110 research outputs found
Associations between multimorbidity and neuropathology in dementia: Consideration of functional cognitive disorders, psychiatric illness and dementia mimics
\ua9 The Author(s), 2024. Published by Cambridge University Press on behalf of Royal College of Psychiatrists.Background Multimorbidity, the presence of two or more health conditions, has been identified as a possible risk factor for clinical dementia. It is unclear whether this is due to worsening brain health and underlying neuropathology, or other factors. In some cases, conditions may reflect the same disease process as dementia (e.g. Parkinson\u27s disease, vascular disease), in others, conditions may reflect a prodromal stage of dementia (e.g. depression, anxiety and psychosis). Aims To assess whether multimorbidity in later life was associated with more severe dementia-related neuropathology at autopsy. Method We examined ante-mortem and autopsy data from 767 brain tissue donors from the UK, identifying physical multimorbidity in later life and specific brain-related conditions. We assessed associations between these purported risk factors and dementia-related neuropathological changes at autopsy (Alzheimer\u27s-disease related neuropathology, Lewy body pathology, cerebrovascular disease and limbic-predominant age-related TDP-43 encephalopathy) with logistic models. Results Physical multimorbidity was not associated with greater dementia-related neuropathological changes. In the presence of physical multimorbidity, clinical dementia was less likely to be associated with Alzheimer\u27s disease pathology. Conversely, conditions which may be clinical or prodromal manifestations of dementia-related neuropathology (Parkinson\u27s disease, cerebrovascular disease, depression and other psychiatric conditions) were associated with dementia and neuropathological changes. Conclusions Physical multimorbidity alone is not associated with greater dementia-related neuropathological change; inappropriate inclusion of brain-related conditions in multimorbidity measures and misdiagnosis of neurodegenerative dementia may better explain increased rates of clinical dementia in multimorbidit
EEG Functional Connectivity Differences Predict Future Conversion to Dementia in Mild Cognitive Impairment With Lewy Body or Alzheimer Disease
Sustained attention in mild cognitive impairment with Lewy bodies and Alzheimer\u27s disease
\ua9 The Author(s), 2023. Published by Cambridge University Press on behalf of International Neuropsychological Society. Objective: Attentional impairments are common in dementia with Lewy bodies and its prodromal stage of mild cognitive impairment (MCI) with Lewy bodies (MCI-LB). People with MCI may be capable of compensating for subtle attentional deficits in most circumstances, and so these may present as occasional lapses of attention. We aimed to assess the utility of a continuous performance task (CPT), which requires sustained attention for several minutes, for measuring attentional performance in MCI-LB in comparison to Alzheimer\u27s disease (MCI-AD), and any performance deficits which emerged with sustained effort. Method: We included longitudinal data on a CPT sustained attention task for 89 participants with MCI-LB or MCI-AD and 31 healthy controls, estimating ex-Gaussian response time parameters, omission and commission errors. Performance trajectories were estimated both cross-sectionally (intra-task progress from start to end) and longitudinally (change in performance over years). Results: While response times in successful trials were broadly similar, with slight slowing associated with clinical parkinsonism, those with MCI-LB made considerably more errors. Omission errors were more common throughout the task in MCI-LB than MCI-AD (OR 2.3, 95% CI: 1.1-4.7), while commission errors became more common after several minutes of sustained attention. Within MCI-LB, omission errors were more common in those with clinical parkinsonism (OR 1.9, 95% CI: 1.3-2.9) or cognitive fluctuations (OR 4.3, 95% CI: 2.2-8.8). Conclusions: Sustained attention deficits in MCI-LB may emerge in the form of attentional lapses leading to omissions, and a breakdown in inhibitory control leading to commission errors
Longitudinal changes in cardiac mIBG scintigraphy in mild cognitive impairment with Lewy bodies
The aim of this study was to determine whether there was a significant change in cardiac [123I]-metaiodobenzylguanidine uptake between baseline and follow-up in individuals with mild cognitive impairment with Lewy bodies (MCI-LB) who had normal baseline scans. Eight participants with a diagnosis of probable MCI-LB and a normal baseline scan consented to a follow-up scan between 2 and 4 years after baseline. All eight repeat scans remained normal; however, in three cases uptake decreased by more than 10%. The mean change in uptake between baseline and repeat was −5.2% (range: −23.8% to +7.0%). The interpolated mean annual change in uptake was −1.6%
Patterns of tau, amyloid and synuclein pathology in ageing, Alzheimer\u27s disease and synucleinopathies
Alzheimer\u27s disease (AD) is neuropathologically defined by deposits of misfolded hyperphosphorylated tau (HP-tau) and β-amyloid. Lewy body (LB) dementia, which includes dementia with Lewy bodies (DLB) and Parkinson\u27s disease dementia (PDD), is characterised pathologically by α-synuclein aggregates. HP-tau and β-amyloid can also occur as copathologies in LB dementia, and a diagnosis mixedAD/DLB can be made if present in sufficient quantities. We hypothesised the spread of these abnormal proteins selectively affects vulnerable areas, resulting in pathologic regional covariance that differentially associates with pre-mortem clinical characteristics. Our aims were to map regional quantitative pathology (HP-tau, β-amyloid, α-synuclein) and investigate the spatial distributions from tissue microarray (TMA) post-mortem samples across healthy aging, AD and LB dementia. The study involved 159 clinico-pathologically diagnosed human post-mortem brains (48 controls, 47 AD, 25 DLB, 