1
Effects of exercise training on inflammasome-related mediators and their associations to glucometabolic variables in patients with
combined CAD and T2DM: substudy of a randomized control trial.
Hani Zaidi1-4, Rune Byrkjeland1-3, Ida U. Njerve1-2, Sissel Åkra1-2, Svein Solheim 1-2, Harald Arnesen1-3, Ingebjørg Seljeflot1-3, Trine B. Opstad1-3
1 Center for Clinical Heart Research, Department of Cardiology, Oslo University Hospital, Ullevål, Norway
2 Center for Heart Failure Research, Oslo University Hospital, Norway
3 Faculty of Medicine, University of Oslo, Oslo, Norway
4 Akershus University Hospital, Department of Cardiology, Norway
Corresponding author:
Hani Zaidi
Center for Clinical Heart Research Department of Cardiology
Oslo University Hospital Ullevål PB 4956 Nydalen
0424 Oslo Norway
Email: hani.zaidi@medisin.uio.no
2 Abstract
Background: Adipose tissue (AT) produces pro-inflammatory mediators involved in the atherosclerotic process. We investigated whether 12-months exercise training in patients with type-2 diabetes mellitus (T2DM) and coronary artery disease (CAD) would reduce circulating levels and genetic expression of mediators in the IL-18, Caspase-1 and NLRP3 pathway. Correlations to glucometabolic variables; fasting glucose, HbA1C, duration of diabetes, insulin, C-peptide, insulin resistance (measured by HOMA2-IR) and body mass index at baseline, were further assessed.
Methods: One-hundred-and-thirty-seven patients (age 41-81 years, 17.2% females) were included and randomized to a 12-month exercise program or to a control group. Fasting blood and AT samples were taken at inclusion and after 12-months.
Results: No statistically significant difference in changes of any variable between the intervention and the control group was found. At baseline, a positive correlation between insulin and HOMA2 -IR and IL-18 expression in AT and an inverse correlation between some glucometabolic variables and leukocyte expression of NLRP3 and Caspase-1 were observed.
Conclusion: No significant effects of long-term exercise training were observed on the inflammasome-related mediators in our patients with combined CAD and T2DM. The observed correlations may indicate a pro-inflammatory state in AT by overweight and a compensatory downregulation of these mediators in circulating leucocytes.
Keywords: IL-18 pathway, adipose tissue, inflammation, coronary artery disease, diabetes type 2, exercise training
List of abbreviations AT – adipose tissue
3 BMI – body mass index
CAD – coronary artery disease cDNA – copy DNA
CVD – cardiovascular disease CV – coefficient of variation
ELISA – enyme-linked immunosorbent assay
EXCADI – Exercise training in patients with type 2 diabetes and coronary artery disease HOMA2-IR – homeostatic model assessment 2 of insulin resistance
HT – hypertension
IFN-ɣ - Interferon gamma IL – interleukin
MI - myocardial infarction
NLRP3 – NLR pyrin domain containing-3 T2DM – type 2 diabetes mellitus
4 Introduction
Type 2 diabetes mellitus (T2DM) is considered as one of the major risk factors for developing cardiovascular disease (CVD)1 , in which the atherosclerotic process is the main underlying condition. Atherosclerosis was previously considered to be a lipid-disorder, however, in recent years the prominent role of inflammation and immune response in the formation of the atherosclerotic plaque has become well recognized 2. This involves the recruitment and activation of many different cell types, including endothelial cells, smooth muscle cells, monocyte-derived macrophages, and T-cells, all contributing to a pro-
inflammatory environment 3.
Interleukin (IL)-18 is a pro-inflammatory cytokine involved in the development and progression of both atherosclerosis and T2DM 4. It is also known as an interferon (IF)-gamma (IFN-ɣ) inducing factor and is biologically active after being cleaved by Caspase-1 5. IFN-ɣ Caspase-1 is in turn activated by the NLRP3. Circulating IL-18 has been identified as an independent predictor of CVD 6, particularly related to hyperglycemia 7. Also, patients with T2DM and multi-vessel coronary artery disease (CAD) seem to be characterized by higher serum IL-18 levels, which may explain their vulnerability to secondary cardiovascular events
4, 6. Increased gene expression of Caspase-1 in aortic tissue has been demonstrated to be correlated to the severity of CAD 8, and the expression of NLRP3-inflammasome in
subcutaneous adipose tissue (AT) and peripheral blood monocytes has also been shown to be significantly higher in patients with CAD compared with healthy individuals 9, 10.
The AT has been recognized as an important source of pro-inflammatory cytokines, secreted from both the adipocytes and the infiltrated immune cells, particularly in
overweight patients 11, 12. As AT is vascularized, cytokines from AT will give rise to a systemic inflammation, which may influence the development of atherosclerosis,
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insulin resistance, T2DM, and metabolic syndrome 12. Despite some reported links between glucose and the IL-18 pathway, the importance of glycemic control for the inflammasome- related mediators in T2DM is not fully understood.
