Normal Cognition Group Research Articles

Correlation between lipoprotein-associated phospholipase A2 and poststroke mild cognitive impairment

ABSTRACT Objectives This study aimed to investigate the correlationbetween serum lipoprotein-associated phospholipase A2 (Lp-PLA2) and poststrokemild cognitive impairment (PSMCI). Methods The patients included in the study were divided into PSMCI (68 cases)and cognitively normal (CN) (218 cases) groups and followed up for six months.Demographic and clinical data were collected. A logistic regression analysiswas performed to determine whether Lp-PLA2 is an independent risk factor forPSMCI. Spearman’s correlation analysis was used to examine the correlationbetween Lp-PLA2 levels and Montreal CognitiveAssessment (MoCA) scores. A receiver operating characteristic (ROC) curveanalysis was performed to determine the diagnostic threshold value of Lp-PLA2for PSMCI. Results Serum Lp-PLA2 levels were significantly higherin the PSMCI group than in the CN group. The logistic regression analysisshowed that Lp-PLA2 was an independent risk factor for PSMCI (OR = 1.05, 95% CI= 1.03–1.07). Spearman’s correlation analysis revealed a significantcorrelation between the Lp-PLA2 levels and MoCA scores (R= -0.49). The area under the ROC curve forLp-PLA2 was 0.849, and the threshold value for PSMCI occurrence was 236.8 ng/ml. Conclusions Elevated serum Lp-PLA2 is an independent riskfactor for PSMCI and may serve as a potential biomarker for PSMCI.

Disrupted single-subject gray matter networks are associated with cognitive decline and cortical atrophy in Alzheimer's disease.

Research has shown disrupted structural network measures related to cognitive decline and future cortical atrophy during the progression of Alzheimer's disease (AD). However, evidence regarding the individual variability of gray matter network measures and the associations with concurrent cognitive decline and cortical atrophy related to AD is still sparse. To investigate whether alterations in single-subject gray matter networks are related to concurrent cognitive decline and cortical gray matter atrophy during AD progression. We analyzed structural MRI data from 185 cognitively normal (CN), 150 mild cognitive impairment (MCI), and 153 AD participants, and calculated the global network metrics of gray matter networks for each participant. We examined the alterations of single-subject gray matter networks in patients with MCI and AD, and investigated the associations of network metrics with concurrent cognitive decline and cortical gray matter atrophy. The small-world properties including gamma, lambda, and sigma had lower values in the MCI and AD groups than the CN group. AD patients had reduced degree, clustering coefficient, and path length than the CN and MCI groups. We observed significant associations of cognitive ability with degree in the CN group, with gamma and sigma in the MCI group, and with degree, connectivity density, clustering coefficient, and path length in the AD group. There were significant correlation patterns between sigma values and cortical gray matter volume in the CN, MCI, and AD groups. These findings suggest the individual variability of gray matter network metrics may be valuable to track concurrent cognitive decline and cortical atrophy during AD progression. This may contribute to a better understanding of cognitive decline and brain morphological alterations related to AD.

Markers of brain injury in patients with aneurysmal subarachnoid hemorrhage

Aim To investigate the correlation of serum changes and markers of brain injury (BI) in cerebrospinal fluid (CSF) with postoperative cognitive dysfunction (POCD) in patients with cerebral aneurysmal subarachnoid haemorrhage (aSAH). Methods 120 patients diagnosed with aSAH were included. 3 months after surgery, these patients were divided into a normal cognition group and a cognitive dysfunction (CD) group relying on the Montreal Cognitive Assessment (MoCA) Scale. Results The correlations were analysed between the serological changes and the levels of BI markers, such as neurofilament-light (NF-L) protein, Ubisquitin C-terminal hydrolase L1(UCH-L1), Glial Fibrillary Acidic Protein (GFAP), and neuron specific enolase (NSE) in patients after surgery. Hunt-Hess grading standard was employed to determine the severity of aSAH in patients. The mean values of NF-L, UCH-L1, GFAP, and NSE were (8.2 ± 4.3) pg/mL, (0.7 ± 0.3) ng/mL, (2.2 ± 0.4) ng/mL, and (48.5 ± 10.9) ng/mL in patients with severe aSAH, which were remarkably higher than those in patients with mild aSAH [(3.5 ± 0.7) pg/mL, (0.5 ± 0.2) ng/mL, (1.3 ± 0.7) ng/mL, (30.7 ± 8.2) ng/mL]. The sensitivity, specificity, and accuracy of the combined prediction of four detections for POCD were 90.80%, 84.20%, and 82.80%, respectively, which were greatly higher than those of four independent predictions (p < 0.05). The combined prediction effect of the four items, with the area under the curve (AUC) of 0.938 and the 95% confidence interval (CI) of 0.851-0.926. Conclusions BI markers NF-L, UCH-L1, GFAP, and NSE could be utilized as predictors of POCD in patients with aSAH, deserving a reference value.

