Brain ERP components predict which individuals progress to Alzheimer's disease and which do not

Abstract

Predicting which individuals will progress to Alzheimer’s disease (AD) is important in both clinical and research settings. We used brain Event-Related Potentials (ERPs) obtained in a perceptual/cognitive paradigm with various processing demands to predict which individual Mild Cognitive Impairment (MCI) subjects will develop AD versus which will not. ERP components, including P3, memory “storage” component, and other earlier and later components, were identified and measured by Principal Components Analysis. When measured for particular task conditions, a weighted set of eight ERP component_conditions performed well in discriminant analysis at predicting later AD progression with good accuracy, sensitivity, and specificity. The predictions for most individuals (79%) had high posterior probabilities and were accurate (88%). This method, supported by a cross-validation where the prediction accuracy was 70–78%, features the posterior probability for each individual as a method of determining the likelihood of progression to AD. Empirically obtained prediction accuracies rose to 94% when the computed posterior probabilities for individuals were 0.90 or higher (which was found for 40% of our MCI sample).

The sleep–wake Cycle and Alzheimer’s Disease: What do We know?

“…During wakefulness, AD patients show a shift in the EEG power spectrum shift to lower frequencies and incoherent fast rhythms [13]. While these non-specific EEG changes have also been described in other neurodegenerative diseases, newer quantitative EEG techniques may hold promise in distinguishing AD from other dementias early in the disease course [14–16]. Thus, early sleep assessment and EEG may provide more sensitive diagnostic tools for the preclinical detection of AD rather than more traditional cognitive testing [17].…”

Event related potentials in patients with transient global amnesia—A prospective controlled study

“…No association was found, however, between TGA and the ApoE genotype, which is considered another risk factor for Alzheimer's disease, nor between the dementia and vascular comorbidities in TGA patients with persisting mild cognitive impairment (i.e., verbal and nonverbal isolated memory impairment) even several years after the period [8]. ERP have recently been proven to identify early stages of mild cognitive impairment [28] or progression in a subgroup of patients with Alzheimer's disease [29]. Thus, follow-up examinations of ERP might be useful to differentiate between patients with prior TGA and patients with neurodegenerative cognitive decline.…”

Event-related potentials for the diagnosis of mild cognitive impairment and Alzheimer's disease

“…In particular, visual ERPs may be used as an AD diagnostic marker by predicting which MCI patients will later progress to AD with sensitivity and specificity 80 and 79%, respectively [70].…”

“…Papaliagkas et al [53] P300 wave In combination with CSF b-amyloid (1 --42) levels, sensitivity and specificity for P300 latency is 80 and 90% and for P300 amplitude 100 and 89%, respectively Chapman et al [70] Visual ERPs Sensitivity 80% and specificity 79% Papaliagkas et al [54] N200 wave In combination with CSF cytochrome c levels, N200 latency has sensitivity and specificity > 75% Papaliagkas et al [54] N200 wave In combination with CSF b-amyloid (1 --42) levels, N200 latency has sensitivity and specificity 100% Papaliagkas et al [50] N200 wave N200 latency has sensitivity 100% and specificity 91% Olichney et al [63] N400, P600 waves Sensitivity 81 --94% Accurate classification between 81 and 89% of MCI patients as MCI converters or stable MCI Golob et al [16] P50, N100, P300 Larger P300 latency, P50 amplitude and N100 amplitude in MCI converters Missionnier et al [51] P200, N200, [58] Late positive component (P600)…”