Exercise training has evolved into an established evidence-based therapeutic strategy with prognostic benefits in CAD, mainly through the beneficial influence on CVD risk factors
13. Improved glycemic control and beneficial effects on systolic blood pressure, triglycerides and waist circumference by exercise training are also evident 14, 15, whereas the effect on pro-inflammatory mediators is not clarified, especially in patients with combined CAD and T2DM.
We aimed to investigate whether exercise training would reduce the levels of circulating IL-18, as well as gene expression of IL-18, Caspase-1 and NLRP3 in circulating leukocytes and in AT in patients with CAD and T2DM. Any association between these inflammatory mediators and glucometabolic variables, as well as any relation to CAD subgroups, was further assessed.
We believe that exercise training might reduce the inflammatory burden, here investigated through IL-18 and its upstream regulators, and thereby decrease the risk of future cardiovascular events.
6 Methods
Study population
This is a sub-study of the EXCADI (Exercise training in patients with type 2 diabetes and coronary artery disease) trial, in which patients with T2DM and CAD (n=137) were included at the department of Cardiology, Oslo University Hospital, Ullevål, Norway, between August 2010 and March 2012. The study design has previously been described in details 16. In brief, the subjects were randomized 1:1 to a combination of endurance and strength training or to a control group with conventional follow-up by their general
practitioner. All patients had known T2DM and stable CAD verified by coronary angiography.
Exclusion criteria were presence of proliferative retinopathy, end-stage renal disease, cancer, stroke or acute myocardial infarction (MI) within the last 3 months, unstable angina, decompensated heart failure, serious arrhythmia, severe valvular disease, severe
rheumatologic disease, chronic obstructive pulmonary disease stadium GOLD IV,
thromboembolic disease, ongoing infections, severe musculoskeletal disorders and other disabilities limiting the ability for physical activity.
Patients with previous MI and/or diabetic microvascular complications (defined as history of nephropathy, neuropathy or retinopathy, and/or abnormal monofilament test and/or (micro-) albuminuria) were defined to have advanced vascular disease. Hypertension (HT) was defined as those on antihypertensive medication. To estimate insulin resistance, the updated HOMA2-IR was applied.
The Regional Committee of Medical Research Ethics in South-Eastern Norway approved the study and all patients gave their written informed consent to participate. The study was conducted in accordance to the Declaration of Helsinki.
7 Physical exercise intervention
The physical exercise program was developed and conducted in collaboration with the Norwegian school of Sport Sciences. Details on the exercise program have previously been described 16. Briefly, the exercise group had two group-based sessions per week with qualified instructors, and a third home-based session, for a total volume of at least 150 min per week. About two-thirds were aerobic and one-third resistance training, and each of the supervised sessions included parts with high-intensity interval training. The weekly,
unsupervised home-based exercise session was registered in exercise diaries. General activity (outside the training program), was not accounted for in either group.
A 24-h dietary recall was used for assessment of dietary intake at baseline and after the 1- year intervention16.
Laboratory methods
Venous blood samples were drawn in fasting condition by standard venipuncture between 08:00 and 10:00 a.m. before intake of morning medication at time of inclusion, and after 1 year. Subcutaneous AT taken from the gluteal region was immediately frozen at -80°C until RNA extraction. PAXgene tubes (PreAnalytix, Hombrechtikon, Switzerland) were
collected for RNA extraction from circulating leukocytes. Routine blood samples including HbA1, insulin and C-peptide were determined by conventional methods. Serum was prepared by centrifugation within 1 hour at 2500X g for 10 min for the determination of circulating IL-18, measured by ELISA (MBL, Medical & Biological Laboratories CO., LTD., Nagoya, Japan). The inter-assay CV in our laboratory was 7.7%.
Total RNA was extracted using the PAXgene® Blood RNA Kit (PreAnalytix Qiagen, Germany), with an extra cleaning step (RNeasy® MinElute® Cleanup Kit; Qiagen). RNA quality
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and quantity (ng/µL) were determined by the NanoDrop™ 1000 Spectrophotometer
(Nanodrop technologies, DE, USA). Total RNA from the adipose tissue was isolated, including disruption and homogenization in Tissue lyser (Qiagen), by the use of a High Pure RNA Tissue Kit (Hoffman-La Roche Ltd., Basel, Switzerland), according to a combination of the kit
protocol and previous experience in our laboratory. Extracted RNA from both sources was stored at -80°C until analyses. cDNA was synthesized from equal amount of RNA with qScript™ cDNA superMix (Quanta Biosciences Inc., Gaithersburg, USA). Real-time PCR was performed on a ViiA™7 instrument, using TaqMan® Universal PCR Master Mix (P/N 4324018) and TaqMan® assays for IL-18 (Hs00155517_m1), NLRP3 (Hs00918082_m1) and Caspase-1 (Hs00354836_m1) (Applied Biosystems, Foster City, CA, USA). β2-microglobulin
(HS99999907-m1) (Applied Biosystems) was used as endogenous control, and mRNA levels were determined by relative quantification (RQ) using the ΔΔCT method 17.
