BACKGROUND: We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer\'s disease (AD) pathophysiology, neuroinflammation, and neurodegeneration.
METHODS: We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer\'s Disease (EMIF-AD) study using the EPIC array.
RESULTS: We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development.
CONCLUSIONS: We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain.
CONCLUSIONS: Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer\'s disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

Alzheimer\'s disease (AD) is a neurodegenerative disease that severely affects the activities of daily living in aged individuals, which typically needs to be diagnosed at an early stage. Generative adversarial networks (GANs) provide a new deep learning method that show good performance in image processing, while it remains to be verified whether a GAN brings benefit in AD diagnosis. The purpose of this research is to systematically review psychoradiological studies on the application of a GAN in the diagnosis of AD from the aspects of classification of AD state and AD-related image processing compared with other methods. In addition, we evaluated the research methodology and provided suggestions from the perspective of clinical application. Compared with other methods, a GAN has higher accuracy in the classification of AD state and better performance in AD-related image processing (e.g. image denoising and segmentation). Most studies used data from public databases but lacked clinical validation, and the process of quantitative assessment and comparison in these studies lacked clinicians\' participation, which may have an impact on the improvement of generation effect and generalization ability of the GAN model. The application value of GANs in the classification of AD state and AD-related image processing has been confirmed in reviewed studies. Improvement methods toward better GAN architecture were also discussed in this paper. In sum, the present study demonstrated advancing diagnostic performance and clinical applicability of GAN for AD, and suggested that the future researchers should consider recruiting clinicians to compare the algorithm with clinician manual methods and evaluate the clinical effect of the algorithm.

OBJECTIVE: Early diagnosis of mild cognitive impairment (MCI) is one of the essential measures to prevent its further development into Alzheimer\'s disease (AD). In this paper, we propose a hybrid deep learning model for early diagnosis of MCI, called spatio-temporal convolutional gated recurrent unit network (STCGRU).
METHODS: The STCGRU comprises three bespoke convolutional neural network (CNN) modules and a bi-directional gated recurrent unit (BiGRU) module, which can effectively extract the spatial and temporal features of EEG and obtain excellent diagnostic results. We use a publicly available EEG dataset that has not undergone pre-processing to verify the robustness and accuracy of the model. Ablation experiments on STCGRU are conducted to showcase the individual performance improvement of each module.
RESULTS: Compared with other state-of-the-art approaches using the same publicly available EEG dataset, the results show that STCGRU is more suitable for early diagnosis of MCI. After 10-fold cross-validation, the average classification accuracy of the hybrid model reached 99.95 %, while the average kappa value reached 0.9989.
CONCLUSIONS: The experimental results show that the hybrid model proposed in this paper can directly extract compelling spatio-temporal features from the raw EEG data for classification. The STCGRU allows for accurate diagnosis of patients with MCI and has a high practical value.

BACKGROUND: Square dancing is a kind of aerobic fitness exercise without environmental restrictions that yields many benefits for physical and mental health; this exercise is popular among middle-aged and elderly people in China and in these populations in other countries. This study aimed to evaluate the effects of square dance exercise on the overall cognitive function of elderly individuals with mild cognitive impairment (MCI) and to research its mechanisms.
METHODS: A total of 60 elderly people with MCI (60-69 years old) without square dance experience were selected and randomly divided into an experimental group (n = 30) and a control group (n = 30). The experimental group participated in square dance exercise for 12 weeks, while the control group maintained their original lifestyle habits. One week before and after the intervention period, the overall cognitive function, physical fitness, and executive function of both groups were measured.
RESULTS: According to the results, square dance exercise directly improved the overall cognitive function of elderly individuals with MCI and indirectly affected overall cognitive function through the mediating effects of balance ability and executive function.
CONCLUSIONS: Square dance exercise represents a nonpharmacological intervention for the prevention and treatment of MCI. Importantly, it is best to combine this exercise with other forms of physical exercise and comprehensive treatment programs such as cognitive training, social interaction, and psychological intervention to realize its maximum effect.

OBJECTIVE: To identify different mild cognitive impairment (MCI) phenotypes based on substantial relative impairment in specific cognitive domains and then characterize the complex process of general cognitive and daily functions over time in older adults with these MCI subtypes.
METHODS: A total of 1020 participants with MCI at baseline from the Alzheimer\'s Disease Neuroimaging Initiative (ADNI) were recruited. MCI subtypes were obtained based on neuropsychological tests in five cognitive domains: memory (M), visuospatial function (V), language (L), processing speed (P), and executive function (E). General cognitive function and daily function were measured by the Mini-Mental State Examination (MMSE) and the Functional Assessment Questionnaire (FAQ), respectively. Linear mixed models were fitted to curve their trajectories across different MCI subtypes.
RESULTS: Considering visuospatial function, subtypes were MO (memory impaired only), M&V (memory and visuospatial function impaired) and M&nV (memory impaired and visuospatial function non-impaired). Similar subtypes and naming rules were obtained based on language, executive function, and processing speed. Further, depending on the number of relative impaired cognitive domains M&S and M&M were obtained. Participants with MO had the highest prevalence in the sample (53.4 %), followed by M&nV (31.1 %). Participants with M&V had the highest mean age (74.69 years) at baseline and the greatest dementia conversion rate (53.2 %). The MMSE and FAQ score trajectories changed most slowly in participants with MO while fastest in those with M&V. Obvious different trajectories of both MMSE and FAQ scores were observed across different subtypes based on visuospatial function and executive function.
CONCLUSIONS: Compared to MO, individuals with multi-dimensional cognitive impairment have worse general cognitive and daily functions, especially for those with M&V.

The brain\'s dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer\'s disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.

