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Introduction: Previous validation studies demonstrated that BrainCheck Assess (BC-Assess), a computerized cognitive test battery, can reliably and sensitively distinguish individuals with different levels of cognitive impairment (i.e., normal cognition (NC), mild cognitive impairment (MCI), and dementia). Compared with other traditional paper-based cognitive screening instruments commonly used in clinical practice, the Montreal Cognitive Assessment (MoCA) is generally accepted to be among the most comprehensive and robust screening tools, with high sensitivity/specificity in distinguishing MCI from NC and dementia. In this study, we examined: (1) the linear relationship between BC-Assess and MoCA and their equivalent cut-off scores, and (2) the extent to which they agree on their impressions of an individual's cognitive status. Methods: A subset of participants (N = 55; age range 54-94, mean/SD = 80/9.5) from two previous studies who took both the MoCA and BC-Assess were included in this analysis. Linear regression was used to calculate equivalent cut-off scores for BC-Assess based on those originally recommended for the MoCA to differentiate MCI from NC (cut-off = 26), and dementia from MCI (cutoff = 19). Impression agreement between the two instruments were measured through overall agreement (OA), positive percent agreement (PPA), and negative percent agreement (NPA). Results: A high Pearson correlation coefficient of 0.77 (CI = 0.63-0.86) was observed between the two scores. According to this relationship, MoCA cutoffs of 26 and 19 correspond to BC-Assess scores of 89.6 and 68.5, respectively. These scores are highly consistent with the currently recommended BCAssess cutoffs (i.e., 85 and 70). The two instruments also show a high degree of agreement in their impressions based on their recommended cut-offs: (i) OA = 70.9%, PPA = 70.4%, NPA = 71.4% for differentiating dementia from MCI/NC; (ii) OA = 83.6%, PPA = 84.1%, NPA = 81.8% for differentiating dementia/MCI from NC. Discussion: This study provides further validation of BC-Assess in a sample of older adults by showing its high correlation and agreement in impression with the widely used MoCA. [ABSTRACT FROM AUTHOR]

BackgroundThis study aims to examine the association between gut microbe-dependent trimethylamine N-oxide (TMAO) and its precursors (choline, betaine, and carnitine) levels and mild cognition impairment (MCI), alongside changes in the Chinese version of the Montreal Cognitive Assessment-Basic (ΔMoCA-BC) score in rural adults.MethodsDrawing data from a large-scale epidemiological study conducted in rural areas of Fuxin County, Liaoning Province, China. 1,535 participants free from brain-related ailments were initially surveyed. MCI was assessed through the MoCA-BC score. Logistic regression models and restricted cubic spline were used to investigate the association between TMAO and its precursors levels and MCI. Additionally, the association between TMAO and its precursors levels and ΔMoCA-BC was analyzed using a generalized linear model in the longitudinal study.ResultsThe average age of the study participants was 58.6 ± 9.4 years and the prevalence rate of MCI was 34.5%. With the second quartile as the reference in the logistic regression model, the OR for risk of MCI in the highest quartile for TMAO, betaine, and carnitine was 1.685 (95% CI: 1.232–2.303, p = 0.001), 2.367 (95% CI: 1.722–3.255, p

Abstract Background Mild cognitive impairment (MCI) is a common condition in the elderly population. It is characterized by confusion, disorientation, memory complaints, as well as restricted attention, learning, and language abilities. Objectives The objective of this study was to compare the effect of internal and external cognitive training in patients with mild cognitive impairment. Methods Twenty-six patients with mild cognitive impairment participated in this study. An equal number of participants (n=13) were allocated into two groups, i.e., the internal cognitive training group (group A) and external cognitive training (group B). Cognitive training session was administered 40 min per day, at a frequency of 2 sessions per week, for a period of 4 weeks for both groups, and aerobic exercise was also performed for 15 min per day, for a period of 4 weeks. Outcome measures were undertaken at baseline and at the end of the 4th week. Results The result shows a significant improvement on MoCA components in the internal cognitive training group than the external cognitive training group (P