Statistical analyses
Demographic data are given as proportions, mean (± standard deviation), or median (25th and 75th percentiles) for skewed data. Differences between groups at baseline were analyzed by Student`s T-test or Mann-Whitney U test for continuous variables and Chi- square test for categorical variables. Within-group changes after intervention were analyzed by Wilcoxon Signed Rank test, and differences in change between randomized groups were performed by Mann-Whitney U test. Baseline associations were analyzed by the use of Spearman`s rho correlations. Statistical calculations were preformed using SPSS version 24 (SPSS lnc., Chicago Illinois, USA). P-values <0.05 were defined as statistically significant.
9 Results
Baseline characteristics of the total population and according to the randomized groups are shown in Table 1. No significant differences in baseline characteristics between the randomized groups were observed. Of the 137 included patients, 123 completed the study and 9 patients with the lowest adherence to the intervention principle were excluded
16. Thus, a total of 114 patients were analyzed for the intervention effect.
As previously reported there were no significant between-group differences in changes in weight, waist circumference, energy intake nutrients or diabetes medication during the study period16.
Blood samples at baseline were available in all, whereas after intervention, the numbers of successfully analyzed samples were 114 for circulating IL-18 and 107 for leukocyte gene expression of IL-18, NLRP3 and Caspase-1, respectively. The number of successfully analyzed AT samples at baseline and after intervention was 102 and 64 (IL-18), 69 and 26 (Caspase-1) and 62 and 17 (NLRP3), respectively. The limited number of AT samples was mainly because of patients’ unwillingness to take fat tissue biopsies, particularly after the intervention period, and inadequate quantity and quality of the samples. Due to limited number of samples with acceptable quality, especially after intervention, results on Caspase-1 and NLRP3 in AT were excluded.
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Table 1 Baseline characteristics of the total study population (n = 137) and according to the randomized groups
All (137) Exercise (69) Control (68) P-value
Age 63 (± 8) 64 (± 8) 63 (±8) 0.745
Sex (m/f) 115/22 61/8 54/14 0.152
Previous AMI, n (%) 62 (45) 28 (41) 34 (50) 0.268
Advanced disease*, n (%) 32 (23) 16 (23) 16 (24) 0.963
CHF, n (%) 11 (8) 5 (7) 6 (9) 0.734
PAD, n (%) 13 (9,5) 7 (10) 6 (9) 0.792
Duration of DM (years) 9.0 (5,15) 9.5 (5.3,15.0) 9.0 (5.0,13.5) 0.480
Hypertension, n (%) 100 (73) 49 (71) 51 (75) 0.599
Current smokers, n (%) 23 (16.8) 12 (17.4) 11 (16.2) 0.606
SBP (mmHg) 138 (127,150) 136 (128,150) 139 (124,150) 0.845
DBP (mmHg) 79 (71,86) 76 (71,76) 80 (71,87) 0.227
Weight (Kg) 86.5 (77.1,97.0) 87.5 (77.4,97.9) 85.0 (76.8,95.8) 0.662
HBA1c (%) 7.4 (± 1.34) 7.7 (±1.5) 7.5 (± 1.2) 0.709
Insulin (pmol/L) 57 (33, 101) 54 (34,99) 64 (32,108) 0.530
C-peptide (pmol/L) 965 (713,1290) 958 (711,1198) 1014 (710,1442) 0.342 Total cholesterol (mmol/L) 4.1 (±0,96) 3.9 (±0.82) 4.1 (3.3,4.8) 0.192 Triglycerides (mmol/L) 1.42 (1.06,1.91) 1.43 (1.07,1.90) 1.39 (1.01,1.94) 0.835
LDL (mmol/L) 2.0 (1.6,2.6) 1.9 (1.6,2.5) 2.1 (1.6,2.9) 0.209
HOMA2-IR 1.3 (0.7,2.1) 1.2 (0.7,1.2) 1.3 (0.7,2.3) 0.736
BMI (kg/m2) 28.7 (25.7,31.6) 29.0 (25.7,31.8) 28.2 (25.7,31.6) 0.774 Medication, n (%)
ACE-inhibitors 43 (31.6) 20 (28.9) 23 (34.3) 0.503
A2-blockers 55 (40.1) 26 (37.7) 29 (42.6) 0.553
Statins 128 (93.4) 64 (92.7) 64 (94.1) 0.747
Metformin 101 (73.7) 52 (75.4) 49 (72.1) 0.660
Sulfonylureas 48 (35.0) 29 (42.0) 19 (27.9) 0.084
Gliptin 17 (12.4) 6 11 0.992
Insulin 26 (19.1) 12 (17.4) 14 (20.9) 0.603
Aspirin 124 (90.5) 59 (86) 65 (96) 0.045
Clopidogrel 30 (21.9) 14 (20) 16 (24) 0.648
11
Values are given as number (proportions), (mean (±SD) or median (25, 75 percentile)
AMI; acute myocardial infarction, SBP; systolic blood pressure, DBP; diastolic blood pressure, DM;
diabetes mellitus, LDL; low-density lipoprotein, CHF; congestive heart failure, PAD; peripheral artery disease, HOMA2-IR; homeostatic model assessment indexes – insulin resistance, BMI; body mass index, ACE; angiotensin converting enzyme, A2; angiotensin II.
p-values refer to differences between the exercise and control group.
