- Academic Editor
Background: Coronary artery atherosclerosis development and progression are related to generic, clinical, and lifestyle factors combined with inflammatory activation. The relationship between trace element concentration and morbidity is under investigation to gain a clearer understanding of underlying pathological processes. Methods: Thirty-five consecutive patients (22 males and 13 females) with a median [interquartile range (IQR)] age of 67 (61–73) years presenting with anginal symptoms were included in the single center prospective analysis in 2022 and divided into a epicardial coronary artery disease (CAD) and non-CAD group. Scalp hair chemical analysis and inflammatory markers from a peripheral blood count were analyzed. Results: The correlation analysis of elements and inflammatory indexes showed statistical significance between median hair lithium (Li) concentration and the systemic inflammatory index (SII) (r = –0.476, p = 0.046), antimony (Sb) (r = –0.521, p = 0.028) followed by chromium (Cr) (r = –0.478, p = 0.045) and iron (Fe) (r = –0.604, p = 0.008) in the CAD group. Similar correlations were not found in non-CAD group. Conclusions: The correlation between scalp hair lithium (Li), antimony (Sb), chromium (Cr) and iron (Fe) concentration and the systemic inflammatory index (SII) were revealed only in patients with coronary artery disease. Our analysis identified a strong correlation between inflammatory activation and iron concentration.
Coronary artery atherosclerosis development and progression are related to well-known factors, including genetic burden, arterial hypertension, diabetes, obesity, smoking, hypercholesterolemia, but also inflammatory activation [1, 2]. Inflammatory reactions are said to be involved in the initial stages of atherosclerotic plaque formation [3], but also in the pathophysiology of acute coronary syndromes [4].
Anginal symptoms may be related to epicardial coronary artery disease (CAD) [5]. Currently, up to 40% of symptomatic patients referred for coronary angiography present with normal coronary arteries, and microvascular disease indicating endothelial dysfunction, coronary spasm, or small vessel disease [6].
Serum concentration of trace elements have been found to be related to inflammatory markers by Akdas et al. [7]. Not only serum but also hair mineral concentration is claimed to possess diagnostic properties in patients with inflammatory diseases [8]. A negative correlation between trace metal serum concentration and chronic inflammatory diseases was postulated [9]. Serum trace elements are involved in vital cellular reactions as co-factors [10].
On the contrary, metals and metalloid concentrations, especially measured in hair, represent an increased risk for dietary, pollution or working environment toxication and are related to increased morbidity in the current population [11]. The vascular effects of metal concentration have been presented [12]. A relationship between serum trace elements and inflammatory indexes were found among patients with CAD [13].
The prognostic value of inflammatory activation, estimated by indexes, for long-term prognosis in patients with atherosclerosis of coronary arteries was already proven [14].
The aim of the study was to compare trace elements, metalloids and metal concentration in hair with inflammatory indices obtained from the whole blood count in patients with multivessel CAD.
Thirty-five consecutive symptomatic patients (22 males and 13 females) with a median age of 67 (61–73) years who were white, not Hispanic nor Latino, were included in the single center prospective study in 2022 and divided into two groups (Supplementary Fig. 1). The first group (CAD) was composed of 18 (13 (72%) males and 5 (28%) women) consecutive patients with a median age of 69 (62–73) years, admitted for revascularization due to stable multivessel CAD. Group 2 (non-CAD) consisted of 17 (9 (53%) males and 8 (47%) females) in a median age of 66 (61–70) years presenting with anginal symptoms and normal result of coronary angiography. All patients were married, and gave information about their high-school education (20 (57%)) and less than high (15 (43%)), respectively.
All patients were referred for coronary angiography due to clinical symptoms after careful evaluation. On admission, whole blood count samples were obtained for analysis. Patients with element supplementation, chronic kidney dysfunction, co-existence of valvular or aortic pathology requiring surgery or with a history of inflammatory, autoimmune, hematological proliferative or other oncological diseases, were excluded from the analysis. Moreover, patients with co-existing metabolic syndrome, liver steatosis/liver cirrhosis, gout, carotid artery disease, thyroid disease, anemias, drug abuse heart failure mental disorders and gastrointestinal bleeding history, depression, and positive viral infection (including hepatic and human immunodeficiency (HIV) viruses) were not included into the analysis. Those with outstanding, restrictive or exclusion diets were not included in the study.
