A new tool for fusioning PET and omics data

Background Positron emission tomography (PET) imaging plays a key role in the diagnosis of Alzheimer’s disease (AD). The idea of integrating PET and omics data can provide blood‐new insights about AD pathophysiology. In this context, state‐of‐the‐art techniques such as transcriptomics hold much potential for discovering altered biological processes in AD and other neurodegenerative diseases. However, tools for integrating PET and omics data are still unexplored. Here, we developed a new method that combines blood transcriptomics with PET data. We hypothesized that our method will allow advancing our understanding of AD neurobiology and potentially unravel clinically relevant new peripheral biomarkers. Method Imaging and transcriptomics data were acquired from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Microarray gene expression profiling from blood samples of 69 cognitively unimpaired (CU) and 158 mild cognitively impaired (MCI) individuals were submitted to differential expression (DE) analysis using the limma R package. Genes obtained from DE analysis were selected to undergo integration with [18F]Fluorodeoxyglucose (FDG)‐PET images using voxel‐wise generalized linear regression (GLR) models adjusted for age, gender and APOEε4 (RMINC package). Result The DE analysis resulted in 1232 differentially expressed genes (DEGs) in CU vs MCI individuals (p‐value