Extracellular volume-guided late gadolinium enhancement analysis for non-ischemic cardiomyopathy: The Women's Interagency HIV Study

Background Quantification of non-ischemic myocardial scar remains a challenge due to the patchy diffuse nature of fibrosis. Extracellular volume (ECV) to guide late gadolinium enhancement (LGE) analysis may achieve a robust scar assessment. Methods Three cohorts of 80 non-ischemic-training, 20 non-ischemic-validation, and 10 ischemic-validation were prospectively enrolled and underwent 3.0 Tesla cardiac MRI. An ECV cutoff to differentiate LGE scar from non-scar was identified in the training cohort from the receiver-operating characteristic curve analysis, by comparing the ECV value against the visually-determined presence/absence of the LGE scar at the highest signal intensity (SI) area of the mid-left ventricle (LV) LGE. Based on the ECV cutoff, an LGE semi-automatic threshold of n-times of standard-deviation (n-SD) above the remote-myocardium SI was optimized in the individual cases ensuring correspondence between LGE and ECV images. The inter-method agreement of scar amount in comparison with manual (for non-ischemic) or full-width half-maximum (FWHM, for ischemic) was assessed. Intra- and inter-observer reproducibility were investigated in a randomly chosen subset of 40 non-ischemic and 10 ischemic cases. Results The non-ischemic groups were all female with the HIV positive rate of 73.8% (training) and 80% (validation). The ischemic group was all male with reduced LV function. An ECV cutoff of 31.5% achieved optimum performance (sensitivity: 90%, specificity: 86.7% in training; sensitivity: 100%, specificity: 81.8% in validation dataset). The identified n-SD threshold varied widely (range 3 SD-18 SD), and was independent of scar amount (beta = -0.01, p = 0.92). In the non-ischemic cohorts, results suggested that the manual LGE assessment overestimated scar (%) in comparison to ECV-guided analysis [training: 4.5 (3.2-6.4) vs. 0.92 (0.1-2.1); validation: 2.5 (1.2-3.7) vs. 0.2 (0-1.6); P < 0.01 for both]. Intra- and inter-observer analyses of global scar (%) showed higher reproducibility in ECV-guided than manual analysis with CCC = 0.94 and 0.78 versus CCC = 0.86 and 0.73, respectively (P < 0.01 for all). In ischemic validation, the ECV-guided LGE analysis showed a comparable scar amount and reproducibility with the FWHM. Conclusions ECV-guided LGE analysis is a robust scar quantification method for a non-ischemic cohort. Trial registration ClinicalTrials.gov; NCT00000797, retrospectively-registered 2 November 1999; NCT02501811, registered 15 July 2015.Cardiovascular Aspects of Radiolog

Human Immunodeficiency Virus and Cardiac End-Organ Damage in Women: Findings From an Echocardiographic Study Across the United States

BACKGROUND: People with human immunodeficiency virus (HIV) have been reported to have increased risk of clinical and subclinical cardiovascular disease. Existing studies have focused on men and often have been uncontrolled or lacked adequate HIV-negative comparators. METHODS: We performed echocardiography in the Women's Interagency HIV Study to investigate associations of HIV and HIV-specific factors with cardiac phenotypes, including left ventricular systolic dysfunction (LVSD), isolated LV diastolic dysfunction (LVDD), left atrial enlargement (LAE), LV hypertrophy (LVH), and increased tricuspid regurgitation velocity (TRV). RESULTS: Of 1654 participants (age 51 ± 9 years), 70% had HIV. Sixty-three (5.4%) women with HIV (WWH) had LVSD; 71 (6.5%) had isolated LVDD. Compared with women without HIV (WWOH), WWH had a near-significantly increased risk of LVSD (adjusted relative risk = 1.69; 95% confidence interval = 1.00 to 2.86; P = .051). No significant association was noted for HIV seropositivity with other phenotypes, but there was a risk gradient for decreasing CD4+ count among WWH that approached or reached significance for isolated LVDD, LAE, and LVH. WWH with CD4+ count <200 cells/mm3 had significantly higher prevalence of LAE, LVH, and high TRV than WWOH. There were no consistent associations for viral suppression or antiretroviral drug exposure. CONCLUSIONS: This study suggests that WWH have a higher risk of LVSD compared with sociodemographically similar WWOH, but their risk for isolated LVDD, LAE, LVH, and high TRV is increased only with reduced CD4+ count. Although these findings warrant replication, they support the importance of cardiovascular risk-factor and HIV-disease control for heart disease prevention in this population

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Fetuin-A and risk of coronary heart disease: A Mendelian randomization analysis and a pooled analysis of AHSG genetic variants in 7 prospective studies