Hair was collected on the day of admission for chemical analysis. The hair was cut from the scalp, just above the neck, using scissors made of titanium. Hair samples were stored in plastic containers. Blood samples were collected on admission after 6 hours of fasting. The analyses were performed three times each using acquired sample.
Peripheral blood count parameter analysis was performed using a routine hematology analyzer (Sysmex Europe GmbH, Norderstedt, Germany). The inflammatory indexes were calculated based on the whole blood sample analysis, including neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), platelet to lymphocyte ratio (PLR), as well as systemic inflammatory response index (SIRI) – neutrophils and monocytes counts divided by the lymphocyte count, systemic inflammatory index (SII) – neutrophils and platelets counts divided by the lymphocyte count, and aggregate index of systemic inflammation (AISI) – neutrophils, monocytes, and platelets counts divided by the lymphocyte count [15, 16]. Serum troponin and creatinine concentrations were included in the biochemical analysis.
A total of 0.5 g of hair for each subject was collected for this analysis. Hair
samples were washed by stirring with different solvents in sequence: acetone,
deionized water, 0.5% Triton X-100 solution and deionized water. Next hair was
dried and cut into smaller pieces. These prepared samples were digested in a
high-pressure closed microwave digestion system (Ethos One, Milestone, Sorisole,
Italy). Digestion was carried out as follows: 200 mg of dry hair sample was
accurately weighed into the microwave vessels and then 3 mL of 65% HNO
The validity of the analytical method was assessed by analysing the certified reference materials (CRMs) NCS ZC 81002b Human Hair (Beijing, China). The CRMs were digested according to the same procedure as the hair samples. Validation parameters such as linearity, precision, limit of detection (LOD) and trueness were evaluated. The linearity of the calibration curve was calculated as the correlation coefficient (R), the value of which is greater than 0.9996 for all analytes. The linear range for the calibration curve of the elements was reached from the detection limit up to 100 µg/L. The detection limit (LOD) was defined as 3.3 s/b, where s is the standard deviation corresponding to 10 blank injections and b is the slope of the calibration graph. The LOD values were in range of 0.006 µg/g for Cd to 10 µg/g for Ca. Precision values were calculated as coefficient of variation (CV) (%) ranged from 1.5% to 3.4% for all elements. Trueness was evaluated by applying the certified reference material and expressed as recovery values (%), and ranged from 94% to 107%, respectively.
Calculations were made using using MedCalc® Statistical Software version 20.027 (MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org; 2022). The significance level was p = 0.05. The normality of the distribution of variables was tested with the Shapiro-Wilk test. The t-test, Cochran-Cox test or Mann-Whitney tests were calculated to compare the variables between two groups. The influence of the concentration of chemical elements on the parameters of inflammation was examined using the Pearson’s linear correlation coefficient or the Spearman’s rank correlation coefficient. In order to examine the relationship between categorical variables, Fisher’s exact test was calculated.
Multivessel CAD was defined as coronary artery atherosclerosis with diameter of more than 50% in more than one major coronary artery or its branches. By consecutive patients, we defined patients who were operated on in a succeeding manner. Symptomatic patients were defined by having chest pain on exertion, while patients with unstable CAD were not included in the analysis.
The study groups comprised thirty-five patients, 22 males and 13 females with a median [interquartile range (IQR)] age of 67 (61–73) years. Over 80% of them presented with traditional risk factors of CAD, including arterial hypertension (n = 32, 91%), hypercholesterolemia (n = 31, 87%), and diabetes (n = 15, 43%). Moreover, two patients (6%) reported a history of chronic obstructive pulmonary disease, three (9%) had peripheral artery disease, five (14%) had paroxysmal atrial fibrillation. Smoking history was present in 17 (49%) patients as presented in Table 1.
