Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia.

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins (proximity extension-based (PEA) immunoassays) in a deeply-phenotyped mixed-memory clinic cohort (n=502, mean age (sd) = 64.1 [8.7] years, 181 female [35.4%]), including patients with Alzheimer's disease (AD, n=213), dementia with Lewy bodies (DLB, n=50) and frontotemporal dementia (FTD, n=93), and controls (n=146). Validation was assessed in independent cohorts (n=99 PEA platform, n=198, MRM-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1-CR2 (rs3818361, P=1.65e-08), ZCWPW1-PILRB (rs1476679, P=2.73e-32), CTSH-CTSH (rs3784539, P=2.88e-24) and HESX1-RETN (rs186108507, P=8.39e-08), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90e-7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for frontotemporal dementia, either for the total sample as for analyses performed within FTD only. pQTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.

PURPOSE: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA). METHODS: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level. RESULTS: Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912). CONCLUSION: Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

Visual associative learning to detect early episodic memory deficits and distinguish Alzheimer's disease from other types of dementia.

OBJECTIVE: We investigated how well a visual associative learning task discriminates Alzheimer's disease (AD) dementia from other types of dementia and how it relates to AD pathology. METHODS: 3,599 patients (63.9 ± 8.9 years old, 41% female) from the Amsterdam Dementia Cohort completed two sets of the Visual Association Test (VAT) in a single test session and underwent magnetic resonance imaging. We performed receiver operating curve analysis to investigate the VAT's discriminatory ability between AD dementia and other diagnoses and compared it to that of other episodic memory tests. We tested associations between VAT performance and medial temporal lobe atrophy (MTA), and amyloid status (n = 2,769, 77%). RESULTS: Patients with AD dementia performed worse on the VAT than all other patients. The VAT discriminated well between AD and other types of dementia (area under the curve range 0.70-0.86), better than other episodic memory tests. Six-hundred forty patients (17.8%) learned all associations on VAT-A, but not on VAT-B, and they were more likely to have higher MTA scores (odds ratios range 1.63 (MTA 0.5) through 5.13 for MTA ≥ 3, all p < .001) and to be amyloid positive (odds ratio = 3.38, 95%CI = [2.71, 4.22], p < .001) than patients who learned all associations on both sets. CONCLUSIONS: Performance on the VAT, especially on a second set administered immediately after the first, discriminates AD from other types of dementia and is associated with MTA and amyloid positivity. The VAT might be a useful, simple tool to assess early episodic memory deficits in the presence of AD pathology.

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease.

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.

Sex differences in brain atrophy in dementia with Lewy bodies.

INTRODUCTION: Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS: We included 436 patients from the European-DLB consortium and the Mayo Clinic. Sex differences and sex-by-age interactions were assessed through visual atrophy rating scales (n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness (n = 165; 69 ± 9 years, 72% males). RESULTS: We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex-by-age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION: We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. HIGHLIGHTS: Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales. Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods. Sex differences in gray matter measures in DLB tended to disappear with increasing age.

Iatrogenic Cerebral Amyloid Angiopathy Post Neurosurgery: Frequency, Clinical Profile, Radiological Features, and Outcome.

