Association Between Body Mass Index and Cognitive Function in Mild Cognitive Impairment Regardless of APOE ε4 Status

Mun, Ye Sol; Park, Hee Kyung; Kim, Jihee; Yeom, Jiyoung; Kim, Geon Ha; Chun, Mun-Suk; Lee, Hye Ah; Yoon, Soo Jin; Park, Kyung Won; Kim, Eun-Joo; Yoon, Bora; Jang, Jae-Won; Hong, Jin Yong; Choi, Seong Hye; Jeong, Jee Hyang

doi:10.12779/dnd.2022.21.1.30

Cited by 9 publications

(6 citation statements)

References 53 publications

(56 reference statements)

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“… 41 , 42 Higher metabolic consumption may be related to neurotoxicity, which consumes nutrients in the body, thus oxidizing and damaging brain tissue. 43 Therefore, we believe that appropriate weight gain has a protective effect on AD patients. Interestingly, JDYZF can achieve this result.…”

Section: Discussionmentioning

confidence: 98%

Jiedu Yizhi Formula Improves Cognitive Function by Regulating the Gut Dysbiosis and TLR4/NF-κB Signaling Pathway

Zhang

Wang

Zhu

et al. 2023

NDT

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Objective The objective of this study was to explore the neuroprotective mechanism of JDYZF in treating AD from the perspective of inflammation and intestinal microflora. Methods A total of 24 APP/PS1 mice were randomly divided into four groups: model (n = 6), JDYZF low-dose (n = 6), JDYZF high-dose (n = 6), and positive drug (n = 6), six C57 mice were used as the control group. The body weights and diets of all mice were examined daily. After 8 weeks of administration, the learning and memory of mice were evaluated by the Morris water maze test. The histopathological changes of hippocampus, liver and kidney in mice were observed by HE staining after being euthanized. The expression of p-tau in hippocampus tissue was detected by immunohistochemistry. After that, 16S rDNA sequencing was used to investigate the relationship between JDYZF and intestinal microbiota. Finally, a comparison of TLR4, p65, p-p65, iκB, p-iκB, and IL-1β protein expression in the hippocampus tissue of mice in each group was measured by Western blot. Results The results showed that APP/PS1 mice taking JDYZF orally were generally in good condition. Compared with the control group, JDYZF significantly improved learning and memory ability in ethology. Histology showed that JDYZF improved the hippocampal structure of mice and inhibited the deposition of p-tau. JDYZF treatment could regulate the gut microbiota of APP/PS1 mice by increasing the richness of Lachnospiraceae, Ruminococcaceae , and Actinobacteria and reducing that of Alistipes and Muribaculaceae . It also significantly inhibited the activation of the TLR4/NF-κB signaling pathway in the brain. In addition, no obvious toxic reactions were found in the liver and kidney of APP/PS1 mice after taking JDYZF for 8 weeks. Conclusion The findings revealed that JDYZF improved cognitive ability and alleviated the TLR4/NF-κB signaling pathway in APP/PS1 mice, and the modulating the gut microbiota presented here may help illuminate its activation mechanism.

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Section: Discussionmentioning

confidence: 98%

Jiedu Yizhi Formula Improves Cognitive Function by Regulating the Gut Dysbiosis and TLR4/NF-κB Signaling Pathway

Zhang

Wang

Zhu

et al. 2023

NDT

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“…While there is evidence that these removed markers are associated with the development of cognitive impairment, several studies have reported findings similar to ours. Three previously published studies have indicated that BMI is associated with cognitive function (37)(38)(39); specifically, for every 1 kg/m2 increase in BMI, the prevalence of cognitive impairment increased by 3% (40), while another study reported the opposite result (41). A previous study based on large population data revealed a potential relationship between several obesity-related indicators, including WC, waist-to-hip ratio (WHR), BMI, LDL-C, and cognitive impairment (42).…”

Section: Discussionmentioning

confidence: 99%

A risk prediction model based on machine learning for early cognitive impairment in hypertension: Development and validation study

