Back to Search
Start Over
Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort
- Source :
- Biomolecules, Vol 10, Iss 7, p 1049 (2020)
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- The development of high throughput assays for assessing lipid metabolism in metabolic disorders, especially in diabetes research, nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH), provides a reliable tool for identifying and characterizing potential biomarkers in human plasma for early diagnosis or prognosis of the disease and/or responses to a specific treatment. Predicting the outcome of weight loss or weight management programs is a challenging yet important aspect of such a program’s success. The characterization of potential biomarkers of metabolic disorders, such as lysophospholipids and bile acids, in large human clinical cohorts could provide a useful tool for successful predictions. In this study, we validated an LC-MS method combining the targeted and untargeted detection of these lipid species. Its potential for biomarker discovery was demonstrated in a well-characterized overweight/obese cohort subjected to a low-caloric diet intervention, followed by a weight maintenance phase. Relevant markers predicting successful responses to the low-caloric diet intervention for both weight loss and glycemic control improvements were identified. The response to a controlled weight loss intervention could be best predicted using the baseline concentration of three lysophospholipids (PC(22:4/0:0), PE(17:1/0:0), and PC(22:5/0:0)). Insulin resistance on the other hand could be best predicted using clinical parameters and levels of circulating lysophospholipids and bile acids. Our approach provides a robust tool not only for research purposes, but also for clinical practice, as well as designing new clinical interventions or assessing responses to specific treatment. Considering this, it presents a step toward personalized medicine.
Details
- Language :
- English
- ISSN :
- 2218273X
- Volume :
- 10
- Issue :
- 7
- Database :
- Directory of Open Access Journals
- Journal :
- Biomolecules
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5fe7f7bf8e824a0dae70d1cf69cc2110
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/biom10071049