Agnė Liuizė (Abramavičiūtė)

In recent years, the study of interleukins (ILs), crucial cytokines involved in inflammation, has garnered significant attention within coronary artery disease including atherosclerosis. This review provides a detailed overview of anti-inflammatory ILs, elucidating their functions within the pathogenesis of atherosclerosis. We examine aspects of all the known anti-inflammatory ILs role in atherosclerosis, the direct impact of these ILs on the inflammation; endothelial, smooth vascular cells and macrophage’s function; and their interactions with signaling pathways and molecules. The potential for diagnostic possibilities and targeted drug therapy to modulate anti-inflammatory ILs activity in atherosclerosis was explored. Taken together, findings from recent studies suggest that the main pathways through which ILs exerts its anti-inflammatory effects are: (1) taking part in the regulation of cholesterol transport or oxidised low-density lipoprotein (oxLDL) phagocytosis (IL-1Ra and IL-36Ra—indirectly); (2) affecting different blood cells’ participation in the inflammation (monocytes, lymphocytes, macrophages); (3) taking place in the remodelation of the arterial wall (affecting smooth muscle and endothelium cells). Overall, IL-35, IL-37, and IL-38 appear to be the most promising for modulation of signaling pathways in experimental works and could be investigated as treatment targets. Recombinant IL-10 is investigated in experimental models as therapeutic tool. IL-1Ra is started being translated into clinical practice already. IL-13 and IL-19 are the least studied. It turns out that anti-inflammatory ILs are unlikely to serve as diagnostic markers for atherosclerosis due to their limited specificity and inconsistent associations with disease progression, as well as insufficient validation in large human cohorts. Moreover, key challenges related to delivery, dosing, and safety remain unresolved.

This pilot hypothesis-generating study evaluated whether lipid-related biomarkers (Lp(a), ApoB, and oxLDL), endothelial injury markers (endocan, vimentin), and extracellular matrix glycoproteins (TSP-1, TSP-2) reflect the severity of coronary artery disease (CAD) in patients with stable angina pectoris. 93 patients underwent invasive coronary angiography/coronary CT angiography. CAD severity was evaluated using Gensini, SIS, SSS, and CAD-RADS scores. CAD was confirmed in 76.3% (n = 71). OxLDL correlated with Gensini (r = 0.455; p = 0.006), atherosclerotic segments (r = 0.469; p = 0.005), arteries (r = 0.479; p = 0.004), revascularization indication (r = 0.318; p = 0.003), circumflex artery stenosis (r = 0.323; p = 0.005). OxLDL also correlated with vimentin (r = 0.459; p < 0.001). Vimentin correlated with Gensini (r = 0.480; p = 0.005), SIS (r = 0.349; p = 0.003), SSS (r = 0.320; p = 0.008), CAD-RADS (r = 0.331; p = 0.005), atherosclerotic segments (r = 0.515; p = 0.003), arteries (r = 0.384; p = 0.030), revascularization indication (r = 0.324; p = 0.003). Endocan, TSP-1, and TSP-2 showed no significant associations. These exploratory findings suggest that oxLDL and vimentin may be associated with CAD severity; however, confirmation in larger, prospective cohorts is required.

Background/Objectives: Some calculated total blood count readings are investigated as novel additional readings to help with evaluation of personalized CAD patients’ clinical management and prognosis. We aimed to investigate the association between readings such as NLR, MLR, PLR, NMR, LMR, MHR, SII, and SIRI and the severity of CAD in patients with SAP. Methods: This retrospective pilot study included 166 patients. All patients underwent CA or CCTA, or both, to assess severity of CAD. Patients were divided three ways: (1) according to presence (n = 146) or absence (n = 20) of CAD; (2) according to Gensini score; (3) according to the CAD-RADS score. Results: Patients with CAD had lower LMR, higher NLR, SIRI, MLR, and SII compared to patients without CAD (p < 0.001 and p = 0.018, respectively for SII). According to the CAD severity by Gensini score, the NLR, MLR, SII, and SIRI values increase and LMR decreases gradually with severity of CAD (p < 0.001). A moderate correlation was found between SII (r = 0.511, p < 0.001), NLR (r = 0.567, p < 0.001), and SIRI (r = 0.474, p < 0.001) and severity of CAD according to Gensini score. MLR and LMR had a low corelation with severity of CAD according to Gensini score (r = 0.356, p < 0.001; r = −0.355, p < 0.001, respectively). The CAD-RADS score weakly correlated with NLR and MHR (r = 0.365, p < 0.001; r = 0.346, p < 0.001, respectively), and moderately with LMR, MLR, and SIRI (r = −0.454, p < 0.001; r = 0.455, p < 0.001; r = 0.522, p < 0.001, respectively). Conclusions: NLR, LMR, and SIRI appear to be potential predictors of chronic inflammation, and SIRI is the best predictor of the degree of atherosclerosis of all the other assessed blood parameters.

Background: Some calculated total blood count readings are investigated as additional readings to help with evaluation of CAD patients’ clinical management and prognosis. Aim: We aimed to investigate the association between readings such as NLR, MLR, PLR, NMR, LMR, MHR, SII, SIRI and the severity of CAD in patients with SAP. Methods: This retrospective pilot study included 166 patients. All these patients underwent CA or CCTA, or both, to assess severity of CAD. Patients were divided into three ways: 1) according to presence (n=146) or absence (n=20) of CAD; 2) according to Gensini score; 3) according to the CAD-RADS score. Results: Patients with CAD had lower LMR, higher NLR, SIRI, MLR and SII compared to patients without CAD (p respectively for SII). According to the CAD severity by Gensini score, the NLR, MLR, SII and SIRI values increases and LMR decreases gradually with severity of CAD (p , NLR (r=0.567, p and SIRI (r=0.474, p and severity of CAD according to Gensini score. MLR and LMR low correlated with severity of CAD according to Gensini score (r=0.356, p ; r=-0.355, p respectively ) . The CAD-RADS score weakly correlated with NLR and MHR (r=0.365, p , respectively), and moderately – with LMR, MLR and SIRI ( r=-0.454, p respectively ) . Conclusions: NLR, LMR and SIRI appear to be potential predictors of chronic inflammation, and SIRI is the best predictor of the degree of atherosclerosis of all the other assessed blood parameters.