Clinical Dementia Rating Scale Sum Research Articles

18F]FDG PET integrated with structural MRI for accurate brain age prediction.

Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data. The dataset comprised participants from both the Universal Medical Imaging Diagnostic Center (UMIDC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The former recruited 395 normal control (NC) subjects, while the latter included 438 NC subjects, 51 mild cognitive impairment (MCI) subjects, and 56 Alzheimer's disease (AD) subjects. We developed a novel dual-pathway, 3D simple fully convolutional network (Dual-SFCNeXt) to estimate brain age using [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) and structural magnetic resonance imaging (sMRI) images of NC subjects as input. Several prevailing DL models were trained and tested using either MRI or PET data for comparison. Model accuracies were evaluated using mean absolute error (MAE) and Pearson's correlation coefficient (r). Brain age gap (BAG), deviations of brain age from chronologic age, was correlated with cognitive assessments in MCI and AD subjects. Both PET- and MRI-based models achieved high prediction accuracy. The leading model was the SFCNeXt (the single-pathway version) for PET (MAE = 2.92, r = 0.96) and MRI (MAE = 3.23, r = 0.95) on all samples. By integrating both PET and MRI images, the Dual-SFCNeXt demonstrated significantly improved accuracy (MAE = 2.37, r = 0.97) compared to all single-modality models. Significantly higher BAG was observed in both the AD (P < 0.0001) and MCI (P < 0.0001) groups compared to the NC group. BAG correlated significantly with Mini-Mental State Examination (MMSE) scores (r=-0.390 for AD, r=-0.436 for MCI) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) scores (r = 0.333 for AD, r = 0.372 for MCI). The integration of [18F]FDG PET with structural MRI enhances the accuracy of brain age prediction, potentially introducing a new avenue for related multimodal brain age prediction studies.

Breakdown of TMS evoked EEG signal propagation within the default mode network in Alzheimer’s disease

BackgroundThe neural activity of the Default Mode Network (DMN) is disrupted in patients with In Alzheimer’s disease (AD). ObjectivesWe used a novel multimodal approach to track neural signal propagation within the DMN in AD patients. MethodsTwenty mild to moderate AD patients were recruited. We used transcranial magnetic stimulation (TMS) pulses to probe with a millisecond time resolution the propagation of evoked electroencephalography (EEG) signal following the neural activation of the Precuneus (PC), which is a key hub area of the DMN. Moreover, functional and structural magnetic resonance imaging (MRI) data were collected to reconstruct individual features of the DMN. ResultsIn AD patients a probe TMS pulse applied over the PC evokes an increased local activity unmasking underlying hyperexcitability. In contrast, the EEG evoked neural signal did not propagate efficiently within the DMN showing a remarkable breakdown of signal propagation. fMRI and structural tractography showed that impaired signal propagation was related to the same connectivity matrices derived from DMN BOLD signal and transferred by specific white matter bundles forming the cingulum. These features were not detectable stimulating other areas (left dorsolateral prefrontal cortex) or for different networks (fronto-parietal network). Finally, connectivity breakdown was associated with cognitive impairment, as measured with the Clinical Dementia Rating Scale sum of boxes (CDR-SB). ConclusionsTMS-EEG in AD shows both local hyperexcitability and a lack of signal propagation within the DMN. These neurophysiological features also correlate with structural and cognitive attributes of the patients. SignificanceNeuronavigated TMS-EEG may be used as a novel neurophysiological biomarker of DMN connectivity in AD patients.

Sarcopenia is a predictor for Alzheimer’s continuum and related clinical outcomes

Low body mass index is closely related to a high risk of Alzheimer’s disease (AD) and related biomarkers including amyloid-β (Aβ) deposition. However, the association between sarcopenia and Aβ-confirmed AD remains controversial. Therefore, we investigated the relationship between sarcopenia and the AD continuum. We explored sarcopenia’s association with clinical implications of participants on the AD continuum. We prospectively enrolled 142 participants on the AD continuum (19 with preclinical AD, 96 with mild cognitive impairment due to AD, and 28 with AD dementia) and 58 Aβ-negative cognitively unimpaired participants. Sarcopenia, assessed using dual-energy X-ray absorptiometry and hand grip measurements, was considered a predictor. AD continuum, defined by Aβ deposition on positron emission tomography served as an outcome. Clinical severity in participants on the AD continuum assessed using hippocampal volume, Mini-Mental State Examination (MMSE), Seoul Verbal Learning Test (SVLT), and Clinical Dementia Rating Scale Sum of Boxes Scores (CDR-SOB) were also considered an outcome. Sarcopenia (odds ratio = 4.99, p = 0.004) was associated independently with the AD continuum after controlling for potential confounders. Moreover, sarcopenia was associated with poor downstream imaging markers (decreased hippocampal volume, β = − 0.206, p = 0.020) and clinical outcomes (low MMSE, β = − 1.364, p = 0.025; low SVLT, β = − 1.077, p = 0.025; and high CDR-SOB scores, β = 0.783, p = 0.022) in participants on the AD continuum. Sarcopenia was associated with the AD continuum and poor clinical outcome in individuals with AD continuum. Therefore, our results provide evidence for future studies to confirm whether proper management of sarcopenia can effective strategies are required for sarcopenia management to prevent the AD continuum and its clinical implications.

