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Interleukin-15 and irisin serum concentrations are not related to cardiometabolic risk factors in patients with type 2 diabetes from Korea and Germany

  • Kyung Mook ChoiEmail author
  • Soon Young Hwang
  • Kyungdo Han
  • Hye Soo Chung
  • Nam Hoon Kim
  • Hye Jin Yoo
  • Ji-A. Seo
  • Sin Gon Kim
  • Nan Hee Kim
  • Sei Hyun Baik
  • Thomas Ebert
  • Mathias Fasshauer
  • Matthias BlüherEmail author
Open Access
Short Communication
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Introduction

Physical exercise plays an important role in both the prevention and treatment of cardiometabolic diseases. Peptides secreted or released from skeletal muscle, so-called myokines, contribute to the beneficial anti-inflammatory and insulin-sensitizing effects of increased muscle activity and may, therefore, counteract pathomechanisms of obesity and type 2 diabetes (T2D) [1]. However, the impact of myokines including interleukin (IL)-6, IL-8, IL-13, IL-15, angiopoietin-like 4 (ANGPTL4), fibroblast growth factors (FGF)-2, FGF-21, and irisin on altered organ cross-talk in cardiometabolic diseases is still poorly understood [1]. Irisin has been described as a protein released from skeletal muscle after physical activity [2] which may, in rodents and more controversially discussed in humans [1], mediate browning of white adipose tissue. Although the existence of circulating human irisin has even been questioned because human FNDC5 has a noncanonical ATA translation start, irisin has been detected in human plasma using mass spectrometry with appropriate control peptides [3]. IL-15 increases upon both aerobic and resistance exercise and exerts beneficial metabolic effects in patients with obesity and T2D [1]. IL-15 inhibits lipogenesis, induces fat oxidation, enhances energy expenditure, and improves insulin sensitivity and glucose metabolism [4]. To better understand the potential role of these myokines in T2D, we tested the hypotheses that IL-15 and irisin serum concentrations correlate with cardiometabolic risk parameters and are different in subgroups of T2D patients with or without diabetes complications independently of ethnicity.

Methods

Study design and participants

Korea

We included cross-sectional data from 400 Korean participants of the ongoing Korean Sarcopenic Obesity Study (KSOS) described in detail elsewhere [5]. Blood and random spot urine samples were collected in the morning after a 12 h fasting. Kidney function was assessed by estimating the eGFR using the Chronic Kidney Disease Epidemiology Collaboration formula. The urinary albumin and creatinine levels were used to calculate the urine albumin/creatinine ratio (ACR, μg/mg), and albuminuria was defined as ≥ 30 μg/mg urinary ACR. Diabetic retinopathy was diagnosed by specialized ophthalmologists from Korea University. The Korea University Institutional Review Board approved the study protocol.

Germany

We included a total of 400 participants (200 women, 200 men) with an established diagnosis of T2D which have been consecutively recruited at the Department of Medicine of the University Hospital in Leipzig (Germany). Patients were excluded from the analyses according to the criteria defined for the Korean subcohort. The study has been approved by the ethics committee of the University of Leipzig (approval no. 017-12-23012012), and all subjects gave written informed consent before taking part in the study. All blood samples were collected between 8 and 10 a.m. after 12 h overnight fast. T2D complications were defined as described in the Korean cohort.

IL-15 and irisin measurements

Serum samples were analyzed centrally at Woongbee Meditech Inc., Korea. Irisin (Biovendor, Brno, Czech Republic) and IL-15 (R&D Systems Inc., Minneapolis, MN, USA) concentrations were measured using specific enzyme-linked immunosorbent assays (ELISA).

Statistical analyses

Korean and German study populations were compared using the Mann–Whitney U test or independent t test. Fisher’s exact test or Pearson’s Chi-square was utilized to evaluate the differences in the categorical variable distribution. To investigate correlations between myokines and cardiometabolic variables, Spearman partial correlation analysis was used after adjusting for age and sex. Data were analyzed using SAS 9.2 (SAS Institute, Cary, NC, USA). A p value < 0.05 indicates statistical significance.

