Cholinergic white matter pathways along the Alzheimer's disease continuum
Jazyk angličtina Země Anglie, Velká Británie Médium print
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
36288546
PubMed Central
PMC10151179
DOI
10.1093/brain/awac385
PII: 6775152
Knihovny.cz E-zdroje
- Klíčová slova
- Alzheimer’s disease, CSF markers, MRI, cholinergic system, nucleus basalis of Meynert,
- MeSH
- Alzheimerova nemoc * psychologie MeSH
- bílá hmota * MeSH
- cholinergní látky MeSH
- kognitivní dysfunkce * psychologie MeSH
- lidé MeSH
- mozek MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- cholinergní látky MeSH
Previous studies have shown that the cholinergic nucleus basalis of Meynert and its white matter projections are affected in Alzheimer's disease dementia and mild cognitive impairment. However, it is still unknown whether these alterations can be found in individuals with subjective cognitive decline, and whether they are more pronounced than changes found in conventional brain volumetric measurements. To address these questions, we investigated microstructural alterations of two major cholinergic pathways in individuals along the Alzheimer's disease continuum using an in vivo model of the human cholinergic system based on neuroimaging. We included 402 participants (52 Alzheimer's disease, 66 mild cognitive impairment, 172 subjective cognitive decline and 112 healthy controls) from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study. We modelled the cholinergic white matter pathways with an enhanced diffusion neuroimaging pipeline that included probabilistic fibre-tracking methods and prior anatomical knowledge. The integrity of the cholinergic white matter pathways was compared between stages of the Alzheimer's disease continuum, in the whole cohort and in a CSF amyloid-beta stratified subsample. The discriminative power of the integrity of the pathways was compared to the conventional volumetric measures of hippocampus and nucleus basalis of Meynert, using a receiver operating characteristics analysis. A multivariate model was used to investigate the role of these pathways in relation to cognitive performance. We found that the integrity of the cholinergic white matter pathways was significantly reduced in all stages of the Alzheimer's disease continuum, including individuals with subjective cognitive decline. The differences involved posterior cholinergic white matter in the subjective cognitive decline stage and extended to anterior frontal white matter in mild cognitive impairment and Alzheimer's disease dementia stages. Both cholinergic pathways and conventional volumetric measures showed higher predictive power in the more advanced stages of the disease, i.e. mild cognitive impairment and Alzheimer's disease dementia. In contrast, the integrity of cholinergic pathways was more informative in distinguishing subjective cognitive decline from healthy controls, as compared with the volumetric measures. The multivariate model revealed a moderate contribution of the cholinergic white matter pathways but not of volumetric measures towards memory tests in the subjective cognitive decline and mild cognitive impairment stages. In conclusion, we demonstrated that cholinergic white matter pathways are altered already in subjective cognitive decline individuals, preceding the more widespread alterations found in mild cognitive impairment and Alzheimer's disease. The integrity of the cholinergic pathways identified the early stages of Alzheimer's disease better than conventional volumetric measures such as hippocampal volume or volume of cholinergic nucleus basalis of Meynert.