*Advanced disease is defined as those with previous MI and/or diabetic microvascular complications in addition to CAD
12 Effects of exercise training
Levels of the inflammatory mediators in the exercise and control group before and after the intervention period are shown in Table 2 and Figure 1.
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Table 2 Inflammatory mediators at baseline and after 12-months of intervention in both randomized groups
Values are median (25,75 percentiles)
1 P-value refers to changes within the control group from baseline to 12 months (Wilcoxon Signed Rank test)
2 P-value refers to changes within the exercise group from baseline to 12 months (Wilcoxon Signed Rank test) Delta p ( p) refers to difference in change between the groups during intervention (Mann-Whitney test) Leukoc. refers to gene expression in circulating leukocytes
AT; refers to gene expression in adipose tissue Control
p 1
Exercise
p 2
Baseline 12-months Baseline 12-months Δp
IL-18 circulating 292 (221,378) 296.0 (207,373) 0.712 332 (225,430) 322 (233,434) 0.407 0.124 IL-18 Leukoc. 1.29 (1.12,1.91) 1.32 (1.04,1.76) 0.809 1.47 (1.11,1.73) 1.38 (1.16,1.82) 0.175 0.383 IL-18 AT 0.72 (0.48,0.99) 0.83 (0.47,1.35) 0.187 0.72 (0.48,1.02) 0.62 (0.49,1,01) 0.559 0.488 NLRP3 Leukoc. 0.73 (0.44,1.13) 0.79 (0.46,1.13 0.448 0.76 (0.54,1.00) 0.71 (0.50,1.03) 0.807 0.303 Caspase-1 Leukoc. 0.99 (0.83,1.24) 1.03 (0.84,1.19) 0.124 0.99 (0.84,1.14) 1.01 (0.83,1.20) 0.432 0.102
14
Figure 1. Relative gene expression of the measured markers before and after 12-months in
both groups
Relative gene expression of the measured markers in circulating leukocytes and in adipose tissue (AT) before and after 12-months of intervention
Circulating levels
Circulating levels of IL-18 did not differ between the groups at baseline, and the difference in change between the two randomized groups did not reach statistical significance.
Gene expression in circulating leukocytes
No statistically significant differences in the expression of IL-18, Caspase-1 and NLRP3 were observed between the groups, neither at baseline and after 12-months, nor in the change after intervention (Table 2 and Figure 1).
15 Gene expression in subcutaneous AT
There was also no statistically significant difference in the gene expression of any of the measured markers in AT before and after intervention (Table 2 and Figure 1).
Advanced vascular disease
When analyzing the intervention effect according to the subgroups of patients
presenting with advanced vascular disease (n = 79), no significant difference at baseline or in change in either group after 12 months were observed, except for a more pronounced decrease in circulating IL-18 in the exercise group compared to the control group (p=0.007) (data not shown).
Baseline associations to glucometabolic variables (Table 3)
Our data showed limited significant correlations between circulating IL-18 and the glucometabolic variables, except for a correlation to C-peptide (p<0.001). IL-18 expression in circulating leukocytes was inversely correlated to C-peptide (p=0.009) and BMI (p=0.004) whereas IL-18 expression in AT, correlated positively to insulin (p<0.001), HOMA2-IR (p=0.004) and BMI (p=0.002). The expression of NLRP3 and Caspase-1 in circulating
leukocytes was inversely correlated to insulin (p=0.013 and p=0.011 respectively), C-peptide (p<0.001 and p=0.004, respectively), HOMA2-IR (p=0.002 and p= 0.001, respectively) and BMI (p=0.002 and p=0.007). No significant correlations between expression of NLRP3 and Caspase-1 in AT and the glucometabolic variables were observed.
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Table 3 Baseline correlations between glucometabolic variables and inflammatory mediators
IL-18 Leukoc. IL-18 Leukoc. NLRP3 Leukoc. Caspase1 AT IL-18 AT NLRP3 AT Caspase Duration of diabetes r = -0.108
p = 0.215
r = 0.150 p = 0.085
r = 0.148 p = 0.089
r = 0.093 p = 0.283
r = -0.093 p = 0.360
r = - 0.050 p = 0.705
r = - 0.064 p = 0.605
Glucose r = -0.049
p = 0.576
r = -0.037 p = 0.668
r = -0.018 p = 0.837
r = -0.059 p = 0.499
r = 0.105 p = 0.300
r = -0.014 p = 0.917
r = 0.095 p = 0.443
Insulin r = 0.127
p = 0.141
r = -0.134 p = 0.119
r = -0.213*
p = 0.013
r = - 0.216*
p = 0.011
r = 0.352**
p <0.001
r = - 0.139 p = 0.280
r = - 0.032 p = 0.795 C-peptide r = 0.297**
p < 0.001
r = -0.222*
p = 0.009
r = -0.340**
p <0.001
r = - 0.248**
p = 0.004
r = 0.181 p = 0.069
r = - 0.153 p = 0.235
r = 0.041 p = 0.735
HOMA2-IR r = 0.125
p = 0.162
r = -0.125 p = 0.164
r = -0.271**
p = 0.002
r = - 0.289**
p = 0.001
r = 0.294**
p = 0.004
r = - 0.172 p = 0.192
r = - 0.032 p = 0.801
BMI r = 0.122
p = 0.157
r = -0.248**
p = 0.004
r = -0.262**
p = 0.002
r = - 0.230**
p = 0.007
r = 0.309**
p = 0.002
r = - 0.119 p = 0.359
r = - 0.001 p = 0.995
*p<0.05
**p<0.005
BMI; body mass index, HOMA2-IR; homeostatic model assessment index – insulin resistance.
