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  • Research note
  • Open Access

Adipocytokines in obese Ghanaian subjects with or without type 2 diabetes

  • 1,
  • 2,
  • 3Email author,
  • 3,
  • 4,
  • 5 and
  • 6
BMC Research Notes201811:109

https://doi.org/10.1186/s13104-018-3149-4

Received: 14 October 2017

Accepted: 9 January 2018

Published: 8 February 2018

Abstract

Objective

This study aimed to evaluate serum leptin and high sensitivity C-reactive protein (hsCRP) concentrations in obese Ghanaians with or without type 2 diabetes and to find out the extent to which their levels are influenced by underlying disorders.

Results

Obese subjects with type 2 diabetes had lower leptin but higher hsCRP levels compared with obese non-diabetic controls. There were negative correlations within the control group for glucose vs % muscle mass (r = − 0.378, p = 0.016), leptin vs % muscle mass (r = − 0.555, p = 0.001) and within the obese diabetic group for leptin vs % muscle mass (r = − 0.602, p = 0.001). Obese persons without diabetes were about three times more likely to have higher leptin levels compared with their obese diabetic counterparts (Odds ratio = 3.315, p < 0.001). Obese females independently had a tenfold increase in leptin levels compared with obese males.

Keywords

  • Leptin
  • Obesity
  • C-reactive protein
  • Type 2 diabetes

Introduction

Chronic disorders such as obesity and diabetes mellitus have reached epidemic proportions globally [13] with approximately eighty percent (80%) of the populace with type 2 diabetes mellitus either obese or overweight [4, 5]. Reports by International Diabetes Federation in 2015 revealed that an estimated (3.3–6.0) % of Ghanaians aged 20–79 years had diabetes mellitus with a further 7.8% being glucose impaired [1]. Inflammatory markers have generally been implicated in insulin resistance [69]. Leptin, a 16 kDa protein, secreted by the adipose tissue is a potential determinant of adiposity and risk for type 2 diabetes [1013]. High sensitivity C-reactive protein (hsCRP), an acute phase protein is synthesized by the liver and increases in concentration following infection, inflammation or trauma [9]. Levels of hsCRP have been observed to be increased in obese persons with diabetes mellitus and correlate with measures of adiposity including body mass index (BMI) and waist circumference [14, 15]. The extent to which these biomarkers contribute to metabolic function and/or dysfunction is not fully understood especially in relation to gender and ethnicity. The purpose of this study was to evaluate serum leptin and hsCRP concentrations in Ghanaian obese subjects with and/or without type 2 diabetes and to find out the extent to which their levels are influenced by the underlying disorder. We hypothesized that obese subjects with type 2 diabetes will have higher leptin and hsCRP levels compared with their obese non-diabetic counterparts.

