Oxidative Stress Biomarkers in the Relationship between Type 2 Diabetes and Air Pollution.
Francesca GoriniLaura SabatinoMelania GagginiKyriazoula ChatzianagnostouCristina VassallePublished in: Antioxidants (Basel, Switzerland) (2021)
The incidence and prevalence of type 2 diabetes have increased in the last decades and are expected to further grow in the coming years. Chronic hyperglycemia triggers free radical generation and causes increased oxidative stress, affecting a number of molecular mechanisms and cellular pathways, including the generation of advanced glycation end products, proinflammatory and procoagulant effects, induction of apoptosis, vascular smooth-muscle cell proliferation, endothelial and mitochondrial dysfunction, reduction of nitric oxide release, and activation of protein kinase C. Among type 2 diabetes determinants, many data have documented the adverse effects of environmental factors (e.g., air pollutants) through multiple exposure-induced mechanisms (e.g., systemic inflammation and oxidative stress, hypercoagulability, and endothelial and immune responses). Therefore, here we discuss the role of air pollution in oxidative stress-related damage to glycemic metabolism homeostasis, with a particular focus on its impact on health. In this context, the improvement of new advanced tools (e.g., omic techniques and the study of epigenetic changes) may provide a substantial contribution, helping in the evaluation of the individual in his biological totality, and offer a comprehensive assessment of the molecular, clinical, environmental, and epidemiological aspects.
Keyphrases
- oxidative stress
- type diabetes
- diabetic rats
- air pollution
- smooth muscle
- glycemic control
- nitric oxide
- dna damage
- ischemia reperfusion injury
- cell proliferation
- induced apoptosis
- immune response
- cardiovascular disease
- risk factors
- healthcare
- protein kinase
- endothelial cells
- insulin resistance
- particulate matter
- heat shock
- gene expression
- endoplasmic reticulum stress
- cell cycle
- drug induced
- mental health
- cell death
- machine learning
- heavy metals
- big data
- electronic health record
- weight loss
- emergency department
- cystic fibrosis