Preferential degradation of cognitive networks differentiates Alzheimer’s disease from ageing
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Le résumé fourni par la source
Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Preferential degradation of cognitive networks differentiates Alzheimer’s disease from ageing
- Date Crossref
- 07/03/2018
- Éditeur
- Oxford University Press (OUP)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Brigham and Women's Hospital Department of Neurology pays non établi dans la noticeÉtablissement de santé
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Harvard University pays non établi dans la noticeUniversité ou école supérieure
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Massachusetts General Hospital Department of Neurology pays non établi dans la noticeÉtablissement de santé
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Athinoula A. Martinos Center for Biomedical Imaging pays non établi dans la noticeStructure de recherche
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Washington University in St. Louis pays non établi dans la noticeUniversité ou école supérieure
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Mallinckrodt (United States) pays non établi dans la noticeEntreprise
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Mayo Clinic Department of Radiology pays non établi dans la noticeÉtablissement de santé
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WinnMed pays non établi dans la noticeOrganisation à but non lucratif
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University of Southern California pays non établi dans la noticeUniversité ou école supérieure
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Indiana University School of Medicine Department of Pathology and Laboratory Medicine pays non établi dans la noticeUniversité ou école supérieure
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Indiana University – Purdue University Indianapolis pays non établi dans la noticeUniversité ou école supérieure
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German Center for Neurodegenerative Diseases pays non établi dans la noticeStructure de recherche
Department of Neurology — Brigham and Women's Hospital, Harvard University et Department of Neurology — Massachusetts General Hospital, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.