Metabolic and Vascular Risk Factor Variability Over 25 Years Relates to Midlife Brain Volume and Cognition.

Humans Male Female Cognition / physiology Brain / diagnostic imaging Risk Factors Cognitive Dysfunction / diagnostic imaging Blood Pressure / physiology Magnetic Resonance Imaging / methods
Brain volume cognition metabolic syndrome partial least squares vascular risk factors

Journal

Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863

Informations de publication

Date de publication:
2023
Historique:
entrez: 23 1 2023
pubmed: 24 1 2023
medline: 25 1 2023
Statut: ppublish

Résumé

Metabolic and vascular risk factors (MVRF) are associated with neurodegeneration and poor cognition. There is a need to better understand the impact of these risk factors on brain health in the decades that precede cognitive impairment. Longitudinal assessments can provide new insight regarding changes in MVRFs that are related to brain imaging features. To investigate whether longitudinal changes in MVRF spanning up to 25 years would be associated with midlife brain volume and cognition. Participants were from the CARDIA study (N = 467, age at year 25 = 50.6±3.4, female/male = 232/235, black/white = 161/306). Three models were developed, each designed to capture change over time; however, we were primarily interested in the average real variability (ARV) as a means of quantifying MVRF variability across all available assessments. Multivariate partial least squares that used ARV metrics identified two significant latent variables (partial correlations ranged between 0.1 and 0.26, p < 0.01) that related MVRF ARV and regional brain volumes. Both latent variables reflected associations between brain volume and MVRF ARV in obesity, cholesterol, blood pressure, and glucose. Subsequent bivariate correlations revealed associations among MVRF factors, aggregate brain volume and cognition. This study demonstrates that MVRF variability over time is associated with midlife brain volume in regions that are relevant to later-life cognitive decline.

Sections du résumé

BACKGROUND BACKGROUND
Metabolic and vascular risk factors (MVRF) are associated with neurodegeneration and poor cognition. There is a need to better understand the impact of these risk factors on brain health in the decades that precede cognitive impairment. Longitudinal assessments can provide new insight regarding changes in MVRFs that are related to brain imaging features.
OBJECTIVE OBJECTIVE
To investigate whether longitudinal changes in MVRF spanning up to 25 years would be associated with midlife brain volume and cognition.
METHODS METHODS
Participants were from the CARDIA study (N = 467, age at year 25 = 50.6±3.4, female/male = 232/235, black/white = 161/306). Three models were developed, each designed to capture change over time; however, we were primarily interested in the average real variability (ARV) as a means of quantifying MVRF variability across all available assessments.
RESULTS RESULTS
Multivariate partial least squares that used ARV metrics identified two significant latent variables (partial correlations ranged between 0.1 and 0.26, p < 0.01) that related MVRF ARV and regional brain volumes. Both latent variables reflected associations between brain volume and MVRF ARV in obesity, cholesterol, blood pressure, and glucose. Subsequent bivariate correlations revealed associations among MVRF factors, aggregate brain volume and cognition.
CONCLUSION CONCLUSIONS
This study demonstrates that MVRF variability over time is associated with midlife brain volume in regions that are relevant to later-life cognitive decline.

Identifiants

DOI: 10.3233/JAD-220340 PMID: 36683514
pubmed: 36683514
pii: JAD220340
doi: 10.3233/JAD-220340
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

627-635

Auteurs

Zahra Shirzadi (Z)

Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.

Jennifer Rabin (J)

Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Toronto, ON, Canada.
Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada.
Rehabilitation Sciences, University of Toronto, Toronto, ON, Canada.

Lenore J Launer (LJ)

Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD, USA.

R Nick Bryan (RN)

Department of Diagnostic Medicine, University of Texas, Austin, TX, USA.

Abdulla Al-Ozairi (A)

Dasman Diabetes Institute, Kuwait City, Kuwait.

Jasmeer Chhatwal (J)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Ebaa Al-Ozairi (E)

Dasman Diabetes Institute, Kuwait City, Kuwait.

John A Detre (JA)

Center for Functional Neuroimaging, University of Pennsylvania, Philadelphia, PA, USA.

Sandra E Black (SE)

Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada.

Walter Swardfager (W)

Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada.
KITE, UHN-Toronto Rehab, Toronto, ON, Canada.

Bradley J MacIntosh (BJ)

Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Hurvitz Brain Sciences, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Metabolic and Vascular Risk Factor Variability...
questionsmedicales.fr › Phénomènes psychologiques › Processus mentaux › Cognition › Metabolic and Vascular Risk Factor Variability...
questionsmedicales.fr › Système nerveux › Système nerveux central › Encéphale › Metabolic and Vascular Risk Factor Variability...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Risque › Facteurs de risque › Metabolic and Vascular Risk Factor Variability...
questionsmedicales.fr › Troubles mentaux › Troubles neurocognitifs › Troubles de la cognition › Dysfonctionnement cognitif › Metabolic and Vascular Risk Factor Variability...
questionsmedicales.fr › Phénomènes physiologiques respiratoires et circulatoires › Phénomènes physiologiques cardiovasculaires › Hémodynamique › Pression sanguine › Metabolic and Vascular Risk Factor Variability...
questionsmedicales.fr › Diagnostic › Techniques et procédures diagnostiques › Imagerie diagnostique › Tomographie › Imagerie par résonance magnétique › Metabolic and Vascular Risk Factor Variability...