[P4–134]: INSULIN RESISTANCE IS ASSOCIATED WITH REDUCTIONS IN SPECIFIC COGNITIVE DOMAINS AND INCREASES IN CSF TAU IN COGNITIVELY NORMAL ADULTS
Bibliographic record
Abstract
Growing evidence supports the notion that type 2 diabetes increases the risk of developing dementia. Experimental evidence from mouse models show that the induction of type 2 diabetes/insulin resistance can promote the accumulation of Alzheimer's disease (AD) pathological features. However, the association of type 2 diabetes with pathological and clinical phenotypes in humans is unclear. The overall aim of this study was to investigate if assessments of insulin resistance (HOMA-IR) or pancreatic β-cell function (HOMA-B) are altered across the course of AD and ascertain their associations with pathological and clinical expressions of AD in the Australian Imaging Biomarker and Lifestyle (AIBL) study. In this cross-sectional study, a calculated HOMA-IR index was compared between clinical groups (cognitively normal (CN), mild cognitive impairment (MCI), dementia (AD)) using analysis of covariance (ANCOVA). Associations between HOMA-IR and cognitive composite measures (Verbal Episodic Memory, Visual Episodic Memory, Executive Function, Language and Global composite scores) and pathological markers of AD (CSF Aβ42, CSF T-tau/P-tau, hippocampal volume and neocortical Aβ-amyloid burden), were investigated using linear regression. HOMA-IR (F=7.240, p=0.001) increased across clinical classification being elevated significantly in MCI and AD groups compared to CN. In CN adults higher HOMA-IR was associated with poorer performance on measures of verbal episodic memory (p=0.012), executive function (p=0.048) and global cognitive performance (p=0.008), higher CSF total tau levels (p=0.016). Associations with verbal episodic and global composites, in addition to T-tau, remained significant after correction for the false discovery rate. Together our data suggest that insulin resistance may be a contributing factor to AD development through impacting cognitive performance and accumulation of CSF biomarkers at early preclinical stages of the disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".