Biomarker For Mild Cognitive Impairment Research Articles

The influence of alterations in the composition of intestinal microbiota on neurovascular coupling and cognitive dysfunction in individuals afflicted with CSVD

IntroductionAn expanding body of research has explored the crucial role of gut microbiota in cerebral small vessel disease (CSVD). The objective of this study is to investigate alterations in the gut microbiota structure among CSVD patients, to explore the correlation between differential taxonomic levels and the neurovascular coupling index as well as cognitive function and to elucidate the imaging and biomarkers of mild cognitive impairment (MCI) in CSVD. MethodsWe enrolled 104 patients with CSVD and 40 healthy controls (HC). Based on cognitive test scores, CSVD patients were categorized into a cognitively normal group (CSVD-NCI, n=61) and a mild cognitive impairment group (CSVD-MCI, n=43). Performing magnetic resonance imaging (MRI) scans, gut microbiota analysis, as well as clinical and neuropsychological assessments for all participants. Based on arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) imaging data, cerebral blood flow (CBF) and neural activity indices are computed. The coupling indices of CBF/mReHo, CBF/mfALFF, CBF/mALFF, and CBF/mDC are calculated to assess the whole-brain neurovascular coupling changes in patients with CSVD. ResultsSpecies annotation revealed differences in the composition at the phylum and genus levels among the HC, CSVD-NCI, and CSVD-MCI groups. Additionally, differential analysis using the Kruskal-Wallis test demonstrated specific dominant microbial communities in all three groups. The relative abundance of certain dominant microbial communities in CSVD patients exhibited correlations with neurovascular coupling and cognitive function. The combined assessment of Bacteroides genus and CBF/mDC proved effective in distinguishing between CSVD-NCI and CSVD-MCI, providing a novel non-invasive approach for the diagnosis of MCI in CSVD.

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

Disentangling normal and pathological brain atrophy for the diagnosis of mild cognitive impairment and Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder. Mild cognitive impairment (MCI) is the prodromal stage of AD. Accurate identification of these conditions is crucial for the early diagnosis of these diseases. Brain tissue atrophies, observable in regions such as the hippocampus and cortices, serve as an essential biomarker for MCI and AD. However, similar atrophies are also present in elderly individuals with normal cognitive function, albeit to a lesser extent, and can be found in other non-biomarker brain tissues. To address this challenge, we introduce an atrophy disentanglement network (AD-Net), designed to decouple age-related normal atrophies and disease-specific pathological atrophies in structural magnetic resonance imaging images. Specifically, we first design a dual-task prediction module, guiding the model to differentiate normal and pathological atrophies. Subsequently, we devise a feature orthogonality module for enhanced separation of the two types of atrophies. Our extensive experiments demonstrate that AD-Net outperforms existing methods, highlighting the efficiency of the devised dual-task prediction and feature orthogonality modules in disentangling normal and pathological image features and further improving the diagnosis for AD and MCI. The source code is publicly avaliable at https://github.com/CVAPPS24/ADNet.git.

Interleukin-5: an indicator of mild cognitive impairment in patients with type 2 diabetes mellitus - a comprehensive investigation ranging from bioinformatics analysis to clinical research.

Neuroinflammation constitutes an underlying mechanism for cognitive impairment. Here, we endeavor to scrutinize the potential contribution of interleukin-5 (IL-5) towards mild cognitive impairment (MCI), and to assess its diagnostic value for MCI in patients with type 2 diabetes mellitus (T2DM). RNA-seq was used to explore the potential neuroinflammation factors in the hippocampus of diabetic mice with cognitive decline. Additionally, the promising risk factor was verified in animals. Finally, the association between IL-5 levels and cognitive function and its diagnostic value for MCI were assessed. In animals, up-regulated IL-5 mRNA and protein levels were detected by RNA-seq and (or) verified experiments in the hippocampus of diabetic db/db mice with cognitive decline, compared to those of db/m mice without diabetes. In human, compared to diabetic patients without MCI, those with MCI demonstrate elevated levels of IL-5. It is natively associated with Montreal Cognitive Assessment (MoCA) scores, reflecting global cognitive function, and positively correlated with Trail Making Test A (TMTA) scores, reflecting information processing speed. Furthermore, an elevated level of IL-5 is identified as a risk factor for MCI, and a factor that influences TMTA scores. Finally, it is recommended that the cut-off value for IL-5 in the diagnosis of MCI is 22.98 pg/mL, with a sensitivity of 68.6% and specificity of 72.9%. IL-5 is considered a risk factor for MCI in T2DM patients and is associated with their performance in information processing speed. Moreover, an elevated level of IL-5 is a plausible biomarker for MCI in T2DM patients.