An analysis of factors influencing cognitive dysfunction among older adults in Northwest China based on logistic regression and decision tree modelling

BackgroundCognitive dysfunction is one of the leading causes of disability and dependence in older adults and is a major economic burden on the public health system. The aim of this study was to investigate the risk factors for cognitive dysfunction and their predictive value in older adults in Northwest China.MethodsA cross-sectional study was conducted using a multistage sampling method. The questionnaires were distributed through the Elderly Disability Monitoring Platform to older adults aged 60 years and above in Northwest China, who were divided into cognitive dysfunction and normal cognitive function groups. In addition to univariate analyses, logistic regression and decision tree modelling were used to construct a model to identify factors that can predict the occurrence of cognitive dysfunction in older adults.ResultsA total of 12,494 valid questionnaires were collected, including 2617 from participants in the cognitive dysfunction group and 9877 from participants in the normal cognitive function group. Univariate analysis revealed that ethnicity, BMI, age, educational attainment, marital status, type of residence, residency status, current work status, main economic source, type of chronic disease, long-term use of medication, alcohol consumption, participation in social activities, exercise status, social support, total scores on the Balanced Test Assessment, total scores on the Gait Speed Assessment total score, and activities of daily living (ADL) were significantly different between the two groups (all P < 0.05). According to logistic regression analyses, ethnicity, BMI, educational attainment, marital status, residency, main source of income, chronic diseases, annual medical examination, alcohol consumption, exercise status, total scores on the Balanced Test Assessment, and activities of daily living (ADLs) were found to influence cognitive dysfunction in older adults (all P < 0.05). In the decision tree model, the ability to perform activities of daily living was the root node, followed by total scores on the Balanced Test Assessment, marital status, educational attainment, age, annual medical examination, and ethnicity.ConclusionsTraditional risk factors (including BMI, literacy, and alcohol consumption) and potentially modifiable risk factors (including balance function, ability to care for oneself in daily life, and widowhood) have a significant impact on the increased risk of cognitive dysfunction in older adults in Northwest China. The use of decision tree models can help health care workers better assess cognitive function in older adults and develop personalized interventions. Further research could help to gain insight into the mechanisms of cognitive dysfunction and provide new avenues for prevention and intervention.

The Shape Trail Test Is Sensitive in Differentiating Older Adults with Mild Cognitive Impairment: A Culture-neutral Five-minute Test

IntroductionThe Shape Trail Test (STT) was developed based upon the Trail Making Test, as a culture-neutral test for measuring processing speed and mental flexibility. This study aims to evaluate the accuracy and validity of this five-minute test for differentiating individuals with normal cognition (NC), subjective memory impairment (SMI), and mild cognitive impairment (MCI).MethodThe study included 210 participants aged 50–80 years, with 70 participants in each group matched for age, education, and gender.ResultsNo significant difference in STT measures was found between the NC and SMI groups. In contrast, both the NC and SMI groups exhibited significantly better performance (shorter completion time in STT-A and STT-B and fewer STT-B errors) than the MCI group. No significant group differences were found in STT-A errors. Stepwise regression analysis identified three significant predictors for classifying the MCI group from the NC and/or SMI groups, including the STT-B completion time, the STT-A errors, and the interaction between STT-B completion time and STT-B errors. The composite score of these three predictors demonstrated good discriminatory power for classifying the MCI group from the other groups, with area under the curves (AUCs) of 0.76–0.79 (p < 0.001), sensitivities of 78.6%–80%, and specificities of 60%–61.4%. However, none of the STT measures or their interactions were significant predictors for differentiating the SMI group from the NC group. Besides, the STT measures were significantly correlated with age, education, and executive function measures.DiscussionThe STT could be a culture- and language-free, reliable test for assessing executive function and a sensitive test for predicting MCI.

