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<p>Cross-sectional data from a sample of older adults with obesity was used to determine how peripheral insulin resistance (PIR) and neuronal insulin signaling abnormalities (NISAs) relate to executive function and functional brain network topology. Older adults (n = 71) with obesity but without type 2 diabetes were included. PIR was quantified by HOMA2-IR. NISAs were quantified according to an established neuron-derived small-extracellular-vesicle-based metric, R. An executive function composite score, summed scores to the Auditory Verbal Learning Test (AVLT) trials 1–5, and functional brain networks generated from resting-state functional magnetic resonance imaging data were outcomes in analyses. We used general linear models and a novel regression framework for brain network analysis to identify relationships between insulin-related biomarkers and brain-related outcomes. HOMA2-IR, but not R, was negatively associated with executive function. Neither measure was associated with AVLT score. HOMA2-IR was also related to hippocampal network topology in participants who had undergone functional neuroimaging. Neither HOMA2-IR nor R were significantly related to network topology of the central executive network. This study provides further evidence that PIR is associated with aging brain function. NISAs were not found to be related to PIR, cognition, or functional brain network topology.</p>

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Insulin resistance, cognition, and functional brain network topology in older adults with obesity

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月2日

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  • Clayton C. McIntyre,
  • Robert G. Lyday,
  • Yixin Su,
  • Barbara Nicklas,
  • Sean L. Simpson,
  • Gagan Deep,
  • Shannon L. Macauley,
  • Christina E. Hugenschmidt

摘要

Cross-sectional data from a sample of older adults with obesity was used to determine how peripheral insulin resistance (PIR) and neuronal insulin signaling abnormalities (NISAs) relate to executive function and functional brain network topology. Older adults (n = 71) with obesity but without type 2 diabetes were included. PIR was quantified by HOMA2-IR. NISAs were quantified according to an established neuron-derived small-extracellular-vesicle-based metric, R. An executive function composite score, summed scores to the Auditory Verbal Learning Test (AVLT) trials 1–5, and functional brain networks generated from resting-state functional magnetic resonance imaging data were outcomes in analyses. We used general linear models and a novel regression framework for brain network analysis to identify relationships between insulin-related biomarkers and brain-related outcomes. HOMA2-IR, but not R, was negatively associated with executive function. Neither measure was associated with AVLT score. HOMA2-IR was also related to hippocampal network topology in participants who had undergone functional neuroimaging. Neither HOMA2-IR nor R were significantly related to network topology of the central executive network. This study provides further evidence that PIR is associated with aging brain function. NISAs were not found to be related to PIR, cognition, or functional brain network topology.