Impairment In Mild Cognitive Impairment Research Articles

Detecting language network alterations in mild cognitive impairment using task-based fMRI and resting-state fMRI: A comparative study.

The objective of this study was to investigate the functional changes associated with mild cognitive impairment (MCI) using independent component analysis (ICA) with the word generation task functional magnetic resonance imaging (fMRI) and resting-state fMRI. In this study 17 patients with MCI and age and education-matched 17 healthy individuals as control group are investigated. All participants underwent resting-state fMRI and task-based fMRI while performing the word generation task. ICA was used to identify the appropriate independent components (ICs) and their associated networks. The Dice Coefficient method was used to determine the relevance of the ICs to the networks of interest. IC-14 was found relevant to language network in both resting-state and task-based fMRI, IC-4 to visual, and IC-28 to dorsal attention network (DAN) in word generation task-based fMRI by Sorento-Dice Coefficient. ICA showed increased activation in language network, which had a larger voxel size in resting-state functional MRI than word generation task-based fMRI in the bilateral lingual gyrus. Right temporo-occipital fusiform cortex, right hippocampus, and right thalamus were also activated in the task-based fMRI. Decreased activation was found in DAN and visual network MCI patients in word generation task-based fMRI. Task-based fMRI and ICA are more sophisticated and reliable tools in evaluation cognitive impairments in language processing. Our findings support the neural mechanisms of the cognitive impairments in MCI.

Altered cortical and subcortical morphometric features and asymmetries in the subjective cognitive decline and mild cognitive impairment.

This study aimed to evaluate morphological changes in cortical and subcortical regions and their asymmetrical differences in individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). These morphological changes may provide valuable insights into the early diagnosis and treatment of Alzheimer's disease (AD). We conducted structural MRI scans on a cohort comprising 62 SCD patients, 97 MCI patients, and 70 age-, sex-, and years of education-matched healthy controls (HC). Using Freesurfer, we quantified surface area, thickness, the local gyrification index (LGI) of cortical regions, and the volume of subcortical nuclei. Asymmetry measures were also calculated. Additionally, we explored the correlation between morphological changes and clinical variables related to cognitive decline. Compared to HC, patients with MCI exhibited predominantly left-sided surface morphological changes in various brain regions, including the transverse temporal gyrus, superior temporal gyrus, insula, and pars opercularis. SCD patients showed relatively minor surface morphological changes, primarily in the insula and pars triangularis. Furthermore, MCI patients demonstrated reduced volumes in the anterior-superior region of the right hypothalamus, the fimbria of the bilateral hippocampus, and the anterior region of the left thalamus. These observed morphological changes were significantly associated with clinical ratings of cognitive decline. The findings of this study suggest that cortical and subcortical morphometric changes may contribute to cognitive impairment in MCI, while compensatory mechanisms may be at play in SCD to preserve cognitive function. These insights have the potential to aid in the early diagnosis and treatment of AD.

The use of the integrated cognitive assessment to improve the efficiency of primary care referrals to memory services in the accelerating dementia pathway technologies study.

Current primary care cognitive assessment tools are either crude or time-consuming instruments that can only detect cognitive impairment when it is well established. This leads to unnecessary or late referrals to memory services, by which time the disease may have already progressed into more severe stages. Due to the COVID-19 pandemic, some memory services have adapted to the new environment by shifting to remote assessments of patients to meet service user demand. However, the use of remote cognitive assessments has been inconsistent, and there has been little evaluation of the outcome of such a change in clinical practice. Emerging research has highlighted computerized cognitive tests, such as the Integrated Cognitive Assessment (ICA), as the leading candidates for adoption in clinical practice. This is true both during the pandemic and in the post-COVID-19 era as part of healthcare innovation. The Accelerating Dementias Pathways Technologies (ADePT) Study was initiated in order to address this challenge and develop a real-world evidence basis to support the adoption of ICA as an inexpensive screening tool for the detection of cognitive impairment and improving the efficiency of the dementia care pathway. Ninety-nine patients aged 55-90 who have been referred to a memory clinic by a general practitioner (GP) were recruited. Participants completed the ICA either at home or in the clinic along with medical history and usability questionnaires. The GP referral and ICA outcome were compared with the specialist diagnosis obtained at the memory clinic.Participants were given the option to carry out a retest visit where they were again given the chance to take the ICA test either remotely or face-to-face. The primary outcome of the study compared GP referral with specialist diagnosis of mild cognitive impairment (MCI) and dementia. Of those the GP referred to memory clinics, 78% were necessary referrals, with ~22% unnecessary referrals, or patients who should have been referred to other services as they had disorders other than MCI/dementia. In the same population the ICA was able to correctly identify cognitive impairment in ~90% of patients, with approximately 9% of patients being false negatives. From the subset of unnecessary GP referrals, the ICA classified ~72% of those as not having cognitive impairment, suggesting that these unnecessary referrals may not have been made if the ICA was in use. ICA demonstrated a sensitivity of 93% for dementia and 83% for MCI, with a specificity of 80% for both conditions in detecting cognitive impairment. Additionally, the test-retest prediction agreement for the ICA was 87.5%. The results from this study demonstrate the potential of the ICA as a screening tool, which can be used to support accurate referrals from primary care settings, along with the work conducted in memory clinics and in secondary care. The ICA's sensitivity and specificity in detecting cognitive impairment in MCI surpassed the overall standard of care reported in existing literature.