Background: Polyphenols are naturally occurring organic compounds found in plants. Research suggests that their intake reduces the risk of cognitive decline and related dementias. Grapes and blueberries are polyphenol-rich foods that have attracted attention for their potential cognitive-enhancing effects. Purpose: Examine the effects of supplementation with a standardized and patented polyphenol-rich grape and blueberry extract (Memophenol™) on cognitive function in older adults with mild cognitive impairment. Study design: Two-arm, 6 month, parallel-group, randomized, double-blind, placebo-controlled trial. Methods: One hundred and forty-three volunteers aged 60 to 80 years with mild cognitive impairment were supplemented with either 150 mg of Memophenol™, twice daily or a placebo. Outcome measures included computer-based cognitive tasks, the Behavior Rating Inventory of Executive Function (BRIEF-A), the Cognitive Failures Questionnaire, and the CASP-19. Results: Compared to the placebo, Memophenol™ supplementation was associated with greater improvements in the speed of information processing (p = 0.020), visuospatial learning (p = 0.012), and the BRIEF-A global score (p = 0.046). However, there were no other statistically significant between-group differences in the performance of other assessed cognitive tests or self-report questionnaires. Memophenol™ supplementation was well-tolerated with no reports of significant adverse reactions. Conclusion: The promising results from this trial suggest that 6-months of supplementation with Memophenol™ may improve aspects of cognitive function in adults with mild cognitive impairment. Further research will be important to expand on the current findings and identify the potential mechanisms of action associated with the intake of this polyphenol-rich extract. [ABSTRACT FROM AUTHOR]

BackgroundPolyphenols are naturally occurring organic compounds found in plants. Research suggests that their intake reduces the risk of cognitive decline and related dementias. Grapes and blueberries are polyphenol-rich foods that have attracted attention for their potential cognitive-enhancing effects.PurposeExamine the effects of supplementation with a standardized and patented polyphenol-rich grape and blueberry extract (Memophenol™) on cognitive function in older adults with mild cognitive impairment.Study designTwo-arm, 6 month, parallel-group, randomized, double-blind, placebo-controlled trial.MethodsOne hundred and forty-three volunteers aged 60 to 80 years with mild cognitive impairment were supplemented with either 150 mg of Memophenol™, twice daily or a placebo. Outcome measures included computer-based cognitive tasks, the Behavior Rating Inventory of Executive Function (BRIEF-A), the Cognitive Failures Questionnaire, and the CASP-19.ResultsCompared to the placebo, Memophenol™ supplementation was associated with greater improvements in the speed of information processing (p = 0.020), visuospatial learning (p = 0.012), and the BRIEF-A global score (p = 0.046). However, there were no other statistically significant between-group differences in the performance of other assessed cognitive tests or self-report questionnaires. Memophenol™ supplementation was well-tolerated with no reports of significant adverse reactions.ConclusionThe promising results from this trial suggest that 6-months of supplementation with Memophenol™ may improve aspects of cognitive function in adults with mild cognitive impairment. Further research will be important to expand on the current findings and identify the potential mechanisms of action associated with the intake of this polyphenol-rich extract.

Background: This study aims to examine the association between gut microbe-dependent trimethylamine N-oxide (TMAO) and its precursors (choline, betaine, and carnitine) levels and mild cognition impairment (MCI), alongside changes in the Chinese version of the Montreal Cognitive Assessment-Basic (ΔMoCA-BC) score in rural adults., Methods: Drawing data from a large-scale epidemiological study conducted in rural areas of Fuxin County, Liaoning Province, China. 1,535 participants free from brain-related ailments were initially surveyed. MCI was assessed through the MoCA-BC score. Logistic regression models and restricted cubic spline were used to investigate the association between TMAO and its precursors levels and MCI. Additionally, the association between TMAO and its precursors levels and ΔMoCA-BC was analyzed using a generalized linear model in the longitudinal study., Results: The average age of the study participants was 58.6 ± 9.4 years and the prevalence rate of MCI was 34.5%. With the second quartile as the reference in the logistic regression model, the OR for risk of MCI in the highest quartile for TMAO, betaine, and carnitine was 1.685 (95% CI: 1.232-2.303, p  = 0.001), 2.367 (95% CI: 1.722-3.255, p  < 0.001), and 2.239 (95% CI: 1.742-3.295, p  < 0.001), respectively. The OR of choline for the highest versus lowest quartile was 2.711 (95% CI: 2.012-3.817, p  < 0.001) for the risk of MCI. We find a J-shaped association between betaine ( P non-linear  = 0.001) and carnitine ( P non-linear  = 0.003) levels and MCI. Furthermore, TMAO and its precursors levels were associated with ΔMoCA-BC in the third and fourth quartiles group (All p  < 0.05)., Conclusion: The findings suggest the existence of an optimal concentration range for serum levels of TMAO, betaine, and carnitine that mitigates MCI risk, paving the way for enhanced dietary interventions aimed at preventing and treating MCI., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Bai, Zhang, Tian, Wu, Peng, Liang, Ruan, Cai, Lu, Ma and Zheng.)

