Neural correlates of stress and leucocyte telomere length in patients with coronary artery disease

BACKGROUND

Accelerated biological aging, as indicated by telomere shortening, is associated with CAD pathogenesis. In a cross-sectional study, we investigated neural correlates of acute psychological stress and short telomeres in patients with CAD.

METHODS

Individuals with CAD (N = 168) underwent a validated mental stress protocol including public speaking and mental arithmetic. Imaging of the brain with [O-15] water and high-resolution positron emission tomography (HR-PET) was performed during mental stress and control conditions. Blood flow during stressful tasks (average of speech and arithmetic) and control tasks were assessed. Telomere length in peripheral leucocytes was measured by quantitative polymerase chain reaction and expressed as Telomere/Single Copy Gene (T/S) ratio. Voxel-wise regression models were constructed to assess the association between brain areas and activity during rest and mental stress after adjustments for demographic factors and clinical characteristics.

RESULTS

The mean (SD) age of the sample was 62 (8) years, and 69% were men. Increased activation with mental stress in the lingual gyrus, cerebellum and superior and inferior frontal gyri were associated with reduced telomere length; 1.6 higher voxel activation of these areas was associated with 0.1 T/S-units reduction in telomere length (P < 0.005). Additionally, during neutral counting and speaking tasks, brain activity in the precentral, middle and superior frontal and middle temporal gyri was inversely associated with telomere length. Results remained consistent after adjustment for demographic and clinical risk factors.

CONCLUSION

Increased stress-induced activity in brain areas mediating the stress response was associated with shortened telomere length in CAD patients.

Associations Between Inflammation, Cardiovascular Regenerative Capacity, and Cardiovascular Events: A Cohort Study

Objective

Circulating progenitor cells possess immune modulatory properties and might mitigate inflammation that is characteristic of patients with coronary artery disease. We hypothesized that patients with fewer circulating progenitor cells (CPCs) will have higher inflammatory markers and worse outcomes.

Approach and Results

Patients with stable coronary artery disease were enrolled in a prospective study enumerating CPCs as CD (cluster of differentiation)-34-expressing mononuclear cells (CD34+) and inflammation as levels of IL (interleukin)-6 and high-sensitivity CRP (C-reactive protein) levels. Patients were followed for 5 years for the end points of death and myocardial infarction with repeat inflammatory biomarkers measured after a median of 2 years. In the entire cohort of 392 patients, IL-6 and high-sensitivity CRP levels remained unchanged (0.3+/-2.4 pg/mL and 0.1+/-1.0 mg/L; P=0.45) after 2 years. CPC counts (log-transformed) were inversely correlated with the change in IL-6 levels (r, -0.17; P<0.001). Using linear regression, IL-6 and high-sensitivity CRP levels declined by -0.59 (95% CI, -0.90 to -0.20) pg/mL and -0.13 (-0.28 to 0.01) mg/L per 1 log higher CPC counts after adjustment for the demographic and clinical variables, as well as medications. Using Cox models adjusted for these risk factors, a rise in 1 pg/mL of IL-6 was associated with a 11% (95% CI, 9-13) greater risk of death/myocardial infarction. We found that the change in IL6 level partly (by 40%) mediated the higher risk of adverse events among those with low CPC counts.

Conclusions

Reduced cardiovascular regenerative capacity is independently associated with progressive inflammation in patients with coronary artery disease that in turn is associated with poor outcomes.

An open-source automated algorithm for removal of noisy beats for accurate impedance cardiogram analysis

OBJECTIVE

The impedance cardiogram (ICG) is a non-invasive sensing modality for assessing the mechanical aspects of cardiac function, but is sensitive to artifacts from respiration, speaking, motion, and electrode displacement. Electrocardiogram (ECG)-synchronized ensemble averaging of ICG (conventional ensemble averaging method) partially mitigates these disturbances, as artifacts from intra-subject variability (ISVar) of ICG morphology and event latency remain. This paper describes an automated algorithm for removing noisy beats for improved artifact suppression in ensemble-averaged (EA) ICG beats.

APPROACH

Synchronized ECG and ICG signals from 144 male subjects at rest in different psychological conditions were recorded. A 'three-stage EA ICG beat' was formed by passing 60-seconds non-overlapping ECG-synchronized ICG signals through three filtering stages. The amplitude filtering stage removed spikes/noisy beats with amplitudes outside of normal physiological ranges. Cross-correlation was applied to remove noisy beats in coarse and fine filtering stages. The accuracy of the algorithm-detected artifacts was measured with expert-identified artifacts. Agreement between the expert and the algorithm was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plots. The ISVar of the cardiac parameters was evaluated to quantify improvement in these estimates provided by the proposed method.

MAIN RESULTS

The proposed algorithm yielded an accuracy of 96.3% and high inter-rater reliability (ICC > 0.997). Bland-Altman plots showed consistently accurate results across values. The ISVar of the cardiac parameters derived using the proposed method was significantly lower than those derived via conventional ensemble averaging method (p < 0.0001). Enhancement in resolution of fiducial points and smoothing of higher-order time derivatives of the EA ICG beats were observed.

SIGNIFICANCE

The proposed algorithm provides a robust framework for removal of noisy beats and accurate estimation of ICG-based parameters. Importantly, the methodology reduced the ISVar of cardiac parameters. An open-source toolbox has been provided to enable other researchers to readily reproduce and improve upon this work.