Parameters | Whole group | Group 1 CAD | Group 2 non-CAD | p | |
n = 35 | n = 18 | n = 17 | 1 vs 2 group | ||
Demographical: | |||||
Age (mean (SD) years) | 65.8 (8.7) | 66.7 (8.2) | 64.8 (9.4) | 0.538 | |
Gender (M (%)/F (%)) | 22 (62.9)/13 (37.1) | 13 (72.2)/5 (27.8) | 9 (52.9)/8 (47.1) | 0.305 | |
BMI (median (Q1–Q3)) | 27.4 (26.2–32.2) | 27.3 (24.4–30.8) | 31.8 (26.8–33.5) | 0.192 | |
Waist circumference | 101 (94–110) | 99 (92–105) | 104 (96–112) | 0.112 | |
Waist/hip ratio | 0.92 (0.87–0.96) | 0.88 (0.86–0.94) | 0.93 (0.91–1.01) | 0.089 | |
Pharmacotherapy: | |||||
Beta-blocker (n (%)) | 35 (100) | 18 (100) | 17 (100) | 1.000 | |
ACEI (n (%)) | 32 (91.4) | 18 (100) | 14 (82.4) | 0.104 | |
Aspirin (n (%)) | 35 (100) | 18 (100) | 17 (100) | 1.000 | |
Statins (n (%)) | 31 (88.6) | 15 (83.3) | 16 (91.4) | 0.603 | |
Metformin (n (%)) | 15 (42.9) | 5 (27.8) | 10 (58.2) | 0.090 | |
NOAC (n (%)) | 5 (14.3) | 0 (0) | 5 (29.4) | 0.019 | |
Inhaled medication (n (%)) | 2 (5.7) | 0 (0) | 2 (11.8) | 0.229 | |
Heart rate (median (Q1–Q3)) | 61 (53–70) | 62 (53–71) | 59 (53–67) | 0.897 | |
Systolic blood pressure (median (Q1–Q3)) | 126 (120–136) | 124 (119–135) | 128 (121–137) | 0.911 | |
Diastolic blood pressure (median (Q1–Q3)) | 78 (73–83) | 78 (73–83) | 79 (74–83) | 0.891 | |
Clinical: | |||||
Arterial hypertension (n (%)) | 32 (91.4) | 18 (100) | 14 (82.4) | 0.104 | |
DM (n (%)) | 15 (42.9) | 5 (27.8) | 10 (58.5) | 0.090 | |
COPD (n (%)) | 2 (5.7) | 0 (0) | 2 (11.8) | 0.229 | |
PAD (n (%)) | 3 (8.6) | 1 (5.6) | 2 (11.8) | 0.603 | |
Hypercholesterolemia (n (%)) | 31 (88.6) | 15 (83.3) | 16 (94.1) | 0.603 | |
Atrial fibrillation (n (%)) | 5 (14.3) | 0 (0) | 5 (29.4) | 0.019 | |
Nicotinism (n (%)) | 17 (48.6) | 9 (50) | 8 (47) | 1.000 |
Abbreviations: CAD, coronary artery disease; SD, standard deviation; ACEI, angiotensin converting enzyme inhibitor; BMI, body mass index; COPD, chronic obstructive pulmonary disease; DM, diabetes mellitus; F, female; NOAC, novel oral anticoagulant; M, male; PAD, peripheral artery disease.
In the presented group 1, there were no intra nor postoperative deaths, and the median [IQR] hospitalization time after surgery was 7 (6–9) days. Surgical procedures were performed as off-pump surgery (beating heart surgery). The mean (SD) number of performed grafts was 2 (2.3). Ten patients underwent total arterial revascularization, including eight with two internal mammary arteries and one with three arterial grafts application (two mammary arteries and left radial artery). The preoperative laboratory results were analyzed as presented in Table 2.
