Assay for predicting patients' conversion to Alzheimer's Disease and monitoring disease progression
Dr Sandrine Thuret
Dr Barry Porter
Fig1: Progression of AD
Alzheimer’s disease (AD) is a progressive neurodegenerative condition without any effective treatment options.
Dementia due to AD is preceded by a long preclinical stage, followed by diagnosis of MCI and not everyone diagnosed with MCI will develop AD. It is generally agreed that any putative disease-modifying therapy would be most beneficial if administered before the clinical onset of dementia or during the preclinical stage. Therefore, without refining diagnosis of individuals with MCI at risk of conversion to AD, it remains impossible to correctly target pharmacological and lifestyle interventions aiming at preventing or delaying the onset of clinical symptoms of dementia and preserving functional independence
While researchers have traditionally focused on examining methods to prevent neuronal loss in AD, adult new-born neuron generation, (i.e. neurogenesis), is emerging as a target for therapeutic interventions and a potential biomarker for early disease detection. By utilising HN progenitor cells and longitudinal serum samples from patients diagnosed with mild cognitive impairment (MCI), considered to be a pre-dementia state, who either converted to AD (MCI converters) or remained cognitively stable (MCI non-converters), the role of the human systemic environment was investigated in an in vitro model of human HN, to determine if an HN assay could be used in predicting conversion from MCI to AD.
The team have demonstrated that the systemic environment significantly impacts on hippocampal progenitor cells during progression from MCI to AD and that conversion to AD is associated with changes in average cell count, proliferation, cell death and neurogenesis. MCI converters can be distinguished from MCI non-converters using markers of proliferation, neurogenesis and cell death leading to the development of a predictive model to estimate conversion probability from MCI to AD for individuals with MCI.
Fig2: Receiver-operator characteristic-curve –prediction of conversion to Alzheimer’s disease. The prediction model (AUC=0.9675) indicates an excellent discriminative performance of the model. Sensitivity = 92.11%, Specificity = 94.12%, Positive predictive value = 97.22%, Negative predictive value = 84.21%.
This assay has so far been established in small longitudinal cohorts over 6 years follow-up (MCI converters, n=38), (MCI non-converters, n=18) and validated via machine-learning. Further assay development and validation work is ongoing using a significantly larger cohort of clinical samples.
Applications and Benefits: Potential use cases and/or markets. The advantages over existing solutions (eg, faster, more accurate).
This in-vitro cell-based assay can be used for:
Monitoring disease progression from MCI to AD in a patient diagnosed with MCI whereby early diagnosis enables earlier implementation of interventions aimed at delaying symptom progression and facilitates decisions regarding lifestyle changes
Stratification of patients who have received a diagnosis of MCI for suitability for inclusion in an AD drug clinical trial leading to the design of smaller trials with cleaner readout
Assessment of the efficacy of a therapy administered to a patient diagnosed with MCI
The Project is currently seeking licensees or partners to fund and support development of the biomarker and further validation.
A UK priority patent application claiming the assay was filed on 30/09/2016 (GB1616691.0).