Relationship Between Infectious Burden, Systemic Inflammatory Response, and Risk of Stable Coronary Artery Disease: Role of Confounding and Reference Group
Overview
Authors
Affiliations
Aim: The purpose of the study was to assess the association between seropositivity to various infectious agents and stable coronary artery disease (CAD), controlling simultaneously for a variety of potential confounders. We also investigated whether the choice of a larger reference group might affect the results, and whether or not seropositivity to multiple agents was associated with a systemic inflammatory response.
Methods: We assessed the simultaneous prevalence of antibodies against Helicobacter pylori, Chlamydia, cytomegalovirus, and herpes simplex virus in 312 patients with angiographically proven coronary artery disease (CAD) and in 479 age and sex matched controls. C-reactive protein, interleukin-6, fibrinogen, PAI-1-activity, D-dimer, von Willebrand Factor, plasma viscosity, and a complete blood cell count were determined in all subjects.
Results: Seropositivity to all of the four agents was 21.8% in cases and 13.6% in controls (P=0.0003). We found a dose-response relationship between combined IgG-seropositivity to H. pylori, Chlamydia, cytomegalovirus, and herpes simplex virus and odds for the presence of angiographically confirmed stable CAD which, however, was strongly reduced after controlling for a variety of potential confounders. The dose-response pattern was no longer evident if a more stable reference group (subjects seropositive for two agents) was used instead of the relatively small reference group with zero or one seropositivity. We found no consistent pattern between IgG-seropositivity to several pathogens and inflammatory markers.
Conclusions: Based on serological evidence of various infectious agents, this study suggests that the aggregate number of persistent infections is not independently associated with an increased risk for CAD if control for confounding and use of a stable reference group are guaranteed.
Mendelian randomization analysis using multiple biomarkers of an underlying common exposure.
Jin J, Qi G, Yu Z, Chatterjee N Biostatistics. 2024; 25(4):1015-1033.
PMID: 38459704 PMC: 11879930. DOI: 10.1093/biostatistics/kxae006.
Wang Q, Liu Y, Xu Z, Wang Z, Xue M, Li X Front Microbiol. 2023; 14:1259579.
PMID: 37779702 PMC: 10538966. DOI: 10.3389/fmicb.2023.1259579.
Tong L, Wang B, Li F, Lv S, Pan F, Dong X Front Cardiovasc Med. 2022; 9:794445.
PMID: 35571162 PMC: 9098821. DOI: 10.3389/fcvm.2022.794445.
Hartog L, S van Rooijen M, Ujcic-Voortman J, Prins M, van Valkengoed I BMC Public Health. 2018; 18(1):276.
PMID: 29471811 PMC: 5824549. DOI: 10.1186/s12889-018-5162-x.
Nazmi A, Diez-Roux A, Jenny N, Tsai M, Szklo M, Aiello A BMC Public Health. 2010; 10:706.
PMID: 21083905 PMC: 2996373. DOI: 10.1186/1471-2458-10-706.