Background and aims: Fetuin-A has a plausible role in the inhibition of arterial calcification, but its association with risk of coronary heart disease (CHD) in the general population is unclear. We used two common genetic variants in the fetuin-A gene (AHSG) that are strongly associated with circulating fetuin-A levels to investigate the associations with risk of CHD and subclinical cardiovascular measures (intima-media thickness, ankle-arm index, and coronary artery calcification). Methods: Genetic variation and fetuin-A levels were assessed in 3299 community-living individuals (2733 Caucasians and 566 African Americans) 65 years of age or older, free of previous cardiovascular disease, who participated in the Cardiovascular Health Study (CHS) in 1992-1993. Results: Among Caucasians, both rs2248690 and rs4917 were associated with 12% lower fetuin-A concentrations per minor allele (P < 0.0001). The hazard ratios (HRs) per minor allele for incident CHD were 1.12 (95% CI: 1.00-1.26) for rs2248690 and 1.02 (0.91-1.14) for rs4917. Using both genotypes as an instrumental variable for measured fetuin-A, the HRs for one standard deviation increase in genetically determined fetuin-A levels on CHD risk were 0.84 (95% CI: 0.70-1.00) for rs2248690 and 0.97 (95% CI: 0.82-1.14) for rs4917, respectively. However, in CHS neither of the genotypes were associated with subclinical cardiovascular measures and when CHS data were meta-analyzed with data from six other prospective studies (totaling 26,702 Caucasian participants and 3295 CHD cases), the meta-analyzed HRs for incident CHD were 1.12 (0.93-1.34) and 1.06 (0.93-1.20) for rs2248690 and rs4917, respectively (p heterogeneity 0.005 and 0.0048). Conclusion: Common variants in the AHSG gene are strongly associated with fetuin-A levels, but their concurrent association with CHD risk in current prospective studies is inconsistent. Further investigation in studies with measured fetuin-A and AHSG variants is needed to clarify the potential causal association of fetuin-A with CHD risk

Separate prediction of intracerebral hemorrhage and ischemic stroke

Objectives: To develop and validate 10-year cumulative incidence functions of intracerebral hemorrhage (ICH) and ischemic stroke (IS). Methods: We used data on 27,493 participants from 3 population-based cohort studies: the Atherosclerosis Risk in Communities Study, median age 54 years, 45% male, median follow-up 20.7 years; the Rotterdam Study, median age 68 years, 38%male, median follow-up 14.3 years; and the Cardiovascular Health Study, median age 71 years, 41%male, median follow-up 12.8 years. Among these participants, 325 ICH events, 2,559 IS events, and 9,909 nonstroke deaths occurred. We developed 10-year cumulative incidence functions for ICH and IS using stratified Cox regression and competing risks analysis. Basic models including only established nonlaboratory risk factors were extended with diastolic blood pressure, total cholesterol/high-density lipoprotein cholesterol ratio, body mass index, waist-to-hip ratio, and glomerular filtration rate. The cumulative incidence functions' performances were cross-validated in each cohort separately by Harrell C-statistic and calibration plots. Results: High total cholesterol/high-density lipoprotein cholesterol ratio decreased the ICH rates but increased IS rates (p for difference across stroke types <0.001). For both the ICH and IS models, C statistics increased more by model extension in the Atherosclerosis Risk in Communities and Cardiovascular Health Study cohorts. Improvements in C statistics were reproduced by cross-validation. Models were well calibrated in all cohorts. Correlations between 10-year ICH and IS risks were moderate in each cohort. Conclusions: We developed and cross-validated cumulative incidence functions for separate prediction of 10-year ICH and IS risk. These functions can be useful to further specify an individual's stroke risk

The association of obesity and cardiometabolic traits with incident hfpef and hfref

Objectives:  This study evaluated the associations of obesity and cardiometabolic traits with incident heart failure with preserved versus reduced ejection fraction (HFpEF vs. HFrEF). Given known sex differences in HF subtype, we examined men and women separately. Background:  Recent studies suggest that obesity confers greater risk of HFpEF versus HFrEF. Contributions of associated metabolic traits to HFpEF are less clear. Methods:  We studied 22,681 participants from 4 community-based cohorts followed for incident HFpEF versus HFrEF (ejection fraction ≥50% vs. <50%). We evaluated the association of body mass index (BMI) and cardiometabolic traits with incident HF subtype using Cox models. Results:  The mean age was 60 ± 13 years, and 53% were women. Over a median follow-up of 12 years, 628 developed incident HFpEF and 835 HFrEF. Greater BMI portended higher risk of HFpEF compared with HFrEF (hazard ratio [HR]: 1.34 per 1-SD increase in BMI; 95% confidence interval [CI]: 1.24 to 1.45 vs. HR: 1.18; 95% CI: 1.10 to 1.27). Similarly, insulin resistance (homeostatic model assessment of insulin resistance) was associated with HFpEF (HR: 1.20 per 1-SD; 95% CI: 1.05 to 1.37), but not HFrEF (HR: 0.99; 95% CI: 0.88 to 1.11; p < 0.05 for difference HFpEF vs. HFrEF). We found that the differential association of BMI with HFpEF versus HFrEF was more pronounced among women (p for difference HFpEF vs. HFrEF = 0.01) when compared with men (p = 0.34). Conclusions: Obesity and related cardiometabolic traits including insulin resistance are more strongly associated with risk of future HFpEF versus HFrEF. The differential risk of HFpEF with obesity seems particularly pronounced among women and may underlie sex differences in HF subtypes