Leukoc; refers to gene expression in circulating leukocytes AT; refers to gene expression in adipose tissue
17 Inflammatory variables in CAD subgroups at baseline
The examined sub-groups were sex, HT, smoking history and advanced vascular disease, as defined. The results are presented in Table 4.
In AT, significantly higher IL-18 expression was found in women compared to men (p=0.03).
In circulating leukocytes lower IL-18 and NLRP3 expression were found in patients with HT compared to those without (p ≤ 0.03, both). Otherwise, no statistically significant differences were observed, although numerically higher levels of circulating IL-18 were found in patients with HT, in smokers and in patients with advanced vascular disease.
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Table 4 Differences between subgroups in baseline levels of inflammatory mediators
Sex Hypertension Smoking history Advanced vascular disease
m f + - + - + -
IL-18 circulating 303 (222,384) 306 (224, 3778) 311(222, 382) 288 (223, 383) 327 (242, 388) 299 (222, 379) 338 (223, 399) 301 (222, 377) IL-18 Leukoc. 1.41 (1.07, 1.87) 1.45 (1.13, 1.96) 1.26 (0.50, 1.59)* 1.52 (1.32, 1.91)* 1.39 (1.01, 1.67) 1.42 (1.12, 1.90) 1.52 (1.16, 1.93) 1.37 (1.05, 1.88) IL-18 AT 0.65 (0.46, 0.98)* 0.92 (0.71, 1.21)* 0.73 (0.50, 1.00) 0.65 (0.46, 1.03) 0.97 (0.61, 1.14) 0.70 (0.45, 0.97) 0.70 (0.59, 1.00) 0.75 (0.41, 1.00) NLRP3 Leukoc. 0.78 (0.51, 1.03) 0.68 (0.49, 1.16) 0.68 (0.44, 1.02)* 0.86 (0.65, 1.16)* 0.64 (0.41, 0.91) 0.78 (0.52, 1.09) 0.86 (0.44, 1.04) 0.75 (0.53, 1.05) Caspase-1 Leukoc. 0.98 (0.84, 1.15) 1.06 (0.86, 1.37) 0.98 (0.83, 1.16) 1.01 (0.87, 1.25) 0.90 (0.77, 1.10) 1.00 (0.87, 1.25) 1.01 (0.83, 1.09) 1.00 (0.86, 1.20)
*p≤0.05
Advanced vascular disease defined as previous MI and/or diabetic microvascular complications (defined as history of nephropathy, neuropathy or retinopathy, and/or abnormal monofilament test and/or (micro-) albuminuria) in addition to CAD
Leukoc. refers to gene expression in leukocytes AT; refers to gene expression in adipose tissue
19 Discussion
The main finding in our study on patients with combined T2DM and CAD was that the levels of inflammatory mediators related to the investigated IL-18 regulatory pathway did not change significantly after the exercise intervention. Some associations between the measured markers and glucometabolic variables were demonstrated, especially in relation to C-peptide and BMI. In AT, IL-18 expression was significantly more pronounced in women, whereas in patients with HT, the expression of IL-18 and NLRP3 in leukocytes was
significantly attenuated.
Although significant effects on the pro-inflammatory mediators after intervention were lacking, we observed a tendency towards lower values of circulating IL-18, and lower expression of the IL-18 gene in AT and in leukocytes after 12-months. Looking at the population, especially taken into consideration their age, weight, established CAD and several years with T2DM, it raises the question whether this population had too advanced disease to achieve the hypothesized effect of reduced inflammation after 12-months
exercise. It is also intriguing whether the amount of exercise training was sufficient to detect the expected effects. As previously reported 16, there was no significant change in weight in this group, again reflecting the possibility of insufficient exercise training. Especially when taken into consideration, that AT is regarded as an important source for the production of the investigated inflammatory mediators. Previous studies have shown an association between body weight reduction and plasma levels of IL-18 18 and between BMI and expression of IL-18 in AT 19. This may indicate AT to be an important source of IL-18 production and might reflect a close relationship between a pro-inflammatory state and obesity. Furthermore, a small study with 23 obese subjects that underwent a 15-week life style intervention with an average weight loss of 18 kg, showed a 22% reduction in
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circulating IL-18 20. There are, however, studies showing reduction of pro-inflammatory markers after exercise, regardless of weight change. A small study conducted on 36 subjects with metabolic syndrome, showed reduced serum levels of IL-18 in patients that underwent a 12-week training program or received pravastatin, compared to the control group 21. Another study showed a significant decrease in IL-18 without significant change in weight after exercise in subjects with T2DM, without vascular complications 22. This indicates that reduction in the pro-inflammatory markers is achievable without significant weight change, though the subjects in these studies seemed to have less disease progression compared to our study population.
