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Background: The early degeneration of the cholinergic nucleus basalis of Meynert (NBM) and its cortical projections is a hallmark of both dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). In addition to the NBM, the other major cholinergic projection system originates in the pedunculopontine nucleus (PPN) and provides innervation to the thalamus. Given that visual hallucinations are a hallmark of DLB, but not AD, and have recently been attributed to thalamic degeneration, we tested whether the PPN projection system is differentially altered in DLB compared to AD. Methods: NBM‐cortical and PPN‐thalamus white matter pathways were tracked using diffusion‐weighted imaging data from 46 patients with AD, 48 with DLB, 35 with mild cognitive impairment (MCI) with AD, 38 with MCI with Lewy bodies, and 71 control participants. A free‐water corrected DTI model was estimated. Free water fraction along the cholinergic pathways was compared between groups controlling for age, sex, and free water fraction from a white matter control mask. Multiple linear regression was applied to test associations with cognitive function, core Lewy body symptoms with a focus on visual hallucinations, and changes in cognition using longitudinal follow‐up data. Results: Free water fraction in the NBM lateral pathway was increased in both dementia and MCI groups compared to controls and this was associated with performance on overall cognition and phonemic fluency tests as well as with longitudinal changes in cognition (Figure 1). Free water fraction along the PPN‐thalamus tract was increased only in DLB patients while it appeared relatively spared in AD and this increase in the Lewy body patients was related to the presence of visual hallucinations (Figure 2). These results were largely replicated in an independent validation cohort (34 AD, 34 DLB, 35 controls). Conclusion: Our cross‐validated findings show that the cholinergic input to the thalamus from the PPN is selectively affected in DLB and contributes to visual hallucinations. [ABSTRACT FROM AUTHOR]

Background: Neurodegenerative diseases lead to memory disorders and cognitive impairments with major impacts on day‐to‐day function. Early detection of patients is essential for an efficient care approach, and differential diagnosis is essential for determining prognosis and tailoring management. Most research studies compare patients by pairwise comparison methods, but this does not correspond to daily clinical practice, in which clinicians need to distinguish many different possible types of dementia concomitantly. It has been shown that magnetic resonance imaging (MRI) can mark with good accuracy the different types of dementia, such as: Alzheimer's disease (AD), Frontotemporal dementia (FTD), Parkinson's disease (PD), dementia with Lewy bodies (DLB). Recently, Deep Learning approaches have started being used although differential diagnosis is still almost ignored. The aim of this study was to develop a Convolution Neural Network (CNN) to classify probable AD, FTD, DLB, PD and healthy elderly control (CN) subjects starting from Diffusion Tensor Imaging (DTI). Method: The cohort used in this study came from six different initiatives: ADNI1, NIFD2, NACC3, PDBP4, PPMI5 and Newcastle University6,7,8,9. We analysed a total of 108 CN, 110 AD, 135 FTD, 150 DLB, 132 PD. Demographic and neuropsychological characterization is shown in Table 1. The DTI scans were pre‐processed using the FMRIB software library (FSL) with eddy current correction, skull‐stripping and diffusion tensor calculation. We post‐processed the Fractional Anisotropy (FA) map using 3D CNN. The proposed CNN structure consisted of an image input layer, convolutional filters, several batch normalization with max‐pooling layers and, finally, the classification layer. A data augmentation approach was adopted that ultimately resulted in a dataset of 26'450 brain scans. A hold‐out validation (70% training set 30% test set) was performed. Result: We found excellent performance of the 3D CNN in discriminating the different neurodegenerative diseases. Figure 1 shows the confusion matrix with the following values for the area under the ROC curve in each class: 0.92 for CN, 0.90 for AD, 0.97 for DLB, 0.96 for FTD, 0.99 for PD. Conclusion: These results prove that Deep Learning and the 3D CCN method are suitable for clinical practice and provide additional clues that can help clinicians in diagnosis making. [ABSTRACT FROM AUTHOR]