Background and Objective: Identifying biomarkers for predicting progression to dementia in patients with mild cognitive impairment (MCI) is crucial. To this end, the comprehensive visual rating scale (CVRS), which is based onmagnetic resonance imaging (MRI), was developed for the assessment of structural changes in the brains of patients with MCI. This study aimed to investigate the use of the CVRS score for predicting dementia in patients with MCI over a 2-year follow-up period using various machine learning (ML) algorithms. Methods: We included 197 patients with MCI who were followed up more than once. The data used for this study were obtained from the Japanese-Alzheimer's Disease Neuroimaging Initiative study. We assessed all the patients using their CVRS scores, cortical thickness data, and clinical data to determine their progression to dementia during a follow-up period of over 2 years. ML algorithms, such as logistic regression, random forest (RF), XGBoost, and LightGBM, were applied to the combination of the dataset. Further, feature importance that contributed to the progression from MCI to dementia was analyzed to confirm the risk predictors among the various variables evaluated. Results: Of the 197 patients, 108 (54.8%) showed progression from MCI to dementia. Tree-based classifiers, such as XGBoost, LightGBM, and RF, achieved relatively high performance. In addition, the prediction models showed better performance when clinical data and CVRS score (accuracy 0.701-0.711) were used than when clinical data and cortical thickness (accuracy 0.650-0.685) were used. The features related to CVRS helped predict progression to dementia using the tree-based models compared to logistic regression. Conclusions: Tree-based ML algorithms can predict progression from MCI to dementia using baseline CVRS scores combined with clinical data. [ABSTRACT FROM AUTHOR]

Introduction: Integrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a "metabolic map" of the brain in prodromal AD. Methods: In 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort. Results: The multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05). Conclusion: By integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches. [ABSTRACT FROM AUTHOR]

Background: With the progressive course of diabetes and the decline in islet function, the cognitive dysfunction of patients aggravated. Objective: We aimed to investigate the roles of brain-derived neurotrophic factor (BDNF) and the Val66Met polymorphism in mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 169 Chinese patients with T2DM were involved and divided into long-term (diabetes duration >10 years) and short-term (diabetes duration ≤10 years) diabetes, and in each group, the patients were separated as MCI and the control. Demographic characteristics, clinical variables, and cognitive performances were assessed. The plasma BDNF level was measured via enzyme-linked immunosorbent assay. The Val66Met polymorphisms were analyzed. Results: Long-term T2DM have lower 2 h postprandial C-peptide (p < 0.05). The BDNF level was slightly higher in patients with MCI than in the controls in each duration group without statistical significance. The relationship of BDNF to Montreal Cognitive Assessment was not proven either. However, in the long-term diabetes group, BDNF concentration remained as an independent factor of logical memory test (β = −0.27; p < 0.05), and they were negatively correlated (r = −0.267; p = 0.022); BDNF was also negatively correlated with fasting C-peptide (r = −0.260; p = 0.022), 2 h postprandial C-peptide (r = −0.251; p = 0.028), and homeostasis model assessment of insulin resistance (r = −0.312; p = 0.006). In genotypic groups, BDNF Val/Val performed better in logical memory test than Met/Met and Val/Met. Conclusion: Elevated peripheral BDNF level associated with declined islet function, when combined with its Val66Met polymorphism, may forecast memory dysfunction in patients with long-term T2DM. [ABSTRACT FROM AUTHOR]

