Obesity-induced hypoadiponectinaemia: the opposite influences of central and peripheral fat compartments

Abstract

Background and aims: The substantial reduction in adiponectin concentration among obese individuals seems to depend on fat distribution and is a marker of metabolic and adipose tissue dysfunction. We aimed to: (i) address whether abdominal fat from different compartments (visceral, deep subcutaneous abdominal and superficial subcutaneous abdominal) and gluteofemoral fat are independently associated with blood adiponectin concentration; and (ii) investigate whether abdominal (proxied by waist circumference) and gluteofemoral fat (proxied by hip circumference) accumulation causally determine blood adiponectin concentration.

Methods: To investigate the independent association of abdominal and gluteofemoral fat with adiponectin concentration, we used multivariable regression and data from 30-year-old adults from the 1982 Pelotas Birth Cohort (n = 2,743). To assess the causal role of abdominal and gluteofemoral fat accumulation on adiponectin concentration, we used Mendelian randomization and data from two consortia of genome-wide association studies-the GIANT (n > 210 000) and ADIPOGen consortia (n = 29 347).

Results: In the multivariable regression analysis, all abdominal fat depots were negatively associated with adiponectin concentration, specially visceral abdominal fat [men: β = -0.24 standard unit of log adiponectin per standard unit increase in abdominal fat; 95% confidence interval (CI) = -0.31, -0.18; P = 8*10-13; women: β = -0.31; 95% CI = -0.36, -0.25; P = 7*10-27), whereas gluteofemoral fat was positively associated with adiponectin concentration (men: β = 0.13 standard unit of log adiponectin per standard unit increase in gluteofemoral fat; 95% CI = 0.03, 0.22; P = 0.008; women: β = 0.24; 95% CI = 0.17, 0.31; P = 7*10-11). In the Mendelian randomization analysis, genetically-predicted waist circumference was inversely related to blood adiponectin concentration (β = -0.27 standard unit of log adiponectin per standard unit increase in waist circumference; 95% CI = -0.36, -0.19; P = 2*10-11), whereas genetically-predicted hip circumference was positively associated with blood adiponectin concentration (β = 0.17 standard unit of log adiponectin per standard unit increase in hip circumference; 95% CI = 0.11, 0.24; P = 1*10-7).

Conclusions: These results support the hypotheses that there is a complex interplay between body fat distribution and circulating adiponectin concentration, and that whereas obesity-induced hypoadiponectinaemia seems to be primarily attributed to abdominal fat accumulation, gluteofemoral fat accumulation is likely to exert a protective effect.

Keywords: Adiponectin; Mendelian randomization; abdominal fat; adipokines; adiposity; body fat distribution; subcutaneous fat.

Figure 1

Mean difference (95% CI) in standardized log adiponectin concentration per unit increase in standardized fat depots for males (A) and females (B). Unadjusted models estimates are represented by grey dots and adjusted models by black squares. Adjusted models included genomic ancestry, smoking status, alcohol intake and other fat depots. SD, standard deviation. Data from the 2012 follow-up of the 1982 Pelotas Birth Cohort.

Figure 2

Dose-response relation between fat depots and adiponectin concentration in males. (A) Visceral fat (P for nonlinear trend = 0.003); (B) deep subcutaneous abdominal fat (P for nonlinear trend = 0.121); (C) superficial subcutaneous abdominal fat (P for nonlinear trend = 5*10⁻⁶); (D) gluteofemoral fat (P for nonlinear trend = 3*10⁻⁴). SD, standard deviation. Data from the 2012 follow-up of the 1982 Pelotas Birth Cohort.

Figure 3

Dose-response relation between fat depots and adiponectin concentration in females. (A) Visceral fat (P for nonlinear trend = 0.006); (B) deep subcutaneous abdominal fat (P for nonlinear trend = 0.105); (C) superficial subcutaneous abdominal fat (P for nonlinear trend = 0.058); (D) gluteofemoral fat (P for nonlinear trend = 0.037). SD, standard deviation. Data from the 2012 follow-up of the 1982 Pelotas Birth Cohort.

Figure 4

Causal diagram representing assumed causal relationships in the Mendelian randomization analysis. The solid lines represent the relationships being tested (i.e. effect of WC or HipC on adiponectin concentration using genetic instruments). WC, waist circumference; HipC, hip circumference; SNP, single nucleotide polymorphisms.

Figure 5

Main (A) and sensitivity (B) Mendelian randomization analyses of the mean difference (95% CI) in standardized log adiponectin concentration per unit increase in standardized waist (grey dots) or hip circumference (black squares). Data from GIANT (n = up to 210 088 individuals) and ADIPOGen (n = 29 347 individuals) consortia. Adjusted IVW model: IVW method adjusted for hip circumference (in waist circumference model) or waist circumference (in hip circumference model). Waist and hip circumference were adjusted by body mass index before analysis. IVW method, inverse variance method; MR, Mendelian randomization.

Figure 6

Mean difference in standardized log adiponectin concentration according to genetically increased standardized waist (A) or hip (B) circumference. Data from GIANT (n = up to 210 088 individuals) and ADIPOGen (n = 29 347 individuals) consortia. Each data point represents betas for SNP-adiponectin (Y axis) and SNP-waist or hip circumference (X axis) association. Predicted values for the main analyses are represented by the full black line (unadjusted IVW method) and full grey line (adjusted IVW method). Predicted values for the sensitivity analyses are represented by the dashed black line (weighted median estimator) and dashed grey line (MR-Egger method). IVW method, inverse-variance weighted method; MR-Egger method, Mendelian randomization-Egger method.