Association of systemic inflammatory markers with white matter hyperintensities and microstructural injury: an analysis of UK Biobank data
Notice bibliographique
Résumé
BACKGROUND: White matter damage is closely associated with cognitive and psychiatric symptoms and is prevalent in cerebral small vessel disease (CSVD); although the pathophysiological mechanisms involved in CSVD remain elusive, inflammation plays a crucial role. We sought to investigate the relationship between systemic inflammation markers and imaging markers of CVSD, namely white matter hyperintensity (WMH) and microstructural injury. METHODS: We conducted a study involving both cross-sectional and longitudinal data from the UK Biobank Cohort. We performed multiple linear regression analyses, adjusted for potential confounders, to explore the associations between systemic inflammation markers (e.g., systemic immune-inflammation index [SII], neutrophil-to-lymphocyte ratio [NLR], C-reactive protein [CRP] levels, monocyte count, neutrophil count) and macro- and microstructural white matter injury, as markers of CSVD. We performed Mendelian randomization analysis to investigate the genetically predictive effect of monocytes on WMH, as well as mediation analysis to clarify whether inflammatory markers affected cognitive function via white matter injury. RESULTS: We included 36 411 participants (mean age 54.8 ± 7.5 yr, 51.9% female) from the UK Biobank Cohort. We found that SII was significantly associated with both WMH and microstructural injury markers (fractional anisotropy, mean diffusivity, intracellular volume fraction, and isotropic compartment volume fraction [ISOVF]), and the neutrophil-to-lymphocyte ratio was significantly associated with WMH and some markers of microstructural injury (mean diffusivity and ISOVF). Our analysis revealed that the CRP level was significantly associated with WMH and WMH progression but not with microstructural injury. We also demonstrated that monocyte count was significantly associated with WMH and ISOVF, and that neutrophil count was significantly associated with WMH, mean diffusivity, and ISOVF. In 2-sample Mendelian randomization analyses, we found positive associations between genetic determinants of monocytes and WMH. The mediating role of WMH suggested that a higher SII value and monocyte count could contribute to cognitive impairment through white matter injury. LIMITATIONS: Although the study includes both cross-sectional and longitudinal components, the sample size for the longitudinal aspect is limited, and the use of blood biomarkers from a single timepoint is also a limitation of this research. CONCLUSION: The SII and neutrophil-to-lymphocyte ratio may be early detection markers for white matter damage in patients with CSVD, whereas the CRP level is more closely associated with disease severity and progression. Our findings highlight the clinical relevance of systemic inflammation markers with white matter macro- and microstructural injuries, revealing that systemic inflammation is likely involved in the mechanism of early white matter injury among patients with CSVD.
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 | 0,004 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».