The effects of exercise training on gene expression of IL-18 and its regulators in leukocytes have to our knowledge not previously been reported in humans. There is also limited data on exercise effects on NLRP3 and Caspase-1. Ringseis et al were able to
demonstrate that resistant and endurant exercise in obese mice on a high fat diet, lead to a reduction in AT expression of NLRP3 after a 10-week exercise program 23.
At baseline, we found a significant correlation between expression of IL-18 in AT and BMI, Insulin and HOMA2-IR. AT expression of IL-18 has been reported to be positively correlated to insulin resistance, and the observed reduction in AT IL-18 expression after exercise training was thought to partly be due to the beneficial effects on insulin-resistance
20, 24. This is in accordance with our hypothesis of inflammation being closely linked to, not only obesity per se, but a pathological metabolic state.
The baseline findings with the inverse correlations between gene expression of NLRP3 and Caspase-1 in circulating leukocytes and the glucometabolic variables, could be indicative of a down regulatory mechanism of their expression in leukocytes with increasing insulin production and insulin resistance. This poses the question of the leukocytes potential
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protective role in this particular setting, also highlighted by the observed inverse correlation between gene expression of IL-18 in circulating leukocytes and C-peptide and BMI in our study. This is partly consistent with our recently published results from a study conducted on young adult men, demonstrating an inverse correlation between leukocyte expression of NLRP3 and insulin, C-peptide and BMI. In that particular study, we also showed even
stronger associations between glucometabolic variables and circulating and AT gene expression of IL-18 compared to the present study 25. This difference between our two studies may in part be explained by the comorbid population in the present study, heavily medicated on statins and anti-diabetic drugs, hence an altered glucometabolic state and a different composition of the AT is most likely present. However, the clear similarities between our two studies are interesting and supports our claim that glucometabolic variables are associated with an inflammatory state, particularly in AT.
We could further demonstrate a correlation between circulating IL-18 and C-peptide which is partly in accordance with a study on young females showing a possible role of C- peptide in predicting CVD 26. This might be suggestive of an increased inflammatory activity in patients with increased insulin production and overweight, which is also consistent with other previous findings 20, 25 and our initial assumptions. Overweight and insulin-resistance seems to be closely linked to gene expression of IL-18 in AT as discussed previously 20, 24. C- peptide is widely used and accepted in clinical practice as a measure of β-cell function and insulin resistance 27. It is co-secreted with insulin in equimolar amounts in the islets of Langerhans. The kinetics of its degradation is not exactly the same as insulin, but its concentration in serum does closely reflect the insulin-producing capacity of β-cells in pancreas. IL-18 in combination with IFN- ɣ seems to be involved in the impairment of β-cell function by apoptotic cell death, at least in vitro 28.
22
In the subgroup analyses, we found higher levels of AT IL-18 expression in women compared to men. In hypertensive patients, lower levels of IL-18 and NLRP3 expression in leukocytes were observed compared to normotensive patients, which further supports the theory of leukocytes’ possible protective role in this setting. An association between HT and elevated levels of circulating and vascular levels of IL-18 and its regulators has previously been reported, but it is unknown whether elevated circulating IL-18 is a cause or a mere consequence of long-standing elevated blood pressure 29.
Patients with previous AMI and/or diabetic microvascular complications were defined as those with advanced vascular disease. When stratifying patients by these criteria in the main EXCADI study and excluding patients with advanced vascular disease, an improvement in HbA1c and VO2max was observed in the exercise group 16. We could, however, not demonstrate any differences on the investigated markers in this subgroup in the present investigation.
Limitations
The limitations of this study is that it was initially designed for the purpose of measuring effects on HbA1c after exercise training 16, hence, the initial power calculations have not considered effects on the investigated pro-inflammatory mediators. The subjects in our study were also heavily medicated with ACEI/A2 blockers, statins, platelet inhibitors and antidiabetics. Some of these medications, like statins (93% users) and platelet inhibitors (94% users) are known to have anti-inflammatory properties 30, which may have suppressed the values of the investigated inflammatory mediators, thereby masking potential effects of exercise training. As occurs from Table 1, there was significant higher number of aspirin users in the control group. In AT tissue, aspirin has been shown to reduce expression of the
23
pro-inflammatory cytokines IL-1β and IL-6 in macrophages and further to increase IL-10 expression, which have anti-inflammatory properties31. The effects of aspirin specifically on IL-18, Caspase-1 and NLRP3 have, to the best of our knowledge, not previously been
reported on.