Comparison of Cognitive Impairment Diagnosis Criteria in Clinical Settings: Conventional vs. Neuropsychological.

Theories on Alzheimer disease pathogenesis propose a gap between pathological changes and the onset of clinical symptoms. The early detection of cognitive decline is crucial for the implementation of preventive strategies. Mild cognitive impairment is a transitional stage and an accurate diagnosis is vital. However, the diagnosis of mild cognitive impairment varies due to inconsistent diagnostic criteria. This study aims to explore the effectiveness of comprehensive neuropsychological criteria, including all cognitive domains, for diagnosing cognitive impairment in clinical settings. The study included 509 subjects with subjective cognitive complaints between 2017 and 2021. They were diagnosed using the conventional and neuropsychological criteria, and the results were named the complex criteria (conventional criteria-neuropsychological criteria). Concordance between the conventional and neuropsychological diagnostic criteria diagnoses was 87.82%. Some participants diagnosed with mild cognitive impairment or dementia using the conventional criteria were classified as normal according to the neuropsychological criteria. Notably, the mild cognitive impairment - normal cognition (MCI-NC) and dementia (DEM)-NC (normal cognition) groups exhibited distinct characteristics. The MCI-NC group had higher depression scores (P = .008) and better memory performance (P = .026) and executive function (P = .020) than the MCI-MCI group. The DEM-NC group had better instrumental activities of daily living (P < .001) than the DEM-DEM group. This study highlights the complexity of diagnosing cognitive impairment and the importance of comprehensive criteria. Relying solely on conventional criteria may lead to overdiagnosis. The neuropsychological criteria consider various cognitive domains and better discriminate between individuals with MCIs or other factors that contribute to cognitive difficulties.

Whole Transcriptome Sequencing of Peripheral Blood Identifies the Alzheimer's Disease-Related circRNA-miRNA-lncRNA Pathway.

Previous studies on transcriptional profiles suggested dysregulation of multiple RNA species in Alzheimer's disease. However, despite recent investigations revealing various aspects of circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) networks in Alzheimer's Disease (AD) pathogenesis, few genome-wide studies have explored circRNA-associated profiles in AD patients exhibiting varying degrees of cognitive loss. To investigate the potential pathogenesis-related molecular biological changes in the various stages of AD progression. Whole transcriptome sequencing was performed on the peripheral blood of 7 normal cognition (NC) subjects, 8 patients with mild cognitive impairment, 8 AD patients with mild dementia (miD), and 7 AD patients with moderate dementia (moD). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to predict the potential functions of the maternal genes of microRNAs (miRNAs), circRNAs and long non-coding RNAs (lncRNAs). The construction of ceRNA network was performed between the NC group and each diseased group based on the differently expressed RNAs. In total, 3568 messenger RNAs (mRNAs), 142 miRNAs, 990 lncRNAs, and 183 circRNAs were identified as significantly differentially expressed across the four groups. GO and KEGG enrichment analysis revealed the significant roles of GTPase activity and the MAPK signaling pathway in AD pathogenesis. A circRNA-miRNA-lncRNA ceRNA pathway, characterized by the downregulated hsa-miR-7-5p and upregulated hsa_circ_0001170, was identified based on the differentially expressed RNAs between the NC group and the moD group. The study suggests that circRNAs may be independent of mRNAs in AD pathogenesis and holds promise as potential biomarkers for AD clinical manifestations and pathological changes.

Correlation between serum inflammatory factors and cognitive function in patients with high-altitude polycythemia: A case-control study.