Relationship between the response to donepezil and plasma amyloid beta oligomers in patients with Alzheimer's disease.

To date, there is no reported effective biomarker that can predict which Alzheimer's disease (AD) patients will respond to donepezil and which will not. This study aimed to investigate whether baseline values of Aβ oligomers (AβOs), measured by the Multimer Detection System-Oligomeric Aβ (MDS-OAβ), can be used to predict responders after 6 months of donepezil medication. The study enrolled 104 patients diagnosed with probable AD. After 6 months of donepezil medication, the response to treatment was evaluated by re-assessing the Korean version of the Mini-Mental State Examination (K-MMSE) and Clinical Dementia Rating scale-Sum of Box (CDR-SB) scales conducted at baseline. The patients were categorized into two groups according to the baseline MDS-OAβ values known as the cut-off for AD diagnosis: a group with values below 0.78 and another group with values equal to or above 0.78. After 6 months of medication, the number of responders was 50 (49.5%). Responders exhibited significantly worse baseline CDR, CDR-SB, K-MMSE, and Barthel index compared with non-responders. There was a significantly higher number of responders among patients with MDS-OAβ values below the cut-off of 0.78 compared with those with values equal to or above this threshold. Furthermore, there was a significant improvement in the K-MMSE and CDR-SB after 6 months of donepezil medication in patients with MDS-OAβ values below 0.78 compared with those with values equal to or above 0.78. Baseline MDS-OAβ values might constitute a novel biochemical marker for the efficacy of 6 months of donepezil treatment in AD. Geriatr Gerontol Int 2024; ••: ••-••.

The Different Associations of White Matter Hyperintensities With Severity of Dementia and Cognitive Impairment According to the Distance From the Lateral Ventricular Surface in Patients With Alzheimer's Disease.

White matter hyperintensities (WMH) are common among the elderly. Although WMH play a key role in lowering the threshold for the clinical expression of dementia in Alzheimer's disease (AD)-related pathology, the clinical significance of their location is not fully understood. This study aimed to investigate the association between WMH and cognitive function according to the location of WMH in AD. Subjects underwent clinical evaluations including volumetric brain magnetic resonance imaging study and neuropsychological tests using the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet. WMH were calculated using automated quantification method. According to the distance from the lateral ventricular surface, WMH within 3 mm, WMH within 3-13 mm, and WMH over 13 mm were classified as juxtaventricular WMH (JVWMH), periventricular WMH (PVWMH), and deep WMH (DWMH), respectively. Total WMH volume was associated with poor performance in categorical verbal fluency test (β=-0.197, p=0.035). JVWMH volume was associated with poor performances on categorical verbal fluency test (β=-0.201, p=0.032) and forward digit span test (β= -0.250, p=0.012). PVWMH volume was associated with poor performances on categorical verbal fluency test (β=-0.185, p=0.042) and word list memory test (β=-0.165, p=0.042), whereas DWMH volume showed no association with cognitive tests. PVWMH volume were also related to Clinical Dementia Rating Scale Sum of Boxes score (β=0.180, p=0.026). WMH appear to exhibit different associations with the severity of dementia and cognitive impairment according to the distance from ventricle surface in AD.

Osteopontin: A novel marker of pre-symptomatic sporadic Alzheimer's disease.

