Development of analytical methods for detecting biomarkers in biological matrices to explore the mechanism of neurodegenerative disorders.
Lead Research Organisation:
University of Oxford
Department Name: Oxford Chemistry
Abstract
The number of people affected by cognitive impairment has been gradually increasing. Moreover, the predictions show that this trend is likely to continue in the upcoming years and the currently available pharmacotherapies do not represent a sufficient solution. Furthermore, an early and accurate diagnosis of a specific disease is not possible, as the diagnostic methods are costly, highly invasive, and not available at most clinics. Similarly, the onset of several neurodegenerations is often gradual and inconspicuous, further impeding early diagnosis. The project aims to develop a low-cost and rapid analytical method for an effective diagnosis of various neurological disorders. Such a setup would be far easier to use in a clinical setting and would enable more frequent monitoring of the patient. This could allow not only an early and reliable diagnosis but also monitoring the disease progression and even assessing the patient`s responsiveness to different therapies. Furthermore, the developed method could be used as a screening tool to search for new biomarkers or to recruit suitable patients for clinical trials for novel therapies. The methods applied in the project will combine Nuclear Magnetic Resonance (NMR) analysis of blood with advanced multivariate statistical techniques. The initial study will use biobanked blood samples (from the OPTIMA and VITACOG trials which are already available in Oxford and ethical approval for this project has been granted) to search for Alzheimer`s disease (AD)-specific blood biomarkers. The subsequent use of mathematical algorithms will allow combining these markers into metabolite constellations leading to the formation of a panel of diagnostically-crucial biomarkers. The primary objective of this initial study will be to identify novel diagnostic biomarkers of AD and to determine if these biomarkers can allow diagnosis at the earliest stages of the disease. Similarly, the panel aims to enable monitoring of the disease progression as well as the efficacy of the administered pharmacotherapy. Subsequently, the available biological samples will be used for the development of protocols for multi-omics analysis, including primarily the mass spectroscopic metabolomics, glycomics, and lipidomics experiments. These measurements will allow evaluation of whether a multi-omics approach improves the developed diagnostic models. Furthermore, this novel multi-omics approach should enable elucidation of the related metabolic pathways and potentially explain the role of some prominent biomarkers in the onset and/or development of a specific cognitive impairment. The initial results from the AD cohort will be then translated into a new sample databank with the aim of assembling diagnostic biomarker panels not only for AD but also for other neurodegenerative disorders such as vascular dementia or multiple sclerosis. In the long-term, the method will be validated and importantly, the academic findings will be translated to an established clinical NMR platform (AXINON) resulting in a 'prototype' test. This part of the project will be conducted in collaboration with Oxford University's long-standing industrial partner Numares AG. The proposed research falls squarely within the analytical science and clinical technologies EPSRC research areas. In particular, the development of a novel biochemical test able to provide personalised diagnostic, prognostic, and disease activity information in patients with different neurological disorders is in ideal alignment with the EPSRC's health care technologies' priority theme of optimising treatment through effective diagnosis and patient-specific prediction.
Organisations
People |
ORCID iD |
| Tereza Kacerova (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/W524311/1 | 30/09/2022 | 29/09/2028 | |||
| 2758414 | Studentship | EP/W524311/1 | 30/09/2022 | 29/09/2025 | Tereza Kacerova |