The purpose of this study is to investigate the serum inflammatory factors in patients with high-altitude polycythemia (HAPC) and their correlation with cognitive function. The subjects were recruited and placed into a HAPC group and control group. Serum samples were collected, and inflammatory factors (interleukin-1beta [IL-1β], monocyte chemoattractant protein-1 [MCP-1], and tumor necrosis factor-alpha [TNF-α]) were measured using ELISA kits. The mini-mental State Examination (MMSE) was used to assess cognitive function. According to the MMSE scores, HAPC group was further divided into normal cognitive function group (HNCF) and cognitive dysfunction group (HCDF). In comparison with the control group, the MMSE scores in the HAPC group were significantly low (P < .05), whereas the serum levels of IL-1β, MCP-1, and TNF-α were significantly high (P < .01). Among the HAPC group (n = 60), 21 belonged to the HCDF and 39 belonged to the HNCF. Compared with the HNCF, the IL-1β, MCP-1, and TNF-α in the HCDF were significantly increased (P < .01). The Pearson correlation analysis showed that inflammatory factors were positively correlated with hemoglobin, and negatively correlated with MMSE. Serum inflammatory cytokines IL-1, MCP-1, and TNF-α were increased in HAPC, and HAPC exhibited cognitive dysfunction. Considering chronic hypoxia environment influences the change of the red blood cell metabolic and inflammatory factor, red blood cells and inflammatory factor in plateau is likely to be affected by patients with vascular lesions, increase cognitive impairment.

Circulating plasma-derived extracellular vesicles expressing bone and kidney markers are associated with neurocognitive impairment in people living with HIV.

Although effective antiretroviral therapy (ART) has improved the life expectancy of people with HIV (PWH), the prevalence of milder forms of HIV-associated neurocognitive disorders (HAND) persist, and it is associated with systemic and neuro-inflammatory processes that could impact other organ systems. However, the complex signaling mechanisms between the bone-kidney systems and the brain in HAND remain unknown. Extracellular vesicles (EVs) play a potential role in inter-organ communication and are involved in regulating cell activity in distant tissues. In this study, we examined whether levels of EVs from bone-and kidney-related cells associate with cognitive dysfunction and explored the relationship between kidney-bone EV axis in PWH experiencing cognitive deficits. EV subtypes were characterized in plasma from 61 PWH with either cognitive impairment (CI, n = 53) or normal cognition (NC, n = 8) based on the American Academy of Neurology criteria for HIV-associated dementia (HAD, n = 11), minor cognitive motor disorder (MCMD, n = 25) or asymptomatic neurocognitive impairment (ANI, n = 17) by spectral flow cytometry. EVs were profiled with markers reflecting bone and kidney cell origin. A support vector machine learning-based model was employed for analyses of EV phenotypes to predict the cognitive dysfunction. Plasma-EVs expressing osteocalcin, sclerostin, and nephrin were significantly higher in the cognitive impairment group compared to the normal cognition group. EVs bearing kidney cell markers correlated significantly with bone-derived EVs. A machine learning-based model, comprised of osteocalcin+, nephrin+, and CD24+ EVs predicted cognitive impairment in PWH on ART. Our study reveals that neurocognitive impairment in PWH is associated with increased levels of plasma EVs enriched with the bone markers osteocalcin and sclerostin and the kidney marker nephrin, suggesting that these EV subtypes may be novel candidate biomarkers for disease-spanning neurocognitive dysfunction. Moreover, the relationship between bone-derived EVs with kidney-derived EVs may suggest their role in mediating inter-organ crosstalk in the pathogenesis of HIV-associated cognitive impairment.

Cholinergic hyperintensity pathways are associated with cognitive performance in patients with asymptomatic carotid artery stenosis

ObjectivesWe aimed to determine whether asymptomatic carotid artery stenosis (ACS) induced cognitive impairments were related to the cholinergic hyperintensity pathway. MethodsThis cross-sectional study included patients with moderate-to-severe ACS, who were categorized into mild cognitive impairment (MCI) and normal cognition groups on the basis of Montreal Cognitive Assessment (MoCA) scores. The cholinergic pathway hyperintensity scale (CHIPS), Fazekas, and medial temporal atrophy (MTA) scores were assessed. SPSS software was used for statistical analyses. ResultsA total of 117 ACS patients (70.89 ± 8.81 years) and 105 controls (67.87 ± 9.49 years) were evaluated (t = 2.46, p = 0.015). The ACS group showed a worse median Mini-Mental Status Examination (MMSE) score (z = −2.41, p = 0.016) and MoCA score (z = −3.51, p < 0.001), and a significantly higher median total CHIPS score (z = 4.88, p < 0.001) and mean Fazekas score (t = 2.39, p = 0.018). In the correlation analysis, the MoCA score showed a significant negative correlation with the CHIPS score (ρ = −0.41, p < 0.001) and Fazekas score (ρ = −0.31, p < 0.001) in ACS group. Logistic regression analyses suggested that CHIPS scores were risk factors for MCI in patients with ACS (odds ratio [OR] = 1.07, 95% Confidence Interval [CI]1.01–1.13 and controls (OR = 1.09, 95%CI 1.01–1.17), while the MTA and Fazekas scores showed no predictive power. The receiver operating characteristic curve showed that the area under the curve of the CHIPS score for predicting MCI was 0.71 in ACS group, but was only 0.57 in controls. ConclusionsPatients with ACS showed poorer cognitive performance and higher CHIPS and Fazekas scores. CHIPS, but not Fazekas, scores were risk factors for cognitive impairment and were a valuable factor to predict MCI in patients with ACS.