Parameters | Whole group | Group 1 CAD | Group 2 non-CAD | p | |
(median (Q1–Q3)) | n = 35 | n = 18 | n = 17 | 1 vs 2 group | |
Whole blood count analysis: | |||||
WBC (K/µL) | 8.3 (2.1) | 8.2 (2.1) | 8.5 (2.1) | 0.771 (t-S) | |
Neutrophils (K/µL) | 5.1 (4.2–7.3) | 5.9 (2.0) | 5.608 (2.5) | 0.669 (t-S) | |
Lymphocytes (K/µL) | 1.6 (1.4–2.1) | 1.6 (0.4) | 1.867 (0.9) | 0.187 (t-S) | |
NLR | 3.6 (2.1–4.7) | 3.9 (2.8–4.9) | 2.3 (1.9–3.7) | 0.151 (MW) | |
Monocytes (K/µL) | 0.5 (0.4–0.6) | 0.4 (0.3–0.5) | 0.6 (0.4–0.7) | 0.028 (MW) | |
MLR | 0.3 (0.2–0.4) | 0.3 (0.2–0.3) | 0.3 (0.2–0.4) | 0.804 (MW) | |
SII | 833 (490–1191) | 921 (693–1429) | 569 (424–922) | 0.151 (MW) | |
AISI | 355 (256–602) | 383 (312–63) | 330 (217–844) | 0.882 (MW) | |
SIRI | 1.5 (1.0–2.3) | 1.7 (1.1–2.2) | 1.4 (0.9–3.7) | 0.882 (MW) | |
LUC (K/µL) | 0.1 (0.1–0.1) | 0.11 (0.03) | 0.13 (0.049) | 0.177 (t-S) | |
Eosinophils (K/µL) | 0.1 (0.09–0.2) | 0.13 (0.1) | 0.18 (0.09) | 0.08 (t-S) | |
Basophils (K/µL) | 0.03 (0.03–0.05) | 0.03 (0.02) | 0.04 (0.022) | 0.263 (t-S) | |
Rbc (M/µL) | 4.7 (4.3–5.0) | 4.8 (0.4) | 4.7 (0.9) | 0.702 | |
Hemoglobin | 8.8 (0.7) | 8.8 (0.5) | 8.8 (0.9) | 0.918 | |
Hematocrit (%) | 43 (41–45) | 43 (42–45) | 43 (41–49) | 0.790 (MW) | |
Platelets (K/µL) | 231 (58) | 235 (70) | 227 (44) | 0.692 (t-S) | |
MPV (fL) | 8.5 (7.8–9.2) | 8.2 (7.4–8.7) | 8.6 (8.2–9.4) | 0.124 (MW) | |
Lipid profile: | |||||
Total cholesterol (mmol/L) | 4.2 (0.9) | 4.03 (3.6–4.7) | 4.1 (3.67–4.2) | 0.890 (MW) | |
HDL (mmol/L) | 1.2 (0.3) | 1.2 (0.3) | 1.2 (0.4) | 0.832 (t-S) | |
LDL (mmol/L) | 2.4 (2.1–2.9) | 2.4 (2.3–3.2) | 2.3 (2.0–2.6) | 0.295 (MW) | |
Kidney function: | |||||
GFR (mL/min) | 70 (18) | 76 (19) | 64 (186) | 0.065 (t-S) | |
Creatinine (mmol/L) | 89 (73–111) | 84 (72–107) | 94 (78–111) | 0.338 (MW) | |
CRP | 5 (3–8) | 6 (3–7) | 5 (4–8) | 0.678 (MW) |
Abbreviations: CAD, coronary artery disease; AISI, aggregate inflammatory syndrome index; CRP, C-reactive protein; GFR, glomerular filtration rate; HDL, high density lipoprotein; MLR, monocyte to lymphocyte ratio; MPV, mean platelet volume; MW, test Mann-Whitney; NLR, neutrophil to lymphocyte ratio; LDL, low density lipoprotein; LUC, large unstained cell count; Rbc, red blood cell count; t-S, t-Student test; SII, systemic inflammatory index; SIRI, systemic inflammatory response index; WBC, white blood cell count.
The whole blood count component comparison between both groups revealed
significant differences, including median [IQR] monocyte count (0.44 [0.35–0.46]
The median [IQR] concentrations of metal in head hair included three samples for each patient giving 105 examinations overall. There were no statistical differences regarding metal concentration in head hair between CAD and non-CAD group as presented in Table 3.
