Posterior atrophy predicts time to dementia in patients with amyloid-positive mild cognitive impairment

Cholinesterase inhibitor use in amyloid PET-negative mild cognitive impairment and cognitive changes

BACKGROUND

Cholinesterase inhibitors (ChEIs) are prescribed for Alzheimer's disease (AD) and sometimes for mild cognitive impairment (MCI) without knowing underlying pathologies and its effect on cognition. We investigated the frequency of ChEI prescriptions in amyloid-negative MCI and their association with cognitive changes in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.

METHODS

We included participants with amyloid positron emission tomography (PET)-negative MCI from the ADNI. We analyzed the associations of ChEI use with cognitive changes, brain volume, and cerebrospinal fluid (CSF) total tau (t-tau), hyperphosphorylated tau181 (p-tau181), and p-tau181/t-tau ratio.

RESULTS

ChEIs were prescribed in 27.4% of amyloid PET-negative MCI and were associated with faster cognitive decline, reduced baseline hippocampal volume and entorhinal cortical thickness, and a longitudinal decrease in the frontal lobe cortical thickness.

CONCLUSIONS

The association between ChEI use and accelerated cognitive decline may stem from underlying pathologies involving reduced hippocampal volume, entorhinal cortical thickness and faster frontal lobe atrophy. We suggest that ChEI use in amyloid PET-negative MCI patients might need further consideration, and studies investigating the causality between ChEI use and cognitive decline are warranted in the future.

The impact of medial temporal and parietal atrophy on cognitive function in dementia

Although medial temporal atrophy (MTA) and parietal atrophy (Koedam score) have been used to diagnose Alzheimer's disease (AD), early detection of other dementia types remains elusive. The study aims to investigate the association between these brain imaging markers and cognitive function in dementia. This cross-sectional study collected data from the Memory Clinic of Dr. Sardjito General Hospital Yogyakarta, Indonesia from January 2020 until December 2022. The cut-off value of MTA and Koedam score was set with Receiver Operating Curve. Multivariate analysis was performed to investigate the association between MTA and Koedam score with cognitive function. Of 61 patients, 22.95% had probable AD, 59.01% vascular dementia, and 18.03% mixed dementia. Correlation test showed that MTA and Koedam score were negatively associated with Montreal Cognitive Assessment-Indonesian Version (MoCA-INA) score. MTA score ≥ 3 (AUC 0.69) and Koedam score ≥ 2 (AUC 0.67) were independently associated with higher risk of poor cognitive function (OR 13.54, 95% CI 1.77-103.43, p = 0.01 and OR 5.52, 95% CI 1.08-28.19, p = 0.04). Higher MTA and Koedam score indicate worse cognitive function in dementia. Future study is needed to delineate these findings as prognostic markers of dementia severity.

Prognostic and Predictive Factors in Early Alzheimer's Disease: A Systematic Review

Background

Alzheimer's disease (AD) causes progressive decline of cognition and function. There is a lack of systematic literature reviews on prognostic and predictive factors in its early clinical stages (eAD), i.e., mild cognitive impairment due to AD and mild AD dementia.

Objective

To identify prognostic factors affecting eAD progression and predictive factors for treatment efficacy and safety of approved and/or under late-stage development disease-modifying treatments.

Methods

Databases were searched (August 2022) for studies reporting prognostic factors associated with eAD progression and predictive factors for treatment response. The Quality in Prognostic Factor Studies tool or the Cochrane risk of bias tool were used to assess risk of bias. Two reviewers independently screened the records. A single reviewer performed data extraction and quality assessment. A second performed a 20% check. Content experts reviewed and interpreted the data collected.

Results

Sixty-one studies were included. Self-reporting, diagnosis definition, and missing data led to high risk of bias. Population size ranged from 110 to 11,451. Analyses found data indicating that older age was and depression may be associated with progression. Greater baseline cognitive impairment was associated with progression. APOE4 may be a prognostic factor, a predictive factor for treatment efficacy and predicts an adverse response (ARIA). Elevated biomarkers (CSF/plasma p-tau, CSF t-tau, and plasma neurofilament light) were associated with disease progression.

Conclusions

Age was the strongest risk factor for progression. Biomarkers were associated with progression, supporting their use in trial selection and aiding diagnosis. Baseline cognitive impairment was a prognostic factor. APOE4 predicted ARIA, aligning with emerging evidence and relevant to treatment initiation/monitoring.

