Precise prediction of cerebrospinal fluid amyloid beta protein for early Alzheimer's disease detection using multimodal data.

Alzheimer's disease (AD) constitutes a neurodegenerative disorder marked by a progressive decline in cognitive function and memory capacity. The accurate diagnosis of this condition predominantly relies on cerebrospinal fluid (CSF) markers, notwithstanding the associated burdens of pain and substantial financial costs endured by patients. This study encompasses subjects exhibiting varying degrees of cognitive impairment, encompassing individuals with subjective cognitive decline, mild cognitive impairment, and dementia, constituting a total sample size of 82 participants. The primary objective of this investigation is to explore the relationships among brain atrophy measurements derived from magnetic resonance imaging, atypical electroencephalography (EEG) patterns, behavioral assessment scales, and amyloid ß-protein (Aß) indicators. The findings of this research reveal that individuals displaying reduced Aß1-42/Aß-40 levels exhibit significant atrophy in the frontotemporal lobe, alongside irregularities in various parameters related to EEG frequency characteristics, signal complexity, inter-regional information exchange, and microstates. The study additionally endeavors to estimate Aß1-42/Aß-40 content through the application of a random forest algorithm, amalgamating structural data, electrophysiological features, and clinical scales, achieving a remarkable predictive precision of 91.6%. In summary, this study proposes a cost-effective methodology for acquiring CSF markers, thereby offering a valuable tool for the early detection of AD.

Combination of Paper and Electronic Trail Making Tests for Automatic Analysis of Cognitive Impairment: Development and Validation Study.

BACKGROUND: Computer-aided detection, used in the screening and diagnosing of cognitive impairment, provides an objective, valid, and convenient assessment. Particularly, digital sensor technology is a promising detection method. OBJECTIVE: This study aimed to develop and validate a novel Trail Making Test (TMT) using a combination of paper and electronic devices. METHODS: This study included community-dwelling older adult individuals (n=297), who were classified into (1) cognitively healthy controls (HC; n=100 participants), (2) participants diagnosed with mild cognitive impairment (MCI; n=98 participants), and (3) participants with Alzheimer disease (AD; n=99 participants). An electromagnetic tablet was used to record each participant's hand-drawn stroke. A sheet of A4 paper was placed on top of the tablet to maintain the traditional interaction style for participants who were not familiar or comfortable with electronic devices (such as touchscreens). In this way, all participants were instructed to perform the TMT-square and circle. Furthermore, we developed an efficient and interpretable cognitive impairment-screening model to automatically analyze cognitive impairment levels that were dependent on demographic characteristics and time-, pressure-, jerk-, and template-related features. Among these features, novel template-based features were based on a vector quantization algorithm. First, the model identified a candidate trajectory as the standard answer (template) from the HC group. The distance between the recorded trajectories and reference was computed as an important evaluation index. To verify the effectiveness of our method, we compared the performance of a well-trained machine learning model using the extracted evaluation index with conventional demographic characteristics and time-related features. The well-trained model was validated using follow-up data (HC group: n=38; MCI group: n=32; and AD group: n=22). RESULTS: We compared 5 candidate machine learning methods and selected random forest as the ideal model with the best performance (accuracy: 0.726 for HC vs MCI, 0.929 for HC vs AD, and 0.815 for AD vs MCI). Meanwhile, the well-trained classifier achieved better performance than the conventional assessment method, with high stability and accuracy of the follow-up data. CONCLUSIONS: The study demonstrated that a model combining both paper and electronic TMTs increases the accuracy of evaluating participants' cognitive impairment compared to conventional paper-based feature assessment.

A cross-sectional study of retinal vessel changes based on optical coherence tomography angiography in Alzheimer's disease and mild cognitive impairment.

Background: The involvement of retina and its vasculature has been recently described in Alzheimer's disease (AD). Optical coherence tomography angiography (OCTA) is noninvasively used to assess the retinal blood flow. Objective: This study was to compare vessel density (VD) and blood perfusion density (PD) of the macular in AD patients, mild cognitive impairment (MCI) patients and healthy controls by OCTA, which may provide new ideas for diagnosis of AD or MCI. Methods: AD patients, MCI patients and healthy controls underwent a comprehensive ophthalmic and neurological evaluations, including cognitive function assessments as well as visual acuity, intraocular pressure (IOP), slit lamp examinations, and OCTA. General demographic data, cognitive function, retinal VD and PD were compared among three groups. The correlations among retinal VD, PD and cognitive function, amyloid-beta (Aß) protein and phosphorylated Tau (p-Tau) protein were further evaluated. The correlations between retinal superficial capillary plexus and cognitive function, Aß protein and p-Tau protein were also explored. Results: A total of 139 participants were recruited into this study, including 43 AD patients, 62 MCI patients, and 34 healthy controls. After adjusting for sex, age, history of smoking, history of alcohol intake, hypertension, hyperlipidemia, best corrected visual acuity, and IOP, VD and PD in the nasal and inferior regions of the inner ring, superior and inferior regions of outer ring in the AD group were significantly lower than in the control group (p < 0.05). PD in nasal region of outer ring also significantly decreased in the AD group. VD and PD in superior and inferior regions of inner ring, superior and temporal regions of outer ring in the MCI group were markedly lower than in the control group (p < 0.05). After adjusting for sex and age, VD and PD were correlated with Montreal Cognitive Assessment Basic score, Mini-mental State Examination score, visuospatial function and executive function (p < 0.05), while Aß protein and p-Tau protein had no relationship with VD and PD. Conclusion: Our findings suggest that superficial retinal VD and PD in macula may be potential non-invasive biomarkers for AD and MCI, and these vascular parameters correlate with cognitive function.

