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Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants
Authors:Regan Kelly  Wang Kanix  Doughty Emily  Li Haiquan  Li Jianrong  Lee Younghee  Kann Maricel G  Lussier Yves A
Institution:Department of Medicine, University of Illinois at Chicago, Chicago, Illinois 60637, USA.
Abstract:

Objective

Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome.

Materials and methods

An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer''s disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism.

Results

Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001).

Discussion

The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein–protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP).

Conclusion

These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as ‘unique personal variants’. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics.
Keywords:Personal genomics  protein interaction networks  medicine  translational bioinformatics  complex disease  ontology  protein–protein interactions  bioinformatcis  alternative splicing  genetics  network  SNP  protein networks  text-mining  bioinformatics  knowledge representations  uncertain reasoning and decision theory  languages  computational methods
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