ACBP/DBI as a possible prognostic marker for weight loss in patients undergoing bariatric surgery

Introduction Prevalence and incidence of obesity and related disorders are increasing worldwide [1]. Especially in patients with a body mass index (BMI)≥35 kg/m2 bariatric surgery, such as laparoscopic adjustable gastric banding (LAGB), remains a key therapeutic approach. Acyl-CoA binding protein, also termed diazepam-binding inhibitor (ACBP/DBI), regulates metabolism [2] and blockade of it has been recently shown to improve liver damage in different experimental models [3].

Material and Methods Paired liver biopsies and serum samples from 30 obese patients undergoing LAGB were collected at the timepoint of surgery and six months after surgery [4]. Expression of ACBP/DBI in liver tissue was measured via qPCR and serum ACBP/DBI concentrations were measured using ELISA. Expression and concentration values were correlated with clinical findings.

Results Bariatric surgery did induce weight loss in patients [4]. Serum levels of ACBP/DBI increased after weight loss induced by bariatric surgery. Serum ACBP/DBI levels at surgery correlated positively with the NAFLD activity score (NAS), a histopathological score including steatosis, lobular inflammation and hepatocyte ballooning. Surprisingly, expression of ACBP/DBI in liver tissue did not significantly change after bariatric surgery compared to before. Using the median weight loss of 20 kg patients were classified as responders (weight loss≥20 kg) and non-responders (weight loss<20 kg). Responders had significantly lower ACBP/DBI expression in liver tissue at the timepoint of surgery compared to the group of non-responders.

Conclusion ACBP/DBI expression in liver tissue could be used as a prognostic marker in patients undergoing bariatric surgery. Future studies are warranted to investigate if ACBP/DBI expression can be used as a prognostic marker to predict which patients profit the most from bariatric surgery.

Publikationsverlauf

Artikel online veröffentlicht:
13. Mai 2025

• References

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• 4 Moschen AR. et al. JHEP 2009; 51 (04) 765-77