Background: Blood‐based biomarkers of Alzheimer's disease (AD) may help to rule AD in, with particular promise at the mild cognitive impairment (MCI) stage when potential disease‐modifying treatments may be most effective. However, AD is not the only common cause of cognitive impairment: Lewy body disease and other non‐AD pathologies are common and under‐recognised. Reliance on AD‐specific biomarkers alone may therefore contribute to missed diagnosis of non‐AD aetiologies. We aimed to examine the utility of emerging AD plasma biomarkers in identifying disease‐specific MCI due to AD (MCI‐AD), MCI with Lewy bodies (MCI‐LB) and in disease‐general MCI. We also aimed to compare these with alternative disease‐general biomarkers of neurodegeneration, and examined any change over time. Method: In a longitudinal study, plasma samples were collected for 172 participants (31 healthy controls, 48 MCI‐AD, 28 possible MCI‐LB and 65 probable MCI‐LB) at baseline, and a subset (n = 55) who provided repeated samples after ≥1 year. Samples were analysed with Simoa assays for Alzheimer's disease (Aβ42, Aβ40, ptau‐181) and neurodegeneration (GFAP and NfL) biomarkers. MCI cases were differentially classified as MCI‐AD or MCI‐LB by an expert panel of old age psychiatrists, based on current consensus diagnostic criteria, and including Lewy body disease‐specific imaging biomarkers. Age‐adjusted mixed effects models assessed any longitudinal changes over time in each biomarker, and associations with severity of cognitive impairment as assessed by the Addenbrooke's Cognitive Examination – Revised. Result: GFAP performed comparably to AD‐specific biomarkers in identifying any‐cause MCI (GFAP AUC = 0.75; ptau‐181 = 0.73), while maintaining good accuracy in identifying MCI‐AD specifically. AD biomarkers did not reliably distinguish MCI‐AD from MCI‐LB. Severity of cognitive impairment in any‐cause MCI and MCI‐AD was most strongly correlated with the disease‐nonspecific neurodegenerative biomarker NfL (r = 0.48, p = 0.005; cf. GFAP r = 0.23, p = 0.121), which progressively increased over time. Conclusion: Given the high prevalence of unrecognised non‐AD pathologies at autopsy (>1/3 cases in UK brain banks), blood biomarkers of neurodegeneration may be a useful alternative to AD‐specific biomarkers in screening for neurodegenerative disease in MCI. As AD biomarkers do not reliably differentiate MCI‐AD from MCI‐LB, there is a need for disease‐specific biomarkers of synucleinopathies. [ABSTRACT FROM AUTHOR]

Objective: Significant amyloid deposition is present in approximately half of all cases of dementia with Lewy bodies (DLB). We sought to determine whether amyloid deposition was associated with more rapid clinical decline over 1 year.Methods: Twenty-eight participants had a baseline clinical assessment and amyloid PET scan, followed by a further clinical assessment after 1 year. Changes in clinical measures were compared with amyloid deposition assessed by visual rating and cortical standardized uptake value ratio.Results: Amyloid deposition on visual rating was associated with greater decline in Mini-Mental State Examination and daily function over 1 year. There was no correlation between cortical standardized uptake value ratio and clinical measures.Conclusions: This study provides further evidence for a link between amyloid deposition and clinical progression in DLB. Pathologies such as amyloid, and their interaction with α-synuclein, remain possible treatment targets in DLB. [ABSTRACT FROM AUTHOR]