Refueling the post COVID-19 brain: potential role of ketogenic medium chain triglyceride supplementation: an hypothesis.

COVID-19 infection causes cognitive changes in the acute phase, but also after apparent recovery. Over fifty post (long)-COVID symptoms are described, including cognitive dysfunction ("brain fog") precluding return to pre-COVID level of function, with rates twice as high in females. Additionally, the predominant demographic affected by these symptoms is younger and still in the workforce. Lack of ability to work, even for six months, has significant socio-economic consequences. This cognitive dysfunction is associated with impaired cerebral glucose metabolism, assessed using 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET), showing brain regions that are abnormal compared to age and sex matched controls. In other cognitive conditions such as Alzheimer's disease (AD), typical patterns of cerebral glucose hypometabolism, frontal hypometabolism and cerebellar hypermetabolism are common. Similar FDG-PET changes have also been observed in post-COVID-19, raising the possibility of a similar etiology. Ketone bodies (B-hydroxybutyrate, acetoacetate and acetone) are produced endogenously with very low carbohydrate intake or fasting. They improve brain energy metabolism in the face of cerebral glucose hypometabolism in other conditions [mild cognitive impairment (MCI) and AD]. Long-term low carbohydrate intake or prolonged fasting is not usually feasible. Medium chain triglyceride (MCT) is an exogenous route to nutritional ketosis. Research has supported their efficacy in managing intractable seizures, and cognitive impairment in MCI and AD. We hypothesize that cerebral glucose hypometabolism associated with post COVID-19 infection can be mitigated with MCT supplementation, with the prediction that cognitive function would also improve. Although there is some suggestion that post COVID-19 cognitive symptoms may diminish over time, in many individuals this may take more than six months. If MCT supplementation is able to speed the cognitive recovery, this will impact importantly on quality of life. MCT is readily available and, compared to pharmaceutical interventions, is cost-effective. Research shows general tolerability with dose titration. MCT is a component of enteral and parenteral nutrition supplements, including in pediatrics, so has a long record of safety in vulnerable populations. It is not associated with weight gain or adverse changes in lipid profiles. This hypothesis serves to encourage the development of clinical trials evaluating the impact of MCT supplementation on the duration and severity of post COVID-19 cognitive symptoms.

Levels of chemokines and other inflammatory mediators in patients with mild cognitive impairment undergoing rehabilitation

Alzheimer's disease is the most common neurodegenerative disease in old age. In some cases, it is preceded by mild cognitive impairment (MCI). One of the important components in the pathogenesis of neurodegeneration is chronic neuroinflammation (inflammatory activation of microglia and astrocytes in the brain). Systemic inflammatory response and immune dysregulation may contribute to neuroinflammation. The purpose of this study was to investigate the level of chemokines and other inflammatory mediators in patients with MCI who underwent medical rehabilitation, and to study its associations with the severity of cognitive impairment. The study group included 48 patients with MCI undergoing rehabilitation. Rehabilitation included cognitive therapy, psychotherapy and tasks for unaided performance. Repeated examination was conducted 6 months after the completion of rehabilitation. The control group included 46 healthy volunteers. Multiplex assay was used to determine serum cytokine and chemokine concentrations. Student's t-test was used to assess the significance of differences. Assessment of cognitive functions was performed using international neuropsychological scales. In patients with MCI, we have found an increase in the levels of several cytokines and chemokines (TNFα, CXCL10/IP10, MDC) that regulate systemic inflammation, cellular and humoral mechanisms of adaptive immunity. After the rehabilitation course their levels returned to normal. It was also found that decrease in CCL7 level in the patients before the rehabilitation course is associated with the severity of cognitive impairment. The findings contribute to understanding the role of chemokines in the pathogenesis of MCI, and indicate that their levels can be potential biomarkers of the severity of cognitive impairment. For translation of the findings into clinical practice, their validation in larger studies is needed, as well as assessing the associations between chemokine levels and the severity of cognitive impairment in MCI over long-term follow-up.

