Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 137-147
DOI: 10.26355/eurrev_202312_34698

AKR1C1 and hormone metabolism in lipedema pathogenesis: a computational biology approach

J. Kaftalli, G. Bonetti, G. Marceddu, K. Dhuli, P.E. Maltese, K. Donato, K.L. Herbst, S. Michelini, P. Chiurazzi, M. Hill, S. Michelini, S. Michelini, A. Bernini, M. Bertelli

MAGI EUREGIO, Bolzano, Italy. jurgen.kaftalli@assomagi.org


OBJECTIVE: Lipedema is an autosomal dominant genetic disease that mainly affects women. It is characterized by excess deposition of subcutaneous adipose tissue, pain, and anxiety. The genetic and environmental etiology of lipedema is still largely unknown. Although considered a rare disease, this pathology has been suggested to be underdiagnosed or misdiagnosed as obesity or lymphedema. Steroid hormones seem to be involved in the pathogenesis of lipedema. Indeed, aldo-keto reductase family 1 member C1 (AKR1C1), a gene coding for a protein involved in steroid hormones metabolism, was the first proposed to be correlated with lipedema.

PATIENTS AND METHODS: In this study, we employed a molecular dynamics approach to assess the pathogenicity of AKR1C1 genetic variants found in patients with lipedema. Moreover, we combined information theory and structural bioinformatics to identify AKR1C1 polymorphisms from the gnomAD database that could predispose to the development of lipedema.

RESULTS: Three genetic variants in AKR1C1 found in patients with lipedema were disruptive to the protein’s function. Furthermore, eight AKR1C1  variants found in the general population could predispose to the development of lipedema.

CONCLUSIONS: The results of this study provide evidence that AKR1C1 may be a key gene in lipedema pathogenesis, and that common polymorphisms could predispose to lipedema development.

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J. Kaftalli, G. Bonetti, G. Marceddu, K. Dhuli, P.E. Maltese, K. Donato, K.L. Herbst, S. Michelini, P. Chiurazzi, M. Hill, S. Michelini, S. Michelini, A. Bernini, M. Bertelli
AKR1C1 and hormone metabolism in lipedema pathogenesis: a computational biology approach

Eur Rev Med Pharmacol Sci
Year: 2023
Vol. 27 - N. 6 Suppl
Pages: 137-147
DOI: 10.26355/eurrev_202312_34698