We investigate the role of osteopontin (OPN) in participants with Pre-symptomatic Alzheimer's disease (AD), mild cognitive impairment (MCI), and in AD brains. Cerebrospinal fluid (CSF) OPN, AD, and synaptic biomarker levels were measured in 109 cognitively unimpaired (CU), parental-history positive Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer's Disease (PREVENT-AD) participants, and in 167 CU and 399 participants with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. OPN levels were examined as a function of amyloid beta (Aβ) and tau positivity. Survival analyses investigated the link between OPN and rate of conversion to AD. In PREVENT-AD, CSF OPN was positively correlated with synaptic biomarkers. In PREVENT-AD and ADNI, OPN was elevated in CSF Aβ42/40(+)/total tau(+) and CSF Aβ42/40(+)/phosphorylated tau181(+) individuals. In ADNI, OPN was increased in Aβ(+) positron emission tomography (PET) and tau(+) PET individuals, and associated with an accelerated rate of conversion to AD. OPN was elevated in autopsy-confirmed AD brains. Strong associations between CSF OPN and key markers of AD pathophysiology suggest a significant role for OPN in tau neurobiology, particularly in the early stages of the disease. In the Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer's Disease cohort, we discovered that cerebrospinal fluid (CSF) osteopontin (OPN) levels can indicate early synaptic dysfunction, tau deposition, and neuronal loss in cognitively unimpaired elderly with a parental history. CSF OPN is elevated in amyloid beta(+) positron emission tomography (PET) and tau(+) PET individuals. Elevated CSF OPN is associated with an accelerated rate of conversion to Alzheimer's disease (AD). Elevated CSF OPN is associated with an accelerated rate of cognitive decline on the Alzheimer's Disease Assessment Scale-Cognitive subscale 13, Montreal Cognitive Assessment, Mini-Mental State Examination, and Clinical Dementia Rating Scale Sum of Boxes. OPN mRNA and protein levels are significantly upregulated in the frontal cortex of autopsy-confirmed AD brains.

Impact of Different Diagnostic Measures on Drug Class Association with Dementia Progression Risk: A Longitudinal Prospective Cohort Study.

The Clinical Dementia Rating Scale Sum of Boxes (CDRSOB) score is known to be highly indicative of cognitive-functional status and is regularly employed for clinical and research purposes. Our aim is to determine whether CDRSOB is consistent with clinical diagnosis in evaluating drug class associations with risk of progression to mild cognitive impairment (MCI) and dementia. We employed weighted Cox regression analysis on longitudinal NACC data, to identify drug classes associated with disease progression risk, using clinical diagnosis and CDRSOB as the outcome. Aspirin (antiplatelet/NSAID), angiotensin II inhibitors (antihypertensive), and Parkinson's disease medications were significantly associated with reduced risk of progression to MCI/dementia and Alzheimer's disease medications were associated with increased MCI-to-Dementia progression risk with both clinical diagnosis and CDRSOB as the outcome. However, certain drug classes/subcategories, like anxiolytics, antiadrenergics, calcium (Ca2+) channel blockers, and diuretics (antihypertensives) were associated with reduced risk of disease progression, and SSRIs (antidepressant) were associated with increased progression risk only with CDRSOB. Additionally, metformin (antidiabetic medication) was associated with reduced MCI-to-Dementia progression risk only with clinical diagnosis as the outcome. Although the magnitude and direction of the effect were primarily similar for both diagnostic outcomes, we demonstrate that choice of diagnostic measure can influence the significance of risk/protection attributed to drug classes and consequently the conclusion of findings. A consensus must be reached within the research community with respect to the most accurate diagnostic outcome to identify risk and improve reproducibility.

Clinically feasible automated MRI volumetry of the brain as a prognostic marker in subjective and mild cognitive impairment.

The number of patients suffering from cognitive decline and dementia increases, and new possible treatments are being developed. Thus, the need for time efficient and cost-effective methods to facilitate an early diagnosis and prediction of future cognitive decline in patients with early cognitive symptoms is becoming increasingly important. The aim of this study was to evaluate whether an MRI based software, NeuroQuant® (NQ), producing volumetry of the hippocampus and whole brain volume (WBV) could predict: (1) conversion from subjective cognitive decline (SCD) at baseline to mild cognitive impairment (MCI) or dementia at follow-up, and from MCI at baseline to dementia at follow-up and (2) progression of cognitive and functional decline defined as an annual increase in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score. MRI was performed in 156 patients with SCD or MCI from the memory clinic at Oslo University Hospital (OUH) that had been assessed with NQ and had a clinical follow-up examination. Logistic and linear regression analyses were performed with hippocampus volume and WBV as independent variables, and conversion or progression as dependent variables, adjusting for demographic and other relevant covariates including Mini-Mental State Examination-Norwegian Revised Version score (MMSE-NR) and Apolipoprotein E ɛ4 (APOE ɛ4) carrier status. Hippocampus volume, but not WBV, was associated with conversion to MCI or dementia, but neither were associated with conversion when adjusting for MMSE-NR. Both hippocampus volume and WBV were associated with progression as measured by the annual change in CDR-SB score in both unadjusted and adjusted analyses. The results indicate that automated regional MRI volumetry of the hippocampus and WBV can be useful in predicting further cognitive decline in patients with early cognitive symptoms.