Role of hippocampal subfields in neurodegenerative disease progression analyzed with a multi-scale attention-based network

Background and ObjectiveBoth Alzheimer’s disease (AD) and Parkinson’s disease (PD) are progressive neurodegenerative diseases. Early identification is very important for the prevention and intervention of their progress. Hippocampus plays a crucial role in cognition, in which there are correlations between atrophy of Hippocampal subfields and cognitive impairment in neurodegenerative diseases. Exploring biomarkers in the prediction of early cognitive impairment in AD and PD is significant for understanding the progress of neurodegenerative diseases. MethodsA multi-scale attention-based deep learning method is proposed to perform computer-aided diagnosis for neurodegenerative disease based on Hippocampal subfields. First, the two dimensional (2D) Hippocampal Mapping Image (HMI) is constructed and used as input of three branches of the following network. Second, the multi-scale module and attention module are integrated into the 2D residual network to improve the diversity of the extracted features and capture significance of various voxels for classification. Finally, the role of Hippocampal subfields in the progression of different neurodegenerative diseases is analyzed using the proposed method. ResultsClassification experiments between normal control (NC), mild cognitive impairment (MCI), AD, PD with normal cognition (PD-NC) and PD with mild cognitive impairment (PD-MCI) are carried out using the proposed method. Experimental results show that subfields subiculum, presubiculum, CA1, and molecular layer are strongly correlated with cognitive impairment in AD and MCI, subfields GC-DG and fimbria are sensitive in detecting early stage of cognitive impairment in MCI, subfields CA3, CA4, GC-DG, and CA1 show significant atrophy in PD. For exploring the role of Hippocampal subfields in PD cognitive impairment, we find that left parasubiculum, left HATA and left presubiculum could be important biomarkers for predicting conversion from PD-NC to PD-MCI. ConclusionThe proposed multi-scale attention-based network can effectively discover the correlation between subfields and neurodegenerative diseases. Experimental results are consistent with previous clinical studies, which will be useful for further exploring the role of Hippocampal subfields in neurodegenerative disease progression.

Validation of a Remote and Fully Automated Story Recall Task to Assess for Early Cognitive Impairment in Older Adults: Longitudinal Case-Control Observational Study.

BackgroundStory recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring.ObjectiveThis study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD.MethodsThe “Amyloid Prediction in Early Stage Alzheimer’s disease” (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants’ personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer’s Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire.ResultsOf the 200 participants recruited in the AMYPRED studies, 151 (75.5%)—78 cognitively unimpaired (CU) and 73 MCI or mild AD—engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent validity with established cognitive tests.ConclusionsThe unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring.

Salience network anatomical and molecular markers are linked with cognitive dysfunction in mild cognitive impairment.

Recent studies indicate disrupted functional mechanisms of salience network (SN) regions-right anterior insula, left anterior insula, and anterior cingulate cortex-in mild cognitive impairment (MCI). However, the underlying anatomical and molecular mechanisms in these regions are not clearly understood yet. It is also unknown whether integration of multimodal-anatomical and molecular-markers could predict cognitive impairment better in MCI. Herein we quantified anatomical volumetric markers via structural MRI and molecular amyloid markers via PET with Pittsburgh compound B in SN regions of MCI (n=33) and healthy controls (n=27). From these markers, we built support vector machine learning models aiming to estimate cognitive dysfunction in MCI. We found that anatomical markers are significantly reduced and molecular markers are significantly elevated in SN nodes of MCI compared to healthy controls (p<.05). These altered markers in MCI patients were associated with their worse cognitive performance (p<.05). Our machine learning-based modeling further suggested that the integration of multimodal markers predicts cognitive impairment in MCI superiorly compared to using single modality-specific markers. These findings shed light on the underlying anatomical volumetric and molecular amyloid alterations in SN regions and show the significance of multimodal markers integration approach in better predicting cognitive impairment in MCI.

