Down’s Syndrome (DS) is a genetic disorder associated with intellectual disability, accelerated aging and a propensity for early-onset Alzheimer’s disease (AD). Beta-amyloid plaques are one of the pathological hallmarks of AD, and also a common characteristic of the older DS brain. AD treatment trials are now moving towards administration of the intervention at preclinical stages, with the goal of preventing cognitive decline in the first place, rather than trying to halt or reverse existing pathology. Consequently, it has become essential to develop biomarkers of AD, which can: 1. Predict clinical changes and 2. Track the effectiveness of putative preventative treatments. The strong association between DS and AD means that this research is particularly important for people with DS and it presents a high-risk group for exploring predictive biomarkers.

Electroencephalography (EEG) is a non-invasive and inexpensive measure of cortical activity, which is being evaluated with the typically developing (TD) population as a potential biomarker of AD. This thesis aims to evaluate EEG as a potential predictor of cognitive decline associated with DS-AD. There are several potential EEG measures that could be explored. Following a review of the literature, the predictive potential of the following event-related potentials (ERPs): mismatch negativity (MMN) and P300 (P3a and P3b), were chosen for exploration with cross-sectional and longitudinal investigations.

The thesis begins by exploring how the ERPs differ for a cross-section of 36 adults with DS and 39 age- and gender-matched TD controls. As expected, the MMN waveform was smaller for adults with DS than TD controls. However, the P3b waveform was predominantly absent for adults with DS, whilst the P3a response was significantly enlarged. The P3a response was also enlarged for the adults with DS who scored lower on a neuropsychological measure. The neuropsychological measure indexes frontal functions, which are compromised early in DS-AD.

This experiment also provided evidence that MMN was related to age in DS, with increasing latencies and decreasing amplitudes for older participants. The differences in MMN amplitude between the groups (DS, TD) were isolated to the older adults. These findings lend support to the premature aging hypothesis of DS.

The thesis also included a longitudinal follow-up in which 34 adults with DS underwent a repeated cognitive examination one year after their EEG and initial cognitive assessment. The analyses found that adults with DS who had lower MMN amplitudes at the initial assessment were more likely to decline at the cognitive follow-up. This finding suggests that MMN may be a potentially useful clinical tool for predicting the cognitive decline associated with DS-AD.