.51-0.82), p<0.001) or adjusting additionally for all significant risk factors for SCD (LVEF, sex, creatinine level, history of myocardial infarction and atrial fibrillation, corrected QT interval) (HRCRF0.69 (0.52-0.93), p<0.01, HRHRR0.74 (0.58-0.95) p=0.02). CONCLUSIONS: CRF and HRR are significantly associated with the risk of SCD regardless of LVEF.

Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome - the MADDEC study.

Objective: Investigation of the clinical potential of extensive phenotype data and machine learning (ML) in the prediction of mortality in acute coronary syndrome (ACS). Methods: The value of ML and extensive clinical data was analyzed in a retrospective registry study of 9066 consecutive ACS patients (January 2007 to October 2017). Main outcome was six-month mortality. Prediction models were developed using two ML methods, logistic regression and extreme gradient boosting (xgboost). The models were fitted in training set of patients treated in 2007-2014 and 2017 (81%, n = 7344) and validated in a separate validation set of patients treated in 2015-2016 with full GRACE score data available for comparison of model accuracy (19%, n = 1722). Results: Overall, six-month mortality was 7.3% (n = 660). Several variables were found to be significantly associated with six-month mortality by both ML methods. The xgboost scored the best performance: AUC 0.890 (0.864-0.916). The AUC values for logistic regression and GRACE score were 0.867(0.837-0.897) and 0.822 (0.785-0.859), respectively. The AUC value of xgboost was better when compared to logistic regression (p = .012) and GRACE score (p < .00001). Conclusions: The use of extensive phenotype data and novel machine learning improves prediction of mortality in ACS over traditional GRACE score. KEY MESSAGES The collection of extensive cardiovascular phenotype data from electronic health records as well as from data recorded by physicians can be used highly effectively in prediction of mortality after acute coronary syndrome. Supervised machine learning methods such as logistic regression and extreme gradient boosting using extensive phenotype data significantly outperform conventional risk assessment by the current golden standard GRACE score. Integration of electronic health records and the use of supervised machine learning methods can be easily applied in a single centre level to model the risk of mortality.

Thyroid-stimulating hormone and risk of sudden cardiac death, total mortality and cardiovascular morbidity.

BACKGROUND: Previous data on the association of thyroid function with total mortality, cardiovascular disease (CVD) outcomes and sudden cardiac death (SCD) are conflicting or limited. We investigated associations of thyroid-stimulating hormone (TSH) with these outcomes in a nationwide population-based prospective cohort study. METHODS: We examined 5211 participants representative of the Finnish population aged ≥30 years in 2000-2001 and followed them for a median of 13.2 years. Using Cox proportional hazards regression models adjusted for baseline age, gender, smoking, diabetes, systolic blood pressure and total and high-density lipoprotein cholesterol, we assessed the associations of continuous baseline TSH and TSH categories (low [<0.4 mU/L], reference range [0.4-3.4 mU/L] and high [>3.4 mU/L]) with incident total mortality, SCD, coronary heart disease events, stroke, CVD, major adverse cardiac events and atrial fibrillation. RESULTS: High TSH at baseline was related to a greater risk of total mortality (HR 1.34, 95% CI 1.02-1.76) and SCD (HR 2.28, 95% CI 1.13-4.60) compared with TSH within the reference range. High TSH was not associated with the other outcomes (P ≥ .51), whereas low TSH was not associated with any of the outcomes (P ≥ .09). TSH at baseline over the full range did not have a linear relation with any of the outcomes (P ≥ .17). TSH showed a U-shaped association with total mortality after a restricted cubic spline transformation (P = .01). CONCLUSIONS: Thyroid function abnormalities could be linked with higher risks of total mortality and SCD. Large-scale randomized studies are needed for evidence-based recommendations regarding treatment of mild thyroid failure.

Aortic sinus diameter in middle age is associated with body size in young adulthood.