Ageing Epidemiology Research Unit School of Public Health Imperial College London London UK
Berlin Center for Advanced Neuroimaging Charité Universitätsmedizin Berlin Berlin Germany
Centre for Clinical Brain Sciences University of Edinburgh and UK DRI Edinburgh UK
Department for Biomedical Magnetic Resonance University of Tübingen Tübingen Germany
Department of Neurology University of Bonn Bonn Germany
Department of Psychiatry and Psychotherapy Charité Berlin Germany
Department of Psychiatry and Psychotherapy University Hospital LMU Munich Munich Germany
Department of Psychiatry Charité Universitätsmedizin Berlin Campus Benjamin Franklin Berlin Germany
Department of Psychiatry Medical Faculty University of Cologne Cologne Germany
Department of Psychosomatic Medicine Rostock University Medical Center Rostock Germany
German Center for Neurodegenerative Diseases Berlin Germany
German Center for Neurodegenerative Diseases Bonn Germany
German Center for Neurodegenerative Diseases Goettingen Germany
German Center for Neurodegenerative Diseases Magdeburg Germany
German Center for Neurodegenerative Diseases Munich Germany
German Center for Neurodegenerative Diseases Rostock Germany
German Center for Neurodegenerative Diseases Tübingen Germany
Institute for Stroke and Dementia Research University Hospital LMU Munich Munich Germany
Leibniz Institute for Neurobiology Magdeburg Germany
Munich Cluster for Systems Neurology Munich Germany
Sheffield Institute for Translational Neurosciences University of Sheffield Sheffield UK
Theme Inflammation and Aging Karolinska University Hospital Stockholm Sweden
Zobrazit více v PubMed
Buchhave P, Minthon L, Zetterberg H, Wallin ÅK, Blennow K, Hansson O. Cerebrospinal fluid levels of β-amyloid 1–42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia. Arch Gen Psychiatry. 2012;69:98–106. PubMed
Villemagne VL, Burnham S, Bourgeat P, et al. . Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: A prospective cohort study. Lancet Neurol. 2013;12:357–367. PubMed
Albert M, Zhu Y, Moghekar A, et al. . Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years. Brain. 2018;141:877–887. PubMed PMC
Sperling RA, Aisen PS, Beckett LA, et al. . Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement. 2011;7:280–292. PubMed PMC
Dubois B, Hampel H, Feldman HH, et al. . Preclinical Alzheimer’s disease: Definition, natural history, and diagnostic criteria. Alzheimer’s Dement. 2016;12:292–323. PubMed PMC
Jack CR, Bennett DA, Blennow K, et al. . NIA-AA research framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s Dement. 2018;14:535–562. PubMed PMC
Fu H, Hardy J, Duff KE. Selective vulnerability in neurodegenerative diseases. Nat Neurosci. 2018;21:1350–1358. PubMed PMC
Brueggen K, Dyrba M, Barkhof F, et al. . Basal forebrain and hippocampus as predictors of conversion to Alzheimer’s disease in patients with mild cognitive impairment–A multicenter DTI and volumetry study. J Alzheimer’s Dis. 2015;48:197–204. PubMed
Schmitz TW, Nathan Spreng R, Alzheimer's Disease Neuroimaging Initiative . Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer’s pathology. Nat Commun. 2016;7:13249. PubMed PMC
Bartus RT, Dean RL, Beer B, Lippa AS. The cholinergic hypothesis of geriatric memory dysfunction. Science. 1982;217:408–414. PubMed
Kanaan NM, Pigino GF, Brady ST, Lazarov O, Binder LI, Morfini GA. Axonal degeneration in Alzheimer’s disease: When signaling abnormalities meet the axonal transport system. Exp Neurol. 2013;246:44–53. PubMed PMC
Li X, Li TQ, Andreasen N, Wiberg MK, Westman E, Wahlund LO. The association between biomarkers in cerebrospinal fluid and structural changes in the brain in patients with Alzheimer’s disease. J Intern Med. 2014;275:418–427. PubMed
Li X, Westman E, Ståhlbom AK, et al. . White matter changes in familial Alzheimer’s disease. J Intern Med. 2015;278:211–218. PubMed
Schumacher J, Ray NJ, Hamilton CA, et al. . Cholinergic white matter pathways in dementia with Lewy bodies and Alzheimer’s disease. Brain. 2022;145(5):1773–1784. PubMed PMC
Ballinger EC, Ananth M, Talmage DA, Role LW. Basal forebrain cholinergic circuits and signaling in cognition and cognitive decline. Neuron. 2016;91:1199–1218. PubMed PMC
Jessen F, Spottke A, Boecker H, et al. . Design and first baseline data of the DZNE multicenter observational study on predementia Alzheimer’s disease (DELCODE). Alzheimer’s Res Ther. 2018;10:21. PubMed PMC
Folstein MF, Folstein SE, McHugh PR. Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–198. PubMed
Yesavage JA, Sheikh JI. Geriatric Depression Scale (GDS). Clin Gerontol. 1986;5:165–173.
Jessen F, Amariglio RE, Van Boxtel M, et al. . A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimer’s Dement. 2014;10:844–852. PubMed PMC
Albert MS, DeKosky ST, Dickson D, et al. . The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement. 2011;7:270–279. PubMed PMC
McKhann GM, Knopman DS, Chertkow H, et al. . The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement. 2011;7:263–269. PubMed PMC
Mohs RC, Knopman D, Petersen RC, et al. . Development of cognitive instruments for use in clinical trials of antidementia drugs: Additions to the Alzheimer’s disease assessment scale that broaden its scope. Alzheimer Dis Assoc Disord. 1997;11:13–21. PubMed
Smith A. Symbol digit modality test (SDMT): Manual (revised). Western Psychological Services; 1982.