Similarly, there was higher number of sulfonylurea users in the control group, the difference approaching statistical significance. Sulfonylurea seems to possess several anti- inflammatory attributes, such as suppressing the pro-inflammatory cytokines IL-8 and IL-1β production by leukocytes32, 33.
Due to limited number of AT samples after intervention, effects on Caspase-1 and NLRP3 could not be investigated. The strength of this study was the randomization principle with long-term intervention with equal distribution of the study population and few
differences between groups at baseline.
Conclusions
We could not demonstrate any significant effect of long-term exercise intervention on the pro-inflammatory mediator IL-18 and the upstream activators Caspase-1 and NLRP3 in our population of patients with a combination of CAD and T2DM.
We did observe inverse associations between leukocyte expression of IL-18, NLRP3 and Caspase-1 and glucometabolic variables, indicating their protective role. A close link
between overweight, insulin resistance and expression of IL-18 in AT, probably representing an increased inflammatory state in AT, was confirmed.
This study may indicate that a population with less comorbidities and less medicated would benefit more from exercise training to reduce the inflammatory burden than the population in our study.
24 Acknowlgedements
The authors want to thank Vibeke Bratseth and Beate Vestad for laboratory assistance. Trial registration: clinicaltrials.gov, NCT01232608.
Availability of data and materials
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request
Declarations of conflicting interest
The authors declare that there is no conflict of interest Funding
This work was supported by the Stein Erik Hagen Foundation for Clinical Heart Research; and the Ada og Hagbart Waages Humanitære og Veldedige Stiftelse, Oslo, Norway.
25 References
1. Kannel WB and McGee DL. Diabetes and cardiovascular risk factors: the Framingham study.
Circulation 1979; 59: 8-13. 1979/01/01.
2. Libby P, Ridker PM and Maseri A. Inflammation and atherosclerosis. Circulation 2002; 105:
1135-1143. 2002/03/06.
3. Hernesniemi JA, Anttila K, Nieminen T, et al. IL-18 gene polymorphism, cardiovascular mortality and coronary artery disease. Eur J Clin Invest 2010; 40: 994-1001. 2010/08/26. DOI:
10.1111/j.1365-2362.2010.02356.x.
4. Suchanek H, Mysliwska J, Siebert J, et al. High serum interleukin-18 concentrations in patients with coronary artery disease and type 2 diabetes mellitus. Eur Cytokine Netw 2005; 16: 177- 185. 2005/11/04.
5. Dinarello CA. Interleukin-18. Methods 1999; 19: 121-132. 1999/10/20. DOI:
10.1006/meth.1999.0837.
6. Chen MC, Chen CJ, Yang CH, et al. Interleukin-18: a strong predictor of the extent of coronary artery disease in patients with unstable angina. Heart Vessels 2007; 22: 371-375. 2007/11/29. DOI:
10.1007/s00380-007-0991-z.
7. Troseid M, Seljeflot I, Hjerkinn EM, et al. Interleukin-18 is a strong predictor of cardiovascular events in elderly men with the metabolic syndrome: synergistic effect of inflammation and
hyperglycemia. Diabetes Care 2009; 32: 486-492. 2008/12/19. DOI: 10.2337/dc08-1710.
8. Zheng F, Gong Z, Xing S, et al. Overexpression of caspase-1 in aorta of patients with coronary atherosclerosis. Heart Lung Circ 2014; 23: 1070-1074. 2014/06/24. DOI: 10.1016/j.hlc.2014.04.256.
9. Bando S, Fukuda D, Soeki T, et al. Expression of NLRP3 in subcutaneous adipose tissue is associated with coronary atherosclerosis. Atherosclerosis 2015; 242: 407-414. 2015/08/19. DOI:
10.1016/j.atherosclerosis.2015.07.043.
10. Paramel Varghese G, Folkersen L, Strawbridge RJ, et al. NLRP3 Inflammasome Expression and Activation in Human Atherosclerosis. Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease 2016; 5: e003031. DOI: 10.1161/JAHA.115.003031.
11. Jung UJ and Choi M-S. Obesity and Its Metabolic Complications: The Role of Adipokines and the Relationship between Obesity, Inflammation, Insulin Resistance, Dyslipidemia and Nonalcoholic Fatty Liver Disease. Int J Mol Sci 2014; 15: 6184-6223. DOI: 10.3390/ijms15046184.
12. Libby P, Okamoto Y, Rocha VZ, et al. Inflammation in atherosclerosis: transition from theory to practice. Circ J 2010; 74: 213-220. 2010/01/13.
13. Gielen S, Laughlin MH, O'Conner C, et al. Exercise training in patients with heart disease:
review of beneficial effects and clinical recommendations. Prog Cardiovasc Dis 2015; 57: 347-355.
2014/12/03. DOI: 10.1016/j.pcad.2014.10.001.
14. Chudyk A and Petrella RJ. Effects of exercise on cardiovascular risk factors in type 2 diabetes:
a meta-analysis. Diabetes Care 2011; 34: 1228-1237. 2011/04/29. DOI: 10.2337/dc10-1881.
15. Adamu B, Sani MU and Abdu A. Physical exercise and health: a review. Niger J Med 2006; 15:
190-196. 2006/11/23.
