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This preclinical AD CSF proteome study identified a panel of 12-CSF markers detecting amyloid positivity and clinical progression to AD with high accuracy; some of these CSF proteins related to immune function, neurotrophic processes, energy metabolism and endolysosomal functioning (e.g., ITGB2, CLEC5A, IGFBP-1, CST3) changed before amyloid positivity is established., Competing Interests: Declarations Ethics approval and consent to participate The study was approved by the Institutional Ethical Review Boards (AD CSF biobank METC number.00–211) and informed consent was obtained from all subjects or their authorized representatives. Consent for publication Not applicable. Competing interests MC has been an invited speaker at Eisai and Novonordisk. She is an associate editor at Alzheimer´s Research & Therapy and has been an invited writer for Springer Healthcare. LV received a grant for CORAL consortium by Olink, and has been invited speaker for Eli Lilly, and consultant for Roche. IV received a TKI Health ~ Holland grant for a collaborative project with OLINK and Quanterix. IV has been an invited speaker by Quanterix, funding is paid to her institution. WvF has been an invited speaker at Biogen MA Inc, Danone, Eisai, WebMD Neurology (Medscape), NovoNordisk, Springer Healthcare, European Brain Council. WF is consultant to Oxford Health Policy Forum CIC, Roche, Biogen MA Inc, and Eisai. WF is member of steering cie of NovoNordisk evoke/evoke + . WvF participated in advisory boards of Biogen MA Inc, Roche, and Eli Lilly. All funding is paid to her institution. WvF is member of the steering committee of PAVE, and Think Brain Health. WvF was associate editor of Alzheimer, Research & Therapy in 2020/2021. WvF is associate editor at Brain. CET has a collaboration contract with ADx Neurosciences, Quanterix and Eli Lilly, performed contract research or received grants from AC-Immune, Axon Neurosciences, Bioconnect, Bioorchestra, Brainstorm Therapeutics, Celgene, EIP Pharma, Eisai, Grifols, Novo Nordisk, PeopleBio, Roche, Toyama, Vivoryon. She serves on editorial boards of Medidact Neurologie/Springer, Alzheimer Research and Therapy, Neurology: Neuroimmunology & Neuroinflammation, and is editor of a Neuromethods book Springer. She had speaker contracts for Roche, Grifols, Novo Nordisk. The rest of the authors declare no competing interest., (© 2024. The Author(s).)

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 (standard deviation, 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, mass reaction monitoring-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 = 1.65 × 10-8), ZCWPW1-PILRB (rs1476679, P = 2.73 × 10-32), CTSH-CTSH (rs3784539, P = 2.88 × 10-24) and HESX1-RETN (rs186108507, P = 8.39 × 10-8), 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 = 3.90 × 10-7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for FTD loci, either for the total sample as for analyses performed within FTD only. Protein QTL 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., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Diagnosis of Frontotemporal dementia (FTD) and the specific underlying neuropathologies (frontotemporal lobar degeneration; FTLD- Tau and FTLD-TDP) is challenging, and thus fluid biomarkers are needed to improve diagnostic accuracy. We used proximity extension assays to analyze 665 proteins in cerebrospinal fluid (CSF) samples from a multicenter cohort including patients with FTD (n = 189), Alzheimer's Disease dementia (AD; n = 232), and cognitively unimpaired individuals (n = 196). In a subset, FTLD neuropathology was determined based on phenotype or genotype (FTLD-Tau = 87 and FTLD-TDP = 68). Forty three proteins were differentially regulated in FTD compared to controls and AD, reflecting axon development, regulation of synapse assembly, and cell-cell adhesion mediator activity pathways. Classification analysis identified a 14- and 13-CSF protein panel that discriminated FTD from controls (AUC: 0.96) or AD (AUC: 0.91). Custom multiplex panels confirmed the highly accurate discrimination between FTD and controls (AUCs > 0.96) or AD (AUCs > 0.88) in three validation cohorts, including one with autopsy confirmation (AUCs > 0.90). Six proteins were differentially regulated between FTLD-TDP and FTLD-Tau, but no reproducible classification model could be generated (AUC: 0.80). Overall, this study introduces novel FTD-specific biomarker panels with potential use in diagnostic setting.