OBJECTIVE: Aortic sinus dilatation can lead to aortic valve regurgitation or even aortic dissection. Our objective was to examine the association between body surface area (BSA) measures from childhood to middle age and aortic sinus diameter in middle age. Understanding the relation of these two clarifies how aortic size is normally determined. METHODS: Cardiovascular Risk in Young Finns Study is a longitudinal study with follow-up of over 31 years (1980-2011). The study comprises information of body composition from multiple time points of 1950 subjects with cardiac ultrasound measurements made in 2011. The association between BSA in different ages and aortic sinus diameter in middle age was analysed by linear regression modelling adjusted with age, sex and diastolic blood pressure. Missing BSA values were derived for each life year (ages 3-33 years) from subject-specific curves for body weight and height estimated from longitudinal measurements using mixed model regression splines. RESULTS: BSA estimates in early 20s are most strongly associated with aortic sinus diameter in middle age. Top association was observed at age 23 years with one SD increase in estimated BSA corresponding to 1.04 mm (0.87-1.21 mm) increase in aortic diameter. Increase in body weight beyond early 20s does not associate with aortic sinus diameter, and the association between middle age BSA and aortic size is substantially weaker (0.74 mm increase (0.58-0.89 mm)). These results were confirmed in a subpopulation using only measured data. CONCLUSION: The association between aortic sinus diameter and BSA is stronger when considering BSA in young adulthood compared with BSA in middle age.

High-sensitivity cardiac troponin I and NT-proBNP as predictors of incident dementia and Alzheimer's disease: the FINRISK Study.

Cardiac troponin and N-terminal pro-brain natriuretic peptide (NT-proBNP) are known to associate with incident dementia. The purpose of our study was to examine whether high-sensitivity cardiac troponin I (hs-TnI) and NT-proBNP are associated with incident dementia and Alzheimer's disease (AD) independently of each other. Our study was a part of the national population-based health examination survey, FINRISK 1997, with a total sample of 7114 subjects, including 407 incident dementia cases and 319 AD cases during the follow-up time of 18 years. Using multivariate Cox regression analyses, we calculated the hazard ratios (HR) for hs-TnI and NT-proBNP. Analyses were adjusted for the previously known dementia/AD risk factors, including the apoE genotype. NT-proBNP was independently associated with incident dementia (HR 1.32, 95% CI 1.17-1.49) and AD (HR 1.30, 95% CI 1.13-1.5). Hs-TnI was also associated with incident dementia (HR 1.12, 95% CI 1.02-1.23), but not independent of NT-proBNP (HR 1.10, 95% CI 0.99-1.21). Hs-TnI was not associated with incident AD. The results remained similar in cause-specific Cox regression models and among subjects over 40 years of age. NT-proBNP and hs-TnI improved the reclassification of dementia risk in 10 years follow-up, and hs-TNI also in 18 years of follow-up. Neither hs-TnI nor NT-proBNP was able to outperform each other in risk reclassification of dementia. Both cardiovascular biomarkers, NT-proBNP and hs-TnI, were associated with incident dementia independently of traditional dementia risk factors including the apoE genotype. NT-proBNP was also associated with AD. Both markers offered a better dementia risk reclassification compared with traditional risk factors.

Apolipoproteins and HDL cholesterol do not associate with the risk of future dementia and Alzheimer's disease: the National Finnish population study (FINRISK).

Data on associations of apolipoproteins A-I and B (apo A-I, apo B) and HDL cholesterol (HDL-C) with dementia and Alzheimer's disease (AD) are conflicting. Our aim was to examine, whether apo B, apoA-I, their ratio, or HDL-C are significant, independent predictors of incident dementia and AD in the general population free of dementia at baseline. We analyzed the results from two Finnish prospective population-based cohort studies in a total of 13,275 subjects aged 25 to 74 years with mainly Caucasian ethnicity. The follow-up time for both cohorts was 10 years. We used Cox proportional hazards regression to evaluate hazard ratios (HR) for incident dementia (including AD) (n = 220) and for AD (n = 154). Cumulative incidence function (CIF) analysis was also performed to adjust the results for competing risks of death. Adjusted for multiple dementia and AD risk factors, log-transformed apo A-I, log HDL-C, log apo B, and log apo B/A-I ratio were not associated with incident dementia or AD. HDL-C was inversely associated with AD risk when adjusted for competing risks but no other statistically significant associations were observed in the CIF analyses. Apo A-I, HDL-C, apo B, or apo B/A-I ratio were not associated with future dementia or AD. HDL-C was inversely associated with incident AD risk when adjusted for competing risks of death, but the finding is unlikely to be of clinical relevance. Our study does not support the use of these risk markers to predict incident dementia or AD.

