Artificial intelligence and omics-based autoantibody profiling in dementia.

The cognitive evolution of early dementia with Lewy bodies (DLB) is less well known than that of Alzheimer's disease (AD). During dementia, DLB progresses like AD. The aim of this study was to analyze the long-term cognitive decline of early DLB. Participants were recruited for either mild cognitive impairment or mild dementia with a suspicion of DLB or AD, or as healthy older subjects (AlphaLewyMA study, NCT01876459, 2013). Using beta regression, we compared the slope of the Mini-Mental State Examination (MMSE) score of 110 DLB patients (DLB group), 57 AD patients (AD group), 19 DLB and AD patients (DLB + AD group), 30 patients with other cognitive diseases (DC group), and 31 healthy older controls (HC group). The mean follow-up was 4.8 years. All patients' groups had a significant decrease in MMSE score. The slope of MMSE decline of the DLB group (-0.49 point a year) was higher than the HC group (+ 0.03; P < .0001), lower than that of the AD (-2.78; P < .0001) and DLB + AD (-2.92; P < .0001) groups and not different from the DC group (-0.29; P = .8000). The variability of annual variations in MMSE score was greater in the DLB group (2.13 points) than in the AD group (1.73 points). There was no difference between patients' group in terms of death or admission to a nursing home. Patients with early DLB decline cognitively more slowly while fluctuating, whereas AD and DLB + AD patients decline markedly. These results suggest that there is a more dysfunctional than neurodegenerative phase at the beginning of DLB.

BackgroundGlial fibrillary acidic protein (GFAP) is a novel Alzheimer’s Disease (AD) biomarker that associates with amyloid pathology and pathology‐related changes can be detected in different biofluids. We studied how the performance of GFAP to distinguish between controls, AD and dementia with Lewy bodies (DLB), depends on the studied biofluid (cerebrospinal fluid (CSF), serum or plasma) and the confounding effects of age or sex.MethodFrom the Amsterdam Dementia Cohort and a local repository of healthy controls we included 372 cognitively normal individuals (CN), 255 patients with AD and 120 patients with DLB (Table 1) and GFAP levels were measured in one (n=322), two (n=416) or three (n=9) biofluids. GFAP was measured using Simoa in CSF (n=473), plasma (n=257) and serum (n=451) samples. For individuals with DLB, GFAP was measured in CSF and serum only. Effects of clinical diagnosis, age and sex on GFAP levels in each body fluid were estimated with linear models. Estimated differences between diagnostic groups were corrected for age and sex, age effects were corrected for sex and diagnostic group, and sex effects were corrected for age and diagnostic group.ResultGFAP levels were increased in AD relative to controls in all biofluids (fold change (FC): 1.6(CSF), 1.9(plasma) and 1.4(serum), p‐values&lt;0.001) and increased in AD relative to DLB (FC: 1.7(CSF) and 1.3(serum), p‐values&lt;0.001, Figure 1). No difference was found between DLB and controls. CSF GFAP levels increased with age in all clinical groups (range of standard deviation protein level increase per year (SD/year): 0.020‐0.024), while plasma GFAP levels increased with age only in CN (SD/year: 0.032). Serum GFAP levels increased with age in CN and DLB (SD/year: 0.058(CN) and 0.074(DLB), Figure 2). CSF GFAP showed sex effects in AD only (FC in males compared to females: 1.1), whereas serum GFAP showed sex effects in all clinical groups (FC in males: 0.83(AD), 0.85(NC) and 0.72(DLB)), and plasma GFAP showed no sex effects (Figure 3A‐C).ConclusionDifferences in GFAP levels between clinical diagnoses showed the same trend for all three matrices. With older age, differences in GFAP levels between controls and AD become harder to detect.