Consensus on rapid screening for prodromal Alzheimer's disease in China

Alzheimer's disease (AD) is a common cause of dementia, characterised by cerebral amyloid-β deposition, pathological tau and neurodegeneration. The prodromal stage of AD (pAD) refers to patients with mild cognitive impairment (MCI) and evidence of AD's pathology. At this stage, disease-modifying interventions should be used to prevent the progression to dementia. Given the inherent heterogeneity of MCI, more specific biomarkers are needed to elucidate the underlying AD's pathology. Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology, their clinical applications are limited by their high costs and invasiveness, particularly in low-income areas in China. Therefore, to improve the early detection of Alzheimer's disease (AD) pathology through cost-effective screening methods, a panel of 45 neurologists, psychiatrists and gerontologists was invited to establish a formal consensus on the screening of pAD in China. The supportive evidence and grades of recommendations are based on a systematic literature review and focus group discussion. National meetings were held to allow participants to review, vote and provide their expert opinions to reach a consensus. A majority (two-thirds) decision was used for questions for which consensus could not be reached. Recommended screening methods are presented in this publication, including neuropsychological assessment, peripheral biomarkers and brain imaging. In addition, a general workflow for screening pAD in China is established, which will help clinicians identify individuals at high risk and determine therapeutic targets.

Associations of carotid artery flow parameters with MRI markers of cerebral small vessel disease and patterns of brain atrophy

OBJECTIVES

A growing body of evidence links age related brain pathologies to systemic vascular processes. We aimed to study the prevalence and interrelations between magnetic resonance imaging (MRI) markers of cerebral small vessel disease and patterns of brain atrophy, and their association to carotid duplex ultrasound flow parameters.

MATERIALS AND METHODS

We investigated a population based randomised cohort of older adults (n=391) aged 70-87, part of the Swedish Good Aging in Skåne Study. Peak systolic and end diastolic velocities of the carotid arteries were measured by ultrasound, and resistivity- and pulsatility indexes were calculated. Subjects with increased peak systolic velocity indicating carotid stenosis were excluded from analysis. Nine MRI findings were rated by visual scales: white matter changes, pontine white matter changes, microbleeds, lacunar infarctions, medial temporal lobe atrophy, global cortical atrophy, parietal atrophy, precuneus atrophy and central atrophy.

RESULTS

MRI pathologies were found in 80% of subjects. Mean end diastolic velocity in common carotid arteries was inversely associated with white matter hyperintensities (OR=0.92; p=0.004), parietal lobe atrophy (OR=0.94; p=0.039), global cortical atrophy (OR=0.90; p=0.013), precuneus atrophy (OR=0.94; p=0.022), "number of CSV pathologies" (β=-0.07; p<0.001) and "MRI-burden score" (β=-0.11; p<0.001), after adjustment for age and sex. The latter three were also associated with pulsatility and resistivity indexes.

CONCLUSIONS

Low carotid end diastolic velocity, as well as increased carotid resistivity and pulsatility, were associated with signs of cerebral small vessel disease and patterns of brain atrophy, indicating a vascular component in the process of brain aging.

Predicting progression to dementia with “comprehensive visual rating scale” and machine learning algorithms

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.

Associations of multiple visual rating scales based on structural magnetic resonance imaging with disease severity and cerebrospinal fluid biomarkers in patients with Alzheimer’s disease

The relationships between multiple visual rating scales based on structural magnetic resonance imaging (sMRI) with disease severity and cerebrospinal fluid (CSF) biomarkers in patients with Alzheimer’s disease (AD) were ambiguous. In this study, a total of 438 patients with clinically diagnosed AD were recruited. All participants underwent brain sMRI scan, and medial temporal lobe atrophy (MTA), posterior atrophy (PA), global cerebral atrophy-frontal sub-scale (GCA-F), and Fazekas rating scores were visually evaluated. Meanwhile, disease severity was assessed by neuropsychological tests such as the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Clinical Dementia Rating (CDR). Among them, 95 patients were tested for CSF core biomarkers, including Aβ_1–42, Aβ_1–40, Aβ_1–42/Aβ_1–40, p-tau, and t-tau. As a result, the GCA-F and Fazekas scales showed positively significant correlations with onset age (r = 0.181, p < 0.001; r = 0.411, p < 0.001, respectively). Patients with late-onset AD (LOAD) showed higher GCA-F and Fazekas scores (p < 0.001, p < 0.001). With regard to the disease duration, the MTA and GCA-F were positively correlated (r = 0.137, p < 0.05; r = 0.106, p < 0.05, respectively). In terms of disease severity, a positively significant association emerged between disease severity and the MTA, PA GCA-F, and Fazekas scores (p < 0.001, p < 0.001, p < 0.001, p < 0.05, respectively). Moreover, after adjusting for age, gender, and APOE alleles, the MTA scale contributed to moderate to severe AD in statistical significance independently by multivariate logistic regression analysis (p < 0.05). The model combining visual rating scales, age, gender, and APOE alleles showed the best performance for the prediction of moderate to severe AD significantly (AUC = 0.712, sensitivity = 51.5%, specificity = 84.6%). In addition, we observed that the MTA and Fazekas scores were associated with a lower concentration of Aβ_1–42 (p < 0.031, p < 0.022, respectively). In summary, we systematically analyzed the benefits of multiple visual rating scales in predicting the clinical status of AD. The visual rating scales combined with age, gender, and APOE alleles showed best performance in predicting the severity of AD. MRI biomarkers in combination with CSF biomarkers can be used in clinical practice.

