Date of Award
Doctor of Philosophy
School of Medical and Health Sciences
Associate Professor Veer Bala Gupta
Professor Ralph N. Martins
Alzheimer’s disease (AD) is a slow and progressive neurodegenerative disorder.With new treatment strategies failing in clinical trials, there is a need to initiate a targeted treatment strategy, by administering the right medication, to the right individual, at the right stage. This concept of precision medicine not only requires diagnosis at the preclinical stage, but a thorough understanding of the stage-associated neuropathological changes that occur along the continuum of AD. Pathophysiological biomarkers indicative of neuropathological changes in the brain are needed to identify the preclinical stage of AD, as well as track the extent of cognitive deficit that occurs with the evolution of such changes.
The current study was conducted to assess the diagnostic and prognostic potential of cerebrospinal fluid (CSF) biomarkers in AD, associated with neurodegeneration (neurofilament light chain protein, NfL; visinin-like protein-1, VILIP-1; fatty acid binding protein 3, FABP3), neuroinflammation (YKL-40) and synaptic dysfunction (neurogranin, growth-associated protein 43, GAP-43; synaptosomal-associated protein 25, SNAP-25; synaptotagmin-1). CSF samples of participants (n = 221) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing were used in the study. The study participants were clinically classified as healthy controls (HC, n = 159), mild cognitive impairment (MCI, n = 34) and AD (n = 28). The study aimed to assess the diagnostic potential of CSF biomarkers, their preclinical diagnostic utility, prediction of disease onset and progression, association with central AD pathology, as well as their ability to predict baseline cognition, brain atrophy and amyloid accumulation.
The CSF biomarkers NfL, VILIP-1, FABP3, YKL-40, neurogranin, GAP-43 and SNAP-25 distinguished AD participants from HC with a fairly high area under the receiver operating characteristic curve (AUC). CSF biomarkers of neurodegeneration (NfL and FABP3) predicted disease onset among HC who converted from Clinical Dementia Rating (CDR) 0 to CDR ≥ 0.5, over a follow-up period of 4.5 years. CSF biomarkers predicted disease progression among patients (MCI and AD), assessed through the annual change in cognitive scores in patients, divided into tertiles based on 33rd and 66th percentile of CSF measures. CSF levels of NfL significantly increase in the earlier stages of the disease, but not in the later stages, indicating that the brain reaches a stage of irreversible neurodegeneration in late AD, with not much further evolution. CSF biomarkers significantly correlated with core CSF biomarkers total tau (T-tau) and phosphorylated tau (P-tau); classified study participants according to the A/T/N classification (based on biomarker of amyloid deposition, A; tau pathology, T and neurodegeneration, N) and predicted baseline cognition and brain atrophy. All CSF biomarkers were weak predictors of baseline amyloid load, and did not distinguish amyloid positives from negatives with a high sensitivity. This makes it apparent that neurodegeneration, neuroinflammation and synaptic dysfunction, all run independent of amyloid pathology along the disease continuum, but amyloid beta (Aβ) accumulation does contribute to the disruption of spines or neuritis, and inflammatory response.
These biomarkers and the pathologies they drive conglomerate at one stage or the other to constitute the AD neuropathology, and demonstrate an excellent diagnostic accuracy in combination. Neurodegeneration and neuroinflammation evolve in synchronisation at all stages, along the disease continuum. Neurodegeneration and synaptic dysfunction are synchronised as well, but not in an advanced stage of the disease continuum. These biomarkers give a clear picture of the pathological changes that occur along the disease continuum, and can be used as endpoint measures in clinical trials.
Dhiman, K. (2020). Utility of CSF biomarkers for the diagnosis, prognosis and assessment of cognitive decline in Alzheimer’s disease. https://ro.ecu.edu.au/theses/2284
Available for download on Saturday, February 24, 2024