In Silico Identification of New Genetic Variations as Potential Risk Factors for Alzheimer’s Disease in a Microarray-oriented Simulation

Abstract

Genomic and proteomic studies of neurodegenerative disorders require complementary approaches to integrate the massive amount of data generated in high throughput experimental procedures. We propose a Bioinformatics pipeline in which expression studies guide the selection of candidate genes that should be screened for potential new genetic variations from a public expressed site tags (ESTs) database. Motivated by the former interest of our group in genetic polymorphisms involved with the immune system, we selected five genes from a previous expression microarrays study of hippocampal cornu ammonis (CA1) area of Alzheimer's Disease subjects (AD). The CLCbio Workbench Combined version 3.6.2. was initially used to build ESTs and mRNA files retrieved respectively from the Goldenpath of University of California Santa Cruz (UCSC) and National Center for Biotechnology Information (NCBI) databases and latter to perform multiple batches of Smith-Waterman alignments. A total of 116 ESTs sequences were selected after proper stringent parameters were applied to the first set of mismatches. The annotation revealed various classes of variations, most of them deletions (176). Amongst this specific group, some were frameshift deletions (35) and the virtual translation of a few others (5) were predicted to induce no change other than a single aminoacid removal, with no subsequent repercussions at the protein sequence. In addition, the analysis identified transitions (three), transversions (52), synonymous (41), non-synonymous (12), and deletions in 36 ESTs located in Untranslated Regions -UTRs (Supplementary data). Deletions are often associated to major genetics syndromes with dysmorphic features. However, various recent studies show that common microdeletions might be highly associated with common neuropsychiatric disorders such as schizophrenia, autism, mental retardation, or even in various ethnicities, detected in whole genome sequencing experiments. A virtual validation confirmed that some of the variations identified were previously reported and confirmed in DNA samples, showing that this method is a feasible way to detect genetic variations that merit further exploration in AD genetic risk factor association studies.

Searching for New Genetic Risk Factors for Neuropsychiatric Disorders in Expression Databases

“…Curiously, this pattern of variations was similar to our previous study in candidate genes for AD (Lemos et al 2009). …”

“…The methodology was according to Lemos et al (2009), and the software CLCbio Workbench Combined® version 3.6.2. was used during all the following steps, initially to build spliced ESTs and mRNA files retrieved respectively from the Goldenpath (www.genome.ucsc.edu) and NCBI (www.ncbi.nlm.nih.gov) databases and latter to perform multiples batches of Smith-Waterman BLASTn alignments (Fig. 1).…”

“…This finding motivated the development of original approaches in using expression studies to guide the finding of new polymorphic regions, which might include single nucleotide polymorphisms (SNPs), deletions and insertions of a few base pairs, microdeletions, or even major chromosomal changes (Coppola et al 2008;Lemos et al 2009). …”

“…However, our group recently screened ESTs databases and predicted the existence of deletions ranging from 1 to 10 bp in genes from the inflammatory pathway in Alzheimer disease (AD) that showed expression levels altered in microarray studies with the Cornu Ammonia 1 (CA1) subregion of the hippocampus (Lemos et al 2009;Colangelo et al 2002).…”

Using ESTs database to predict and validate single polymorphisms at the HLA system

“…A virtual validation confirmed that some of the variations identified had been reported previously and had been confirmed in DNA samples, showing that this method is a feasible way to detect genetic variations that merit further exploration in genetic risk factor association studies (Colangelo et al. , 2002; Lemos et al. , 2009).…”