BackgroundWith the progressive course of diabetes and the decline in islet function, the cognitive dysfunction of patients aggravated.ObjectiveWe aimed to investigate the roles of brain-derived neurotrophic factor (BDNF) and the Val66Met polymorphism in mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM).MethodsA total of 169 Chinese patients with T2DM were involved and divided into long-term (diabetes duration >10 years) and short-term (diabetes duration ≤10 years) diabetes, and in each group, the patients were separated as MCI and the control. Demographic characteristics, clinical variables, and cognitive performances were assessed. The plasma BDNF level was measured via enzyme-linked immunosorbent assay. The Val66Met polymorphisms were analyzed.ResultsLong-term T2DM have lower 2 h postprandial C-peptide (p < 0.05). The BDNF level was slightly higher in patients with MCI than in the controls in each duration group without statistical significance. The relationship of BDNF to Montreal Cognitive Assessment was not proven either. However, in the long-term diabetes group, BDNF concentration remained as an independent factor of logical memory test (β = −0.27; p < 0.05), and they were negatively correlated (r = −0.267; p = 0.022); BDNF was also negatively correlated with fasting C-peptide (r = −0.260; p = 0.022), 2 h postprandial C-peptide (r = −0.251; p = 0.028), and homeostasis model assessment of insulin resistance (r = −0.312; p = 0.006). In genotypic groups, BDNF Val/Val performed better in logical memory test than Met/Met and Val/Met.ConclusionElevated peripheral BDNF level associated with declined islet function, when combined with its Val66Met polymorphism, may forecast memory dysfunction in patients with long-term T2DM.

IntroductionIntegrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a “metabolic map” of the brain in prodromal AD.MethodsIn 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort.ResultsThe multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05).ConclusionBy integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches.

Introduction: Previous validation studies demonstrated that BrainCheck Assess (BC-Assess), a computerized cognitive test battery, can reliably and sensitively distinguish individuals with different levels of cognitive impairment (i.e., normal cognition (NC), mild cognitive impairment (MCI), and dementia). Compared with other traditional paper-based cognitive screening instruments commonly used in clinical practice, the Montreal Cognitive Assessment (MoCA) is generally accepted to be among the most comprehensive and robust screening tools, with high sensitivity/specificity in distinguishing MCI from NC and dementia. In this study, we examined: (1) the linear relationship between BC-Assess and MoCA and their equivalent cut-off scores, and (2) the extent to which they agree on their impressions of an individual's cognitive status., Methods: A subset of participants ( N = 55; age range 54-94, mean/SD = 80/9.5) from two previous studies who took both the MoCA and BC-Assess were included in this analysis. Linear regression was used to calculate equivalent cut-off scores for BC-Assess based on those originally recommended for the MoCA to differentiate MCI from NC (cut-off = 26), and dementia from MCI (cut-off = 19). Impression agreement between the two instruments were measured through overall agreement (OA), positive percent agreement (PPA), and negative percent agreement (NPA)., Results: A high Pearson correlation coefficient of 0.77 (CI = 0.63-0.86) was observed between the two scores. According to this relationship, MoCA cutoffs of 26 and 19 correspond to BC-Assess scores of 89.6 and 68.5, respectively. These scores are highly consistent with the currently recommended BC-Assess cutoffs (i.e., 85 and 70). The two instruments also show a high degree of agreement in their impressions based on their recommended cut-offs: (i) OA = 70.9%, PPA = 70.4%, NPA = 71.4% for differentiating dementia from MCI/NC; (ii) OA = 83.6%, PPA = 84.1%, NPA = 81.8% for differentiating dementia/MCI from NC., Discussion: This study provides further validation of BC-Assess in a sample of older adults by showing its high correlation and agreement in impression with the widely used MoCA., Competing Interests: DH, KS, RG and BH were employed by BrainCheck Inc., Austin. RG was also employed by Frontier Psychiatry, PLLC, Billings. All authors receive salaries and stock options from BrainCheck., (Copyright © 2024 Huynh, Sun, Ghomi and Huang.)