Reitan RM. Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills. 1958;8:271–276.
Janelidze S, Zetterberg H, Mattsson N, et al. . CSF Aβ42/Aβ40 and Aβ42/Aβ38 ratios: Better diagnostic markers of Alzheimer disease. Ann Clin Transl Neurol. 2016;3:154–165. PubMed PMC
Jezzard P, Balaban RS. Correction for geometric distortion in echo planar images from B0 field variations. Magn Reson Med. 1995;34:65–73. PubMed
Nemy M, Cedres N, Grothe MJ, et al. . Cholinergic white matter pathways make a stronger contribution to attention and memory in normal aging than cerebrovascular health and nucleus basalis of Meynert. Neuroimage. 2020;211:116607. PubMed
Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL. Neuroimage. 2012;62:782–790. PubMed
Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143–155. PubMed PMC
Reber PJ, Wong EC, Buxton RB, Frank LR. Correction of off resonance-related distortion in echo-planar imaging using EPI-based field maps. Magn Reson Med. 1998;39:328–330. PubMed
Andersson JLR, Sotiropoulos SN. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage. 2016;125:1063–1078. PubMed PMC
Behrens TEJ, Berg HJ, Jbabdi S, Rushworth MFS, Woolrich MW. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage. 2007;34:144–155. PubMed PMC
Hernández M, Guerrero GD, Cecilia JM, et al. . Accelerating fibre orientation estimation from diffusion weighted magnetic resonance imaging using GPUs. PLoS ONE. 2013;8:e61892. PubMed PMC
Selden NR, Gitelman DR, Salamon-Murayama N, Parrish TB, Mesulam MM. Trajectories of cholinergic pathways within the cerebral hemispheres of the human brain. Brain. 1998;121:2249–2257. PubMed
Kilimann I, Grothe M, Heinsen H, et al. . Subregional basal forebrain atrophy in Alzheimer’s disease: A multicenter study. J Alzheimer’s Dis. 2014;40:687–700. PubMed PMC
Mori S, Wakana S, Van Zijl PC, Nagae-Poetscher L. MRI atlas of human white matter. Elsevier; 2005. PubMed
Behrens TEJ, Woolrich MW, Jenkinson M, et al. . Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50:1077–1088. PubMed
Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001;20:45–57. PubMed
Buckner RL, Head D, Parker J, et al. . A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: Reliability and validation against manual measurement of total intracranial volume. Neuroimage. 2004;23:724–738. PubMed
Kim HJ, Moon WJ, Han SH. Differential cholinergic pathway involvement in Alzheimer’s disease and subcortical ischemic vascular dementia. J Alzheimer’s Dis. 2013;35:129–136. PubMed
Cedres N, Ferreira D, Machado A, et al. . Predicting Fazekas scores from automatic segmentations of white matter signal abnormalities. Aging (Albany NY). 2020;12:894–901. PubMed PMC
Leritz EC, Shepel J, Williams VJ, et al. . Associations between T1 white matter lesion volume and regional white matter microstructure in aging. Hum Brain Mapp. 2014;35:1085–1100. PubMed PMC
Fischl B, Salat DH, Busa E, et al. . Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341–355. PubMed
Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage. 2014;92:381–397. PubMed PMC
Cedres N, Ferreira D, Nemy M, et al. . Association of cerebrovascular and Alzheimer disease biomarkers with cholinergic white matter degeneration in cognitively unimpaired individuals. Neurology. 2022;99(15):e1619–e1629. PubMed PMC
Breiman L. Random forests. Mach Learn. 2001;45:5–32.
Breiman L. Bagging predictions. Mach Learn. 1996;24:123–140.
