Introduction Poor sleep¹ as well as white matter hyperintensities (WMH), which are macroscale markers of cerebrovascular health indicating white matter lesion,² have been shown to increase the risk of dementia. However, the relationship between these two putative risk factors of dementia is unclear.

Method Here we use data from the UK Biobank (N=5505, aged from 45 to 73) to elucidate the effect of poor sleep (insomnia, snoring, daytime sleepiness and short sleep duration) on WMH load. The sleep variables were obtained using a digital questionnaire, whereas the WMH load was derived from automated segmentation of T2 FLAIR magnetic resonance images using the BIANCA tool in FSL.

Results We show that age, snoring and daytime sleepiness significantly predict a higher WMH load (linear model, adjusted R²=0.13, p<0.0001). The WMH load of patients with potential sleep issues is significantly larger than those who reported no sleep issue (figure 1). Markers of poor sleep are associated with a higher body mass index (BMI) (linear model, adjusted R²=0.041, p<0.0001). A small but significant relationship exists between age, BMI and WMH (linear model, adjusted R²=0.14, p<0.0001).

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Abstract P038 Figure 1

Self-reported variables of poor sleep are linked to a higher white matter hyperintensity (WMH) load. Patients with complaints (score of 1) about insomnia, daytime sleepiness, snoring and short sleep duration (less than 7 hours per night) had a higher WMH load index than those that did not report any complaint (score of 0). T-tests were used to compare all 4 sets of data. The WMH load index is log-transformed.

Finally, a sleep burden score summing poor sleep markers significantly predicted the WMH load, when controlling for cardiovascular factors (table 1). Removing the sleep burden score leads to a significant decrease in the power of the model (ANOVA, p=0.027).

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Abstract P038 Table 1

The sleep burden score, corresponding to the presence of insomnia, snoring, daytime sleepiness and short sleep duration, significantly predicts white matter hyperintensity (WMH) load. A multiple linear regression was performed, controlling for age, body mass index (BMI), blood pressure (diastolic and systolic), waste-hip ratio (whr), the genetic status of alipoproteinE (APOE), health conditions including diabetes, high cholesterol, hypertension and high blood pressure (adjusted R-squared: 0.18, p-value: < 2.2 10-16). Significant variables are indicated in bold.

Discussion This exploratory analysis confirms the impact of measures of poor sleep on cerebrovascular health, proposing a complex relationship between sleep and WMH loads involving cardiovascular features ^{3 4} in a large ageing population. Further work will examine the wider implications of measures of poor sleep on cognition and brain function.

References

1. Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010;341:c3666.

2. Ju YS, Lucey BP, Holtzman DM. Sleepand Alzheimer disease pathology—a bidirectional relationship. Nature reviews Neurology 2014;10(2):115.

3. Kocevska D, Cremers LG, Lysen TS, Luik AI, Ikram MA, Vernooij MW, et al. Sleep complaints and cerebral white matter: A prospective bidirectional study. J Psychiatr Res 2019;112:77–82.

4. Lu S, Song L, Wang D, Zhang X, Lv X, Yin H, et al. White matter hyperintensity and cognitive impairments in chronic insomniacs. Neuroreport 2019;30(9):612–618.