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Abstract

The purpose of this study was to explore and compare the relationship among serum testosterone, systemic inflammatory response index (SIRI), lymphocyte-to-monocyte ratio (LMR) neutrophil-lymphocyte ratio (NLR), and carotid atherosclerosis in middle-aged and elderly men of Han nationality in the real world. With reference to the inclusion criteria, 89 middle-aged and elderly Han male patients were finally selected. Local weighted regression (LOESS) and multivariate logistic regression models were used to explore the independent correlation between serum testosterone, new inflammatory markers, and atherosclerosis. The diagnostic value of related indexes was evaluated by the receiver working curve characteristic curve (ROC), and the best critical value of testosterone and related inflammatory indexes was discussed. In the LOESS model, bioavailable testosterone (BT), free testosterone (FT), total testosterone (TT) and SIRI, NLR, LMR, and atherosclerosis were significantly correlated. After adjusting for confounding factors, BT, FT, TT, and LMR were negatively correlated with atherosclerosis (odds ratio [OR] < 1, p < .05), and SIRI and NLR were positively associated with atherosclerosis (OR > 1, p < .05). According to the ROC curve results, the area under the curve (AUG) of BT is 0.870, and the optimal threshold point is 4.875. The AUG of SIRI is 0.864, and the best threshold point is 0.769. Low testosterone and high inflammatory levels are closely related to atherosclerosis. Testosterone (TT, FT, and BT) and new inflammatory markers, SIRI, NLR, and LMR, are associated with carotid atherosclerosis in middle-aged and elderly men.

Keywords

atherosclerosis bioavailable testosterone systemic inflammation response index neutrophil-lymphocyte ratio lymphocyte-to-monocyte ratio

Introduction

Cardiovascular disease has become a major cause of harm to human health, especially among the elderly. In 2016, more than 17 million people died prematurely due to cardiovascular disease (Mendis, 2017). Atherosclerosis is the main pathological process of most cardiovascular diseases such as hypertension, coronary heart disease, and stroke. Much evidence reports that chronic low-grade inflammation plays a key role in the pathogenesis of atherosclerosis and cardiovascular disease (Ross, 1999). Carotid Doppler ultrasound can provide a “window” to identify the potential cardiovascular risk of carotid atherosclerosis. Doppler ultrasound measurement of carotid plaque is becoming a crucial research tool for atherosclerosis screening and identification (Touboul et al., 2012).

Studies suggest that chronic systemic inflammatory response mediates the entire pathological process and mechanism of atherosclerosis and plays a significant role in its occurrence, development, and eventual thrombosis (Nguyen et al., 2019). Studies by Nasser et al. (2021) have identified that testosterone is closely related to chronic inflammation, and testosterone affects the progression of atherosclerosis and related cardiovascular diseases by regulating vascular cells and immune cells in the process of inflammation (Kelly & Jones, 2013; Nettleship et al., 2007; Wilhelmson et al., 2018). Boden et al. (2020) have discovered that decreased testosterone levels in men have been associated with a higher risk of atherosclerosis, even after adjusting for risk factors such as age, blood lipids, and body mass index (BMI). Testosterone levels were considerably lower in males with coronary heart disease compared to men with normal coronary angiographic results (English, 2000). In addition, a clinical study reported that men with low testosterone levels had increased levels of C-reactive protein (CRP), interleukin 6 (IL-6), soluble vascular cell adhesion molecule-1 and soluble intercellular adhesion molecule-1, and increased carotid plaque area, indicating that low testosterone levels coexist with inflammation, which jointly affects the process of atherosclerosis in elderly men (Mohamad et al., 2019). Related animal experiments have also provided consistent evidence that testosterone has an anti-atherosclerosis effect (Kelly et al., 2013). The abovementioned studies further support that testosterone is involved in the mutual regulation of inflammation, which may be one of the ways that androgens affect atherosclerosis.

The assessment of chronic inflammation is generally measured by the abundance of pro-inflammatory cytokines, compared with classical inflammatory markers such as interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-α (TNF-α), peripheral blood cell count and its derived indicators reflecting the degree of inflammation have been widely used in the study of clinical chronic inflammation. The Systemic Inflammatory Response Index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) are novel composite indicators based on peripheral venous blood neutrophil, monocyte, lymphocyte, and platelet counts (Jin et al., 2021). As credible, levels of inexpensive and readily available inflammatory markers are associated with an increased risk of coronary heart disease and stroke and have great predictive value for cardiovascular disease prognosis and related mortality (Abete et al., 2019). NLR is a marker expressing the interaction between innate immunity and adaptive immunity, and it is a new marker of the relationship between the immune system and disease. Previous studies have reported that NLR is independently related to the mortality of septicemia, pneumonia, cancer, atherosclerotic cardiovascular disease, and so on (Buonacera et al., 2022). A large-sample retrospective clinical study also confirmed that NLR is a strong predictor of carotid plaque and that use of NLR may help to identify the risk of carotid atherosclerosis (Corriere et al., 2018).