Intoduction: In systems biology, an organism is viewed as a system of interconnected molecular entities. To understand the functioning of organisms it is essential to integrate information about the variations in the concentrations of those molecular entities. This information can be structured as a set of networks with interconnections and with some hierarchical relations between them. Few methods exist for the reconstruction of integrative networks., Objective: In this work, we propose an integrative network reconstruction method in which the network organization for a particular type of omics data is guided by the network structure of a related type of omics data upstream in the omic cascade. The structure of these guiding data can be either already known or be estimated from the guiding data themselves., Methods: The method consists of three steps. First a network structure for the guiding data should be provided. Next, responses in the target set are regressed on the full set of predictors in the guiding data with a Lasso penalty to reduce the number of predictors and an L2 penalty on the differences between coefficients for predictors that share edges in the network for the guiding data. Finally, a network is reconstructed on the fitted target responses as functions of the predictors in the guiding data. This way we condition the target network on the network of the guiding data., Conclusions: We illustrate our approach on two examples in Arabidopsis. The method detects groups of metabolites that have a similar genetic or transcriptomic basis., (© 2024. The Author(s).)

Diagnosis of dementia with Lewy bodies (DLB) is challenging and specific biofluid biomarkers are highly needed. We employed proximity extension-based assays to measure 665 proteins in the cerebrospinal fluid (CSF) from patients with DLB (n = 109), Alzheimer´s disease (AD, n = 235) and cognitively unimpaired controls (n = 190). We identified over 50 CSF proteins dysregulated in DLB, enriched in myelination processes among others. The dopamine biosynthesis enzyme DDC was the strongest dysregulated protein, and could efficiently discriminate DLB from controls and AD (AUC:0.91 and 0.81 respectively). Classification modeling unveiled a 7-CSF biomarker panel that better discriminate DLB from AD (AUC:0.93). A custom multiplex panel for six of these markers (DDC, CRH, MMP-3, ABL1, MMP-10, THOP1) was developed and validated in independent cohorts, including an AD and DLB autopsy cohort. This DLB CSF proteome study identifies DLB-specific protein changes and translates these findings to a practicable biomarker panel that accurately identifies DLB patients, providing promising diagnostic and clinical trial testing opportunities., (© 2023. Springer Nature Limited.)

Three subtypes of distinct pathological proteins accumulate throughout multiple brain regions and shape the heterogeneous clinical presentation of frontotemporal lobar degeneration (FTLD). Besides the main pathological subtypes, co-occurring pathologies are common in FTLD brain donors. The objective of this study was to investigate how the location and burden of (co-)pathology correlate to early psychiatric and behavioural symptoms of FTLD. Eighty-seven brain donors from The Netherlands Brain Bank cohort (2008-2017) diagnosed with FTLD were included: 46 FTLD-TAR DNA-binding protein 43 (FTLD-TDP), 34 FTLD-tau, and seven FTLD-fused-in-sarcoma (FTLD-FUS). Post-mortem brain tissue was dissected into 20 standard regions and stained for phosphorylated TDP-43, phosphorylated tau, FUS, amyloid-β, and α-synuclein. The burden of each pathological protein in each brain region was assessed with a semi-quantitative score. Clinical records were reviewed for early psychiatric and behavioural symptoms. Whole-brain clinico-pathological partial correlations were calculated (local false discovery rate threshold = 0.01). Elaborating on the results, we validated one finding using a quantitative assessment of TDP-43 pathology in the granular layer of the hippocampus in FTLD-TDP brain donors with (n = 15) and without (n = 15) hallucinations. In subcortical regions, the presence of psychiatric symptoms showed positive correlations with increased hippocampal pathology burden: hallucinations with TDP-43 in the granular layer (R = 0.33), mania with TDP-43 in CA1 (R = 0.35), depression with TDP-43 in CA3 and with parahippocampal tau (R = 0.30 and R = 0.23), and delusions with CA3 tau (R = 0.26) and subicular amyloid-β (R = 0.25). Behavioural disinhibition showed positive correlations with tau burden in the thalamus (R = 0.29) and with both TDP-43 and amyloid-β burden in the subthalamus (R = 0.23 and R = 0.24). In the brainstem, the presence of α-synuclein co-pathology in the substantia nigra correlated with disinhibition (R = 0.24), tau pathology in the substantia nigra correlated with depression (R = 0.25) and in the locus coeruleus with both depression and perseverative/compulsive behaviour (R = 0.26 and R = 0.32). The quantitative assessment of TDP-43 in the granular layer validated the higher burden of TDP-43 pathology in brain donors with hallucinations compared to those without hallucinations (P = 0.007). Our results show that psychiatric symptoms of FTLD are linked to subcortical pathology burden in the hippocampus, and hallucinations are linked to a higher burden of TDP-43 in the granular layer. Co-occurring non-FTLD pathologies in subcortical regions could contribute to configuring the clinical phenotype of FTLD., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Development of disease-modifying therapies against Alzheimer's disease (AD) requires biomarkers reflecting the diverse pathological pathways specific for AD. We measured 665 proteins in 797 cerebrospinal fluid (CSF) samples from patients with mild cognitive impairment with abnormal amyloid (MCI(Aβ+): n = 50), AD-dementia (n = 230), non-AD dementias (n = 322) and cognitively unimpaired controls (n = 195) using proximity ligation-based immunoassays. Here we identified >100 CSF proteins dysregulated in MCI(Aβ+) or AD compared to controls or non-AD dementias. Proteins dysregulated in MCI(Aβ+) were primarily related to protein catabolism, energy metabolism and oxidative stress, whereas those specifically dysregulated in AD dementia were related to cell remodeling, vascular function and immune system. Classification modeling unveiled biomarker panels discriminating clinical groups with high accuracies (area under the curve (AUC): 0.85-0.99), which were translated into custom multiplex assays and validated in external and independent cohorts (AUC: 0.8-0.99). Overall, this study provides novel pathophysiological leads delineating the multifactorial nature of AD and potential biomarker tools for diagnostic settings or clinical trials., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process., Methods: Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis., Results: Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified., Conclusions: We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts., (© 2022. The Author(s).)

