United States: A new study shows that people in their early middle age who don’t sleep well might have older-looking brains later in life. This research, published on October 23 in the journal Neurology, used MRI scans to look at brain health.
While the study doesn’t prove that bad sleep makes our brains age faster, it does suggest that there’s a link between poor sleep and signs of brain aging, according to lead researcher Clémence Cavaillès from the University of California, San Francisco.
As reported by the auntminnie, “In prior studies on sleep disturbances, poor thinking and memory later in life that raises one’s chances for dementia have been associated,” Cavaillès said. ‘Our study — for which the participants’ brain age was calculated with the help of an MRI — establishes that early weakening of sleep is associated with almost three years of premature brain aging even in middle-aged individuals.’
The investigators pointed out that sleep disturbances have been linked to adverse cognitive effects and increased rates of Alzheimer’s disease and Alzheimer’s disease-related dementias. However, for such research, young people have not been targeted although Alzheimer’s disease pathology starts in the brain several decades beyond the onset of clinical symptoms as pointed out by the authors.
In order to meet this gap of knowledge, Cavaillès’ group had to conduct a study that involved 589 individuals with a median age of 40. Research participants filled out sleep questionnaires at baseline and another at the five-year interval and given brain MRI scans 15 years into the project.
The investigators tracked six poor sleep characteristics, including the following:
- Short sleep duration
- Bad sleep quality
- Difficulty falling asleep
- Difficulty staying asleep
- Early morning awakening
- Daytime sleepiness
Study participants were slotted into three groups: A low group without more than one poor sleep characteristic; a middle group with two or three of the poor sleep characteristics; and a high group with more than 3 poor sleep characteristics. Thus, at the beginning of the work 70% of participants were in the ‘low’ group, 22 % participants in ‘middle’ group, and 8% participants in ‘high’ group.
Cavaillès and colleagues compared participants’ brain morphology with the scan of their age, and employed machine learning to predict the brain age of each participant.