EEG and ERP Biomarkers Across Modifiable Risk Domains Associated with Cognitive Decline: A Case-Based Clinical Synthesis

Background: Metabolic dysfunction, cardiovascular disease, and impaired sleep are recognized as potentially modifiable factors associated with cognitive decline. Clinical evaluations commonly include blood biomarkers, vascular measurements, body composition, and sleep testing; however, these measures do not directly characterize concurrent electrophysiological findings. Quantitative electroencephalography (EEG) and event-related potentials (ERP) may provide complementary information regarding brain electrical activity and stimulus-evoked responses.

Objective: To describe EEG and ERP findings across clinical cases involving metabolic, cardiovascular, and sleep-related risk factors associated with cognitive decline, and to evaluate how these electrophysiological measures changed or differed alongside clinical management and conventional health measures.

Methods: Findings were synthesized from three case-based clinical reports comprising six adults. The metabolic case series included three cognitively asymptomatic men with elevated glycemic or metabolic risk markers who participated in individualized physician-directed programs incorporating dietary, exercise, hormonal, and other clinical interventions. Measurements included HbA1C, fasting insulin, body fat, individual alpha frequency, and auditory P300 amplitude and latency. The cardiovascular case involved an older adult undergoing evaluation and longitudinal management of vascular risk factors. The sleep-related cases involved two adults with mild cognitive impairment and obstructive sleep apnea who made different decisions regarding apnea treatment. EEG and auditory oddball ERP measurements were acquired as part of the clinical evaluations.

Results: In the metabolic case series, all three patients demonstrated reductions in fasting insulin and body fat, with HbA1C moving toward clinical targets. P300 amplitude increased beyond reported test-retest expectations in all three patients. The oldest patient also demonstrated an increase in individual alpha frequency from 8.8 to 10.5 Hz and a decrease in P300 latency from 408 to 300 ms.

In the cardiovascular case, physician-directed risk management was accompanied by longitudinal changes in dominant EEG frequency, P300 amplitude, and P300 latency. In the sleep-related cases, the treated patient demonstrated a comparatively shorter P300 latency, greater P300 amplitude, and stronger connectivity patterns than the patient who declined treatment. These observations were accompanied by differences in selected reaction-time and Trail Making measures.

Conclusions: Across metabolic, cardiovascular, and sleep-related clinical contexts, quantitative EEG and ERP measures provided electrophysiological information that complemented conventional risk-factor assessments. The observed associations do not establish causation or treatment efficacy, but they support further prospective investigation of EEG and ERP biomarkers as components of longitudinal assessment in patients with modifiable risk factors associated with cognitive decline.