Progression of Clinical Features in Lewy Body Dementia Can Be Detected Over 6 Months

Copyright \ua9 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.OBJECTIVE: This study aimed to quantify the trajectory and magnitude of change of the key clinical features and corresponding symptom domains of dementia with Lewy bodies (DLB) and Parkinson disease dementia (PDD), including global cognition, parkinsonism, recurrent visual hallucinations, cognitive fluctuations, and sleep disturbance. METHODS: One hundred sixteen patients with Lewy body dementia (DLB = 72, PDD = 44) underwent assessment at baseline and 3 and 6 months as part of a prospective multicenter randomized controlled trial. Linear mixed models were constructed for core outcome measures using the Mini-Mental State Examination (MMSE), motor section of the Unified Parkinson\u27s Disease Rating Scale (UPDRS-III), Dementia Cognitive Fluctuations Scale (DCFS), and Neuropsychiatric Inventory (NPI). RESULTS: Within the time frame of our study (6 months), we were able to identify a significant cognitive decline of 1.3 points on the MMSE (p = 0.002) and significant worsening of motor parkinsonism with an increase in UPDRS-III score of 3.2 points (p = 0.018). Fluctuation severity also increased using the DCFS with a 6-month change in score of 1.3 points (p = 0.001). Uniquely, a signal for increased severity of sleep symptoms of 1.2 points (NPI-sleep) was also detectable (p = 0.04). Significant changes in neuropsychiatric symptoms were not detected. There was no difference in rates of change of scores between DLB and PDD. DISCUSSION: Clinically significant rates of change in core clinical features can be detected and quantified in Lewy body dementia over a relatively short period (6 months) using common clinical instruments and thus may be useful as clinical endpoints for therapeutic trials of disease-modifying and symptomatic agents

Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer’s disease: a cross-sectional metabolomic analysis

Copyright \ua9 2024 Pan, Donaghy, Roberts, Chouliaras, O’Brien, Thomas, Heslegrave, Zetterberg, McGuinness, Passmore, Green and Kane.Background: In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis. Methods: A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 \ub1 8.2 years), probable AD (n = 15; 76.1 \ub1 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 \ub1 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data. Results: The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809–0.996; sensitivity = 0.90; specificity = 0.90). Discussion: Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts

Developing a core outcome set (COS) for Dementia with Lewy bodies (DLB) [version 2; peer review: 2 approved, 1 approved with reservations]

\ua9 2023 Grycuk E et al.Background: Dementia with Lewy bodies (DLB) is an important cause of dementia with a range of clinical manifestations, including motor, neuropsychiatric, and autonomic symptoms. Compared with more common forms of dementia such as Alzheimer’s disease, DLB has been the focus of significantly fewer treatment studies, often with diverse outcome measures, making comparison and clinical implementation difficult. A core outcome set (COS) can address this by ensuring that data are comparable, relevant, useful, and usable for making the best healthcare decisions. Methods: Using a multi-stage approach, development of the DLB-COS will include the following stages: (1) A systematic review, following PRISMA guidelines to create an initial long list of outcomes; (2) A two-round online Delphi including clinicians, scientists, policymakers, and individuals with lived experience of DLB and their representatives; (3) An online consensus meeting to agree on the final core list of outcomes (the final DLB-COS) for use in research and clinical practice; (4) A literature search to identify appropriate measurement instruments for the DLB-COS outcomes; (5) A final consensus meeting of the professional stakeholders who attended the online consensus meeting to agree on the instruments that should be used to measure the outcomes in the DLB-COS; and (6) Global dissemination. Discussion: This is a multi-stage project to develop a COS to be used in treatment trials for DLB. A DLB-COS will ensure the selection of relevant outcomes and will identify the instruments to be used to measure DLB globally

Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer’s Disease: A Pragmatic Review for Clinicians

\ua9 The Author(s) 2024.This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer’s disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)—parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners

Clinical diagnosis of Lewy body dementia

This is the final version. Available on open access from Cambridge University Press via the DOI in this recordBackground Lewy body dementia consisting of both dementia with Lewy bodies (DLB) and Parkinson’s disease (PD) dementia (PDD) is considerably under-recognised clinically compared to its frequency in autopsy series. Aims This study investigated the clinical diagnostic pathways of patients with Lewy body dementia to assess if difficulties in diagnosis maybe contributing to these differences. Methods We reviewed the medical notes of 74 DLB and 72 non-DLB dementia cases matched for age, gender and cognitive performance, together with 38 PDD cases and 35 PD cases, matched for age and gender, from two geographically distinct UK regions. Results DLB cases took longer to reach a final diagnosis (1.2v0.6 years, p=0.003), underwent more scans (1.7v1.2, p=0.017) and had more alternative prior diagnoses (0.8v0.4, p=0.002), than non-DLB cases. Cases diagnosed in one region had significantly more core features (2.1v1.5, p=0.007) than in the other and were less likely to have dopamine transporter imaging (p<0.001). For PDD cases, more than 1.4 years prior to receiving a dementia diagnosis, 46% had documented impaired activities of daily living due to cognitive impairment, 57% had cognitive impairment in multiple domains, with 38% having both, and 39% already receiving anti-dementia drugs. 3 Conclusions Our results show the pathway to diagnosis of DLB is longer and more complex than nonDLB dementia. There were also marked differences between regions in the thresholds clinicians adopt for diagnosing DLB and also in the use of dopamine transporter imaging. Whilst for PDD, a diagnosis of dementia was delayed well beyond symptom onset and even treatment.National Institute for Health Research (NIHR

123I-MIBG scintigraphy utility and cut-off value in a clinically representative dementia cohort.

OBJECTIVE: To determine the utility of 123I-metaiodobenzylguanidine cardiac scintigraphy (MIBG), and optimum heart: mediastinum ratio (HMR) for differentiating dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) in a clinically representative population, comparing findings with those of 123I-2β -carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane (FP-CIT) SPECT. METHODS: We recruited subjects with probable DLB (n = 17) and probable AD (n = 16) from clinical services. Each participant underwent clinical examination, cardiac MIBG scintigraphy and FP-CIT SPECT. Diagnosis was made on the basis of clinical symptoms using validated criteria. Cardiac MIBG uptake was measured by the planar HMR, blind to clinical diagnosis, with values below a cut-off taken from a previous study (<2.2 at four hours) defining scans as abnormal. FP-CIT scans were blindly rated according to a visual rating scale. RESULTS: MIBG had a sensitivity, specificity and overall accuracy of 71%, 81% and 76% for distinguishing DLB from AD. FP-CIT demonstrated a sensitivity, specificity and accuracy of 82%, 88% and 85%. Using a lower HMR cut-off to distinguish between abnormal and normal MIBG scans improved the accuracy of MIBG, raising specificity (100%) and overall accuracy (85%) without compromising sensitivity (71%). Neither prescription of potentially interfering medications, nor a history of myocardial infarction (MI), had a significant effect on HMR. CONCLUSION: We found that MIBG did not demonstrate superior sensitivity and overall accuracy to FP-CIT. HMR cut-off influences biomarker utility, and clinical and Caucasian populations may require a lower cut-off than those reported elsewhere. Future MIBG studies should include clinically representative cohorts as neither medications nor previous MI appear to influence HMR