Microglial NF-κB Signaling Deficiency Protects Against Metabolic Disruptions Caused by Volatile Organic Compound via Modulating the Hypothalamic Transcriptome.
Lucas K DebarbaH S M JayarathneL StilgenbauerAna Luiza Romero Terra Dos SantosL KoshkoS ScofieldR SullivanA MandalUlrike KluehMarianna SadagurskiPublished in: bioRxiv : the preprint server for biology (2023)
Prolonged exposure to benzene, a prevalent volatile organic compound (VOC), at concentrations found in smoke, triggers hyperglycemia, and inflammation in mice. Corroborating this with existing epidemiological data, we show a strong correlation between environmental benzene exposure and metabolic impairments in humans. To uncover the underlying mechanisms, we employed a controlled exposure system and continuous glucose monitoring (CGM), revealing rapid blood glucose surges and disturbances in energy homeostasis in mice. These effects were attributed to alterations in the hypothalamic transcriptome, specifically impacting insulin and immune response genes, leading to hypothalamic insulin resistance and neuroinflammation. Moreover, benzene exposure activated microglial transcription characterized by heightened expression of IKKβ/NF-κB-related genes. Remarkably, selective removal of IKKβ in immune cells or adult microglia in mice alleviated benzene-induced hypothalamic gliosis, and protected against hyperglycemia. In summary, our study uncovers a crucial pathophysiological mechanism, establishing a clear link between airborne toxicant exposure and the onset of metabolic diseases.
Keyphrases
- lps induced
- high fat diet induced
- blood glucose
- insulin resistance
- immune response
- inflammatory response
- signaling pathway
- oxidative stress
- diabetic rats
- lipopolysaccharide induced
- genome wide
- type diabetes
- gene expression
- neuropathic pain
- glycemic control
- adipose tissue
- rna seq
- single cell
- particulate matter
- poor prognosis
- metabolic syndrome
- spinal cord injury
- transcription factor
- wild type
- pi k akt
- dendritic cells
- risk assessment
- cell proliferation
- high resolution
- machine learning
- quantum dots
- spinal cord
- young adults
- polycystic ovary syndrome
- human health