Metaproteomics Approach and Pathway Modulation in Obesity and Diabetes: A Narrative Review.
Francesco Maria CalabreseAnnalisa PorrelliMirco VaccaBlandine ComteKatharina NimptschMariona PinartTobias PischonEstelle Pujos-GuillotMaria De AngelisPublished in: Nutrients (2021)
Low-grade inflammatory diseases revealed metabolic perturbations that have been linked to various phenotypes, including gut microbiota dysbiosis. In the last decade, metaproteomics has been used to investigate protein composition profiles at specific steps and in specific healthy/pathologic conditions. We applied a rigorous protocol that relied on PRISMA guidelines and filtering criteria to obtain an exhaustive study selection that finally resulted in a group of 10 studies, based on metaproteomics and that aim at investigating obesity and diabetes. This batch of studies was used to discuss specific microbial and human metaproteome alterations and metabolic patterns in subjects affected by diabetes (T1D and T2D) and obesity. We provided the main up- and down-regulated protein patterns in the inspected pathologies. Despite the available results, the evident paucity of metaproteomic data is to be considered as a limiting factor in drawing objective considerations. To date, ad hoc prepared metaproteomic databases collecting pathologic data and related metadata, together with standardized analysis protocols, are required to increase our knowledge on these widespread pathologies.
Keyphrases
- type diabetes
- low grade
- insulin resistance
- weight loss
- metabolic syndrome
- glycemic control
- cardiovascular disease
- high fat diet induced
- weight gain
- big data
- high grade
- neoadjuvant chemotherapy
- healthcare
- endothelial cells
- electronic health record
- randomized controlled trial
- oxidative stress
- binding protein
- protein protein
- adipose tissue
- case control
- skeletal muscle
- locally advanced
- microbial community
- single cell
- induced pluripotent stem cells
- systematic review
- small molecule
- data analysis
- transcription factor
- clinical practice
- radiation therapy
- artificial intelligence