BACKGROUND: Prion-like transmission of amyloid-ß through cadaveric dura, decades after neurosurgical procedures, has been hypothesized as an iatrogenic cause of cerebral amyloid angiopathy (CAA). We investigated new and previously described patients to assess the clinical profile, radiological features, and outcome of this presumed iatrogenic CAA-subtype (iCAA). METHODS: Patients were collected from our prospective lobar hemorrhage and CAA database (n=251) with patients presenting to our hospital between 2008 and 2022. In addition, we identified patients with iCAA from 2 other Dutch CAA-expertise hospitals and performed a systematic literature-search for previously described patients. We classified patients according to the previously proposed diagnostic criteria for iCAA, assessed clinical and radiological disease features, and calculated intracerebral hemorrhage (ICH)-recurrence rates. We evaluated the spatial colocalization of cadaveric dura placement and CAA-associated magnetic resonance imaging markers. RESULTS: We included 49 patients (74% men, mean age 43 years [range, 27-84]); 15 from our database (6% [95% CI, 3%-10%]; 45% of patients <55 years), 3 from the 2 other CAA-expertise hospitals, and 31 from the literature. We classified 43% (n=21; 1 newly identified patient) as probable and 57% (n=28) as possible iCAA. Patients presented with lobar ICH (57%), transient focal neurological episodes (12%), or seizures (8%). ICH-recurrence rate in the new patients (16/100 person-years [95% CI, 7-32], median follow-up 18 months) was lower than in the previously described patients (77/100 person-years [95% CI, 59-99], median follow-up 18 months). One patient had a 10 year interlude without ICH-recurrence. We identified no clear spatial relationship between dura placement and CAA-associated magnetic resonance imaging markers. During follow-up (median, 18 months), 20% of the patients developed transient focal neurological episodes and 20% cognitively declined. CONCLUSIONS: iCAA seems common in patients presenting with nonhereditary CAA under the age of 55. Clinical and radiological features are comparable with sCAA. After diagnosis, multiple ICH-recurrences but also long symptom-free intervals can occur. Harmonized registries are necessary to identify and understand this potentially underrecognized CAA-subtype.

Neuroinflammatory CSF biomarkers MIF, sTREM1, and sTREM2 show dynamic expression profiles in Alzheimer's disease.

BACKGROUND: There is a need for novel fluid biomarkers tracking neuroinflammatory responses in Alzheimer's disease (AD). Our recent cerebrospinal fluid (CSF) proteomics study revealed that migration inhibitory factor (MIF) and soluble triggering receptor expressed on myeloid cells 1 (sTREM1) increased along the AD continuum. We aimed to assess the potential use of these proteins, in addition to sTREM2, as CSF biomarkers to monitor inflammatory processes in AD. METHODS: We included cognitively unimpaired controls (n = 67, 63 ± 9 years, 24% females, all amyloid negative), patients with mild cognitive impairment (MCI; n = 92, 65 ± 7 years, 47% females, 65% amyloid positive), AD (n = 38, 67 ± 6 years, 8% females, all amyloid positive), and DLB (n = 50, 67 ± 6 years, 5% females, 54% amyloid positive). MIF, sTREM1, and sTREM2 levels were measured by validated immunoassays. Differences in protein levels between groups were tested with analysis of covariance (corrected for age and sex). Spearman correlation analysis was performed to evaluate the association between these neuroinflammatory markers with AD-CSF biomarkers (Aß42, tTau, pTau) and mini-mental state examination (MMSE) scores. RESULTS: MIF levels were increased in MCI (p < 0.01), AD (p < 0.05), and DLB (p > 0.05) compared to controls. Levels of sTREM1 were specifically increased in AD compared to controls (p < 0.01), MCI (p < 0.05), and DLB patients (p > 0.05), while sTREM2 levels were increased specifically in MCI compared to all other groups (all p < 0.001). Neuroinflammatory proteins were highly correlated with CSF pTau levels (MIF: all groups; sTREM1: MCI, AD and DLB; sTREM2: controls, MCI and DLB). Correlations with MMSE scores were observed in specific clinical groups (MIF in controls, sTREM1 in AD, and sTREM2 in DLB). CONCLUSION: Inflammatory-related proteins show diverse expression profiles along different AD stages, with increased protein levels in the MCI stage (MIF and sTREM2) and AD stage (MIF and sTREM1). The associations of these inflammatory markers primarily with CSF pTau levels indicate an intertwined relationship between tau pathology and inflammation. These neuroinflammatory markers might be useful in clinical trials to capture dynamics in inflammatory responses or monitor drug-target engagement of inflammatory modulators.

Protein disulfide isomerases as CSF biomarkers for the neuronal response to tau pathology.

