Homocysteine, interleukin-1β, and fasting blood glucose levels as prognostic markers for diabetes mellitus complicated with cerebral infarction and correlated with carotid intima-media thickness.

Diabetes mellitus complicated with cerebral infarction (DMCI) has a high incidence and disability rate. Therefore, identification of biomarkers for the early prediction of the development and progression of cerebral infarction (CI) is of great significance for the prevention and treatment of this disease. The roles of serum homocysteine (Hey), interleukin-1β (IL-1β), and fasting blood glucose (FBG) in DMCI and their correlations with carotid intima-media thickness (CIMT) were explored. A total of 124 patients with DMCI (DMCI group) and 103 patients with diabetes mellitus (DM) (DM group) admitted to the People's Hospital of Liuhe District of Nanjing were enrolled in this study. A further 100 healthy controls undergoing physical examinations during the same period (HC group) were also enrolled. CIMT value was detected by carotid artery ultrasound. Hey and FBG levels were determined by a fully automatic biochemical analyzer. The IL-1β level was detected by enzyme-linked immunosorbent assay (ELISA). The levels of Hey, IL-1β, and FBG and the CIMT value in the DMCI and DM groups were significantly higher than those in the HC group (P<0.001). The levels and the value in the DMCI group were significantly higher than those in the DM group (P<0.001). Hey, IL-1β, and FBG levels were positively correlated with CIMT value (r=0.542, P<0.001; r=0.522, P<0.001; r=0.402, P<0.001). Receiver operating characteristic (ROC) curves showed that the sensitivity and specificity of Hey for diagnosing DMCI were 86.29 and 80.58%; those of IL-1β were 68.55 and 86.41%; those of FBG were 69.35 and 88.35%. Multivariate logistic regression analysis revealed that systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), Hey, IL-1β, FBG, and CIMT were independent risk factors for DMCI (P<0.05). In conclusion, patients with DMCI have severe atherosclerosis. Hey, IL-1β, and FBG are involved in the development and progression of DMCI, so they can be used as predictive markers for the disease. Hey, IL-1β, FBG, and CIMT are independent risk factors for patients with DMCI. Copyright: © Dai et al.

Introduction

Diabetes mellitus (DM) is a metabolic disease characterized by hyperglycemia, and its chronic complications can cause patient death and disability (1). There are about 415 million patients with DM worldwide, and the number has been increasing annually (2). Currently, about 193 million of the patients have not been diagnosed. Chronic DM that is untreated induces many complications and the incidence rates are still on the rise even after blood glucose is controlled (3). The long-term development of DM causes pathological changes of vascular structure, and then leads to microvascular and macrovascular complications (4). Previous findings have shown that DM is an independent risk factor for cerebral infarction (CI). The development of CI is closely related to severe metabolic dysfunction, and early CI is caused by arterial occlusion (5,6). The mortality of patients with diabetes mellitus complicated with cerebral infarction (DMCI) is very high. The pathological basis of the disease is atherosclerosis and the pathological change is thrombosis (7). Therefore, the timely detection and control of macroangiopathy is of great significance to prevent and for treatment of DMCI.

Carotid intima-media thickness (CIMT) is an early manifestation of atherosclerosis, and changes in its value reflect the severity of atherosclerosis. It is practical, easy to operate, and conducive to assessing the risk of cerebrovascular diseases (8). Homocysteine (Hey) level plays an important role in the development and progression of DM. Its high level causes atherosclerosis and cardio-cerebrovascular diseases through damaging vascular endothelium, inducing thrombosis, and promoting the proliferation of vascular smooth muscle cells (9). DM is a chronic low-grade inflammation and is characterized by the excessive secretion of interleukin-1β (IL-1β) and other pro-inflammatory cytokines, which enhances inflammatory signals and then results in complications such as vasculopathy (10,11). Previous studies have reported that systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are major risk factors for CI (12–14). However, there are currently few studies on the diagnostic values of Hey, IL-1β, and fasting blood glucose (FBG) levels for DMCI, or whether IL-1β is a risk factor for CI.