The Diagnostic Value of Language Screening in Primary Progressive Aphasia: Validation and Application of the Sydney Language Battery.

The three variants of primary progressive aphasia (PPA) differ in clinical presentation, underlying brain pathology, and clinical course, which stresses the need for early differentiation. However, brief cognitive tests that validly distinguish between all PPA variants are lacking. The Sydney Language Battery (SYDBAT) is a promising screening instrument that can be used as a first step in a comprehensive neuropsychological assessment to distinguish PPA subtypes, but evidence on its validity and reliability is to date limited. In the current study, the validation and diagnostic value of the SYDBAT are described for discriminating PPA subtypes as well as distinguishing PPA from mild cognitive impairment (MCI) or Alzheimer's dementia (AD). Forty-five patients with PPA (13 with semantic PPA, 20 with logopenic PPA, and 12 with nonfluent/agrammatic PPA), 25 MCI patients, 13 AD patients, and 50 cognitively unimpaired controls were included in this study. Both patients and controls completed the SYDBAT-NL (Dutch version). Performance on and predictive ability of the four subtests (i.e., Naming, Word Comprehension, Repetition, and Semantic Association) were assessed. In addition, construct validity and internal consistency were examined. Different SYDBAT performance patterns were found across PPA and non-PPA patient groups. While a discriminant function analysis based on SYDBAT subtest scores could predict PPA subtype with 78% accuracy, it was more difficult to disentangle PPA from non-PPA patients based on SYDBAT scores alone. For assisting in clinical interpretation, simple rules were set up and translated into a diagnostic decision tree for subtyping PPA, which was capable of diagnosing a large proportion of the cases. Satisfying validity and reliability measures were found. The SYDBAT is an easy-to-use and promising screen for assessing single-word language processes, which may contribute to the differential diagnostic process of PPA and the assessment of language impairment in MCI and AD. It can be easily implemented for initial screening of patients in a memory clinic.

Alzheimer’s disease polygenic scores predict changes in executive function across 12 years in late middle age

Genome-wide association studies are instrumental in quantifying genetic influences underlying Alzheimer's disease (AD), and applications of polygenic scores derived from association studies have already shed light on early disease pathology. For example, AD polygenic scores (AD-PGS) are associated with amnestic mild cognitive impairment (MCI) diagnoses in midlife. What remains unclear is how AD-PGS relate to objectively measured cognitive changes across midlife. Moreover, executive function abilities have been somewhat neglected despite prominent executive impairments in MCI and AD. Here we tested the hypothesis that an AD-PGS would be associated with executive function and episodic memory changes across late midlife.We examined 1412 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively normal at their first assessment and had up to 3 cognitive assessments across 10-12 years (mean ages 56, 62, and 68). Latent growth models of executive function were based on 6 tasks spanning inhibition, shifting, and working memory subdomains and growth models of episodic memory were based on 7 subtests from the Logical Memory, Visual Reproductions, and California Verbal Learning tests. The AD-PRS (Lambert et al. 2013) significantly differentiated MCI and cognitively normal participants in earlier VETSA investigations.Latent growth models of executive function and memory indicated that, compared to baseline performance (i.e., intercept at mean age 56), 10-year variability in cognitive change was comparatively larger for executive function (e.g., slope variance/intercept variance ratio=39% for executive function, 22% for memory). Importantly, individuals with higher AD-PGS had sharper declines in executive functioning (r= -.24, 95% CI [-.41, -.08]) but not episodic memory (r= -.11, 95% CI [-.25, .04]). Baseline executive function (r=.00) and memory (r=-.02) were not associated with PD-PGS.AD genetic risk was associated with executive function changes, but not episodic memory changes, across midlife. These findings highlight the importance of considering executive function changes in midlife, especially for predicting disease progression and AD biology. Executive functions are one of the first cognitive abilities to decline in midlife in normal aging. This study is among the first to demonstrate that this decline also relates to AD genetic influences.

Associations among sleep-disordered breathing, arousal response, and risk of mild cognitive impairment in a northern Taiwan population.

