The DOI matches its Crossref record; 280 of the 281 references it cites were found in a registry or an index.
“New Old Pathologies”: AD, PART, and Cerebral Age-Related TDP-43 With Sclerosis (CARTS)
Open accessAbstract
The pathology-based classification of Alzheimer's disease (AD) and other neurodegenerative diseases is a work in progress that is important for both clinicians and basic scientists. Analyses of large autopsy series, biomarker studies, and genomics analyses have provided important insights about AD and shed light on previously unrecognized conditions, enabling a deeper understanding of neurodegenerative diseases in general. After demonstrating the importance of correct disease classification for AD and primary age-related tauopathy, we emphasize the public health impact of an underappreciated AD "mimic," which has been termed "hippocampal sclerosis of aging" or "hippocampal sclerosis dementia." This pathology affects >20% of individuals older than 85 years and is strongly associated with cognitive impairment. In this review, we provide an overview of current hypotheses about how genetic risk factors (GRN, TMEM106B, ABCC9, and KCNMB2), and other pathogenetic influences contribute to TDP-43 pathology and hippocampal sclerosis. Because hippocampal sclerosis of aging affects the "oldest-old" with arteriolosclerosis and TDP-43 pathologies that extend well beyond the hippocampus, more appropriate terminology for this disease is required. We recommend "cerebral age-related TDP-43 and sclerosis" (CARTS). A detailed case report is presented, which includes neuroimaging and longitudinal neurocognitive data. Finally, we suggest a neuropathology-based diagnostic rubric for CARTS.
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“As the distribution of TDP-43 increases from limbic regions to other parts of the brain, it is associated with worsening cognition and with medial temporal atrophy on antemortem brain imaging [130, 132, 133].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [130]
In the citing paper
“Primary age-related tauopathy (PART) and aging-related tau astrogliopathy (ARTAG) are independent tau pathologies commonly observed in patients over 80 years of age, and PART may account for a proportion of the misdiagnosed clinical AD cases in the elderly [130, 141, 142].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [130]
In the citing paper
“Hippocampal sclerosis of aging is now recognized to almost always include TDP-43 deposits and sometimes arteriolosclerosis that lead to intracellular and neuritic deposits of TDP-43 in the hippocampus during the preclinical state and eventually hippocampal sclerosis and cerebral atrophy in the disease state [130, 131].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [130]
In the citing paper
“Lesions are found in the hippocampus and adjacent regions similar to those observed in Braak I-IV, but PART is distinct from AD in that it lacks amyloid plaques, and it has distinct morbidity and age range [130, 142].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [130]
In the citing paper
“ARTAG represents astrocytic tau pathology distinct from that observed in primary tauopathies including PSP, CBD and GGT. It is associated with 4R tau deposits in subpial or perivascular thorn-shaped astrocytes or granular fuzzy astrocytes in gray matter [130].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [130]
In the citing paper
“The frequency of PART increases in the 80s and 90s when AD prevalence is level or declining [130].”
From The neuropathological diagnosis of Alzheimer's disease (2019) · cites this paper as [130]
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Metadata
- Authors
- Nelson, P. T., Trojanowski, J. Q., Abner, E. L., Al-Janabi, O. M., Jicha, G. A., Schmitt, F. A., Smith, C. D., Fardo, D. W., Wang, W.-X., Kryscio, R. J., Neltner, J. H., Kukull, W. A., Cykowski, M. D., Van Eldik, L. J., & Ighodaro, E. T.
- Affiliations
- Houston Methodist (US)
- ORCID
- Venue
- Journal of Neuropathology & Experimental Neurology
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-05-21
- Volume
- 75
- Issue
- 6
- Pages
- 482-498
- ISSN
- 0022-3069 (ISSN-L)
- 1554-6578
- PMC
- PMC6366658
- OpenAlex
- W2400971574
- Cited by
- 158
- References
- 281
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 6 · 2023: 12 · 2022: 11 · 2021: 11 · 2020: 21 · 2019: 19 · 2018: 28 · 2017: 21 · 2016: 10
- FWCI
- 23.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Neuropathology & Experimental Neurology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UKnowledge (University of Kentucky) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institute on Aging (P30AG028383, U01AG016976, P30AG010124, P01AG017586, K25AG043546, U19AG010483)
- National Institute of Neurological Disorders and Stroke (F30NS090714)
- 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
- Health Sciences › Medicine › Clinical Neurology › Amyotrophic Lateral Sclerosis Research
- Keywords
- Alzheimer's disease, primary age-related tauopathy, TDP-43 pathology, CART, disease classification, genetic risk factors, gene regulatory networks, TMEM106B, ABCC9, arteriolosclerosis, oldest old, cognitive impairment
- MeSH terms
- Aged, 80 and over, Aging, Alzheimer Disease, Animals, DNA-Binding Proteins, Female, Hippocampus, Humans, Sclerosis, Tauopathies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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