Zhong

Jiang

et al. 2023

Front. Public Health

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BackgroundClinical practice guidelines recommend early identification of cognitive impairment in individuals with hypertension with the help of risk prediction tools based on risk factors.ObjectiveThe aim of this study was to develop a superior machine learning model based on easily collected variables to predict the risk of early cognitive impairment in hypertensive individuals, which could be used to optimize early cognitive impairment risk assessment strategies.MethodsFor this cross-sectional study, 733 patients with hypertension (aged 30–85, 48.98% male) enrolled in multi-center hospitals in China were divided into a training group (70%) and a validation group (30%). After least absolute shrinkage and selection operator (LASSO) regression analysis with 5-fold cross-validation determined the modeling variables, three machine learning classifiers, logistic regression (LR), XGBoost (XGB), and gaussian naive bayes (GNB), were developed. The area under the ROC curve (AUC), accuracy, sensitivity, specificity, and F1 score were used to evaluate the model performance. Shape Additive explanation (SHAP) analysis was performed to rank feature importance. Further decision curve analysis (DCA) assessed the clinical performance of the established model and visualized it by nomogram.ResultsHip circumference, age, education levels, and physical activity were considered significant predictors of early cognitive impairment in hypertension. The AUC (0.88), F1 score (0.59), accuracy (0.81), sensitivity (0.84), and specificity (0.80) of the XGB model were superior to LR and GNB classifiers.ConclusionThe XGB model based on hip circumference, age, educational level, and physical activity has superior predictive performance and it shows promise in predicting the risk of cognitive impairment in hypertensive clinical settings.

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“…24 To date, the role of BMI in cognitive impairment is not understood well. Some studies have demonstrated a directional, 25 indirect, inverse, 26 or U-shaped association 27 between low or high BMI and cognitive deterioration. However, changes in body composition with age make BMI a rough measure of nutritional status in older adults.…”

Section: Discussionmentioning

confidence: 99%

Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment

Qin

Han

et al. 2023

Neurology

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Background and Objectives:Various resources exist for treating mild cognitive impairment (MCI) or dementia separately as terminal events or for focusing solely on a one-way path from MCI to dementia without taking into account heterogeneous transitions. Little is known about the trajectory of reversion from MCI to normal cognition (NC) or near-NC and patterns of post-reversion, which refers to cognitive trajectories of patients who have reversed from MCI to NC. Our objectives were to: 1) quantitatively predict bidirectional transitions of MCI (reversion and progression), 2) explore patterns of future cognitive trajectories for post-reversion, and 3) estimate the effects of demographic characteristics, apolipoprotein E (APOE), cognition, daily activity ability, depression and neuropsychiatric symptoms on transition probabilities.Methods:We constructed a retrospective cohort by reviewing patients with an MCI diagnosis at study entry and at least two follow-up visits between June 2005 and February 2021. Defining NC or near-NC and MCI as transient states and dementia as an absorbing state, we used continuous-time multi-state Markov models to estimate instantaneous transition intensity between states, transition probabilities from one state to another at any given time during follow-up, and hazard ratios of reversion-related variables.Results:Among 24,220 observations from 6,651 participants, there were 2,729 transitions to dementia and 1,785 reversions. As for post-reversion, there were 630 and 73 transitions of progression to MCI and dementia, respectively. The transition intensity of progression to MCI for post-reversion was 0.317 (2.48-fold greater than that for MCI progression or reversion). For post-reversion participants, the probability of progressing to dementia increased by 2% yearly. Participants who progressed to MCI were likely to reverse again (probability of 40% over 15 years). Age, independence level, APOE, cognition, daily activity ability, depression and neuropsychiatric symptoms were significant predictors of bidirectional transitions.Discussion:The nature of bidirectional transitions cannot be ignored in multi-dimensional MCI research. We found that post-reversion participants remained at an increased risk of progression to MCI or dementia over the longer term and experienced recurrent reversions. Our findings may serve as a valuable reference for future research and enable healthcare professionals to better develop proactive management plans and targeted interventions.

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Association Between Body Mass Index and Cognitive Function in Mild Cognitive Impairment Regardless of APOE ε4 Status

Cited by 9 publications

References 53 publications

Jiedu Yizhi Formula Improves Cognitive Function by Regulating the Gut Dysbiosis and TLR4/NF-κB Signaling Pathway

Jiedu Yizhi Formula Improves Cognitive Function by Regulating the Gut Dysbiosis and TLR4/NF-κB Signaling Pathway

A risk prediction model based on machine learning for early cognitive impairment in hypertension: Development and validation study

Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment

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