scholarly journals Differential Methylation in APOE Genes (Chr19; exon four; from 44,909,188 to 44,909,373) and Increased Apolipoprotein E Plasmatic Levels in Subjects with Mild Cognitive Impairment”

2019 ◽  
Author(s):  
Oscar Mancera Páez ◽  
Kelly Estrada Orozco ◽  
Maria Fernanda Mahecha ◽  
Francy Cruz Sanabria ◽  
Kely Bonilla-Vargas ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Social History ◽  
Regression Models ◽  
Neuropsychological Testing ◽  
Logistic Regression Models ◽  
And Gender ◽  
Epigenetic Patterns ◽  
Risk Association

Background: Biomarkers are essential for identification of individuals at high risk of mild cognitive impairment (MCI) for potential prevention of dementia. We investigated DNA methylation in the ApoE gene and plasmatic apolipoprotein E (ApoE) levels as MCI biomarkers in Colombian subjects with MCI and controls. Methods: 100 participants were included (71% women, average age, 70 yrs., range 43-91). MCI was diagnosed by neuropsychological testing, medical and social history, activities of daily living, cognitive symptoms and neuroimaging. Multivariate logistic regression models adjusted by age and gender were performed to examine the risk association of MCI with plasma ApoE and APOE methylation Results: MCI was diagnosed in 41 subjects (average age, 66.5±9.6 yrs.) and compared with 59 controls. Elevated plasma ApoE and APOE methylation of CpGs 165, 190, and 198 were risk factors for MCI (P<0.05). Higher CpG-227 methylation correlated with lower risk for MCI (P=0.002). Only CpG-227 was significantly correlated with plasmatic ApoE levels (correlation coefficient=-0.665; P=0.008). Conclusion: Differential APOE methylation and increased plasma ApoE levels were correlated with MCI. These epigenetic patterns can be used as potential biomarkers to identify early stages of MCI.

scholarly journals Differential Methylation in APOE (Chr19; Exon Four; from 44,909,188 to 44,909,373/hg38) and Increased Apolipoprotein E Plasma Levels in Subjects with Mild Cognitive Impairment

2019 ◽  
Vol 20 (6) ◽  
pp. 1394 ◽  
Author(s):  
Oscar Mancera-Páez ◽  
Kelly Estrada-Orozco ◽  
María Mahecha ◽  
Francy Cruz ◽  
Kely Bonilla-Vargas ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Social History ◽  
Plasma Levels ◽  
Neuropsychological Testing ◽  
Logistic Regression Models ◽  
And Gender ◽  
Epigenetic Patterns ◽  
Risk Association

Background: Biomarkers are essential for identification of individuals at high risk of mild cognitive impairment (MCI) for potential prevention of dementia. We investigated DNA methylation in the APOE gene and apolipoprotein E (ApoE) plasma levels as MCI biomarkers in Colombian subjects with MCI and controls. Methods: In total, 100 participants were included (71% women; average age, 70 years; range, 43–91 years). MCI was diagnosed by neuropsychological testing, medical and social history, activities of daily living, cognitive symptoms and neuroimaging. Using multivariate logistic regression models adjusted by age and gender, we examined the risk association of MCI with plasma ApoE and APOE methylation. Results: MCI was diagnosed in 41 subjects (average age, 66.5 ± 9.6 years) and compared with 59 controls. Elevated plasma ApoE and APOE methylation of CpGs 165, 190, and 198 were risk factors for MCI (p < 0.05). Higher CpG-227 methylation correlated with lower risk for MCI (p = 0.002). Only CpG-227 was significantly correlated with plasma ApoE levels (correlation coefficient = −0.665; p = 0.008). Conclusion: Differential APOE methylation and increased plasma ApoE levels were correlated with MCI. These epigenetic patterns require confirmation in larger samples but could potentially be used as biomarkers to identify early stages of MCI.

Risk Factors Predicting Amyloid PET Positivity in Patients with Mild Cognitive Impairment and Apolipoprotein E ɛ3/ɛ3 Genotypes

2020 ◽  
Vol 77 (3) ◽  
pp. 1017-1024
Author(s):  
Seong Hee Ho ◽  
Dong-Won Yang
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Brain Mri ◽  
Multivariate Logistic Regression Model ◽  
Amyloid Pet ◽  
Logistic Regression Models ◽  
E4 Allele

