In their study, now published in the journal Nature’s agingThey showed that the level of non-coding RNA in the blood of a Parkinson patient can be used to track the course of the disease. For their study, the team led by bioinformatics professor Andreas Keeler and doctoral student Fabian Kern created and analyzed the molecular features of more than 5,000 blood samples from more than 1,600 Parkinson’s patients. This resulted in about 320 billion data points, which researchers analyzed for Parkinson’s disease biomarkers using artificial intelligence methods. “Our project is among the largest studies of RNA biomarkers in the world,” says Andreas Keeler, head of the Research Group for Clinical Bioinformatics at Saarland University and spokesperson for the Center for Bioinformatics at the Saarland Informatics Campus.
Of great importance was the level of a particular class of RNA in blood samples, the so-called microRNAs. MicroRNAs are short, non-coding parts of RNA that play an important regulatory role in translating genetic information. “Since microRNAs are stable in the bloodstream, contain various information for diagnosis and prognosis, and their effect on the genetics of the organism has been well studied, we consider them promising candidates for strong biomarkers, also in the context of Parkinson’s disease,” says Fabian Kern. PhD in the Keeler Research Group. The group has already successfully identified microRNA as diagnostic biomarkers of Alzheimer’s disease and lung cancer in other large-scale studies.
With regard to Parkinson’s disease, bioinformatics from Saarbrucken have now proven that the disease develops in particularly strong molecular waves during the third decade of life and from around the age of seventy. We found blood samples from the corresponding study cohort, ”explains Andreas Keeler. The researchers obtained blood samples from one of the largest studies of Parkinson’s disease in the world, the“ Parkinson’s Disease Progress Markers Initiative (PPMI) ”from the United States of America. Because the PPMI dataset is a study Longitudinal, they were able to specifically investigate whether the concentration of microRNAs varied over time and thus draw conclusions about disease progression.The researchers replicated their results using samples collected independently from a second group of more than 1,000 patients provided to them by the Center for Biomedical Systems at Luxembourg.
In the current study, bioinformatics experts at the University of Saarland worked with complete blood analyzes and examined the total concentration of microRNAs in all blood cells. By doing this, they were able to show that the information content of certain types of cells varies with the age of the person involved and the stage of the disease. “In the future, we want to analyze the blood down to the single cell level, which will allow us to provide more accurate data,” says Keller of future research projects.
A total of 11 institutions participated in the current study, among them Stanford University, where Andreas Keeler was a visiting professor in 2019 and 2020, the Institute for Translational Genomics Research (TGen) in Phoenix, University of Southern California in Los Angeles, and University of California, San Diego. “The fact that our expertise in microRNA and bioinformatics is internationally recognized and that we are playing a pioneering role in a predominantly American study demonstrates the quality of research at the Saarland Informatics campus,” says Andreas Keeler.
Saarland campus informatics background 😕
800 scientists and nearly 2,100 students from more than 80 countries make the Saarland Campus for Informatics (SIC) one of the leading sites for computer science in Germany and Europe. Five world-renowned research institutes, namely the German Research Center for Artificial Intelligence (DFKI), the Max Planck Institute for Computer Science, the Max Planck Institute for Software Systems, the Center for Bioinformatics, the “Multimedia Computing and Interaction” group, as well as the University of Saarland, which includes three departments and 21 programs. Academically speaking, it covers the full spectrum of computer science.
The publication titled “Deep Sequencing of sncRNAs Reveals Distinguishing Features and Regulatory Units of Transcript during the Development of Parkinson’s Disease” and will be published as a cover story in the March issue of the journal.Nature’s agingHe will be accompanied by comment from an independent expert.