Background: Neuropsychiatric symptoms (NPS) in Lewy body diseases, including dementia with Lewy bodies (DLB) and Parkinson's disease (PD) dementia, occur frequently and at an early stage in disease progression. Such symptoms are significantly associated with quality of life, caregiver burden and functional limitations. Limited evidence exists, however, outlining the relationship between NPS and cognitive decline. Methods: Data from 217 participants were derived from three cohort studies. Patients diagnosed with either MCI with Lewy bodies (MCI‐LB, n = 67), PD‐MCI (n = 56) or Alzheimer's disease (MCI‐AD, n = 39) and a group of healthy older adults (n = 55) completed comprehensive neuropsychological and neuropsychiatric assessment and were followed up longitudinally for a median of three years. NPS identified at baseline by the Neuropsychiatric Inventory (NPI) were included as predictors in linear regressions and linear mixed effects models to assess the relationship between NPS and performance on a range of cognitive tests both at baseline and longitudinally. Results: At baseline, NPS were most prevalent and severe among the MCI‐LB group (49% with NPI score >4 in at least one symptom) and least prevalent in controls (7% with NPI score >4). Total NPI score was not related to baseline cognitive function in any domain in any group. Greater baseline total NPI score was associated with steeper rates of decline among PD‐MCI patients on a measure of processing speed (p =.01). Among healthy adults, only sleep disturbance was associated with steeper rates of decline on global cognition (p =.005). None of the patient groups showed any association between individual NPS and decline on a measure of global cognitive function. Conclusions: The lack of a significant relationship found between NPS and either global cognitive function or decline in global cognition seen among MCI patients suggests that at this prodromal stage of disease, NPS appear to be of limited clinical impact and indicates that the mechanisms of cognitive and neuropsychiatric symptoms may differ in early Lewy body disease. Future work will investigate these mechanisms using multimodal imaging data from this cohort. [ABSTRACT FROM AUTHOR]

Hypertension is associated with reduced cerebral blood flow (CBF). Intensive (<130/80 mm Hg) blood pressure (BP) lowering in older people might give greater reduction in cardiovascular risk, but there are concerns that this might produce hypoperfusion which may precipitate falls and possibly stroke. We determined the effect of intensive compared with usual BP lowering on CBF in hypertensive older subjects. Individuals aged >70 years with a history of systolic hypertension on 1 or no BP lowering drugs were recruited from primary care (n=37; age, 75±4 years; systolic BP, >150 mm Hg) and randomized to receive intensive (target BP, <130/80 mm Hg) or usual (target BP, <140/85 mm Hg) BP lowering for 12 weeks, with reviews every 2 weeks. CBF, determined using 3T arterial spin labeling MRI, and 24-hour ambulatory BP were performed at baseline and after 12 weeks of treatment. Baseline BP (ambulatory or in clinic) and baseline gray matter CBF were not significantly different between the groups. After treatment, BP was reduced significantly in both groups but fell more in the intensive group (26/17 versus 15/5 mm Hg; P<0.01). Over the same period, gray matter CBF increased significantly in the intensive group (7±11 mL/min per 100 g; P=0.013) but was unchanged in the usual BP target group (-3±9 mL/min per 100 g; P=0.23); P<0.01 for comparison. Intensive BP lowering in older people with hypertension increases CBF, compared with BP lowering to usual target. These findings suggest hypertension in older people shifts the autoregulatory CBF curve rightward and downward and is reversible with BP lowering. [ABSTRACT FROM AUTHOR]

The article describes a study which tested for visuoperceptual impairment in Alzheimer disease and Lewy body dementia patients using the computerized Newcastle visuoperception battery (NEVIF) test. The NEVIF evaluated subjects' discrimination of angle, color, and form and motion perception. The results indicated that visual impairment was strongly correlated with global cognitive impairment, but not motor deficits.

