Cited by 130Cerebrovascular and genetic disordersDementia and Cognitive Impairment ResearchNeurological Disease Mechanisms and Treatments

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White matter hyperintensities across the adult lifespan: relation to age, Aβ load, and cognition

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Garnier-Crussard, Antoine, Bougacha, Salma, Wirth, Miranka, André, Claire, Delarue, Marion, Landeau, Brigitte, Mézenge, Florence, Kuhn, Elizabeth, Gonneaud, Julie, Chocat, Anne, Quillard, Anne, Ferrand-Devouge, Eglantine, de La Sayette, Vincent, Vivien, Denis, Krolak-Salmon, Pierre, Chételat, Gaël·2020·Alzheimer's Research & Therapy

DOI 10.1186/s13195-020-00669-4PMC PMC7545576

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Abstract

BACKGROUND: White matter hyperintensities (WMH) are very frequent in older adults and associated with worse cognitive performance. Little is known about the links between WMH and vascular risk factors, cortical β-amyloid (Aβ) load, and cognition in cognitively unimpaired adults across the entire lifespan, especially in young and middle-aged adults. METHODS: One hundred and thirty-seven cognitively unimpaired adults from the community were enrolled (IMAP cohort). Participants underwent (i) a comprehensive neuropsychological assessment of episodic memory, processing speed, working memory, and executive functions; (ii) brain structural T1 and FLAIR MRI scans used for the automatic segmentation of total and regional (frontal, parietal, temporal, occipital, and corpus callosum) WMH; and (iii) a Florbetapir-PET scan to measure cortical Aβ. The relationships of total and regional WMH to age, vascular risk factors, cortical Aβ, and cognition were assessed within the whole sample, but also splitting the sample in two age groups (≤ or > 60 years old). RESULTS: WMH increased with age across the adult lifespan, i.e., even in young and middle-aged adults. Systolic blood pressure, diastolic blood pressure, and glycated hemoglobin were all associated with higher WMH before, but not after, adjusting for age and the other vascular risk factors. Higher frontal, temporal, and occipital WMH were associated with greater Aβ, but this association was no longer significant when adjusting for age and vascular risk factors. Higher total and frontal WMH were associated with worse performance in executive functions, with no interactive effect of the age group. In contrast, there was a significant interaction of the age group on the link between WMH and working memory, which was significant within the subgroup of young/middle-aged adults only. Adding cortical Aβ load in the models did not alter the results, and there was no interaction between WMH and Aβ on cognition. CONCLUSION: WMH increased with age and were associated with worse executive functions across the adult lifespan and with worse working memory in young/middle-aged adults. Aβ load was weakly associated with WMH and did not change the relationship found between WMH and executive functions. This study argues for the clinical relevance of WMH across the adult lifespan, even in young and middle-aged adults with low WMH.

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Fig. 1 Relationship between WMH and age across the adult lifespan. a Total WMH as a function of age across the adult lifespan (raw volumes on the left; log-transformed volumes and linear regression curve on the right). b Total raw WMH as a function of age in young/middle-aged adults (on the left) and in older adults (on the right), with regression linear curve; the scale of the y axis is different for the two groups. c Regional log-transformed WMH (frontal, parietal, temporal, occipital, and corpus callosum) as a function of age across the adult lifespanCC BY · PubMed Central

Fig. 2 Association between total WMH and cognition. Plots represent cognitive scores (episodic memory, processing speed, working memory, and executive functions) regressed onto total WMH, controlling for age, sex, level of education, and TIV. Uncorrected p values < 0.05 are in bold. *p < 0.05 after applying Bonferroni correctionCC BY · PubMed Central

Fig. 3 Association between total WMH and working memory in the subgroup of young/middle-aged adults and in the subgroup of older adults. Plots represent composite scores of working memory regressed onto total WMH, controlling for age, sex, level of education, and TIV, in young/middle-aged adults (N = 86, mean age 37.41 ± 12.85) on the left and in older adults (N = 51, mean age 71.20 ± 6.26) on the right. p values < 0.05 are in boldCC BY · PubMed Central

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He, H., Jiang, J. C., Peng, S., He, C., Sun, T., Fan, F., Song, H., Sun, D., Xu, Z., Wu, S., et al. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121279 · Cited by 9
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Tosun, D., Thropp, P., Southekal, S. S., Spottiswoode, B. S., Fahmi, R., & Initiative, A. D. N. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13164 · Cited by 9
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Xia, C., Lu, Y., Zhou, Z., Marchi, M., Kweon, H., Ning, Y., Liewald, D. C. M., Anderson, E. L., Koellinger, P., Cox, S. R., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03047-4 · Cited by 6
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Physical frailty and MRI markers of structural brain integrity in the community-dwelling late middle-aged and old adults
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Authors: Garnier-Crussard, A., Bougacha, S., Wirth, M., André, C., Delarue, M., Landeau, B., Mézenge, F., Kuhn, E., Gonneaud, J., Chocat, A., Quillard, A., Ferrand-Devouge, E., de La Sayette, V., Vivien, D., Krolak-Salmon, P., & Chételat, G.
Affiliations: Inserm (FR)
German Center for Neurodegenerative Diseases (DZNE) Dresden (DE)
Corresponding author: Chételat, Gaël
ORCID: Wirth, Miranka
André, Claire
Delarue, Marion
Landeau, Brigitte
Kuhn, Elizabeth
Gonneaud, Julie
Vivien, Denis
Chételat, Gaël
Venue: Alzheimer's Research & Therapy
Publisher: Springer Science and Business Media LLC
Published: 2020-10-08
Volume: 12
Issue: 1
Pages: 127-127
ISSN: 1758-9193 (ISSN-L)
DOI: 10.1186/s13195-020-00669-4
PMC: PMC7545576
OpenAlex: W3092538613
Cited by: 130
References: 54
Citations by year: 2026: 18 · 2025: 33 · 2024: 22 · 2023: 25 · 2022: 20 · 2021: 12
FWCI: 6.17
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Alzheimer s Research & Therapy (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
HAL (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
DZNE Pub (submittedVersion, other-oa)
Funders: Institut National de la Santé et de la Recherche Medicale
Programme Hospitalier de Recherche Clinique (PHRCN 2011-A01493-38, 2012 12-006-0347)
Agence Nationale de la Recherche
Fondation Plan Alzheimer
Fondation LECMA-Vaincre Alzheimer (13732)
Association France Alzheimer et maladies apparentées, the Région Basse-Normandie
Agence régionale de santé Auvergne-Rhône-Alpes
Horizon 2020 (667696)
Topics: Health Sciences › Medicine › Clinical Neurology › Cerebrovascular and genetic disorders
Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
Keywords: white matter hyperintensities, vascular risk factors, aging, executive function, working memory, episodic memory, processing speed, young and middle-aged adults, systolic blood pressure, HbA1c, cognitive aging
MeSH terms: Aged, Brain, Cognition, Humans, Longevity, Magnetic Resonance Imaging, Middle Aged, Neuropsychological Tests, White Matter

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White matter hyperintensities across the adult lifespan: relation to age, Aβ load, and cognition

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