Associations Between Insulin-Like Growth Factor-1 and Resting-State Functional Connectivity in Cognitively Unimpaired Midlife Adults.
Alzheimer’s disease
cognitive dysfunction
functional MRI
insulin-like growth factor-1
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
2023
Historique:
medline:
1
8
2023
pubmed:
31
1
2023
entrez:
30
1
2023
Statut:
ppublish
Résumé
Insulin-like growth factor (IGF)-1 plays an important role in Alzheimer's disease (AD) pathogenesis and increases disease risk. However, prior research examining IGF-1 levels and brain neural network activity is mixed. The present study investigated the relationship between IGF-1 levels and 21 neural networks, as measured by functional magnetic resonance imaging (fMRI) in 13,235 UK Biobank participants. Linear mixed models were used to regress IGF-1 against the intrinsic functional connectivity (i.e., degree of network activity) for each neural network. Interactions between IGF-1 and AD risk factors such as Apolipoprotein E4 (APOE4) genotype, sex, AD family history, and age were also tested. Higher IGF-1 was associated with more network activity in the right Executive Function neural network. IGF-1 interactions with APOE4 or sex implicated motor, primary/extrastriate visual, and executive function related neural networks. Neural network activity trends with increasing IGF-1 were different in different age groups. Higher IGF-1 levels relate to much more network activity in the Sensorimotor Network and Cerebellum Network in early-life participants (40-52 years old), compared with mid-life (52-59 years old) and late-life (59-70 years old) participants. These findings suggest that sex and APOE4 genotype may modify the relationship between IGF-1 and brain network activities related to visual, motor, and cognitive processing. Additionally, IGF-1 may have an age-dependent effect on neural network connectivity.
Sections du résumé
BACKGROUND
Insulin-like growth factor (IGF)-1 plays an important role in Alzheimer's disease (AD) pathogenesis and increases disease risk. However, prior research examining IGF-1 levels and brain neural network activity is mixed.
OBJECTIVE
The present study investigated the relationship between IGF-1 levels and 21 neural networks, as measured by functional magnetic resonance imaging (fMRI) in 13,235 UK Biobank participants.
METHODS
Linear mixed models were used to regress IGF-1 against the intrinsic functional connectivity (i.e., degree of network activity) for each neural network. Interactions between IGF-1 and AD risk factors such as Apolipoprotein E4 (APOE4) genotype, sex, AD family history, and age were also tested.
RESULTS
Higher IGF-1 was associated with more network activity in the right Executive Function neural network. IGF-1 interactions with APOE4 or sex implicated motor, primary/extrastriate visual, and executive function related neural networks. Neural network activity trends with increasing IGF-1 were different in different age groups. Higher IGF-1 levels relate to much more network activity in the Sensorimotor Network and Cerebellum Network in early-life participants (40-52 years old), compared with mid-life (52-59 years old) and late-life (59-70 years old) participants.
CONCLUSION
These findings suggest that sex and APOE4 genotype may modify the relationship between IGF-1 and brain network activities related to visual, motor, and cognitive processing. Additionally, IGF-1 may have an age-dependent effect on neural network connectivity.
Identifiants
pubmed: 36710671
pii: JAD220608
doi: 10.3233/JAD-220608
pmc: PMC10473072
doi:
Substances chimiques
Apolipoprotein E4
0
Insulin-Like Growth Factor I
67763-96-6
IGF1 protein, human
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
S309-S318Subventions
Organisme : NIA NIH HHS
ID : R00 AG047282
Pays : United States
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