Cognitive profile in cerebral small vessel disease: comparison between cerebral amyloid angiopathy and hypertension-related microangiopathy.

Arteriolosclerosis Cerebral amyloid angiopathy Cerebral small vessel disease Cognition Cognitive decline Cognitive impairment Cognitive profile Microangiopathy Neuropsychological patterns

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
11 Mar 2024
Historique:
received: 13 11 2023
accepted: 27 02 2024
medline: 12 3 2024
pubmed: 12 3 2024
entrez: 12 3 2024
Statut: epublish

Résumé

Cerebral amyloid angiopathy (CAA) is recognized as a cause of cognitive impairment, but its cognitive profile needs to be characterized, also respect to hypertension-related microangiopathy (HA). We aimed at comparing difference or similarity of CAA and HA patients' cognitive profiles, and their associated factors. Participants underwent an extensive clinical, neuropsychological, and neuroimaging protocol. HA patients (n = 39) were more frequently males, with history of vascular risk factors than CAA (n = 32). Compared to HA, CAA patients presented worse performance at MoCA (p = 0.001) and semantic fluency (p = 0.043), and a higher prevalence of amnestic MCI (46% vs. 68%). In univariate analyses, multi-domain MCI was associated with worse performance at MoCA, Rey Auditory Verbal Learning Test (RAVLT), and semantic fluency in CAA patients, and with worse performance at Symbol Digit Modalities Test (SDMT) and phonemic fluency in HA ones. In multivariate models, multi-domain deficit remained as the only factor associated with RAVLT (β = - 0.574) in CAA, while with SDMT (β = - 0.364) and phonemic fluency (β = - 0.351) in HA. Our results highlight different patterns of cognitive deficits in CAA or HA patients. While HA patients' cognitive profile was confirmed as mainly attentional/executive, a complex cognitive profile, characterized also by deficit in semantic memory, seems the hallmark of CAA patients.

Identifiants

pubmed: 38467658
doi: 10.1038/s41598-024-55719-w
pii: 10.1038/s41598-024-55719-w
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5922

Informations de copyright

© 2024. The Author(s).

