Associations between iron deposition in the brain and grey matter volumes in cognitively unimpaired adults
Bibliographic record
Abstract
Abstract Background Iron dyshomeostasis is involved in the pathophysiology of Alzheimer’s disease (AD). Magnetic resonance imaging (MRI) is sensitive to iron in the brain as its concentration decreases the intensity of T2‐weighted images. However, there is little evidence on how iron affects structural changes in the brain of cognitively unimpaired individuals at the inception of the Alzheimer’s continuum. This research aimed to investigate the relationship between T2 MR hypointensities, as a proxy for iron content, and grey matter volume (GMv) in middle‐aged cognitively unimpaired (CU) individuals. Methods This cross‐sectional study included 302 CU adults from the ALFA+ cohort who underwent MRI, cerebrospinal fluid sampling (CSF) and neuropsychological assessment (Table 1). T2‐weighted images were used to calculate mean hypointensity values in a set of 18 subcortical nuclei ( http://nist.mni.mcgill.ca/?p=1209 ). T1w scans were entered into voxel‐based morphometry (VBM) analysis to evaluate the relationship between regional T2 intensities and GM volumes. Due to the strong correlations between the T2 intensity of the subcortical regions, we performed principal component analysis (PCA) to reduce the dimensionality (Table 2). We created a general linear model where GMv was the dependent variable, the first principal component (PC1) was the independent variable and age, sex, APOE‐ε4 status, education level and total intracranial volume (TIV) were the covariates. In an additional model, CSF levels of amyloid‐beta (Aβ) ratio (CSF Aβ42/40) and phosphorylated tau (p‐tau) were entered as covariates. Statistical significance was set at p<0.001 uncorrected for multiple comparisons with a cluster‐level threshold of 100. Results PC1 explained 47.64% of the variance, and it was significantly and negatively associated with grey matter volumes in a highly symmetrical pattern which included the parahippocampal cortex (Table 3. Figure 1). These results remained largely unchanged when entering CSF AD biomarkers in the model. Conclusions Our results indicate that, in cognitively unimpaired individuals, a higher content of iron deposition, as expressed by lower T2‐weighted MR intensities in subcortical regions, are associated with higher grey matter volumes in parahippocampus, independently of CSF AD biomarkers. These preliminary results may suggest that iron accumulation might be associated with neuroinflammatory mechanisms and render the brain more vulnerable to early AD pathology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".