Comparative analysis of sensitivity and specificity of computer-aided cognitive test in screening mild cognitive impairment patients and test of reliability and validity.

OBJECTIVES: To evaluate the reliability and validity of the computer-aided cognitive test (CACT). METHODS: 219 Subjects of Tongji Hospital's Brain Health cohort (115 cases of Mild Cognitive Impairment (MCI) patients and 104 cases of normal controls) were enrolled, of which 24 cases received a retest after 2 weeks. Finally, the reliability and validity of the scale were tested and analyzed. RESULTS: (1) Reliability: (a) the internal consistency reliability of the total score of the scale was 0.645; (b) the retest reliability correlation coefficient of the total score of the scale was 0.900; (c) the Guttman Split-Half coefficient was 0.631; (2) Validity: (a) construct validity analysis showed that the correlation coefficient between each section score was between 0.036 and 0.408, and the correlation coefficient between each section score and the total score was between 0.468 and 0.781; (b) criterion validity analysis showed that the correlation coefficient between the total score of CACT and that of the Mini Mental State Examination (MMSE) was 0.733, and the coefficient between the total score of CACT and that of the basic version of the Montreal Cognitive Assessment (MoCA) was 0.763; (c) the area under the ROC curve of the CACT to distinguish between MCI patients and controls was 0.920, with an optimal diagnostic threshold of 20, a sensitivity of 88.5%, and a specificity of 80.9%. CONCLUSION: The CACT is little influenced by education level. It has good reliability and validity, which can be used for early clinical screening of cognitive dysfunction.

Dysfunction of Emotion Regulation in Mild Cognitive Impairment Individuals Combined With Depressive Disorder: A Neural Mechanism Study.

Depression increases the risk of progression from mild cognitive impairment (MCI) to dementia, where impaired emotion regulation is a core symptom of depression. However, the neural mechanisms underlying the decreased emotion regulation in individuals with MCI combined with depressive symptoms are not precise. We assessed the behavioral performance by emotion regulation tasks and recorded event-related electroencephalography (EEG) signals related to emotion regulation tasks simultaneously. EEG analysis, including event-related potential (ERP), event-related spectral perturbation (ERSP), functional connectivity and graph theory, was used to compare the difference between MCI individuals and MCI depressed individuals in behavioral performance, the late positive potential (LPP) amplitudes, neural oscillations and brain networks during the processing of emotional stimuli. We found that MCI depressed individuals have negative preferences and are prone to allocate more attentional resources to negative stimuli. Results suggested that theta and alpha oscillations activity is increased, and gamma oscillations activity is decreased during negative stimulus processing in MCI depressed individuals, thus indicating that the decreased emotion regulation in MCI depressed individuals may be associated with enhanced low-frequency and decreased high-frequency oscillations activity. Functional connectivity analysis revealed a decrease in functional connectivity in the left cerebral hemisphere of the alpha band and an increase in functional connectivity in the right cerebral hemisphere of the alpha band in MCI depressed individuals. Graph theory analysis suggested that global network metrics, including clustering coefficients and disassortative, decreased, while nodal and modular network metrics regarding local nodal efficiency, degree centrality, and betweenness centrality were significantly increased in the frontal lobe and decreased in the parieto-occipital lobe, which was observed in the alpha band, further suggesting that abnormal alpha band network connectivity may be a potential marker of depressive symptoms. Correlational analyses showed that depressive symptoms were closely related to emotion regulation, power oscillations and functional connectivity. In conclusion, the dominant processing of negative stimuli, the increased low-frequency oscillations activity and decreased high-frequency activity, so as the decrease in top-down information processing in the frontal parieto-occipital lobe, results in the abnormality of alpha-band network connectivity. It is suggested that these factors, in turn, contribute to the declined ability of MCI depressed individuals in emotion regulation.