TY - JOUR
T1 - Sleep quality, perivascular spaces and brain health markers in ageing - A longitudinal study in the Lothian Birth Cohort 1936
AU - Aribisala, Benjamin S.
AU - Valdés Hernández, Maria del C.
AU - Okely, Judith A.
AU - Cox, Simon R.
AU - Ballerini, Lucia
AU - Dickie, David Alexander
AU - Wiseman, Stewart J.
AU - Riha, Renata L.
AU - Muñoz Maniega, Susana
AU - Radakovic, Ratko
AU - Taylor, Adele
AU - Pattie, Alison
AU - Corley, Janie
AU - Redmond, Paul
AU - Bastin, Mark E.
AU - Deary, Ian
AU - Wardlaw, Joanna M.
N1 - Funding Information: This study is partially funded by the Galen and Hilary Weston Foundation under the Novel Biomarkers 2019 scheme (ref UB190097) administered by the Weston Brain Institute. The LBC1936 is supported by the Biotechnology and Biological Sciences Research Council, and the Economic and Social Research Council [BB/W008793/1], Age UK as The Disconnected Mind Project (http://www.disconnectedmind.ed.ac.uk), the Medical Research Council (MRC)[G1001245/96099] and The University of Edinburgh. LBC1936 MRI brain imaging was supported by Medical Research Council (MRC) grants [G0701120], [G1001245], [MR/M013111/1] and [MR/R024065/1]. Magnetic Resonance Image acquisition and analyses were conducted at the Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh (www.bric.ed. ac.uk) which is part of SINAPSE (Scottish Imaging Network—A Platform for Scientific Excellence) collaboration (www.sinapse. ac.uk) funded by the Scottish Funding Council and the Chief Scientist Office. This work was supported by the Centre for Cognitive Ageing and Cognitive Epidemiology, funded by the Medical Research Council and the Biotechnology and Biological Sciences Research Council (MR/K026992/1), the Row Fogo Charitable Trust (BRO-D.FID3668413), the European Union Horizon 2020, (PHC-03-15, project No 666881), SVDs@Target, the Fondation Leducq Transatlantic Network of Excellence for the Study of Perivascular Spaces in Small Vessel Disease, ref no. 16 CVD 05, the US National Institutes of Health (R01AG054628), a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust, the Royal Society (SRC, Grant Number 221890/Z/20/Z), and the UK Dementia Research Institute at the University of Edinburgh funded by the Medical Research Council, Alzheimer's Society and Alzheimer's Research UK (JMW). BSA was funded to visit the University of Chicago through Fulbright Scholarship award which gave him the opportunity to work on part of the modelling and manuscript finalization. This work was funded in part by the Wellcome Trust; for the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
Funding Information:
This study is partially funded by the Galen and Hilary Weston Foundation under the Novel Biomarkers 2019 scheme ( ref UB190097 ) administered by the Weston Brain Institute . The LBC1936 is supported by the Biotechnology and Biological Sciences Research Council , and the Economic and Social Research Council [ BB/W008793/1 ], Age UK as The Disconnected Mind Project ( http://www.disconnectedmind.ed.ac.uk ), the Medical Research Council (MRC) [ G1001245/96099 ] and The University of Edinburgh . LBC1936 MRI brain imaging was supported by Medical Research Council (MRC) grants [ G0701120 ], [ G1001245 ], [ MR/M013111/1 ] and [ MR/R024065/1 ]. Magnetic Resonance Image acquisition and analyses were conducted at the Brain Research Imaging Centre, Neuroimaging Sciences, University of Edinburgh ( www.bric.ed . ac.uk) which is part of SINAPSE (Scottish Imaging Network—A Platform for Scientific Excellence) collaboration ( www.sinapse . ac.uk) funded by the Scottish Funding Council and the Chief Scientist Office . This work was supported by the Centre for Cognitive Ageing and Cognitive Epidemiology , funded by the Medical Research Council and the Biotechnology and Biological Sciences Research Council ( MR/K026992/1 ), the Row Fogo Charitable Trust ( BRO-D.FID3668413 ), the European Union Horizon 2020 , ( PHC-03-15 , project No 666881 ), SVDs@Target, the Fondation Leducq Transatlantic Network of Excellence for the Study of Perivascular Spaces in Small Vessel Disease, ref no. 16 CVD 05, the US National Institutes of Health ( R01AG054628 ), a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust , the Royal Society (SRC, Grant Number 221890/Z/20/Z ), and the UK Dementia Research Institute at the University of Edinburgh funded by the Medical Research Council , Alzheimer's Society and Alzheimer's Research UK (JMW) . BSA was funded to visit the University of Chicago through Fulbright Scholarship award which gave him the opportunity to work on part of the modelling and manuscript finalization. This work was funded in part by the Wellcome Trust ; for the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
PY - 2023/6
Y1 - 2023/6
N2 - Background: Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s. Method: We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life. Results: Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (β = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = −0.20, P < 0.001), and with increasing white matter damage metric (β = −0.122, P = 0.018) and faster WMH growth (β = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (β = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (β = −0.16, P = 0.012) and increasing white matter damage metric (β = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes. Conclusion: Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.
AB - Background: Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s. Method: We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life. Results: Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (β = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = −0.20, P < 0.001), and with increasing white matter damage metric (β = −0.122, P = 0.018) and faster WMH growth (β = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (β = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (β = −0.16, P = 0.012) and increasing white matter damage metric (β = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes. Conclusion: Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.
KW - Ageing
KW - Brain atrophy
KW - Brain volume
KW - Cerebrovascular disease
KW - Leukoaraiosis
KW - Magnetic resonance imaging
KW - Perivascular spaces
KW - Sleep
KW - Virchow Robin spaces
KW - White matter hyperintensities
UR - http://www.scopus.com/inward/record.url?scp=85151441462&partnerID=8YFLogxK
U2 - 10.1016/j.sleep.2023.03.016
DO - 10.1016/j.sleep.2023.03.016
M3 - Article
C2 - 37005116
AN - SCOPUS:85151441462
VL - 106
SP - 123
EP - 131
JO - Sleep Medicine Reviews
JF - Sleep Medicine Reviews
SN - 1087-0792
ER -