Identification of a Fatty Acid for Diagnosing Non-Alcoholic Steatohepatitis in Patients with Severe Obesity Undergoing Metabolic Surgery.
Naoto TakahashiAkira SasakiAkira UmemuraTamotsu SugaiKeisuke KakisakaYasushi IshigakiPublished in: Biomedicines (2022)
The prevalence of nonalcoholic steatohepatitis (NASH) in severely obese Japanese patients is extremely high. However, there are currently no methods other than liver biopsy to assess hepatic steatosis and fibrosis. The purpose of this study was to comprehensively analyze changes in fatty acid (FA) and serum-free fatty acid (FFA) metabolism in severely obese Japanese patients to determine whether these could be surrogate markers. In this study, we enrolled 20 Japanese patients who underwent laparoscopic sleeve gastrectomy (LSG) for severe obesity and intraoperative liver biopsy. Serum FFAs were analyzed with liquid chromatography-mass spectrometry, and FAs in liver tissue were assessed using matrix-assisted laser desorption/ionization-imaging mass spectrometry to determine FAs that may be indicative of a positive NASH diagnosis. All patients showed significant weight loss and metabolic improvement following LSG. Regarding weight loss and metabolic improvement indices, 23 FFAs showed significant correlations with the baseline data. Narrowing down the phospholipids to commonly detected FAs detected in liver tissue, PC(18:1e_20:4) was significantly changed in the NASH group, suggesting that it could be used as a surrogate marker for NASH diagnosis. The results suggest that specific postoperative changes in blood phospholipids could be used as surrogate markers for NASH treatment.
Keyphrases
- weight loss
- fatty acid
- mass spectrometry
- liquid chromatography
- bariatric surgery
- roux en y gastric bypass
- metabolic syndrome
- gastric bypass
- high resolution
- end stage renal disease
- insulin resistance
- adipose tissue
- chronic kidney disease
- high resolution mass spectrometry
- minimally invasive
- glycemic control
- high performance liquid chromatography
- prognostic factors
- patients undergoing
- weight gain
- ejection fraction
- early onset
- tandem mass spectrometry
- risk factors
- acute coronary syndrome
- obese patients
- machine learning
- coronary artery bypass
- body mass index
- smoking cessation
- coronary artery disease
- liver fibrosis
- data analysis
- deep learning
- replacement therapy