Imaging Transcriptomics in Neurodegenerative Diseases

Abstract

Imaging transcriptomics investigates the relationship between neuroanatomical/neuroimaging features and gene expression. The spatial and temporal distribution of the expressed genes and their pattern of spreading over time can contribute to elucidating cellular and molecular processes involved in neurodegeneration. In this study, we review recent findings regarding the correlation between neuroimaging and expression data in neurodegenerative diseases with a focus on Alzheimer's disease and Parkinson's disease. An association between gene expression data and different neuroimaging neurodegeneration features, such as R2 relaxation time and volumetric cortical atrophy, was established. Several positive and negative expression correlations were identified, and they confirmed the focal nature of neurodegeneration. Positively correlated genes were associated with cell motility, immune system activity, neuroinflammation, and microglia. Data from connectome studies support the hypothesis of selective network vulnerability and a temporal spreading pattern in neurodegenerative pathologies. Genes related to cellular mobility and transport are overexpressed in the neuroimaging-defined delineated areas of degeneration. In addition, expression enrichment of genes involved in immunological processes in vulnerable regions-such as the Toll-like receptor, a receptor involved in innate immunity-plays a major role in neuroinflammation in neurodegenerative diseases. However, substantial limitations must be overcome in future studies: the lack of high-quality resolution expression data, the lack of standardized study protocols, and insufficient sensitive early stage neuroimaging markers of degeneration. Identifying neuroimaging and expression prodromal biomarkers and investigating their causal relation in the preclinical disease stage may enable early targeted therapy before the onset of irreversible brain changes.

Singling out motor neurons in the age of single-cell transcriptomics

“…Abbreviation: TF, transcription factor. studying neurodegenerative changes at single-cell resolution is the rapidly maturing field of spatial transcriptomics [119,[121][122][123]. Leveraging the twin powers of oligonucleotide-based barcoding and in situ hybridization, numerous recent studies have demonstrated simultaneous recognition of hundreds to thousands of RNA species in morphologically intact brain tissue [18,19,124].…”

The molecular genetic landscape of human brain size variation

“…Prior studies of brain size have primarily relied on in vivo neuroimaging, which have been only indirectly linked with brain gene expression because of the relative inaccessibility of in vivo human brain tissue. The burgeoning field of "imaging-transcriptomics" [68][69][70] has demonstrated a high degree of spatial alignment between neuroimaging "gradients" -representing topographical variation of brain morphology, function, or connectivity typically derived from magnetic resonance imaging (MRI) data [71][72][73] -and the spatial topography of gene expression identified in highresolution transcriptomic resources such as the Allen Human Brain Atlas (AHBA) 25,[74][75][76][77] . However, only one previous study has directly examined brain size and brain gene expression using the comprehensive Allen Mouse Brain Atlas 78 , finding a robust power-law scaling relationship between spatial gene expression gradients and brain size across mouse development -a model which accurately predicted human brain size 79 .…”

Neuroimaging of Mouse Models of Alzheimer’s Disease

“…These include susceptibility-weighted imaging (SWI), magnetic resonance spectroscopy (MRS) and perfusion-based MRI to, name a few (see [ 22 ]). Intriguing advances in imaging transcriptomics are leading the way to identify genomic alterations that correlate to neuroimaging measures [ 57 ]. In summary, multimodal MRI for the study of MCI and AD provides diagnostic information on the progression of disease, whereby clinicians and investigators alike can select the appropriate imaging sequence(s) based on the question being probed.…”