Altered brain connectivity in mild cognitive impairment is linked to elevated tau and phosphorylated tau, but not to GAP-43 and Amyloid-β measurements: a resting-state fMRI study

Mild Cognitive Impairment (MCI) is a neurological condition characterized by a noticeable decline in cognitive abilities that falls between normal aging and dementia. Along with some biomarkers like GAP-43, Aβ, tau, and P-tau, brain activity and connectivity are ascribed to MCI; however, the link between brain connectivity changes and such biomarkers in MCI is still being investigated. This study explores the relationship between biomarkers like GAP-43, Aβ, tau, and P-tau, and brain connectivity. We enrolled 25 Participants with normal cognitive function and 23 patients with MCI. Levels of GAP-43, Aβ1–42, t-tau, and p-tau181p in the CSF were measured, and functional connectivity measures including ROI-to-voxel (RV) correlations and the DMN RV-ratio were extracted from the resting-state fMRI data. P-values below 0.05 were considered significant. The results showed that in CN individuals, higher connectivity within the both anterior default mode network (aDMN) and posterior DMN (pDMN) was associated with higher levels of the biomarker GAP-43. In contrast, MCI individuals showed significant negative correlations between DMN connectivity and levels of tau and P-tau. Notably, no significant correlations were found between Aβ levels and connectivity measures in either group. These findings suggest that elevated levels of GAP-43 indicate increased functional connectivity in aDMN and pDMN. Conversely, elevated levels of tau and p-tau can disrupt connectivity through various mechanisms. Thus, the accumulation of tau and p-tau can lead to impaired neuronal connectivity, contributing to cognitive decline.

Abnormal postcentral gyrus voxel-mirrored homotopic connectivity as a biomarker of mild cognitive impairment: A resting-state fMRI and support vector machine analysis

BackgroundWhile patients affected by mild cognitive impairment (MCI) exhibit characteristic voxel-mirrored homotopic connectivity (VMHC) alterations, the ability of such VMHC abnormalities to predict the diagnosis of MCI in these patients remains uncertain. As such, this study was performed to evaluate the potential role of VMHC abnormalities in the diagnosis of MCI. MethodsMCI patients and healthy controls (HCs) were enrolled and subjected to resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing. VMHC and support vector machine (SVM) techniques were then used to examine the collected imaging data. ResultsTotally, 53 MCI patients and 68 healthy controls were recruited. Compared to HCs, MCI patients presented with an increase in postcentral gyrus VMHC. SVM classification demonstrated the ability of postcentral gyrus VMHC values to classify HCs and MCI patients with accuracy, sensitivity, and specificity values of 63.64 %, 71.69 %, and 89.71 %, respectively. ConclusionVMHC abnormalities in the postcentral gyrus may be mechanistically involved in the pathophysiological progression of MCI patients, and these abnormal VMHC patterns may also offer utility as a neuroimaging biomarker for MCI patient diagnosis.

Association of caffeine consumption with cerebrospinal fluid biomarkers in mild cognitive impairment and Alzheimer's disease: A BALTAZAR cohort study.

