Diabetologia

, Volume 58, Issue 11, pp 2647–2652

Ethnic differences in hepatic and systemic insulin sensitivity and their associated determinants in obese black and white South African women

  • Julia H. Goedecke
  • Dheshnie Keswell
  • Carsten Weinreich
  • Jia Fan
  • Jon Hauksson
  • Hendriena Victor
  • Kristina Utzschneider
  • Naomi S. Levitt
  • Estelle V. Lambert
  • Steven E. Kahn
  • Tommy Olsson
Short Communication

DOI: 10.1007/s00125-015-3720-7

Cite this article as:
Goedecke, J.H., Keswell, D., Weinreich, C. et al. Diabetologia (2015) 58: 2647. doi:10.1007/s00125-015-3720-7
  • 453 Downloads

Abstract

Aims/hypothesis

There is evidence to suggest that ectopic fat deposition in liver and skeletal muscle may differ between black and white women resulting in organ-specific differences in insulin sensitivity. Accordingly, the aim of the study was to examine ethnic differences in hepatic and peripheral insulin sensitivity, and the association with hepatic and skeletal muscle lipid content, and skeletal muscle gene expression.

Methods

In a cross-sectional study including 30 obese premenopausal black and white women, body composition (dual energy x-ray absorptiometry), liver fat and skeletal muscle (soleus and tibialis anterior) fat accumulation (proton-magnetic resonance spectroscopy), skeletal muscle gene expression, insulin sensitivity (two-step isotope labelled, hyperinsulinaemic–euglycaemic clamp with 10 mU m−2 min−1 and 40 mU m−2 min−1 insulin infusions), and serum adipokines were measured.

Results

We found that, although whole-body insulin sensitivity was not different, obese white women presented with lower hepatic insulin sensitivity than black women (% suppression of endogenous glucose production [% supp EGP], median [interquartile range (IQR)]: 17 [5–51] vs 56 [29–100] %, p = 0.002). While liver fat tended to be lower (p = 0.065) and skeletal muscle fat deposition tended to be higher (p = 0.074) in black compared with white women, associations with insulin sensitivity were only observed in black women (% supp EGP vs liver fat: r = −0.57, p < 0.05 and % supp EGP vs soleus fat: r = −0.56, p < 0.05).

Conclusions/interpretation

These findings may suggest that black women are more sensitive to the effects of ectopic lipid deposition than white women.

Keywords

Black African Ectopic fat Ethnicity Euglycaemic–hyperinsulinaemic clamp Hepatic insulin sensitivity Liver fat Peripheral insulin sensitivity Skeletal muscle lipid 

Abbreviations

% supp EGP

% Suppression of endogenous glucose production

DXA

Dual energy x-ray absorptiometry

EGP

Endogenous glucose production

EMCL

Extra-myocellular lipid

FFM

Fat-free mass

FMI

Fat mass index

hs-CRP

High sensitivity C-reactive protein

IFG

Impaired fasting glucose

IGT

Impaired glucose tolerance

IMCL

Intra-myocellular lipid

M/I

Glucose infusion adjusting for circulating insulin concentrations

MRS

1H-magnetic resonance spectroscopy

Rd

Rate of disposal

RER

Respiratory exchange ratio

SAT

Subcutaneous adipose tissue

SCD1

Stearoyl-CoA desaturase 1

SI

Insulin sensitivity

TA

Tibialis anterior

VAMP

Vesicle associated membrane protein

VAT

Visceral adipose tissue

Introduction

Type 2 diabetes and insulin resistance are more prevalent in populations of African origin than white populations [1, 2], but the main site of insulin resistance in obese black women is not known. Ectopic fat deposition in liver and skeletal muscle may differ by ethnicity [3, 4], resulting in organ-specific differences in insulin resistance. Whether this is related to tissue-specific alterations in insulin signalling among obese black women has, to our knowledge, not been studied.

Accordingly, in a sample of obese premenopausal black and white women, we sought to: (1) examine ethnic differences in hepatic and peripheral insulin sensitivity (SI); (2) measure differences in hepatic and skeletal muscle lipid content and their association with SI; and (3) measure the expression of genes involved in insulin signalling, fat oxidation and inflammation in skeletal muscle, and their ethnic-specific associations with SI.