Main text

Methods

The study design was a cross-sectional one conducted among 160 obese (BMI > 30 kg/m2) Ghanaian subjects between October 2014 and April 2015. Study participants included 80 type 2 diabetic persons attending the National Diabetes Management and Research Centre (NDMRC), Korle-Bu, Accra and 80 age and gender-matched obese staff/workers of the Korle-Bu Teaching Hospital, Accra, Ghana without diabetes mellitus. Consecutive subjects who agreed to the study and met the criteria for inclusion were recruited. An oral glucose tolerance test (OGTT), regarded as diagnostic of type 2 diabetes were performed on all volunteers. Obesity was defined based on BMI ≥ 30 kg/m2. Type 2 diabetes was confirmed by a physician at the National Diabetes Management and Research Centre (NDMRC), Korle-Bu, Accra, based on results of fasting blood glucose ≤ 6.9 mmol/L and a 2 h-OGTT > 11.1 mmol/L on two separate occasions. Case subjects were either being lifestyle managed or were on oral hypoglycemic drugs. A pre tested structured (Additional file 1: Questionnaire) was administered to assess the socio-economic status, medical history and medications, family history of diabetes mellitus, and level of physical activity of subjects. Habitual smokers, defined as subjects who smoked tobacco or other smoking products (and are still smoking) continuously for at least 6 months, persons with gestational diabetes, chronic illnesses (having a persistent ailment for more than 3 months), stroke or amputation were excluded from the study. Assuming an odds ratio of 2 among obese subjects for type 2 diabetes, at 95% confidence interval and a power of 80%, a sample size of 60 persons were adequate for this study. The study was approved (Protocol Identification Number: MS-Et/M.6–P3.2/2014-2015) by the Institutional Ethics and Protocol Review Committee of School of Medicine and Dentistry, College of Health Sciences, University of Ghana. Detailed explanations on purpose of the study, risk and benefits were made known to participants. Written informed consent was obtained from all participants. Height of all participants were measured using a stadiometer (Secca, Germany). Weight was measured using a Full Body Sensor Body Composition Monitor and Scale (Omron model HBF-516, Omron Healthcare, USA). This scale employed bio-impedance analysis to compute percentage body fat (% body fat), percentage muscle mass (% muscle mass) and visceral fats. Blood pressure was taken using a mercury sphygmomanometer and stethoscope after participants had rested for 15 min. Venous blood (5 mL) was obtained from the subjects between 07:00 and 09:00 h each day, after an overnight fast, according to Helsinki protocol declaration (2008). One milliliter (1 mL) of whole blood was transferred into sodium fluoride containing tube and the plasma separated for the estimation of glucose. The remaining four milliliters (4 mL) of whole blood was placed into serum separator tubes for processing. Resulting sera were then aliquoted in 0.5 mL portions into sterile eppendorf tubes and stored at − 20 °C until required for use. Fasting blood glucose, total cholesterol (TCHOL), triglycerides (TG), low density lipoprotein (LDL) and high density lipoprotein cholesterol (HDL) were analyzed using auto-analyzer (Roche-Hitachi Modular Analytics, Tokyo, Japan) at the Department of Chemical Pathology Laboratory of the School of Biomedical and Allied Health Sciences, University of Ghana. Serum leptin and hsCRP levels were measured using enzyme-linked immunosorbent assay kits (GenWay Biotech Inc. VA, USA) at the Public Health Reference Laboratory, Accra. A calibration curve was used to determine analyte concentrations from the strength of signal produced in the immunoassay. Unspecific substrate binding was eliminated by using a specific secondary antibody. The GraphPad prism software version 6.0 (San Diego California, USA) was used for statistical analysis. Values are expressed as mean ± standard deviation. The unpaired student t test was used for the comparison between means of clinical and biochemical parameters. Several associations were tested using Pearson’s correlation co-efficient. The odds ratio with 95% confidence interval (CI) was calculated for all variables to determine their contribution to the variances in leptin levels. A probability level less than 5% was considered statistically significant.

Results

Data were obtained from 80 persons with type 2 diabetes (cases) and 80 persons without diabetes mellitus (controls). The clinical and biochemical parameters of the study population are shown in Table 1. Difference in means for age, BMI, % body fat, % muscle mass, and visceral fat, respectively between the two groups were not significant (p = 0.9119, 0.2666, 0.4008, 0.1735, 0.4810). Case subjects had higher systolic blood pressure (SBP), glucose, hsCRP and lower TCHOL, LDL and leptin levels, respectively (p = 0.0001, 0.0009, 0.0036; 0.0135, 0.0069, 0.0018) than their control counterparts. When categorized into severity in glucose levels, male diabetic persons with glucose levels > 11.0 mmol/L and between 6.2 and 11.0 mmol/L had higher leptin and hsCRP levels, respectively (p = 0.0465; p = 0.0203) compared to the other grouping (Table 1). Associations between several correlates with body composition parameters are shown in Table 2. There were negative correlation within the obese non-diabetic group for glucose vs % muscle mass (r = − 0.378, p = 0.016), leptin vs % muscle mass (r = − 0.555, p = 0.001) and within the obese diabetic group for leptin vs % muscle mass (r = − 0.602, p = 0.001). Positive associations were observed for glucose vs % body fat (r = 0.315, p = 0.048), % body fat vs leptin (r = 0.572, p = 0.001), BMI vs leptin (r = 0.444, p = 0.004) within the control group and leptin vs % body fat (r = 0.635, p = 0.001) within the case group. Risk assessment of leptin levels in this study are provided in Table 3. Obese persons with diabetes were about three times more likely to have lower leptin levels than their obese non-diabetic counterparts (Odds ratio = 3.315, CI = 1.918, 5.824; p < 0.001). Further, obese women, independent of other factors were about 10 times more likely to have higher leptin levels than obese men (Odds ratio = 9.750, CI = 4.461, 21.311; p < 0.001).
Table 1