Subjective Cognitive Decline in Community-Dwelling Older Adults With Objectively Normal Cognition: Mediation by Depression and Instrumental Activities of Daily Living.

Subjective cognitive decline (SCD) refers to self-reported memory loss despite normal cognitive function and is considered a preclinical stage of Alzheimer's disease. This study aimed to examine the mediating effects of depression and Instrumental Activities of Daily Living (IADL) on the association between the scoring of Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and Subjective Cognitive Decline Questionnaire (SCD-Q). A sample of 139 community-dwelling older adults aged 65-79 with normal cognitive function completed the SCD-Q, a comprehensive neuropsychological battery, and functional/psychiatric scales. We conducted 1) a correlation analysis between SCD-Q scores and other variables and 2) a path analysis to examine the mediating effects of depression and IADL on the relationship between CDR-SB and SCD-Q. CDR-SB was found to be indirectly associated with SCD-Q, with depressive symptoms mediating this relationship. However, no direct association was observed between SCD-Q and CDR-SB. Additionally, IADL was not associated with SCD-Q and did not mediate the relationship between CDR-SB and SCD-Q. The model fit was acceptable (minimum discrepancy function by degrees of freedom divided [CMIN/DF]=1.585, root mean square error of approximation [RMSEA]=0.065, comparative fit index [CFI]=0.955, Tucker-Lewis index [TLI]=0.939). Our results suggest that SCD-Q is influenced by depressive symptoms, but not by IADL. The role of depressive symptoms as a mediator between CDR-SB and SCD-Q indicates that psychological factors may contribute to the perception of SCD. Therefore, interventions targeting depression may mitigate the concerns associated with SCD and reduce feelings of worse performance compared to others of the same age group.

Irisin Levels in Cerebrospinal Fluid Correlate with Biomarkers and Clinical Dementia Scores in Alzheimer Disease.

Irisin, released by muscles during exercise, was recently identified as a neuroprotective factor in mouse models of Alzheimer disease (AD). In a cohort of AD patients, we studied cerebrospinal fluid (CSF) and plasma irisin levels, sex interactions, and correlations with disease biomarkers. Correlations between CSF and plasma irisin levels and AD biomarkers (amyloid β 1-42, hyperphosphorylated tau, and total tau [t-tau]) and Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB) were analyzed in a cohort of patients with Alzheimer dementia (n = 82), mild cognitive impairment (n = 44), and subjective memory complaint (n = 20) biologically characterized according to the recent amyloid/tau/neurodegeneration classification. CSF irisin was reduced in Alzheimer dementia patients (p < 0.0001), with lower levels in female patients. Moreover, CSF irisin correlated positively with Aβ42 in both female (r = 0.379, p < 0.001) and male (r = 0.262, p < 0.05) patients, and negatively with CDR-SOB (r = -0.234, p < 0.05) only in female patients. A negative trend was also observed between CSF irisin and t-tau levels in all patients (r = -0.144, p = 0.082) and in the female subgroup (r = -0.189, p = 0.084). The results highlight the relationship between irisin and biomarkers of AD pathology, especially in females. Our findings also offer perspectives toward the use of irisin as a marker of the AD continuum. ANN NEUROL 2024;96:61-73.

Seeing beyond the symptoms: biomarkers and brain regions linked to cognitive decline in Alzheimer's disease.

Early Alzheimer's disease (AD) diagnosis remains challenging, necessitating specific biomarkers for timely detection. This study aimed to identify such biomarkers and explore their associations with cognitive decline. A cohort of 1759 individuals across cognitive aging stages, including healthy controls (HC), mild cognitive impairment (MCI), and AD, was examined. Utilizing nine biomarkers from structural MRI (sMRI), diffusion tensor imaging (DTI), and positron emission tomography (PET), predictions were made for Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale Sum of Boxes (CDRSB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS). Biomarkers included four sMRI (e.g., average thickness [ATH]), four DTI (e.g., mean diffusivity [MD]), and one PET Amyloid-β (Aβ) measure. Ensemble regression tree (ERT) technique with bagging and random forest approaches were applied in four groups (HC/MCI, HC/AD, MCI/AD, and HC/MCI/AD). Aβ emerged as a robust predictor of cognitive scores, particularly in late-stage AD. Volumetric measures, notably ATH, consistently correlated with cognitive scores across early and late disease stages. Additionally, ADAS demonstrated links to various neuroimaging biomarkers in all subject groups, highlighting its efficacy in monitoring brain changes throughout disease progression. ERT identified key brain regions associated with cognitive scores, such as the right transverse temporal region for Aβ, left and right entorhinal cortex, left inferior temporal gyrus, and left middle temporal gyrus for ATH, and the left uncinate fasciculus for MD. This study underscores the importance of an interdisciplinary approach in understanding AD mechanisms, offering potential contributions to early biomarker development.