Therefore, this study aimed to explore the correlation between testosterone, novel inflammatory markers SIRI, NLR, LMR, and carotid atherosclerosis in real-world middle-aged and elderly Han men to find better early warning signals of clinical carotid atherosclerosis.

Method

Research Object

The subjects were middle-aged and elderly Han male patients who were hospitalized or examined in the Department of Geriatrics, the First Affiliated Hospital of USTC from July 2014 to January 2020. According to the age division of the World Health Organization, 45 to 59 years old are the middle-aged and ≥60 years old are the elderly (Ahmad et al., 2001). The exclusion criteria include: (a) acute infection, including virus and bacterial and other pathogenic bacteria infection; (b) autoimmune or related diseases; (c) acute complications of diabetes, gout acute arthritis, and so on; (d) stroke, transient ischemic attack, peripheral vascular disease, and so on; (e) malignant tumors; (f) severe heart, lung, liver, and kidney insufficiency; (g) hematological diseases; (h) gonadal diseases; (i) adrenal and pituitary diseases; and (j) in the past 3 months, receive any sex hormone or glucocorticoid preparation treatment. Finally, a total of 89 people were divided into two groups according to the presence of carotid atherosclerotic plaque: non-plaque group (n = 33) and plaque group (n = 56; the diagnostic criteria of carotid atherosclerotic plaque refer to Mannheim intima-media thickness and plaque consensus; Touboul et al., 2012).

Demographic Data

Baseline data were obtained from the questionnaire, which included name, date of birth, history of hypertension, diabetes, coronary heart disease, obesity, and other diseases as well as treatment and medication.

Height and weight measurement: in the morning, take off your hat, wear light clothes, take off your shoes and socks, the altimeter measures the body weight (accurate to 0.1 cm), and the weight meter measures weight (accurate to 0.5 kg). Calculate BMI: BMI = weight (kg) / height² (m²).

Blood Sample Collection and Testing

Fasting blood samples were collected in the early morning after fasting for 12 hours in all patients. The technicians in the central laboratory of the First Affiliated Hospital of USTC used standard reagents and an automatic blood cell analyzer to draw 2 ml of whole blood for the absolute count of neutrophil (N), lymphocyte (L), and monocyte (M), and calculated NLR, LMR, and SIRI, respectively (NLR = N/L, LMR = L/M, SIRI = N × M/L).

Fasting blood glucose, blood urea nitrogen (BUN), urinary acid, serum creatinine, albumin (ALB), total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), low density lipoprotein, very low-density lipoprotein cholesterol, Apolipoprotein A1 (APOA1), and Apolipoprotein B (APOB) were detected by the same technician and Hitachi 7170S automatic biochemical analyzer. The content of serum C-peptide was determined by the chemiluminescence method. Postprandial 2-hr blood glucose (P2hBG), serum insulin, and C-peptide were measured after eating 100 g steamed bread. Glycosylated hemoglobin (HbA1c) was detected by MQ-2000PT high-performance liquid chromatography. The concentration of 25-hydroxy vitamin D was determined by liquid chromatography-tandem mass spectrometry. Insulin resistance index and insulin sensitivity index were evaluated by the steady-state model.

The level of total testosterone (TT) was detected by automatic chemiluminescence immunoassay made by Siemens. Serum sex hormone binding protein (SHBG) was determined by electrochemiluminescence (RocheCobas, E601, Switzerland). Free testosterone (FT) and bioavailable testosterone (BT) were calculated by FT and BT calculator (http://www.issam.ch/freetesto.htm) developed by Ghent University Hospital in Belgium (Vermeulen et al., 1999).

