Illustration of circadian rhythm dysregulation in insomnia. On the alarm clock display, the open eye at dawn (AM) and the closed eye in the afternoon (PM) illustrate the disruption of the biological clock. This regulation depends on the clock genes analysed in the study. Illustration: Rita Félix

A research team led by the Center for Neuroscience and Cell Biology at the University of Coimbra (CNC-UC) and the Centre for Innovative Biomedicine and Biotechnology (CiBB), in collaboration with the University of Aveiro, has identified, using a bioinformatics model, changes in the expression of so-called clock genes that are associated with a diagnosis of chronic insomnia.

This is the first time that the relationship between these genes and chronic insomnia has been studied. The study may contribute to a more accurate diagnosis of the disorder and to understanding how clock genes could function as new biomarkers of the disease. Currently, because there are no biological markers, insomnia has an ambiguous diagnosis and is difficult to treat.

Insomnia is the most prevalent sleep disorder worldwide. In Portugal, it is estimated that around 10% of the population may suffer from chronic insomnia. Insomnia is considered chronic when there is difficulty maintaining sleep for more than three nights a week, for three or more consecutive months.

The changes identified in the study were observed in at least three clock genes, which regulate the circadian rhythm, or biological clock — the body’s internal system that regulates sleep, temperature and hormones throughout the day in accordance with sunlight.

The study also associates changes in the expression of these genes with dysregulation of cortisol and melatonin levels and body temperature, biological markers that are naturally affected in people with sleep disorders.

“Understanding the profile of clock genes in people with insomnia, and that this profile may serve as a biomarker for diagnosing insomnia more objectively, was one of the major advances achieved through this study”, explains Ana Rita Álvaro, the study’s lead researcher and coordinator of the Sleep and Biological Rhythms in Ageing and Age-Related Diseases research subgroup at CNC-UC.

The team of the Sleep and Biological Rhythms in Ageing and Age-Related Diseases research subgroup at CNC-UC: Rodrigo Ribeiro, Laetitia Gaspar, João Alves, Bárbara Santos, Catarina Carvalhas-Almeida, Joaquim Moita, Cláudia Cavadas e Ana Rita Álvaro (lead researcher)

The scientists also found significant changes in the activity of clock genes in people with short sleep duration, the most severe subtype (when a person sleeps for less than six hours). These individuals also had higher body temperatures at night (which makes it more difficult to initiate sleep) and higher cortisol levels at night, both signs of biological clock dysregulation.

“We confirmed that the more severe the insomnia in these patients, the more altered the circadian rhythm signals measured by actigraphy — an activity measurement performed using a wristband-like device that records activity and temperature”, the researcher highlights.

Pioneeringly, the use of artificial intelligence through machine learning not only made it possible to distinguish people with insomnia from healthy individuals, with 92% accuracy, but also to identify the insomnia subtypes present in each study participant (short sleep duration and normal sleep duration). The study analyzed patients with chronic insomnia, including those with short sleep duration, and compared them with healthy individuals.

“This study combines approaches that have already been explored separately in other sleep disorders, such as analyzing ‘clock gene’ expression in patients with sleep apnea, but now applies them, innovatively, to chronic insomnia, particularly to distinguishing between its subtypes”, explains Ana Rita Álvaro.

The study also involved the Sleep Medicine Centre of the Coimbra Local Health Unit and the University of Pennsylvania (United States).

The scientific article Clock gene signature predicts insomnia and links to sleep/circadian parameters, published in the journal Translational Psychiatry, is available here.

Inês Amado da Silva with Catarina Ribeiro (UC)