ALZHEIMER'S DISEASE DETECTION AT THE PRECLINICAL STAGE USING A NOVEL SNP GENOTYPING ARRAY

Abstract

It is currently considered that the efficacy of disease-modifying treatments should be assessed at the earliest stages of the disease, ideally in the preclinical one. To this aim, we require both sensitive diagnostic and prognostic tools for asymptomatic at-risk for AD (AR-AD) subjects and also to identify variables and biomarkers defining their risk of progression/conversion to established disease. In both cases, advanced genetic analysis is a promising route to diagnostic dissection. The INSIGHT program investigates a mono-centric cohort at the Pitié-Salpêtrière University Hospital (Paris, France) including 318 cognitively normal individuals with subjective memory complaints (SMC) with a defined brain amyloid status: 88 amyloid positive (28%), showing significantly increased cortical uptake of amyloid tracer 18F-AV-45 (Amyvid) above threshold on PET imaging; 230 amyloid negative. Demographic, cognitive, functional, nutritional, biological (blood/plasma/serum), genetic/genomic, volumetric/functional MRI, DTI and ASL sequences, FDG-PET imaging, high-density EEG recordings with resting state and event-related measures (actigraphy, CSF investigations optional), were performed at baseline. All subjects are enrolled in a 5-year follow-up with comprehensive neuropsychological assessments every 6 months (including new episodic memory tests, functional measures and subjective questionnaires for identifying possible progression), EEG and actigraphy investigations every year, complete MRI, FDG-PET and amyloid-PET scans every 2 years. Whole exome sequencing (WES) approach of the well characterised, amyloid-PET stratified, multi-modal biomarker assessed in AD patients and healthy controls, has been used to define the content of a novel array of single nucleotide polymorphism (SNP) markers. This panel, which performed with high levels of accuracy (AUC) in differentiating AD and healthy controls in an independent test set of samples, is now being used in the SNP genotyping of INSIGHT cohort subjects using Affymetrix Axiom Genotyping technology. Genetic risk variants (SNPs) will be identified. They can be used, ultimately, to develop an algorithm predicting AD progression/conversion. In turn, this is expected to facilitate early AD detection, clinical diagnosis, and therapy trials by reducing both misdiagnosis rates and enabling more accurate prediction of expected disease progression rates to defined milestones. The results from the initial cross-sectional analysis of the INSIGHT cohort will be presented.