INTRODUCTION: Cerebrospinal fluid (CSF) biomarkers for specific cellular disease processes are lacking for tauopathies. In this translational study we aimed to identify CSF biomarkers reflecting early tau pathology-associated unfolded protein response (UPR) activation. METHODS: We employed mass spectrometry proteomics and targeted immunoanalysis in a combination of biomarker discovery in primary mouse neurons in vitro and validation in patient CSF from two independent large multicentre cohorts (EMIF-AD MBD, n = 310; PRIDE, n = 771). RESULTS: First, we identify members of the protein disulfide isomerase (PDI) family in the neuronal UPR-activated secretome and validate secretion upon tau aggregation in vitro. Next, we demonstrate that PDIA1 and PDIA3 levels correlate with total- and phosphorylated-tau levels in CSF. PDIA1 levels are increased in CSF from AD patients compared to controls and patients with tau-unrelated frontotemporal and Lewy body dementia (LBD). HIGHLIGHTS: Neuronal unfolded protein response (UPR) activation induces the secretion of protein disulfide isomerases (PDIs) in vitro. PDIA1 is secreted upon tau aggregation in neurons in vitro. PDIA1 and PDIA3 levels correlate with total and phosphorylated tau levels in CSF. PDIA1 levels are increased in CSF from Alzheimer's disease (AD) patients compared to controls. PDIA1 levels are not increased in CSF from tau-unrelated frontotemporal dementia (FTD) and Lewy body dementia (LBD) patients.

A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET.

PURPOSE: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer's disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare model's performance to that of multiple expert nuclear medicine physicians' readers. MATERIALS AND METHODS: Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimer's disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human readers on the same independent test set. The model's performance was analyzed with sensitivity, specificity, precision, F1 score, receiver operating characteristic (ROC). The regional metabolic changes driving classification were visualized using uniform manifold approximation and projection (UMAP) and network attention. RESULTS: The proposed model achieved area under the ROC curve of 96.2% (95% confidence interval: 90.6-100) on predicting the final diagnosis of DLB in the independent test set, 96.4% (92.7-100) in AD, 71.4% (51.6-91.2) in MCI-AD, and 94.7% (90-99.5) in CN, which in ROC space outperformed human readers performance. The network attention depicted the posterior cingulate cortex is important for each neurodegenerative disease, and the UMAP visualization of the extracted features by the proposed model demonstrates the reality of development of the given disorders. CONCLUSION: Using only 18F-FDG PET of the brain, a 3D deep learning model could predict the final diagnosis of the most common neurodegenerative disorders which achieved a competitive performance compared to the human readers as well as their consensus.

Disease progression in dementia with Lewy bodies: A longitudinal study on clinical symptoms, quality of life and functional impairment.

BACKGROUND AND OBJECTIVES: Dementia with Lewy Bodies (DLB) is a heterogeneous disease, with variable signs and symptoms across multiple domains. We aimed to identify associations with rate of change in cognition, everyday functioning (IADL) and quality of life (QoL). METHODS: We included 121 DLB patients (69 ± 6 yrs, 14%F, MMSE: 25 ± 3) in our prospective cohort (follow-up 2 ± 1 yrs). We described progression of symptoms and cognitive decline over time. Mixed models were used to investigate whether changes in symptoms were associated to changes in IADL (FAQ), QoL (QoL-AD) and caregiver burden (ZBI). Last, we investigated whether baseline symptoms and biomarkers predicted decline in cognition (MMSE), IADL (FAQ) and QoL (QoL-AD). RESULTS: Parkinsonism and RBD were most frequently present early in the disease course, while hallucinations were more likely to develop in a later stage. MMSE (annual change ß ± SE = -2.06 ± 0.23), QoL-AD (-1.03 ± 0.20), and FAQ (3.04 ± 0.30) declined over time. Increasing severity of clinical symptoms was associated to increases in FAQ, QoL-AD and caregiver burden. Baseline clinical symptoms were not predictive for decline in these outcomes. By contrast, AD co-pathology (CSF pTau/Aß42 ratio) was associated to steeper decline in MMSE (-1.23 ± 0.54). Medial temporal atrophy (-0.81 ± 0.26) and global cortical atrophy (-0.73 ± 0.36) predisposed for decline in QoL-AD. CONCLUSIONS: Our findings imply that underlying disease processes, rather than clinical symptomatology aid in predicting decline. These findings are relevant for treatment strategies and the development of DLB specific outcome measures.

