Silent Ischemic Heart Disease and Pericardial Fat Volume in HIV-Infected Patients: A Case-Control Myocardial Perfusion Scintigraphy Study

Objectives

to determine the prevalence of asymptomatic ischemic heart disease (IHD) in HIV patients by myocardial perfusion scintigraphy (MPS) and to determine the value of coronary artery calcium score (CACS), carotid intima-media thickness (cIMT) and pericardial fat volume as screening tools for detection of IHD in subjects with HIV.

Background

Patients with HIV seem prone to early development of IHD.

Methods

105 consecutive HIV patients (mean age 47.4 years; mean duration of HIV 12.3 years; mean CD4+ cell count 636×10⁶/L; all receiving antiretroviral therapy) and 105 controls matched for age, gender and smoking status, without history of IHD were recruited. MPS, CACS, cIMT, pericardial fat volume, and cardiovascular risk scores were measured.

Results

HIV patients demonstrated higher prevalence of perfusion defects than controls (18% vs. 0%; p<0.001) despite similar risk scores. Of HIV patients with perfusion defects, 42% had a CACS = 0. CACS and cIMT were similar in HIV patients and controls. HIV patients on average had 35% increased pericardial fat volume and increased concentration of biomarkers of atherosclerosis in the blood. HIV patients with myocardial perfusion defects had increased pericardial fat volume compared with HIV patients without perfusion defects (314±43 vs. 189±12 mL; p<0.001).

Conclusions

HIV patients had an increased prevalence of silent IHD compared to controls as demonstrated by MPS. The finding was strongly associated with pericardial fat volume, whereas cardiovascular risk scores, cIMT and CACS seem less useful as screening tools for detection of myocardial perfusion defects in HIV patients.     

The Association between Atrium Electromechanical Interval and Pericardial Fat

Objectives

Pericardial fat (PCF) may induce local inflammation and subsequent structural remodeling of the left atrium (LA). However, the adverse effects of PCF on LA are difficult to be evaluated and quantified. The atrial electromechanical interval determined by transthoracic echocardiogram was shown to be a convenient parameter which can reflect the process of LA remodeling. The goal of the present study was to investigate the association between the electromechanical interval and PCF.

Methods and Results

A total of 337 patients with mean age of 51.9±9.0 years were enrolled. The electromechanical interval (PA-PDI) defined as the time interval from the initiation of the P wave deflection to the peak of the mitral inflow A wave on the pulse wave Doppler imaging was measured for every patient. The amount of PCF was determined by multi-detector computed tomography. The PA-PDI interval was significantly correlated with the amount of PCF (r = 0.641, p value <0.001). Graded prolongation of PA-PDI interval was observed across 3 groups of patients divided according to the tertile values of PCF. The AUC for the PA-PDI interval in predicting an increased amount of PCF (third tertile) was 0.796. At a cutoff value of 130 ms identified by the ROC curve, the sensitivity and specificity of PA-PDI interval in identifying patients with a highest tertile of PCF were 63.4% and 85.3%, respectively.

Conclusions

The PA-PDI intervals were longer in patients with an increased amount of PCF. It may be a useful parameter to represent the degree of PCF-related atrial remodeling.     

Longitudinal variance-components analysis of the Framingham Heart Study data

The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages.     

Pedigree and genotype errors in the Framingham Heart Study

The pedigree and genotype data from the Framingham Heart Study were examined for errors. Errors in 21 of 329 pedigrees were detected with the program PREST, and of these the errors in 16 pedigrees were resolved. Genotyping errors were then detected with SIMWALK2. Five Mendelian errors were found following the pedigree corrections. Double-recombinant errors were more common, with 142 being detected at mistyping probabilities of 0.25 or greater.     