Parameters | Whole group | Group 1 (CAD) | Group 2 (non-CAD) | p |
(Median (Q1–Q3)) | n = 35 | n = 18 | n = 17 | 1 vs 2 group |
Li | 0.08 (0.06–0.17) | 0.07 (0.04–0.13) | 0.10 (0.06–0.19) | 0.245 |
Na | 537 (362–1328) | 435 (345–1326) | 591 (410–1240) | 0.568 |
Mg | 60 (28–130) | 59 (38–123) | 60 (24–138) | 0.935 |
Al | 38 (19–90) | 33 (22–104) | 38 (16–79) | 0.684 |
K | 173 (112–337) | 161 (111–342) | 174 (119–304) | 0.807 |
Ca | 960 (344–2011) | 938 (344–2167) | 960 (416–1404) | 0.660 |
Cr | 1.65 (1.14–3.69) | 1.65 (1.12–4.61) | 1.71 (1.21–3.61) | 0.935 |
Mn | 1.07 (0.73–1.94) | 1.07 (0.75–1.72) | 1.19 (0.28–2.09) | 0.935 |
Fe | 18 (12–34) | 21 (14–32) | 19 (10–41) | 0.987 |
Co | 0.02 (0.01–0.05) | 0.02 (0.01–0.08) | 0.01 (0.00–0.05) | 0.364 |
Ni | 0 (0–0.55) | 0.01 (0–0.98) | 0 (0–0) | 0.114 |
Cu | 20 (17–27) | 19 (15– 22) | 23 (19–33) | 0.118 |
Zn | 66 (0–132) | 54 (0–134) | 107 (0–127) | 0.711 |
As | 0.18 (0.09–0.31) | 0.16 (0–0.25) | 0.22 (0.14–0.31) | 0.191 |
Se | 0.46 (0.16–0.97) | 0.35 (0.09–0.65) | 0.50 (0.23–1.32) | 0.215 |
Cd | 0.04 (0.02–0.07) | 0.04 (0.02–0.10) | 0.03 (0.01–0.06) | 0.399 |
Sb | 0.01 (0.00–0.01) | 0.01 (0.000–0.01) | 0.01 (0.00–0.01) | 0.732 |
Pb | 0 (0–0) | 0 (0–0.13) | 0 (0–0) | 0.158 |
Abbreviations: CAD, coronary artery disease; Al, aluminium; As, arsenic; Ca, calcium; Cd, cadmium; Co, cobalt; Cr, chromium; Cu, copper; Fe, iron; K, potassium; Li, lithium; Mg, magnesium; Mn, manganese; Na, sodium; Ni, nickel; Pb, lead; Sb, antimony; Se, selenium; Zn, zinc.
The correlation analyses of trace elements and inflammatory indexes in the CAD group were performed and a statistical significance was found between median hair lithium (Li) concentration and the systemic inflammatory index (SII) (r = –0.476, p = 0.046), as presented in Fig. 1a, antimony (Sb) (r = –0.521, p = 0.028) as presented in Fig. 1b, followed by chromium (Cr) (r = –0.478, p = 0.045) in relation to SII presented in Fig. 1c. The relationship between hair iron (Fe) concentration and SII (r = –0.604, p = 0.008) in CAD group is presented in Fig. 1d.
The correlation analyses of trace elements and inflammatory indexes. (a) Correlation between the systemic inflammatory index (SII) and lithium (Li) hair scalp concentration. (b) Correlation between systemic inflammatory index (SII) and antimony (Sb) hair scalp concentration. (c) Correlation between the systemic inflammatory index (SII) and chromium (Cr) hair scalp concentration. (d) Correlation between the systemic inflammatory index (SII) and iron (Fe) hair scalp concentration.
The significance of the presented correlations was not detected in the non-CAD group between median hair lithium (Li) concentration and the systemic inflammatory index (SII) (r = 0.309, p = 0.227), antimony (Sb) (r = 0.141, p = 0.589) followed by chromium (Cr) (r = 0.397, p = 0.114) and iron (Fe) (r = 0.444, p = 0.074).
Moreover, the correlation between antimony (Sb) hair concentration and neutrophil to lymphocyte ratio (NLR) was found to be significant (r = 0.560, p = 0.016) in the CAD group.
The median chromium (Cr) hair concentration (r = –0.507, p = 0.032) and iron (Fe) concentration (r = –0.472, p = 0.048) correlated with platelet to lymphocyte ratio (PLR) in the CAD group.
Further correlations between sex differences were performed and did not reveal significant differences regarding trace metal concentration or inflammatory markers.