Background: The apolipoprotein E (APOE) ɛ4 allele is a well-known risk factor for AD and is associated with higher amyloid deposition and earlier dementia onset. However, the relationship between amyloid pathology and the most common APOE allele, ɛ3, has not been well studied. Objective: In this study, we aimed to identify the risk factors predicting amyloid PET positivity in patients with mild cognitive impairment (MCI) and APOE ɛ3/ɛ3 genotypes. Methods: We retrospectively reviewed the medical records of MCI patients with APOE ɛ3/ɛ3 genotypes who underwent amyloid PET scanning. Demographics, neuropsychological tests, and brain MRI were obtained. We analyzed which risk factors could affect amyloid PET positivity in MCI patients with APOE ɛ3/ɛ3 genotypes using logistic regression models. Results: We recruited 171 MCI patients with APOE ɛ3/ɛ3 genotypes in this study. Out of 171 patients, 49 patients (28.65%) showed positive results in the amyloid PET scans. In a multivariate logistic regression model, amyloid positivity was associated with frontal atrophy (OR = 2.63, p = 0.009), and CDR-SOB scores (OR = 2.46, p = 0.013). The odds ratio for amyloid PET positivity in patients older than and equal to 75 years with both frontal atrophy and CDR-SOB scores >1.0 was 3.63. Conclusion: Our study demonstrated that frontal atrophy, high CDR-SOB scores, and old age were risk factors associated with amyloid PET positivity in MCI with APOE ɛ3/ɛ3 genotypes.

scholarly journals Inequality in Social Support Associated With Mild Cognitive Impairment: A Cross-Sectional Study of Older (≥60 Years) Residents in Shanghai, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Yuan Lu ◽  
Chaojie Liu ◽  
Sally Fawkes ◽  
Jia Ma ◽  
Yalin Liu ◽  
...  
Keyword(s):  
Social Support ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Regression Models ◽  
Income Group ◽  
Interaction Effects ◽  
Personal Income ◽  
Additive Interaction ◽  
Logistic Regression Models

Objective: Social support plays a critical role in the detection and management of mild cognitive impairment (MCI). However, socioeconomic inequalities exist in both social support and health care services. Our study aimed to compare the level of social support received by MCI patients in comparison with those without MCI and to determine its link with income.Methods: Secondary data analyses were performed. Social support was measured using the Duke Social Support Index (DSSI) and satisfaction ratings. Multivariate logistic regression models were constructed to determine the associations of personal income and MCI with social support after adjustment for variations in the sociodemographic and health characteristics of the respondents. The multiplicative and additive interaction effects of income and MCI were further examined through introducing the MCI*Income variable to the regression models and using the relative excess risk due to interaction (RERI) analysis, respectively.Results: The logistic regression models showed that the respondents with MCI had significantly lower social support as measured by the DSSI scores (AOR = 33.03, p &lt; 0.001) and satisfaction ratings (AOR = 7.48, p &lt; 0.001) compared with those without MCI. Similarly, social support decreased with lower personal income (p &lt; 0.001). There existed a significant multiplicative interaction effect between personal income and MCI on social support (AOR = 0.30–0.32, p &lt; 0.01). The gap in social support between those with and without MCI was higher in the higher income group compared with the lower income group (p &lt; 0.001). No significant additive interaction effects on social support were found between MCI and income.Conclusions: There are significant disparities in social support between people living with and without MCI. Such a gap is more profound in people with higher income. The inequality in social support associated with MCI may present a significant challenge to the successful implementation of community MCI detection and management.

scholarly journals Resting State Alpha Electroencephalographic Rhythms Are Differently Related to Aging in Cognitively Unimpaired Seniors and Patients with Alzheimer’s Disease and Amnesic Mild Cognitive Impairment

2021 ◽  
pp. 1-30
Author(s):  
Claudio Babiloni ◽  
Raffaele Ferri ◽  
Giuseppe Noce ◽  
Roberta Lizio ◽  
Susanna Lopez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Resting State ◽  
Diagnostic Biomarkers ◽  
Eyes Closed ◽  
Topographical Effects ◽  
And Gender ◽  
International Archive

Background: In relaxed adults, staying in quiet wakefulness at eyes closed is related to the so-called resting state electroencephalographic (rsEEG) rhythms, showing the highest amplitude in posterior areas at alpha frequencies (8–13 Hz). Objective: Here we tested the hypothesis that age may affect rsEEG alpha (8–12 Hz) rhythms recorded in normal elderly (Nold) seniors and patients with mild cognitive impairment due to Alzheimer’s disease (ADMCI). Methods: Clinical and rsEEG datasets in 63 ADMCI and 60 Nold individuals (matched for demography, education, and gender) were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands, as well as fixed beta (14–30 Hz) and gamma (30–40 Hz) bands. Each group was stratified into three subgroups based on age ranges (i.e., tertiles). Results: As compared to the younger Nold subgroups, the older one showed greater reductions in the rsEEG alpha rhythms with major topographical effects in posterior regions. On the contrary, in relation to the younger ADMCI subgroups, the older one displayed a lesser reduction in those rhythms. Notably, the ADMCI subgroups pointed to similar cerebrospinal fluid AD diagnostic biomarkers, gray and white matter brain lesions revealed by neuroimaging, and clinical and neuropsychological scores. Conclusion: The present results suggest that age may represent a deranging factor for dominant rsEEG alpha rhythms in Nold seniors, while rsEEG alpha rhythms in ADMCI patients may be more affected by the disease variants related to earlier versus later onset of the AD.