Age-stratified heritability estimation in the Framingham Heart Study families

The Framingham Heart Study provides a unique source of longitudinal family data related to CVD risk factors. Age-stratified heritability estimates were obtained over three age groups (31-49 years, 50-60 years, and 61-79 years), reflecting the longitudinal nature of the data, for four quantitative traits. Age-adjusted heritability estimates were obtained at a single common time point for the same four quantitative traits. The importance of these groups is that they consist of the same individuals. The highest age-stratified heritability estimate (h2 = 0.88 (+/- 0.06)) was for height in the model adjusting for gender over all three age groups. SBP gave the lowest heritability estimate (h2 = 0.15 (+/- 0.11)) for the 70 age group in the model adjusting for gender, height, BMI, smoker, and drinker. BMI had slightly higher estimates (h2 = 0.64 (+/- 0.11)) in the 40 age group than previously published. The highest age-adjusted heritability estimate (h2 = 0.90 (+/- 0.06)) was for height in the model adjusting for gender. SBP gave the lowest heritability estimate (h2 = 0.38 (+/- 0.09)) for unadjusted model. These results indicate that some common, complex traits may vary little in their genetic architecture over time and suggest that a common set of genes may be contributing to observed variation for these longitudinally collected phenotypes.     

Association of Pericardial Fat With Liver Fat and Insulin Sensitivity After Diet‐Induced Weight Loss in Overweight Women

Pericardial adipose tissue (PAT) is positively associated with fatty liver and obesity‐related insulin resistance. Because PAT is a well‐known marker of visceral adiposity, we investigated the impact of weight loss on PAT and its relationship with liver fat and insulin sensitivity independently of body fat distribution. Thirty overweight nondiabetic women (BMI 28.2–46.8 kg/m², 22–41 years) followed a 14.2 ± 4‐weeks low‐calorie diet. PAT, abdominal subcutaneous (SAT), and visceral fat volumes (VAT) were measured by magnetic resonance imaging (MRI), total fat mass, trunk, and leg fat by dual‐energy X‐ray absorptiometry and intrahepatocellular lipids (IHCL) by (¹)H‐magnetic resonance spectroscopy. Euglycemic hyperinsulinemic clamp (M) and homeostasis model assessment of insulin resistance (HOMA_IR) were used to assess insulin sensitivity or insulin resistance. At baseline, PAT correlated with VAT (r = 0.82; P < 0.001), IHCL (r = 0.46), HOMA_IR (r = 0.46), and M value (r = ?0.40; all P < 0.05). During intervention, body weight decreased by ?8.5%, accompanied by decreases of ?12% PAT, ?13% VAT, ?44% IHCL, ?10% HOMA2‐%B, and +24% as well as +15% increases in HOMA2‐%S and M, respectively. Decreases in PAT were only correlated with baseline PAT and the loss in VAT (r = ?0.56; P < 0.01; r = 0.42; P < 0.05) but no associations with liver fat or indexes of insulin sensitivity were observed. Improvements in HOMA_IR and HOMA2‐%B were only related to the decrease in IHCL (r = 0.62, P < 0.01; r = 0.65, P = 0.002) and decreases in IHCL only correlated with the decrease in VAT (r = 0.61, P = 0.004). In conclusion, cross‐sectionally PAT is correlated with VAT, liver fat, and insulin resistance. Longitudinally, the association between PAT and insulin resistance was lost suggesting no causal relationship between the two.     