Dementia is associated with sleep disorders. However, the relationship between dementia and sleep arousal remains unclear. This study explored the associations among sleep parameters, arousal responses, and risk of mild cognitive impairment (MCI). Participants with the chief complaints of memory problems and sleep disorders, from the sleep center database of Taipei Medical University Shuang-Ho Hospital, were screened, and the parameters related to the Cognitive Abilities Screening Instrument, Clinical Dementia Rating, and polysomnography were determined. All examinations were conducted within 6 months and without a particular order. The participants were divided into those without cognitive impairment (Clinical Dementia Rating = 0) and those with MCI (Clinical Dementia Rating = 0.5). Mean comparison, linear regression models, and logistic regression models were employed to investigate the associations among obtained variables. This study included 31 participants without MCI and 37 with MCI (17 with amnestic MCI, 20 with multidomain MCI). Patients with MCI had significantly higher mean values of the spontaneous arousal index and spontaneous arousal index in the non-rapid eye movement stage than those without MCI. An increased risk of MCI was significantly associated with increased spontaneous arousal index and spontaneous arousal index in the non-rapid eye movement stage with various adjustments. Significant associations between the Cognitive Abilities Screening Instrument scores and the oximetry parameters and sleep disorder indexes were observed. Repetitive respiratory events with hypoxia were associated with cognitive dysfunction. Spontaneous arousal, especially in non-rapid eye movement sleep, was related to the risk of MCI. However, additional longitudinal studies are required to confirm their causality. Tsai C-Y, Hsu W-H, Lin Y-T, etal. Associations among sleep-disordered breathing, arousal response, and risk of mild cognitive impairment in a northern Taiwan population. J Clin Sleep Med. 2022;18(4): 1003-1012.

Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia.

Introduction: Early detection and monitoring of mild cognitive impairment (MCI) and Alzheimer's Disease (AD) patients are key to tackling dementia and providing benefits to patients, caregivers, healthcare providers and society. We developed the Integrated Cognitive Assessment (ICA); a 5-min, language independent computerised cognitive test that employs an Artificial Intelligence (AI) model to improve its accuracy in detecting cognitive impairment. In this study, we aimed to evaluate the generalisability of the ICA in detecting cognitive impairment in MCI and mild AD patients.Methods: We studied the ICA in 230 participants. 95 healthy volunteers, 80 MCI, and 55 mild AD participants completed the ICA, Montreal Cognitive Assessment (MoCA) and Addenbrooke's Cognitive Examination (ACE) cognitive tests.Results: The ICA demonstrated convergent validity with MoCA (Pearson r=0.58, p<0.0001) and ACE (r=0.62, p<0.0001). The ICA AI model was able to detect cognitive impairment with an AUC of 81% for MCI patients, and 88% for mild AD patients. The AI model demonstrated improved performance with increased training data and showed generalisability in performance from one population to another. The ICA correlation of 0.17 (p = 0.01) with education years is considerably smaller than that of MoCA (r = 0.34, p < 0.0001) and ACE (r = 0.41, p < 0.0001) which displayed significant correlations. In a separate study the ICA demonstrated no significant practise effect over the duration of the study.Discussion: The ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large-scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture, and education.

Disrupted Network Topology Contributed to Spatial Navigation Impairment in Patients With Mild Cognitive Impairment.

Impairment in spatial navigation (SN) and structural network topology is not limited to patients with Alzheimer’s disease (AD) dementia and can be detected earlier in patients with mild cognitive impairment (MCI). We recruited 32 MCI patients (65.91 ± 11.33 years old) and 28 normal cognition patients (NC; 69.68 ± 10.79 years old), all of whom underwent a computer-based battery of SN tests evaluating egocentric, allocentric, and mixed SN strategies and diffusion-weighted and T1-weighted Magnetic Resonance Imaging (MRI). To evaluate the topological features of the structural connectivity network, we calculated its measures such as the global efficiency, local efficiency, clustering coefficient, and shortest path length with GRETNA. We determined the correlation between SN accuracy and network topological properties. Compared to NC, MCI subjects demonstrated a lower egocentric navigation accuracy. Compared with NC, MCI subjects showed significantly decreased clustering coefficients in the left middle frontal gyrus, right rectus, right superior parietal gyrus, and right inferior parietal gyrus and decreased shortest path length in the left paracentral lobule. We observed significant positive correlations of the shortest path length in the left paracentral lobule with both the mixed allocentric–egocentric and the allocentric accuracy measured by the average total errors. A decreased clustering coefficient in the right inferior parietal gyrus was associated with a larger allocentric navigation error. White matter hyperintensities (WMH) did not affect the correlation between network properties and SN accuracy. This study demonstrated that structural connectivity network abnormalities, especially in the frontal and parietal gyri, are associated with a lower SN accuracy, independently of WMH, providing a new insight into the brain mechanisms associated with SN impairment in MCI.

