48 Sex Differences and Longitudinal Changes in White Matter Microstructure in Healthy Older Adults
Bibliographic record
Abstract
Objective: As the global population of older adults increases, it is crucial to study the healthy aging brain. Despite representing approximately 50% of brain tissue, investigations of changes in white matter (WM) have been limited. Given that women outlive men in most populations worldwide, evaluating factors such as sex and gender in the normal aging trajectory are particularly important. However, past research has been limited by varying definitions of these terms and methodological challenges. Further, limited studies have employed longitudinal designs. The objective of the present study was to 1) compare sex similarities and differences in WM microstructure, and 2) investigate longitudinal changes in WM in healthy older adults. The Parkinson’s Progression Markers Initiative (PPMI) is an ongoing observational longitudinal study designed to investigate biomarkers related to Parkinson’s disease. For up-to-date information, please see: https://www.ppmi-info.org/. The PPMI study presents a convenient opportunity to investigate the expected aging trajectory among healthy older adults by using data from its healthy control cohort. Participants and Methods: Participants (N=40) included 16 females (mean age = 60.50 + 5.99) and 24 males (mean age = 65.50 + 7.53) from the healthy control cohort of the PPMI. Diffusion tensor imaging (DTI) data from two time points (baseline and approximately one year later) were analyzed using tract-based spatial statistics from the FMRIB Software Library (FSL). Diffusion weighted images were acquired with a Siemens 3T TIM Trio scanner with a 12 channel Matrix head coil. All images were acquired with a spin echo, echo planar imaging sequence with 64 gradient directions and a b-value of 1000s/mm2 with a voxel size of 2 mm3. Two analyses were conducted: 1) between-groups, comparing differences in WM microstructure between males and females at baseline while controlling for age and total brain volume (TBV), and 2) within-subject, examining longitudinal changes in WM from baseline to one year later. DTI metrics included fractional anisotropy (FA) and mean diffusivity (MD). Results: Males were significantly older than females and had significantly larger TBVs. Results of voxelwise comparisons revealed no statistically significant differences in FA or MD between males and females when controlling for age and TBV. Longitudinally over one year, decreases in MD (p<.05, corrected) were found in the right superior and inferior longitudinal fasciculus, the right corticospinal tract, and the right inferior fronto-occipital fasciculus. Stability in FA was observed over one year. There was also an average of a one-point decline on the Montreal Cognitive Assessment during the study period of one year. Conclusions: No significant sex differences in WM microstructure were found, which agrees with a published review of the literature that men and women show very similar brain structure after accounting for brain size differences. Across the entire sample, longitudinal changes in WM were captured via neuroimaging across a one-year time frame. Follow-up exploration of these data suggests great intraindividual variability in trajectories over time, which may have affected the overall group trajectory. Continued research of factors that contribute to the identifying individual healthy aging trajectories is warranted.
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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 | 0.000 |
| 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) | 0.003 | 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".