Associations of functional alanine-glyoxylate aminotransferase 2 gene variants with atrial fibrillation and ischemic stroke.

Asymmetric and symmetric dimethylarginines (ADMA and SDMA) impair nitric oxide bioavailability and have been implicated in the pathogenesis of atrial fibrillation (AF). Alanine-glyoxylate aminotransferase 2 (AGXT2) is the only enzyme capable of metabolizing both of the dimethylarginines. We hypothesized that two functional AGXT2 missense variants (rs37369, V140I; rs16899974, V498L) are associated with AF and its cardioembolic complications. Association analyses were conducted using 1,834 individulas with AF and 7,159 unaffected individuals from two coronary angiography cohorts and a cohort comprising patients undergoing clinical exercise testing. In coronary angiography patients without structural heart disease, the minor A allele of rs16899974 was associated with any AF (OR = 2.07, 95% CI 1.59-2.68), and with paroxysmal AF (OR = 1.98, 95% CI 1.44-2.74) and chronic AF (OR = 2.03, 95% CI 1.35-3.06) separately. We could not replicate the association with AF in the other two cohorts. However, the A allele of rs16899974 was nominally associated with ischemic stroke risk in the meta-analysis of WTCCC2 ischemic stroke cohorts (3,548 cases, 5,972 controls) and with earlier onset of first-ever ischemic stroke (360 cases) in the cohort of clinical exercise test patients. In conclusion, AGXT2 variations may be involved in the pathogenesis of AF and its age-related thromboembolic complications.

The prevalence of abdominal aortic aneurysm is consistently high among patients with coronary artery disease.

OBJECTIVE: Emerging evidence suggests high prevalence of abdominal aortic aneurysm (AAA) among patients with coronary disease. Accurate characterization of the association between coronary disease and AAA and of the actual prevalence of AAA among patients with angiography-verified coronary artery disease (CAD) is needed to evaluate the possible benefits of systematic screening for AAA. METHODS: We searched for studies that reported the association between AAA and CAD or coronary heart disease (CHD; wider phenotype definition) in the general population (randomized controlled trials, prospective population cohorts) and those that reported the prevalence of AAA among patients with angiography-verified CAD through PubMed, Embase, and reference lists for the period between 1980 and 2014. Random-effects models were applied because of the high heterogeneity between included studies. RESULTS: Among the general population, 23 studies reported the association between CHD and the occurrence of subclinical AAA (positive ultrasound screening; meta-analyzed odds ratio of 2.38 with 95% confidence interval [CI] of 1.78-3.19; P = 4.1 × 10(-9)). According to four prospective studies, CHD is a strong predictor of future AAA events (fatal and nonfatal; meta-analyzed hazard ratio of 3.49 with 95% CI of 2.56-4.76; P = 2.4 × 10(-15)). Altogether, 10 studies reported the prevalence of AAA among patients with angiography-verified CAD or undergoing coronary artery bypass grafting. Among men, meta-analyzed prevalence was 9.5% (95% CI, 7.6%-11.7%). Among men undergoing coronary artery bypass grafting or with three-vessel disease, the prevalence was 11.4% (95% CI, 9.1%-13.9%). Among women, the prevalence was low (0.35%). CONCLUSIONS: The risk of subclinical AAA and future AAA events is high among patients with coronary disease. Screening for AAA among CAD patients by cardiologists would be easy and inexpensive, with possible benefits to survival and risk evaluation.

