Analysis of Alzheimer's disease associated deleterious non-synonymous single nucleotide polymorphisms and their...

Alzheimer's disease (AD) is a neurodegenerative disorder that is presented with a progressive loss of memory, a decline in cognitive abilities and multiple changes in behavior. Its pathogenicity has been linked to genetic factors in approximately 60-80% of the cases specifically APOE gene family and as well as other gene families. This study utilized advanced computational biology methods to analyze AD-associated nsSNPs extracted from the NHGRI-EBI GWAS Catalog. Ensembl Variant Effect Predictor (VEP) is used to annotate the variants associated with AD. Annotated missense variants were subjected to PolyPhen-2, SNPs&Go, PredictSNP servers which were used to predict pathogenicity of selected missense variants by protein sequence information. DynaMut and DUET servers were applied to determine protein stability due to the amino acid change by integrating protein structure information. Missense variations associated with AD were annotated to 26 proteins and further analyzed in our study. Following rigorous data filtration steps, 15 candidate variants (13 proteins) were identified and subjected to sequence and structure-based analysis. Finally in this in-silico study, five deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) were identified in ACKR2(V41A), APOE(R176C), ATP8B4(G395S), LAMB2(E987K), and TOMM40(R239W), and these findings were subsequently backed-up by existing in-vivo and in-vitro literature. This study not only provides invaluable insight into the intricate pathogenic mechanisms underlying AD but also offers a distinctive perspective that paves the way for future, more comprehensive investigations aimed at unraveling the molecular intricacies responsible for the development and progression of AD. Nonetheless, it is imperative that further rigorous in vivo and in vitro experiments are conducted to validate and expand upon the findings presented here.