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Person-specific contribution of neuropathologies to cognitive loss in old age
Open accessAbstract
Objective: Mixed neuropathologies are the most common cause of dementia at the population level, but how different neuropathologies contribute to cognitive decline at the individual level remains unknown. We quantified the contribution of 9 neuropathologies to cognitive loss at an individual level. Methods: Participants (n = 1,079) came from 2 longitudinal clinical–pathologic studies of aging. All completed 2 + cognitive evaluations (maximum = 22), died, and underwent neuropathologic examinations to identify Alzheimer disease (AD), other neurodegenerative diseases, and vascular pathologies. Linear mixed models examined associations of neuropathologies with cognitive decline and estimated the proportion of cognitive loss accounted for by each neuropathology at a person‐specific level. Results: Neuropathology was ubiquitous, with 94% of participants having 1+, 78% having 2+, 58% having 3+, and 35% having 4+. AD was most frequent (65%) but rarely occurred in isolation (9%). Remarkably, >230 different neuropathologic combinations were observed, each of which occurred in <6% of the cohort. The relative contributions of specific neuropathologies to cognitive loss varied widely across individuals. Although AD accounted for an average of about 50% of the observed cognitive loss, the proportion accounted for at the individual level ranged widely from 22% to 100%. Lewy bodies and hippocampal sclerosis also had potent effects, but again their impacts varied at the person‐specific level. Interpretation: There is much greater heterogeneity in the comorbidity and cognitive impact of age‐related neuropathologies than currently appreciated, suggesting an urgent need for novel therapeutic approaches that embrace the complexity of disease to combat cognitive decline in old age. Ann Neurol 2018;83:74–83
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“Studies suggest that mixed dementia is the norm, not just for those diagnosed with Alzheimer's dementia but also for those diagnosed with other types of dementia.”
From 2024 Alzheimer's disease facts and figures (2024) · cites this paper as [37]
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“As inquiries move in this direction—through the use of PET imaging, cerebrospinal fluid, blood, or autopsy—it is important to note that mixed dementia is the most common type of dementia and that a diverse set of neuropathologies may contribute to the clinical syndrome that we diagnose as dementia (Boyle et al. 2018; Brenowitz et al. 2017; Power et al. 2018b).”
From Exposure to Air Pollution in Relation to Risk of Dementia and Related Outcomes: An Updated Systematic Review of the Epidemiological Literature (2021) · cites this paper as Boyle et al. 2018
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“A further RCT of cognitively stimulating activities for people with delirium in dementia did not improve the delirium.293”
From Dementia prevention, intervention, and care: 2020 report of the Lancet Commission (2020) · cites this paper as [293]
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“First, it captures all the factors affecting cognition, including diverse pathologies as well as biological mechanisms independent of pathologies4–6.”
From Large-scale proteomic analysis of human brain identifies proteins associated with cognitive trajectory in advanced age (2019) · cites this paper as [5]
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“Second, it likely captures co-occurring disease processes and co-occurring age-related pathologies, which are known to be prevalent in the brains of aged individuals4,5.”
From Large-scale proteomic analysis of human brain identifies proteins associated with cognitive trajectory in advanced age (2019) · cites this paper as [5]
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“However, pathologies such as β-amyloid plaques, neurofibrillary tangles, microinfarct, macroinfarct, and Lewy bodies together capture only about 41% of the variance in cognitive trajectory, leaving 59% unexplained5,7.”
From Large-scale proteomic analysis of human brain identifies proteins associated with cognitive trajectory in advanced age (2019) · cites this paper as [5]
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Dementia prevention, intervention, and care: 2020 report of the Lancet Commission
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Metadata
- Authors
- Boyle, P. A., Yu, L., Wilson, R. S., Leurgans, S. E., Schneider, J. A., & Bennett, D. A.
- Affiliations
- Rush University Medical Center (US)
- Corresponding author
- Boyle, Patricia A.
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 2018-01
- Volume
- 83
- Issue
- 1
- Pages
- 74-83
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- PMC
- PMC5876116
- OpenAlex
- W2771599582
- Cited by
- 508
- References
- 26
- Citations by year
- 2026: 33 · 2025: 65 · 2024: 66 · 2023: 67 · 2022: 82 · 2021: 49 · 2020: 82 · 2019: 47 · 2018: 16
- FWCI
- 32.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annals of Neurology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (R01AG34374, R01AG42210, R01AG17917, P30AG10161, R01AG15819)
- Illinois Department of Public Health
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- neuropathology, cognitive decline, dementia, Alzheimer's disease, Lewy bodies, hippocampal sclerosis, vascular pathology, neurodegenerative diseases, individual heterogeneity, aging
- MeSH terms
- Aged, Aged, 80 and over, Aging, Alzheimer Disease, Autopsy, Brain, Female, Humans, Longitudinal Studies, Male, Nervous System Diseases, Neuropsychological Tests, Dementia, Vascular, Cohort Studies, Comorbidity, Lewy Body Disease, Cognitive Dysfunction
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