BackgroundCognitive frailty describes cognitive impairment associated with physical decline. Few studies have explored whether short cognitive screens identify frailty. We examined the diagnostic accuracy of the Chinese versions of the Quick Mild Cognitive Impairment (Qmci-CN) screen and Montreal Cognitive Assessment (MoCA-CN) in identifying cognitive frailty.MethodsNinety-five participants with cognitive symptoms [47 with mild cognitive impairment (MCI), 34 with subjective cognitive disorder, and 14 with dementia] were included from two outpatient rehabilitation clinics. Energy (work intensity) and physical activity levels were recorded. Cognitive frailty was diagnosed by an interdisciplinary team using the IANA/IAGG consensus criteria, stratified on the Clinical Frailty Scale (CFS). Instruments were administered sequentially and randomly by trained assessors, blind to the diagnosis.ResultsThe mean age of the sample was 62.6 ± 10.2 years; median CFS score was 4 ± 1 and 36 (38%) were cognitively frail. The Qmci-CN had similar accuracy in differentiating the non-frail from cognitively frail compared to the MoCA-CN, AUC 0.82 versus 0.74, respectively (p = 0.19). At its optimal cut-off (≤55/100), the Qmci-CN provided a sensitivity of 83% and specificity of 67% versus 91% and 51%, respectively, for the MoCA-CN (≤23/30). Neither was accurate in separating MCI from cognitive frailty but both accurately separated cognitive frailty from dementia.ConclusionEstablished short cognitive screens may be useful in identifying cognitive frailty in Chinese adults with cognitive complaints but not in separating MCI from cognitive frailty. The Qmci-CN had similar accuracy to the MoCA-CN and a shorter administration time in this small and under-powered study, necessitating the need for adequately powered studies in different healthcare settings.

Background: Cognitive frailty describes cognitive impairment associated with physical decline. Few studies have explored whether short cognitive screens identify frailty. We examined the diagnostic accuracy of the Chinese versions of the Quick Mild Cognitive Impairment (Q mci -CN) screen and Montreal Cognitive Assessment (MoCA-CN) in identifying cognitive frailty. Methods: Ninety-five participants with cognitive symptoms [47 with mild cognitive impairment (MCI), 34 with subjective cognitive disorder, and 14 with dementia] were included from two outpatient rehabilitation clinics. Energy (work intensity) and physical activity levels were recorded. Cognitive frailty was diagnosed by an interdisciplinary team using the IANA/IAGG consensus criteria, stratified on the Clinical Frailty Scale (CFS). Instruments were administered sequentially and randomly by trained assessors, blind to the diagnosis. Results: The mean age of the sample was 62.6 ± 10.2 years; median CFS score was 4 ± 1 and 36 (38%) were cognitively frail. The Q mci -CN had similar accuracy in differentiating the non-frail from cognitively frail compared to the MoCA-CN, AUC 0.82 versus 0.74, respectively (p = 0.19). At its optimal cut-off (≤55/100), the Q mci -CN provided a sensitivity of 83% and specificity of 67% versus 91% and 51%, respectively, for the MoCA-CN (≤23/30). Neither was accurate in separating MCI from cognitive frailty but both accurately separated cognitive frailty from dementia. Conclusion: Established short cognitive screens may be useful in identifying cognitive frailty in Chinese adults with cognitive complaints but not in separating MCI from cognitive frailty. The Q mci- CN had similar accuracy to the MoCA-CN and a shorter administration time in this small and under-powered study, necessitating the need for adequately powered studies in different healthcare settings. [ABSTRACT FROM AUTHOR]

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification.

Background: In addition to glucose metabolism, adipocytokine Nicotinamide phosphoribosyltransferase (Nampt) has been proposed as a multifunctional protein involved in insulin resistance. Insulin resistance always occurs before the onset of type 2 diabetes mellitus (T2DM) and damages the cognition of T2DM patients very early.Objective: We aimed to investigate the role and potential clinical value of Nampt in early cognitive decline of T2DM.Methods: A total of 195 Chinese T2DM patients were enrolled and divided into a mild cognition impairment (MCI) group and a healthy cognition group according to Montreal Cognitive Assessment (MoCA) score. Their cognitive function was extensively assessed. The plasma level of Nampt was measured via enzyme-linked immunosorbent assay.Results: In the MCI group (n = 78, MoCA < 26), the plasma level of Nampt was significantly higher than the controls (p < 0.01). After adjusting for age, sex, and level of education, Nampt levels were negatively associated with most of the cognitive domains forecasting hypomnesia (all p < 0.007). Nevertheless, hierarchical regression analysis further revealed that Nampt was an independent risk factor of MCI in Chinese T2DM patients (all p < 0.05), including Logic Memory Test (β= -0.31, p < 0.01), Auditory Verbal Learning Test delayed recall (β= -0.26, p < 0.01), and so on, which represent memory function. Correlation analysis showed that Nampt related to insulin resistance (HOMA-IR), glycosylated hemoglobin (HbA1c), and lipid levels (all p < 0.05).Conclusions: We found that higher plasma level of Nampt presages memory dysfunction in MCI in Chinese T2DM patients. Further studies are necessary to confirm its scanning and prognosis prediction value of the disease clinically. [ABSTRACT FROM AUTHOR]

