White Matter Hyperintensity Increase in Chronic Heart Failure and Its Association with Proteomic Markers: A Longitudinal Cohort Study
Notice bibliographique
Résumé
Abstract Background White matter hyperintensity (WMH) is a common cerebral finding in older adults and is associated with an increased risk of neurological diseases, including stroke and dementia. Chronic heart failure (CHF) leads to hypoperfusion of multiple organs, including the brain, and alters neurohumoral factors such as the renin-angiotensin-aldosterone system and inflammatory cytokines. However, the relationship between CHF and WMH progression remains unclear. Purpose This study aimed to determine whether WMH differs between patients with and without CHF and to explore its association with neurohumoral factors. Methods Longitudinal data from 3D-T2 structural brain MRI and plasma samples were analyzed in 32 patients with Stage B CHF (mean age 63.3 ± 10.5 years; 21.5% women) and 23 patients with Stage C CHF (mean age 67.3 ± 7.1 years; 30.4% women) over a mean follow-up period of 3.1 years. WMH volumes were delineated from T2 images using MRI-based image analysis. The segmented WMH volumes were normalized to the Montreal Neurological Institute standard space, a commonly used brain template that allows for anatomical comparisons across individuals. Voxel-wise analysis, adjusted for age, sex, and intracranial volume, was conducted to identify regions with significant WMH changes between Stage B and C patients. Proteomic analysis using Somascan v4.1 (targeting over 7,000 proteins) was performed to identify proteins associated with both Stage C CHF and WMH changes, adjusting for age and sex. Mendelian randomization (MR) analysis was applied to assess potential causal associations between identified proteins and both Stage C CHF and WMH changes. Statistical significance was set at P<0.05, with voxel-wise analyses corrected for multiple comparisons using the family-wise error method. Results Baseline characteristics, including WMH volumes, did not significantly differ between Stage B and C patients (Stage B vs. C: 7,151 ± 9,387 mm³ vs. 10,113 ± 13,646 mm³; P>0.05). However, global WMH volumes increased significantly in Stage C compared to Stage B patients (2,116 ± 3,134 mm³ vs. 4,717 ± 5,334 mm³; P=0.027) (Figure A). Changes in WMH volumes were mapped (Figure B: Stage B; Figure C: Stage C), with voxel-wise analysis revealing increased WMH in the anterior corpus callosum (corrected P<0.05; Figure D [green regions]). Proteomic analysis identified 44 proteins associated with both Stage C CHF and WMH changes (P<0.05; Figure D). MR analysis indicated that inosine triphosphate pyrophosphatase (ITPA) showed causal associations with both WMH changes and Stage C CHF (P<0.05), with a trend toward significance for the association from ITPA to WMH change (P=0.092; Figure E). Conclusions These findings suggest that CHF may contribute to WMH progression, potentially mediated by ITPA. Humoral mediators such as ITPA could represent novel therapeutic targets in the brain-heart axis, potentially aiding in the prevention of stroke and dementia in patients with CHF.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».