Ultrasonographic Examination of Carotid Arteriosclerosis

Before the examination, the subjects rested for at least 15 min, lay supine on the examination bed, stretched their head and neck, and exposed the common carotid artery to be examined. The carotid arterial intima-media thickness (CIMT) at 10, 15, and 20 mm from the bifurcation of bilateral common carotid arteries were measured, the average value of CIMT measured at three places on both sides was calculated, which was marked as CIMTmax. Diagnostic criteria of atherosclerotic plaque: carotid intima thickened locally, protruding in the lumen, CIMT > 1.5mm, or mass strong echo followed by sound shadow could be seen in the intima (Touboul et al., 2012). Cervical plaque can be divided into three types: soft plaque (mainly weak echo), hard plaque (mainly medium intensity echo, strong echo), and mixed plaque (composed of hard plaque and soft plaque). All operations were performed by experienced attending doctors in the ultrasound department of our hospital, and the ultrasound instrument was the IUELITE color Doppler ultrasound diagnostic instrument of Philips.

Diagnostic Criteria of Related Diseases

Diagnosis of Hypertension: According to Global Practice Guidelines for Hypertension (Prabhakaran & Schutte, 2020).

Diabetes diagnosis: according to the 2014 ADA Diabetes Guidelines (American Diabetes Association, 2014).

Definition of coronary heart disease: coronary heart disease refers to the deposition of atherosclerotic plaques in the inner wall of the coronary artery, resulting in lumen stenosis or obstruction, resulting in myocardial ischemia and hypoxia. According to clinical characteristics, it can be divided into acute coronary syndrome and chronic coronary syndrome (Knuuti, 2020).

Statistical Processing

All data management, analysis, and visualization were performed using STATAMP version 15.1 (copyright 1985-2017 National, Texas) and RStudio version 1.2.5033 (copyright 2009-2019; RStudio). The normal distribution variable was described as mean ± standard deviation, and the group t test was used to compare the difference between the two groups. Variables that are not normally distributed are represented as the median (quartile) and compared using the Wilcoxon rank-sum test. The LOESS was used to study the relationship between BT, FT, TT, SIRI, NLR, LMR, and atherosclerosis. Multivariate logistic regression was used to correct the variables with differences in the single factor and the variables screened by LASSO regression. Draw a receiver–operator characteristic (ROC) curve for the indicators with diagnostic value, evaluate the performance of the prediction model by estimating the area under the curve (AUC), and explore the optimal threshold of related indicators. The p value of <.05 was considered statistically significant.

Results

General Index Analysis

A total of 89 male subjects, aged from 48 to 85 years, were included in this study. According to the presence or absence of carotid plaque, the patients were divided into two groups: non-plaque group (n = 33) and plaque group (n = 56). Table 1 lists the demographic and clinical characteristics of the subjects. There were significant differences in age, L, M, N, ALB, TC, TG, HDL, ApoA1, BUN, HbA1c, P2hBG, TT, FT, BT, SIRI, NLR, and LMR between the two groups (p < .001, p = .001, p = .004, p = .03, p < .001, p = .001, p < .001, p = .006, p < .001, p = .017, p = .004, p = .014, p < .001, p < .001, p < .001, p < .001, p < .001, p < .001, respectively; Table 1), while the differences in other variables between the two groups did not reach a significant level. In the plaque group, the age, M, N, BUN, HbA1c, P2hBG, SIRI, and NLR were significantly higher than those in the non-plaque group, while L, ALB, TC, TG, HDL, ApoA1, BT, FT, TT, and LMR were significantly lower than those in the non-plaque group. In the plaque group, 42 people took statins, accounting for 75%, and there was a significant difference compared with the no plaque group (n = 33; 3%), so we can see abnormal differences in TC, TG, HDL, and ApoA1 (p = .001, p < .001, p = .006, p < .001).

Table 1.