Deficits in saccadic eye movements differ between subtypes of patients with mild cognitive impairment

ABSTRACT Introduction: Mild cognitive impairment (MCI) is known to be heterogeneous in its cognitive features and course of progression. Whilst memory impairment is characteristic of amnestic MCI (aMCI), cognitive deficits other than memory can occur in both aMCI and non-amnestic MCI (naMCI) and accurate assessment of the subtypes of MCI is difficult for clinicians without the application of extensive neuropsychological testing. In this study, we examine metrics derived from recording of reflexive and voluntary saccadic eye movements as a potential alternative method for discriminating between subtypes and assessing cognitive functions in MCI. Method: A total of 29 MCI patients and 29 age- and education-matched healthy controls (HCs) participated in the cross-sectional study. We recorded horizonta l and vertical pro-saccades and anti-saccade responses. All the participants also completed a comprehensive neuropsychological tests battery. Results: Significant differences in saccadic eye movement were found between the subtypes of MCI and HCs. Patients with aMCI had a higher percentage of short latency “express” saccades than HCs. We found strong associations between saccadic reaction times and cognitive domains, including executive functions and attention. The mini-mental state examination (MMSE) was also found to correlate with uncorrected errors in the anti-saccade task. Conclusions: The increased proportion of saccades in the express latency range in aMCI may be indicative of problems with cognitive inhibitory control in these patients. A focus on this and other saccade metrics in the preclinical and prodromal stages of dementia may help to predict the clinical progression of the disease and direct interventions for the management of MCI. The clinical significance of saccadic eye movement impairments in MCI is not yet fully understood and should be investigated in further studies using larger samples.

Motor dysfunction in mild cognitive impairment as tested by kinematic analysis and transcranial magnetic stimulation

ObjectivePrevious studies have demonstrated voluntary movement alterations as well as motor cortex excitability and plasticity changes in patients with mild cognitive impairment (MCI). To investigate the pathophysiology of movement abnormalities in MCI, we tested possible relationships between movement abnormalities and primary motor cortex alterations in patients. MethodsFourteen amnestic MCI (aMCI) patients and 16 healthy controls were studied. Cognitive assessment was performed using clinical scales. Finger tapping was recorded by a motion analysis system. Transcranial magnetic stimulation was used to test the input/output curve of motor evoked potentials, intracortical inhibition, and short-latency afferent inhibition. Primary motor cortex plasticity was probed by theta burst stimulation. We investigated correlations between movement abnormalities, clinical scores, and cortical neurophysiological parameters. ResultsMCI patients showed less rhythmic movement but no other movement abnormalities. Cortical excitability measures were normal in patients, whereas plasticity was reduced. Movement rhythm abnormalities correlated with frontal dysfunction scores. ConclusionOur study in MCI patients demonstrated abnormal voluntary movement and plasticity changes, with no correlation between the two. Altered rhythm correlated with frontal dysfunction. SignificanceOur results contribute to the understanding of pathophysiological mechanisms of motor impairment in MCI.

Neuropsychiatric symptoms in subjective cognitive complaints (SCC) and mild cognitive impairment (MCI): Detecting changes over time with the Mild Behavioral Impairment Checklist (MBI‐C)