Results

For almost all cardiometabolic risk parameters and the occurrence of T2D complications, we found significant differences between the German and Korean subcohorts (Table 1). Despite these differences, irisin and IL-15 serum concentrations were indistinguishable between German and Korean study participants, except for higher circulating irisin levels in Korean women compared to German women (p = 0.002). Independent of ethnicity, irisin and IL-15 serum concentrations were not correlated with most cardiometabolic risk factors (Table 2). In German participants, fat-free mass was negatively associated with irisin levels, whereas all other anthropometric and laboratory variables were not significantly correlated with irisin or IL-15 concentrations (Table 2). In Korean patients, irisin levels were negatively related to ACR levels and IL-15 concentrations only were negatively correlated with liver aminotransferases (Table 2).
Table 1

Interleukin-15 and irisin serum concentrations in two independent cohorts from Germany and Korea

 

Men

p

Women

p

Germans (n = 200)

Koreans (n = 213)

Germans (n = 200)

Koreans (n = 187)

Age (years)

55.7 (51.0, 61.5)

58.0 (51.0, 66.0)

0.014

55.0 (49.1, 61.3)

60.0 (53.0, 66.0)

< 0.001

BMI (kg/m2)

43.0 (38.4, 49.5)

24.5 (22.8, 26.8)

< 0.001

42.4 (37.4, 50.5)

25.0 (23.0, 27.2)

< 0.001

SBP (mmHg)

134 (127, 145)

126 (118, 134)

< 0.001

134 (126, 146)

127 (115, 138)

< 0.001

DBP (mmHg)

80 (75, 86)

82 (74, 88)

0.797

82 (75, 89)

78 (72, 86)

0.001

AST (IU/L)

31.7 (25.7, 38.9)

15.0 (12.0, 22.0)

< 0.001

27.2 (22.8, 34.7)

13.0 (9.0, 20.0)

< 0.001

ALT (IU/L)

32.3 (23.4, 46.7)

18.0 (15.0, 24.0)

< 0.001

26.3 (20.4, 39.5)

18.0 (14.0, 22.0)

< 0.001

Total cholesterol (mmol/L)

4.8 (4.1, 5.5)

3.3 (2.7, 4.1)

< 0.001

5.1 (4.5, 6.0)

3.5 (2.8, 4.1)

< 0.001

HDL cholesterol (mmol/L)

1.1 (1.0, 1.3)

1.0 (0.8, 1.1)

< 0.001

1.3 (1.1, 1.5)

1.0 (0.8, 1.3)

< 0.001

Triglycerides (mmol/L)

1.8 (1.4, 2.7)

2.9 (1.9, 4.4)

< 0.001

1.7 (1.3, 2.5)

2.7 (1.9, 4.0)

< 0.001

LDL cholesterol (mmol/L)

2.8 (2.3, 3.4)

1.6 (1.2, 2.2)

< 0.001

3.1 (2.6, 3.9)

1.8 (1.3, 2.3)

< 0.001

FPG (mmol/L)

7.3 (5.9, 9.1)

5.9 (4.9, 6.9)

< 0.001

6.7 (5.3, 8.7)

5.8 (4.9, 7.1)

< 0.001

Creatinine (mg/dL)

1.1 (0.9, 1.3)

0.8 (0.6, 0.9)

< 0.001

0.9 (0.8, 1.1)

0.6 (0.5, 0.7)

< 0.001

eGFR (ml/min/1.73 m2)

71.2 (57, 87)

98.7 (81.5, 129.6)

< 0.001

64.5 (52.6, 76.2)

101.2 (82.7, 137.7)

< 0.001

HbA1c (%)

6.5 (5.8, 7.3)

7.1 (6.5, 7.6)

< 0.001

6.0 (5.5, 6.9)

7.1 (6.6, 7.9)

< 0.001

Smoking (n, %)

28 (14)

74 (34.7)

< 0.001

30 (15)

11 (5.9)

0.004

Retinopathy (n, %)

86 (43.0)

53 (27.7)

0.002

104 (52.0)

45 (27.1)

< 0.001

 No retinopathy

114 (57.0)

138 (72.3)

 

96 (48.0)

121 (72.9)

 

 NPDR

77 (38.5)

45 (23.6)

 

94 (47.0)

35 (21.1)

 

 PDR

9 (4.5)

8 (4.2)

 

10 (5.0)

10 (6.0)

 

Albuminuria (n, %)

31 (15.5)

54 (25.8)

0.010

38 (19.0)

46 (25.0)

