This marks another important step in unraveling the genetic causes of Alzheimer's disease.
Uffelmann investigated which genetic differences increase the risk of Alzheimer's and how that knowledge can be translated into understandable and usable risk predictions for individuals. He compared the DNA of more than 100,000 people with Alzheimer's to that of 2.6 million people without the disease. This analysis revealed 127 regions in the human genome associated with Alzheimer's. Of these genetic risk regions, 48 had not been discovered before.
From abstract score to an understandable probability
In another part of his dissertation, Uffelmann investigated the prediction of disease risks. Genetic risk is often expressed in complex scores that are difficult for patients to interpret. Uffelmann therefore developed a method that translates this genetic information into an understandable personal probability. Instead of an abstract score, someone might, for example, be told that he or she has a 30 percent chance of developing the disease.
According to Uffelmann, precisely this translation could play an important role in the future of healthcare. In Alzheimer's, brain damage often begins ten to twenty years before memory problems become visible. If people with an increased genetic risk can be identified early, it creates the possibility to monitor them closely and offer new preventive treatments at an early stage.
Sex differences important
In a separate study, Uffelmann showed that some genetic variants can have different effects in men and women. This means that taking sex differences into account can be important for future genetic research and for the development of more personalized treatments.
Importance for practice
For patients and doctors, predicting genetic risk offers the prospect of better risk assessments and potentially earlier interventions. For drug developers, the newly discovered genes from Alzheimer's research provide valuable clues for new treatment strategies. At the same time, Uffelmann emphasizes that careful scientific validation remains necessary.
This warning is timely, as commercial companies are increasingly offering genetic risk reports and even using genetic information in embryo selection. The researcher emphasizes that such applications are only responsible when the underlying predictions are reliable, well-researched, and carefully interpreted.
The dissertation thus marks an important step towards a future in which genetic knowledge not only helps to better understand diseases but also to detect them earlier.