Clinical and biochemical measurements of study participants

Variables

Obese subjects

p value

Diabetics (80)

Non-diabetics (80)

Age

48.60 ± 5.928

48.40 ± 7.877

0.9119

Sex (M/F)

30/50

30/50

 

Height (cm)

172.2 ± 9.996

168.6 ± 4.623

0.0734

Weight (kg)

98.55 ± 18.53

91.30 ± 8.952

0.0586

BMI (kg/m2)

34.08 ± 2.97

33.13 ± 2.361

0.2666

% Body fat

30.19 ± 7.319

31.47 ± 3.969

0.4008

% Muscle mass

32.72 ± 3.009

31.64 ± 3.062

0.1735

Visceral fat

16.00 ± 4.202

15.27 ± 3.796

0.4810

SBP (mmHg)

138.4 ± 9.027

126.9 ± 7.780

0.0001

DBP (mmHg)

85.87 ± 8.295

83.53 ± 6.684

0.2351

Glucose (mmol/L)

6.500 ± 2.956

4.947 ± 0.739

0.0009

TCHOL (mmol/L)

4.369 ± 0.898

5.059 ± 1.181

0.0135

TG (mmol/L)

1.515 ± 1.206

1.366 ± 0.745

0.5678

HDL (mmol/L)

1.019 ± 0.202

1.021 ± 0.275

0.9830

LDL (mmol/L)

2.724 ± 0.744

3.345 ± 0.959

0.0069

CR (ratio)

4.437 ± 1.259

5.158 ± 1.399

0.0402

Leptin (ng/ml)

13.84 ± 4.759

17.92 ± 5.506

0.0018

hsCRP (ng/ml)

0.256 ± 0.108

0.184 ± 0.106

0.0036

Variables

Glucose level among diabetic subjects

p value

3.6–6.19 mmol/L

6.2–11.0 mmol/L

> 11.0 mmol/L

Male

 Leptin

10.33 ± 4.08b

10.14 ± 1.88b

6.000 ± 0.71a

0.0465

 hsCRP

0.193 ± 0.09b

0.314 ± 0.12a

0.150 ± 0.02b

0.0203

Female

 Leptin

14.60 ± 3.19

15.95 ± 3.86

15.83 ± 2.021

0.3484

 hsCRP

0.301 ± 0.10

0.264 ± 0.13

0.202 ± 0.138

0.4913

Values are given as mean ± standard deviation

Categorized glucose grouping by one way ANOVA

Italic results indicate significant relationships

M male; F is female; SBP systolic blood pressure; DBP diastolic blood pressure; TCHOL total cholesterol; TG triglyceride; HDL high density lipoprotein; LDL low density lipoprotein; BMI body mass index; hsCRP high sensitivity C-reactive protein; CR coronary risk; % percentage

a, bDenotes differences between groups. p < 0.05 is statistically significant

Table 2

Association between biochemical indices and body composition parameters

Variables

Control group (obese non-diabetics (80)

Case group (obese diabetics (80)