The differential diagnosis between mild cognitive impairment (MCI) and Alzheimer\'s disease (AD) has been highly demanded for its effectiveness in preventing and contributing to early diagnosis of AD. To this end, we developed a single plasmonic asymmetric nanobridge (PAN)-based biosensor to differentially diagnose MCI and AD by quantitative profiling of phosphorylated tau proteins (p-tau) in clinical plasma samples, which revealed a significant correlation with AD development and progression. The PAN was designed to have a conductive junction and asymmetric structure, which was unable to be synthesized by the traditional thermodynamical methods. For its unique morphological characteristics, PAN features high electromagnetic field enhancement, enabling the biosensor to achieve high sensitivity, with a limit of detection in the attomolar regime for quantitative analysis of p-tau. By introducing support vector machine (SVM)-based machine learning algorithm, the improved diagnostic system was achieved for prediction of healthy controls, MCI, and AD groups with an accuracy of 94.47 % by detecting various p-tau species levels in human plasma. Thus, our proposed PAN-based plasmonic biosensor has a powerful potential in clinical utility for predicting the onset of AD progression in the asymptomatic phase.

OBJECTIVE: We investigated the volumetric changes in the components of the cholinergic pathway for patients with early mild cognitive impairment (EMCI) and those with late mild cognitive impairment (LMCI). The effect of patients\' apolipoprotein 4 (APOE-ε4) allele status on the structural changes were analyzed.
METHODS: Structural magnetic resonance imaging data were collected. Patients\' demographic information, plasma data, and validated global cognitive composite scores were included. Relevant features were extracted for constructing machine learning models to differentiate between EMCI (n = 312) and LMCI (n = 541) and predict patients\' neurocognitive function. The data were analyzed primarily through one-way analysis of variance and two-way analysis of covariance.
RESULTS: Considerable differences were observed in cholinergic structural changes between patients with EMCI and LMCI. Cholinergic atrophy was more prominent in the LMCI cohort than in the EMCI cohort (P < 0.05 family-wise error corrected). APOE-ε4 differentially affected cholinergic atrophy in the LMCI and EMCI cohorts. For LMCI cohort, APOE-ε4 carriers exhibited increased brain atrophy (left amygdala: P = 0.001; right amygdala: P = 0.006, and right Ch123, P = 0.032). EMCI and LCMI patients showed distinctive associations of gray matter volumes in cholinergic regions with executive (R2 = 0.063 and 0.030 for EMCI and LMCI, respectively) and language (R2 = 0.095 and 0.042 for EMCI and LMCI, respectively) function.
CONCLUSIONS: Our data confirmed significant cholinergic atrophy differences between early and late stages of mild cognitive impairment. The impact of the APOE-ε4 allele on cholinergic atrophy varied between the LMCI and EMCI groups.

UNASSIGNED: Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are neurodegenerative processing stages of Alzheimer\'s disease (AD). Cognitive decline is thought to manifest in intrinsic brain activity changes, but research results yielded conflicting and few studies have explored the roles of brain regions in cognitive decline, and sensitivity of the cognitive field to changes in the altered intrinsic brain activity.
UNASSIGNED: In this cross-sectional study, 158 elderly participants were recruited from the memory clinic of the First Affiliated Hospital of Nanjing Medical University from July 2019 to May 2021, and grouped into SCD (n=73), MCI (n=46), and normal controls (NC) (n=39). The amplitude of low-frequency fluctuation (ALFF) was calculated and evaluated among the groups. Then canonical correlation analysis (CCA) was conducted to investigate the associations between imaging outcomes and cognitive behaviors.
UNASSIGNED: Neuropsychological tests in different cognitive dimensions and ALFF values of the prefrontal, parietal, and temporal gyrus, were significantly different (P<0.05) among the three groups, with no appreciable decline in daily activity. The changes in intrinsic activities were closely related to the decline in cognitive function (R=0.73, P=0.002). ALFF values in the left middle occipital gyrus, right middle frontal gyrus, left superior frontal gyrus, left angular gyrus, and superior temporal gyrus played significant roles in the analysis, while the Montreal Cognitive Assessment (MoCA) and Auditory-Verbal Learning Test scores were found to be more sensitive to changes in ALFF values.
UNASSIGNED: Spontaneous brain activity is a stable imaging biomarker of cognitive impairment. ALFF changes of the prefrontal, occipital, left angular, and temporal gyrus were sensitive to identifying cognitive decline, and the scores of the Auditory-Verbal Learning Test and MoCA could predict the abnormal intrinsic activities.

To synthesize evidence and summarize research findings related to the effectiveness and feasibility of dance movement intervention (DMI) in older adults with mild cognitive impairment (MCI), Alzheimer\'s disease (AD), and dementia; to systemically map existing research gaps and research directions for future practice.
A systematic search was conducted using six electronic databases: Web of Science, PubMed, PsycINFO, MEDLINE, ScienceDirect, and Cochrane Central Register of Controlled Trials. The methodological quality of included studies was assessed using the Cochrane Risk of Bias Tool for Randomized Trials (RoB 2) and The Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I).
29 dance intervention studies (13 RCT studies) were included in the scoping review: 62% of MCI, 10% of AD, and 28% of dementia; a total of 1708 participants (Female=1247; Male=461) aged from 63.8 ( ± 5.24) to 85.8 ( ± 5.27) years old. Eight RCT studies were included in the meta-analysis; results indicated that dance interventions had a significant effect on global cognition, memory, balance, and significantly decreased depression. No significant effects were found for executive function.
Dance is a non-pharmacological, effective, affordable, and engaging intervention that can be used as a complementary treatment for older adults with MCI, AD, and dementia.