Predicting sudden cardiac death using common genetic risk variants for coronary artery disease.

AIMS: Genome-wide association studies (GWAS) have identified many variants associating with an increased risk of coronary artery disease (CAD). We studied the possible association between these variants and the risk of sudden cardiac death (SCD). METHODS AND RESULTS: A weighted genetic risk score (GRSCAD) was formed from variants most strongly associating with CAD identified by the CARDIoGRAMplusC4D Consortium explaining 10.6% of the heritability of CAD [153 single-nucleotide polymorphisms with r(2) < 0.2]. The association between GRSCAD and the occurrence of SCD was studied in three independent autopsy series of consecutive cases combining altogether 1035 autopsies with 306 SCDs due to CAD (SCDCAD). The results were replicated in a prospective follow-up study of 2321 patients (mean follow-up time of 6.2 years with 48 incident SCDs of which 39 due to CAD) undergoing clinical exercise test at baseline. In a meta-analysis of the autopsy series, GRSCAD associated significantly with the risk of SCDCAD with age, body mass index, and sex adjusted odds ratio (OR) of 1.042 (1.023-1.061, P = 9.1 × 10(-6)) for one allele increase in GRSCAD. The same association was seen in both sexes. GRSCAD predicted significantly the risk of SCDCAD also in a prospective study setting (Cox regression analysis adjusted with all relevant clinical data): hazard ratio 1.049 (1.010-1.090, P = 0.014). In meta-analysis of all cohorts (adjusting further for other genetic markers related to traditional risk factors and QT-interval), the association was highly significant [OR 1.045 (1.028-1.063), P = 1.7 × 10(-7)]. CONCLUSION: Genetic risk estimate for CAD may also be used to predict SCD.

NT-proBNP and the risk of dementia: a prospective cohort study with 14 years of follow-up.

BACKGROUND: Memory disorders and Alzheimer's disease (AD) share the same risk factors with cardiovascular diseases. OBJECTIVE: We tested whether elevated N-terminal pro-brain natriuretic peptide (NT-proBNP) levels would predict any incident dementia or AD. METHODS: The association between NT-proBNP and the risk of dementia was evaluated in a total of 7,158 subjects without previous memory disorders in a prospective study with a median follow-up of 13.8 years. RESULTS: A total of 220 new dementia cases occurred, of which 149 were AD. Baseline logNT-proBNP levels were associated significantly with the risk of dementia in the entire study population (HR 1.32, 95%CI 1.17-1.56, p = 0.001) per 1SD difference, adjusted for multiple cardiovascular risk factors. Integrated discrimination improvement (IDI) and continuous net-reclassification improvement (continuous NRI) were improved in the study population over 40 years of age: continuous NRI was 17.5% (95%CI 4.4-30.6%, p = 0.009) and IDI was 0.005 (95%CI 0.001-0.010, p = 0.021). Regarding AD, the HR for 1SD logNT-proBNP change was 1.23 (95%CI 1.01-1.49, p = 0.040) in the entire study population, but no IDI or continuous NRI improvement was seen. CONCLUSION: NT-proBNP is also an independent risk marker for dementia, and patient discrimination regarding dementia risk could be improved by using it.

Significant interactions between traditional risk factors affect cardiovascular risk prediction in healthy general population.