BMI

Body fat

Muscle mass

Visceral fat

BMI

Body fat

Muscle mass

Visceral fat

Glucose

 r

0.258

0.315

 0.378

-0.091

0.077

0.104

− 0.080

0.145

 p

0.107

0.048

0.016

0.579

0.636

0.525

0.624

0.373

TCHOL

 r

− 0.004

− 0.138

0.195

0.300

0.078

0.004

0.022

− 0.077

 p

0.981

0.397

0.229

0.060

0.633

0.979

0.895

0.638

TG

 r

0.025

− 0.301

0.351

0.504

0.075

− 0.178

0.197

0.222

 p

0.878

0.059

0.026

0.001

0.644

0.271

0.224

0.169

HDL

 r

− 0.227

0.165

− 0.160

− 0.179

− 0.033

0.117

− 0.101

− 0.230

 p

0.159

0.310

0.325

0.357

0.841

0.473

0.535

0.153

LDL

 r

0.131

− 0.057

0.125

0.292

0.075

0.024

− 0.004

− 0.090

 p

0.421

0.727

0.443

0.067

0.645

0.884

0.978

0.579

VLDL

 r

0.029

− 0.303

0.355

0.515

0.076

− 0.184

0.204

0.222

 p

0.858

0.058

0.025

0.001

0.641

0.255

0.207

0.169

CR

 r

0.278

− 0.166

0.242

0.350

0.044

− 0.070

0.062

0.076

 p

0.082

0.306

0.133

0.027

0.786

0.668

0.705

0.639

Leptin

 r

0.444

0.572

 0.555

− 0.114

0.237

0.635

 0.602

− 0.144

 p

0.004

0.001

0.001

0.483

0.141

0.001

0.001

0.377

hsCRP

 r

0.033

0.211

− 0.158

− 0.005

0.172

0.113

− 0.035

0.125

 p

0.840

0.191

0.329

0.973

0.289

0.489

0.830

0.443

Table 2 shows the association between several correlates with body composition

Italic results indicate significant relationships

TCHOL total cholesterol; HDL high density lipoprotein; LDL low density lipoprotein; VLDL very low density lipoprotein; TG triglyceride; BMI body mass index; hsCRP high sensitivity C-reactive protein; CR coronary risk

Table 3

Risk assessment of serum leptin in study participants

Variable

OR

p-value

95% CI

aOR

p-value

95% CI

Diabetics

 Non-diabetics

3.315

< 0.0001

1.918–5.824

3.217

< 0.0001

1.008–6.045

Gender

 Male

      

 Female

9.750

< 0.0001

4.461–21.311

9.561

< 0.0001

4.060–24.200

Exercise

 Yes

      

 No

1.296

0.466

0.646–2.600

1.245

0.566

0.588–2.636

Viceral fats

 < 9.0

      

 > 9.0

0.163

0.090

0.020–1.330

0.223

0.176

0.025–1.962

Family history of DM

 No

      

 Yes

0.655

0.211

0.338–1.270

1.018

0.962

0.490–2.114

TCHOL

 3.5–6.5 mmol/L

     

 > 6.5 mmol/l

1.453

0.671

0.259–8.157

0.819

0.83

0.132–5.094

TG

 1.7–2.2 mmol/L

     

 > 2.2 mmol/l

0.711

0.737

0.098–5.163

1.041

0.97

0.128–6.477

HDL

 1.3–1.5 mmol/L

     

 > 1.5 mmol/l

1.835

0.476

0.346–3.739

1.764

0.532

0.298–4.434

LDL

 3.37–4.12 mmol/L

     

 > 4.12 mmol/l

0.685

0.428

0.269–1.746

0.418

0.099

0.148–1.179

Risk assessment for serum leptin levels within the study population

Italic results indicate significant relationships

CI confidence interval; OR odd ratio; aOR adjusted odd ratio; TCHOL total cholesterol; TG triglyceride; HDL high density lipoprotein; LDL low density lipoprotein