Characteristics of Study Population

Variables	No-plaque group (n = 33)	Plaque group (n = 56)	p value
Age, years	51.0 (48.0,53.0)	80.0 (69.0,85.0)	<.001
Body mass index (Kg/m²)	24.2 (22.9,25.4)	24.5 (22.9,26.6)	.167
Hypertension, yes/no	13/20 (39%)	34/22 (61%)	.078
Coronary heart disease, yes/no	1/32 (3%)	9/47 (16%)	.084
Diabetes, yes/no	11/22 (33%)	21/35 (38%)	.820
Total white blood cell (× 10⁹/L)	6.2±1.5	6.4±1.5	.530
Lymphocyte (×10⁹/L)	2.1±0.6	1.7±0.6	.001
Monocyte (×10⁹/L)	0.3 (0.3,0.4)	0.4 (0.3,0.5)	.004
Neutrophil (×10⁹/L)	3.5±0.9	4.1±1.2	.030
Albumin (g/L)	45.0 (42.5,46.5)	40.9 (37.1,44.9)	<.001
Taking statins, yes/no	1/32 (3%)	42/14 (75%)	<.001
Total cholesterol (mmol/L)	5.1±1.0	4.4±0.9	.001
Triglyceride (mmol/L)	1.8 (1.5,2.7)	1.2 (0.8,1.7)	<.001
High-density lipoprotein (mmol/L)	1.2±0.2	1.0±0.2	.006
Low-density lipoprotein (mmol/L)	2.9±0.8	2.6±0.8	.071
Very low-density lipoprotein (mmol/L)	0.7 (0.5,1.3)	0.6 (0.5,0.9)	.064
Apolipoprotein A1 (g/L)	1.5±0.2	1.3±0.2	<.001
Apolipoprotein B (g/L)	1.0 (0.8,1.2)	0.9 (0.8,1.1)	.157
Creatinine (μmol/L)	80.0 (68.0,90.0)	84.0 (71.0,97.0)	.219
Blood urea nitrogen (mmol/L)	5.7 (4.8,6.8)	6.4 (5.7,7.8)	.017
Urinary acid (μmol/L)	405.8±85.7	382.7±95.9	.258
Fasting blood glucose (mmol/l)	5.3 (4.7,5.6)	5.2 (4.7,6.2)	.615
Postprandial 2-hour blood glucose (mmol/l)	6.7 (5.1,9.0)	7.9 (6.7,11.3)	.014
Glycosylated hemoglobin (%)	5.5 (5.2,6.1)	5.9 (5.5,6.9)	.004
HOMA-IR	2.3 (1.9,3.6)	2.4 (1.6,4.1)	.964
HOMA-IS	0.4 (0.3,0.5)	0.4 (0.2,0.6)	.939
25(OH) vitamin D (nmol/L)	15.8 (12.1,19.4)	19.4 (12.7,24.0)	.206
Serum sex hormone binding protein (nmol/L)	33.6 (26.5,42.1)	40.2 (27.4,53.0)	.114
Total testosterone (nmol/L)	13.5 (10.9,16.2)	9.8 (6.7,11.5)	<.001
Free testosterone (nmol/L)	0.2(0.2,0.3)	0.2 (0.1,0.2)	<.001
Bioavailable testosterone (nmol/L)	5.7 (5.4,7.2)	3.7 (2.8,4.7)	<.001
SIRI	0.6 (0.5,0.7)	1.0 (0.8,1.2)	<.001
LMR	6.3±1.9	4.0±1.4	<.001
NLR	1.6 (1.4,2.0)	2.4 (1.9,3.1)	<.001

Note. HOMA-IR = homeostasis model assessment-insulin resistance; HOMA-IS = homeostasis model assessment-insulin sensitivity; 25(OH) vitamin D = 25-hydroxy vitamin D; SIRI = systemic inflammatory response index; LMR = lymphocyte-to-monocyte ratio; NLR = neutrophil-lymphocyte ratio.

Testosterone, Inflammation-Related Indexes, and Atherosclerosis

It can be clearly seen from Figure 1 that based on the LOESS model, there is a significant negative correlation between atherosclerosis and the levels of BT, FT, TT, and LMR, and a significant positive correlation between atherosclerosis, SIRI, and NLR. Table 2 presents the correlation between atherosclerosis and the levels of BT, FT, TT, NLR, SIRI, and LMR in the logistic regression model based on unadjusted and adjusted conditions, it can be seen that after correcting some confounding factors, BT, FT, TT, NLR, SIRI, and LMR are still significantly independently correlated with atherosclerosis. According to the increased standard deviation (SD) of BT, the atherosclerotic adjusted odds ratio (OR) decreased by 85% (OR 0.15; 95% confidence interval [CI]: [0.05, 0.43]), according to the increased SD of FT, the atherosclerotic adjusted OR decreased by 49% (OR 0.51; 95% CI [0.27, 0.95]), according to the increased SD of TT, the adjusted OR of atherosclerosis decreased by an average of 53% (OR 0.47; 95% CI [0.26, 0.86]), and according to the increase of LMR SD, the atherosclerotic adjusted OR decreased by 88% on average (OR 0.12; 95% CI [0.04, 0.38]), which strongly indicated that BT, TT, FT, and LMR would be independent protective factors of atherosclerosis. At the same time, according to the increased SD of NLR, the atherosclerotic adjusted OR increased by an average of 364% (OR 4.64; 95% CI [1.39; 15.50]), according to the increase of the SD of SIRI, the adjusted OR of atherosclerosis increased by an average of 634% (OR 7.34; 95% CI [2.28, 26.69]), which strongly indicated that the inflammatory indexes NLR and SIRI were independent risk factors for atherosclerosis.