AIMS: The aim was to carry out a systematic screening of interactions between the traditional risk factors and to evaluate which interactions are truly relevant for estimation of cardiovascular disease (CVD) risk. METHODS: Cox regression was used in a meta-analysis of five independent, population-based health examination surveys (the National FINRISK Study). End-points were 10-year incidence of coronary heart disease (CHD), ischemic stroke (IS), and CVD in a population free of cardiovascular disease (n = 35,460). RESULTS: In addition to expected age interactions, systolic blood pressure was found to be a markedly stronger risk factor for CVD (and for CHD) among subjects with normal BMI (BMI < 25: HR 1.42 [1.30-1.55] for one SD increase in systolic blood pressure) when compared to obese subjects (BMI > 30: HR 1.10 [1.01-1.19]) (P < 0.001 for interaction) and among subjects with highest high-density lipoprotein (HDL) (33% tertile: HR 1.43 [1.29-1.58]) when compared to subjects with low HDL (lowest 33% tertile: HR 1.20 [1.13-1.28]) (P < 0.001 for interaction). Interactions improved risk prediction of CVD (cross-validated continuous net reclassification improvement [NRI] 49.4% with 95% CI 44.7%-54.1%, P < 0.0001 and clinical NRI 4.7%, with 95% CI 2.8%-6.5%, P < 0.0001). The C-statistic improved from 0.8438 to 0.8455 (P = 0.010). No significant interaction was associated with the risk of IS. CONCLUSIONS: There are significant effect modifications between major risk factors, and accounting for them leads to significantly more accurate estimation of cardiovascular risk.

Association of the novel single-nucleotide polymorphism which increases oxidized low-density lipoprotein levels with cerebrovascular disease events.

BACKGROUND AND PURPOSE: Patients with genetic background for high circulating oxidized low-density lipoprotein (oxLDL) levels might be at an increased risk of cerebrovascular disease (CVD). METHODS: The association of oxLDL-variant rs676210 with CVD events was studied in patients undergoing coronary angiography (study A; N = 2913 [271 cases]). We sought to replicate the results in a large genome-wide association study meta-analysis of ischaemic stroke (study B; N = 3548 cases, 5972 controls). RESULTS: In study A, the prevalence of hypertension, diabetes and >50% carotid stenosis as well as the levels of LDL cholesterol differed significantly between cases and controls. In a logistic regression model adjusted for the significant covariates, rs676210 associated with CVD events (p = 0.030; odds ratio = 1.29 [95% confidence interval 1.03‒1.63] for risk allele G). In study B, rs676210 did not associate with the history of ischaemic stroke. CONCLUSIONS: The oxLDL levels increasing variant rs676210 associates with CVD events in patients undergoing coronary angiography.

Genome-wide association study on dimethylarginines reveals novel AGXT2 variants associated with heart rate variability but not with overall mortality.

AIMS: The purpose of this study was to identify novel genetic variants influencing circulating asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA) levels and to evaluate whether they have a prognostic value on cardiovascular mortality. METHODS AND RESULTS: We conducted a genome-wide association study on the methylarginine traits and investigated the predictive value of the new discovered variants on mortality. Our meta-analyses replicated the previously known locus for ADMA levels in DDAH1 (rs997251; P = 1.4 × 10(-40)), identified two non-synomyous polymorphisms for SDMA levels in AGXT2 (rs37369; P = 1.4 × 10(-40) and rs16899974; P = 1.5 × 10(-38)) and one in SLC25A45 (rs34400381; P = 2.5 × 10(-10)). We also fine-mapped the AGXT2 locus for further independent association signals. The two non-synonymous AGXT2 variants independently associated with SDMA levels were also significantly related with short-term heart rate variability (HRV) indices in young adults. The major allele (C) of the novel non-synonymous rs16899974 (V498L) variant associated with decreased SDMA levels and an increase in the ratio between the low- and high-frequency spectral components of HRV (P = 0.00047). Furthermore, the SDMA decreasing allele (G) of the non-synomyous SLC25A45 (R285C) variant was associated with a lower resting mean heart rate during the HRV measurements (P = 0.0046), but not with the HRV indices. None of the studied genome-wide significant variants had any major effect on cardiovascular or total mortality in patients referred for coronary angiography. CONCLUSIONS: AGXT2 has an important role in SDMA metabolism in humans. AGXT2 may additionally have an unanticipated role in the autonomic nervous system regulation of cardiac function.

Genome-wide association study pinpoints a new functional apolipoprotein B variant influencing oxidized low-density lipoprotein levels but not cardiovascular events: AtheroRemo Consortium.

