Circulating Inflammatory Markers Are Inversely Associated with Heart Rate Variability Measures in Type 1 Diabetes

Abstract

Introduction. A neuroimmune communication exists, and compelling evidence suggests that diabetic neuropathy and systemic inflammation are linked. Our aims were (1) to investigate biomarkers of the ongoing inflammation processes including cytokines, adhesion molecules, and chemokines and (2) to associate the findings with cardiovascular autonomic neuropathy in type 1 diabetes by measuring heart rate variability and cardiac vagal tone. Materials and Methods. We included 104 adults with type 1 diabetes. Heart rate variability, time domain, and frequency domains were calculated from a 24-hour Holter electrocardiogram, while cardiac vagal tone was determined from a 5-minute electrocardiogram. Cytokines (interleukin- (IL-) 1α, IL-4, IL-12p70, IL-13, IL-17, and tumor necrosis factor- (TNF-) α), adhesion molecules (E-selectin, P-selectin, and intercellular adhesion molecule- (ICAM-) 1), and chemokines (chemokine (C-C motif) ligand (CCL)2, CCL3, CCL4, and C-X-C motif chemokine (CXCL)10) were assessed using a Luminex multiplexing technology. Associations between concentrations of inflammatory biomarkers and continuous variables of heart rate variability and cardiac vagal tone were estimated using multivariable linear regression adjusting for age, sex, disease duration, and smoking. Results. Participants with the presence of cardiovascular autonomic neuropathy had higher systemic levels of IL-1α, IL-4, CCL2, and E-selectin than those without cardiovascular autonomic neuropathy. IL-1α, IL-4, IL-12, TNF-α, and E-selectin were inversely associated with both sympathetic and parasympathetic heart rate variability measures (p>0.01). Discussion. Our results show that several pro- and anti-inflammatory factors, believed to be involved in the progression of diabetic polyneuropathy, are associated with cardiovascular autonomic neuropathy, suggesting that these factors may also contribute to the pathogenesis of cardiovascular autonomic neuropathy. Our findings emphasize the importance of the neuroimmune regulatory system in the pathogenesis of neuropathy in type 1 diabetes.

Elevated levels of interleukin-12/23p40 may serve as a potential indicator of dysfunctional heart rate variability in type 2 diabetes

“…For instance, it has been shown that anticoagulative medications decrease the risk of thromboembolism in diabetes [34], the triglyceride-glucose index is associated with the risk of stroke [35], and adiponectin is associated with major adverse cardiovascular events [36]. Neither of these was measured in this study, we have, however, previously shown an association between adiponectin with heart rate variability measures in type 1 diabetes [37]. Fourthly, a large proportion of the cohort used antihypertensive medication, including β-blockers, which may affect the study results.…”

Serum ICAM-1 as a Predictor of Prognosis in Patients with Acute Ischemic Stroke

“…ICAM-1 can produce soluble ICAM-1 through alternative splicing, which can be measured in various body fluids [ 9 ]. Studies have shown that ICAM-1 levels are elevated in atherosclerosis, cardiovascular disease, and metabolic vascular neuropathy [ 10 – 13 ]. However, there are still few studies on the correlation between ICAM-1 and AIS.…”

Associations between heart rate variability, peripheral inflammatory markers and major depressive disorder

“…In our study, lower RSA correlated with increased inflammation-related cytokines (most strongly TNFa, but also IL-6, IL1a and IFNg; not with CRP). Relationships between heart rate variability and cytokines have been reported earlier in patients with a broad range of diseases such as those with heart failure (Malave et al, 2003;Nikolic et al, 2013), obesity and diabetes (Parish et al, 2016;Wegeberg et al, 2020), obstructive sleep apnea (Xie et al, 2020), infants with hypoxic ischemic encephalopathy (Al-Shargabi et al, 2017;Yasova Barbeau et al, 2019), in traumatic brain injury (Deepika et al, 2018), to name just a few, and in larger samples of healthy subjects (Cooper et al, 2015;Lampert et al, 2008;von Kanel et al, 2008). Note that all papers cited demonstrated a low-HRV-associated-with-high-cytokines relationship, although not always using the same measures for HRV/cytokines, but according to a recent meta-analysis, SDNN and HF-HRV should show the largest effect sizes (Williams et al, 2019).…”