White Matter Microstructure Alterations in Older Adults With Dyslipidemia Associated With Cognitive and Locomotor Dysfunction Evaluated Using Neurite Orientation Dispersion and Density Imaging
Bibliographic record
Abstract
INTRODUCTION: Diffusion tensor imaging (DTI) studies have shown white matter (WM) microstructural alterations in individuals with dyslipidemia; however, DTI indices are not specific to WM pathology. However, neurite orientation dispersion and density imaging (NODDI) provides more specific measurements of WM microstructure. This study aimed to evaluate dyslipidemia-related WM microstructure alterations and their association with cognitive and motor functions using NODDI. METHODS: The DTI and NODDI metrics were analyzed through tract-based spatial statistics between 24 older adults with dyslipidemia (low-density lipoprotein ≥140 mg/dL, high-density lipoprotein <40 mg/dL, and triglyceride ≥150 mg/dL, or under treatment) and 18 healthy control participants (HCs). Partial correlation tests were performed between diffusion magnetic resonance imaging measures and lipid profiles, cognitive, or locomotor scores in the dyslipidemia and HC groups separately. WM volumetry between HCs and dyslipidemia groups was also assessed. Age, gender, intracranial volume, and years of education were included as covariates in all analyses. A false discovery rate-corrected P value of <0.05 was considered statistically significant. RESULTS: Individuals with dyslipidemia exhibited a notably reduced neurite density index (NDI) in several WM areas, including the posterior and superior corona radiata, the body, the genu, and the splenium of the corpus callosum, as well as the bilateral anterior and posterior internal capsule, compared with HCs. In the dyslipidemia group, lower NDI was significantly correlated with lower scores on the stand-up test and the Japanese version of the Montreal Cognitive Assessment. No significant differences were found in DTI metrics or WM volumes between dyslipidemia individuals and HCs. CONCLUSION: Our findings suggest that NODDI can serve as a biomarker for assessing WM microstructural alterations in older adults with dyslipidemia. Particularly, NODDI indicates a lower intra-axonal volume, which may suggest axonal loss associated with dyslipidemia, and correlates with cognitive and locomotor function decline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".