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Obesity Reviews· 2026Q1· Review

Investigating Overweight and Obesity Risk in Shift Workers Using Omics Technologies

Katrin Scionti, Ivana Vaclavkova, Vanessa Schoissengeier, Karl‐Heinz Wagner

Short summary

Omics technologies reveal specific molecular pathways, including clock genes, hormones, and microorganisms, implicated in the increased obesity risk faced by night shift workers due to circadian rhythm disruption.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Circadian rhythm disruption in night shift workers causes metabolic alterations linked to overweight and obesity.
  • Omics technologies (transcriptomics, proteomics, metabolomics, metagenomics) identify molecular pathways involved.
  • Key molecules implicated include clock genes, hormones, and microorganisms.
  • Human field studies using omics are needed to understand obesity risk in shift workers.

AI-generated from the title and abstract; the full text is not read.

Abstract

Night shift workers are at higher risk of developing overweight and obesity. The disruption of the physiological circadian rhythm leads to metabolic alterations, such as decreased insulin sensitivity, increased adipogenesis, and inflammation, with effects on their health and leading, among other diseases, to obesity. Omics technologies represent novel investigation tools to understand in depth the biological mechanisms behind the circadian disruption and consequent effects on metabolism. The data obtained from the use of omics technologies in the field of transcriptomics, proteomics, metabolomics, and metagenomics reveal the involvement of molecular pathways in the circadian disruption due to shift work and give comprehensive insights into the most crucial molecules, such as clock genes, hormones, or microorganisms responsible for a downstream cascade effect. There is a clear need to further explore obesity risk in night shift workers through omics-based studies, particularly in human field studies. Many of the investigations so far have focused on animal models with simulated circadian disruption. Upcoming omics data can undoubtedly support the advancement toward a personalized approach that could protect the health of night shift workers. This review focuses on studies supported by omics technologies on circadian disruption and metabolic alterations leading to obesity or increasing its risk.

The authors' abstract, as published at the source. Obesity Reviews, 2026 · DOI ↗

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Field: Endocrine and Autonomic Systems

Endocrine and Autonomic SystemsNeuroscience