Discussion

Obesity is a major contributor to the burden of metabolic dysfunction and to several chronic diseases including type 2 diabetes [1]. In the southern parts of Ghana, especially in the Greater Accra region and its environs, the prevalence of obesity and type 2 diabetes have been reported to be increasing steadily [2, 16]. What is not clear is the contributory effects of gender, physical activity and diabetes mellitus on obesity. The present study evaluated the impact of serum leptin and hsCRP levels in obese Ghanaian subjects with and/or without type 2 diabetes. In this study, obese subjects with type 2 diabetes had lower serum leptin but higher hsCRP concentrations than obese non-diabetic individuals. Multivariate analysis further revealed that, obese persons with type 2 diabetes were three times less likely to have elevated leptin levels than obese controls. Further, obese diabetic men in this study, with poor glycemic control, had lower leptin levels. A possible explanation for reduced leptin levels in persons with type 2 diabetes may be due to insulin resistance, a modulator of leptin production. Thus defect in glucose sensing, as seen in type 2 diabetes could be responsible for the lower leptin production, suggesting a signalling crosstalk in glucose regulation. Altered body fat distribution in diabetic subjects have been suggested as an alternative explanation for lowered leptin levels [1720]. Even though this study did not observe differences in visceral fat among the two groups, leptin levels correlated positively with measures of adiposity and body composition in both groups indicating a possible synergistic effect. A third explanation could be due to the use of statin medications. Twelve (12) of our case subjects were on lipid lowering drugs and this could have contributed to such an observation. Result however were not statistically significantly when we excluded those on lipid lowering drugs from the analysis. Serum leptin levels in this study was also influenced by gender. Obese females were about 10 times more likely to have higher leptin levels than obese males. Stimulation of leptin mRNA production by 17β-estradiol in females could explain the above observation [21]. An inverse relationship has also been observed in a male cohort for leptin versus testosterone levels [22]. Levels of hsCRP among obese persons with type 2 diabetes in this study, was significantly higher than controls suggesting a possible directional relationship between insulin resistance and chronic inflammation. Whereas this study showed no variations in body composition, prior studies showed a strong association between hsCRP and measures of central obesity [23]. In summary, results highlight relationships of leptin and hsCRP with obesity and type 2 diabetes. We demonstrated that type 2 diabetes and gender were independent factors in determining serum leptin levels among obese subjects.

Limitations

This study had some limitations. Although the authors primarily focused on obese subjects, a normal weight control group would have been useful in a cross-sectional comparison manner. Another limitation was our inability to measure the insulin resistant state of our subjects. Further, the authors could not measure glycated hemoglobin (HbA1c), a marker that could have provided information on diabetes management. Future studies should focus on large population-based longitudinal studies to understand with change over time, the mechanistic role of adipocytokines in obesity and related disorders.

Abbreviations

BMI: 

body mass index

hs-CRP: 

high sensitivity C-reactive protein

OGTT: 

oral glucose tolerance test

SBP: 

systolic blood pressure

DBP: 

diastolic blood pressure

TG: 

triglyceride

TCHOL: 

total cholesterol

LDL: 

low density lipoprotein

HDL: 

high density lipoprotein

CR: 

coronary risk

HbA1c: 

glycated hemoglobin

OR: 

odds ratio

CI: 

confidence interval

Declarations

Authors’ contributions

YA participated in the recruitment and sampling of subjects. He also analyzed all the data. EKO made contributions to the draft and review of the manuscript. HAA and SDA supervised and reviewed the manuscript. GKA made intellectual contributions to the study. RN and EA participated in the analysis of blood samples. All authors read and approved the final manuscript.

Acknowledgements

The authors acknowledge the National Diabetes Management and Research Centre and the Public Health Reference Laboratory of the Ghana Health Service, both situated in Korle-Bu, Accra, for facility support in carrying out this research. We also acknowledge the School of Biomedical and Allied Health Sciences, University of Ghana for institutional support.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

Data will be provided by the authors upon request.

Consent for publication

Not applicable.

Ethical approval and consent to participate

This study (Protocol Identification Number: MS-Et/M.6–P3.2/2014-2015) was approved by the Institutional Ethics and Protocol Review Committee of School of Medicine and Dentistry, College of Health Sciences, University of Ghana. Written informed consent was obtained from all subjects prior to study participation.

Funding

The authors are grateful to the University of Ghana Postgraduate Scholarship Scheme for part-funding this study.

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Authors’ Affiliations

(1)
Department of Biomedical and Laboratory Sciences, University of Development Studies, Tamale, Ghana
(2)
Department of Physiology, University of Lausanne, Lausanne, Switzerland
(3)
Department of Chemical Pathology, School of Biomedical and Allied Health Sciences (S.B.A.H.S), University of Ghana, Accra, Ghana
(4)
Department of Biochemistry, S.B.A.H.S, Accra, Ghana
(5)
Department of Physiology, S.B.A.H.S, Accra, Ghana
(6)
Department of Nutrition and Dietetics, S.B.A.H.S, Accra, Ghana

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Copyright

© The Author(s) 2018

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