Associations of Overall Sleep Quality, measured by the Pittsburgh Sleep Quality Index (PSQI), and Cardiovascular Inflammatory Biomarkers; a cross-sectional study Öffentlichkeit
Krishnaswamy, Akshaya (Spring 2019)
Published
Abstract
Background: Previous research has demonstrated a link between sleep duration and cardiovascular disease (CVD) risk, potentially through systemic inflammation. However, most of this evidence has emerged from experimental sleep deprivation studies in healthy populations. The goal of this investigation was to examine the relationship between chronic sleep quality and circulating levels of inflammatory biomarkers among healthy patients and patients with a history of myocardial infarction (MI), as well as by race within these subgroups.
Methods: Individuals with a verified history of MI and matched community controls completed the Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality and sleep-related symptoms in the previous month. Inflammatory biomarkers including interleukin-6 (IL-6), C-reactive protein (CRP), monocyte chemoattractant protein (MCP-1), and matrix metallopeptidase 9 (MMP-9) were measured from venous blood samples. We conducted unadjusted and adjusted linear regression analyses to assess the percent difference in each of these biomarkers for each 5-point increase in PSQI score within study groups.
Results: Mean overall PSQI score among MI cases and healthy controls was 8.08 and 5.90, respectively. The overall PSQI score was positively weakly correlated with IL-6 (r=0.14, p=0.03), CRP (r=0.21, p=0.0007), and MCP-1 (r=0.24, p<.0001) among MI cases, with slightly weaker but overall similar correlations among controls. There were similar correlations across races within each study group. While we did not detect significant interactions between PSQI score and study group, PSQI score and race, and PSQI score, study group, and race, associations between PSQI score and inflammatory biomarkers appeared stronger among MI cases. Linear regression analyses revealed that each 5-point increase in overall PSQI score was associated with a 7.1% difference in MCP-1 among MI cases (p=0.003), and a 6.0% (p=0.2) difference among controls after adjustment for demographic and clinical risk factors. The percent difference in other inflammatory biomarkers and PSQI score were weaker and tended to attenuate after adjustment.
Conclusion: Our data show poor sleep quality is significantly associated with elevated levels of inflammatory biomarker MCP-1, among MI cases and controls. These findings suggest that poor sleep quality is related to increased systemic inflammation in both healthy individuals and those with a prior MI.
Table of Contents
1. Introduction
2. Methods
2.1 Study design
2.2 Assessment of sleep quality
2.3 Measurement of inflammatory biomarkers
2.4 Other measurements
2.5 Study participants
2.6 Statistical Analysis
3. Results
3.1 Descriptive characteristics
3.2 Sleep characteristics by study group and race
3.3. Inflammatory biomarker levels by study group and race
3.4 Associations between overall PSQI score and inflammatory biomarkers by study group and race
Discussion
References
Table 1. Characteristics of MIMS-2 Study Participants, by Study Group.
Table 2. Characteristics of MIMS-2 Study Participants, by Study Group and Race.
Table 3. Sleep Characteristics of MIMS-2 Study Participants by Study Group.
Table 4. Sleep Characteristics of MIMS-2 Study Participants, by Study Group and Race.
Table 5. Geometric Mean Inflammatory Biomarker Levels of MIMS-2 Study Participants by Study Group.
Table 6. Geometric Mean Inflammatory Biomarker Levels of MIMS-2 Study Participants by Study Group and Race.
Table 7. Spearman Correlation Coefficients between Overall PSQI Score and Individual Inflammatory Biomarkers, by Study Group.
Table 8. Spearman Correlation Coefficients between Overall PSQI Score and Individual Inflammatory Biomarkers, by Study Group and Race.
Table 9. Unadjusted and Adjusted Percent Difference in Inflammatory Biomarkers for Each 5-point increase in Overall PSQI Score.
Table 10. Associations between PSQI Subscale Scores and Inflammatory Biomarkers (Continuous) in MIMS-2 population.
Figure 1. Geometric Mean of IL-6 (pg/ml) by Study Group.
Figure 2. Geometric Mean of CRP (mg/L) by Study Group.
Figure 3. Geometric Mean of MCP-1 (pg/ml) by Study Group.
Figure 4. Geometric Mean of MMP-9 (ng/ml) by Study Group.
About this Master's Thesis
| School | |
|---|---|
| Department | |
| Subfield / Discipline | |
| Degree | |
| Submission | |
| Language |
|
| Research Field | |
| Stichwort | |
| Committee Chair / Thesis Advisor |
Primary PDF
| Thumbnail | Title | Date Uploaded | Actions |
|---|---|---|---|
|
|
Associations of Overall Sleep Quality, measured by the Pittsburgh Sleep Quality Index (PSQI), and Cardiovascular Inflammatory Biomarkers; a cross-sectional study () | 2019-04-25 10:24:14 -0400 |
|
Supplemental Files
| Thumbnail | Title | Date Uploaded | Actions |
|---|