0.155

 < 30 mg/g

169 (84.5)

155 (74.2)

 

162 (81.0)

138 (75.0)

 

 30–299 mg/g

29 (14.5)

42 (20.1)

 

33 (16.5)

36 (19.6)

 

 ≥ 300 mg/g

2 (1.0)

12 (5.7)

 

5 (2.5)

10 (5.4)

 

ACR (mg/g)

4.4 (0, 17.6)

8.2 (4.8, 31.2)

< 0.001

1.3 (0., 15.8)

10.2 (5.1, 30.0)

< 0.001

Body fat (%)

36.0 (31.3, 39.5)

21.7 (19.0, 24.9)

< 0.001

46.4 (43.2, 49.8)

31.1 (27.2, 34.8)

< 0.001

Fat mass (kg)

49.2 (38.5, 60.4)

15.1 (12.3, 19.1)

< 0.001

53.0 (44.4, 64.6)

18.8 (15.4, 22.8)

< 0.001

Fat-free mass (kg)

88.8 (80.4, 98.3)

53.2 (49.8, 57.5)

< 0.001

62.0 (56.9, 67.9)

40.8 (37.5, 44.6)

< 0.001

CIMT (mm)

0.68 (0.44, 0.93)

0.78 (0.69, 0.92)

< 0.001

0.68 (0.46, 0.91)

0.72 (0.64, 0.87)

0.010

Irisin (μg/mL)

4.4 (3.5, 5.5)

4.2 (3.4, 5.7)

0.659

4.3 (3.5, 5.3)

4.6 (3.5, 7.3)

0.002

IL-15 (pg/mL)

1.1 (0.9, 1.4)

1.1 (0.8, 1.4)

0.330

1.1 (0.8, 1.3)

1.0 (0.8, 1.3)

0.762

BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate aminotransferase; ALT, alanine aminotransferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; FPG, fasting plasma glucose; eGFR, estimated glomerular filtration rate; PDR, proliferative retinopathy; NDPR, nonproliferative retinopathy; ACR, urine albumin-to-creatinine ratio; CIMT, carotid intima-media thickness; IL-15, interleukin-15

Table 2

Age- and sex-adjusted partial correlation analyses of irisin and IL-15 serum concentrations, clinical and laboratory parameters

 

Germans

Koreans

Irisin

IL-15

Irisin

IL-15

r

p

r

p

r

p

r

p

BMI

− 0.044

0.389

− 0.050

0.326

− 0.033

0.513

0.064

0.207

SBP

0.022

0.665

0.042

0.404

0.023

0.646

0.038

0.446

DBP

0.026

0.611

0.027

0.592

0.049

0.326

− 0.022

0.668

AST

0.031

0.535

0.068

0.177

− 0.059

0.243

− 0.151

0.003 a

ALT

0.020

0.686

0.017

0.741

− 0.033

0.517

− 0.120

0.017 a

Total cholesterol

0.004

0.937

0.008

0.867

0.057

0.258

− 0.080

0.114

HDL cholesterol

− 0.008

0.881

0.047

0.353

0.082

0.102

− 0.061

0.230

Triglycerides

0.049

0.333

0.001

0.988

0.019

0.702

0.003

0.953

LDL cholesterol

− 0.003

0.957

− 0.017

0.731

0.038

0.454

− 0.061

0.227

FPG

− 0.015

0.765

− 0.009

0.864

0.080

0.113

− 0.022

0.667

HbA1c

− 0.064

0.204

− 0.043

0.394

− 0.026

0.603

0.018

0.716

Creatinine

− 0.043

0.394

0.001

0.990

− 0.087

0.082

0.027

0.594

eGFR

0.047

0.347

0.007

0.883

0.092

0.068

− 0.024

0.639

ACR

− 0.095

0.059

− 0.030

0.548

− 0.162

0.001 a

0.089

0.079

Body fat

− 0.038

0.519

− 0.054

0.360

0.035

0.487

0.043

0.400

Fat mass

− 0.076

0.192

− 0.076

0.193

0.018

0.722

0.090

0.076

Fat-free mass

− 0.116

0.047 a

− 0.084

0.151

− 0.042

0.404

0.094

0.062

CIMT

− 0.005

0.943

− 0.047

0.506

− 0.089

0.082

− 0.005

0.915

aAfter adjusting correlation coefficients to correct for multiple comparisons by Bonferroni’s correction, none of the significant correlations (bold) remained significant

BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate aminotransferase; ALT, alanine aminotransferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; FPG, fasting plasma glucose; eGFR, estimated glomerular filtration rate; ACR, urine albumin-to-creatinine ratio; CIMT, carotid intima-media thickness

In analyses of the entire study population and in the German and Korean subgroups, irisin and IL-15 serum concentrations were not significantly different between T2D patients with or without evidence for diabetic retinopathy (data not shown). Comparisons of participants with or without albuminuria only revealed significantly lower irisin (but not IL-15) serum concentrations (p = 0.029) in Korean T2D patients with albuminuria.

Discussion

The key result of our study is that despite significant differences in almost all anthropometric parameters and cardiometabolic risk factors between German and Korean T2D patients, both irisin and IL-15 serum concentrations were indistinguishable. Noteworthily, Korean women displayed slightly higher irisin levels than German women. In addition, we could reproducibly show for the German and Korean cohort that irisin and IL-15 serum concentrations are not related to cardiometabolic risk factors or the presence of diabetes complications. There was only one exception that Korean T2D patients with albuminuria showed lower irisin levels compared to those without albuminuria, generating the hypothesis that there are ethnic differences in the interplay between irisin secretion or clearance and renal function. An important limitation of our study is that we only analyzed the circulating myokines at one time point. We can, therefore, not exclude that these myokines may be relevant biomarkers for the prognosis of cardiometabolic diseases and/or for the evaluation of treatment response. Another limitation is that our study combined two separate data collections into one evaluation, which may have created a potential bias.

In conclusion, our data suggest that neither irisin nor IL-15 serum concentrations reflect cardiometabolic risk factors or T2D complications in two independent cohorts from Korea and Germany.

Notes

Acknowledgements

This research was supported by the European Foundation for the Study of Diabetes (EFSD)/Sanofi research grant, which is funded by the European Association for the Study of Diabetes (EASD) (individual Creditor No. 94909).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Approval of the study was given by the ethics committee of the University of Leipzig and the Korea University Institutional Review Board.

Informed consent

All persons gave their informed consent prior to their inclusion into the study.

References

  1. 1.
    Eckel J (2019) Myokines in metabolic homeostasis and diabetes. Diabetologia.  https://doi.org/10.1007/s00125-019-4927-9 Google Scholar
  2. 2.
    Boström P, Wu J, Jedrychowski MP et al (2012) A PGC1-α-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature 481:463–468CrossRefGoogle Scholar
  3. 3.
    Jedrychowski MP, Wrann CD, Paulo JA et al (2015) Detection and quantitation of circulating human Irisin by tandem mass spectrometry. Cell Metab 22:734–740CrossRefGoogle Scholar
  4. 4.
    Ye J (2015) Beneficial metabolic activities of inflammatory cytokine interleukin 15 in obesity and type 2 diabetes. Front Med 9:139–145CrossRefGoogle Scholar
  5. 5.
    Kim TN, Park MS, Yang SJ et al (2010) Prevalence and determinant factors of sarcopenia in patients with type 2 diabetes: the Korean Sarcopenic Obesity Study (KSOS). Diabetes Care 33:1497–1499CrossRefGoogle Scholar

Copyright information

© The Author(s) 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Kyung Mook Choi
    • 1
    Email author
  • Soon Young Hwang
    • 2
  • Kyungdo Han
    • 3
  • Hye Soo Chung
    • 1
  • Nam Hoon Kim
    • 1
  • Hye Jin Yoo
    • 1
  • Ji-A. Seo
    • 1
  • Sin Gon Kim
    • 1
  • Nan Hee Kim
    • 1
  • Sei Hyun Baik
    • 1
  • Thomas Ebert
    • 4
  • Mathias Fasshauer
    • 4
  • Matthias Blüher
    • 4
    Email author
  1. 1.Division of Endocrinology and Metabolism, Department of Internal Medicine, College of MedicineKorea UniversitySeoulKorea
  2. 2.Department of Biostatistics, College of MedicineKorea UniversitySeoulKorea
  3. 3.Department of Biostatistics, College of MedicineThe Catholic University of KoreaSeoulKorea
  4. 4.Department of MedicineUniversity of LeipzigLeipzigGermany

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