ArticleJournal of Alzheimer's disease : JAD2023
Partial Least Squares Regression Analysis of Alzheimer's Disease Biomarkers, Modifiable Health Variables, and Cognitive Change in Older Adults with Mild Cognitive Impairment.
Article in Journal of Alzheimer's disease : JAD, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Tracing neuroinflammation in neurodegeneration: insights from a scoping review on biofluid biomarkers.Brain communications · 2026Review
- Neuronal and glial dysfunction, white matter hyperintensities and cognition in ageing and Alzheimer's disease.Brain communications · 2025Article
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundPrior work has shown that certain modifiable health, Alzheimer's disease (AD) biomarker, and demographic variables are associated with cognitive performance. However, less is known about the relative importance of these different domains of variables in predicting longitudinal change in cognition.
objectiveIdentify novel relationships between modifiable physical and health variables, AD biomarkers, and slope of cognitive change over two years in a cohort of older adults with mild cognitive impairment (MCI).
methodsMetrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, and AD pathology were assessed in 123 older adults with MCI at baseline from the Alzheimer's Disease Neuroimaging Initiative (mean age = 73.9; SD = 7.6; mean education = 16.0; SD = 3.0). Partial least squares regression (PLSR)-a multivariate method which creates components that best predict an outcome-was used to identify whether these physiological variables were important in predicting slope of change in episodic memory or executive function over two years.
resultsAt two-year follow-up, the two PLSR models predicted, respectively, 20.0% and 19.6% of the variance in change in episodic memory and executive function. Baseline levels of AD biomarkers were important in predicting change in both episodic memory and executive function. Baseline education and neurotrophic/growth factors were important in predicting change in episodic memory, whereas cardiometabolic variables such as blood pressure and cholesterol were important in predicting change in executive function.
conclusionThese data-driven analyses highlight the impact of AD biomarkers on cognitive change and further clarify potential domain specific relationships with predictors of cognitive change.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.