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake. Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed. Results: 18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions. Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification. [ABSTRACT FROM AUTHOR]

Background and Objective: Identifying biomarkers for predicting progression to dementia in patients with mild cognitive impairment (MCI) is crucial. To this end, the comprehensive visual rating scale (CVRS), which is based on magnetic resonance imaging (MRI), was developed for the assessment of structural changes in the brains of patients with MCI. This study aimed to investigate the use of the CVRS score for predicting dementia in patients with MCI over a 2-year follow-up period using various machine learning (ML) algorithms., Methods: We included 197 patients with MCI who were followed up more than once. The data used for this study were obtained from the Japanese-Alzheimer's Disease Neuroimaging Initiative study. We assessed all the patients using their CVRS scores, cortical thickness data, and clinical data to determine their progression to dementia during a follow-up period of over 2 years. ML algorithms, such as logistic regression, random forest (RF), XGBoost, and LightGBM, were applied to the combination of the dataset. Further, feature importance that contributed to the progression from MCI to dementia was analyzed to confirm the risk predictors among the various variables evaluated., Results: Of the 197 patients, 108 (54.8%) showed progression from MCI to dementia. Tree-based classifiers, such as XGBoost, LightGBM, and RF, achieved relatively high performance. In addition, the prediction models showed better performance when clinical data and CVRS score (accuracy 0.701-0.711) were used than when clinical data and cortical thickness (accuracy 0.650-0.685) were used. The features related to CVRS helped predict progression to dementia using the tree-based models compared to logistic regression., Conclusions: Tree-based ML algorithms can predict progression from MCI to dementia using baseline CVRS scores combined with clinical data., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Park, Jang, Joo, Kim, Kim, Byeon, Park, Kasani, Yum, Pyun, Park, Lim, Youn, Choi, Park, Im and Kim.)

Objectives: There is an increasing call for a stronger consideration of impairment in instrumental activities of daily living (IADL) in the diagnostic criteria of Mild Cognitive Impairment (MCI) to improve the prediction of dementia. Thus, the aim of the study was to determine the predictive capability of MCI and IADL impairment for incident dementia. Design: Longitudinal cohort study with four assessments at 1.5-year intervals over a period of 4.5 years. Setting: Primary care medical record registry sample. Participants: As part of the German Study on Ageing, Cognition, and Dementia in Primary Care Patients, a sample of 3,327 patients from general practitioners, aged 75 years and omen, was assessed. Measurements: The predictive capability of MCI and IADL impairment for incident dementia was analysed using receiver operating characteristics, Kaplan-Meier survival analyses, and Cox proportional hazards models. Results: MCI and IADL impairment were found to be significantly associated with higher conversion to, shorter time to, and better predictive power for future dementia. Regarding IADL, a significant impact was particularly found for impairment in responsibility for one's own medication, shopping, and housekeeping, and in the ability to use public transport. Conclusions: Combining MCI with IADL impairment significantly improves the prediction of future dementia. Even though information on a set of risk factors is required to achieve a predictive accuracy for dementia in subjects with MCI being clinically useful, IADL impairment should be a very important element of such a risk factor set. [ABSTRACT FROM AUTHOR]

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18 F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18 F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18 F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18 F-AV1451 brain uptake. Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18 F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18 F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18 F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed. Results: 18 F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18 F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups ( p < 0.01). Although there was an increasing tendency of 18 F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18 F-AV1451 deposition was found between CN and MCI brains with or without PVC ( p > 0.05). Declined MMSE score was observed with increasing 18 F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18 F-AV1451 deposition. PVC improved the results of 18 F-AV-1451 tau deposition and correlation studies in small brain regions. Conclusion: The typical deposition of 18 F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18 F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18 F-AV1451 tau PET quantification.