Beta Amyloid Peptide: Beta Amyloid Peptide: Research Paper : Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

Beta Amyloid Peptide: Research Paper : Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

Abstract

Background: Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism.

Results: In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse.

Conclusions: The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies.

Keywords: Brain imaging; Consensus modules; Multivariate gene-based genome-wide analysis; iPINBPA network analysis.

Conflict of interest statement

The authors have no actual or potential conflicts of interest including any financial, personal, or other relationships with other people or organizations that could inappropriately influence (bias) our work.

This article originally appeared in the "https://pubmed.ncbi.nlm.nih.gov/33372590/" and has their copyrights. We do not claim copyright on the content. This information is for research purposes only. This Blog is made available by publishers for educational purposes only as well as to give you general information and a general understanding , not to provide specific advice. By using this blog site you understand that there is no client relationship between you and the Blog publisher. The Blog should not be used as a substitute for competent research advice.  



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