Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis.

Brain-predicted age difference scores are calculated by subtracting chronological age from 'brain' age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylül University (n = 175), the Cognitive Reserve/Reference Ability Neural Network study (n = 380), and The Irish Longitudinal Study on Ageing (n = 487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.

Cognitive Impairment in Parkinson's Disease Is Reflected with Gradual Decrease of EEG Delta Responses during Auditory Discrimination.

Parkinson's disease (PD) is a neurodegenerative disease that is characterized by loss of dopaminergic neurons in the substantia nigra. Mild Cognitive impairment (MCI) and dementia may come along with the disease. New indicators are necessary for detecting patients that are likely to develop dementia. Electroencephalogram (EEG) Delta responses are one of the essential electrophysiological indicators that could show the cognitive decline. Many research in literature showed an increase of delta responses with the increased cognitive load. Furthermore, delta responses were decreased in MCI and Alzheimer disease in comparison to healthy controls during cognitive paradigms. There was no previous study that analyzed the delta responses in PD patients with cognitive deficits. The present study aims to fulfill this important gap. 32 patients with Parkinson's disease (12 of them were without any cognitive deficits, 10 of them were PD with MCI, and 10 of them were PD with dementia) and 16 healthy subjects were included in the study. Auditory simple stimuli and Auditory Oddball Paradigms were applied. The maximum amplitudes of each subject's delta response (0.5-3.5 Hz) in 0-600 ms were measured for each electrode and for each stimulation. There was a significant stimulation × group effect [F(df = 6,88) = 3,21; p < 0.015; [Formula: see text] = 0.180], which showed that the difference between groups was specific to the stimulation. Patients with Parkinson's disease (including PD without cognitive deficit, PD with MCI, and PD with dementia) had reduced delta responses than healthy controls upon presentation of target stimulation (p < 0.05, for all comparisons). On the other hand, this was not the case for non-target and simple auditory stimulation. Furthermore, delta responses gradually decrease according to the cognitive impairment in patients with PD. Conclusion: The results of the present study showed that cognitive decline in PD could be represented with decreased event related delta responses during cognitive stimulations. Furthermore, the present study once more strengthens the hypothesis that decrease of delta oscillatory responses could be the candidate of a general electrophysiological indicator for cognitive impairment.

Improved Cerebrospinal Fluid-Based Discrimination between Alzheimer's Disease Patients and Controls after Correction for Ventricular Volumes.

Cerebrospinal fluid (CSF) biomarkers may support the diagnosis of Alzheimer's disease (AD). We studied if the diagnostic power of AD CSF biomarker concentrations, i.e., Aß42, total tau (t-tau), and phosphorylated tau (p-tau), is affected by differences in lateral ventricular volume (VV), using CSF biomarker data and magnetic resonance imaging (MRI) scans of 730 subjects, from 13 European Memory Clinics. We developed a Matlab-algorithm for standardized automated segmentation analysis of T1 weighted MRI scans in SPM8 for determining VV, and computed its ratio with total intracranial volume (TIV) as proxy for total CSF volume. The diagnostic power of CSF biomarkers (and their combination), either corrected for VV/TIV ratio or not, was determined by ROC analysis. CSF Aß42 levels inversely correlated to VV/TIV in the whole study population (Aß42: r = -0.28; p < 0.0001). For CSF t-tau and p-tau, this association only reached statistical significance in the combined MCI and AD group (t-tau: r = -0.15; p-tau: r = -0.13; both p < 0.01). Correction for differences in VV/TIV improved the differentiation of AD versus controls based on CSF Aß42 alone (AUC: 0.75 versus 0.81) or in combination with t-tau (AUC: 0.81 versus 0.91). In conclusion, differences in VV may be an important confounder in interpreting CSF Aß42 levels.