| Title: | Cross-sectional associations of insulin resistance surrogate indices with cognitive disorders and cognitive performance in UK Biobank. |
| Journal: | Journal of Alzheimer's Disease |
| Published: | 14 Oct 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42873210/ |
| DOI: | https://doi.org/10.1177/13872877261494125 |
Publication 21529
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Abstract
BackgroundWhile systemic insulin resistance (IR) is a well-established risk factor for Alzheimer's disease (AD), its connections to broader cognitive conditions, particularly mild cognitive impairment (MCI) and specific cognitive domains, remain unclear.ObjectiveThis study aims to explore the associations between IR surrogates and cognitive status, including AD, MCI, and normal cognition (NC) group, and to assess their association with domain-specific cognitive functions.MethodsData from 381,818 UK Biobank participants were analyzed. Logistic regression was used to assess relationships between IR surrogates-the triglyceride-glucose (TyG) index, TyG-waist-to-height ratio (TyG-WHtR), and triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio-and cognitive groups (AD, MCI, NC). Domain-specific cognitive functions, including prospective memory (PM) and reaction time (RT), were evaluated using multivariable linear regression, logistic models, and restricted cubic splines.ResultsTyG-WHtR was independently associated with MCI (adjusted odds ratio [OR] = 1.166, 95% CI: 1.084-1.255, p < 0.001). Elevated TG/HDL-C and TyG-WHtR were both linked to slower RT (ORs > 1, p < 0.05), whereas RCS analysis revealed an inverted M-shaped nonlinear association between TyG and mean RT. All IR surrogates were significantly associated with poorer PM performance (ORs < 1, p < 0.05).ConclusionsThis study suggests that elevated TyG-WHtR levels are independently associated with MCI. Higher TG/HDL-C and TyG-WHtR correlate with slower processing speed, with TyG showing a unique nonlinear progression. All IR indices are also associated with poorer PM performance, suggesting potential metabolic markers linked with cognitive performance.</p>
13 Authors
- Zhinan Ye
- Xiaoya Xie
- Shiyue Wang
- Jiawen Chen
- Bo Zhang
- Jiaxuan Chen
- Bingxin Teng
- Ruting Wei
- Bohao Li
- Qihan Zhang
- Suwen Huang
- Yiyun Weng
- Dehao Yang
1 Application
| Application ID | Title |
|---|---|
| 151172 | Multimodal Analysis of Genetic and Neuroimaging Data for Parkinson's disease or Atypical Parkinsonism. |
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