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

2021 ◽  
pp. 1-15
Author(s):  
Sung Hoon Kang ◽  
Bo Kyoung Cheon ◽  
Ji-Sun Kim ◽  
Hyemin Jang ◽  
Hee Jin Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Cross Validation ◽  
Good Accuracy ◽  
External Validation ◽  
Amnestic Mild Cognitive Impairment ◽  
Temporal Region ◽  
Apolipoprotein E Genotype

Background: Amyloid (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer’s disease. However, Aβ evaluation through amyloid positron emission tomography (PET) is limited due to high cost and safety issues. Objective: We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers. Methods: We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers). Results: Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity. Conclusion: Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.

scholarly journals A score based on screening tests to differentiate mild cognitive impairment from subjective memory complaints

2013 ◽  
Vol 5 (3) ◽  
pp. 16 ◽  
Author(s):  
Fábio Henrique De Gobbi Porto ◽  
Lívia Spíndola ◽  
Maira Okada De Oliveira ◽  
Patrícia Helena Figuerêdo Do Vale ◽  
Marco Orsini ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Characteristic Curve ◽  
Neuropsychological Testing ◽  
Area Under The Curve ◽  
Screening Tests ◽  
Elderly Subjects ◽  
Subjective Memory ◽  
Delayed Recall ◽  
Memory Complaints

It is not easy to differentiate patients with mild cognitive impairment (MCI) from subjective memory complainers (SMC). Assessments with screening cognitive tools are essential, particularly in primary care where most patients are seen. The objective of this study was to evaluate the diagnostic accuracy of screening cognitive tests and to propose a score derived from screening tests. Elderly subjects with memory complaints were evaluated using the Mini Mental State Examination (MMSE) and the Brief Cognitive Battery (BCB). We added two delayed recalls in the MMSE (a delayed recall and a late-delayed recall, LDR), and also a phonemic fluency test of letter P fluency (LPF). A score was created based on these tests. The diagnoses were made on the basis of clinical consensus and neuropsychological testing. Receiver operating characteristic curve analyses were used to determine area under the curve (AUC), the sensitivity and specificity for each test separately and for the final proposed score. MMSE, LDR, LPF and delayed recall of BCB scores reach statistically significant differences between groups (P=0.000, 0.03, 0.001 and 0.01, respectively). Sensitivity, specificity and AUC were MMSE: 64%, 79% and 0.75 (cut off &lt;29); LDR: 56%, 62% and 0.62 (cut off &lt;3); LPF: 71%, 71% and 0.71 (cut off &lt;14); delayed recall of BCB: 56%, 82% and 0.68 (cut off &lt;9). The proposed score reached a sensitivity of 88% and 76% and specificity of 62% and 75% for cut off over 1 and over 2, respectively. AUC were 0.81. In conclusion, a score created from screening tests is capable of discriminating MCI from SMC with moderate to good accurancy.

Association of Dietary Habits with Mild Cognitive Impairment among Elderly in Rural Area of North China

2021 ◽  
Vol 18 ◽  
Author(s):  
Huilian Duan ◽  
Changqing Sun ◽  
Yun Zhu ◽  
Qian Liu ◽  
Yue Du ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Rural Area ◽  
Dietary Habits ◽  
Cross Sectional Study ◽  
Community Dwelling ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Cooking Oil ◽  
Meal Timing