The features in a high-dimensional biomedical prediction problem are often well described by low-dimensional latent variables (or factors). We use this to include unlabeled features and additional information on the features when building a prediction model. Such additional feature information is often available in biomedical applications. Examples are annotation of genes, metabolites, or p-values from a previous study. We employ a Bayesian factor regression model that jointly models the features and the outcome using Gaussian latent variables. We fit the model using a computationally efficient variational Bayes method, which scales to high dimensions. We use the extra information to set up a prior model for the features in terms of hyperparameters, which are then estimated through empirical Bayes. The method is demonstrated in simulations and two applications. One application considers influenza vaccine efficacy prediction based on microarray data. The second application predicts oral cancer metastasis from RNAseq data., (© 2022 The Authors. Biometrical Journal published by Wiley-VCH GmbH.)

Psychoneurological symptoms are commonly reported by newly diagnosed head and neck cancer (HNC) patients, yet there is limited research on the associations of these symptoms with biomarkers of stress and inflammation. In this article, pre-treatment data of a multi-center cohort of HNC patients were analyzed using a network analysis to examine connections between symptoms (poor sleep quality, anxiety, depression, fatigue, and oral pain), biomarkers of stress (diurnal cortisol slope), inflammation markers (c-reactive protein [CRP], interleukin [IL]-6, IL-10, and tumor necrosis factor alpha [TNF-α]), and covariates (age and body mass index [BMI]). Three centrality indices were calculated: degree (number of connections), closeness (proximity of a variable to other variables), and betweenness (based on the number of times a variable is located on the shortest path between any pair of other variables). In a sample of 264 patients, poor sleep quality and fatigue had the highest degree index; fatigue and CRP had the highest closeness index; and IL-6 had the highest betweenness index. The model yielded two clusters: a symptoms-cortisol slope-CRP cluster and a IL-6-IL-10-TNF-α-age-BMI cluster. Both clusters were connected most prominently via IL-6. Our findings provide evidence that poor sleep quality, fatigue, CRP, and IL-6 play an important role in the interconnections between psychoneurological symptoms and biomarkers of stress and inflammation in newly diagnosed HNC patients., Competing Interests: The authors declare no conflict of interest.