BACKGROUND: Oxidized low-density lipoprotein may be a key factor in the development of atherosclerosis. We performed a genome-wide association study on oxidized low-density lipoprotein and tested the impact of associated single-nucleotide polymorphisms (SNPs) on the risk factors of atherosclerosis and cardiovascular events. METHODS AND RESULTS: A discovery genome-wide association study was performed on a population of young healthy white individuals (N=2080), and the SNPs associated with a P<5×10(-8) were replicated in 2 independent samples (A: N=2912; B: N=1326). Associations with cardiovascular endpoints were also assessed with 2 additional clinical cohorts (C: N=1118; and D: N=808). We found 328 SNPs associated with oxidized low-density lipoprotein. The genetic variant rs676210 (Pro2739Leu) in apolipoprotein B was the proxy SNP behind all associations (P=4.3×10(-136), effect size=13.2 U/L per allele). This association was replicated in the 2 independent samples (A and B, P=2.5×10(-47) and 1.1×10(-11), effect sizes=10.3 U/L and 7.8 U/L, respectively). In the meta-analyses of cohorts A, C, and D (excluding cohort B without angiographic data), the top SNP did not associate significantly with the age of onset of angiographically verified coronary artery disease (hazard ratio=1.00 [0.94-1.06] per allele), 3-vessel coronary artery disease (hazard ratio=1.03 [0.94-1.13]), or myocardial infarction (hazard ratio=1.04 [0.96-1.12]). CONCLUSIONS: This novel genetic marker is an important factor regulating oxidized low-density lipoprotein levels but not a major genetic factor for the studied cardiovascular endpoints.

Genetic profiling using genome-wide significant coronary artery disease risk variants does not improve the prediction of subclinical atherosclerosis: the Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey--a meta-analysis of three independent studies.

BACKGROUND: Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis--i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE)--beyond classical risk factors. SUBJECTS AND METHODS: We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30-45 years in 2007) respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS). The Bogalusa Heart Study (BHS; n = 1179) was used as a replication cohort (mean age of 37.5). For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46-76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS(24SNP/CAD)) calculated as a weighted (by allelic odds ratios for CAD) sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up. RESULTS: CIMT or CAE did not significantly associate with GRS(24SNP/CAD) before or after adjusting for classical CAD risk factors (p>0.05 for all) in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs. CONCLUSION: Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults.

Genetic variants and their interactions in the prediction of increased pre-clinical carotid atherosclerosis: the cardiovascular risk in young Finns study.

The relative contribution of genetic risk factors to the progression of subclinical atherosclerosis is poorly understood. It is likely that multiple variants are implicated in the development of atherosclerosis, but the subtle genotypic and phenotypic differences are beyond the reach of the conventional case-control designs and the statistical significance testing procedures being used in most association studies. Our objective here was to investigate whether an alternative approach--in which common disorders are treated as quantitative phenotypes that are continuously distributed over a population--can reveal predictive insights into the early atherosclerosis, as assessed using ultrasound imaging-based quantitative measurement of carotid artery intima-media thickness (IMT). Using our population-based follow-up study of atherosclerosis precursors as a basis for sampling subjects with gradually increasing IMT levels, we searched for such subsets of genetic variants and their interactions that are the most predictive of the various risk classes, rather than using exclusively those variants meeting a stringent level of statistical significance. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive value of the variants, and cross-validation was used to assess how well the predictive models will generalize to other subsets of subjects. By means of our predictive modeling framework with machine learning-based SNP selection, we could improve the prediction of the extreme classes of atherosclerosis risk and progression over a 6-year period (average AUC 0.844 and 0.761), compared to that of using conventional cardiovascular risk factors alone (average AUC 0.741 and 0.629), or when combined with the statistically significant variants (average AUC 0.762 and 0.651). The predictive accuracy remained relatively high in an independent validation set of subjects (average decrease of 0.043). These results demonstrate that the modeling framework can utilize the "gray zone" of genetic variation in the classification of subjects with different degrees of risk of developing atherosclerosis.