New approaches for medical diagnostics

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Positron emission tomography (PET) of a patient. The new procedure makes it poss
Positron emission tomography (PET) of a patient. The new procedure makes it possible to use PET to visualize the characteristics of the human genome. (Source: Hirslanden Klinik St. Anna)

An international research group led by the University of Lucerne has developed novel approaches for medical imaging. These hold great potential for earlier diagnosis, more precise localization and a better understanding of many human diseases.

Imaging procedures such as computed tomography (CT) or positron emission tomography (PET) are nowadays indispensable 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 human genetic material (genome). The new genome-based imaging has the potential for the earlier diagnosis of cancer, heart disease and dementia, among other things. 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 regarded as paving the way for the early diagnosis of cancer, heart disease or neurological disorders. However, one of the main problems to date has been the translation of new genome findings into easy-to-use 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 that can be captured with medical imaging," explains 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 virtually 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.

"Our first task was to identify every single gene of the Imageable Genome in the existing medical literature, which comprises several million publications," says Pablo Jané from Geneva University Hospital. To this end, Jané developed a method that combines human and artificial intelligence and records and processes the entire published medical literature. This made it possible to describe the entire imageable genome.

Clinical application of the new procedure

"Our second task was to find out whether the Imageable Genome enables new diagnostic tests for human diseases," says Xioaying Xu from the University of Lucerne, under whose leadership the Imageable Genome was compared with individual genome data from over 60,000 patients. The researchers thus identified new test options that can help to better diagnose, localize and treat a broad spectrum of human diseases, particularly in neurology, cardiology and oncology.

"The final step," adds the research team’s lead radiochemist, Dr. Taelman from the University of Lucerne, "was to identify the imaging tests that would be best suited to implementing the new method in practice and thus bring tangible benefits to patients in clinics." To demonstrate the broad applicability of their approach, the researchers identified new imaging tests for Alzheimer’s disease, bipolar disorder, schizophrenia, coronary heart disease, various forms of cardiomyopathy and a variety of different tumors, among others, in their publication.

"We see the Imageable Genome as a key with which new findings from genomics can be used for imaging procedures," says Martin Walter. "With this key, we see great potential for further medical research and innovations in the field of big data and artificial intelligence," Walter continues.

The research group is made up of scientists from the University of Lucerne, the University Hospital of Geneva and the University Hospital of Madrid.

Pablo Jané, Xiaoying Xu, Vincent Taelman, Eduardo Jané, Karim Gariani, Rebecca A. Dumont, Yonathan Garama, Francisco Kim, María del Val Gomez & Martin A. Walter.
The Imageable Genome
Nature Communications, 2023