Methods

Participant selection

This cross-sectional study included 30 obese premenopausal black and white women, matched for age (30–45 years) and BMI (≥30 kg/m2), with no known diseases, not pregnant or lactating, and who consumed <20 g alcohol/day. The study was undertaken in accordance with the guidelines of The Declaration of Helsinki and approved by the University of Cape Town Faculty of Health Sciences Human Research Ethics Committee. Participants gave written informed consent prior to participation.

Testing procedures

A questionnaire was administered to measure family history of type 2 diabetes, smoking, alcohol and dietary intake (food frequency) [5]. Physical activity was measured using actigraphy (ActiGraph LLC, Pensacola, FL, USA). Fat mass, fat-free mass (FFM), abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) areas were measured by dual energy x-ray absorptiometry (DXA, Discovery-W, software 12.7.3.7; Hologic, Bedford, MA, USA).

Fasting blood samples were drawn for metabolites, insulin and adipocytokines before a standard 75 g OGTT. On another day, a two-step euglycaemic (±5 mmol/l), hyperinsulinaemic clamp, with 6,6-[2H2]glucose isotope label was performed, with a 3 h low-dose insulin infusion (10 mU m−2 min−1), followed by a 2 h higher dose insulin infusion (40 mU m−2 min−1), with samples drawn and respiratory exchange ratio (RER) measured (Quark RMR, Cosmed, Rome, Italy) in the last 30 min of each period. Serum metabolites, insulin and adipocytokines were measured using standard techniques (Electronic Supplementary Material [ESM] Methods) and 6,6-[2H2]glucose was measured using Agilent 6890 gas chromatograph and analysed using ChemStation software (Agilent Technologies, Palo Alto, CA, USA).

Hepatic, and intra- (IMCL) and extra-myocellular lipid (EMCL), and total lipid content of the soleus and tibialis anterior (TA) muscles of the calf were measured by 1H-magnetic resonance spectroscopy (MRS) and MRI, respectively, using a 3 Tesla scanner (GE Healthcare, Global Diagnostic Imaging, Pewaukee, WI, USA).

A biopsy was taken from the vastus lateralis muscle from which RNA was extracted and the expression of genes (ESM Table 1) was measured using the Applied Biosystems 7900HT Fast Real-time PCR system using standard cycling conditions (Applied Biosystems, Foster City, CA, USA) and expressed relative to β2 microglobulin.

Statistics

Differences in participant characteristics were compared using χ2 analysis, one-way analysis of variance and/or covariance, adjusting for fat mass index (FMI), which takes into account differences in height and fat mass between groups. Bivariate associations were explored using Pearson’s correlation coefficients, which informed multiple regression analyses that included an interaction term (ethnicity × independent variable). Data were analysed using STATA version 11.1 (StataCorp, College Station, TX, USA).

Results

Participant characteristics

The obese white and black women were of similar age, BMI, FFM and VAT, but black women were shorter and had a greater % body fat and FMI (Table 1). The women performed similar daily physical activity and consumed similar amounts of dietary fat. More white than black women consumed alcohol and had a family history of diabetes (26.7 vs 6.7%, p = 0.087). Serum adiponectin was higher in white than black women, but high sensitivity C-reactive protein (hs-CRP) and other circulating inflammatory markers (data not shown) were not different.
Table 1

Participant characteristics

Variable

Obese white (n = 15)

Obese black (n = 15)

p value

p adjust FMI

Age (years)

36 ± 4

36 ± 5

0.978

 

Body composition

  BMI (kg/m2)

35.2 ± 3.5

37.9 ± 5.1

0.106

 

  FFM (kg)

52.4 ± 7.4

49.7 ± 6.7

0.297

 

  Fat mass (kg)

42.5 ± 6.1

47.1 ± 9.8

0.131

 

  Body fat (%)

44.8 ± 3.6

48.4 ± 3.4

0.008

 

  FMI (kg/m2)

15.4 ± 2.2

18.1 ± 3.6

0.017

 

  Waist (cm)

97.6 ± 7.5

101.8 ± 10.3

0.207

 

  VAT (cm2)

170 ± 40

179 ± 45

0.590

0.646

  SAT (cm2)

534 ± 89

596 ± 101

0.085

0.903

Circulating proteins

  Adiponectin (mg/l)

4.4 (3.2–5.9)

2.7 (2.0–3.8)

0.025

0.022

  hs-CRP (ng/ml)

4.4 ± 2.2

5.2 ± 2.8

0.425

0.983

Ectopic fat

  Liver fat (%)

3.6 (1.2–9.5)

1.5 (1.1–2.1)