AbstractBackgroundNeurobehavioral Symptoms (NPS) have been usually measured with the Neuropsychiatric‐Inventory (NPI‐Q) (Kaufer et al., 2000) in pre‐dementia individuals. However, this instrument was designed to dementia states. The Mild Behavioral Impairment Checklist (MBI‐C) (Ismail et al., 2017) is an instrument developed to evaluate NPS in pre‐dementia states, including Mild cognitive impairment (MCI) and people with Subjective Cognitive Complaints (SCC). Evidence of longitudinal behavioral change obtained with the MBI‐C is still scarce. Our objective was to compare NPS scores, measured with the NPI‐Q and the MBI‐C, in MCI and SCC participants, at follow‐up.MethodTwo hundred forty participants from the Compostela Ageing Study recruited from primary care health centers, were classified into two groups, MCI (84) and SCC (166). Socio‐demographic, neuropsychological and NPS measures, including MBI‐C and NPI‐Q total scores on severity, were collected at baseline and at follow‐up (mean interval, 24 months) (Table 1). Instrument (NPI‐Q and MBI‐C) total score differences as a function of measurement Time (baseline vs follow‐up) were analyzed using repeated measure ANOVAs including Group (SCC vs MCI) as inter‐subject factor.ResultsSignificant main effects of Time, F(1, 251)=7.68, p = .006, ηp 2=.030, observed power=.789, and Group, F(1, 251)=9.88, p = .002, ηp 2=.038, observed power=.879, were observed for the NPI‐Q total scores (Figure 1). Time*Group interaction was not found. Mixed ANOVA for the MBI‐C total score showed significant main effect of Group, F(1, 248)=13.93, p &lt; .001, ηp 2=.053, observed power=.961, and Time*Group interaction, F(1, 248)=4.89, p = .028, ηp 2=.020, observed power=.596. Post hoc Bonferroni tests for the MBI‐C total score showed (Figure 2) significantly higher behavioral impairment in MCI than in SCC group in both time measurements (baseline and follow‐up).ConclusionsTime main effect in NPI‐Q total scores showed decreases in severity of behavioral symptoms in the follow‐up measurement in spite of the Group (SCC vs MCI). On the contrary, MBI‐C scores pointed‐out slight increases in the follow‐up measurement and, considering the descriptive trends, particularly in MCI group. Only the MBI‐C was able to detect significant differences between MCI and SCC groups both in baseline and follow‐up measurements.

Association between APOEε4 genotype and cardiovascular risk factors in Mexican elderly adults with amnestic and non‐amnestic mild cognitive impairment

AbstractBackgroundThe prevalence of mild cognitive impairment (MCI) is 14 to 18%. MCI has been associated with cardiovascular risk factors. Likewise, the APOEε4 genotype is a gene that confers susceptibility to Alzheimer’s disease. However, the association between APOE genotype, cardiovascular risk and MCI in the Mexican population is not clear, probably as a result of genetic heterogeneity.MethodWe included patients from memory clinic (INCMNSZ) from 2017 to 2019, &gt; 70 years. Three groups were studied: controls without cognitive impairment, with amnestic and nonamnestic MCI. Parametric and nonparametric statistics (x2, ANOVA, multivariate logistic regression analysis, Kruskal‐Wallis) were used for the analysis of statistical differences between groups.Result131 patients were studied, 67.9% were women, the average age was 73.6 (SD 7.3) and the educational level was 12.62 (SD 4.98). Regarding the APOE genotype, 93 (71%) were e3 / e3, 35 (26.7%) e3 / e4, 3 (2.3%) e4 / e4. Three groups of cognitive function were formed: cognitively healthy controls: 59 (45%), amnestic MCI: 29 (22.1%) and nonamnestic MCI: 42 (32.1%). In the group with nonamnestic MCI, statistically significant differences were found in dyslipidemia 48% (P = 0.014), history of CVD 16.5% (P = 0.033) and anemia 8% (0.034). For the group with amnestic MCI, 44.4% hypothyroidism was found (p = 0.15). The multivariate logistic regression analysis showed that the APOE genotype did not significantly modify the association with cardiovascular risk factors and MCI. A greater effect on motor executive function was found in the group of carriers of the APOEε4 genotype (p = 0.042)ConclusionOur study found a low frequency of APOE ε4, compared to African or European populations (Pygmy population, khoisan, waiwai) where the frequency is high (possibly related to race). Previous studies have shown an association between cardiovascular risk and cognitive risk in patients with APOE ε4, however, our study does not show an association between the state of APOE and risk for cognitive impairment, possibly related to variability genetics of the Mexican population, as well as the existence of possible polymorphisms not described in this population. Few studies have shown the association between APOE ε4 polymorphism, hypothyroidism and amnestic DCL.

The cerebrospinal fluid fractalkine as a biomarker in mild cognitive impairment (MCI)

