Literature DB >> 33368775

Imaging Transcriptomics in Neurodegenerative Diseases.

Magdalena Mroczek1, Ahmed Desouky2, Wadid Sirry3.   

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.
© 2020 American Society of Neuroimaging.

Entities:  

Keywords:  Imaging transcriptomics; neurodegeneration; neuroimaging

Mesh:

Year:  2020        PMID: 33368775     DOI: 10.1111/jon.12827

Source DB:  PubMed          Journal:  J Neuroimaging        ISSN: 1051-2284            Impact factor:   2.486


  4 in total

1.  Identifying Alzheimer's genes via brain transcriptome mapping.

Authors:  Jae Young Baik; Mansu Kim; Jingxuan Bao; Qi Long; Li Shen
Journal:  BMC Med Genomics       Date:  2022-05-19       Impact factor: 3.622

2.  Deep phenotyping for precision medicine in Parkinson's disease.

Authors:  Ann-Kathrin Schalkamp; Nabila Rahman; Jimena Monzón-Sandoval; Cynthia Sandor
Journal:  Dis Model Mech       Date:  2022-06-01       Impact factor: 5.732

Review 3.  Singling out motor neurons in the age of single-cell transcriptomics.

Authors:  Jacob A Blum; Aaron D Gitler
Journal:  Trends Genet       Date:  2022-04-26       Impact factor: 11.821

Review 4.  Neuroimaging of Mouse Models of Alzheimer's Disease.

Authors:  Amandine Jullienne; Michelle V Trinh; Andre Obenaus
Journal:  Biomedicines       Date:  2022-01-28
  4 in total

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