0.077

0.065

  TA IMCL

148 (90–274)

119 (42–143)

0.070

0.206

  Sol IMCL

711 (507–1080)

925 (506–1600)

0.485

0.792

  TA fat content (%)

6.7 (5.5–9.1)

9.4 (7.1–14.2)

0.028

0.083

  Sol fat content (%)

10.8 (9.7–14.7)

15.5 (13.4–18.9)

0.003

0.074

Basal clamp

  Fasting glucose (mmol/l)

5.1 ± 0.2

5.1 ± 0.4

0.591

0.903

  Fasting insulin (pmol/l)

64.4 ± 5.4

90.7 ± 39.1

0.028

0.188

  EGP (mg min−1 [kg FFM]−1)

2.6 (2.0–3.8)

2.7 (1.8–2.9)

0.335

0.497

  Fasting RER

0.73 ± 0.04

0.77 ± 0.07

0.076

0.084

  Fasting RMR (kJ [kg FFM]−1 day−1)

134 (128–145)

132 (126–152)

0.702

0.767

Low-dose clamp

  Glucose-low (mmol/l)

4.6 ± 0.3

4.6 ± 0.3

0.671

0.716

  Insulin-low (pmol/l)

134.1 ± 42.6

158.4 ± 35.2

0.100

0.237

  EGP-low (mg min–1 [kg FFM]−1)

1.9 (1.6–2.7)

0.8 (0–1.8)

0.006

0.002

  Suppression of EGP (%)

17 (5–51)

56 (29–100)

0.006

0.002

   M-low (mg min−1 [kg FFM]−1)

0.75 (0.39–1.98)

1.19 (0.33–3.73)

0.757

0.187

   M/I-low (mg min−1 [kg FFM]−1 mmol/l−1)

0.31 (0.15–0.80)

0.39 (0.09–0.91)

0.871

0.320

  Rd-low (mg min−1 [kg FFM]−1)

3.0 (2.4–4.1)

2.5 (2.0–3.7)

0.178

0.418

  RER-low

0.75 ± 0.06

0.77 ± 0.06

0.317

0.218

  RMR-low (kJ [kg FFM]−1 day−1)

136 (129–142)

137 (129–145)

0.791

0.712

High-dose clamp

  Glucose-high (mmol/l)

4.4 ± 0.4

4.6 ± 0.3

0.300

0.376

  Insulin-high (pmol/l)

513.0 ± 88.5

589.0 ± 133.4

0.077

0.149

   M-high (mg min−1 [kg FFM]−1)

9.3 (5.7–12.2)

8.5 (4.8–12.2)

0.962

0.631

   M/I-high (mg min−1 [kg FFM]−1 mmol/l−1)

0.82 (0.70–1.36)

0.76 (0.58–0.93)

0.462

0.898

  RER-high

0.83 ± 0.06

0.85 ± 0.08

0.573

0.457

  RMR-high (kJ [kg FFM]−1 day−1)

139 (133–153)

137 (130–156)

0.964

0.731

For non-normally distributed data, values are median (IQR), with p values for log10-transformed data. For normally distributed data, values are means ± SD

EGP, calculated as the rate of appearance of glucose minus the glucose infusion rate; High-dose clamp, high-dose (40 mU m−2 min−1) insulin infusion; Low-dose clamp, low-dose (10 mU/m−2 min−1) insulin infusion; M, glucose infusion rate, which reflects whole-body insulin sensitivity; RMR, resting metabolic rate; Sol, soleus; Suppression of EGP, calculated as the % change in EGP between baseline and the low-dose insulin infusion

Liver fat tended to be higher in white than black women. Calf TA and soleus IMCL content were similar, but total soleus fat content was higher in black than white women. Skeletal muscle expression of genes involved in insulin signalling, glucose transport and fat oxidation did not differ between black and white women (ESM Table 1), nor did they correlate with any measure of skeletal muscle fat content.

Fasting glucose, insulin and NEFA concentrations did not differ by ethnicity. More white than black women had impaired fasting glucose (IFG; 26.7 vs 6.7 p = 0.142) and impaired glucose tolerance (IGT; 26.7 vs 0%, p = 0.031). While basal endogenous glucose production (EGP) was not different, white women had higher EGP and less EGP suppression than black women during the low-dose clamp. Only one white woman had incomplete suppression of EGP during the high-dose clamp. SI and RER during the low-dose and high-dose clamps were similar between white and black women.