Références

Pantoni, L. Cerebral small vessel disease: From pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol. 9(7), 689–701. https://doi.org/10.1016/S1474-4422(10)70104-6 (2010).
doi: 10.1016/S1474-4422(10)70104-6 pubmed: 20610345
Wardlaw, J. M., Smith, C. & Dichgans, M. Small vessel disease: Mechanisms and clinical implications. Lancet Neurol. 18(7), 684–696. https://doi.org/10.1016/S1474-4422(19)30079-1 (2019).
doi: 10.1016/S1474-4422(19)30079-1 pubmed: 31097385
Wardlaw, J. M. et al. STandards for ReportIng Vascular changes on nEuroimaging (STRIVE v1). Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 12(8), 822–838. https://doi.org/10.1016/S1474-4422(13)70124-8 (2013).
doi: 10.1016/S1474-4422(13)70124-8 pubmed: 23867200 pmcid: 3714437
Duering, M. et al. Neuroimaging standards for research into small vessel disease-advances since 2013. Lancet Neurol. 22(7), 602–618. https://doi.org/10.1016/S1474-4422(23)00131-X (2023).
doi: 10.1016/S1474-4422(23)00131-X pubmed: 37236211
Chen, X. et al. Cerebral small vessel disease: Neuroimaging markers and clinical implication. J. Neurol. 266(10), 2347–2362. https://doi.org/10.1007/s00415-018-9077-3 (2019).
doi: 10.1007/s00415-018-9077-3 pubmed: 30291424
Zanon Zotin, M. C., Sveikata, L., Viswanathan, A. & Yilmaz, P. Cerebral small vessel disease and vascular cognitive impairment: From diagnosis to management. Curr. Opin. Neurol. 34(2), 246–257. https://doi.org/10.1097/WCO.0000000000000913 (2021).
doi: 10.1097/WCO.0000000000000913 pubmed: 33630769 pmcid: 7984766
Charidimou, A., Pantoni, L. & Love, S. The concept of sporadic cerebral small vessel disease: A road map on key definitions and current concepts. Int. J. Stroke 11(1), 6–18. https://doi.org/10.1177/1747493015607485 (2016).
doi: 10.1177/1747493015607485 pubmed: 26763016
Charidimou, A. et al. White matter hyperintensity patterns in cerebral amyloid angiopathy and hypertensive arteriopathy. Neurology 86(6), 505–511. https://doi.org/10.1212/WNL.0000000000002362 (2016).
doi: 10.1212/WNL.0000000000002362 pubmed: 26747886 pmcid: 4753727
Xiong, L. et al. Cognitive profile and its association with neuroimaging markers of non-demented cerebral amyloid angiopathy patients in a Stroke Unit. J. Alzheimer’s Dis. 52(1), 171–178. https://doi.org/10.3233/JAD-150890 (2016).
doi: 10.3233/JAD-150890
Yamada, M. Cerebral amyloid angiopathy: Emerging concepts. J. Stroke 17(1), 17–30. https://doi.org/10.5853/jos.2015.17.1.17 (2015).
doi: 10.5853/jos.2015.17.1.17 pubmed: 25692104 pmcid: 4325636
Li, Q. et al. Cerebral small vessel disease. Cell Transplant. 27(12), 1711–1722. https://doi.org/10.1177/0963689718795148 (2018).
doi: 10.1177/0963689718795148 pubmed: 30251566 pmcid: 6300773
O’Brien, J. T. Vascular cognitive impairment. Am. J. Geriatr. Psychiatry 14(9), 724–733. https://doi.org/10.1097/01.JGP.0000231780.44684.7e (2006).
doi: 10.1097/01.JGP.0000231780.44684.7e pubmed: 16943169
Salvadori, E., Brambilla, M., Cova, I., Pomati, S. & Pantoni, L. Cognitive evaluation in cerebral small vessel disease: Towards an evidence-based identification of the reference standards. Part 1. A systematic review and qualitative data synthesis. J. Neurol. 268(12), 4563–4572. https://doi.org/10.1007/s00415-020-10262-2 (2021).
doi: 10.1007/s00415-020-10262-2 pubmed: 33048216
Salvadori, E. et al. The clinical profile of cerebral small vessel disease: Toward an evidence-based identification of cognitive markers. Alzheimer’s Dement. J. Alzheimer’s Assoc. 19(1), 244–260. https://doi.org/10.1002/alz.12650 (2023).
doi: 10.1002/alz.12650
Schrag, M. & Kirshner, H. Neuropsychological effects of cerebral amyloid angiopathy. Curr. Neurol. Neurosci. Rep. 16(8), 76. https://doi.org/10.1007/s11910-016-0674-1 (2016).
doi: 10.1007/s11910-016-0674-1 pubmed: 27357378
Planton, M., Raposo, N., Albucher, J. F. & Pariente, J. Cerebral amyloid angiopathy-related cognitive impairment: The search for a specific neuropsychological pattern. Revue Neurologique 173(9), 562–565. https://doi.org/10.1016/j.neurol.2017.09.006 (2017).
doi: 10.1016/j.neurol.2017.09.006 pubmed: 28993004
Boyle, P. A. et al. Cerebral amyloid angiopathy and cognitive outcomes in community-based older persons. Neurology 85(22), 1930–1936. https://doi.org/10.1212/WNL.0000000000002175 (2015).
doi: 10.1212/WNL.0000000000002175 pubmed: 26537052 pmcid: 4664125
Case, N. F. et al. Cerebral amyloid angiopathy is associated with executive dysfunction and mild cognitive impairment. Stroke 47(8), 2010–2016. https://doi.org/10.1161/STROKEAHA.116.012999 (2016).
doi: 10.1161/STROKEAHA.116.012999 pubmed: 27338926
Chan, E. et al. Domain-specific neuropsychological investigation of CAA with and without intracerebral haemorrhage. J. Neurol. 270(12), 6124–6132. https://doi.org/10.1007/s00415-023-11977-8 (2023).
doi: 10.1007/s00415-023-11977-8 pubmed: 37672105 pmcid: 10632296
Smith, E. E. Cerebral amyloid angiopathy as a cause of neurodegeneration. J. Neurochem. 144(5), 651–658. https://doi.org/10.1111/jnc.14157 (2018).
doi: 10.1111/jnc.14157 pubmed: 28833176
Ciolli, L. et al. The VAS-COG clinic: An out-patient service for patients with cognitive and behavioral consequences of cerebrovascular diseases. Neurol. sci. 33(6), 1277–1283. https://doi.org/10.1007/s10072-012-0941-0 (2012).
doi: 10.1007/s10072-012-0941-0 pubmed: 22258361
