Weighted Gene Co‐Expression Network Analysis for peripheral whole‐blood RNA sequencing in asymptomatic Alzheimer’s disease

Abstract

AbstractBackgroundAlzheimer’s disease (AD) blood‐based biomarkers are becoming widely researched. Their requirement in the asymptomatic phase of AD is high to determine individuals who are in the early stages of disease. We investigate gene network expression to better understand molecular changes in this asymptomatic phase.MethodRNA was extracted and sequenced for 63 cognitively healthy Flemish Prevent AD Cohort KU Leuven (F‐PACK) participants (70 (56‐80) years) at baseline and follow‐up (interval: 4.6 (3.4‐8.59) years, 30 APOE4 carriers). Participants received amyloid‐PET and structural MRI at both timepoints. We performed weighted gene co‐expression network analysis (WGCNA) 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 ([follow‐up – baseline amyloid load], divided by time interval (years)) using Pearson’s correlation coefficient. Significantly correlated modules were functionally annotated using Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) in R. Potential hub genes were identified if the module contained genes with eigen‐based connectivity >0.7. These were visualised using STRING to create protein‐protein interaction networks. The top four hub genes (with highest Maximal Clique Centrality values) were then selected.ResultA gene co‐expression network was built on 9,149 genes that passed the read count threshold (genes with >10 read counts in >90% of samples). From this co‐expression network, 22 co‐expression modules were constructed (Figure 1A) and correlated with traits of interest. For the tan module (including 188 genes) APOE4 carriership was significantly negatively correlated (p=0.03, r=‐0.22), whereas amyloid rate of change was significantly positively correlated (p=0.03, r=0.21). Top GO processes for this module included T cell activation and differentiation, and top KEGG pathways included T cell receptor signalling, and Th1 and Th2 cell differentiation. The top four hub genes were GZMA, NKG7, TBX21 and PRF1 (Figure 1B).ConclusionBaseline gene expression networks differ between APOE4 carrier status, and with respect to amyloid rate of change. This suggests there are network alterations in the asymptomatic phase of AD that can be detected in blood. These results may aid in development of targets for biomarker development or druggable targets for AD.