Machine learning analyses reveal circadian clock features predictive of anxiety among UK biobank participants
Abstract Mood disorders, including depression and anxiety, affect almost one-fifth of the world’s adult population and are becoming increasingly prevalent. Mutations in circadian clock genes have previously been associated with mood disorders both directly and indirectly through alterations in circa...
Main Authors: | Cole Ventresca, Wael Mohamed, William A. Russel, Ahmet Ay, Krista K. Ingram |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-12-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-49644-7 |
Similar Items
-
Machine learning and expression analyses reveal circadian clock features predictive of anxiety
by: Aziz Zafar, et al.
Published: (2022-04-01) -
Risk for Seasonal Affective Disorder (SAD) Linked to Circadian Clock Gene Variants
by: Thanh Dang, et al.
Published: (2023-12-01) -
Diurnal Preference Predicts Phase Differences in Expression of Human Peripheral Circadian Clock Genes
by: Andrew Ferrante, et al.
Published: (2015-06-01) -
Machine Learning Analyses Reveal Circadian Features Predictive of Risk for Sleep Disturbance
by: Overton R, et al.
Published: (2022-10-01) -
Association between circadian physical activity patterns and mortality in the UK Biobank
by: Michael J. Stein, et al.
Published: (2023-09-01)