The reality of life in modern times is that our internal circadian rhythms are often out of alignment with the light/dark cycle of the external environment. This is known as circadian disruption, and a wealth of epidemiological evidence shows that it is associated with an increased risk for cardiovascular disease. Cardiovascular disease remains the top cause of death in the United States, and kidney disease in particular is a tremendous public health burden that contributes to cardiovascular deaths. There is an urgent need for new treatments for kidney disease; circadian rhythm–based therapies may be of potential benefit. The goal of this Review is to summarize the existing data that demonstrate a connection between circadian rhythm disruption and renal impairment in humans. Specifically, we will focus on chronic kidney disease, lupus nephritis, hypertension, and aging. Importantly, the relationship between circadian dysfunction and pathophysiology is thought to be bidirectional. Here we discuss the gaps in our knowledge of the mechanisms underlying circadian dysfunction in diseases of the kidney. Finally, we provide a brief overview of potential circadian rhythm–based interventions that could provide benefit in renal disease.
Rajesh Mohandas, Lauren G. Douma, Yogesh Scindia, Michelle L. Gumz
Usage data is cumulative from June 2024 through June 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,828 | 1,351 |
247 | 132 | |
Figure | 253 | 9 |
Citation downloads | 96 | 0 |
Totals | 2,424 | 1,492 |
Total Views | 3,916 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.