AbstractBackgroundMild cognitive impairment (MCI) is a neurological disorder that occurs in older adults and could be a very early phase of AD dementia. It is not only medical but also socioeconomic and legal problem. Since the MCI symptoms are not yet associated with such serious memory problems as in dementia, it may be difficult to assess the patient's legal capacity. This is an extremely important issue, among others, from the point of view of the patient's decision about his/her treatment process. His ability to fully understand his health situation and the ability to make rational decisions, including being aware of its effects, can be difficult to assess, which has significant legal effects. Therefore, the biomarkers of early stage of dementia are critically important. Growing body of evidence indicated that overexpression of CX3CL‐1 may influence on tau pathology and modulate the dementia disorders development. In our investigation we aim to measure the cerebrospinal fluid concentration of fractalkine to assess the potential usefulness of this protein in the diagnosis of MCI patients. Moreover, the CSF CX3CL‐1 level was compared to the concentrations of classical AD biomarkers, including Aβ‐42, Aβ‐42/Aβ‐40, tau and pTau181.MethodThe study included 18 patients with MCI and 18 non‐demented controls. The cerebrospinal fluid levels of CX3CL‐1 and classical AD biomarkers, such as Aβ‐42, Aβ‐42/Aβ‐40, tau and pTau181, were assessed by immunoenzyme assays.ResultThe concentration of fractalkine was significantly higher in cerebrospinal fluid of MCI patients when compared to non‐demented controls. The increased CSF levels of CX3CL‐1 were observed to significantly correlate with amyloid beta 1‐42 (Aβ‐42) and phosphorylated tau protein (pTau181) in mild cognitive impairment MCI subjects. Moreover, similar association between CX3CL‐1 concentrations and Aβ‐42/Aβ‐40 ratio was revealed in the control group.ConclusionPresented findings indicate a potential role of CX3CL‐1 in the pathology of MCI and possible usefulness of this protein in the early diagnosis of patients with cognitive impairment. The study was conducted with the use of equipment purchased by Medical University of Białystok as part of the RPOWP 2007‐2013 funding, Priority I, Axis 1.1, contract No. UDA‐RPPD.01.01.00‐20‐001/15‐00 dated 26.06.2015.

Investigation on the Alteration of Brain Functional Network and Its Role in the Identification of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is generally regarded as a prodromal stage of Alzheimer’s disease (AD). In coping with the challenges caused by AD, we analyzed resting-state functional magnetic resonance imaging data of 82 MCI subjects and 93 normal controls (NCs). The alteration of brain functional network in MCI was investigated on three scales, including global metrics, nodal characteristics, and modular properties. The results supported the existence of small worldness, hubs, and community structure in the brain functional networks of both groups. Compared with NCs, the network altered in MCI over all the three scales. In scale I, we found significantly decreased characteristic path length and increased global efficiency in MCI. Moreover, altered global network metrics were associated with cognitive level evaluated by neuropsychological assessments. In scale II, the nodal betweenness centrality of some global hubs, such as the right Crus II of cerebellar hemisphere (CERCRU2.R) and fusiform gyrus (FFG.R), changed significantly and associated with the severity and cognitive impairment in MCI. In scale III, although anatomically adjacent regions tended to be clustered into the same module regardless of group, discrepancies existed in the composition of modules in both groups, with a prominent separation of the cerebellum and a less localized organization of community structure in MCI compared with NC. Taking advantages of random forest approach, we achieved an accuracy of 91.4% to discriminate MCI patients from NCs by integrating cognitive assessments and network analysis. The importance of the used features fed into the classifier further validated the nodal characteristics of CERCRU2.R and FFG.R could be potential biomarkers in the identification of MCI. In conclusion, the present study demonstrated that the brain functional connectome data altered at the stage of MCI and could assist the automatic diagnosis of MCI patients.

Digital Biomarkers for the Early Detection of Mild Cognitive Impairment: Artificial Intelligence Meets Virtual Reality.

Elderly people affected by Mild Cognitive Impairment (MCI) usually report a perceived decline in cognitive functions that deeply impacts their quality of life. This subtle waning, although it cannot be diagnosable as dementia, is noted by caregivers on the basis of their relative’s behaviors. Crucially, if this condition is also not detected in time by clinicians, it can easily turn into dementia. Thus, early detection of MCI is strongly needed. Classical neuropsychological measures – underlying a categorical model of diagnosis - could be integrated with a dimensional assessment approach involving Virtual Reality (VR) and Artificial Intelligence (AI). VR can be used to create highly ecologically controlled simulations resembling the daily life contexts in which patients’ daily instrumental activities (IADL) usually take place. Clinicians can record patients’ kinematics, particularly gait, while performing IADL (Digital Biomarkers). Then, Artificial Intelligence employs Machine Learning (ML) to analyze them in combination with clinical and neuropsychological data. This integrated computational approach would enable the creation of a predictive model to identify specific patterns of cognitive and motor impairment in MCI. Therefore, this new dimensional cognitive-behavioral assessment would reveal elderly people’s neural alterations and impaired cognitive functions, typical of MCI and dementia, even in early stages for more time-sensitive interventions.