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                                                          4. New biomarker algorithm for detecting 4-repeat tauopathies
                                                          News | 12.09.2024 | Research Spotlight

                                                          New biomarker algorithm for detecting 4-repeat tauopathies

                                                          Researchers from Ludwig-Maximilians-Universität (LMU) Munich, in collaboration with Monash University Melbourne, have developed a novel biomarker algorithm that differentiates rare primary 4-repeat-tauopathies from Alzheimer’s disease with unprecedented precision. This innovative approach, which combines cerebrospinal fluid analysis with PET imaging, offers new insights into disease mechanisms and paves the way for advanced clinical trials.
                                                            Research Spotlight: photo of researcher with citation on impact of research

                                                          This is a summary of R. Dilcher, S. Wall, M. Groß et. al. (2024). Combining cerebrospinal fluid and PI-2620 tau-PET for biomarker-based stratification of Alzheimer’s disease and 4R-tauopathies. Published in Alzheimer’s & Dementia. https://doi.org/10.1002/alz.14185


                                                          The challenge

                                                          Patients regularly show up at university hospitals with diseases so rare and specific as to be scarcely known to physicians in private practice. Primary 4-repeat tauopathies are a good example. These diseases are primarily associated with movement disorders but include symptoms that often resemble those of Alzheimer’s disease, making precise diagnosis difficult. Primary 4-repeat tauopathies are currently diagnosed almost exclusively using clinical criteria – without specific biomarkers that enable conclusive diagnosis in patients. In our study, we, therefore, developed a novel biomarker algorithm.


                                                          Our approach

                                                          We cross-sectionally assessed combinations of cerebrospinal fluid measures (CSF p-tau181 and t-tau) and [18F]PI-2620 tau-PET in patients with AD (n=64), clinically suspected 4R-tauopathies (PSP or CBS, n=82) and healthy controls (n=19).


                                                          Our findings

                                                          Our study revealed that tau in primary 4-repeat-tauopathies can be detected with the novel tau-PET tracer, but unlike in Alzheimer’s, it appears in unique subcortical brain regions while cerebrospinal fluid biomarker levels remain normal. Additionally, we found new biomarkers that indicate the presence of a 4-repeat tauopathy. Diagnosis gets really effective when we analyze a combination of cerebrospinal fluid test, innovative biomarkers, and PET signal in the subcortical regions. This allows us to recognize a 4-repeat tauopathy with high certainty.


                                                          Implications

                                                          The new diagnostic workflow allows for more precise differentiation between Alzheimer’s disease and primary 4-repeat-tauopathies, facilitating earlier and more accurate diagnoses and supporting personalized treatment strategies – integrating neuronal injury biomarkers, such as [18F]PI-2620-PET-assessed blood flow, increases diagnostic efficiency and minimizes radiation exposure. Implementing the new biomarker algorithm in clinical trials marks a significant advancement, accelerating the development of disease-modifying therapies for both Alzheimer’s disease and primary 4-repeat-tauopathies.


                                                          Creating SyNergies

                                                          SyNergy members Matthias Brendel and Nicolai Franzmeier combined their imaging expertise in this study with the clinical expertise of Günter Höglinger, Johannes Levin and Robert Perneczky. 

                                                          Teilnehmende Universitäten
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                                                          SyNergy wird von der Deutschen Forschungsgemeinschaft im Rahmen der deutschen Exzellenzstrategie gefördert (EXC 2145 SyNergy - ID 390857198). Die Exzellenzstrategie fördert herausragende Forschung an deutschen Universitäten. 

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