Poggesi, A. et al. The Florence VAS-COG clinic: a model for the care of patients with cognitive and behavioral disturbances consequent to cerebrovascular diseases. J. Alzheimer’s Dis. 42(Suppl 4), S453–S461. https://doi.org/10.3233/JAD-141569 (2014).
doi: 10.3233/JAD-141569
Greenberg, S. M. & Charidimou, A. Diagnosis of cerebral amyloid angiopathy: Evolution of the Boston criteria. Stroke 49(2), 491–497. https://doi.org/10.1161/STROKEAHA.117.016990 (2018).
doi: 10.1161/STROKEAHA.117.016990 pubmed: 29335334 pmcid: 5892842
Winblad, B. et al. Mild cognitive impairment–beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment. J. Intern. Med. 256(3), 240–246. https://doi.org/10.1111/j.1365-2796.2004.01380.x (2004).
doi: 10.1111/j.1365-2796.2004.01380.x pubmed: 15324367
Salvadori, E. et al. Development and psychometric properties of a neuropsychological battery for mild cognitive impairment with small vessel disease: the VMCI-Tuscany Study. J. Alzheimer’s Dis. 43(4), 1313–1323. https://doi.org/10.3233/JAD-141449 (2015).
doi: 10.3233/JAD-141449
Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A. & Jaffe, M. W. Studies of illness in the aged. The index of adl: A standardized measure of biological and psychosocial function. JAMA 185, 914–919. https://doi.org/10.1001/jama.1963.03060120024016 (1963).
doi: 10.1001/jama.1963.03060120024016 pubmed: 14044222
Lawton, M. P. & Brody, E. M. Assessment of older people: seLf-maintaining and instrumental activities of daily living. Gerontologist 9(3), 179–186 (1969).
doi: 10.1093/geront/9.3_Part_1.179 pubmed: 5349366
Sheikh, J. & Yesavage, J. Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. In Clinical Gerontology (eds Sheikh, J. & Yesavage, J.) (Routledge, 1986).
Fazekas, F., Chawluk, J. B., Alavi, A., Hurtig, H. I. & Zimmerman, R. A. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am. J. Roentgenol. 149(2), 351–356. https://doi.org/10.2214/ajr.149.2.351 (1987).
doi: 10.2214/ajr.149.2.351 pubmed: 3496763
Gregoire, S. M. et al. The Microbleed Anatomical Rating Scale (MARS): Reliability of a tool to map brain microbleeds. Neurology 73(21), 1759–1766. https://doi.org/10.1212/WNL.0b013e3181c34a7d (2009).
doi: 10.1212/WNL.0b013e3181c34a7d pubmed: 19933977
Linn, J. et al. Prevalence of superficial siderosis in patients with cerebral amyloid angiopathy. Neurology 74(17), 1346–1350. https://doi.org/10.1212/WNL.0b013e3181dad605 (2010).
doi: 10.1212/WNL.0b013e3181dad605 pubmed: 20421578 pmcid: 2875936
Ramusino, M. C. et al. Vascular lesions and brain atrophy in Alzheimer’s, vascular and mixed dementia: An optimized 3T MRI protocol reveals distinctive radiological profiles. Curr. Alzheimer Res. 19(6), 449–457. https://doi.org/10.2174/1567205019666220620112831 (2022).
doi: 10.2174/1567205019666220620112831 pubmed: 35726416
Keage, H. A. et al. Population studies of sporadic cerebral amyloid angiopathy and dementia: A systematic review. BMC Neurol. 9, 3. https://doi.org/10.1186/1471-2377-9-3 (2009).
doi: 10.1186/1471-2377-9-3 pubmed: 19144113 pmcid: 2647900
Jiménez-Sánchez, L. et al. Sex differences in cerebral small vessel disease: A systematic review and meta-analysis. Front. Neurol. 12, 756887. https://doi.org/10.3389/fneur.2021.756887 (2021).
doi: 10.3389/fneur.2021.756887 pubmed: 34777227 pmcid: 8581736
Charidimou, A. et al. The Boston criteria version 2.0 for cerebral amyloid angiopathy: A multicentre, retrospective, MRI-neuropathology diagnostic accuracy study. Lancet Neurol. 21(8), 714–725. https://doi.org/10.1016/S1474-4422(22)00208-3 (2022).
doi: 10.1016/S1474-4422(22)00208-3 pubmed: 35841910 pmcid: 9389452
Perosa, V. et al. Implications of quantitative susceptibility mapping at 7 Tesla MRI for microbleeds detection in cerebral small vessel disease. Front. Neurol. 14, 1112312. https://doi.org/10.3389/fneur.2023.1112312 (2023).
doi: 10.3389/fneur.2023.1112312 pubmed: 37006483 pmcid: 10050564
Sun, Y. et al. Characterization of white matter over 1–2 years in small vessel disease using MR-based quantitative susceptibility mapping and free-water mapping. Front. Aging Neurosci. 14, 998051. https://doi.org/10.3389/fnagi.2022.998051 (2022).
doi: 10.3389/fnagi.2022.998051 pubmed: 36247993 pmcid: 9562046

Auteurs

Eleonora Barucci (E)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.

Emilia Salvadori (E)

Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.

Simona Magi (S)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.

Martina Squitieri (M)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.

Giulio Maria Fiore (GM)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.

Lorenzo Ramacciotti (L)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.

Benedetta Formelli (B)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.

Francesca Pescini (F)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.
Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Stroke Unit, Careggi University Hospital, Florence, Italy.

Anna Poggesi (A)

NEUROFARBA Department, Neuroscience Section, University of Florence, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy. anna.poggesi@unifi.it.
Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy. anna.poggesi@unifi.it.
Stroke Unit, Careggi University Hospital, Florence, Italy. anna.poggesi@unifi.it.
Don Carlo Gnocchi Foundation, Florence, Italy. anna.poggesi@unifi.it.

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