Introduction: Cognitive training (CT) has been proposed as a treatment option for cognitive impairment in Parkinson's disease (PD). We aimed to assess the efficacy of adaptive, computerized CT on cognitive function in PD., Methods: In this double-blind, randomized controlled trial we enrolled PD patients that experienced substantial subjective cognitive complaints. Over a period of eight weeks, participants underwent 24 sessions of computerized multi-domain CT or an active control intervention for 45 min each (randomized 1:1). The primary outcome was the accuracy on the Tower of London task; secondary outcomes included effects on other neuropsychological outcomes and subjective cognitive complaints. Outcomes were assessed before and after training and at six-months follow-up, and analyzed with multivariate mixed-model analyses., Results: The intention-to-treat population consisted of 136 participants (n = 68 vs. n = 68, age M: 62.9y, female: 39.7%). Multivariate mixed-model analyses showed no group difference on the Tower of London accuracy corrected for baseline performance (n = 130): B: -0.06, 95% CI: -0.27 to 0.15, p = 0.562. Participants in the CT group were on average 0.30 SD (i.e., 1.5 s) faster on difficulty load 4 of this task (secondary outcome): 95% CI: -0.55 to -0.06, p = 0.015. CT did not reduce subjective cognitive complaints. At follow-up, no group differences were found., Conclusions: This study shows no beneficial effect of eight-week computerized CT on the primary outcome (i.e., planning accuracy) and only minor improvements on secondary outcomes (i.e., processing speed) with limited clinical impact. Personalized or ecologically valid multi-modal intervention methods could be considered to achieve clinically meaningful and lasting effects., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In high-dimensional data settings, additional information on the features is often available. Examples of such external information in omics research are: (i) $p$-values from a previous study and (ii) omics annotation. The inclusion of this information in the analysis may enhance classification performance and feature selection but is not straightforward. We propose a group-regularized (logistic) elastic net regression method, where each penalty parameter corresponds to a group of features based on the external information. The method, termed gren, makes use of the Bayesian formulation of logistic elastic net regression to estimate both the model and penalty parameters in an approximate empirical-variational Bayes framework. Simulations and applications to three cancer genomics studies and one Alzheimer metabolomics study show that, if the partitioning of the features is informative, classification performance, and feature selection are indeed enhanced., (© The Author 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: Knowledge regarding symptom clusters may inform targeted interventions. The current study investigated symptom clusters among cancer survivors, using machine learning techniques on a large data set., Methods: Data consisted of self-reports of cancer survivors who used a fully automated online application 'Oncokompas' that supports them in their self-management. This is done by 1) monitoring their symptoms through patient reported outcome measures (PROMs); and 2) providing a personalized overview of supportive care options tailored to their scores, aiming to reduce symptom burden and improve health-related quality of life. In the present study, data on 26 generic symptoms (physical and psychosocial) were used. Results of the PROM of each symptom are presented to the user as a no well-being risk, moderate well-being risk, or high well-being risk score. Data of 1032 cancer survivors were analysed using Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) on high risk scores and moderate-to-high risk scores separately., Results: When analyzing the high risk scores, seven clusters were extracted: one main cluster which contained most frequently occurring physical and psychosocial symptoms, and six subclusters with different combinations of these symptoms. When analyzing moderate-to-high risk scores, three clusters were extracted: two main clusters were identified, which separated physical symptoms (and their consequences) and psycho-social symptoms, and one subcluster with only body weight issues., Conclusion: There appears to be an inherent difference on the co-occurrence of symptoms dependent on symptom severity. Among survivors with high risk scores, the data showed a clustering of more connections between physical and psycho-social symptoms in separate subclusters. Among survivors with moderate-to-high risk scores, we observed less connections in the clustering between physical and psycho-social symptoms., (© 2021. The Author(s).)