Therefore, the roles and significance of Hey, IL-1β, and FBG levels in patients with DMCI were explored in this study.

Patients and methods

General information

Altogether 124 patients with DMCI (the DMCI group) and 103 patients with DM (the DM group) admitted to the People's Hospital of Liuhe District of Nanjing from February 2016 to January 2019 were enrolled in this study. The DMCI group consisted of 65 males and 59 females aged 46–78 years with an average age of 60.9±9.7 years. The DM group consisted of 53 males and 50 females aged 43–75 years with an average age of 60.1±9.5 years. A further 100 healthy controls undergoing physical examinations during the same period (the HC group) were also enrolled. The group comprised 59 males and 41 females aged 39–70 years with an average age of 58.4±8.6 years. The research subjects were informed and signed an informed consent form. This study did not violate ethics or morality and was approved by the Ethics Committee of the People's Hospital of Liuhe District (Nanjing).

Inclusion and exclusion criteria

Inclusion criteria for the study were: patients in the DMCI and DM groups met the diagnostic criteria for DM from the American Diabetes Association (ADA) in 2017 (15), and their diabetes was type II diabetes mellitus. Patients in the DMCI group met the diagnostic criteria for CI from the American Heart Association (AHA) / the American Stroke Association (ASA) in 2018 (16), and their CI was confirmed by cranial imaging, MRI, or CT. The age range of the patients in the two groups were >38 years, but <78 years, and they had complete clinical data. Exclusion criteria were: those complicated with severe hepatic and renal dysfunction, cardiogenic CI, heart failure, thyroid dysfunction, diabetic nephropathy, autoimmune diseases, severe infections, or malignant tumors; those with cognitive disorders or mental illness; those who had taken immunosuppressants or anti-inflammatory drugs in the previous one month. The inclusion and exclusion criteria were applied to the DMCI and DM groups. The healthy controls were in the HC group.

CIMT examination

Carotid artery ultrasound was performed using a Philips E33 Color Doppler Ultrasonic Diagnosis Apparatus (Koninklijke Philips Electronics N.V). All subjects were examined by the same physician. The subjects laid down for 15-min rest and then their necks were fully exposed. Next, the common carotid artery, internal carotid artery, and carotid bifurcation were successively examined at 7.5 MHz. The vertical distance between the lumen intima and the media-adventitia, which was measured at 1 cm before and after the carotid bifurcation, was the CIMT value. The value was measured 3 times to obtain the average value.

Detection of markers

The subjects fasted for 3 h. In the morning the next day, their venous blood (5 ml) was extracted, placed in vacuum blood collection tubes, and centrifuged at 1,450 × g for 10 min at 4°C with a radius of 10 cm, so as to separate and store the upper layer of the serum for later use. The levels of serum Hey (enzymatic cycling method) and FBG (glucose oxidase method) (Beijing Bioassay Technologies Co., Ltd.; batch no. 301, 401) were detected by the AU5800 fully automatic biochemical analyzer (Beckman Coulter, Inc.). The reference ranges of Hey and FBG were 5–15 µmol/l and 3.33–5.55 mmol/l, respectively. The detection was carried out with reference to the instructions of the corresponding kits and instruments. Serum IL-1β level was detected by enzyme-linked immunosorbent assay (ELISA) (17), with steps carried out with reference to the instructions of human IL-1β ELISA kit [Gelatin & Protein Co., Ltd., batch no. JK-(a)-4956]. Standard wells, sample wells to be tested, and blank control wells (without samples and enzyme-labeled reagents) were set up. The standard wells in the enzyme-labeled plate that was coated were accurately added with standard substances (50 µl), while the sample wells to be tested were added with sample diluent (40 µl) and then the samples to be tested (10 µl) (the final dilution of the sample was 5 times). After that, the plate was coated, incubated at 37°C for 30 min, and then patted dry after liquid in the wells was discarded. The plate was repeatedly washed 5 times. Each well, except the blank control wells, was added with the enzyme-labeled reagents (50 µl), coated, and then incubated at 37°C for 30 min. Next, each well was added with substrate A and then substrate B (50 µl each), and colored at 37°C for 10 min in the dark after the substrates were mixed well. Finally, each well was added with stop solution (50 µl) to cease the reaction. Optical density (OD) values of each well were sequentially measured at 450 nm using a SpectraMax iD5-multifunctional microplate reader (Molecular Devices), to calculate the IL-1β level.

