With the exception of few substances undergoing clinical trials, there are currently only symptomatic treatment approaches available for the treatment of neurodegenerative diseases. Considering the long time-lag between the onset of neuropathological changes and the first clinical symptoms, there is an urgent need for treatment approaches at the pre-clinical stages, which may have the potential to forestall the threat of dementia, or at least delay the onset by several years. The prerequisite for this is to identify high-risk patients in pre-clinical stages, with sufficiently high diagnostic certainty, in order to intervene in a timely and targeted manner. For this predictive dementia diagnosis, so-called biomarkers are required that can already indicate the dementia process in the subclinical stage (surrogate markers). More than 70 different dementias are known, some of which are very rare (Wiltfang et al., 2016). By far the most common neurodegenerative dementia is Alzheimer's disease dementia (or dementia of Alzheimer’s type, DAT), which alone or as a mixed dementia accounts for at least half of all dementias. Biomarker-based predictive dementia diagnostics for the identification of threat of progression to Alzheimer's dementia has now been established internationally and has already found its way into both national and international guideline recommendations. These include the S3 dementia guidelines of the two national neuropsychiatric professional associations (DGN, DGPPN), of which our research group was involved in creating.
These established molecular biomarkers, i.e., dementia biomarkers in the lumbar cerebrospinal fluid (Ab peptides, Tau proteins, neurofilament light chains) or imaging methods such as amyloid positron emission tomography (amyloid PET), can reliably predict the risk of developing DAT as early as 15 years before patients enter the clinical stage of dementia. Unfortunately, these procedures are either comparatively invasive (lumbar CSF puncture) or require complex and expensive technical equipment (amyloid PET) and are therefore not suitable for high-throughput identification of large groups of high-risk patients, for example, in clinical private practice.
The current focus of our research group is to develop minimally invasive, comparatively inexpensive and high-throughput diagnostic procedures to identify patients at high risk of impending DAT in preclinical or prodromal stages, such as subjective cognitive deficit (SCD) or mild cognitive impairment (MCI) (Kornhuber et al., 2009). This will enable the systematic search for promising pharmacological, but also non-pharmacological (electrophysiological neurostimulation methods, age-appropriate physical activity, diet and food supplements), preventive treatment approaches in large patient cohorts. In this context, our research group is establishing innovative approaches for blood-based early diagnosis of Alzheimer's dementia using molecular imaging techniques (antibody-based biosensor with Fourier-transformed near-infrared spectroscopy) and attomolar-sensitive immunoassays (Nabers et al., 2019, 2016a, 2016b; Shahpasand-Kroner et al., 2018; Vogelgsang et al., 2018a, 2018b). The latter work is based on the detection of relative concentration changes (peptide quotients) or changes in the secondary structure of so-called beta-amyloid peptides in the blood plasma of patients. However, other proteomic blood biomarkers, such as the neurofilament light chains or the astroglial biomarker GFAP (Consortium for Frontotemporal Lobar Degeneration German et al., 2019), are also relevant, especially in a longitudinal view.