Background: Recent findings suggest a possible role of diet, particularly nutrient in- takes and dietary patterns, in the prevalence of mild cognitive impairment (MCI); few studies, how- ever, have been explicitly devoted to the relationship between dietary habits and MCI. Objectives: We aimed to explore the association between dietary habits, including meal timing, and MCI among older Chinese adults. Methods: This cross-sectional study involved data collected at the baseline of the Tianjin Elderly Nutrition and Cognition Cohort (TENCC) study, in which 3,111 community-dwelling older adults (326 MCI patients and 2,785 non-MCIs) from a rural area of Tianjin, China, were recruited. In March 2018 to June 2019, all participants underwent a detailed neuropsychological evaluation that allowed for psychometric MCI classification. Information on self-reported dietary behaviors was gathered via face-to-face interviews. Crude and multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression models. Results: In the multivariable-adjusted models, eating breakfast 4 to 6 times per week (vs. ≤3 times per week, OR: 0.45; 95% CI: 0.26, 0.75), drinking water before breakfast (yes vs. no, OR: 0.64; 95% CI: 0.51, 0.82), consuming water ≥1.5L per day (vs. <1.5L per day, OR: 0.64; 95% CI: 0.51, 0.82), and having lunch after 12:00 (vs. before 12:00, OR: 0.59; 95% CI: 0.47, 0.75) were associat- ed with decreased risk of MCI. Participants who consumed higher amounts of cooking oil were at a higher risk of MCI (moderate vs. low, OR: 1.42; 95% CI: 1.04, 1.92; high vs. low, OR: 1.40; 95% CI: 1.07-1.83). Conclusion : This study suggests that dietary habits, including breakfast frequency, daily water consumption, cooking oil consumption, and meal timing, may be associated with the risk of MCI. If replicated, these findings would open new possibilities of dietary interventions for MCI.

Abstract 1122‐000036: Demographic and Pharmacological Characteristics of Alzheimer Dementia Patients with Mild Cognitive Impairment stratified by Gender

2021 ◽  
Vol 1 (S1) ◽  
Author(s):  
Oreoluwa O Coker‐Ayo ◽  
Samuel Nathaniel ◽  
Chika Onuoha ◽  
Nneoma Madubuike ◽  
Lidadi Agbomi ◽  
...  
Keyword(s):  
Gender Differences ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Regression Models ◽  
Operating Characteristic ◽  
Management Strategies ◽  
Roc Curve Analysis ◽  
Alzheimer Dementia ◽  
Dementia Patients ◽  
Specific Factors

Introduction : The role that specific clinical factors play in contributing to gender differences in Alzheimer’s patients with mild cognitive impairment (MCI) is not yet fully understood. In this study, we tested the hypothesis that pharmacological, demographic, and risk factors may contribute to gender difference in Alzheimer’s patients with MCI. Methods : Methods Data collected for 5 years was analyzed using a retrospective data analytical approach on 33,064 Alzheimer patients, including 13,569 men and 19,495 women that presented with MCI. Receiver operating characteristic (ROC) curve analysis and multivariate regression models were used to identify specific factors that contribute to gender differences in MCI patients. Results : Results Our records indicate that women that presented with MCI were more likely to be taking Buspirone (OR = 0.767, 95% CI, 0.683‐0.861, P<0.001) while men within this population were more likely to be taking Galantamine (OR = 0.559, 95% CI, 0.382‐0.818, P<0.001). ETOH use was associated with MCI in both men (OR = 0.696, 95% CI, 0.638‐0.760, P<0.001) and women with Alzheimer’s Dementia (OR = 0.484, 95% CI, 0.442‐0.529, P<0.001). Conclusions : Conclusion Our findings reveal gender differences in men and women that presented with MCI. Management strategies should consider identified factors to provide better care for Alzheimer patients with MCI.

scholarly journals Mild cognitive impairment: prevalence and incidence according to different diagnostic criteria

2003 ◽  
Vol 182 (5) ◽  
pp. 449-454 ◽  
Author(s):  
Anja Busse ◽  
Jeannette Bischkopf ◽  
Steffi G. Riedel-Heller ◽  
Matthias C. Angermeyer
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Longitudinal Study ◽  
Diagnostic Criteria ◽  
Community Sample ◽  
Neuropsychological Testing ◽  
Incidence Rates ◽  
Prevalence Rates ◽  
Case Definitions ◽  
Increased Risk

BackgroundAlthough mild cognitive impairment is associated with an increased risk of developing dementia, there has been little work on its incidence and prevalence.AimsTo report age-specific prevalence, incidence and predictive validities for four diagnostic concepts of mild cognitive impairment.MethodA community sample of 1045 dementia-free individuals aged 75 years and over was examined by neuropsychological testing in a three-wave longitudinal study.ResultsPrevalence rates ranged from 3% to 20%, depending on the concept applied. The annual incidence rates applying different case definitions varied from 8 to 77 per 1000 person-years. Rates of conversion to dementia over 2.6 years ranged from 23% to 47%.ConclusionsMild cognitive impairment is frequent in older people. Prevalence, incidence and predictive validities are highly dependent on the diagnostic criteria applied.

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