Several reports suggest a higher morbidity of depression in patients with dementia with Lewy bodies (DLB) than in patients with Alzheimer's disease (AD). However, these results have not been duplicated consistently. The psychiatric symptoms of dementia, including depression, are important for its diagnosis and management. Thus, the aim of the present study was to clarify the characteristics of the depressive symptoms in DLB compared with AD using the Geriatric Depression Scale (GDS). We examined the GDS score for 86 patients with probable DLB (based on the Consensus Criteria for the clinical diagnosis of DLB) and 86 patients with probable AD (based on criteria of the National Institute for Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association), who were matched according to age, sex, education, and Mini-Mental State Examination (MMSE) scores. We also examined correlations between GDS scores and age, sex, or MMSE scores in both groups. Correlations between GDS scores and metaiodobenzylguanidine (MIBG) scintigraphy were examined in patients with DLB. To characterize the GDS in DLB, its profile was examined using factor structures. Scores for DLB patients were twice as high on the GDS as those for AD patients. There was no correlation between GDS score and age, sex, or MMSE scores in either group. Furthermore, there was no correlation between the results of MIBG scintigraphy and GDS scores in the DLB group. Using factor structures, the depression symptom profile of these diseases suggested that depression-specific symptoms, such as mood, worry, or future outlook, were more frequent in the DLB group than non-specific symptoms, such as lack of energy, decreased concentration, or apathy. The data suggest that depressive symptoms are highly specific symptoms of DLB, independent of other features of this disorder. The GDS could be used as a subsidiary tool in differentiating DLB from AD and is more useful than clinical observations of depression.

The challenges of COVID-19 for people with dementia with Lewy bodies and family caregivers.

BackgroundPredicting brain age from neuroimaging data is an emerging field. The age gap (AG), the difference between chronological age (CA) and brain age (BA), is crucial for indicating individual neuroanatomical aging. Previous deep learning models faced challenges in generalizability and neuroanatomical interpretability. We incorporated patients with different dementia types, including dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), alongside mild cognitive impairment (MCI) and cognitive normal (CN) individuals. This inclusive strategy is essential for comprehensive mapping of neurocognitive trajectories and understanding distinct aging patterns across various cognitive conditions.MethodUtilizing T1‐weighted MRI images of n = 3,859 subjects (Table 1) from the CamCAN, NACC, and ADNI databases, this study aimed to predict brain age in four groups (CN, MCI, AD, and DLB). Structural MRI data were spatial normalized and skull‐striped. Then a 3D Convolutional Neural Network (CNN) based on the skull‐striped data was used for age prediction. The model’s architecture includes three convolutional layers with ReLU activation, max‐pooling, batch normalization, and dropout for regularization, ending with global average pooling and dense layers. The model was trained and validated on CN subjects. The trained model was used to predict age in MCI, DLB, and AD patients as well as the test set of CN subjects.ResultThe 3D CNN model accurately predicted brain age in the CN test set with an AG of 0.64 ± 2.74 years and an absolute AG of 1.86 ± 2.11 years (Figure 1 and Table 1). In DLB and AD patients, the average AG was 3.81 and 2.90 years, respectively, and significantly larger than 0 (P &lt; 10‐5), indicating accelerated aging patterns in these groups. The average AG of MCI was 0.09 years which was significantly smaller than that of both DLB and AD (P &lt; 10‐3), indicating the early stage of impairment in MCI patients.ConclusionOur 3D CNN model accurately predicted brain age in cognitively normal individuals and identified accelerated aging in DLB and AD patients. The model's precision highlights its potential for early detection and understanding of neurocognitive trajectories, contributing to advancements in neurological research and clinical diagnostics.