A Nomogram Including Total Cerebral Small Vessel Disease Burden Score for Predicting Mild Vascular Cognitive Impairment in Patients with Type 2 Diabetes Mellitus.

Total cerebral small vessel disease (CSVD) burden score is an important predictor of vascular cognitive impairment (VCI). However, few predictive models of VCI in type 2 diabetes mellitus (T2DM) patients have included the total CSVD burden score, especially in the early stage of VCI. To develop and validate a nomogram that includes the total CSVD burden score to predict mild VCI in patients with T2DM. A total of 322 eligible participants with T2DM who were divided into mild and normal cognitive groups were enrolled in this retrospective study. Demographic data, laboratory data and imaging markers of CSVD were collected. The total CSVD burden score was calculated by combining the different CSVD markers. Step-backward multivariable logistic regression analysis with the Akaike information criterion was applied to select significant predictors and develop a best-fit predictive nomogram. The performance of the nomogram was assessed in terms of discriminative ability, calibrated ability, and clinical usefulness. The nomogram model consisted of five variables: age, education, hemoglobin A1c level, serum homocysteine level, and total CSVD burden score. A nomogram with these variables showed good discriminative ability (area under the receiver operating characteristic curve was 0.801 in internal verification). In addition, the Hosmer-Lemeshow test (χ2 =9.226, P=0.417) and bootstrap-corrected calibration plot indicated that the nomogram had good calibration. The Brier score of the predictive model was 0.178. Decision curve analysis demonstrated that when the threshold probability ranged between 16% and 98%, the use of the nomogram to predict mild VCI in patients with T2DM provide a greater net benefit. The nomogram, composed of age, education, stroke, HbA1c level, Hcy level, and total CSVD burden score, had good predictive accuracy and may provide clinicians with a practical tool for predicting the risk of mild VCI in T2DM patients.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease.

This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD). Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies. A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926. The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

Difference of Cerebrospinal Fluid Biomarkers and Neuropsychiatric Symptoms Profiles among Normal Cognition, Mild Cognitive Impairment, and Dementia Patient.

The delineation of biomarkers and neuropsychiatric symptoms across normal cognition, mild cognitive impairment (MCI), and dementia stages holds significant promise for early diagnosis and intervention strategies. This research investigates the association of neuropsychiatric symptoms, evaluated via the Neuropsychiatric Inventory (NPI), with cerebrospinal fluid (CSF) biomarkers (Amyloid-β42, P-tau, T-tau) across a spectrum of cognitive states to enhance diagnostic accuracy and treatment approaches. Drawing from the National Alzheimer's Coordinating Center's Uniform Data Set Version 3, comprising 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. To assess neuropsychiatric symptoms, we employed the NPI to understand the behavioral and psychological symptoms associated with each cognitive category. For the analysis of CSF biomarkers, we measured levels of Amyloid-β42, P-tau, and T-tau using the enzyme-linked immunosorbent assay (ELISA) and Luminex multiplex xMAP assay protocols. These biomarkers are critical in understanding the pathophysiological underpinnings of Alzheimer's disease and its progression, with specific patterns indicative of disease stage and severity. This study cohort consists of 1896 participants, which is composed of 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. Dementia is characterized by significantly higher NPI scores, which are largely reflective of mood-related symptoms (p < 0.001). In terms of biomarkers, normal cognition shows median Amyloid-β at 656.0 pg/mL, MCI at 300.6 pg/mL, and dementia at 298.8 pg/mL (p < 0.001). Median P-tau levels are 36.00 pg/mL in normal cognition, 49.12 pg/mL in MCI, and 58.29 pg/mL in dementia (p < 0.001). Median T-tau levels are 241.0 pg/mL in normal cognition, 140.6 pg/mL in MCI, and 298.3 pg/mL in dementia (p < 0.001). Furthermore, the T-tau/Aβ-42 ratio increases progressively from 0.058 in the normal cognition group to 0.144 in the MCI group, and to 0.209 in the dementia group (p < 0.001). Similarly, the P-tau/Aβ-42 ratio also escalates from 0.305 in individuals with normal cognition to 0.560 in MCI, and to 0.941 in dementia (p < 0.001). The notable disparities in NPI and CSF biomarkers among normal, MCI and Alzheimer's patients underscore their diagnostic potential. Their combined assessment could greatly improve early detection and precise diagnosis of MCI and dementia, facilitating more effective and timely treatment strategies.