Objectives: To explore the relationship between specific aspects of cognition, white matter hyperintensities (WMHs), and cardiovascular autonomic parameters in late-life depression (LLD). Design: Cross-sectional analysis. Setting: Secondary care psychiatry. Participants: Forty-one individuals older than 60 years, with current or previous history of major depression, and 32 age-matched comparison subjects. Measurements: Cognition was assessed by a standardized computer battery of tasks (Cognitive Drug Research) that measured processing speed, attention, episodic memory, and working memory. Cardiovascular autonomic parameters were estimated by a noninvasive device that calculated blood pressure, heart rate variability, and baroreflex sensitivity (Task Force Monitor). Magnetic resonance imaging was performed on a 3-T magnetic resonance imaging system, and WMH volume was estimated using an automated validated method. Results: As expected, cognitive deficits in all tested domains were present in LLD subjects compared with comparison subjects. In the LLD group, processing speed was correlated with scores on memory and working memory tasks. Attentional deficits were correlated with total and periventricular WMH volume, and episodic memory was associated with heart rate variability. There were no associations between cognitive variables and traditional vascular risk factors or between cognitive variables and any of these parameters in the comparison subjects. Conclusions: This study suggests that processing speed may be an important factor underlying deficits in LLD, but it also indicates that other factors, including those related to vascular disease, are important and thus provide further support for the vascular depression hypothesis. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether there are differences in brain connectivity in late-life depression (LLD) and nondepressed subjects using the left and right heads of caudate nuclei (hCN) as the seed regions. Design: Resting-state functional magnetic resonance imaging (fMRI) data were collected using a 3-Tesla MRI System. Setting: Subjects were recruited from primary or secondary care services in the Newcastle area. Participants: Thirty-three subjects aged 65 years and older; 16 who had a recent episode of LLD and 17 nondepressed subjects. Measurements: Functional connectivity was analyzed by extracting the temporal signal variation from the left and right hCN and cross correlating with the rest of the brain. Results: Significant connectivity between the hCN and frontal areas was observed in the nondepressed group, whereas in LLD, connectivity was seen over a much wider area. Regions showing significantly greater connectivity (p ≥ 0.05) in LLD compared with the nondepressed group were frontal (precentral, subgyral, middle frontal, and paracentral lobule), sublobar (thalamus and insula), limbic (cingulate), parietal (postcentral gyrus, precuneus, inferior parietal lobule, and supramarginal gyrus), and temporal (superior temporal gyrus). Conversely, no brain regions showed greater connectivity in the nondepressed group than LLD. In both groups, the right hCN showed significantly greater connectivity than the left in numerous brain regions, but connectivity for the left hCN did not exceed the right in any brain regions. Conclusions: This resting-state study showed increased connectivity in specific brain regions in LLD compared with the nondepressed group, which supports the view that functional connectivity is altered in depression. [ABSTRACT FROM AUTHOR]

Background: There is a newly emergent ageing population of people living with HIV (PLWH) in Africa. However, there is little research into HIV‐associated neurocognitive disorder (HAND) in this population. Existing research suggests HAND is prevalent however the aetiology remains unclear. This study aims to determine whether HAND is truly prevalent and explore potential causes in PLWH on c‐ART using objective structural measures. Method: A systematic sample of PLWH aged ≥ 50 receiving combination antiretroviral treatment (cART) according to local guidelines were recruited from a HIV clinic in Kilimanjaro, Tanzania. Demographic data and comorbidities were self‐reported. HIV‐disease management data were obtained from detailed clinic data sheets. HIV viral load and CD4 count were measured. A detailed low‐literacy neurocognitive battery, informant history for functional impairment and neurological examination were conducted and HAND diagnosis made by consensus panel using AAN criteria. Cerebral atrophy (brain and ventricle volume) and WMH were measured using quantitative analysis of 1.5T MRI. Result: This cohort (n=91, 100% on cART, 64.8% female) had well‐managed HIV (75.9% suppressed viral load, median CD4 507 cells/ul). However, 66.7% had gross atrophy on their MRI scan, and HAND had a prevalence of 63.7%. The significant independent predictor (IP) of decreased brain volume was older age at HIV diagnosis (p=.001), and of increased ventricle volume was increased age (p<.0001), male gender (p<.0001) and increased frailty (p<.0001). The significant IPs of increased WMH volume were increased age (p<.0001) and smoking (p=.021). Only memory impairment independently predicted all structural measures. Conclusion: This is the first MRI study of older c‐ART treated PLWH in Africa. Despite c‐ART and good disease management, HAND was objectively prevalent and unrelated to measures of HIV disease severity. Cerebral atrophy and WMH were associated with factors of neurodegeneration. Cerebral atrophy was associated with male gender and older age at diagnosis. Association with older age at diagnosis may be 'legacy effect' of early CNS effect of the HIV virus rather than current management. [ABSTRACT FROM AUTHOR]