Sleep disorders predict dementia risk years before diagnosis, study shows

New research reveals that sleep disorders can signal future risk of Alzheimer’s, Parkinson’s, and other dementias years before symptoms appear, offering hope for early intervention and prevention.

Study: Sleep disturbances as risk factors for neurodegeneration later in life. Image Credit: New Africa / ShutterstockStudy: Sleep disturbances as risk factors for neurodegeneration later in life. Image Credit: New Africa / Shutterstock

In a recent study published in the journal npj Dementia, researchers investigated the neurodegenerative impacts of clinically identified sleep disorders and related disturbances in later life. They mined biobank data of more than 1 million participants across Finland, Wales, and the United Kingdom (UK). Study findings revealed a significant association between these sleep disorders and several neurodegenerative diseases (NDDs), including dementia, Alzheimer's disease (AD), and Parkinson's disease (PD).

Notably, sleep disruptions were able to predict NDD risk as early as 5-15 years before disease diagnosis. For Alzheimer's Disease, this risk appeared largely independent of genetic predisposition, while for Parkinson's Disease, an interaction with genetic factors was observed. These findings highlight the long-term impacts of conditions like sleep apnea and other formally identified sleep disorders, underscoring the importance of sleep interventions in preserving late-life neurological health.

Background

Sleep is a nearly universal, fundamental biological process essential for optimal cognitive function and overall health. Several studies have established strong, bi-directional relationships between sleep and neurodegenerative diseases (NDDs), demonstrating that certain sleep disorders and significant sleep disturbances can trigger both short-term cognitive impairment and exacerbate long-term dementia risk.

Consequently, the World Health Organization (WHO) has emphasized the importance of sleep as a critical health behavior, advocating for research and interventions to address sleep disorders and enhance sleep quality across various human populations. Unfortunately, sleep disturbances are a common and growing global health concern, with reports estimating that 25% of all Europeans have insomnia.

Furthermore, despite research elucidating several genetic and environmental contributors to sleep disruptions, the mechanisms underpinning sleep's role in NDD etiology remain poorly understood. The extent to which specific, clinically recognized sleep disorders can predict NDD risk remains similarly inconclusive. Most studies investigating sleep-NDD associations have limited sample sizes, insufficient follow-up durations, and focus on one of a few NDDs, thereby complicating attempts to establish these outcomes.

About the study

The present study aims to further investigate the associations, and potential causal links, between sleep and NDDs by leveraging an extensive medical electronic health records (EHRs) database comprising more than 1 million individuals across Finland, Wales, and the United Kingdom (UK), analyzing EHR data from a 20-year period (1999-2018), drawing from broader records. Study data were obtained from the Secure Anonymised Information Linkage (SAIL) databank, the FinnGen datasets, and the UK Biobank (UKB).

Participants' NDD and sleep disorder diagnoses were classified using International Classification of Diseases 10th Revision (ICD-10) codes (e.g., G30 for Alzheimer's disease and G47.3 for sleep apnea), ensuring that the study focused on clinically documented conditions rather than self-reported symptoms. Cohort-specific medical histories were further used for statistical modeling and meta-analyses, including the computation of Cox proportional hazard ratios (HRs), polygenic risk scores (PRSs), and logistic regression models.

To isolate the behavioral impacts of sleep (exposure) on NDD, models were controlled for participants' genetic predisposition, age, sex, and other confounding variables. To facilitate the generalizability of results and improve the accuracy of outcomes, all analyses were replicated across multiple populations.

Study findings

Regression and HR analyses revealed strong relationships between ICD-10 coded sleep disorders and a spectrum of late-life NDDs. Circadian rhythm-associated sleep disorders (ICD10 code G47, which include conditions like insomnia, narcolepsy, sleep apnea, and parasomnias,) were demonstrated as substantial risk factors in the subsequent development of Alzheimer's disease (AD; HR = 1.15), Parkinson's disease (PD), dementia, and vascular dementia (HR = 1.41).

Non-organic sleep disorders (ICD10 code F51, such as nightmares and generalized insomnia not due to substances) were similarly associated with increased dementia (HR = 1.67), PD, and vascular dementia (HR = 2.05) risk. The study also found that the severity of certain sleep disorders, indicated by recurrent clinical diagnoses, tended to increase risk for some NDDs. While sleep apnea was demonstrated to be associated with amyotrophic lateral sclerosis (ALS), a lack of sufficient ALS data prevented the generalizability of these results.

Notably, many identified associations persisted even after adjusting for genetic risk factors. Specifically, for Alzheimer's Disease, the contributions of diagnosed sleep disorders to neurodegeneration risk appeared largely independent of genetic factors. However, for Parkinson's Disease, the study found evidence of an interaction between genetic risk and certain sleep disorders.

Individuals with a low genetic predisposition to NDDs still demonstrated high NDD HRs associated with these sleep conditions, suggesting that such disorders are significant risk factors, particularly impactful in those with lower genetic susceptibility.

All identified associations were observed to precede NDD diagnoses by between 5 and 15 years, suggesting sleep evaluations as an early indicator of future NDD risk. These findings highlight the potential of sleep interventions in mitigating late-life neurodegenerative disorders (NDDs), underscoring the importance of early detection and management of sleep disorders to enhance overall neurological well-being.

Conclusions

The present study utilizes the largest-scale sleep dataset to date to elucidate the relationships between clinically documented sleep disorders and late-life NDD risk. It analyzed EHR data from a 20-year period, drawing from broader records from more than 1 million participants, and found clear associations between such sleep disorders and late-life NDDs. These associations often persisted after adjusting for participants' genetic predispositions for conditions like Alzheimer's, though interactions with genetic risk were noted for Parkinson's Disease.

While utilizing a predominantly European cohort and exclusive EHR (as opposed to blood assays) data prevents the global generalizability of these findings, this study presents an ideal first step in non-invasively combating late-life neurodegeneration.

Notably, formally identified sleep disorders were found to be accurate and stable predictors of future neurodegeneration risk, suggesting the assessment of such disorders as both an early indicator of AD, PD, dementia, and vascular dementia, but also highlighting their treatment as a modifiable and treatable avenue to healthy neurological aging.

Journal reference:
Hugo Francisco de Souza

Written by

Hugo Francisco de Souza

Hugo Francisco de Souza is a scientific writer based in Bangalore, Karnataka, India. His academic passions lie in biogeography, evolutionary biology, and herpetology. He is currently pursuing his Ph.D. from the Centre for Ecological Sciences, Indian Institute of Science, where he studies the origins, dispersal, and speciation of wetland-associated snakes. Hugo has received, amongst others, the DST-INSPIRE fellowship for his doctoral research and the Gold Medal from Pondicherry University for academic excellence during his Masters. His research has been published in high-impact peer-reviewed journals, including PLOS Neglected Tropical Diseases and Systematic Biology. When not working or writing, Hugo can be found consuming copious amounts of anime and manga, composing and making music with his bass guitar, shredding trails on his MTB, playing video games (he prefers the term ‘gaming’), or tinkering with all things tech.

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