Lecanemab Questions.

The recently published results of the 18-month randomized controlled trial of lecanemab, reporting the efficacy of the drug in slowing the progression of early Alzheimer disease, quickly led to approval by the FDA and widespread acceptance of lecanemab treatment. However, there are a number of matters that deserve further consideration. The success of blinding was not assessed, even as infusion reactions and the cerebral pathology underlying amyloid-related imaging abnormalities could have signaled to many participants that they were on drug, potentially exerting a potent placebo effect. The value of the outcome to participants is not defined in the absolute terms necessary for clinical decision-making, and the difference attributable to lecanemab was between 18% and 46% of estimates of the minimal clinically important difference on the Clinical Dementia Rating Scale Sum of Boxes. The attenuation of change on the Alzheimer's Disease Assessment Scale-Cognitive 14 achieved by lecanemab at 18 months was 50% of that achieved by donepezil at 6 months. Lecanemab treatment imposes a high treatment burden. The fact that the burden commences at the initiation of lecanemab treatment, whereas the benefit accrues years later requires us to take into account value discounting over time, which would significantly reduce the benefit/burden ratio. Finally, treatment with monoclonal antibodies to cerebral amyloid has consistently been associated with progressive cerebral atrophy. At the least, these issues should be raised in treatment discussions with patients. They also suggest a need to very seriously reconsider how we evaluate clinical trial results preparatory to translating them into clinical practice. Some suggestions are provided.

Juxtaventricular and periventricular white matter hyperintensities (WMH) are associated with cognitive dysfunction in Patients with Alzheimer’s Disease

Introduction White matter hyperintensities (WMH) is common among the elderly. WMH are associated with accelerated cognitive dysfunction and increased risk for Alzheimer`s disease (AD). Although WMHs play a key role in lowering the threshold for the clinical expression of dementia in AD-related pathology, the clinical significance of their location is not fully understood.Objectives The aim of this study was twofold: 1) To investigate the quantitative association between WMH and cognitive function in AD; 2) To investigate whether there is any difference in the association between subclassified WMH and cognitive function in AD.MethodsA total of 171 patients with AD underwent clinical evaluations including volumetric brain MRI study and neuropsychological tests using the CERAD-K neuropsychological assessment battery. WMH volume was calculated using automated quantification method with SPM and MATLAB image processing software. According to the distance from the lateral ventricular surface, WMH within 3 mm, WMH within 3-13 mm, and WMH over 13 mm were classified as juxtaventricular WMH (JVWMH), periventricular WMH (PVWMH) and deep WMH (DWMH), respectively. WMH volume data was logarithmically transformed because it was right-skewed.ResultsWMH volume in AD was 20.7 ± 18.2 ml. Total WMH volume was associated with poor performance in categorical verbal fluency test (p = 0.008) and word list memory test (p = 0.023). JVWMH volume was associated with poor performances on categorical verbal fluency test (p = 0.013) and forward digit span test (p = 0.037). PVWMH volume was associated with poor performances on categorical verbal fluency test (p = 0.011) and word list memory test (p = 0.021), whereas DWMH volume showed no association with cognitive tests. Total WMH and PVWMH volume were also related to Clinical Dementia Rating scale sum of boxes score (p=0.022).Image:ConclusionsGreater JVWMH and PVWMH are related with concurrent impairments in semantic memory and frontal function independent of the hippocampal volume. However, DWMH volume is not associated with any cognitive function. Only PVWMH among subclassified WMH are related to the severity of AD.Disclosure of InterestNone Declared

Comparative Efficacy and Safety of Monoclonal Antibodies for Cognitive Decline in Patients with Alzheimer's Disease: A Systematic Review and Network Meta-Analysis.