Accepted September 14, 1998. From the Neuropharmacology Unit, Defense and Veterans Head Injury Program, Henry M. Jackson Foundation, and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland; Veterans Administration Medical Center GRECC, Bedford, Massachusetts; and Departments of Neurology and Pathology, Boston University Medical School, Boston, Massachusetts. Address correspondence to Dr. Litvan, Neuropharmacology Unit, Defense and Veterans Head Injury Program, Henry M. Jackson Foundation, NINDS, NIH, Federal Building, Room 714, 7550 Wisconsin Avenue, Bethesda, MD 20892-9130; e-mail: litvan1@helix.nih.gov Copyright q 1999 American Psychiatric Press, Inc. Clinicopathologic Case Report

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) are common forms of dementia, characterized by overlapping clinical symptoms. Functional neuroimaging can provide valuable information for precise diagnosis. Our objective was to explore cerebral perfusion alterations in DLB and AD, and to determine which perfusion parameters are helpful in distinguishing DLB and AD. A total of 25 DLB patients, 34 AD patients, and 40 normal controls (NC) underwent neuropsychological testing and pseudo-continuous arterial spin labeling (pcASL) for assessing cerebral perfusion [mean cerebral flow (mCBF); arterial transit time (ATT)] indexes. Differences in perfusion indexes among the three groups were analyzed and the family-wise error (FWE) was used for multiple comparisons. Spearman analysis assessed the relationships between the mCBF and neuropsychological scores [mini-mental state examination (MMSE); Montreal Cognitive Assessment (MoCA)]. A receiver operating characteristic (ROC) analysis was conducted to evaluate the performance and discriminant value of different perfusion indices in distinguishing between the two diseases. Compared with NC, the mCBF of patients with DLB was reduced mainly in the bilateral frontal lobe, bilateral parietal lobes, bilateral temporal lobes, and the right occipital lobe. AD patients showed lower mCBF mainly in the bilateral frontal lobes, the right temporal lobe, and the left parietal lobe. Compared with AD, DLB patients showed decreased mCBF in the bilateral frontal and parietal lobes. ATT in almost all major arterial regions was prolonged in DLB and AD when compared to NC. Compared with AD, ATT was significantly prolonged in DLB (P<0.05). Furthermore, the DLB demonstrated a significant positive correlation between mCBF and MMSE scores, particularly in regions such as the left superior parietal lobule (r=0.596, P=0.002) and the right precuneus (r=0.498, P=0.01). Similarly, AD exhibits a positive correlation between mCBF and MMSE scores within regions, such as the right middle temporal gyrus (r=0.550, P=0.001) and the left inferior parietal lobule (r=0.571, P<0.001). The perfusion indexes could help distinguish DLB from AD. DLB demonstrates a different pattern of regional blood flow reduction and prolonged ATT, which is different from that in AD. ASL-derived parameters provide critical discriminative information for differentiating DLB and AD.

Objective: Dementia with Lewy bodies (DLB) is the second commonest form of dementia. The response to acetylcholinesterase inhibition (AChEI) could be greater in DLB than in Alzheimer’s disease (AD) because cholineacetyl-transferase levels are more reduced in the former. This preliminary trial seeks to compare performances in cognitive tasks before and after tacrine administration in DLB and AD subjects. Methods: Six DLB and 6 AD patients were enrolled in an open, nonrandomized, intervention trial using 80 mg/day tacrine. Patients met ADRDA or DLB consortium criteria for probable diseases. Subjects were matched for Mini Mental State Examination (MMSE) score, age and sex. Mattis Dementia Rating Scale (DRS), Controlled Oral Word Association Test (FAS) and Boston Naming tests were administered at baseline and at 6 months into treatment. Results: AD and DLB groups did not differ in initial mean total DRS scores. In the primary analysis, both groups declined during the course of treatment (–7.3 ± 4.2 and –16.8 ± 39.2 DRS points, respectively). Due to the large variability in DLB posttreatment scores, this group was divided post hoc into responders (DLBr) and nonresponders (DLBnr). The DLBr group outperformed the DLBnr group at baseline (p < 0.05) and, notably, in follow-up DRS test scores (p < 0.001). Two-way MANOVA comparing both DLB subgroups with either the entire AD cohort or similarly stratified AD subgroups showed a significant interaction (F = 7.6; p < 0.015), attributed mostly to declines in DLBnr group scores (p < 0.01). Surprisingly, on DRS memory subscale and FAS tests, there were significant improvements in DLBr scores (p < 0.02). A baseline MMSE (or DRS memory) score ≥15 predicted a positive response to tacrine in DLB. Acceleration of parkinsonism occurred in all DLB subjects. Conclusion: Results from a primary analysis of the therapeutic effect of 80 mg/day tacrine in DLB and AD were negative. However, post hoc analysis showed that mild to moderate DLB responds favorably to AChEI relative to AD through stabilization of global cognitive decline and improvements in specific cognitive areas. These results could be useful in the planning of a more definitive study.

