Adipose markers of metabolic outcome after weight loss

Abstract

Adipose tissue is closely linked to metabolic disturbances in obesity. Bariatric surgery such as roux-en-Y gastric bypass (RYGB) remains the most effective treatment of obesity and obesity-related disease. More factors than fat mass per se determine the metabolic complications of obesity, including alterations in fat cell size, body fat distribution, adipose protein release, inflammation and lipolysis. The aim of this thesis was to further characterize the relationship between adipose tissue characteristics and metabolic parameters before and after weight loss, and to investigate if adipose phenotype can predict metabolic improvement after weight loss.

Study I. At any given fat mass, adipose tissue may constitute of many small fat cells (hyperplasia) or few but large fat cells (hypertrophy). This latter morphology is associated with worse metabolic profile. Study I examined if adipose morphology, i.e. hyperplasia or hypertrophy, could predict improved insulin sensitivity after weight loss. Abdominal subcutaneous adipose biopsies were performed before weight loss by diet or RYGB. Body fat mass was measured by dual-energy x-ray absorptiometry (DXA) or bioimpedance and insulin sensitivity assessed by homeostasis model assessment of insulin resistance (HOMA-IR). Results showed a higher improvement in HOMA-IR in patients with hypertrophy. Study II. The degree of improvement in metabolic profile and adipose tissue phenotype after weight loss is in relation to weight stable controls is not fully understood. In this study, women that had undergone RYGB were compared with a weight stable matched control group. Subjects that had undergone RYGB had lower HOMA-IR, better lipid profile and higher adiponectin levels and their adipose tissue was characterized by smaller fat cells, less visceral fat and lower secretion of tumor necrosis factor α (TNF-α) than controls. Study III. Herein, the CC chemokine ligand 18 (CCL18) was examined in adipose tissue. CCL18 was found to be released from adipose tissue in a time dependent manner. M2 macrophages were the primary source of CCL18. Serum- and adipose secreted levels of CCL18 correlated with metabolic risk factors in women. We could not demonstrate effects of CCL18 on adipocyte expression of inflammatory or extracellular matrix proteins in vitro. Study IV. The aim of this study was to investigate if body fat mass distribution measured by DXA or simple anthropometric measures could predict improved metabolic profile or weight loss after RYGB. Android/gynoid fat mass ratio and waist-to hip ratio could predict improved HOMA-IR, and BMI and body fat percentage could predict weight loss. DXA measures and simple anthropometric measures performed equally well, indicating a limited value for DXA to predict metabolic outcome after RYGB.

Conclusions: Adipose tissue morphology and body fat distribution can predict improved insulin sensitivity following weight loss. Metabolic and adipose phenotype improves beyond the control state after RYGB. CCL18 is released from M2 macrophages in adipose tissue, and adipose released and circulating levels correlate with metabolic risk markers in women.