Identification and characterization of rare coding variants modulating the rate of disease progression in pre-dementia stages of Alzheimer's disease.

• Applicants: Professor Alfredo Ramirez, Ph.D.; Professor Michael Wagner, Ph.D.
• Subject Area: Molecular and Cellular Neurology and Neuropathology ; Human Genetics ; Molecular Biology and Physiology of Neurons and Glial Cells
• Term: from 2019 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 418087061

Alzheimer’s disease (AD) starts years before dementia diagnosis with a preclinical stage and the mild cognitive impairment (MCI) stage. Predicting, however, which MCI patient will progress to dementia is a major challenge and biological determinates of disease progression are poorly understood. Genetic research on disease progression of MCI patients is currently in its infancy. To change this, we have recruited during the last years the largest sample of longitudinally assessed MCI cases in Europe with genome-wide genotype data (~9000), of which ~4000 DNAs are stored at Dr. Ramirez' laboratory. In preliminary work, we showed that only two AD-associated loci were associated with conversion to dementia while a polygenic risk score (PRS) enabled no prediction. This raises the possibility that only a subset of the identified AD loci is related to symptom progression in at-risk-stages of AD and there are still novel variants to discover. Importantly, biological processes underlying resilience against AD may only become effective in the presence of pathology and are therefore best detectable in at-risk populations. In line with this, we could show that the AD-associated rare coding variant p.P522R in PLCG2 reduces the rate of cognitive decline in patients with MCI but not in the general population and that its effect on biomarkers of tau pathology depended on the presence of amyloid pathology. While several funded initiatives (including ours) focus on research on common variants (minor allele frequency (MAF) >5%), few groups have focused their research on rare variants (MAF<1%). However, generating data of each candidate variant one by one is an extremely time consuming and expensive approach. Therefore, we here apply for funding to generate whole exome sequencing (WES) data on 2500 MCI samples with extensive neuropsychological and biomarker data, including several follow-ups assessments over up to 15 years. The WES data will be combined with the longitudinal data using state-of-the-art methods to analyze cognitive decline. We will initially focus on candidate genes derived from loci described in AD and GWAS of constructs related to resilience (i.e. intelligence and education) in order to gain enhanced insight into their biological relevance. In parallel, we will optimize the approach to expand the analysis of rare variants to the genome-wide level. We will also construct a PRS combining rare variants identified herein with common variants derived from the latest GWAS update from the international consortia on AD genetics. In conclusion, our proposal will test existing candidate genes and identify new one that moderates disease progression in MCI. Our findings will likely translate into an improved clinical prediction (precision medicine) and enable prioritization of targets for future interventions specifically relevant to the MCI stage of AD. Furthermore, this proposal will refine existing tools to analyze rare variants in longitudinal phenotypes.

• DFG Programme: Research Grants