Statistical analysis

SPSS 22.0 (IBM Corp.) was used for statistical analysis. Enumeration data were expressed by the number of cases/percentage [n (%)], and the comparison of the data between groups was analyzed by Chi-square test. Measurement data were expressed by mean ± standard deviation (mean ± SD), and comparison of the data between groups was analyzed by independent samples t-test. One-way ANOVA was used for the comparison of means between multiple groups. LSD t-test was used for pairwise comparison between groups. Pearson's test was used to analyze the correlations of Hey, IL-1β, and FBG levels with CIMT value. Receiver operating characteristic (ROC) curves were plotted to calculate the area under the curve (AUC), to determine the cut-off values of Hey, IL-1β, and FBG for diagnosing DMCI, and to calculate their sensitivity and specificity. Multivariate Logistic regression was used to analyze risk factors for DMCI. P<0.05 indicates a statistically significant difference.

Results

There were significant differences between the DMCI, DM, and HC groups in terms of hemoglobin Alc (HbAlc), SBP, DBP, HDL-C, LDL-C, triglyceride (TG), apolipoprotein AI (apoAI), and apolipoprotein B (apoB) (P<0.05), but not in sex, age, body mass index (BMI), years of smoking, history of drinking, place of residence, coronary heart disease (CHD), platelet (PLT) count, and total cholesterol (TC) (P>0.05). There were significant differences between the DMCI and DM groups in terms of SBP, DBP, HDL-C, LDL-C, TG, apoAI, and apoB (P<0.05), not in course of disease, HbAlc, the use of insulin, and CHD (P>0.05) (Table I).

Table I.

General information [n (%)]/(mean ± SD).

Categories	DMCI group (n=124)	DM group (n=103)	HC group (n=100)	t/F/χ2	P-value
Sex				1.398	0.497
Male	65 (52.42)	53 (51.46)	59 (59.00)
Female	59 (47.58)	50 (48.54)	41 (41.00)
Age (years)	60.9±9.7	60.1±9.5	58.4±8.6	2.035	0.132
BMI (kg/m2)	25.46±2.64	26.04±2.49	25.28±2.63	2.426	0.090
Course of disease (years)	12.3±2.5	11.9±2.1	–	1.289	0.199
HbAlc (%)	10.26±2.59[a]	10.12±2.96[a]	4.93±0.83	174.600	<0.001
Use of insulin				0.153	0.696
Yes	80 (64.52)	69 (66.99)	–
No	44 (35.48)	34 (33.01)	–
History of smoking				0.643	0.725
Yes	45 (36.29)	42 (40.78)	36 (36.00)
No	79 (63.71)	61 (59.22)	64 (64.00)
Years of smoking	6.8±2.7	6.4±2.1	6.2±1.8	2.056	0.130
History of drinking				0.344	0.842
Yes	48 (38.71)	43 (41.75)	38 (38.00)
No	76 (61.29)	60 (58.25)	62 (62.00)
Place of residence				2.129	0.349
Yes	91 (73.39)	70 (67.96)	77 (77.00)
No	33 (26.61)	33 (32.04)	23 (23.00)
CHD				0.753	0.385
Yes	11 (8.87)	6 (5.83)	–
No	113 (91.13)	97 (94.17)	–
SBP (mmHg)	151.23±21.86[a,b]	143.59±21.83[a]	109.52±7.15	114.000	<0.001
DBP (mmHg)	85.73±13.67[a,b]	79.41±6.52[a]	76.05±8.49	25.710	<0.001
PLT (xb 109/l)	147.19±61.26	146.75±71.53	153.47±61.58	0.349	0.706
HDL-C (mmol/l)	1.16±0.19[a,b]	1.27±0.13[a]	1.39±0.29	10.610	<0.001
LDL-C (mmol/l)	3.06±0.59[a,b]	2.76±0.43[a]	2.59±0.54	22.910	<0.001
TC (mmol/l)	4.63±0.83	4.49±0.81	4.38±0.71	2.826	0.061
TG (mmol/l)	1.47±0.32[a,b]	1.35±0.21[a]	1.23±0.57	10.520	<0.001
apoAI (g/l)	1.01±0.19[a,b]	1.16±0.23[a]	1.41±0.38	59.850	<0.001
apoB (g/l)	0.98±0.32[a,b]	0.88±0.19[a]	0.78±0.25	16.030	<0.001

