The Role of Diagnostic Biomarkers, Omics Strategies, and Single-Cell Sequencing for Nonalcoholic Fatty Liver Disease in Severely Obese Patients.
Charlotte W WernbergKim RavnskjaerMette Munk Enok LauridsenMaja Sofie ThielePublished in: Journal of clinical medicine (2021)
Liver disease due to metabolic dysfunction constitute a worldwide growing health issue. Severe obesity is a particularly strong risk factor for non-alcoholic fatty liver disease, which affects up to 93% of these patients. Current diagnostic markers focus on the detection of advanced fibrosis as the major predictor of liver-related morbidity and mortality. The most accurate diagnostic tools use elastography to measure liver stiffness, with diagnostic accuracies similar in normal-weight and severely obese patients. The effectiveness of elastography tools are however hampered by limitations to equipment and measurement quality in patients with very large abdominal circumference and subcutaneous fat. Blood-based biomarkers are therefore attractive, but those available to date have only moderate diagnostic accuracy. Ongoing technological advances in omics technologies such as genomics, transcriptomics, and proteomics hold great promise for discovery of biomarkers and increased pathophysiological understanding of non-alcoholic liver disease and steatohepatitis. Very recent developments have allowed for single-cell sequencing and cell-type resolution of gene expression and function. In the near future, we will therefore likely see a multitude of breakthrough biomarkers, developed from a deepened understanding of the biological function of individual cell types in the healthy and injured liver.
Keyphrases
- single cell
- obese patients
- rna seq
- bariatric surgery
- high throughput
- liver fibrosis
- weight loss
- gene expression
- gastric bypass
- roux en y gastric bypass
- end stage renal disease
- randomized controlled trial
- body mass index
- type diabetes
- healthcare
- adipose tissue
- peritoneal dialysis
- dna methylation
- small molecule
- ejection fraction
- mass spectrometry
- public health
- metabolic syndrome
- stem cells
- weight gain
- mental health
- insulin resistance
- chronic kidney disease
- prognostic factors
- oxidative stress
- newly diagnosed
- physical activity
- big data
- artificial intelligence
- mesenchymal stem cells
- liver injury
- bone marrow
- health information
- machine learning
- early onset
- fatty acid
- deep learning
- social media
- body weight
- climate change