We investigated the link between habitual caffeine intake with memory impairments and cerebrospinal fluid (CSF) biomarkers in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. MCI (N=147) and AD (N=116) patients of the Biomarker of AmyLoid pepTide and AlZheimer's diseAse Risk (BALTAZAR) cohort reported their caffeine intake at inclusion using a dedicated survey. Associations of caffeine consumption with memory impairments and CSF biomarkers (tau, p-tau181, amyloid beta 1-42 [Aβ1-42], Aβ1-40) were analyzed using logistic and analysis of covariance models. Adjusted on Apolipoprotein E (APOE ε4), age, sex, education level, and tobacco, lower caffeine consumption was associated with higher risk to be amnestic (OR: 2.49 [95% CI: 1.13 to 5.46]; p=0.023) and lower CSF Aβ1-42 (p=0.047), Aβ1-42/Aβ1-40 (p=0.040), and Aβ1-42/p-tau181 (p=0.020) in the whole cohort. Data support the beneficial effect of caffeine consumption to memory impairments and CSF amyloid markers in MCI and AD patients. We studied the impact of caffeine consumption in the BALTAZAR cohort. Low caffeine intake is associated with higher risk of being amnestic in MCI/AD patients. Caffeine intake is associated with CSF biomarkers in AD patients.

Diosgenin-rich Yam (rhizome of Dioscorea batatas) extract ameliorates cognitive functions and plasma biomarkers for mild cognitive impairment and mild Alzheimer's disease: A randomized controlled trial

IntroductionIn Alzheimer's disease (AD), neural circuit disconnection primarily causes memory dysfunction, which leads to the hypothesis that repairing neural networks may be an appropriate treatment strategy for AD. We previously found that diosgenin stimulated neurite regeneration and synapse formation in AD model mice, and diosgenin-rich Yam extract enhanced cognitive function in healthy people and normal mice. In this study, we investigated the efficacy and safety of Yam extract in patients with mild cognitive impairment (MCI) and mild AD. MethodsPatients were administered either diosgenin-rich Yam extract or placebo, respectively, for 24 weeks. The primary outcome was cognitive function, which was evaluated using the Mini Mental State Examination Japanese version (MMSE-J), Alzheimer's Disease Assessment Scale-Cognition (ADAS-Cog), and verbal fluency test; the secondary outcomes were plasma biomarker levels [neurofilament light chain (NfL); axonal marker, glial fibrillary acidic protein levels; reactive astrocyte marker, and the Aβ42/40 ratio; marker of brain Aβ]. ResultsDiosgenin-rich Yam extract improved the ADAS-Cog Praxis domain score and plasma NfL (12 to 24 weeks) in all patients. The number of patients with improved/maintained ADAS-Cog total, Praxis or Memory scores was high in the Yam extract group, but not in placebo group. Divided by severity of pathology, diosgenin-rich Yam extract also improved the total and Memory domain in ADAS-Cog, and plasma NfL levels in patients with MCI. In the Yam extract group, improvement of MMSE-J was related to plasma Aβ42/40 increase, and improvement of plasma NfL was related to better MMSE-J. ConclusionTreatment with diosgenin-rich Yam extract for 24 weeks resulted in modest cognitive improvement and a decrease in plasma NfL levels, which may suggest axonal protection in the brain.

A randomized controlled trial on the effects of traditional Thai mind-body exercise (Ruesi Dadton) on biomarkers in mild cognitive impairment.

Exercise has been shown to reduce the rate of mild cognitive impairment (MCI) and Alzheimer's disease. Although motor coordination movements and poses in Ruesi Dadton (RD) exercises may improve cognitive function, RD is rarely used for MCI. To date, there is insufficient evidence on whether 12 weeks of RD exercise correlates with blood biomarkers related to neurogenesis and plasticity. To determine the effects on blood biomarkers of 12-week RD in MCI. Two-group parallel randomized controlled trial. Community exercise. Individual with MCI. Fifty-eight participants (n.=29 in each group). The RD group performed 60min of RD exercises (15 poses) three times weekly for 12 weeks. The control group received no intervention. In addition, both groups were given information regarding MCI symptoms by the physician on the first day. Peripheral blood was collected to measure serum brain-derived neurotrophic factor (BDNF) and sirtuin 1 (SIRT1) levels before and after intervention. The effects of 12-week RD pre- and post-intervention were examined using 2×2 repeated multivariate analyses, which showed significant differences in interaction by group and time. Student's t-tests and paired t-tests were employed in subsequent analyses to evaluate between-group and within-group differences for both biomarkers. In each test, we discovered increased levels of BDNF and SIRT1 in the RD group but not in the control group. These findings suggested that RD could benefit MCI patients through enhanced BDNF and SIRT1 levels. Twelve weeks of RD might be helpful to patients with MCI and older people who experience cognitive impairment by improving blood biomarkers responsible for brain plasticity and amyloid plaque degradation.