Correlates of insulin sensitivity

In black women, body fat measures correlated negatively with hepatic and peripheral SI, whereas in white women, only VAT correlated with M/I-high (Table 2). In black women only, liver fat correlated negatively with suppression of EGP, soleus fat correlated negatively with glucose infusion adjusting for circulating insulin concentrations (M/I)-low, and skeletal muscle IRS1, vesicle associated membrane protein (VAMP) and stearoyl-CoA desaturase 1 (SCD1) expression correlated positively with rate of disposal (Rd)-low and M/I-high. In both black and white women, serum adiponectin correlated positively with peripheral SI.
Table 2

Correlates of hepatic and peripheral insulin sensitivity

Variable

% Suppression of EGP

Rd-low

M/I-low

M/I-high

White

Black

White

Black

White

Black

White

Black

Body composition

  Body fat (kg)

0.08

−0.64*

−0.09

−0.34

0.01

−0.64*

0.12

−0.60*

  Waist

0.09

−0.65**

−0.18

−0.73**

−0.25

−0.67**

−0.44

−0.73*

  VAT

−0.04

−0.52*

−0.20

−0.35

−0.34

−0.62*

−0.62*

−0.30

  SAT

0.19

−0.54*

−0.21

−0.26

0.13

−0.45

0.17

−0.50*

Ectopic fat

  Liver fat

0.28

−0.57*

−0.44

−0.41

−0.45

−0.34

−0.53

−0.21

  Soleus IMCL

0.59*

−0.46

−0.16

−0.52

0.12

−0.62*

−0.08

−0.46

  Soleus fat (%)

0.34

−0.56*

−0.04

−0.40

0.27

−0.66*

0.09

−0.33

Muscle gene expression

  IRS

−0.32

0.49

0.04

0.65*

−0.15

0.56*

−0.37

0.66*

  VAMP

−0.37

0.43

−0.07

0.68**

−0.18

0.52

−0.49

0.64*

  SCD1

−0.33

0.49

−0.03

0.90**

−0.23

0.53

−0.29

0.72**

Circulating adipokines

  Adiponectin

0.41

0.49

0.47

0.77**

0.64**

0.56*

0.75**

0.71**

Values are Pearson correlation coefficients

*p < 0.05, **p < 0.01

M/I-high, M/I corrected for circulating insulin levels during the high-dose (40 mU m−2 min−1) clamp; M/I-low, M/I corrected for circulating insulin levels during the low-dose clamp; Rd-low, Rd during the low-dose (10 mU m−2 min−1) clamp

Discussion

The major findings of our study were that obese white women had reduced hepatic SI compared with obese black women, whereas peripheral SI did not differ. Significant associations between ectopic fat accumulation and SI were observed in obese black, but not white women, suggesting that obese black women are more sensitive to the effects of ectopic lipid deposition than obese white women.

Until recently, studies demonstrating ethnic differences in SI between black and white women [1, 2] have only measured whole-body SI. DeLany et al [6] recently showed similar levels of hepatic SI, but lower peripheral SI in young (22–24 years) normal-weight black vs white women. In contrast, in older obese women, we found that peripheral SI did not differ, but white women had lower hepatic SI than black women. Studies in the USA have consistently reported higher liver fat of white compared with black women [7], which is supported in part by our study. However, liver fat was associated with reduced hepatic and whole-body SI in black, but not white women. This indication of increased sensitivity to ectopic lipid deposition confirms data in African-Americans showing that for a given level of liver fat, black women were more insulin resistant than white women [7].

Although there were no ethnic differences in IMCL or EMCL content, IMCL was associated with lower SI during the low-dose clamp in black, but not white women. Studies from the USA that have shown similar [4] or lower [8] IMCL levels in black than white women, but have demonstrated associations with SI in white women only [4, 8]. Differences between our study and others may relate to differences in methods used to measure SI, or to differences in the accumulation of lipid byproducts. Supporting the latter, we showed that in black women only, SI was associated with skeletal muscle SCD1 expression. SCD1 converts saturated fatty acids to monounsaturated fatty acids and increases triacylglycerol esterification, thereby attenuating the accumulation of lipid metabolites such as diacylglycerol and ceramide, which interfere with insulin signalling [9]. Despite no ethnic differences in the skeletal muscle expression of insulin signalling genes, we showed that IRS1 and VAMP expression were associated with increased SI in black, but not white women. IRS1 is integral to insulin signalling, while VAMP is involved in insulin-stimulated GLUT4 translocation, and is upregulated in hyperinsulinaemia [10].