The results of our study highlight a correlation between trace elements (lithium, antimony, chromium and iron) and a systemic inflammatory index in patients with diagnosed epicardial CAD. Interestingly, the entire group representing patients with anginal symptoms did not differ with regards to hair trace element concentration or whole blood count analysis.
Anginal symptoms on exertion indicate myocardial ischemia, which shares common clinical and inflammatory risk factors [17]. The inflammatory background of atherosclerosis has gained much attention in recent years [18]. The increased risk for acute coronary syndromes [19] or for chronic atherosclerotic lesion development and progression [20] is related to inflammatory processes. Though the direct cause of inflammatory activation remains unknown in patients with cardiovascular diseases, we found a possible explanation in hair trace metal concentration. In our study, two separate groups based on the coronary angiography results were distinguished. The group characterized by epicardial coronary disease showed a correlation between inflammatory indexes and hair trace elements. A similar relationship was not observed in the healthy subjects. The novelty of our results is based on one of the possible pathophysiological explanations of atherosclerosis development that can be linked to an interplay between trace metals concentration and inflammatory processes.
Lithium is applied in psychopharmacology, particularly in the therapy of bipolar disorders [21]. Its water content and food contamination including grains and vegetables, such as cabbage, tomatoes, and potatoes, results in seasonal differences in the organism concentrations [22]. Lithium is claimed to be associated with neurotoxicity [23], obesity and endocrinological disorders including hypothyroidism and hyperparathyroidism [24]. Its reversible and mild toxic effect on the heart has been postulated [25]. Lithium may induce inflammatory derangements, resulting in lymphopenia [26] and monocyte activation [27]. In our analysis, the relationship was identified between lithium concentration in hair and inflammatory activation measured by the peripheral blood SII index.
Antimony is a potentially dangerous metal for human organisms, which may cause a serious threat, being absorbed from Sb-contaminated water or foods [28]. The link between antimony serum concentration and increased cardiovascular risk was recently postulated by Li et al. [29]. The analysis of Grau-Perez et al. [30] reported a potentially increased risk of coronary atherosclerosis in patients with elevated urinary antimony concentration. Fernández et al. [31] presented the correlation between antimony and neutrophil activation in leishmaniasis. The immunomodulatory effect of Sb was also postulated by Gómez et al. [32]. In an animal model, the lymphocytic suppressor effect of antimony in antileishmanial chemotherapy was presented by Santos et al. [33]. In accordance to the mentioned publication, our results postulate the relationship between inflammatory activation and hair antimony concentration.
The occupational exposure to water-soluble chromium is postulated [34]. Its toxicity and influence on inflammatory reactions has previously been presented [35]. Chromium is a trace element identified in macrophages, endothelial and smooth muscle cells [36]. The relationship between chromium concentration and patho-mechanisms of CAD related to non-coding ribonucleic acid (RNA) is postulated [37].
Finally, we noticed the relationship between iron (Fe) and inflammatory indexes in patients with epicardial CAD. The presented inverse correlation was found to be the strongest of all in our analysis. The serum Fe concentration deficiency and increased cardiovascular risk including CAD, congestive heart failure (CHF) and pulmonary hypertension, are a matter of current interest [38]. On the contrary, a key cardiovascular risk factor, passive smoking, was found to be related to increased Fe serum concentration [39]. In active smokers, the correlation with Fe hair concentration was also presented [40]. Our analysis indicates the relationship between scalp hair Fe-concentration and coronary atherosclerosis.
The additional novelty of our study results is based on the role of Fe in cardiovascular diseases. Recent trials have recommended iron supplementation in patients with CHF [41] and its beneficial role in clinical status is widely accepted. Since the heart is a high-energy demanding organ, it has been proven that iron deficiency has a negative impact on cardiac function [42]. Among novel pharmacotherapeutic approaches such as quadruple therapies, which are currently recommended for all patients with heart failure and reduced ejection fraction, the iron status assessment and supplementation is recommended to be considered according to the newest European Society of Cardiology (ESC) guidelines [43, 44]. The results of our analysis identify the significance of iron monitoring in patients with preserved ejection fraction as iron overload may interplay with inflammatory activation exaggeration and represent the initial steps into coronary artery atherosclerosis progression. Iron supplementation is considered to be a novel therapeutic in cardiovascular diseases, however in hereditary hemochromatosis, iron overload leads to endothelial function impairment and increased intima–media thickness [45]. Ma et al. [46] in their review described atherosclerosis progression secondary to iron-dependent programmed cell death. Iron overload is harmful, as well as its deficiency, according to Lanser et al. [47] who presented the relationship between anemia and cardiovascular risk.
