Work

Exploring biomarkers of Alzheimer’s disease based on multi-omics and Mendelian randomisation analysis

Year: 2024

Type: article

Abstract: BACKGROUND: Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with no fully curative treatment. AIM: This study aims to identify effective biomarkers for AD diagnosis and treatment by combining multi-omics and Mendelian randomisation (MR) analyses. SUBJECTS AND METHODS: Positron emission tomography (PET), single nucleotide polymorphism (SNP), and gene expression data of AD patients using advanced correlation analysis methods (AdaSMCCA, rAdaSMCCA, and unAdaSMCCA algorithms) are integrated. RESULTS: Several regions of interest, risk SNP sites, and risk genes associated with AD are identified. Expression quantitative trait loci (eQTL) for the top 100 risk genes are retrieved from public datasets. A two-sample MR analysis using genome-wide association study (GWAS) data reveals two genes (FAM117A and ACSL1) causally related to AD. Additionally, single-cell transcriptome (scRNA-seq) data from AD samples are analysed to identify high-scoring cell clusters and their interactions. CONCLUSIONS: The identified multi-omics biomarkers and genes causally related to AD could inform clinical diagnosis and treatment.

Source: Annals of Human Biology

DOI: 10.1080/03014460.2024.2415035

Authors: Kun Tu, Wenhui Zhou, Shubing Kong

Institutions: Xianning Central Hospital, Hubei University of Science and Technology

Language: English

Topic: Alzheimer's disease research and treatments

Subfield: Physiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,390