Analysis of genetic bases of Alzheimer’s disease

To identify regulatory non-coding variants associated with Alzheimer’s disease we performed targeted next-generation sequencing of regulatory genomic elements active in human brain for a cohort of Polish AD patients. We selected rare SNPs, enriched in the analyzed cohort compared to the non-Finnish European population and annotated them with putative target genes and transcription factor motifs. The resulting lists of candidate regulatory SNPs are available under the following links:

We have also developed a pipeline designed for identification and annotation of regulatory SNPs associated with brain diseases. It is available on github and as a virtual disk image (.vdi file to be used for Oracle VM VirtualBox).

Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP) whole-genome sequencing (WGS) data we are also exploring the possibilities of applying machine-learning classification algorithms to single-nucleotide polymorphisms (SNPs) from WGS data. We apply the Boruta feature selection algorithm (Kursa and Rudnicki, 2010) and random forest classification algorithm to three datasets: WGS and GWAS data collected by ADNI and WGS data from ROS/MAP. Our results suggest that that the highest possible classification accuracy is in agreement with estimated AD heritability (around 60%).

People involved:
Marcelina Szczerba, Msc
Marlena Osipowicz, Msc
Bartek Wilczynski, PhD
Magdalena Machnicka, PhD

This research was performed within the Identification of regulatory non-coding variants associated with neurodegenerative disorders based on targeted sequencing of open chromatin regions” project funded by the Foundation for Polish Science (within the POWROTY/REINTEGRATION programme co-financed by the European Union under the European Regional Development Fund, POIR.04.04.00-00-3E86/17-00).

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