We used the state-of-the-art measures of SI and ectopic fat deposition, which have not been performed previously in an obese black African population. NEFAs were not measured during the clamp, precluding measurement of adipose tissue SI; however, fasting and OGTT NEFA concentrations were not different between ethnicities (ESM Fig. 1). While the white women had a greater family history of type 2 diabetes and a higher prevalence of IFG and IGT, adjusting for these differences, or analysis of only women with normal glucose tolerance did not alter the main findings of this study. The paradox of higher hepatic SI but similar EGP in black compared with white SA women may be explained by lower hepatic insulin clearance in obese, insulin resistant black women [11]. Future studies that also include measures of C-peptide are required. Other limitations include self-reported alcohol intake and failure to control for the phase of the menstrual cycle, which may have confounded our results. Further, we only included obese women; therefore these results cannot be extrapolated to non-obese women, or to men.

In conclusion, we found that although whole-body SI was not different between obese black and white women, obese white women presented with lower hepatic SI compared with obese black women. Notably, ectopic fat accumulation was associated with reduced SI in black, but not white women. Future studies are required to gain an understanding of why black women are more sensitive to the effects of ectopic fat deposition than white women.

Acknowledgements

The authors wish to thank the research volunteers for their participation in this study. J. Bergman of Symington Radiology and E. Meintjes of the MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, Cape Town, South Africa are thanked for their assistance with the MRS scans. L. Bewerunge is thanked for performing the DXA scans. We would like to thank I. Söderström of Umeå University, Umeå, Sweden for performing the serum analyses, L. Mokwena of Stellenbosch University, Stellenbosch, South Africa for performing the GCMS analyses, and K. Yarasheski of Washington University School of Medicine, St Louis, MO, USA for assistance with GCMS analysis and interpretation.

Funding

This study was funded by the National Research Foundation of South Africa (Grant no. 73707), the United States Department of Veterans Affairs, the Swedish Research Council (K2011-12237-15-6), the Swedish Heart and Lung Foundation and Umeå University, Sweden.

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Contribution statement

JHG, CW, KU, SEK and TO contributed to the conception and design of the work; JHG, DK, CW, JF, JH, HV, KU, EVL and TO contributed to the acquisition and analysis of the data; JHG, DK, JH, KU, NSL, SEK and TO contributed to the interpretation of the data; JG, DK, and TO contributed to drafting the article; all authors revised the manuscript critically for important intellectual content and approved the final version to be published. JHG is the guarantor of this work.

Supplementary material

125_2015_3720_MOESM1_ESM.pdf (64 kb)
ESM Methods(PDF 64.1 kb)
125_2015_3720_MOESM2_ESM.pdf (51 kb)
ESM Fig. 1(PDF 51 kb)
125_2015_3720_MOESM3_ESM.pdf (64 kb)
ESM Table 1(PDF 64 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Julia H. Goedecke
    • 1
    • 2
  • Dheshnie Keswell
    • 2
  • Carsten Weinreich
    • 3
  • Jia Fan
    • 4
  • Jon Hauksson
    • 5
  • Hendriena Victor
    • 2
  • Kristina Utzschneider
    • 6
  • Naomi S. Levitt
    • 3
  • Estelle V. Lambert
    • 2
  • Steven E. Kahn
    • 6
  • Tommy Olsson
    • 7
    • 8
  1. 1.Non-Communicable Disease Research UnitSouth African Medical Research CouncilTygerbergSouth Africa
  2. 2.Division of Exercise Science and Sports Medicine, Department of Human BiologyUniversity of Cape TownCape TownSouth Africa
  3. 3.Division of Diabetes and Endocrinology, Department of MedicineUniversity of Cape TownCape TownSouth Africa
  4. 4.MRC/UCT Medical Imaging Research Unit, Department of Human BiologyUniversity of Cape TownCape TownSouth Africa
  5. 5.Center for Medical Technology and Radiation PhysicsUmeå University HospitalUmeåSweden
  6. 6.Division of Metabolism, Endocrinology and Nutrition, Department of MedicineVA Puget Sound Health Care System and University of WashingtonSeattleUSA
  7. 7.Department of Public Health and Clinical MedicineUmeå UniversityUmeåSweden
  8. 8.Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research CentreStellenbosch UniversityStellenboschSouth Africa