Aged ; Aged, 80 and over ; Biomarkers / metabolism ; Dopamine Plasma Membrane Transport Proteins* / metabolism ; Electroencephalography* / methods ; Female ; Humans ; Lewy Body Disease* / diagnosis ; Lewy Body Disease* / diagnostic imaging ; Lewy Body Disease* / metabolism ; Lewy Body Disease* / physiopathology ; Male ; Middle Aged ; Neuropsychological Tests ; Positron-Emission Tomography ; Retrospective Studies
Keywords
Dementia with lewy bodies ; Dopamine transporter imaging ; Electroencephalography ; Posterior dominant rhythm ; Theta-to-beta ratio
Abstract
Dopamine transporter (DAT) imaging and electroencephalography (EEG) are recommended biomarkers for diagnosing dementia with Lewy bodies (DLB). However, their interrelationship and independent associations with clinical symptoms remain unclear. We retrospectively analyzed 120 patients with DLB who underwent neuropsychological tests, DAT positron emission tomography, and quantitative EEG analysis. In the first step, partial correlation and univariable logistic regression analyses were conducted to screen for EEG or DAT biomarkers significantly associated with clinical characteristics. In the second step, multivariable regression models were constructed using combinations of the selected EEG and/or DAT variables to identify the best-fitting models. All models were adjusted for age, sex, and education. Lower DAT uptake in the ventral striatum was associated with higher theta power, lower beta power, and higher theta-to-beta ratio (TBR). EEG and DAT imaging biomarkers independently explained clinical symptoms: Fluctuations were best explained by increased temporal theta power and decreased putaminal DAT uptake. While visual hallucinations and rapid eye movement sleep behavior disorder were primarily linked to decreased DAT uptake in the putamen. Cognitive dysfunctions were mainly associated with EEG biomarkers-including lower central-parietal beta power, higher parietal theta power, and higher temporal-parietal TBR-while lower caudate DAT uptake provided additional explanatory value for semantic fluency dysfunction. EEG and DAT biomarkers offer independent and, in some cases complementary information about the clinical features in DLB. These findings support their potential use as multimodal biomarkers for disease monitoring.