16. Byrkjeland R, Njerve IU, Anderssen S, et al. Effects of exercise training on HbA1c and VO2peak in patients with type 2 diabetes and coronary artery disease: A randomised clinical trial.
Diab Vasc Dis Res 2015; 12: 325-333. 2015/06/21. DOI: 10.1177/1479164115590552.
17. Livak KJ and Schmittgen TD. Analysis of relative gene expression data using real-time
quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001; 25: 402-408. 2002/02/16. DOI:
10.1006/meth.2001.1262.
18. Esposito K, Pontillo A, Ciotola M, et al. Weight loss reduces interleukin-18 levels in obese women. J Clin Endocrinol Metab 2002; 87: 3864-3866. 2002/08/06. DOI: 10.1210/jcem.87.8.8781.
26
19. Ahmad R, Thomas R, Kochumon S, et al. Increased adipose tissue expression of IL-18R and its ligand IL-18 associates with inflammation and insulin resistance in obesity. Immunity, inflammation and disease 2017; 5: 318-335. 2017/05/17. DOI: 10.1002/iid3.170.
20. Bruun JM, Stallknecht B, Helge JW, et al. Interleukin-18 in plasma and adipose tissue: effects of obesity, insulin resistance, and weight loss. Eur J Endocrinol 2007; 157: 465-471. 2007/09/26. DOI:
10.1530/eje-07-0206.
21. Troseid M, Lappegard KT, Mollnes TE, et al. The effect of exercise on serum levels of interleukin-18 and components of the metabolic syndrome. Metab Syndr Relat Disord 2009; 7: 579- 584. 2009/11/11. DOI: 10.1089/met.2009.0003.
22. Kadoglou NP, Iliadis F, Angelopoulou N, et al. The anti-inflammatory effects of exercise training in patients with type 2 diabetes mellitus. Eur J Cardiovasc Prev Rehabil 2007; 14: 837-843.
2007/11/29. DOI: 10.1097/HJR.0b013e3282efaf50.
23. Ringseis R, Eder K, Mooren FC, et al. Metabolic signals and innate immune activation in obesity and exercise. Exerc Immunol Rev 2015; 21: 58-68. 2015/04/01.
24. Leick L, Lindegaard B, Stensvold D, et al. Adipose tissue interleukin-18 mRNA and plasma interleukin-18: effect of obesity and exercise. Obesity (Silver Spring, Md) 2007; 15: 356-363.
2007/02/15. DOI: 10.1038/oby.2007.528.
25. Akra S, Aksnes TA, Flaa A, et al. Interleukin-18 and the NLR family pyrin domain containing-3 inflammasome in adipose tissue are strongly associated with glucometabolic variables in a cohort of middle-aged men. Diab Vasc Dis Res 2018: 1479164118785307. 2018/07/05. DOI:
10.1177/1479164118785307.
26. Abdullah A, Hasan H, Raigangar V, et al. C-Peptide versus insulin: relationships with risk biomarkers of cardiovascular disease in metabolic syndrome in young arab females. Int J Endocrinol 2012; 2012: 420792. 2012/08/18. DOI: 10.1155/2012/420792.
27. Leighton E, Sainsbury CAR and Jones GC. A Practical Review of C-Peptide Testing in Diabetes.
Diabetes Ther 2017; 8: 475-487. DOI: 10.1007/s13300-017-0265-4.
28. Banerjee M and Saxena M. Interleukin-1 (IL-1) family of cytokines: role in type 2 diabetes.
Clin Chim Acta 2012; 413: 1163-1170. 2012/04/24. DOI: 10.1016/j.cca.2012.03.021.
29. Krishnan SM, Sobey CG, Latz E, et al. IL-1beta and IL-18: inflammatory markers or mediators of hypertension? Br J Pharmacol 2014; 171: 5589-5602. 2014/08/15. DOI: 10.1111/bph.12876.
30. Muller KA, Chatterjee M, Rath D, et al. Platelets, inflammation and anti-inflammatory effects of antiplatelet drugs in ACS and CAD. Thromb Haemost 2015; 114: 498-518. 2015/08/01. DOI:
10.1160/th14-11-0947.
31. Herova M, Schmid M, Gemperle C, et al. Low dose aspirin is associated with plasma chemerin levels and may reduce adipose tissue inflammation. Atherosclerosis 2014; 235: 256-262. 2014/06/02.
DOI: 10.1016/j.atherosclerosis.2014.05.912.
32. Yaribeygi H, Atkin SL, Pirro M, et al. A review of the anti-inflammatory properties of antidiabetic agents providing protective effects against vascular complications in diabetes. J Cell Physiol 2018 2018/11/13. DOI: 10.1002/jcp.27699.
33. Kewcharoenwong C, Rinchai D, Utispan K, et al. Glibenclamide reduces pro-inflammatory cytokine production by neutrophils of diabetes patients in response to bacterial infection. Sci Rep 2013; 3: 3363. 2013/11/29. DOI: 10.1038/srep03363.