Risk factors and characteristics analysis of cognitive impairment in patients with cerebral infarction during recovery period

Objective To analyze the risk factors and characteristics of cognitive impairment in patients with cerebral infarction during the recovery period. Methods This retrospective case-control study included 183 patients with cerebral infarction in the recovery period. According to the MMSE score, they were divided into a cognitive impairment group of 79 cases and a cognitive normal group of 104 cases. Collect clinical data from all patients, including age, gender, body mass index, laboratory test results, past medical history, National Institute of Health Stroke Scale (NIHSS) score, modified Barthel index, Oxfordshire Community Stroke Project (OCSP) classification, and number of infarcted lesions. Multiple logistic regression analysis was used to identify risk factors related to cognitive impairment in patients with cerebral infarction. Result There were significant differences (p < 0.05) between the cognitive impairment group and the cognitive normal group in terms of age, body mass index, low-density lipoprotein level, NIHSS score, modified Barthel index, and number of infarcted lesions. Multivariate logistic regression analysis showed that age ≥ 65 years, stroke, carotid artery plaques, NIHSS score ≥ 5, anterior circulation infarction type, and multiple infarcted lesions were important risk factors for cognitive impairment. Conclusion Elderly age, presence of carotid artery plaques, high NIHSS score, multiple infarct lesions, and specific infarct types are important risk factors for cognitive dysfunction in patients during the recovery period of cerebral infarction.

Oral Microbiota and Porphyromonas gingivalis Kgp Genotypes Altered in Parkinson's Disease with Mild Cognitive Impairment.

Cognitive impairment (CI) is a common complication of the non-motor symptoms in Parkinson's disease (PD), including PD with mild cognitive impairment (PD-MCI) and PD dementia. Recent studies reported the oral dysbiosis in PD and CI, respectively. Porphyromonas gingivalis (P. gingivalis), a pathogen of oral dysbiosis, plays an important role in PD, whose lysine-gingipain (Kgp) could lead to AD-type pathologies. No previous study investigated the composition of oral microbiota and role of P. gingivalis in PD-MCI. This study aimed to investigate the differences of oral microbiota composition, P. gingivalis copy number, and Kgp genotypes among PD-MCI, PD with normal cognition (PD-NC) and periodontal status-matched control (PC) groups. The oral bacteria composition, the copy number of P. gingivalis, and the Kgp genotypes in gingival crevicular fluid from PD-MCI, PD-NC, and PC were analyzed using 16S ribosomal RNA sequencing, quantitative real-time PCR, and MseI restriction. We found that the structures of oral microbiota in PD-MCI group were significantly different compared to that in PD-NC and PC group. The relative abundances of Prevotella, Lactobacillus, Megasphaera, Atopobium, and Howardella were negatively correlated with cognitive score. Moreover, there was a significant difference of Kgp genotypes among the three groups. The predominant Kgp genotypes of P. gingivalis in the PD-MCI group were primarily Kgp II, whereas in the PD-NC group, it was mainly Kgp I. The Kgp II correlated with lower MMSE and MoCA scores, which suggested that Kgp genotypes II is related to cognitive impairment in PD.