Association of oxidative stress and inflammatory metabolites with Alzheimer’s disease cerebrospinal fluid biomarkers in mild cognitive impairment

BackgroundIsoprostanes and prostaglandins are biomarkers for oxidative stress and inflammation. Their role in Alzheimer's disease (AD) pathophysiology is yet unknown. In the current study, we aim to identify the association of isoprostanes and prostaglandins with the Amyloid, Tau, Neurodegeneration (ATN) biomarkers (Aβ-42, p-tau, and t-tau) of AD pathophysiology in mild cognitive impairment (MCI) subjects.MethodsTargeted metabolomics profiling was performed using liquid chromatography-mass spectrometry (LCMS) in 147 paired plasma-CSF samples from the Ace Alzheimer Center Barcelona and 58 CSF samples of MCI patients from the Mannheim/Heidelberg cohort. Linear regression was used to evaluate the association of metabolites with CSF levels of ATN biomarkers in the overall sample and stratified by Aβ-42 pathology and APOE genotype. We further evaluated the role of metabolites in MCI to AD dementia progression.ResultsIncreased CSF levels of PGF2α, 8,12-iso-iPF2α VI, and 5-iPF2α VI were significantly associated (False discovery rate (FDR) < 0.05) with higher p-tau levels. Additionally, 8,12-iso-iPF2α VI was associated with increased total tau levels in CSF. In MCI due to AD, PGF2α was associated with both p-tau and total tau, whereases 8,12-iso-iPF2α VI was specifically associated with p-tau levels. In APOE stratified analysis, association of PGF2α with p-tau and t-tau was observed in only APOE ε4 carriers while 5-iPF2α VI showed association with both p-tau and t-tau in APOE ε33 carriers. CSF levels of 8,12- iso-iPF2α VI showed association with p-tau and t-tau in APOE ε33/APOE ε4 carriers and with t-tau in APOE ε3 carriers. None of the metabolites showed evidence of association with MCI to AD progression.ConclusionsOxidative stress (8,12-iso-iPF2α VI) and inflammatory (PGF2α) biomarkers are correlated with biomarkers of AD pathology during the prodromal stage of AD and relation of PGF2α with tau pathology markers may be influenced by APOE genotype.

EEG-Based Detection of Mild Cognitive Impairment Using DWT-Based Features and Optimization Methods.

In recent years, electroencephalography (EEG) has been investigated for identifying brain disorders. This technique involves placing multiple electrodes (channels) on the scalp to measure the brain's activities. This study focuses on accurately detecting mild cognitive impairment (MCI) from the recorded EEG signals. To achieve this, this study first introduced discrete wavelet transform (DWT)-based approaches to generate reliable biomarkers for MCI. These approaches decompose each channel's signal using DWT into a set of distinct frequency band signals, then extract features using a non-linear measure such as band power, energy, or entropy. Various machine learning approaches then classify the generated features. We investigated these methods on EEGs recorded using 19 channels from 29 MCI patients and 32 healthy subjects. In the second step, the study explored the possibility of decreasing the number of EEG channels while preserving, or even enhancing, classification accuracy. We employed multi-objective optimization techniques, such as the non-dominated sorting genetic algorithm (NSGA) and particle swarm optimization (PSO), to achieve this. The results show that the generated DWT-based features resulted in high full-channel classification accuracy scores. Furthermore, selecting fewer channels carefully leads to better accuracy scores. For instance, with a DWT-based approach, the full-channel accuracy achieved was 99.84%. With only four channels selected by NSGA-II, NSGA-III, or PSO, the accuracy increased to 99.97%. Furthermore, NSGA-II selects five channels, achieving an accuracy of 100%. The results show that the suggested DWT-based approaches are promising to detect MCI, and picking the most useful EEG channels makes the accuracy even higher. The use of a small number of electrodes paves the way for EEG-based diagnosis in clinical practice.

