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CSF BIOMARKERS AND EFFECT OF APOLIPOPROTEIN E GENOTYPE, AGE AND SEX ON CUT-OFF DERIVATION IN MILD COGNITIVE IMPAIRMENT

      Background

      Cerebrospinal fluid (CSF) biomarkers have been integrated in the research criteria for prodromal Alzheimer’s Disease (AD) (NIA-AA and IWG criteria) and are increasingly used in clinical trials. Aim of this study is to investigate the effect of APOE genotype, age and sex on CSF biomarkers distribution and cut-points to identify prodromal AD.

      Methods

      WP5 of PharmaCog (E-ADNI) harmonized and collected data from 13 European clinical centres. 147 mild cognitive impairment (MCI) patients were followed up for at least 2 years or until they progressed to clinical dementia. Mixture Model Analysis, adjusted or not for covariates (APOEε4 carrier status, age and sex) was applied for CSF cut-points derivation. Linear Mixed Model for repeated measures was performed to validate the derived cut-offs in terms of disease progression, measured using ADAS-cog13 and hippocampal volume.

      Results

      The Gaussian mixture model applied to CSF Aβ42/p-tau established three components and two cut-points (8.9 and 15.2). APOEε4 status correction modified the CSF Aβ42/p-tau distribution establishing two components and maintaining only the lower cut-point of 8.9. Conversely, age and sex correction resulted in a very mild shift of the 3 components and minimally influenced the cut-off derivation. Thus, the Aβ42/p-tau positivity was differently defined based on the APOEε4 status: value above the lower cut-off of 8.9 for non-carriers and below the higher cut-off of 15.2 for carriers. Aβ42/p-tau positive patients showed cognitive decline (time x CSF status interaction effect, p<.001) and increase in hippocampal atrophy rate (interaction effect, p<.001) when compared to negative patients.

      Conclusions

      APOE genotype strongly influences the baseline CSF distribution of Aβ42/P-tau in aMCI patients and genotype specific cut-offs should be considered when defining the pathological thresholds to identify prodromal AD.