The associations between peripheral inflammatory and lipid parameters, white matter hyperintensity, and cognitive function in patients with non-disabling ischemic cerebrovascular events

BackgroundThe global prevalence of VCI has increased steadily in recent years, but diagnostic biomarkers for VCI in patients with non-disabling ischemic cerebrovascular incidents (NICE) remain indefinite. The primary objective of this research was to investigate the relationship between peripheral serological markers, white matter damage, and cognitive function in individuals with NICE.MethodsWe collected clinical data, demographic information, and medical history from 257 patients with NICE. Using the MoCA upon admission, patients were categorized into either normal cognitive function (NCF) or VCI groups. Furthermore, they were classified as having mild white matter hyperintensity (mWMH) or severe WMH based on Fazekas scores. We then compared the levels of serological markers between the cognitive function groups and the WMH groups.ResultsAmong 257 patients with NICE, 165 were male and 92 were female. Lymphocyte count (OR = 0.448, P < 0.001) and LDL-C/HDL-C (OR = 0.725, P = 0.028) were protective factors for cognitive function in patients with NICE. The sWMH group had a higher age and inflammation markers but a lower MoCA score, and lymphocyte count than the mWMH group. In the mWMH group, lymphocyte count (AUC = 0.765, P < 0.001) and LDL-C/HDL-C (AUC = 0.740, P < 0.001) had an acceptable diagnostic value for the diagnosis of VCI. In the sWMH group, no significant differences were found in serological markers between the NCF and VCI groups.ConclusionLymphocyte count, LDL-C/HDL-C were independent protective factors for cognitive function in patients with NICE; they can be used as potential biological markers to distinguish VCI in patients with NICE and are applicable to subgroups of patients with mWMH.

Evaluation of cognitive functions and dementia two years after COVID-19 infection

Background: The Coronavirus disease 2019 (COVID-19) causes high morbidity and mortality in the acute period. Some patients with COVID-19 continue to have symptoms for a long time. However, data on the long-term effects of COVID-19, particularly on cognitive disorders is scarce. We aimed to evaluate cognitive functions and dementia in patients who survived two years after discharge from hospital due to acute covid-19 infection. Methods: Two hundred and five patients who had neurological symptoms during index hospitalization for COVID-19 infection were evaluated two years after discharge, and 64 patients were included in the study. According to cognitive assessments, patients were grouped as having normal cognitive levels (48 patients) or impaired cognitive levels (16 patients). Results: The impaired cognitive level was found in 16 (25.0%) of patients who underwent cognitive tests. Age, the pre-existence of neurological comorbidity, mean intensive care unit day, and Beck’s Anxiety Inventory and Beck’s Depression Inventory scores in the impaired cognitive level group were significantly higher than the normal cognitive level group (p:0.001, p:0.013, p:0.015, p:0.004 and p:0.008). The frequency of cognitive impairment in patients who developed altered mental state during hospitalization was 36.0%, while it was 17.9% in patients with normal mental state. Age, the pre-existence of neurological comorbidity, and anxiety were determined as independent risk factors for impaired cognitive level. In addition, we detected new-onset dementia in 8 patients (12.5%). Conclusion: We found a high frequency of cognitive impairment and new-onset dementia among COVID-19 survivors who developed neurological manifestations during the acute infection phase.

A network approach to subjective cognitive decline: Exploring multivariate relationships in neuropsychological test performance across Alzheimer's disease risk states

Subjective cognitive decline (SCD) is characterized by subjective concerns of cognitive change despite test performance within normal range. Although those with SCD are at higher risk for developing further cognitive decline, we still lack methods using objective cognitive measures that reliably distinguish SCD from cognitively normal aging at the group level. Network analysis may help to address this by modeling cognitive performance as a web of intertwined cognitive abilities, providing insight into the multivariate associations determining cognitive status. Following previous network studies of mild cognitive impairment (MCI) and Alzheimer's dementia (AD), the current study centered upon the novel visualization and analysis of the SCD cognitive network compared to cognitively normal (CN) older adult, MCI, and AD group networks. Cross-sectional neuropsychological data from CIMA-Q and COMPASS-ND cohorts were used to construct Gaussian graphical models for CN (n = 122), SCD (n = 207), MCI (n = 210), and AD (n = 79) groups. Group networks were explored in terms of global network structure, prominent edge weights, and strength centrality indices. CN and SCD group networks were contrasted using the Network Comparison Test. Results indicate that CN and SCD groups did not differ in univariate cognitive performance or global network structure. However, measures of strength centrality, principally in executive functioning and processing speed, showed a CN-SCD-MCI gradient where subtle differences within the SCD network suggest that SCD is an intermediary between CN and MCI stages. Additional results may indicate a distinctiveness of network structure in AD, a reversal in network influence between age and general cognitive status as clinical impairment increases, and potential evidence for cognitive reserve. Together, these results provide evidence that network-specific metrics are sensitive to cognitive performance changes across the dementia risk spectrum and can help to objectively distinguish SCD group cognitive performance from that of the CN group.