Social networks and inflammatory markers in the Framingham Heart Study

Lack of social integration predicts coronary heart disease mortality in prospective studies; however, the biological pathways that may be responsible are poorly understood. The specific aims of this study were to examine whether social networks are associated with serum concentrations of the inflammatory markers interleukin-6 (IL-6), C-reactive protein (CRP), soluble intercellular adhesion molecule-1 (sICAM-1) and monocyte chemoattractant protein-1 (MCP-1). Participants in the Framingham Study attending examinations from 1998 to 2001 (n=3267) were eligible for inclusion in the study. Social networks were assessed using the Berkman-Syme Social Network Index (SNI). Concentrations of IL-6, CRP, sICAM-1 and MCP-1 were measured in fasting serum samples. Multivariable linear regression analyses were used to assess the association of social networks with inflammatory markers adjusting for potential confounders including age, smoking, blood pressure, total:HDL cholesterol ratio, body mass index, lipid-lowering and antihypertensive medication, diabetes, cardiovascular disease, depression and socioeconomic status. Results found that the SNI was significantly inversely associated with IL-6 in men (p=0.03) after adjusting for potential confounders. In age-adjusted analyses, social networks also were significantly inversely associated with IL-6 for women (p=0.03) and were marginally to modestly associated with CRP and sICAM-1 for men (p=0.08 and 0.02, respectively), but these associations were not significant in the multivariate analyses. In conclusion, social networks were found to be inversely associated with interleukin-6 levels in men. The possibility that inflammatory markers may be potential mediators between social integration and coronary heart disease merits further investigation.     

Genotype-by-sex interaction in the regulation of high-density lipoprotein: the Framingham Heart Study

Low levels of high-density lipoprotein (HDL) are widely documented as a risk factor for cardiovascular disease (CVD). Furthermore, there is marked sexual dimorphism in both HDL levels and the prevalence of CVD. However, the extent to which genetic factors contribute to such dimorphism has been largely unexplored. We examined the evidence for genotype-by-sex effects on HDL in a longitudinal sample of 1562 participants from 330 families in the Framingham Heart Study at three times points corresponding approximately to 1971-1974, 1980-1983, and 1988-1991. Using a variance component method, we conducted a genome scan of HDL at each time point in males and females, separately and combined, and tested for genotype-by-sex interaction at a quantitative trait locus (QTL) at each time point. Consistent findings were noted only for females on chromosome 2 near marker D2S1328, with adjusted LOD scores of 2.6, 2.2, and 2.1 across the three time points, respectively. In males suggestive linkage was detected on chromosome 16 near marker D16S3396 at the second time point and on chromosome 18 near marker D18S851 at the third time point (adjusted LOD = 2.2 and 2.4, respectively). Although the heritability of HDL is similar in males and females, sex appears to exert a substantial effect on the QTL-specific variance of HDL. When genotype-by-sex interactions exist and are not modeled, the power to detect linkage is reduced; thus our results may explain in part the paucity of significant linkage findings for HDL.     

Association of subcutaneous and visceral adiposity with albuminuria: the Framingham Heart Study

Microalbuminuria is a common condition associated with increased incidence of cardiovascular events and mortality. Abdominal obesity is associated with microalbuminuria, but studies linking visceral adipose tissue (VAT) and microalbuminuria are limited. Our objective was to determine the associations of albuminuria with VAT and subcutaneous adipose tissue (SAT). We performed a cross-sectional study in the Framingham Multi-Detector Computed Tomography (MDCT) cohort (n = 3099, 48.2% women, mean age 53 years). VAT and SAT volumes were measured using computed tomography. Urinary albumin-to-creatinine ratio (UACR) was calculated from spot urine samples. Microalbuminuria was defined as a UACR >25 mg/g in women or >17 mg/g in men. Overall, 7.9% (n = 244) of the sample had microalbuminuria. Among men, VAT (odds ratio (OR) 1.48 per s.d., P < 0.0001) and SAT (OR 1.37 per s.d., P = 0.0002) were associated with microalbuminuria in minimally adjusted models, which remained significant after multivariable adjustment (VAT OR 1.34 per s.d., P = 0.001; SAT OR 1.28 per s.d., P = 0.005). Additionally, when considered jointly, VAT (P = 0.002) but not SAT (P = 0.2) was associated with microalbuminuria. In women, VAT was associated with microalbuminuria after minimal adjustment (OR 1.28, P = 0.01), but not after multivariable adjustment (OR 1.03, P = 0.8). In multivariable models in women, SAT was associated with a decreased odds of having microalbuminuria (OR 0.75 per s.d., P = 0.03). In conclusion, VAT is associated with microalbuminuria in men but not women. Albuminuria may be a manifestation of visceral adiposity.     