The Role of NAC in Amyloidogenesis in Alzheimer's Disease

OBJECTIVESIn many cases the clinical differentiation of patients with dementia with Lewy bodies (DLB) from those with Alzheimer's disease (AD) has been difficult. Because many neuropsychological studies have reported greater...

Background:Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) are often misdiagnosed with each other because of similar symptoms including progressive memory loss. The metabolic network topology that describes inter-regional metabolic connections can be generated using fluorodeoxyglucose positron emission tomography (FDG-PET) data with the graph-theoretical method. We hypothesized that different metabolic connectivity underlies the symptoms of AD patients, DLB patients, and cognitively normal (CN) individuals.Objective:This study aimed to generate metabolic connectivity using FDG-PET data and assess the network topology to differentiate AD patients, DLB patients, and CN individuals.Methods:This study included 45 AD patients, 18 DLB patients, and 142 CN controls. We analyzed FDG-PET data using the graph-theoretical method and generated the network topology in AD patients, DLB patients, and CN individuals. We statistically assessed the topology with global and nodal parameters.Results:The whole metabolic network was preserved in CN; however, diffusely decreased connection was found in AD and partially but more deeply decreased connection was observed in DLB. The metabolic topology revealed that the right posterior cingulate and the left transverse temporal gyrus were significantly different between AD and DLB.Conclusion:The present findings indicate that metabolic connectivity decreased in both AD and DLB, compared with CN. DLB was characterized restricted but deeper stereotyped network disruption compared with AD. The right posterior cingulate and the left transverse temporal gyrus are significant regions in the metabolic connectivity for differentiating AD from DLB.

Haloperidol in the Treatment of Agitation and Psychosis of Lewy Body Dementia after Failure of Second Generation Antipsychotic: Case Report and Literature Review

The aim of this study was to describe the rate and clinical predictors of cognitive decline in dementia with Lewy bodies (DLB), and compare the findings with Alzheimer's disease (AD) and Parkinson's disease dementia (PDD) patients. Longitudinal scores for the Mini-Mental State Examination (MMSE) in 1,290 patients (835 DLB, 198 PDD, and 257 AD) were available from 18 centers with up to three years longitudinal data. Linear mixed effects analyses with appropriate covariates were used to model MMSE decline over time. Several subgroup analyses were performed, defined by anti-dementia medication use, baseline MMSE score, and DLB core features. The mean annual decline in MMSE score was 2.1 points in DLB, compared to 1.6 in AD (p = 0.07 compared to DLB) and 1.8 in PDD (p = 0.19). Rates of decline were significantly higher in DLB compared to AD and PDD when baseline MMSE score was included as a covariate, and when only those DLB patients with an abnormal dopamine transporter SPECT scan were included. Decline was not predicted by sex, baseline MMSE score, or presence of specific DLB core features. The average annual decline in MMSE score in DLB is approximately two points. Although in the overall analyses there were no differences in the rate of decline between the three neurodegenerative disorders, there were indications of a more rapid decline in DLB than in AD and PDD. Further studies are needed to understand the predictors and mechanisms of cognitive decline in DLB.

