RESUMO
BACKGROUND: A coordinated network of circulating inflammatory molecules centered on the pleotropic pro-atherogenic cytokine interleukin-18 (IL-18) is linked to cerebral small vessel disease. We sought to validate the association of this inflammatory biomarker network with incident stroke risk, cognitive impairment, and imaging metrics in a sample of the Framingham Offspring Cohort. METHODS: Using available baseline measurements of serum levels of IL-18, GDF (growth and differentiation factor)-15, soluble form of receptor for advanced glycation end products, myeloperoxidase, and MCP-1 (monocyte chemoattractant protein-1) from Exam 7 of the Framingham Offspring Cohort (1998-2001), we constructed a population-normalized, equally weighted log-transformed mean Z-score value representing the average level of each serum analyte to create an inflammatory composite score (ICS5). Multivariable regression models were used to determine the association of ICS5 with incident stroke, brain magnetic resonance imaging features, and cognitive testing performance. RESULTS: We found a significant association between ICS5 score and increased risk for incident all-cause stroke (hazard ratio, 1.48 [95% CI, 1.05-2.08]; P=0.024) and ischemic stroke (hazard ratio, 1.51 [95% CI, 1.03-2.21]; P=0.033) in the Exam 7 cohort of 2201 subjects (mean age 62±9 years; 54% female) aged 45+ years with an all-cause incident stroke rate of 6.1% (135/2201) and ischemic stroke rate of 4.9% (108/2201). ICS5 and its component serum markers are all associated with the Framingham Stroke Risk Profile score (ß±SE, 0.19±0.02; P<0.0001). In addition, we found a significant inverse association of ICS5 with a global cognitive score, derived from a principal components analysis of the neuropsychological battery used in the Framingham cohort (-0.08±0.03; P=0.019). No association of ICS5 with magnetic resonance imaging metrics of cerebral small vessel disease was observed. CONCLUSIONS: Circulating serum levels of inflammatory biomarkers centered on IL-18 are associated with an increased risk of stroke and cognitive impairment in the Framingham Offspring Cohort. Linking specific inflammatory pathways to cerebral small vessel disease may enhance individualized quantitative risk assessment for future stroke and vascular cognitive impairment.
Assuntos
Biomarcadores , Inflamação , Interleucina-18 , Acidente Vascular Cerebral , Humanos , Masculino , Feminino , Biomarcadores/sangue , Acidente Vascular Cerebral/sangue , Acidente Vascular Cerebral/epidemiologia , Acidente Vascular Cerebral/diagnóstico por imagem , Pessoa de Meia-Idade , Interleucina-18/sangue , Idoso , Inflamação/sangue , Estudos de Coortes , Incidência , Fatores de Risco , Imageamento por Ressonância Magnética , Disfunção Cognitiva/sangue , Disfunção Cognitiva/epidemiologia , Disfunção Cognitiva/diagnóstico por imagemRESUMO
BACKGROUND: Education level is a well-recognized co-factor for cognitive performance and a potential confounder in the application of cognitive evaluations in diverse populations. The Montreal Cognitive Assessment (MoCA) is a widely utilized screening tool for Mild Cognitive Impairment (MCI) composed of 6 domains of cognition: Executive Function (EFC), Attention and Concentration (AC), Language (LANG), Visuospatial (VIS), Memory (MEM), and Orientation (ORIEN). Education is currently accounted for globally by adding 1 point to the total MoCA score. This study considers the impact of education level on a domain-specific scoring of the MoCA. METHOD: We utilized longitudinal subject level data from one site within the MarkVCID Consortium (UCSF) composed of 578 subjects (59.5% female; 82.9% white), mean age 71.5 (+/- 8.7). Mean educational level was 15.3 (+/-4.7) years. Within the cohort, 37 subjects lacked educational level and were omitted (final n = 541). Multivariate linear regression models were used to relate educational level with total and domain specific MoCA score performance at baseline while controlling for the influence of age, sex, and recognized MarkVCID biomarkers that impact cognitive performance including white matter hyperintensity (logWMH), fractional anisotropy (FA), free water (FW), and peak width of skeletonized mean diffusivity (PSMD). RESULTS: An age-, sex-adjusted model replicated a significant association of education level with MoCA total score (p<0.001, b = .336). Among the MoCA domains, EFC was most affected by education level (p<.001, b = .412), followed by AC (p<.001, b = .352). Other MoCA domains were not significantly associated with educational level. Several MoCA domains, namely MEM and ORIEN, showed an association with MarkVCID biomarkers including WMH and FW (p-values <.001). In regression models controlled for MarkVCID imaging biomarkers, educational level remained significantly associated with total and domain-specific MoCA performance. CONCLUSION: Education does not equally contribute to all cognitive domains assessed by the MoCA, mostly affecting EFC and AC. These findings suggest that considering education level in a domain-specific manner could provide a more accurate interpretation of the cognitive impairment.