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones.

Associations among education, age, and the dementia with Lewy bodies (DLB) metabolic pattern: A European-DLB consortium project.

INTRODUCTION: We assessed the influence of education as a proxy of cognitive reserve and age on the dementia with Lewy bodies (DLB) metabolic pattern. METHODS: Brain 18F-fluorodeoxyglucose positron emission tomography and clinical/demographic information were available in 169 probable DLB patients included in the European DLB-consortium database. Principal component analysis identified brain regions relevant to local data variance. A linear regression model was applied to generate age- and education-sensitive maps corrected for Mini-Mental State Examination score, sex (and either education or age). RESULTS: Age negatively covaried with metabolism in bilateral middle and superior frontal cortex, anterior and posterior cingulate, reducing the expression of the DLB-typical cingulate island sign (CIS). Education negatively covaried with metabolism in the left inferior parietal cortex and precuneus (making the CIS more prominent). DISCUSSION: These findings point out the importance of tailoring interpretation of DLB biomarkers considering the concomitant effect of individual, non-disease-related variables such as age and cognitive reserve.

Metabolic patterns across core features in dementia with lewy bodies.

OBJECTIVE: To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern. METHODS: Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map. RESULTS: Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in the medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, and orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobe metabolism. MMSE positively covaried with metabolism in the left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in the insula, medial frontal gyrus, hippocampus in the left hemisphere, and right cerebellum. INTERPRETATION: Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated with more prominent hypometabolism in specific regions, thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. Ann Neurol 2019;85:715-725.

Prodromal Dementia With Lewy Bodies: Clinical Characterization and Predictors of Progression.

OBJECTIVE: The objective of this study was to examine clinical characteristics, cognitive decline, and predictors for time to dementia in prodromal dementia with Lewy bodies with mild cognitive impairment (MCI-LB) compared with prodromal Alzheimer's disease (MCI-AD). METHODS: We included 73 MCI-LB patients (12% female; 68 ± 6 years; Mini Mental State Examination, 27 ± 2) and 124 MCI-AD patients (48% female; 68 ± 7 years; Mini Mental State Examination, 27 ± 2) from the Amsterdam Dementia Cohort. Follow-up was available for 61 MCI-LB patients and all MCI-AD patients (3 ± 2 years). We evaluated dementia with Lewy bodies core features, neuropsychiatric symptoms, caregiver burden (Zarit caregiver burden interview), MRI, apolipoprotein genotype, and cerebrospinal fluid biomarkers (tau/Aß1-42 ratio). Longitudinal outcome measures included cognitive slopes (memory, attention, executive functions, and language and visuospatial functions) and time to dementia. RESULTS: Parkinsonism was the most frequently present core feature in MCI-LB (69%). MCI-LB patients more often had neuropsychiatric symptoms and scored higher on ZARIT when compared with the MCI-AD patients. Linear mixed models showed that at baseline, MCI-LB patients performed worse on nonmemory cognitive domains, whereas memory performance was worse in MCI-AD patients. Over time, MCI-LB patients declined faster on attention, whereas MCI-AD patients declined faster on the Mini Mental State Examination and memory. Cox proportional hazards regressions showed that in the MCI-LB patients, lower attention (hazard ratio [HR] = 1.6; 95% confidence interval [CI], 1.1-2.3) and more posterior cortical atrophy (HR = 3.0; 95% CI, 1.5-5.8) predicted shorter time to dementia. In the MCI-AD patients, worse performance on memory (HR = 1.1; 95% CI, 1.0-1.2) and executive functions (HR = 1.3; 95% CI, 1.0-1.6) were independently associated with time to Alzheimer's dementia. CONCLUSION: MCI-LB patients have distinct neuropsychiatric and cognitive profiles with prominent decline in attention when compared with MCI-AD patients. Our results highlight the importance of early diagnosis because symptoms already have an impact in the prodromal stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Metabolic Correlates of Dopaminergic Loss in Dementia with Lewy Bodies.

