Associations Between Insulin-Like Growth Factor-1 and Resting-State Functional Connectivity in Cognitively Unimpaired Midlife Adults.
Associations Between Insulin-Like Growth Factor-1 and Resting-State Functional Connectivity in Cognitively Unimpaired Midlife Adults.
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DOI：
10.3233/jad-220608
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Willette AA
中科院分区：
文献类型：
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作者：
Li T;Pappas C;Klinedinst B;Pollpeter A;Larsen B;Hoth N;Anton F;Wang Q;Willette AA
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.