P<0.05 compared with that in the HC group.

P<0.05 compared with that in the DM group. DMCI, diabetes mellitus complicated with cerebral infarction; BMI, body mass index; HbAlc, hemoglobin Alc; SBP, systolic blood pressure; DBP, diastolic blood pressure; PLT, platelet; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; apoAI, apolipoprotein AI; apoB, apolipoprotein B.

Levels of Hey, IL-1β, and FBG and CIMT value

The levels of Hey, IL-1β, and FBG and the CIMT value in the DMCI and DM groups were significantly higher than those in the HC group (P<0.001). The levels and the value in the DMCI group were significantly higher than those in the DM group (P<0.001) (Fig. 1).

Figure 1.

Comparison of levels of Hey, IL-1β, and FBG and CIMT value. (A) Comparison of Hey level between the HC, DM, and DMCI groups. (B) Comparison of IL-1β level between the HC, DM, and DMCI groups. (C) Comparison of FBG level between the HC, DM, and DMCI groups. (D) Comparison of CIMT value between the HC, DM, and DMCI groups. ***P<0.001. HC, healthy controls; DM, diabetes mellitus; DMCI, diabetes mellitus complicated with cerebral infarction; Hey, homocysteine; IL-1β, interleukin-1β; FBG, fasting blood glucose; CIMT, carotid intima-media thickness.

Correlations of Hey, IL-1β, and FBG levels with CIMT value in DMCI group

According to the Pearson's correlation analysis, Hey level was positively correlated with CIMT value (r=0.542, P<0.001). IL-1β level was positively correlated with CIMT value (r=0.522, P<0.001). FBG level was positively correlated with CIMT (r=0.402, P<0.001) (Fig. 2).

Figure 2.

Correlation of Hey, IL-1β, and FBG levels with CIMT value in DMCI group. (A) Correlation of Hey level with CIMT value in the DMCI group. (B) Correlation of IL-1β level with CIMT value in the DMCI group. (C) Correlation of FBG level with CIMT value in the DMCI group. Hey, homocysteine; DMCI, diabetes mellitus complicated with cerebral infarction; IL-1β, interleukin-1β; FBG, fasting blood glucose; CIMT, carotid intima-media thickness.

Diagnostic values of Hey, IL-1β, and FBG levels for DMCI

The ROC curves of Hey, IL-1β, and FBG levels for diagnosing DMCI were plotted. The AUC of Hey for the diagnosis was 0.909 (95% CI, 0.872–0.945) and the cut-off value was 13.53 µmol/l, with the sensitivity of 86.29 and the specificity of 80.58%. The AUC of IL-1β was 0.842 (95% CI, 0.793–0.892) and the cut-off value was 38.67 pg/ml, with the sensitivity of 68.55 and the specificity of 86.41%. The AUC of FBG was 0.837 (95% CI, 0.784–0.889) and the cut-off value was 7.89 pg/ml, with the sensitivity of 69.35 and the specificity of 88.35% (Table II and Fig. 3).

Table II.

Diagnostic values of Hey, IL-1β, and FBG levels for DMCI.

Indicators	AUC	95% CI	Standard error	Cut-off	Sensitivity (%)	Specificity (%)
Hey	0.909	0.872–0.945	0.018	13.53 (µmol/l)	86.29	80.58
IL-1β	0.842	0.793–0.892	0.025	38.67 (pg/ml)	68.55	86.41
FBG	0.837	0.784–0.889	0.027	7.89 (mmol/l)	69.35	88.35

DMCI, diabetes mellitus complicated with cerebral infarction; Hey, homocysteine; IL-1β, interleukin-1β; FBG, fasting blood glucose.