Neurovascular coupling, functional connectivity, and cerebrovascular endothelial extracellular vesicles as biomarkers of mild cognitive impairment.

Mild cognitive impairment (MCI) is a prodromal stage of dementia. Understanding the mechanistic changes from healthy aging to MCI is critical for comprehending disease progression and enabling preventative intervention. Patients with MCI and age-matched controls (CN) were administered cognitive tasks during functional near-infrared spectroscopy (fNIRS) recording, and changes in plasma levels of extracellular vesicles (EVs) were assessed using small-particle flow cytometry. Neurovascular coupling (NVC) and functional connectivity (FC) were decreased in MCI compared to CN, prominently in the left-dorsolateral prefrontal cortex (LDLPFC). We observed an increased ratio of cerebrovascular endothelial EVs (CEEVs) to total endothelial EVs in patients with MCI compared to CN, correlating with structural MRI small vessel ischemic damage in MCI. LDLPFC NVC, CEEV ratio, and LDLPFC FC had the highest feature importance in the random Forest group classification. NVC, CEEVs, and FC predict MCI diagnosis, indicating their potential as markers for MCI cerebrovascular pathology. Neurovascular coupling (NVC) is impaired in mild cognitive impairment (MCI). Functional connectivity (FC) compensation mechanism is lost in MCI. Cerebrovascular endothelial extracellular vesicles (CEEVs) are increased in MCI. CEEV load strongly associates with cerebral small vessel ischemic lesions in MCI. NVC, CEEVs, and FC predict MCI diagnosis over demographic and comorbidity factors.

What Are the Reliable Plasma Biomarkers for Mild Cognitive Impairment? A Clinical 4D Proteomics Study and Validation.

At present, Alzheimer's disease (AD) lacks effective treatment means, and early diagnosis and intervention are the keys to treatment. Therefore, for mild cognitive impairment (MCI) and AD patients, blood sample analysis using the 4D nonstandard (label-free) proteomic in-depth quantitative analysis, looking for specific protein marker expression differences, is important. These marker levels change as AD progresses, and the analysis of these biomarkers changes with this method, which has the potential to show the degree of disease progression and can be used for the diagnosis and preventive treatment of MCI and AD. Patients were recruited according to the inclusion and exclusion criteria and divided into three groups according to scale scores. Elderly patients diagnosed with AD were selected as the AD group (n = 9). Patients diagnosed with MCI were classified into the MCI group (n = 10). Cognitively healthy elderly patients were included in the normal cognition control group (n = 10). Patients' blood samples were used for 4D label-free proteomic in-depth quantitative analysis to identify potential blood biomarkers. The sample size of each group was expanded (n = 30), and the selected biomarkers were verified by enzyme-linked immunosorbent assay (ELISA) to verify the accuracy of the proteomic prediction. Six specific blood markers, namely, APOE, MMP9, UBR5, PLA2G7, STAT5B, and S100A8, were detected by 4D label-free proteomic quantitative analysis. These markers showed a statistically significant upregulation trend in the MCI and AD groups compared with the normal cognition control group (P < 0.05). ELISA results showed that the levels of these six proteins in the MCI group were significantly higher than those in the normal cognition control group, and the levels of these six proteins in the AD group were significantly higher than those in the MCI group (P < 0.05). The plasma levels of APOE, MMP9, UBR5, PLA2G7, STAT5B, and S100A8 in cognitively healthy elderly patients and patients with MCI and AD were significantly different and, more importantly, showed a trend of increasing expression. These results indicate that these six human plasma markers have important diagnostic and therapeutic potential in the identification of cognitive impairment and have value for in-depth research and clinical application.