Figure 1.

Relationship Between Carotid Atherosclerosis and the Level of Bioavailable Testosterone (BT)

Table 2.

Correlation Analysis of Testosterone, Inflammatory Markers and Carotid Atherosclerosis

Variable	Model1	p	Model2	p	Model3	p
Variable	OR (95%, CI)	p	OR (95%, CI)	p	OR (95%, CI)	p
BT	0.15 [0.06, 0.35]	<.001	0.10 [0.03, 0.34]	<.001	0.15 [0.05, 0.43]	<.001
FT	0.42 [0.25, 0.73]	.002	0.39 [0.18, 0.85]	.018	0.51 [0.27, 0.95]	.034
TT	0.40 [0.23, 0.69]	.001	0.30 [0.14, 0.65]	.002	0.47 [0.26, 0.86]	.014
NLR	5.97 [2.36, 15.10]	<.001	3.60 [0.94, 13.82]	.062	4.64 [1.39, 15.50]	.013
LMR	0.20 [0.10, 0.42]	<.001	0.26 [0.10, 0.70]	.007	0.12 [0.04, 0.38]	<.001
SIRI	9.61 [3.43, 26.94]	<.001	20.43 [3.72, 112.16]	.001	7.34 [2.28, 23.69]	.001

Note. Model 1: No variables are corrected. Model 2: Correcting apolipoprotein A1, glycosylated hemoglobin, total cholesterol, triglyceride, high-density lipoprotein. Model 3: Correcting apolipoprotein A1, body mass index, glycosylated hemoglobin, neutrophil, blood urea nitrogen, 25(OH) vitamin D. BT = Bioavailable testosterone; FT = Free testosterone; TT = Total testosterone; NLR = neutrophil-lymphocyte ratio; LMR = lymphocyte-to-monocyte ratio; SIRI = systemic inflammatory response index; 25(OH) vitamin D = 25-hydroxy vitamin D.

ROC Curve Analysis

To identify potential biomarkers of carotid atherosclerosis, an ROC curve was constructed. The results showed that the AUC of FT, BT, NLR, LMR, and SIRI were all >0.8, the lower 95% CI was greater than 0.7, among them, the AUC of BT was the largest, which was 0.870, followed by SIRI, 0.864 (Table 3). The optimal cut-off value of BT is 4.875nmol/l, which has a sensitivity of 76.8% and a specificity of 97% for predicting carotid atherosclerosis. The optimal cut-off value of FT is 0.195nmol/l, with a sensitivity of 66.1% and a specificity of 97%. The optimal cut-off value of NLR is 2.187, the sensitivity is 66.1%, and the specificity is 87.9%. The optimal cut-off value of LMR is 5.498, the sensitivity is 83.9%, and the specificity is 66.7%. The optimal cut-off value of SIRI is 0.769, the sensitivity is 75.0%, and the specificity is 84.8% (Table 4).

Table 3.

ROC Curve (AUC) of TT, FT, BT, NLR, LMR and SIRI

	95%CI
Index AUC		Lower limit	Upper limit
TT	0.762	0.661	0.863
FT	0.813	0.725	0.902
BT	0.870	0.795	0.944
NLR	0.814	0.724	0.904
LMR	0.829	0.741	0.917
SIRI	0.864	0.792	0.936

Note. ROC = receiver–operator characteristic; AUC = area under the curve; BT = Bioavailable testosterone; TT = Total testosterone; FT = Free testosterone; LMR = lymphocyte-to-monocyte ratio; NLR = neutrophil-lymphocyte ratio; SIRI = systemic inflammatory response index.

Table 4.

Cut-Off Values, Sensitivity and Specificity of Predictors of Carotid Atherosclerosis

Index	Cut-off	Sensitivity	Specificity
TT	10.350	0.643	0.818
FT	0.195	0.661	0.970
BT	4.875	0.768	0.970
NLR	2.187	0.661	0.879
LMR	5.498	0.839	0.667
SIRI	0.769	0.750	0.848

Note. TT = Total testosterone; FT = Free testosterone; BT = Bioavailable testosterone; NLR = neutrophil-lymphocyte ratio; LMR = lymphocyte-to-monocyte ratio; SIRI = systemic inflammatory response index.