BACKGROUND: Striatal dopamine deficiency and metabolic changes are well-known phenomena in dementia with Lewy bodies and can be quantified in vivo by 123 I-Ioflupane brain single-photon emission computed tomography of dopamine transporter and 18 F-fluorodesoxyglucose PET. However, the linkage between both biomarkers is ill-understood. OBJECTIVE: We used the hitherto largest study cohort of combined imaging from the European consortium to elucidate the role of both biomarkers in the pathophysiological course of dementia with Lewy bodies. METHODS: We compared striatal dopamine deficiency and glucose metabolism of 84 dementia with Lewy body patients and comparable healthy controls. After normalization of data, we tested their correlation by region-of-interest-based and voxel-based methods, controlled for study center, age, sex, education, and current cognitive impairment. Metabolic connectivity was analyzed by inter-region coefficients stratified by dopamine deficiency and compared to healthy controls. RESULTS: There was an inverse relationship between striatal dopamine availability and relative glucose hypermetabolism, pronounced in the basal ganglia and in limbic regions. With increasing dopamine deficiency, metabolic connectivity showed strong deteriorations in distinct brain regions implicated in disease symptoms, with greatest disruptions in the basal ganglia and limbic system, coincident with the pattern of relative hypermetabolism. CONCLUSIONS: Relative glucose hypermetabolism and disturbed metabolic connectivity of limbic and basal ganglia circuits are metabolic correlates of dopamine deficiency in dementia with Lewy bodies. Identification of specific metabolic network alterations in patients with early dopamine deficiency may serve as an additional supporting biomarker for timely diagnosis of dementia with Lewy bodies. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Heritability and genetic variance of dementia with Lewy bodies.

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

A signature pattern of cortical atrophy in dementia with Lewy bodies: A study on 333 patients from the European DLB consortium.

INTRODUCTION: We explored regional brain atrophy patterns and their clinical correlates in dementia with Lewy bodies (DLB). METHODS: In this multicentre study, we included a total of 333 patients with DLB, 352 patients with Alzheimer's disease (AD), and 233 normal controls and used medial temporal lobe atrophy, posterior atrophy, and frontal atrophy (GCA-F) visual rating scales. Patients were classified according to four atrophy patterns. RESULTS: Patients with DLB had higher scores on all the three atrophy scales than normal controls but had less medial temporal lobe atrophy than those with AD (all P values < .001). A signature hippocampal-sparing pattern of regional atrophy was observed in DLB. The magnetic resonance imaging measures showed 65% ability to discriminate between DLB and AD and marginally contributed to the discrimination over and above the core clinical features. DISCUSSION: The most common pattern of atrophy of DLB was hippocampal-sparing. Future studies should explore whether comorbid AD pathology underlies the atrophy patterns seen in DLB.

VGF Peptides in Cerebrospinal Fluid of Patients with Dementia with Lewy Bodies.