Alterations in brain functional connectivity in patients with mild cognitive impairment: A systematic review and meta-analysis of functional near-infrared spectroscopy studies.

Emerging evidences suggest that cognitive deficits in individuals with mild cognitive impairment (MCI) are associated with disruptions in brain functional connectivity (FC). This systematic review and meta-analysis aimed to comprehensively evaluate alterations in FC between MCI individuals and healthy control (HC) using functional near-infrared spectroscopy (fNIRS). Thirteen studies were included in qualitative analysis, with two studies synthesized for quantitative meta-analysis. Overall, MCI patients exhibited reduced resting-state FC, predominantly in the prefrontal, parietal, and occipital cortex. Meta-analysis of two studies revealed a significant reduction in resting-state FC from the right prefrontal to right occipital cortex (standardized mean difference [SMD]=-.56; p<.001), left prefrontal to left occipital cortex (SMD=-.68; p<.001), and right prefrontal to left occipital cortex (SMD=-.53; p<.001) in MCI patients compared to HC. During naming animal-walking task, MCI patients exhibited enhanced FC in the prefrontal, motor, and occipital cortex, whereas a decrease in FC was observed in the right prefrontal to left prefrontal cortex during calculating-walking task. In working memory tasks, MCI predominantly showed increased FC in the medial and left prefrontal cortex. However, a decreased in prefrontal FC and a shifted in distribution from the left to the right prefrontal cortex were noted in MCI patients during a verbal frequency task. In conclusion, fNIRS effectively identified abnormalities in FC between MCI and HC, indicating disrupted FC as potential markers for the early detection of MCI. Future studies should investigate the use of task- and region-specific FC alterations as a sensitive biomarker for MCI.

Dual-task turn velocity - a novel digital biomarker for mild cognitive impairment and dementia.

Disorders associated with cognitive impairment impose a significant burden on both families and society. Previous studies have indicated that gait characteristics under dual-task as reliable markers of early cognitive impairment. Therefore, digital gait detection has great potential for future cognitive screening. However, research on digital biomarkers based on smart devices to identify cognitive impairment remains limited. The aim of this study is to explore digital gait biomarkers by utilizing intelligent wearable devices for discriminating mild cognitive impairment and dementia. This study included 122 subjects (age: 74.7 ± 7.7 years) diagnosed with normal cognition (NC, n = 38), mild cognitive impairment (MCI, n = 42), or dementia (n = 42). All subjects underwent comprehensive neuropsychological assessments and cranial Magnetic Resonance Imaging (MRI). Gait parameters were collected using validated wearable devices in both single-task and dual-task (DT). We analyzed the ability of gait variables to predict MCI and dementia, and examined the correlations between specific DT-gait parameters and sub-cognitive functions as well as hippocampal atrophy. Our results demonstrated that dual-task could significantly improve the ability to predict cognitive impairment based on gait parameters such as gait speed (GS) and stride length (SL). Additionally, we discovered that turn velocity (TV and DT-TV) can be a valuable novel digital marker for predicting MCI and dementia, for identifying MCI (DT-TV: AUC = 0.801, sensitivity 0.738, specificity 0.842), and dementia (DT-TV: AUC = 0.923, sensitivity 0.857, specificity 0.842). The correlation analysis and linear regression analysis revealed a robust association between DT-TV and memory function, as well as the hippocampus atrophy. This study presents a novel finding that DT-TV could accurately identify varying degrees of cognitive impairment. DT-TV is strongly correlated with memory function and hippocampus shrinkage, suggests that it can accurately reflect changes in cognitive function. Therefore, DT-TV could serve as a novel and effective digital biomarker for discriminating cognitive impairment.

Beyond CSF and Neuroimaging Assessment: Evaluating Plasma miR-145-5p as a Potential Biomarker for Mild Cognitive Impairment and Alzheimer's Disease.

