Development of amyloid-negative neuropsychological norms using GAMLSS

Area of Science:

• Neuroscience and Cognitive Psychology
• Biomarker Research
• Statistical Modeling in Health Sciences

Background:

• Traditional neuropsychological norms may lack sensitivity in detecting cognitive changes.
• Generalized Additive Models for Location, Scale, and Shape (GAMLSS) offer advanced statistical approaches for norming.
• Brain amyloid-beta (Aβ) levels are linked to cognitive performance even in cognitively normal individuals.

Purpose of the Study:

• To develop next-generation norms (NGN) for neuropsychological assessments.
• To utilize GAMLSS for creating amyloid-beta negative (Aβ-) norms.
• To enhance the detection of objective cognitive impairment.

Main Methods:

• Utilized data from 987 cognitively normal (CN) individuals from a Spanish multicenter study.
• Included cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker assessment.
• Developed NGN using GAMLSS with data from 774 Aβ- CN individuals (aged 30-90).

Main Results:

• Generated age-, education-, and sex-adjusted z-scores for 14 neuropsychological measures.
• Covered key cognitive domains: memory, language, attention/executive, and visuospatial functions.
• An open-access online calculator (ShinyApp) was created for easy z-score application.

Conclusions:

• The developed Aβ-negative NGN, based on GAMLSS, may improve the identification of cognitive impairment.
• These norms are applicable in both clinical diagnostics and research settings.
• Free accessibility via an online tool promotes wider adoption and utility.