Discussion

With the deepening of the research, it has been identified that in addition to reproduction and maintenance of secondary sexual function, testosterone also plays a biological role in the regulation of chronic inflammation through the immune system (Nasser et al., 2021). Androgen receptor (AR) expression is found in neutrophils, mast cells, macrophages, lymphocytes, and other immune function cells. Androgen regulates the activity of neutrophils and other immune cells through AR, indicating that androgen plays an important role in immune cell signal transduction and chronic inflammation (Nasser et al., 2021). Huang et al. have reported that AR in monocytes / macrophages upregulates the expression of TNF-α, integrin β-2, and lectin-like oxidized low density lipoprotein receptor-1 (LOX-1), which regulates endothelial cell migration and adhesion and foam cell formation during inflammation (Huang et al., 2014). AR plays a pro-inflammatory role by mediating the degradation of nuclear factor-κB (NF-κB) inhibitor protein IκB, releasing NF-κB translocation to the nucleus and promoting gene transcription (Death et al., 2004). Conversely, in TNF- α-activated endothelial cells, testosterone attenuates the expression of vascular cell adhesion molecule-1 (VCAM-1) by inhibiting the nuclear translocation of NF- κB, thus playing an anti-inflammatory effect (Norata et al., 2006). It was indicated that testosterone could inhibit the expression of VCAM-1 stimulated by TNF- α when endothelial cells were pretreated with aromatase inhibitor anastrozole, suggesting that testosterone has an anti-inflammatory effect after aromatase conversion to 17 β-estradiol (E2) and activation of estrogen receptors (Mukherjee et al., 2002). Vignozzi et al. (2011) reported that testosterone treatment significantly improved lipid accumulation and liver inflammation, decreased the expression of TNF- α in the liver and the level of circulating TNF- α in rabbits fed a high fat diet. Malkin et al. (2004) have shown that testosterone supplementation can help reduce inflammatory cytokines and reduce total cholesterol levels in men. In addition, testosterone replacement therapy can reduce the levels of leptin and adiponectin in patients with type 2 diabetes, thus improving insulin resistance and visceral obesity (Kapoor et al., 2007).

Human studies have confirmed that testosterone is closely related to many inflammation-related diseases such as hypertension, atherosclerosis, metabolic syndrome, type 2 diabetes, coronary heart disease, and so on (Gencer et al., 2021; Traish et al., 2018). In older men, low levels of androgen increase the risk of atherosclerosis and are associated with carotid intima-media thickness and arterial calcification (Muller et al., 2004). In addition, a large sample retrospective study found that male patients with coronary heart disease who underwent angiography had significantly lower testosterone levels than normal, and testosterone levels were a risk indicator for survival (Malkin et al., 2010). Animal experiments have identified that low testosterone levels are associated with an increased risk of early atherosclerosis, which may be associated with elevated serum cholesterol caused by testosterone deficiency (Deng et al., 2021). Song Gao and Geng (2013) pointed out that testosterone deficiency or low levels of testosterone can advance the expression of LOX-1 and the activation of NF-κB, which mediates the formation of atherosclerosis.

Testosterone is the main androgen in men. Testosterone exists in the form of free testosterone and bound testosterone, which includes testosterone bound to albumin and testosterone bound to the sex hormone globulin. Free testosterone and albumin-bound testosterone, collectively known as bioactive testosterone, are the main androgens that play a physiological role (Conover et al., 2017). From the results of this study, it was identified that the levels of BT, FT, and TT in the carotid plaque group were significantly lower than those in the non-plaque group (p < .05), and the age was also significantly higher than that in the non-plaque group (p < .05). Carotid atherosclerosis was closely related to age, hypertension, and other risk factors. In addition, it is worth noting that the levels of TC, TG, and HDL in the plaque group were significantly lower than those in the non-plaque group (p < .05). The seemingly abnormal difference between the two groups may be due to the fact that the subjects were from the real world. In all, 75% of the patients took statins in the plaque group and 3% in the non-plaque group. After the confounding factors were adjusted by stepwise regression model, there was an obvious negative correlation between BT, FT, TT, and atherosclerosis (OR < 1, p < .05). Compared with FT and TT, the correlation between BT and atherosclerosis was stronger (Table 2). In addition, the AUC of FT and BT are 0.813 and 0.870, respectively, and the corresponding cutoff values are 0.195 and 4.875 nmol/L, respectively. Under this cutoff value, the sensitivity of FT and BT in diagnosing atherosclerosis is 66.1% and 76.8%, and the specificity is 97% and 97%, respectively. There are statistical differences in sensitivity and specificity between them in diagnosing atherosclerosis (Tables 3 and 4). Similar to the results of this article, Zhou et al. reported that there was a significant dose-response relationship between the concentration of BT and the level of NLR in middle-aged and elderly Han men, and the cut-off value was 4.7 nmol/L (Zhou et al., 2020).