Figure 3.

ROC curves of Hey, IL-1β, and FBG levels for diagnosing DMCI. (A) ROC curve of Hey level for diagnosing DMCI. (B) ROC curve of IL-1β level for diagnosing DMCI. (C) ROC curve of FBG level for diagnosing DMCI. ROC, receiver operating characteristic; DMCI, diabetes mellitus complicated with cerebral infarction; Hey, homocysteine; IL-1β, interleukin-1β; FBG, fasting blood glucose.

Multivariate logistic regression analysis of risk factors for DMCI

The multivariate Logistic regression analysis was performed on factors with differences between the DMCI and DM groups. The results showed that SBP (P=0.007), DBP (P=0.009), HDL-C (P=0.001), LDL-C (P=0.041), Hey (P<0.001), IL-1β (P=0.003), FBG (P=0.049), and CIMT (P=0.006) were independent risk factors for DMCI (P<0.05) (Tables III and IV).

Table III.

Assignment of multivariate Logistic regression analysis.

Factors	Variables	Assignment
SBP (mmHg)	X1	A continuous variable
DBP (mmHg)	X2	A continuous variable
HDL-C (mmol/l)	X3	A continuous variable
LDL-C (mmol/l)	X4	A continuous variable
TG (mmol/l)	X5	A continuous variable
apoAI (g/l)	X6	A continuous variable
apoB (g/l)	X7	A continuous variable
Hey (µmol/l)	X8	A continuous variable
IL-1β (pg/ml)	X9	A continuous variable
FBG (mmol/l)	X10	A continuous variable
CIMT (mm)	X11	A continuous variable

SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; apoAI, apolipoprotein AI; apoB, apolipoprotein B; Hey, homocysteine; IL-1β, interleukin-1β; FBG, fasting blood glucose; CIMT, carotid intima-media thickness.

Table IV.

Multivariate logistic regression analysis of risk factors for DMCI.

Factors	B	Standard error	Wals	P-value	HR (95% CI)
SBP (mmHg)	0.127	0.047	7.362	0.007	1.135 (1.036–1.245)
DBP (mmHg)	0.062	0.024	6.865	0.009	1.064 (1.016–1.115)
HDL-C (mmol/l)	−6.458	1.988	10.555	0.001	0.002 (0.000–0.077)
LDL-C (mmol/l)	1.16	0.687	2.852	0.041	3.191 (0.830–12.267)
TG (mmol/l)	1.473	1.184	1.549	0.213	4.363 (0.429–44.394)
apoAI (g/l)	−2.839	1.67	2.890	0.089	0.058 (0.002–1.543)
apoB (g/l)	0.359	0.210	2.930	0.087	1.432 (0.949–2.159)
Hey (µmol/l)	0.788	0.159	24.718	<0.001	2.199 (1.612–3.001)
IL-1β (pg/ml)	0.163	0.054	9.031	0.003	1.177 (1.058–1.309)
FBG (mmol/l)	0.311	0.161	3.721	0.049	1.364 (0.995–1.871)
CIMT (mm)	4.267	1.563	7.456	0.006	71.281 (3.333–1524.23)

DMCI, diabetes mellitus complicated with cerebral infarction; systolic SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; apoAI, apolipoprotein AI; apoB, apolipoprotein B; Hey, homocysteine; IL-1β, interleukin-1β; FBG, fasting blood glucose; CIMT, carotid intima-media thickness.

Discussion

DM is the main cause of macroangiopathy and its incidence has been increasing year by year. With the improvement of living standards and the development of economy, increasing number of young people have developed DM (18). The pathological basis of CI is atherosclerotic plaques, which lead to luminal stenosis, then microthrombus, and finally hypoxia and ischemia of the brain tissue (19). As a long-term chronic result, DMCI has no obvious clinical signs and symptoms during this period (20). Therefore, to diagnose DMCI in time and analyze its risk factors is of great significance.