Alzheimer's disease (AD) is the most common cause of dementia. New strategies for the early detection of MCI and sporadic AD are crucial for developing effective treatment options. Current techniques used for diagnosis of AD are invasive and/or expensive, so they are not suitable for population screening. Cerebrospinal fluid (CSF) biomarkers such as amyloid β1-42 (Aβ1-42), total tau (T-tau), and phosphorylated tau181 (P-tau181) levels are core biomarkers for early diagnosis of AD. Several studies have proposed the use of blood-circulating microRNAs (miRNAs) as potential novel early biomarkers for AD. We therefore applied a novel approach to identify blood-circulating miRNAs associated with CSF biomarkers and explored the potential of these miRNAs as biomarkers of AD. In total, 112 subjects consisting of 28 dementia due to AD cases, 63 MCI due to AD cases, and 21 cognitively healthy controls were included. We identified seven Aβ1-42-associated plasma miRNAs, six P-tau181-associated plasma miRNAs, and nine Aβ1-42-associated serum miRNAs. These miRNAs were involved in AD-relevant biological processes, such as PI3K/AKT signaling. Based on this signaling pathway, we constructed an miRNA-gene target network, wherein miR-145-5p has been identified as a hub. Furthermore, we showed that miR-145-5p performs best in the prediction of both AD and MCI. Moreover, miR-145-5p also improved the prediction performance of the mini-mental state examination (MMSE) score. The performance of this miRNA was validated using different datasets including an RT-qPCR dataset from plasma samples of 23 MCI cases and 30 age-matched controls. These findings indicate that blood-circulating miRNAs that are associated with CSF biomarkers levels and specifically plasma miR-145-5p alone or combined with the MMSE score can potentially be used as noninvasive biomarkers for AD or MCI screening in the general population, although studies in other AD cohorts are necessary for further validation.

Metabolic and Environmental Biomarkers in Mild Cognitive Impairment and Dementia: An Exploratory Study.

Objective: To determine the frequency with which suspected pathogenic factors, including metals and metabolites that might contribute to Alzheimer's disease (AD), may be found in patients with cognitive impairment through commonly available blood tests. Methods: A variety of serum studies, including metals, ammonia, homocysteine, vitamin B12, folate, thyroid tests, metabolic products, and inflammatory markers, were measured in two cohorts: one meeting mild cognitive impairment (MCI) criteria and the other meeting mild-to-moderate dementia (DE) criteria. Medications these patients received were reviewed. Results: Metal abnormalities were detected in over half the subjects, including evidence of mercury, lead, and arsenic elevation as well as instances of excessive essential metals, iron (Fe), and copper. Some metal aberration was detected in 64% of the DE group and 66% of the MCI group. Females were more likely to have elevated copper, consistent with hormonal effects on copper excretion. Homocysteinemia was the most common abnormality, detected in 71% with DE and 67% with MCI, while methylmalonic acid was not elevated. Slight hyperammonemia was moderately common (38%) suggesting a hepatic factor in this subset. Findings of moderate insulin resistance were present in nearly half (44% DE, 52% MCI). Sixty of 65 (92%) had at least one abnormal biomarker and 60% had two or more. The most common drug taken by the total cohort was proton pump inhibitors at 22% DE and 38% MCI. Conclusions: This study suggests that both toxic metals and excessive vital metals such as copper and iron, as well as common metabolic and hepatic factors are detectable at both stages of MCI and DE. There appears to be a multiplicity of provocative factors leading to DE. Individualized interventions based on these parameters may be a means to reduce cognitive decline leading to DE. A more comprehensive prospective study of these environmental and metabolic factors with corrective early interventions appears warranted.

Task-evoked pupillary responses as potential biomarkers of mild cognitive impairment.

