Use of <i>UCHL1</i> gene expression to estimate adipocyte size

<p dir="ltr">Adipocyte size is linked to insulin resistance and the risk of developing type 2 diabetes. We aimed to generate a surrogate method to estimate adipocyte size by measuring adipose tissue gene expression using quantitative real-time polymerase-chain reaction (qRT-PCR) which could be used alongside systemic measures of insulin sensitivity to predict type 2 diabetes risk. We examined the relationship of 40591 genes with abdominal subcutaneous adipocyte size in 132 adults and validated the findings in additional cohorts with available transcriptomic and adipocyte size data. qRT-PCR analysis of gene expression in abdominal adipose tissue biopsies was used to develop a standardized adipocyte size estimate. This estimate was compared alongside systemic and adipose insulin sensitivity measures, including adipocyte lipogenesis, hyperinsulinemic euglycemic clamp, adipose insulin resistance and homeostasis model assessment. Transcriptome wide analyses found UCHL1 gene expression as strongly correlating with adipocyte size, independent of other genes and additional co-factors, such as insulin resistance (beta-coefficient=0.32; p=0.002). Using qRT-PCR, UCHL1 expression accurately estimated adipocyte size across a wide range of adipocyte volumes with high precision (ROC analysis area under the curve = 0.94) and showed strong correlations with all insulin sensitivity measures (adjusted r2 0.2-0.6; p<0.0001). We scaled the measurement of UCHL1 expression to 25 mg adipose biopsies and provide a standard operating procedure for routinely estimating adipocyte size. In summary, we provide a simple, accurate and accessible surrogate measure to estimate an individual’s adipocyte size, which may be useful in clinical insulin resistance studies.</p>