There is growing evidence that atherosclerosis is an inflammatory disease, the inflammatory mechanism runs through the whole process of the initiation, progression and complication of atherosclerosis, and participates in a series of processes such as promoting endothelial cell injury, upregulating the expression of adhesion molecules, stimulating the expression of immune cells, and so on (Nasser et al., 2021). Inflammatory markers are not only an important factor involved in the inflammatory response but also a tool to observe, measure, and predict the degree of inflammation. Classical pro-inflammatory factors, including IL-6, TNF-α, and CRP, are important mediators involved in a variety of physiological and immune processes and are reliable markers of infection and inflammation (Koenig et al., 1999; Nguyen et al., 2019). At present, inflammatory markers have been widely studied, and many inflammatory markers have been considered in the risk assessment of cardiovascular disease prevention. The treatment of anti-inflammatory cytokines is widely used in the clinic, such as TNF-α inhibitor Adalimab is used in a variety of autoimmune diseases (Sanchez-Hernandez et al., 2019). Canakinumab is a monoclonal antibody against human IL-1β, which can specifically bind to human IL-1β, thus preventing IL-1β from exerting biological effects. CANTOS study confirmed that Canakinumab can further reduce the occurrence of adverse cardiovascular events in patients with myocardial infarction on the basis of lipid-lowering drugs, which provides direct evidence for the inflammation hypothesis of atherosclerosis and provides a basis for the development of more inflammation-targeting drugs (Ridker et al., 2017).

Combined with previous studies, the formation of fat stripes has been identified as one of the characteristics of the earliest stage of atherosclerosis, which can progress to fibrous plaque formation, followed by arterial lumen stenosis and chronic tissue ischemia. Atherosclerotic plaques may also develop into unstable plaques, such as bleeding and ulcers, which eventually lead to intravascular thrombosis, sudden occlusion of arteries, and eventually acute coronary artery syndrome (Golia et al., 2014). Histopathological and immunocytochemical observations suggest that active inflammatory processes may destabilize the fibrous cap tissue, thus triggering plaque rupture and enhancing the risk of coronary thrombosis (van der Wal et al., 1994). It has been proved that T helper cells play a key role in the deterioration of atherosclerosis. T lymphocytes are activated by antigens in the blood vessel wall, followed by inflammatory cascades, and recruitment of immune cells, endothelial cells, and smooth muscle cells, which eventually lead to the formation and progression of plaques (Agardh et al., 2011). Pathological studies further confirmed that there were high concentrations of inflammatory cells in the direct site of plaque rupture (Duivenvoorden et al., 2013). On the contrary, prospective epidemiological studies have shown a strong and consistent association between clinical manifestations of atherothrombotic disease and systemic markers of inflammation (Ernst et al., 1987). We can speculate that inflammation plays an important role in destroying the stability of arterial plaques.

Neutrophils play a key role in the inflammatory response of atherosclerosis, by secreting a large number of inflammatory mediators such as IL-1, IL-6, TNF-α, and oxygen free radicals, which damage endothelial cells and promote the formation of atherosclerotic plaques (Shah et al., 2017). The transformation of monocytes into lipid-rich macrophages is a necessary process for the formation of atherosclerosis (Kim et al., 2019). Lymphocytes can produce specific immune responses against oxidized low-density lipoprotein (ox-LDL) and are activated and differentiated into Th1, which secretes a large number of pro-inflammatory cytokines, such as interleukin-2 (IL-2), interleukin-3 (IL-3), TNF-α, and interferon-γ, which activate macrophages, endothelial cells and vascular smooth muscle cells, aggravate local inflammation, and thus promote the progression of atherosclerosis (Azab et al., 2010). It may be that the newly discovered inflammatory markers such as SIRI, NLR and LMR obtained from the calculation of blood cell counts such as neutrophils, lymphocytes and monocytes play an important role in early warning of important inflammatory diseases.