Eye movement alterations are effective biomarkers for Alzheimer's disease (AD). This study examines task-evoked pupillary responses (TEPRs) as potential biomarkers of the mild cognitive impairment (MCI), the symptomatic stage preceding AD. The prospective cohort study included 213 MCI patients and 514 cognitively normal controls (CNs). Participants performed a prosaccade (PS) or antisaccade (AS) task while their eye movements were tracked using a Tobii Pro Spectrum system. The CNs showed unique TEPRs linked to better performance, characterized by larger baselines, greater PS target-onset variability, and smaller AS target-onset variability. Conversely, for MCI patients, better performance was linked to larger AS target-onset sizes. Furthermore, MCI patients displayed reduced dilation during the cue and target-onset periods compared to CNs. MCI patients showed altered pupillary response patterns associated with cognitive task performance, highlighting the potential of oculomotor changes as a biomarker for early cognitive decline. MCI patients displayed markedly smaller pupil dilation than CNs in response to cue and target stimuli.For MCI patients, larger pupil size upon target appearance during antisaccades correlated with better performance.Faster and more consistent prosaccades were linked to better performance in both groups.For MCI patients, the association between longer AS latencies and better performance was more pronounced than in CNs.Combined analysis of TEPRs and saccade performances in a sizeable cohort strengthens the generalizability of our findings to the broader MCI population.

Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status.

Although cerebrospinal fluid (CSF) amyloid-β42 peptide (Aβ42) and phosphorylated tau (p-tau) and blood p-tau are valuable for differential diagnosis of Alzheimer's disease (AD) from cognitively normal (CN) there is a lack of validated biomarkers for mild cognitive impairment (MCI). This study sought to determine how plasma and CSF protein markers compared in the characterization of MCI and AD status. This cohort study included Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 75 proteins measured commonly in plasma and CSF (257 total, 46 CN, 143 MCI, and 68 AD). Logistic regression, least absolute shrinkage and selection operator (LASSO) and Random Forest (RF) methods were used to identify the protein candidates for the disease classification. We observed that six plasma proteins panel (APOE, AMBP, C3, IL16, IGFBP2, APOD) outperformed the seven CSF proteins panel (VEGFA, HGF, PRL, FABP3, FGF4, CD40, RETN) as well as AD markers (CSF p-tau and Aβ42) to distinguish the MCI from AD [area under the curve (AUC) = 0.75 (plasma proteins), AUC = 0.60 (CSF proteins) and AUC = 0.56 (CSF p-tau and Aβ42)]. Also, these six plasma proteins performed better than the CSF proteins and were in line with CSF p-tau and Aβ42 in differentiating CN versus MCI subjects [AUC = 0.89 (plasma proteins), AUC = 0.85 (CSF proteins) and AUC = 0.89 (CSF p-tau and Aβ42)]. These results were adjusted for age, sex, education, and APOEϵ4 genotype. This study suggests that the combination of 6 plasma proteins can serve as an effective marker for differentiating MCI from AD and CN.

The plasma derived exosomal miRNA-483-5p/502-5p serve as potential MCI biomarkers in aging

Alzheimer's disease (AD) is the leading cause of dementia and is rapidly becoming one of the most costly, fatal diseases, which is typically discovered in the late stage of molecular pathology, at which point medication intervention is irreversible. As a result, there is an urgent need for a low-cost, least-invasive way of screening cognitive impairment, with the goal of identifying persons at risk of AD. Mild cognitive impairment (MCI) has been described as a transitional state between normal cognitive aging and AD. Early detection and timely tracking of MCI can to some extent prevent the progression towards AD. We found a population in Northwestern China has a comparatively high prevalence of MCI. Continued education, consistent exercise, and a secure financial situation can all help older people maintain cognitive function. Due to the critical role of circulating microRNAs in intercellular signaling and the perturbations thereof, their investigation has assumed paramount significance in elucidating various pathological conditions. Numerous investigations have substantiated the significance of circulating miRNAs specifically in MCI. Here, we evaluated miR-483-5p (Area Under the Curve (AUC) is 0.901, sensitivity 79.2 % and specificity 100 %) and miR-502-5p (AUC is 0.872, sensitivity 79.2 % and specificity 83.3 %), which were derived from plasma exosomes and maintained at high levels in elderly people with MCI, could be employed as promising noninvasive biomarkers.