In a previous proteomic study, we identified the neurosecretory protein VGF (VGF) as a potential biomarker for dementia with Lewy bodies (DLB). Here, we extended the study of VGF by comparing levels in cerebrospinal fluid (CSF) from 44 DLB patients, 20 Alzheimer's disease (AD) patients, and 22 cognitively normal controls selected from the Amsterdam Dementia Cohort. CSF was analyzed using two orthogonal analytical methods: (1) In-house-developed quantitative ELISA and (2) selected reaction monitoring (SRM). We further addressed associations of VGF with other CSF biomarkers and cognition. VGF levels were lower in CSF from patients with DLB compared to either AD patients or controls. VGF was positively correlated with CSF tau and α-synuclein (0.55 < r < 0.75), but not with Aß1-42. In DLB patients, low VGF levels were related to a more advanced cognitive decline at time of first presentation, whereas high levels of VGF were associated with steeper subsequent longitudinal cognitive decline. Hence, CSF VGF levels were lower in DLB compared to both AD and controls across different analytical methods. The strong associations with cognitive decline further points out VGF as a possible disease stage or prognostic marker for DLB.

α-Synuclein species as potential cerebrospinal fluid biomarkers for dementia with lewy bodies.

BACKGROUND: The objective of this study was to investigate the discriminating value of a range of CSF α-synuclein species for dementia with Lewy bodies compared with Alzheimer's disease, PD, and cognitively normal controls. METHODS: We applied our recently published enzyme-linked immunosorbent assays to measure the CSF levels of total α-synuclein, oligomeric α-synuclein, and phosphorylated α-synuclein in dementia with Lewy bodies (n = 42), Alzheimer's disease (n = 39), PD (n = 46), and controls (n = 78). General linear models corrected for age and sex were performed to assess differences in α-synuclein levels between groups. We used backward-elimination logistic regression analysis to investigate the combined discriminating value of the different CSF α-synuclein species and Alzheimer's disease biomarkers. RESULTS: CSF levels of total α-synuclein were lower in dementia with Lewy bodies and PD compared with Alzheimer's disease as well as controls (P < 0.001). In contrast, CSF levels of oligomeric α-synuclein were higher in dementia with Lewy bodies and PD compared with Alzheimer's disease (P < 0.05) and controls (P < 0.001). No group differences were found for phosphorylated α-synuclein. In dementia with Lewy bodies and PD, CSF total α-synuclein levels positively correlated with tau and phosphorylated tau (both r > 0.40, P < 0.01), but not with amyloid-ß1-42 . The optimal combination to differentiate dementia with Lewy bodies from controls consisted of amyloid-ß1-42 , tau, total α-synuclein, oligomeric α-synuclein, age, and sex (AUC, 0.90). To differentiate dementia with Lewy bodies from Alzheimer's disease, the combination of tau and oligomeric α-synuclein resulted in an AUC of 0.83. CSF α-synuclein species do not contribute to the differentiation of dementia with Lewy bodies from PD. CONCLUSIONS: CSF α-synuclein species could be useful as part of a biomarker panel for dementia with Lewy bodies. Evaluating both oligomeric α-synuclein and total α-synuclein in CSF helps in the diagnosis of dementia with Lewy bodies. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Assessing Fitness to Drive in Patients With Different Types of Dementia.

Dementia is a risk factor for unsafe driving. Therefore, an assessment strategy has recently been developed for the prediction of fitness to drive in patients with the Alzheimer disease (AD). The aim of this study was to investigate whether this strategy is also predictive of fitness to drive in patients with non-AD dementia, that is, vascular dementia, frontotemporal dementia, and dementia with Lewy bodies. Predictors were derived from 3 types of assessment: clinical interviews, neuropsychological tests, and driving simulator rides. The criterion was the pass-fail outcome of an official on-road driving assessment. About half of the patients with non-AD dementia (n=34) failed the on-road driving assessment. Neuropsychological assessment [area under the curve (AUC)=0.786] was significantly predictive of fitness to drive in patients with non-AD dementia, however, clinical interviews (AUC=0.559) and driving simulator rides (AUC=0.404) were not. The fitness-to-drive assessment strategy with the 3 types of assessment combined (AUC=0.635) was not found to significantly predict fitness to drive in non-AD dementia. Different types of dementia require different measures and assessment strategies.