Katarzyna Adamczuk (United States of America)
Clario NeuroscienceAuthor Of 1 Presentation
WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS DETECTS CHANGES IN THE PERIPHERAL BLOOD TRANSCRIPTOME IN ASYMPTOMATIC ALZHEIMER’S DISEASE
Abstract
Aims
We investigated peripheral blood gene expression networks to understand the early molecular changes prior to the accumulation of amyloid.
Methods
RNA was extracted and sequenced for 116 cognitively healthy F-PACK participants (70 (56-80) years. 55 APOE4 carriers) at baseline, 71 participants received amyloid-PET at baseline and follow-up (interval: 5.0 (3.4-8.59) years). We performed weighted gene co-expression network analysis to identify networks of co-expressed genes at baseline. These modules were correlated with traits of interest (APOE4 (present/absent) and amyloid rate of change) using Pearson’s correlation coefficient. Significantly correlated modules were annotated using Gene Ontology and KEGG. Highly interconnected genes were identified by eigen-based connectivity >0.7, and the top hub genes were selected. ChEA3 was used to determine the top transcriptional regulators.
Results
A gene co-expression network was built on 8,966 genes. We found 27 co-expression modules with numbers of genes ranging from 55-1,533. One module was significantly positively correlated with amyloid rate of change (p=0.026, r=0.21), meaning it is upregulated with higher rate of change. This module was enriched for terms including regulation of T cell activation and NK cell mediated cytotoxicity. Its top four hub genes were PRF1, GNLY, KLRD1 and GZMA. Top transcriptional regulators included EOMES and STAT4.
Conclusions
Our work suggests there are immune-related network alterations in the asymptomatic phase of AD that can be detected in blood prior to change in amyloid. These results may aid in development of targets for biomarker development or druggable targets for AD.