Recent clinical trials of anti-Aβ monoclonal antibodies (mAbs) in the treatment of early Alzheimer's disease (AD) have produced encouraging cognitive and clinical results. The purpose of this network meta-analysis (NMA) was to compare and rank mAb drugs according to their efficacy and safety. PubMed, Embase, Web of Science, and the Cochrane Library were searched for randomized controlled trials testing various mAbs for the treatment of cognitive decline in patients with AD, up to March 31, 2023. R software (version 4.2.3) along with JAGS and STATA software (version 15.0) were used for statistical analysis. Odds ratio (OR) for binary variables, mean difference (MD) for continuous variables, and their 95% confidence intervals (CI) were utilized to estimate treatment effects and rank probabilities for each mAb in terms of safety and efficacy outcomes. We calculated the surface under the cumulative ranking area (SUCRA) to evaluate each mAb, with higher SUCRA values indicating better efficacy or lower likelihood of adverse events. Thirty-three randomized controlled trials with a total of 21,087 patients were included in the current NMA, involving eight different mAbs. SUCRA values showed that aducanumab (87.01% and 99.37%, respectively) was the most likely to achieve the best therapeutic effect based on the changes of Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale Sum of Boxes (CDR-SB) scores. Donanemab (88.50% and 99.00%, respectively) performed better than other therapies for Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) and Positron Emission Tomography-Standardized Uptake Value ratio (PET-SUVr). Lecanemab (87.24%) may be the most promising way to slow down the decrease of Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) score. In the analysis of the incidence of adverse events (subjects with any treatment-emergent adverse event), gantenerumab (89.12%) had the least potential for adverse events, while lecanemab (0.79%) may cause more adverse events. Solanezumab (95.75% and 80.38%, respectively) had the lowest incidence of amyloid-related imaging abnormalities characterized by edema and effusion (ARIA-E) and by cerebral microhemorrhages (ARIA-H) of the included immunotherapies. While SUCRA values provided a comprehensive measure of treatment efficacy, the inherent statistical uncertainty required careful analysis in clinical application. Despite immunotherapies significantly increasing the risks of adverse events and ARIA, the data suggest that mAbs can effectively improve the cognitive function of patients with mild and moderate AD. According to the NMA, aducanumab was the most likely to achieve significant improvements in different cognitive and clinical assessments (statistically improved MMSE and CDR-SB), followed by donanemab (statistically improved ADAS-Cog, and PET-SUVr) and lecanemab (statistically improved ADCS-ADL).

Progression analysis versus traditional methods to quantify slowing of disease progression in Alzheimer’s disease

BackgroundThe clinical meaningfulness of the effects of recently approved disease-modifying treatments (DMT) in Alzheimer’s disease is under debate. Available evidence is limited to short-term effects on clinical rating scales which may be difficult to interpret and have limited intrinsic meaning to patients. The main value of DMTs accrues over the long term as they are expected to cause a delay or slowing of disease progression. While awaiting such evidence, the translation of short-term effects to time delays or slowing of progression could offer a powerful and readily interpretable representation of clinical outcomes.MethodsWe simulated disease progression trajectories representing two arms, active and placebo, of a hypothetical clinical trial of a DMT. The placebo arm was simulated based on estimated mean trajectories of clinical dementia rating scale–sum of boxes (CDR-SB) recordings from amyloid-positive subjects with mild cognitive impairment (MCI) from Alzheimer’s Disease Neuroimaging Initiative (ADNI). The active arm was simulated to show an average slowing of disease progression versus placebo of 20% at each visit. The treatment effects in the simulated trials were estimated with a progression model for repeated measures (PMRM) and a mixed model for repeated measures (MMRM) for comparison. For PMRM, the treatment effect is expressed in units of time (e.g., days) and for MMRM in units of the outcome (e.g., CDR-SB points). PMRM results were implemented in a health economics Markov model extrapolating disease progression and death over 15 years.ResultsThe PMRM model estimated a 19% delay in disease progression at 18 months and 20% (~ 7 months delay) at 36 months, while the MMRM model estimated a 25% reduction in CDR-SB (~ 0.5 points) at 36 months. The PMRM model had slightly greater power compared to MMRM. The health economic model based on the estimated time delay suggested an increase in life expectancy (10 months) without extending time in severe stages of disease.ConclusionPMRM methods can be used to estimate treatment effects in terms of slowing of progression which translates to time metrics that can be readily interpreted and appreciated as meaningful outcomes for patients, care partners, and health care practitioners.

Effect of altered gene expression in lipid metabolism on cognitive improvement in patients with Alzheimer's dementia following fecal microbiota transplantation: a preliminary study.

