sFIDA Technology
surface-based fluorescence distribution analysis
sFIDA is a platform technology for quantitation and sizing of single protein aggregates.
The sFIDA platform technology offers a cutting-edge approach for the quantitative detection of single oligomers and aggregates, which serve as biomarkers of central nervous system (CNS) diseases such as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD). This platform integrates the precision of selective immunoassays with the superior sensitivity of fluorescence microscopy to count single particles. As a result, sFIDA can detect these biomarkers at unprecedented levels of sensitivity and specificity.
The versatility of the sFIDA platform is further highlighted by its successful application to a range of conditions and biological material, including brain homogenate, cerebrospinal fluid, blood plasma, and even stool samples. This broad applicability enables the use of sFIDA technology in diverse clinical and research settings, allowing for a more comprehensive understanding of the molecular basis of neurodegenerative disorders.
In addition, the sFIDA platform holds significant promise for advancing drug development. By providing valuable insights into the pathogenesis of CNS diseases and the molecular underpinnings of neurodegenerative disorders, sFIDA technology can aid in the identification of novel therapeutic targets and the evaluation of drug efficacy.
The sFIDA platform technology was developed at the Forschungszentrum Jülich, a leading research institute in Germany. Since 2018, the technology is commercialized by the spin-off company attyloid GmbH, which is dedicated to providing innovative solutions for the detection and analysis of biomarkers associated with neurodegenerative diseases.
sFIDA Technology
sFIDA (surface-based fluorescence intensity distribution analysis) is a platform technology for quantitating and sizing single protein aggregates.
sFIDA combines the selectivity of an immunological assay with the sensitivity of fluorescence microscopy. sFIDA features single particle sensitivity and absolute specificity for aggregates.
sFIDA Technology
surface-based fluorescence intensity distribution analysis
Peer-reviewed Publications
1 Wang-Dietrich, L. et al. The amyloid-beta oligomer count in cerebrospinal fluid is a biomarker for Alzheimer’s disease. J Alzheimers Dis 34, 985-994, doi:10.3233/JAD-122047 (2013).
2 Hulsemann, M. et al. Biofunctionalized Silica Nanoparticles: Standards in Amyloid-beta Oligomer-Based Diagnosis of Alzheimer’s Disease. J Alzheimers Dis 54, 79-88, doi:10.3233/JAD-160253 (2016).
3 Kuhbach, K. et al. Application of an Amyloid Beta Oligomer Standard in the sFIDA Assay. Front Neurosci 10, 8, doi:10.3389/fnins.2016.00008 (2016).
4 Herrmann, Y. et al. Nanoparticle standards for immuno-based quantitation of alpha-synuclein oligomers in diagnostics of Parkinson’s disease and other synucleinopathies. Clin Chim Acta 466, 152-159, doi:10.1016/j.cca.2017.01.010 (2017).
5 Herrmann, Y. et al. sFIDA automation yields sub-femtomolar limit of detection for Abeta aggregates in body fluids. Clin Biochem 50, 244-247, doi:10.1016/j.clinbiochem.2016.11.001 (2017).
6 Kravchenko, K. et al. Analysis of anticoagulants for blood-based quantitation of amyloid beta oligomers in the sFIDA assay. Biol Chem 398, 465-475, doi:10.1515/hsz-2016-0153 (2017).
7 Kulawik, A. et al. Advancements of the sFIDA method for oligomer-based diagnostics of neurodegenerative diseases. FEBS Lett 592, 516-534, doi:10.1002/1873-3468.12983 (2018).
8 Schemmert S., et al., Abeta Oligomer Elimination Restores Cognition in Transgenic Alzheimer’s Mice with Full-blown Pathology. Mol Neurobiol 56(3):2211-2223, doi: 10.1007/s12035-018-1209-3 (2019).
9 Kass, B., et al., Aβ oligomer concentration in mouse and human brain and its drug induced reduction ex vivo. Cell Reports Medicine, 3, 100630 https://doi.org/10.1016/j.xcrm.2022.100630 (2022).
10 Blömeke, L. et al., Quantitative detection of α-synuclein and tau oligomers and other aggregates by digital single particle counting. NPJ Parkinsons Dis., 8, 68. https://doi.org/10.1038/s41531-022-00330-x (2022).
11 Schaffrath, A. et al., Patients with isolated REM-sleep behavior disorder have elevated levels of alpha-synuclein aggregates in stool, NPJ Parkinsons Dis., 9, 14. https://doi.org/10.1038/s41531-023-00458-4 (2023).
12 Pils, M et al., Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease. Diagnostics 2023, 13, 1702. https://doi.org/10.3390/diagnostics13101702 (2023)