48 Sex Differences and Longitudinal Changes in White Matter Microstructure in Healthy Older Adults
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».