Integrative computational evaluation of genetic markers for Alzheimer’s disease

Abstract

Recent studies have reported hundreds of genes linked to Alzheimer's Disease (AD). However, many of these candidate genes may be not identified in different studies when analyses were replicated. Moreover, results could be controversial. Here, we proposed a computational workflow to curate and evaluate AD related genes. The method integrates large scale literature knowledge data and gene expression data that were acquired from postmortem human brain regions (AD case/control: 31/32 and 22/8). Pathway Enrichment, Sub-Network Enrichment, and Gene-Gene Interaction analysis were conducted to study the pathogenic profile of the candidate genes, with 4 metrics proposed and validated for each gene. By using our approach, a scalable AD genetic database was developed, including AD related genes, pathways, diseases and info of supporting references. The AD case/control classification supported the effectiveness of the 4 proposed metrics, which successfully identified 21 well-studied AD genes (i.g. TGFB1, CTNNB1, APP, IL1B, PSEN1, PTGS2, IL6, VEGFA, SOD1, AKT1, CDK5, TNF, GSK3B, TP53, CCL2, BDNF, NGF, IGF1, SIRT1, AGER and TLR) and highlighted one recently reported AD gene (i.g. ITGB1). The computational biology approach and the AD database developed in this study provide a valuable resource which may facilitate the understanding of the AD genetic profile.

Differential Expression of mRNAs in the Brain Tissues of Patients with Alzheimer’s Disease Based on GEO Expression Profile and Its Clinical Significance

“…It was reported that ITGB1 interacted with APP to regulate axons outward growth and adhesion and affects cell migration, which was supported by many literatures [ 21 , 26 , 27 ]. Moreover, ITGB1 plays an important role in the regulation of immune response [ 29 ], consistent with our results. Even though their biological function enrichment in PBMCs was not similar to those in HIP, there was a close relationship between the inflammatory and immune changes in peripheral blood and the signaling regulation in HIP.…”

Multi-tissue proteomics identifies molecular signatures for sporadic and genetically defined Alzheimer disease cases

“…Among individuals with CSF and plasma data, AD cases corresponded to those with a diagnosis of dementia of the Alzheimer's type (DAT) using criteria equivalent to the National Institute of Neurological and Communication Disorders and Stroke-Alzheimer's Disease and Related Disorders Association for probable AD, 6,456,43 and AD severity was determined using the Clinical Dementia Rating (CDR®) 46 at the time of lumbar puncture (for CSF samples) or blood draw (for plasma samples). Controls received the same assessment as the cases but were non-demented (CDR=0).…”

“…40 Similar to SPP1, ITBG1 is a microglia gene and has been shown to be differentially expressed in the hippocampus and peripheral blood mononuclear cells (PBMC) of AD cases, 41 important in microglia activation, 42 and part of the causal pathway in network analyses. 43 Recent studies have also demonstrated that meningeal lymphatics affect microglia and AD risk. 44 Our analyses also found several endothelial-speci c proteins (ERK-1, SHC1, and BCAM).…”

Identification of Hub Genes Related to Alzheimer’s Disease and Major Depressive Disorder

“…62 ITGB1 mRNA expression was changed in hippocampus and peripheral blood mononuclear cells (PBMCs) of AD patients, and researchers suggested using ITGB1 as an AD biomarker. 34,63,64 In hippocampal neurons, ITGB1 and its downstream signaling pathway signals through the nonreceptor tyrosine kinase Arg (also known as Abelson tyrosine-protein kinase 2; ABL2) to regulate dendritic branches, synaptic plasticity, and behavior in the postnatal mouse hippocampus. 65 Furthermore, changes in the genetic code of integrin and other cell adhesion molecules (CAM) or proteins that mediate CAM signal transduction affect neural connections and are closely related to neurodevelopmental disorders, such as schizophrenia 66 and autism.…”