Higher remnant cholesterol is associated with an increased risk of amnestic mild cognitive impairment: a community-based cross-sectional study.

Amnestic mild cognitive impairment (aMCI) is the most common subtype of MCI, which carries a significantly high risk of transitioning to Alzheimer's disease. Recently, increasing attention has been given to remnant cholesterol (RC), a non-traditional and previously overlooked risk factor. The aim of this study was to explore the association between plasma RC levels and aMCI. Data were obtained from Brain Health Cognitive Management Team in Wuhan (https://hbtcm.66nao.com/admin/). A total of 1,007 community-dwelling elders were recruited for this project. Based on ten tools including general demographic data, cognitive screening and some exclusion scales, these participants were divided into the aMCI (n = 401) and normal cognitive groups (n = 606). Physical examinations were conducted on all participants, with clinical indicators such as blood pressure, blood sugar, and blood lipids collected. The aMCI group had significantly higher RC levels compared to the normal cognitive group (0.64 ± 0.431 vs. 0.52 ± 0.447 mmol/L, p < 0.05). Binary logistics regression revealed that occupation (P<0.001, OR = 0.533, 95%CI: 0.423-0.673) and RC (p = 0.014, OR = 1.477, 95% CI:1.081-2.018) were associated factors for aMCI. Partial correlation analysis, after controlling for occupation, showed a significant negative correlation between RC levels and MoCA scores (r = 0.059, p = 0.046), as well as Naming scores (r = 0.070, p = 0.026). ROC curve analysis demonstrated that RC levels had an independent predictive efficacy in predicting aMCI (AUC = 0.580, 95%CI: 0.544 ~ 0.615, P < 0.001). Higher RC levels were identified as an independent indicator for aMCI, particularly in the naming cognitive domain among older individuals. Further longitudinal studies are necessary to validate the predictive efficacy of RC.

Correlation between serum ANGPTL4 levels and white matter hyperintensity and cognitive impairment in patients with cerebral small vessel disease.

To investigate the correlation between serum angiopoietin-like protein 4 (ANGPTL4) levels, white matter hyperintensity (WMH), and cognitive impairment (CI) in patients with cerebral small vessel disease (CSVD). This cross-sectional study enrolled 171 patients with CSVD who attended the First Affiliated Hospital of Xinxiang Medical University from December 2021 to July 2022. All subjects underwent a 3.0T head magnetic resonance imaging, neuropsychology assessment, and blood sampling. Serum ANGPTL4 levels were detected by enzyme-linked immunosorbent assay and the severity of WMH was assessed by the Fazekas scale. According to the Montreal Cognitive Assessment (MoCA) scale, subjects were divided into normal cognition group (NC, n=80) and CI group (n=91). According to the total Fazekas scores, subjects were divided into a mild WMH group (n=84), a moderate WMH group (n=70), and a severe WMH group (n=17). Serum ANGPTL4 levels were significantly higher in the CI group than in the NC group (p<.05) and were negatively correlated with mini-mental state examination scores and MoCA scores (r=-0.26, -0.341, p<.05). Serum ANGPTL4 levels increased significantly in the mild to moderate WMH group but tended to decrease in the severe WMH group. Binary logistic regression analysis showed that ANGPTL4 was an independent influencing factor for CSVD-CI (OR=2.062, 95% CI (1.591-2.674), p<.001). The area under curve of ANGPTL4 for CSVD-CI was 0.847 (0.791-0.903). ANGPTL4 may be involved in the process of white matter damage and CI in CSVD patients and shows a diagnostic value for CSVD-CI.