Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals.


Journal

Aging and disease
ISSN: 2152-5250
Titre abrégé: Aging Dis
Pays: United States
ID NLM: 101540533

Informations de publication

Date de publication:
28 Aug 2023
Historique:
received: 23 04 2023
accepted: 18 08 2023
medline: 20 9 2023
pubmed: 20 9 2023
entrez: 20 9 2023
Statut: aheadofprint

Résumé

Abdominal fat is increasingly linked to brain health. A total of 10,001 healthy participants were scanned on 1.5T MRI with a short whole-body MR imaging protocol. Deep learning with FastSurfer segmented 96 brain regions. Separate models segmented visceral and subcutaneous abdominal fat. Regression analyses of abdominal fat types and normalized brain volumes were evaluated, controlling for age and sex. Logistic regression models determined the risk of brain total gray and white matter volume loss from the highest quartile of visceral fat and lowest quartile of these brain volumes. This cohort had an average age of 52.9 ± 13.1 years with 52.8% men and 47.2% women. Segmented visceral abdominal fat predicted lower volumes in multiple regions including: total gray matter volume (r = -.44, p<.001), total white matter volume (r =-.41, p<.001), hippocampus (r = -.39, p< .001), frontal cortex (r = -.42, p<.001), temporal lobes (r = -.44, p<.001), parietal lobes (r = -.39, p<.001), occipital lobes (r =-.37, p<.001). Women showed lower brain volumes than men related to increased visceral fat. Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 5.9; age 40-59, OR = 5.4; 60-80, OR = 5.1) and low white matter volume: (age 20-39: OR = 3.78; age 40-59, OR = 4.4; 60-80, OR = 5.1). Higher subcutaneous fat is related to brain volume loss. Elevated visceral and subcutaneous fat predicted lower brain volumes and may represent novel modifiable factors in determining brain health.

Identifiants

pubmed: 37728587
pii: AD.2023.0820
doi: 10.14336/AD.2023.0820
doi:

Types de publication

Journal Article

Langues

eng

Auteurs

Cyrus A Raji (CA)

Mallinckrodt Institute of Radiology, Neuroradiology Division, Washington University in St. Louis, MO, USA.

Somayeh Meysami (S)

Pacific Brain Health Center, Pacific Neuroscience Institute and Foundation, Santa Monica, CA, USA.
Saint John's Cancer Institute, Providence Saint John's Health Center, Santa Monica, CA, USA.

Sam Hashemi (S)

Prenuvo, Vancouver, Canada.
Voxelwise Imaging Technology, Vancouver, Canada.

Saurabh Garg (S)

Prenuvo, Vancouver, Canada.
Voxelwise Imaging Technology, Vancouver, Canada.

Nasrin Akbari (N)

Prenuvo, Vancouver, Canada.
Voxelwise Imaging Technology, Vancouver, Canada.

Ahmed Gouda (A)

Prenuvo, Vancouver, Canada.
Voxelwise Imaging Technology, Vancouver, Canada.

Yosef Gavriel Chodakiewitz (YG)

Prenuvo, Vancouver, Canada.

Thanh Duc Nguyen (TD)

Prenuvo, Vancouver, Canada.
Voxelwise Imaging Technology, Vancouver, Canada.

Kellyann Niotis (K)

Early Medical, Boca Raton, FL, USA.
Institute of Neurodegenerative Diseases-Parkinson's & Alzheimer's Research Education Foundation, Boca Raton, FL, USA.

David A Merrill (DA)

Pacific Brain Health Center, Pacific Neuroscience Institute and Foundation, Santa Monica, CA, USA.
Providence Saint John's Health Center, Santa Monica, CA, USA.
Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

Rajpaul Attariwala (R)

AIM Medical Imaging, Vancouver, Canada.
Prenuvo, Vancouver, Canada.
Voxelwise Imaging Technology, Vancouver, Canada.

Classifications MeSH