Alpha 1-antichymotrypsin may be a biomarker for the progression of amnestic mild cognitive impairment

Alpha 1-antichymotrypsin (ACT), an acute-phase protein, has been reported to be increased in the brain and blood of Alzheimer's disease (AD) patients. However, few previous studies have focused on amnestic mild cognitive impairment (aMCI) patients. The aim of our study was to investigate the changing trend in ACT concentrations during the progression of aMCI. Hence, we measured the cerebrospinal fluid (CSF) and serum levels of ACT in aMCI subjects and normal controls (NC) at 2-year follow-up assessments using ELISA and Western blot. Forty-four NCs, 28 stable aMCI (sMCI) patients, and 20 progressive aMCI (pMCI) patients finished the follow-up assessments, and their data were used for analysis. We found that CSF and serum ACT levels of both sMCI and pMCI patients increased over time, while those of NCs remained stable; CSF and serum ACT levels were significantly higher in both sMCI and pMCI patients than in NCs, except for baseline serum ACT. In pMCI patients prior to developing AD, CSF and serum ACT levels were already significantly higher than those in sMCI patients. The ROC curve results demonstrated that combining CSF and serum ACT levels can distinguish aMCI patients from NCs with high specificity and sensitivity. Our data suggest that ACT may be a biomarker for diagnosing aMCI.

Cognitive Reserve, Alzheimer's Neuropathology, and Risk of Dementia: A Systematic Review and Meta-Analysis

Cognitive reserve (CR) may reduce the risk of dementia. We summarized the effect of CR on progression to mild cognitive impairment (MCI) or dementia in studies accounting for Alzheimer's disease (AD)-related structural pathology and biomarkers. Literature search was conducted in Web of Science, PubMed, Embase, and PsycINFO. Relevant articles were longitudinal, in English, and investigating MCI or dementia incidence. Meta-analysis was conducted on nine articles, four measuring CR as cognitive residual of neuropathology and five as composite psychosocial proxies (e.g., education). High CR was related to a 47% reduced relative risk of MCI or dementia (pooled-hazard ratio: 0.53 [0.35, 0.81]), with residual-based CR reducing risk by 62% and proxy-based CR by 48%. CR protects against MCI and dementia progression above and beyond the effect of AD-related structural pathology and biomarkers. The finding that proxy-based measures of CR rivaled residual-based measures in terms of effect on dementia incidence underscores the importance of early- and mid-life factors in preventing dementia later.

Medial temporal lobe atrophy and posterior atrophy scales normative values

OBJECTIVES

The medial temporal lobe atrophy (MTA) and the posterior atrophy (PA) scales allow to assess the degree hippocampal and parietal atrophy from magnetic resonance imaging (MRI) scans. Despite reliable, easy and widespread employment, appropriate normative values are still missing. We aim to provide norms for the Italian population.

METHODS

Two independent raters assigned the highest MTA and PA score between hemispheres, based on 3D T1-weighted MRI of 936 Italian Brain Normative Archive subjects (age: mean ± SD: 50.2 ± 14.7, range: 20-84; MMSE>26 or CDR = 0). The inter-rater agreement was assessed with the absolute intraclass correlation coefficient (aICC). We assessed the association between MTA and PA scores and sociodemographic features and APOE status, and normative data were established by age decade based on percentile distributions.

RESULTS

Raters agreed in 90% of cases for MTA (aICC = 0.86; 95% CI = 0.69-0.98) and in 86% for PA (aICC = 0.82; 95% CI = 0.58-0.98). For both rating scales, score distribution was skewed, with MTA = 0 in 38% of the population and PA = 0 in 52%, while a score ≥ 2 was only observed in 12% for MTA and in 10% for PA. Median denoted overall hippocampal (MTA: median = 1, IQR = 0-1) and parietal (PA: median = 0, IQR = 0-1) integrity. The 90th percentile of the age-specific distributions increased from 1 (at age 20-59) for both scales, to 2 for PA over age 60, and up to 4 for MTA over age 80. Gender, education and APOE status did not significantly affect the percentile distributions in the whole sample, nor in the subset over age 60.

CONCLUSIONS

Our normative data for the MTA and PA scales are consistent with previous studies and overcome their main limitations (in particular uneven representation of ages and missing percentile distributions), defining the age-specific norms to be considered for proper brain atrophy assessment.