Identification of genes and blood co‐expression networks associated with cerebrovascular neuroimaging phenotypes
Year: 2023
Type: article
Abstract: Background A hallmark of Alzheimer’s disease is amyloid‐β (Aβ) deposition in the brain parenchyma as senile plaques which Aß frequently accompanies in the cerebral vasculature as cerebral amyloid angiopathy (CAA). Previous studies demonstrated that the cerebrovascular system is essential for Aβ clearance and interactions exist between cerebrovascular disease and AD. Neuroimaging data, including measures on small vessel disease, amyloid deposits, and microhemorrhages (MCH), can reflect both cerebrovascular disease and AD pathology, thereby serving as intermediate phenotypes of both conditions. We aim to identify genes and co‐expression networks in blood associated with these neuroimaging endophenotypes and the biological pathways enriched in these perturbed transcriptional networks. Method We conducted differential gene expression and Weighted Gene Co‐Expression Network analyses (WGCNA) on blood RNA sequencing data of 407 participants from the longitudinally followed Mayo Clinic Study of Aging cohort. The neuroimaging phenotypes include MCH, infarction, and amyloid deposits measured by Pittsburgh compound B positron emission tomography (PiB PET). Result WGCNA analysis showed a nominally significant association (p<0.05) between several module eigengenes (MEs) and MCH and PiB PET. One module, M42, remained significantly associated with PiB PET after Bonferroni correction for all 43 modules tested. Pathway enrichment analysis of M42 identified two significant pathways (FDR‐adjusted p<0.05) including phosphodiesterase I activity and IgE binding. These pathways contain genes such as MS4A2 encoding the high‐affinity IgE receptor involved in the immune response. Similarly, ENPP2 in the phosphodiesterase I activity pathway represents an additional candidate gene previously implicated in Alzheimer’s disease. Conclusion We generated co‐expression networks and identified one network module with a statistically significant association between brain amyloid deposits and blood transcriptome data. Further investigations of this network and its enriched pathways are necessary to understand their roles in amyloidosis, CAA, and neurodegeneration. Future studies will include seeking replication of these results in other datasets. Such studies can help elucidate the biological mechanisms of pathogenesis of cerebrovascular damage and amyloid deposits. In addition, in a clinical setting, blood levels of transcripts discovered in this study may serve as predictive or diagnostic biomarkers with mechanistic implications.
Source: Alzheimer s & Dementia
DOI: 10.1002/alz.078921
Authors: Xuan Chen, Zachary Quicksall, Xue Wang, Denise A. Reyes, Jonathan Graff‐Radford, Thuy Nguyen, Sarah J. Lincoln, Kimberly G. Malphrus, Julia E. Crook, Joseph S. Reddy, Mariet Allen, Clifford R. Jack, Val J. Lowe, David S. Knopman, Ronald C. Petersen, Kejal Kantarci, Guojun Bu, Minerva M. Carrasquillo, Nilufer Ertekin‐Taner
Institutions: Mayo Clinic in Florida, Mayo Clinic
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4390200646