Genome-Wide Association Study of Lp-PLA2 Activity and Mass in the Framingham Heart Study

Lipoprotein-associated phospholipase A₂ (Lp-PLA₂) is an emerging risk factor and therapeutic target for cardiovascular disease. The activity and mass of this enzyme are heritable traits, but major genetic determinants have not been explored in a systematic, genome-wide fashion. We carried out a genome-wide association study of Lp-PLA₂ activity and mass in 6,668 Caucasian subjects from the population-based Framingham Heart Study. Clinical data and genotypes from the Affymetrix 550K SNP array were obtained from the open-access Framingham SHARe project. Each polymorphism that passed quality control was tested for associations with Lp-PLA₂ activity and mass using linear mixed models implemented in the R statistical package, accounting for familial correlations, and controlling for age, sex, smoking, lipid-lowering-medication use, and cohort. For Lp-PLA₂ activity, polymorphisms at four independent loci reached genome-wide significance, including the APOE/APOC1 region on chromosome 19 (p = 6×10⁻²⁴); CELSR2/PSRC1 on chromosome 1 (p = 3×10⁻¹⁵); SCARB1 on chromosome 12 (p = 1×10⁻⁸) and ZNF259/BUD13 in the APOA5/APOA1 gene region on chromosome 11 (p = 4×10⁻⁸). All of these remained significant after accounting for associations with LDL cholesterol, HDL cholesterol, or triglycerides. For Lp-PLA₂ mass, 12 SNPs achieved genome-wide significance, all clustering in a region on chromosome 6p12.3 near the PLA2G7 gene. Our analyses demonstrate that genetic polymorphisms may contribute to inter-individual variation in Lp-PLA₂ activity and mass.     

Pericardial Fat and Atrial Conduction Abnormalities in the Multiethnic Study of Atherosclerosis (MESA)

Pericardial fat (Pfat) overlies the cardiac surface including atria and their inter‐ and intra‐conduction system. Through its local inflammatory effects, Pfat may predispose to atrial abnormalities that could be detected as changes in P‐wave morphology in the 12‐lead electrocardiogram (ECG). We evaluated the association between Pfat and ECG measurements of P wave and PR interval (referred to as P‐wave indexes): PR duration (PR‐dur), P‐wave duration (P‐dur), and P‐wave terminal force (P‐term), in the Multiethnic Study of Atherosclerosis (MESA). Participants with available Pfat measured by computed tomography (CT) and P‐wave indexes measured by ECG were included (N = 996). Differences in P‐wave indexes per 1 standard deviation difference in Pfat were tested in unadjusted linear regression analysis first, then adjusted for demographics (age, sex, and ethnicity), and further adjusted for measures of adiposity (BMI or waist circumference (WC)), or cardiovascular risk factors (hypertension (HTN), diabetes, and smoking). All P‐wave indexes were significantly associated with Pfat in unadjusted analyses (regression‐coefficient (β) (95% CI): PR‐dur (ms) 2.53 (1.02, 4.04), P‐dur (ms) 2.59 (1.84, 3.35), P‐term (µV·s) 0.25 (0.13, 0.36)). After demographics adjustment, P‐dur (1.68 (0.87, 2.49)) and P‐term (0.16 (0.04,0.28)), but not PR‐dur (1.11 (?0.52, 2.74)) were associated with Pfat. No associations were significant after adjustment for BMI, WC, or cardiovascular disease (CVD) risk factors. BMI and WC, separately, were significantly associated with P‐wave indexes in all models, including those that included Pfat as a covariate. BMI, but not WC, was associated with P‐wave indexes when the two were entered into the same model. In conclusion, Pfat is associated with P‐wave indexes, but not after adjusting for measures of adiposity or CVD risk factors. Among Pfat, BMI and WC, BMI had the most robust association with P‐wave indexes. These findings raise doubts about potential local effects of Pfat on atrial electrophysiology and morphology