The brain-gut axis has emerged as a potential target in neurodegenerative diseases, including dementia, as individuals with dementia exhibit distinct gut microbiota compositions. Fecal microbiota transplantation (FMT), the transfer of fecal solution from a healthy donor to a patient, has shown promise in restoring homeostasis and cognitive enhancement. This study aimed to explore the effects of FMT on specific cognitive performance measures in Alzheimer's dementia (AD) patients and investigate the relationship between cognition and the gut microbiota by evaluating changes in gene expression following FMT. Five AD patients underwent FMT, and their cognitive function [Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB)] was assessed before and after FMT. The patients' fecal samples were analyzed with 16S rRNA to compare the composition of their gut microbiota. We also assessed modifications in the serum mRNA expression of patients' genes related to lipid metabolism using serum RNA sequencing and quantitative real-time polymerase chain reaction. Significant improvements in cognitive function, as measured by the MMSE (pre- and post-FMT was 13.00 and 18.00) and MoCA were seen. The MoCA scores at 3 months post-FMT (21.0) were the highest (12.0). The CDR-SOB scores at pre- and post-FMT were 10.00 and 5.50, respectively. Analysis of the gut microbiome composition revealed changes via 16S rRNA sequencing with an increase in Bacteroidaceae and a decrease in Enterococcaceae. Gene expression analysis identified alterations in lipid metabolism-related genes after FMT. These findings suggest a link between alterations in the gut microbiome, gene expression related to lipid metabolism, and cognitive function. The study highlights the importance of gut microbiota in cognitive function and provides insights into potential biomarkers for cognitive decline progression. FMT could complement existing therapies and show potential as a therapeutic intervention to mitigate cognitive decline in AD.

The HOPE4MCI study: A randomized double-blind assessment of AGB101 for the treatment of MCI due to AD.

In addition to the accumulation of amyloid plaques and neurofibrillary tangles, the presence of excess neural activity is a pathological hallmark of Alzheimer's disease (AD) and a prognostic indicator for progression of AD pathology and clinical/cognitive worsening in mild cognitive impairment due to Alzheimer's disease (MCI due to AD). The HOPE4MCI clinical study tested the efficacy of a therapeutic with demonstrated ability to normalize heightened neural activity in the hippocampus in a randomized controlled trial of 78 weeks duration in patients with MCI due to AD. One hundred and sixty-four participants were randomized to placebo (n = 83) or AGB101 (n = 81), an extended-release formulation of low dose (220mg) levetiracetam. The primary endpoint was the change in Clinical Dementia Rating Scale Sum of Boxes score (CDR-SB) comparing follow up at 18 months to baseline. The goal of the primary efficacy analysis was to estimate the difference between the AGB101 and placebo arms in the mean change of the primary endpoint. The mean change in CDR-SB was estimated to be 1.12 (95% confidence interval [CI]: 0.66, 1.69) for the AGB101 arm and 1.22 (95% CI: 0.75, 1.78) for the placebo arm. The estimated difference between arms is -0.10 (95% CI: -0.85, 0.58), which was not statistically significant. In a prespecified analysis, the difference was -0.45 (95% CI: -1.43, 0.53) for ApoE-4 noncarriers and -0.10 (95% CI: -0.92, 0.72) for apolipoprotein E (ApoE)-4 carriers. The possibility that ApoE-4 carriers and noncarriers will respond differently to therapeutic intervention is consistent with recently reported findings from biologics and the present results show further testing of AGB101 in patients with MCI due to AD who are noncarriers of the ApoeE-4 allele is warranted. Conclusions from the HOPE4MCI study are limited primarily due to the small sample size and results can only be regarded as a guide to future research.

Effect of Dietary Habits on Alzheimer's Disease Progression.

Research on the relationship between diet and dementia among Koreans are lacking. This study investigated the association between dietary habits and dementia progression over 3 years in patients with Alzheimer's disease dementia (ADD). This study included 705 patients with mild-to-moderate ADD. Dietary habits were assessed using the Mini Dietary Assessment Index, comprising 10 questions. Outcome measures included the Clinical Dementia Rating scale-Sum of Boxes (CDR-SB), Seoul-Instrumental Activities of Daily Living, Caregiver-Administered Neuropsychiatric Inventory (CGA-NPI), and neuropsychological test battery (NTB) z-scores, which were evaluated annually over 3 years. In Q10 (eat all food evenly without being picky), the 3-year mean differences in CDR-SB (increases in scores represent worsening) compared to the "rarely" group were -1.86 [95% confidence interval (CI)=-3.64 - -0.09, p=0.039] for the "usually" group and -2.23 (95% CI=-4.40 - -0.06, p=0.044) for the "always" group. In Q7 (add salt or soy sauce to food when eating), the 3-year mean differences in CDR-SB compared to the "always" group were -2.47 (95% CI=-4.70 - -0.24, p=0.030) for the "usually" group and -3.16 (95% CI=-5.36 - -0.96, p=0.005) for the "rarely" group. The "rarely" and "usually" groups in Q7 showed significantly less decline in NTB z-score and CGA-NPI compared to the "always" group. Eating a balanced diet and reducing salt intake were associated with a slower decline in dementia severity, cognition, and behavioral alterations in patients with ADD.

