Molecular Insight into the Interaction between Epigenetics and Leptin in Metabolic Disorders.
Adam WróblewskiJustyna StrycharzEwa ŚwiderskaKarolina DrewniakJózef DrzewoskiJanusz SzemrajJacek KasznickiAgnieszka SliwinskaPublished in: Nutrients (2019)
Nowadays, it is well-known that the deregulation of epigenetic machinery is a common biological event leading to the development and progression of metabolic disorders. Moreover, the expression level and actions of leptin, a vast adipocytokine regulating energy metabolism, appear to be strongly associated with epigenetics. Therefore, the aim of this review was to summarize the current knowledge of the epigenetic regulation of leptin as well as the leptin-induced epigenetic modifications in metabolic disorders and associated phenomena. The collected data indicated that the deregulation of leptin expression and secretion that occurs during the course of metabolic diseases is underlain by a variation in the level of promoter methylation, the occurrence of histone modifications, along with miRNA interference. Furthermore, leptin was proven to epigenetically regulate several miRNAs and affect the activity of the histone deacetylases. These epigenetic modifications were observed in obesity, gestational diabetes, metabolic syndrome and concerned various molecular processes like glucose metabolism, insulin sensitivity, liver fibrosis, obesity-related carcinogenesis, adipogenesis or fetal/early postnatal programming. Moreover, the circulating miRNA profiles were associated with the plasma leptin level in metabolic syndrome, and miRNAs were found to be involved in hypothalamic leptin sensitivity. In summary, the evidence suggests that leptin is both a target and a mediator of epigenetic changes that develop in numerous tissues during metabolic disorders.
Keyphrases
- metabolic syndrome
- dna methylation
- gene expression
- insulin resistance
- poor prognosis
- liver fibrosis
- type diabetes
- healthcare
- genome wide
- risk assessment
- adipose tissue
- body mass index
- oxidative stress
- weight gain
- transcription factor
- physical activity
- cardiovascular disease
- machine learning
- single molecule
- pregnant women
- drug induced
- diabetic rats