Thalamic nuclei atrophy at high and heterogenous rates during cognitively unimpaired human aging.


Journal

NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515

Informations de publication

Date de publication:
15 11 2022
Historique:
received: 13 03 2022
revised: 09 08 2022
accepted: 21 08 2022
pubmed: 26 8 2022
medline: 14 9 2022
entrez: 25 8 2022
Statut: ppublish

Résumé

The thalamus is a central integration structure in the brain, receiving and distributing information among the cerebral cortex, subcortical structures, and the peripheral nervous system. Prior studies clearly show that the thalamus atrophies in cognitively unimpaired aging. However, the thalamus is comprised of multiple nuclei involved in a wide range of functions, and the age-related atrophy of individual thalamic nuclei remains unknown. Using a recently developed automated method of identifying thalamic nuclei (3T or 7T MRI with white-matter-nulled MPRAGE contrast and THOMAS segmentation) and a cross-sectional design, we evaluated the age-related atrophy rate for 10 thalamic nuclei (AV, CM, VA, VLA, VLP, VPL, pulvinar, LGN, MGN, MD) and an epithalamic nucleus (habenula). We also used T1-weighted images with the FreeSurfer SAMSEG segmentation method to identify and measure age-related atrophy for 11 extra-thalamic structures (cerebral cortex, cerebral white matter, cerebellar cortex, cerebellar white matter, amygdala, hippocampus, caudate, putamen, nucleus accumbens, pallidum, and lateral ventricle). In 198 cognitively unimpaired participants with ages spanning 20-88 years, we found that the whole thalamus atrophied at a rate of 0.45% per year, and that thalamic nuclei had widely varying age-related atrophy rates, ranging from 0.06% to 1.18% per year. A functional grouping analysis revealed that the thalamic nuclei involved in cognitive (AV, MD; 0.53% atrophy per year), visual (LGN, pulvinar; 0.62% atrophy per year), and auditory/vestibular (MGN; 0.64% atrophy per year) functions atrophied at significantly higher rates than those involved in motor (VA, VLA, VLP, and CM; 0.37% atrophy per year) and somatosensory (VPL; 0.32% atrophy per year) functions. A proximity-to-CSF analysis showed that the group of thalamic nuclei situated immediately adjacent to CSF atrophied at a significantly greater atrophy rate (0.59% atrophy per year) than that of the group of nuclei located farther from CSF (0.36% atrophy per year), supporting a growing hypothesis that CSF-mediated factors contribute to neurodegeneration. We did not find any significant hemispheric differences in these rates of change for thalamic nuclei. Only the CM thalamic nucleus showed a sex-specific difference in atrophy rates, atrophying at a greater rate in male versus female participants. Roughly half of the thalamic nuclei showed greater atrophy than all extra-thalamic structures examined (0% to 0.54% per year). These results show the value of white-matter-nulled MPRAGE imaging and THOMAS segmentation for measuring distinct thalamic nuclei and for characterizing the high and heterogeneous atrophy rates of the thalamus and its nuclei across the adult lifespan. Collectively, these methods and results advance our understanding of the role of thalamic substructures in neurocognitive and disease-related changes that occur with aging.

Identifiants

pubmed: 36007822
pii: S1053-8119(22)00699-1
doi: 10.1016/j.neuroimage.2022.119584
pmc: PMC9787236
mid: NIHMS1837022
pii:
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

119584

Subventions

Organisme : NIA NIH HHS
ID : K99 AG075184
Pays : United States
Organisme : NINDS NIH HHS
ID : UH3 NS095554
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG066515
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG058859
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG048076
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG058111
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR026351
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG065255
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR003142
Pays : United States

Informations de copyright

Copyright © 2022. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None

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Auteurs

Eun Young Choi (EY)

Department of Neurosurgery, Stanford University, 300 Pasteur Drive, MC5327, Stanford, CA 94305, USA.

Lu Tian (L)

Department of Biomedical Data Science, 1265 Welch Road, MC5464, Stanford, CA 94305, USA.

Jason H Su (JH)

Department of Radiology, Stanford University, 300 Pasteur Drive, MC5488, Stanford, CA 94305, USA; Department of Electrical Engineering, Stanford University, 350 Jane Stanford Way, MC9505, Stanford, CA 94305, USA.

Matthew T Radovan (MT)

Department of Computer Science, Stanford University, 353 Jane Stanford Way, MC9025, Stanford, CA 94305, USA.

Thomas Tourdias (T)

Department of Neuroradiology, Bordeaux University Hospital, Bordeaux, France; INSERM U1215, Neurocentre Magendie, University of Bordeaux, France.

Tammy T Tran (TT)

Department of Psychology, Stanford University, Building 420, MC2130, Stanford, CA 94305, USA.

Alexandra N Trelle (AN)

Department of Psychology, Stanford University, Building 420, MC2130, Stanford, CA 94305, USA.

Elizabeth Mormino (E)

Department of Neurology and Neurological Sciences, Stanford, University, 300 Pasteur Drive, MC5235, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, USA.

Anthony D Wagner (AD)

Department of Psychology, Stanford University, Building 420, MC2130, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, USA.

Brian K Rutt (BK)

Department of Radiology, Stanford University, 300 Pasteur Drive, MC5488, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, USA. Electronic address: brutt@stanford.edu.

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Classifications MeSH