MACHINE-LEARNING-BASED INTERPRETABLE PREDICTION FOR MILD COGNITIVE IMPAIRMENT: FROM ADNI DATABASE

Abstract Objective An accurate prediction model was still lacking for mild cognitive impairment (MCI). Therefore, this study aimed to predict the 3- and 5-year MCI risk utilizing interpretable machine learning, and to identify possible biomarkers for intervention. Methods A total of 444 participants were obtained from the ADNI database. Sociodemographic, neuropsychological, ApoE gene, and structural MRI imaging information was used as predictors. Data was randomly divided into training (70%) and test sets (30%). Six machine learning methods were constructed to predict the risk of MCI. Model performance was assessed by area under the ROC curve (AUC). SHapley Additive exPlanations (SHAP) was used to select important predictors. We also constructed a simplified MCI prediction model for clinical practice. Results The mean age (standard deviation) of study population was 73.7 (6.1) years old. A total of 40, and 60 participants progressed into MCI within 3, and 5 years, respectively. Logistic regression (AUC: 0.97) and support vector machine (AUC: 0.93) are the optimal model for 3- and 5-year prediction. The simplified models based on top three neuropsychological test scores also showed high prediction accuracy (AUC &amp;gt; 0.90). APOE gene, intracranial volume, and Clinical Dementia Rating Scale Sum of Boxes (CDRSB) score were top three predictors for 3-year prediction, while CDRSB score, modified Preclinical Alzheimer’s Cognitive Composite Test with Follow-up Test scale (mPACCtrailsB) score, and Functional Activity Questionnaire (FAQ) score were top three predictors for 5-year prediction. Conclusion Interpretable machine learning showed promise in early identification of MCI, and would be valuable for targeted prevention.

Effects of structural and social determinants of health and comorbidities on ethno‐racial differences in ATN plasma biomarkers of Alzheimer’s disease: A HABS‐HD study

AbstractBackgroundEthno‐racial differences are observed in amyloid (A), tau (T), and neurodegeneration (N) plasma biomarkers of Alzheimer’s disease (AD). In neuroimaging studies, structural and social determinant of health (SSDOH) factors and associated health outcomes may mediate observed racial differences in neurodegeneration markers. However, little is known regarding the potential effects of SSDOH and downstream comorbidities on ethno‐racial differences in AT(N) plasma biomarkers. This study A) assessed potential differences in plasma Aβ42, Aβ40, Aβ42/40, t‐tau, and NfL among Mexican Americans (MA), non‐Hispanic Blacks (NHB), and non‐Hispanic Whites (NHW); B) determined whether SSDOH and comorbidity factors mediate potential ethno‐racial differences in AD plasma biomarkers.MethodData were obtained from the diverse and well‐characterized Health and Aging Brain Study – Health Disparities (HABS‐HD) and included MAs (n = 931), NHBs (n = 258), and NHWs (n = 942). Group differences in AT(N) plasma biomarkers were assessed using analysis of covariance. Age, sex, and cognitive status (Clinical Dementia Rating Scale Sum of Boxes) were included as covariates. Two multiple mediation models were performed with SSDOH (acculturation, chronic stress, income, area deprivation index) and comorbidity factors (body mass index [BMI], blood pressure, diabetes history) as the potential mediators, respectively. Models accounted for age, sex, and cognitive status, assumed nonlinear relationships, and allowed for mediators to be considered simultaneously.ResultPlasma Aβ42 was significantly lower in MAs compared to NHWs (p&lt;0.05). Plasma NfL was significantly higher in MAs compared to NHBs (p&lt;0.01) and for NHWs compared to NHBs (p&lt;0.05). No other significant differences in plasma variables were observed (p’s&gt;0.05). Group differences in plasma Aβ42 were mediated by comorbidity factors (BMI and history of diabetes), but not SSDOH. MAs had greater BMIs and history of diabetes compared to NHWs, both of which were associated with lower plasma Aβ42 levels. SSDOH and comorbidity factors did not mediate group differences in plasma NfL.ConclusionUsing a large and diverse community‐based cohort, we demonstrate that ethno‐racial differences in AD‐specific plasma biomarkers are, in part, due to modifiable health and comorbidity factors. This work informs the conditions that give rise to ethno‐racial differences in plasma ATN biomarkers while highlighting potential ethno‐racial disparities in AD research.