As presented in Table 1, in this cross-sectional study of a small sample population, SIRI and NLR in the plaque group were significantly higher than those in non-plaque group (p < .001), and LMR in plaque group was significantly lower than that in non-plaque group (p < .001). Further analysis based on LOESS model indicated that the levels of SIRI, LMR and NLR were significantly correlated with atherosclerosis, in which SIRI and NLR were negatively correlated with atherosclerosis (OR > 1, p < .05), and LMR was positively correlated with atherosclerosis (OR < 1, p < .05). After adjusting for influencing factors such as TC, TG, HDL, APOA1, BMI, and HbA1c, this relationship still existed (Table 2). According to the analysis of ROC curve, the AUC of SIRI, NLR, and LMR were all more than 0.7, their cut-off values were 0.769, 2.187, and 5.498, respectively. Under this cut-off value, the sensitivity of SIRI, NLR, and LMR in diagnosing atherosclerosis was 0.750, 0.661, and 0.839, respectively, and the specificity was 0.848, 0.879, and 0.667, respectively (Table 3 and 4). Previous studies have reported that NLR and LMR are of great value in predicting the prognosis and related mortality of inflammatory diseases through different immune pathways. In patients with ulcerative colitis, NLR is positively correlated with disease activity, while LMR level is negatively correlated (Düzenli et al., 2020). In patients with rheumatoid arthritis, NLR and LMR have good value in disease prediction (Li & Xie, 2021). NLR can be used to predict the risk of arrhythmia and long-term mortality in patients with acute coronary syndrome (ACS) compared with the lowest quartile in a retrospective review of 2,833 patients hospitalized with ACS (average 1.82), patients in the highest NLR quartile (average 9.5) had significantly higher in-hospital mortality (8.5% vs. 1.8%; Afari & Bhat, 2016). A large prospective study reported that SIRI was associated with increased stroke and all-cause mortality, and that elevated SIRI levels were independently associated with an increased risk of myocardial infarction (Jin et al., 2021). Therefore, we have reason to speculate that the new inflammatory markers SIRI, NLR and LMR, which are composed of neutrophils, monocytes and lymphocytes, are closely related to atherosclerosis and have certain clinical predictive value, and SIRI is superior to NLR and LMR.

Limitations

Several limitations of this study should be noted. First of all, this is an observational study with data from only one hospital, which inevitably leads to selection bias to some extent, and the causal relationship between testosterone and inflammatory markers and carotid atherosclerosis cannot be guaranteed. Second, our study was single-center, and the sample size is small, so the critical value of the relevant predictive indicators cannot be extrapolated to the general population. In addition, although we strictly control the subjects according to the exclusion criteria, it is undeniable that there are still uncontrollable factors affecting the level of inflammation, so more large-sample clinical studies are needed to confirm it in the future.

Conclusion

This small sample of middle-aged and elderly men of Chinese Han nationality in the real world, including healthy men, as well as patients with diabetes, hypertension, coronary heart disease, stroke sequelae, and arteriosclerosis, aged from 36 to 90 years old. After analysis, we found that testosterone (TT, FT, and BT) and a new inflammatory marker LMR were significantly negatively correlated with carotid atherosclerosis, while SIRI, NLR, were positively correlated with carotid atherosclerosis. As new inflammatory markers, SIRI, NLR, and LMR may have predictive or indirect evaluation value of atherosclerosis in middle-aged and elderly men, and SIRI is slightly better than NLR and LMR.

Footnotes

Acknowledgements

The authors thank all the members of our research group and gratefully acknowledge the cooperation of the patients.

Author Contributions

Corresponding author Jian Zhou came up with the idea and he is guarantor. Qinhao Chen and Mingzhu Che contributed equally as co-first authors, they performed the drafting of the article and the statistical analyses. Haiyang Yu performed the literature search. Lijie Shao and Wei Shen were responsible for data collection. All authors contributed to the acquisition, analysis or interpretation of data and they all have read and approved the manuscript.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author on reasonable request.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics Statement

All participants provided written informed consent prior to enrolment in this study. The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study were in accordance with the Declaration of Helsinki (as revised in 2013) and this study was approved by the Ethics Committee of the First Affiliated Hospital of University of Science and Technology of China (No. 2022-RE-004) and written informed consent for publication of the patients’ information and images was entirely obtained.

ORCID iD

Qinhao Chen

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Comparison of the Early Warning Effects of Novel Inflammatory Markers SIRI,NLR,and LMR in the Inhibition of Carotid Atherosclerosis by Testosterone in Middle-Aged and Elderly Han Chinese Men in the Real World: A Small Sample Clinical Observational Study

Abstract

Keywords

Introduction

Method

Research Object

Demographic Data

Blood Sample Collection and Testing

Ultrasonographic Examination of Carotid Arteriosclerosis

Diagnostic Criteria of Related Diseases

Statistical Processing

Results

General Index Analysis

Testosterone, Inflammation-Related Indexes, and Atherosclerosis

ROC Curve Analysis

Discussion

Limitations

Conclusion

Footnotes

Acknowledgements

Author Contributions

Data Availability Statement

Declaration of Conflicting Interests

Ethics Statement

ORCID iD

References