Utility of combined inflammatory biomarkers for the identification of cognitive dysfunction in non-diabetic participants of the ELSA-Brasil. (May 2019)

• Record Type: Journal Article
• Authors: Cezaretto, Adriana; Almeida-Pititto, Bianca de; Alencar, Gizelton Pereira; Suemoto, Claudia K.; Bensenor, Isabela; Lotufo, Paulo A.; Ferreira, Sandra R.G.
• Is Part Of: Psychoneuroendocrinology. Volume 103(2019)
• Page Start: 61
• Page End: 66
• Publication Date: 2019-05
• Subjects: Cognitive function -- Prediabetes -- Subclinical inflammation -- Cluster analysis -- Dementia -- Prevention; Psychoneuroendocrinology -- Periodicals; Endocrinology -- Periodicals; Neurology -- Periodicals; Psychiatry -- Periodicals; Neuropsychoendocrinologie -- Périodiques; 616.8
• DOI: 10.1016/j.psyneuen.2019.01.003
• Languages: English
• ISSNs: 0306-4530

Abstract

Highlights: Novel biomarkers are able to detect earlier dementia signals. Higher risk individuals could be identify by inflammatory cluster. Preventive strategies are more effective to avoid dementia in high-risk individuals. Abstract: Introduction: Insulin resistance and low-grade inflammation are pathophysiological mechanisms shared by type 2 diabetes and dementia. A cluster of biomarkers that could help diagnosing cognitive dysfunction prior to the installation of insulin resistance is desirable. This ELSA sub-study examined whether a cluster of selected inflammatory biomarkers was associated with worse cognitive scores in non-diabetic participants. Methods: A sample of 998 non-diabetic participants of ELSA-Brasil had their cognitive function assessed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), a verbal fluency test and a trail making test. An inflammatory cluster was formed by using the k-means method. ANOVA was used to compare the tertiles of a composite global cognitive z-score with clinical and laboratory variables. Logistic regression modelling with forward stepwise model selection was performed considering cognitive performance as the outcome and the cluster as the independent variable of main interest. Models were stratified by sex and adjusted for age, insulin resistance and other confounders. Results: The mean age was 45.7 ± 4.9 years and 54.8% were women, who had a higher frequency of university level, healthier behaviors and lower systolic and diastolic blood pressure (BP) levels, fasting plasma glucose, non-HDL cholesterol and E-selectin levels than men. Individuals in the highest tertile of the composite global cognitive z-score were more likely to be women, with university level, and lower mean values of body mass index, BP levels, and HOMA-IR than those in lower tertiles. Using logistic regression model, the cluster category of the highest grade of inflammation showed to be associated with worse cognitive performance in women only. Conclusion: The association between a cluster of inflammation and worse cognitive performance seems to be useful to identify middle-aged women at risk for cognitive decline, independently of their state of insulin resistance.