Lebedev AV, Westman E, Van Westen GJP, et al. . Random forest ensembles for detection and prediction of Alzheimer’s disease with a good between-cohort robustness. Neuroimage Clin. 2014;6:115–125. PubMed PMC
Strobl C, Boulesteix AL, Zeileis A, Hothorn T. Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinf. 2007;8:25. PubMed PMC
Robin X, Turck N, Hainard A, et al. . pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinf. 2011;12:77. PubMed PMC
Lin C-P, Frigerio I, Boon BDC, et al. . Structural (dys)connectivity associates with cholinergic cell density in Alzheimer’s disease. Brain. 2022;145:2869–2881. PubMed PMC
Wolfsgruber S, Kleineidam L, Guski J, et al. . Minor neuropsychological deficits in patients with subjective cognitive decline. Neurology. 2020;95:e1134–e1143. PubMed
Rami L, Fortea J, Bosch B, et al. . Cerebrospinal fluid biomarkers and memory present distinct associations along the continuum from healthy subjects to AD patients. J Alzheimer’s Dis. 2011;23:319–326. PubMed
Visser PJ, Verhey F, Knol DL, et al. . Prevalence and prognostic value of CSF markers of Alzheimer’s disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the DESCRIPA study: A prospective cohort study. Lancet Neurol. 2009;8:619–627. PubMed
Antonell A, Fortea J, Rami L, et al. . Different profiles of Alzheimer’s disease cerebrospinal fluid biomarkers in controls and subjects with subjective memory complaints. J Neural Transm. 2011;118:259–262. PubMed
Sánchez-Benavides G, Suárez-Calvet M, Milà-Alomà M, et al. . Amyloid-β positive individuals with subjective cognitive decline present increased CSF neurofilament light levels that relate to lower hippocampal volume. Neurobiol Aging. 2021;104:24–31. PubMed
Ferreira D, Falahati F, Linden C, et al. . A “disease severity index” to identify individuals with subjective memory decline who will progress to mild cognitive impairment or dementia. Sci Rep. 2017;7:44368. PubMed PMC
Ebenau JL, Pelkmans W, Verberk IMW, et al. . Association of CSF, plasma, and imaging markers of neurodegeneration with clinical progression in people with subjective cognitive decline. Neurology. 2022;98:E1315–E1326. PubMed PMC
Cicognola C, Hansson O, Scheltens P, et al. . Cerebrospinal fluid N-224 tau helps discriminate Alzheimer’s disease from subjective cognitive decline and other dementias. Alzheimer’s Res Ther. 2021;13:38. PubMed PMC
Sun X, Salat D, Upchurch K, Deason R, Kowall N, Budson A. Destruction of white matter integrity in patients with mild cognitive impairment and Alzheimer disease. J Investig Med. 2014;62:927–933. PubMed PMC
Teipel S, Heinsen H, Amaro E, et al. . Cholinergic basal forebrain atrophy predicts amyloid burden in Alzheimer’s disease. Neurobiol Aging. 2014;35:482–491. PubMed PMC
Lee PL, Chou KH, Chung CP, et al. . Posterior cingulate cortex network predicts Alzheimer’s disease progression. Front Aging Neurosci. 2020;12:466. PubMed PMC
Palmqvist S, Schöll M, Strandberg O, et al. . Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun. 2017;8:1–13. PubMed PMC
Coughlan G, Laczó J, Hort J, Minihane AM, Hornberger M. Spatial navigation deficits–overlooked cognitive marker for preclinical Alzheimer disease? Nat Rev Neurol. 2018;14:496–506. PubMed
Fernández-Cabello S, Kronbichler M, van Dijk KRA, Goodman JA, Nathan Spreng R, Schmitz TW. Basal forebrain volume reliably predicts the cortical spread of Alzheimer’s degeneration. Brain. 2020;143:993–1009. PubMed PMC
Schulz J, Pagano G, Fernández Bonfante JA, Wilson H, Politis M. Nucleus basalis of Meynert degeneration precedes and predicts cognitive impairment in Parkinson’s disease. Brain. 2018;141:1501–1516. PubMed PMC
Nishioka C, Liang HF, Barsamian B, Sun SW. Amyloid-beta induced retrograde axonal degeneration in a mouse tauopathy model. Neuroimage. 2019;189:180–191. PubMed PMC
Teipel SJ, Kuper-Smith JO, Bartels C, et al. . Multicenter tract-based analysis of microstructural lesions within the Alzheimer’s disease Spectrum: Association with amyloid pathology and diagnostic usefulness. J Alzheimers Dis. 2019;72:455–465. PubMed PMC