Comparative analysis of three human adipocyte size measurement methods and their relevance for cardiometabolic risk

Abstract

Objective: To determine whether adipocyte diameters from three measurement methods are similarly associated with adiposity measurements and cardiometabolic variables. Methods: Surgical samples of omental and abdominal subcutaneous adipose tissue were obtained in a sample of 60 women (age 35-59 years; body mass index 20.3-41.1 kg/m 2 ). Median adipocyte diameter of the main cell population was determined by collagenase digestion, osmium tetroxide fixation, and histological analysis. Adiposity and cardiometabolic risk factors were assessed. Results: Adipocyte diameter was consistently smaller with formalin fixation than with collagenase digestion, whereas osmium-fixed cells were larger (P < 0.0001, for all). Median adipocyte diameters derived from all methods were intercorrelated (r 5 0.46-0.83, P < 0.001 for all). Positive associations were found between adipocyte diameters from all techniques and regional or total adiposity measurements (P < 0.01 for all). Omental adipocyte diameter was positively associated with fasting glucose, insulin, and homeostatic model assessment of insulin resistance (r 5 0.30-0.52, P < 0.05 for all), with osmium-fixed cell size as a stronger correlate. Osmium-fixed cell diameter was also a better correlate of plasma adiponectin and leptin. Conclusions: Although measurement techniques generated systematic differences in adipocyte size, associations with adiposity were only slightly affected by the technique. Osmium fixation generated stronger associations with cardiometabolic risk factors than collagenase digestion and histological analysis.

The effect of the transition period and postpartum body weight loss on macrophage infiltrates in bovine subcutaneous adipose tissue

“…Measurement of adipocyte size or enumeration of ATM in relation to the number of adipocytes has been done in previous studies. However, adipocyte size can change with the processing of tissue into histologic sections, resulting in a questionable accuracy of those measurements (Laforest et al, 2017). Due to the inherent inconsistencies in adipocyte size due to fixation, we chose to enumerate the number of cells in an equivalent number of fields across all cases.…”

Machine Learning based histology phenotyping to investigate epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits

“…As previously reported, we find that whilst adipocyte area estimates vary substantially dependent on the method used for quantification, the correlation of adipocyte size and obesity is robust to these differences. 26 Our Adipocyte U-net required less than 6 minutes to predict adipocyte surface area across the ~10,000 images included in fatDIVA and MOBB. In comparison, Adiposoft took~3.5 hours.…”

Adipocyte size redux

“…Laforest et al (5), like researchers before them (1), found that the size of osmium-fixed adipocytes was larger (25%), most likely due to the swelling of the fixed lipid droplet (1). Does it matter that "actual" adipocyte size is likely overestimated after osmium fixation if it better predicts metabolic risk?…”

“…They found fairly good correlations among the three commonly used cell sizing methods (collagenase‐isolated cells, histological tissue sections, and electronic (Multisizer™) sizing of osmium‐fixed adipocytes) yet intriguingly report that the median adipocyte size measured by electronic counting of osmium‐fixed cells best correlated with measures of glucose homeostasis, lipid profiles, and circulating adipokine levels. Beyond the advantages/disadvantages of each method , these new findings bring up several issues that merit wider discussion.…”

“…Assessment of adipocyte size distribution, which is often bimodal, is a cited advantage of the high‐throughput electronic sizing of osmium‐fixed adipocytes . Although the smaller cells in the lower mode do not contribute substantially to the total volume of adipose tissue, the % small cells is important because it correlates with direct measures of insulin resistance . Although it is unclear why different numbers of these cells are detected by different sizing methods (see Figure 1 of Laforest et al ), it would be interesting to determine if the % small cells correlated among the methods and affected the prediction of metabolic risk.…”