We believe that our results can provide a new perspective on the understanding of iron hemostasis. The relationship between this trace metal and inflammatory indices is another subject of our investigation. Ward et al. [48] presented the role of iron-regulatory proteins (IRPs) regulated by pro-inflammatory cytokines in iron deposition in brain cells. The relationship between inflammatory-induced ferroptosis and pathological changes in epicardial arteries were presented by Fan et al. [49]. The further studies into possible methods of inflammatory activation control are required. Most recently, the anti-inflammatory role of colchicine in coronary syndromes prevention has been postulated [50].
Inflammatory activation has been presented in previous publications as a marker of increased risk of all-cause mortality [14]. In groups of patients with multivessel coronary atherosclerosis referred for revascularization, either percutaneous [51, 52] or surgical [53, 54], inflammatory activation was found as an independent long-term prognosis predictor. The inflammatory background of atherosclerosis progression is believed to affect the long-term prognosis [55]. This implicates a possible future therapy direction postulated in recent studies [56, 57]. Anti-inflammatory therapies have recently gained much attention [58], including colchicine [50, 59] or high-density lipoprotein cholesterol [60].
The results of our study, present for the first time, the relationship between inflammatory activation and the concentration of trace elements in scalp hair as a possible explanation for epicardial CAD. The results of the performed analysis may provide new perspectives on the mechanisms of atherosclerosis.
Future directions should focus on iron hemostasis in patients with preserved ejection fraction. The concentration of trace metals in hair indicates food and environmental-related exposure and overload. The possible relationship of high iron content food including cereal, dark leafy green vegetables, whole meal pasta, bread or meat consumption should be taken into consideration in the daily diet regarding at least high-risk CV patients. The plant-based diet as recently recommended by Belardo et al. [61] is believed to lower the risk of coronary disease. Based on the current report we may suggest that more profound studies are necessary to potentially change medical recommendations in terms of food and environmental exposure to trace metals to alter cardiovascular disease risk.
The analysis of this single center prospective study was performed in two limited groups of patients, with multivessel CAD and normal coronary angiography results.
The correlations between the scalp hair concentrations of lithium (Li), antimony (Sb), chromium (Cr) and iron (Fe) and the systemic inflammatory index (SII) were revealed in patients with CAD, while similar ones were not observed in patients with normal coronary angiograms. The concentrations of trace metal and the inflammatory response may be considered as risk factors for coronary atherosclerosis. The interactions between these parameters require further studies.
ACEI, angiotensin converting enzyme inhibitor; AISI, aggregate index of systemic
inflammation; AL, aluminium; As, arsenic; BMI, body mass index; Ca, calcium; CAD,
coronary artery disease; Cd, cadmium; CHF, congestive heart failure; Co,
cobaltum; COPD, chronic obstructive pulmonary disease; Cr, chromium; CRM,
certified reference materials; CRP, c-reactive protein; Cu, copper; CV,
coefficient of variation; DM, diabetes mellitus; ESC, European Society of
Cardiology; F, female; Fe, iron; GFR, glomerular filtration rate; HDL, high
density lipoprotein (cholesterol); HIV, human immunodeficiency virus; HNO
The data supporting their findings may be obtained from the corresponding authors after resonable explanatiuon of requirement by e-mail contact for 3 years following the publications.
TU, AH and AOW designed the research study. TU, AH, AK, AR, MM and PU contributed in the acquisition of data. TU, AH, KJF, AT, MJ analyzed and interpreted the data. TU, AOW, AH, KJF, AT, MJ were involved in drafting the manuscript or reviewing it critically. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
The study was performed according to the principles of Good Clinical Practice and the Declaration of Helsinki and was approved by the Local Ethics Committee of the Poznan University of Medical Sciences, Poznan, Poland (approval number: 875/22). All patients gave their informed consent for the inclusion to the study.
Not applicable.
This research received no external funding.
The authors declare no conflict of interest.
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