CIMT predicts the risk of coronary artery stenosis in asymptomatic patients. Related to the severity of atherosclerosis, its value is significantly higher in patients with type II DM than that in healthy people (21). As an intermediate metabolite of sulfur amino acids, Hey activates the coagulation system and promotes deposition on vascular walls, thus affecting vasodilation (22). IL-1β is a pro-inflammatory cytokine that plays an important role during atherothrombosis. IL-1β-mediated inflammation functions in the deterioration of islet β cell function, atherogenesis, and plaque progression (23). In this study, the levels of Hey, IL-1β, and FBG and the CIMT value in the DMCI and DM groups were significantly higher than those in the HC group; the levels and the value in the DMCI group were significantly higher than those in the DM group. This indicates that patients with DMCI have severe atherosclerosis, and that Hey, IL-1β, and FBG are involved in the development and progression of DMCI. Moreover, Hey, IL-1β, and FBG levels were positively correlated with CIMT value, which shows that the three levels may affect CIMT, so Hey, IL-1β, and FBG are expected to be indicators for evaluating the severity of DMCI. In a study by Matsumoto et al (24), the CIMT value in the DMCI group is significantly higher than that in the CI group. The probability of CI in patients with DM increases by 1.8 times every time CIMT increases by 0.1 mm. HbAlc and age are independently related to CIMT. In a study by Eikelboom et al (25), Hey is closely associated with the pathological changes of arteries, and its level is positively correlated with vascular stenosis and arteriosclerosis, so high Hey level is an independent risk factor for CI. In a study by Huang et al (26), large glucose fluctuations are related to CI and the poor short-term prognosis of patients with the disease. The results of this study showed that SBP, DBP, HDL-C, LDL-C, Hey, FBG, and CIMT were independent risk factors for DMCI, which is similar to the findings of previous studies (27–29). Whether IL-1β can be used as an independent risk factor for DMCI has been rarely studied. According to a previous study, IL-1β release in the cerebral cortex of Fischer rats increases after permanent middle cerebral artery occlusion, while blocking IL-1β with anti-IL-1β antibody reduces the scope of CI, and relieves neurological and behavioral dysfunction (30). Thus, IL-1β may play an important role in CI. The results of the present study showed that IL-1β was an independent risk factor for DMCI. The massive release of Hey damages the vascular endothelial function and unbalances the coagulation and fibrinolytic systems, thereby causing a prethrombotic state (31). Vascular inflammatory responses accelerate the formation of unstable plaques. Hyperglycemia causes acidosis of brain cells through lactic acid accumulation during cerebral ischemia. It also causes brain cell damage through the destruction of mitochondrial function, the promotion of free radical generation, and the enhancement of lipid peroxidation (32,33). Therefore, the development and progression of DMCI may be the result of synergy between Hey, IL-1β, and hyperglycemia. There are currently few studies on the diagnostic values of Hey, IL-1β, and FBG levels for DMCI. According to the ROC curves in this study, the three levels had good predictive values for DMCI, and the cut-off values of the three for diagnosing the disease were 13.53 µmol/l, 38.67 pg/ml, and 7.89 mmol/l, respectively. The observation of the cut-off values was helpful to identify DM and DMCI. Therefore, Hey, IL-1β, and FBG levels can be monitored and intervened, which is conducive to reducing cervical atherosclerosis, delaying the progression of atherosclerosis, and preventing DMCI.

This study confirms the roles of Hey, IL-1β, and FBG in the development and progression of DMCI, but it still has deficiencies. The changes in the three levels during treatment were not observed. Basic experiments were not carried out. The regulatory mechanisms of Hey, IL-1β, and FBG in the development and progression of DMCI were not fully explored. These deficiencies need to be supplemented in future studies to corroborate the conclusions of this study.

In summary, patients with DMCI have severe atherosclerosis. Hey, IL-1β, and FBG are involved in the development and progression of DMCI, so they can be used as predictive markers for the disease. Hey, IL-1β, FBG, and CIMT are independent risk factors for patients with DMCI.