More than half of neurodegenerative disease patients have multiple pathologies at autopsy; however, most receive one diagnosis during life. We used the α-synuclein seed amplification assay (αSyn-SAA) and CSF biomarkers for amyloidosis and Alzheimer's disease (AD) neuropathological change (ADNC) to determine the frequency of co-pathologies in participants clinically diagnosed with Lewy body (LB) disease or AD. Using receiver operating characteristic analyses on retrospective CSF samples from 150 participants determined αSyn-SAA accuracy, sensitivity, and specificity for identifying clinically defined LB disease and predicting future change in clinical diagnosis. CSF biomarkers helped determine the frequency of concomitant Lewy body pathology, ADNC, and/or amyloidosis in participants with LB disease and AD, across clinical spectra. Following a decade-long follow-up, the clinically or autopsy-defined diagnosis changed for nine participants. αSyn-SAA demonstrated improved accuracy (91.3%), sensitivity (89.3%), and specificity (93.3%) for identifying LB disease compared to all non-LB disease, highlighting the limitations of clinical diagnosis alone. When examining biomarkers of co-pathology, amyloidosis was present in 18%, 48%, and 71% (χ2(2) = 13.56, p = 0.001) and AD biomarkers were present in 0%, 8.7%, and 42.9% (χ2(2) = 18.44, p < 0.001) of LB disease participants with different stages of cognitive impairment respectively. Co-occurring biomarkers for αSyn-SAA and amyloidosis were present in 12% and 14% of AD compared to 43% and 57% LB disease participants with different stages of cognitive impairment (χ2(3) = 13.87, p = 0.003). Our study shows that using a combination of αSyn-SAA and AD biomarkers can identify people with αSyn, ADNC, and co-pathology better and earlier than traditional clinical diagnostic criteria alone.

Lewy body dementia and Alzheimer's disease (AD) are leading causes of cognitive impairment, characterized by distinct but overlapping neuropathological hallmarks. Lewy body disease (LBD) is characterized by α-synuclein aggregates in the form of Lewy bodies as well as the deposition of extracellular amyloid plaques, with many cases also exhibiting neurofibrillary tangle (NFT) pathology. In contrast, AD is characterized by amyloid plaques and neurofibrillary tangles. Both conditions often co-occur with additional neuropathological changes, such as vascular disease and TDP-43 pathology. To elucidate shared and distinct molecular signatures underlying these mixed neuropathologies, we extensively analysed transcriptional changes in the anterior cingulate cortex, a brain region critically involved in cognitive processes. We performed bulk tissue RNA sequencing from the anterior cingulate cortex and determined differentially expressed genes (q-value <0.05) in control (n = 81), LBD (n = 436), AD (n = 53) and pathological amyloid cases consisting of amyloid pathology with minimal or no tau pathology (n = 39). We used gene set enrichment and weighted gene correlation network analysis to understand the pathways associated with each neuropathologically defined group. LBD cases had strong upregulation of inflammatory pathways and downregulation of metabolic pathways. The LBD cases were further subdivided into either high Thal amyloid, Braak NFT, or low pathological burden cohorts. Compared to the control cases, the LBD cohorts consistently showed upregulation for genes involved in protein folding and cytokine immune response, as well as downregulation of fatty acid metabolism. Surprisingly, concomitant tau pathology within the LBD cases resulted in no additional changes. Some core inflammatory pathways were shared between AD and LBD but with numerous disease-specific changes. Direct comparison of LBD cohorts versus AD cases revealed strong enrichment of synaptic signalling, behaviour and neuronal system pathways. Females had a stronger response overall in both LBD and AD, with several sex-specific changes. Overall, the results identify genes commonly and uniquely dysregulated in neuropathologically defined LBD and AD cases, shedding light on shared and distinct molecular pathways. Additionally, the study underscores the importance of considering sex-specific changes in understanding the complex transcriptional landscape of these neurodegenerative diseases.