COGNITIVE DIFFERENCES IN PARKINSON’S DISEASE WITH AMYLOID POSITIVITY AND NEGATIVITY

In Parkinson’s Disease (PD), research has shifted to investigate how biomarkers commonly seen in Alzheimer’s Disease (AD), such as amyloid beta (AB), may be associated with cognitive functioning in PD. AB is considered a reliable biomarker for AD pathology, however in PD there is a lacking biomarker that can accurately reflect severity of cognitive impairment. AD research has shown an association between low AB and cognitive decline, but the data in PD has mixed results. Most studies that analyze cognitive decline and biomarkers do not use a cutoff level and the few that do have a threshold vary greatly in terms of the cutoff level. The purpose of this study was to determine if there were any cognitive differences between individuals who are amyloid positive in contrast to those that are amyloid negative. We also examined the association between amyloid beta levels and cognition amongst those individuals who are amyloid negative. This allowed us to determine if subclinical/threshold variability in amyloid was associated with cognition. A secondary analysis using Parkinson’s Progression Marker’s Initiative (PPMI) data was run to analyze 929 newly diagnosed participants for longitudinally in both clinical and biological data including neuropsychiatric assessments, motor assessments, and cerebrospinal fluid yearly. We used two thresholds to determine whether individuals are amyloid positive or negative; a/mL cut-off (Abildgaard et al., 2023) and a/mL cutoff (Shaw et al., 2018). Multilevel modeling (MLM) was conducted to examine group differences (amyloid positive vs amyloid negative) in longitudinal trajectory of cognitive functioning. We examined the longitudinal association between CSF amyloid markers and cognitive functioning among a subsample of amyloid negative PD participants also using MLM analyses. There were no significant group differences or group X time interactions in any cognition domains. Currently there is no consensus on determining toxic levels of amyloid beta (AB). The use of cutoff levels may aid in early clinical diagnosis and provide a more reliable measure of neurodegeneration, however finding an adequate cutoff level proves to be a challenge for researchers

Alzheimer PEThology

Scheltens, P. [Promotor]Lammertsma, A.A. [Promotor]Berckel, B.N.M. van [Copromotor]Flier, W.M. van der [Copromotor

Early detection of Alzheimer’s disease in experimental and natural animal models using novel biologics

According to the World Alzheimer report published in 2020, 50 million people are currently living with dementia and this number is predicted to rise to 150 million in 2050. Alzheimer’s disease (AD) is the most common form of dementia (60% - 70% of cases). Early and accurate diagnosis of AD is a major goal in order to reduce the impact of dementia and also represents an urgent unmet medical need globally. Canine Cognitive Dysfunction (CCD) in aged dogs is a progressive neurodegenerative disorder exhibiting gradual decline of cognitive function and memory loss similar to human AD. In parallel with progressive amyloid beta (Aβ) neuropathology, aged dogs display progressive decline in measures of learning and memory. Of importance, for both AD in human and CCD in dogs, the abnormal accumulation of amyloid beta plaques (Aβp) in the brain is one of the major pathological lesions associated with this devastating disorder. Aβ is subdivided into three major assemblies, including monomers, oligomers, and fibrils of which Aβ soluble oligomers (Aβo) are the most neurotoxic to neurons. Aβo is believed to trigger the pathophysiology of AD and is normally detected two decades before clinical onset of the disease. Similarly, aged dogs affected with CCD display cognitive decline which occurs prior to accumulation of Aβp in the canine brain, suggesting that earlier assembly states of Aβ (e.g., oligomers) may be the neurotoxic species in dogs, as described for human AD. This thesis particularly focused on the early detection of Aβo with the aim of developing a cost-effective diagnostic test for AD before neuropathological and clinical deficits have ensued. Also, to provide an insight to develop the dog as a natural translational model of AD. Accumulating evidence described in my thesis suggested that retinal changes and pathophysiological processes could provide valuable insights into early diagnosis of AD. This thesis provides a strong basis to further validate dogs as a natural AD model where all the AD neuropathological hallmarks have been observed in the brain and retina. Finally, such a model will certainly facilitate the development and clinical applications of an easily accessible, inexpensive, and non-invasive retinal imaging of preclinical AD diagnostic platform to predict and diagnose early stages of AD and monitor disease therapies