Genome-Based Imaging For Medical Diagnostics -- Lukas Portmann, Universität Luzern

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The Imageable Genome. a) A circos plot depicting 1,166 out of 1,173 genes of the Imageable Genome with their chromosome locations. b) Scatter plot summarizing a list of enriched gene ontology terms from 1,165 imageable genes. c) Disease classification of 916 imageable genes. Credit: Nature Communications (2023). DOI: 10.1038/s41467-023-43123-3

Lukas Portmann -- Universität Luzern

Nov. 17, 2023

Imaging techniques such as computed tomography (CT) or positron emission tomography (PET) are indispensable today for the diagnosis and localization of many diseases. A newly developed procedure now enables PET to be used specifically on the basis of changes in the human genome.

The new genome-based imaging has the potential for the earlier diagnosis of cancer, heart disease and dementia, as well as for a wide variety of other diseases. The researchers describe their findings in their article "The Imageable Genome," which was published in mid-November in the journal Nature Communications.

The identification of the 'Imageable Genome'

The decoding of the human genome has long been considered a gateway to the early diagnosis of cancer, heart disease and neurological disorders. However, one of the main problems remained the translation of new genomic findings into easily applicable medical tests such as imaging. The first description of the "Imageable Genome," as the researchers call their method, now provides a solution to this problem.

"The Imageable Genome represents the part of the human genome whose expression can be assessed with medical imaging," explains Prof Dr. Martin Walter, titular professor of medical sciences at the University of Lucerne and specialist in nuclear medicine at the Hirslanden Klinik St. Anna, who led the research group. "It changes during the development and progression of practically every human disease." In order to describe the Imageable Genome, the research team had to develop new methods that bridge the gap between big data, genomics and medical imaging.

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