20 mixedAD/DLB, 19 PDD). The burden of HP-tau, β-amyloid and α-synuclein was quantitatively assessed in cortical and subcortical areas. Principal components (PC) analysis was applied across all cases to determine the pattern nature of HP-tau, β-amyloid and α-synuclein. Further analyses explored the relationships of these pathological patterns with cognitive and symptom variables. Cortical (tauPC1) and temporolimbic (tauPC2) patterns were observed for HP-tau. For β-amyloid, a cortical-subcortical pattern (amylPC1) was identified. For α-synuclein, four patterns emerged: \u27posterior temporal - occipital (synPC1)\u27, \u27anterior temporal-frontal (synPC2)\u27, \u27parieto-cingulate-insula (synPC3)\u27, and \u27frontostriatal-amygdala (synPC4)\u27. Distinct synPC scores were apparent among DLB, mixedAD/DLB and PDD, and may relate to different spreading patterns of α-synuclein pathology. In dementia, cognitive measures correlated with tauPC1, tauPC2 and amylPC1 pattern scores (P≤0.02), whereas such variables did not relate to α-synuclein parameters in these or combined LB dementia cases. Mediation analysis then revealed that in the presence of amylPC1, tauPC1 had a direct effect on global cognition in dementia (n=65, P=0.04), while tauPC1 mediated the relationship between amylPC1 and cognition through the indirect pathway (amylPC1→ tauPC1 → global cognition) (P<0.05). Lastly, in synucleinopathies, synPC1 and synPC4 pattern scores were associated with visual hallucinations and motor impairment, respectively (P=0.02). In conclusion, distinct patterns of α-synuclein pathology were apparent in LB dementia, which could explain some of the disease heterogeneity and differing spreading patterns among these conditions. Visual hallucinations and motor severity were associated with specific α-synuclein topographies in LB dementia that may be important to the clinical phenotype, and could, after necessary testing/validation, be integrated into semi-quantitative routine pathological assessment
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
Brain network connectivity underlying neuropsychiatric symptoms in prodromal Lewy body dementia.
Neuropsychiatric symptoms (NPS) are prevalent, emerge early, and are associated with poorer outcomes in Lewy body dementia (LBD). Research suggests NPS may reflect LBD-related dysfunction in distributed neuronal networks. This study investigated NPS neural correlates in prodromal LBD using resting-state functional MRI. Fifty-seven participants were included with mild cognitive impairment (MCI) with Lewy bodies (MCILB, n=28) or Parkinson’s disease (PD-MCI, n=29). Functional MRI assessed connectivity within five resting-state networks: primary visual, dorsal attention, salience, limbic, and default mode networks. NPS were measured using the Neuropsychiatric Inventory. Principal component analyses identified three neuropsychiatric factors: affective disorder (apathy, depression), psychosis (delusions, hallucinations) and anxiety. Seed-to-voxel connectivity maps were analysed to determine associations between NPS and network connectivity. In PD-MCI, affective symptoms and anxiety were associated with greater connectivity between limbic orbitofrontal cortex and default mode areas, including medial prefrontal cortex, subgenual cingulate and precuneus, and weaker connectivity between limbic orbitofrontal cortex and the brainstem and between the salience network and medial prefrontal cortex (all pFWE<0.001). Psychosis severity in PD-MCI correlated with connectivity across multiple networks (all pFWE<0.001). In MCI-LB, no significant correlations were found between NPS severity and network connectivity. However, participants with anxiety demonstrated a trend towards greater connectivity within medial prefrontal areas than those without (pFWE=0.046). Altered connectivity within and between networks associated with mood disorders may explain affective and anxiety symptoms in PD-MCI. Neural correlates of NPS in MCI-LB, however, remain unclear, highlighting the need for research in larger, more diverse LBD populations to identify symptomatic treatment target
Polygenic risk discriminates Lewy body dementia from Alzheimer\u27s disease
\ua9 2025 The Author(s). Alzheimer\u27s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer\u27s Association.INTRODUCTION: Lewy body dementia (LBD) shares genetic risk factors with Alzheimer\u27s disease (AD), including apolipoprotein E (APOE), but is distinguishable at the genome-wide level. Polygenic risk scores (PRS) may therefore improve diagnostic classification. METHODS: We assessed diagnostic classification using AD-PRS excluding APOE (AD-PRSnoAPOE), APOE risk score (APOE-RS), and plasma phosphorylated tau 181 (p-tau181), in 83 participants with LBD, 27 with positron emission tomography amyloid beta (Aβ)positive mild cognitive impairment or AD (MCI+/AD), and 57 controls. RESULTS: Together AD-PRSnoAPOE and APOE-RS performed similarly to p-tau181 in discriminating MCI+/AD from controls (area under the curve 76% vs. 79%) and LBD (71% vs. 72%). In LBD, Aβ positivity was significantly associated with APOE-RS, but not with AD-PRSnoAPOE, or p-tau181. Combining AD-PRSnoAPOE, APOE-RS, and p-tau181 improved the discrimination of MCI+/AD from controls (81%) and LBD (75%), and the detection of Aβ in LBD (82%). DISCUSSION: Aβ deposition in LBD was associated with APOE, while MCI+/AD was also associated with AD-PRS beyond APOE. AD-PRS explains phenotypic variance not captured by APOE or p-tau181. Highlights: We investigated Alzheimer\u27s disease (AD) polygenic risk score (PRS), apolipoprotein E (APOE), and plasma phosphorylated tau 181 (p-tau181) to classify AD and Lewy body dementia (LBD). AD-PRS with APOE achieved similar classification accuracy to p-tau181. AD-PRS without APOE significantly contributed to discriminating AD from LBD. Amyloid beta positivity in LBD was associated with APOE but not AD-PRS without APOE or p-tau181. Combining AD-PRS, APOE, and p-tau181 improved diagnostic classification accuracy
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