Background: The role of intestinal microbiota in the pathogenesis of late-onset sepsis (LOS) in preterm infants is largely unexplored but could provide opportunities for microbiota-targeted preventive and therapeutic strategies. We hypothesized that microbiota composition changes before the onset of sepsis, with causative bacteria that are isolated later in blood culture., Methods: This multicenter case-control study included preterm infants born under 30 weeks of gestation. Fecal samples collected from the 5 days preceding LOS diagnosis were analyzed using a molecular microbiota detection technique. LOS cases were subdivided into 3 groups: gram-negative, gram-positive, and coagulase-negative Staphylococci (CoNS)., Results: Forty LOS cases and 40 matched controls were included. In gram-negative LOS, the causative pathogen could be identified in at least 1 of the fecal samples collected 3 days prior to LOS onset in all cases, whereas in all matched controls, this pathogen was absent (P = .015). The abundance of these pathogens increased from 3 days before clinical onset. In gram-negative and gram-positive LOS (except CoNS) combined, the causative pathogen could be identified in at least 1 fecal sample collected 3 days prior to LOS onset in 92% of the fecal samples, whereas these pathogens were present in 33% of the control samples (P = .004). Overall, LOS (expect CoNS) could be predicted 1 day prior to clinical onset with an area under the curve of 0.78., Conclusions: Profound preclinical microbial alterations underline that gut microbiota is involved in the pathogenesis of LOS and has the potential as an early noninvasive biomarker., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Objectives: To assess (I) correlations between diffusion-weighted (DWI), intravoxel incoherent motion (IVIM), dynamic contrast-enhanced (DCE) MRI, and 18 F-FDG-PET/CT imaging parameters capturing tumor characteristics and (II) their predictive value of locoregional recurrence-free survival (LRFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy., Methods: Between 2014 and 2018, patients with histopathologically proven HNSCC, planned for curative (chemo) radiotherapy, were prospectively included. Pretreatment clinical, anatomical, and functional imaging parameters (obtained by DWI/IVIM, DCE-MRI, and 18 F-FDG-PET/CT) were extracted for primary tumors (PT) and lymph node metastases. Correlations and differences between parameters were assessed. The predictive value of LRFS and OS was assessed, performing univariable, multivariable Cox and CoxBoost regression analyses., Results: In total, 70 patients were included. Significant correlations between 18 F-FDG-PET parameters and DWI-/DCE volume parameters were found (r > 0.442, p < 0.002). The combination of HPV (HR = 0.903), intoxications (HR = 1.065), PT ADC GTV (HR = 1.252), K trans (HR = 1.223), and V e (HR = 1.215) was predictive for LRFS (C-index = 0.546; p = 0.023). N-stage (HR = 1.058), HPV positivity (HR = 0.886), hypopharyngeal tumor location (HR = 1.111), ADC GTV (HR = 1.102), ADC mean (HR = 1.137), D* (HR = 0.862), K trans (HR = 1.106), V e (HR = 1.195), SUV max (HR = 1.094), and TLG (HR = 1.433) were predictive for OS (C-index = 0.664; p = 0.046)., Conclusions: Functional imaging parameters, performing DWI/IVIM, DCE-MRI, and 18 F-FDG-PET/CT, yielded complementary value in capturing tumor characteristics. More specific, intoxications, HPV-negative status, large tumor volume-related parameters, high permeability (K trans ), and high extravascular extracellular space (V e ) parameters were predictive for adverse locoregional recurrence-free survival and adverse overall survival. Low cellularity (high ADC) and high metabolism (high SUV) were additionally predictive for decreased overall survival. These different predictive factors added to estimated locoregional and overall survival., Key Points: • Parameters of DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT were able to capture complementary tumor characteristics. • Multivariable analysis revealed that intoxications, HPV negativity, large tumor volume and high vascular permeability (K trans ), and extravascular extracellular space (Ve) were complementary predictive for locoregional recurrence. • In addition to predictive parameters for locoregional recurrence, also high cellularity (low ADC) and high metabolism (high SUV) were complementary predictive for overall survival.

Introduction: Our aim was to study whether systemic metabolites are associated with magnetic resonance imaging (MRI) measures of brain and hippocampal atrophy and white matter hyperintensities (WMH)., Methods: We studied associations of 143 plasma-based metabolites with MRI measures of brain and hippocampal atrophy and WMH in three independent cohorts (n = 3962). We meta-analyzed the results of linear regression analyses to determine the association of metabolites with MRI measures., Results: Higher glucose levels and lower levels of three small high density lipoprotein (HDL) particles were associated with brain atrophy. Higher glucose levels were associated with WMH., Discussion: Glucose levels were associated with brain atrophy and WMH, and small HDL particle levels were associated with brain atrophy. Circulating metabolites may aid in developing future intervention trials., (© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.)

Objectives: Numerous clinical and histopathological characteristics have been associated with malignant transformation (MT) of oral leukoplakia (OL), including classic and differentiated epithelial dysplasia, but MT predictions remain suboptimal. The objective of this study was to determine the annual MT rate of OL and to identify clinicopathological risk factors associated with MT., Patients and Methods: 170 patients with OL were included in this retrospective cohort study, 117 females and 53 males. Follow-up ranged from 12 to 219 months (median 54). The analyzed variables included age, gender, smoking habits, clinical presentation, subsite, size and treatment. In a subgroup of 140 patients, histopathological diagnoses were reviewed with regard to the presence of dysplasia, discerning both classic dysplasia and differentiated dysplasia., Results: MT occurred in 23% of the patients, resulting in an annual MT rate of 4.9% (95% CI: 3.5 - 6.6) which remained consistent. High-risk subsite (tongue and floor of mouth) was the only clinical predictor for MT (Hazard Ratio = 2.7, 95% CI: 1.3 - 5.5, p = 0.007). In 140 patients, classic dysplasia (Hazard Ratio = 7.2, 95% CI: 1.6 - 33.1, p = 0.012) and differentiated dysplasia (Hazard Ratio = 6.6, 95% CI: 1.2 - 25.4, p = 0.026) were predictors for MT. Binary grading between dysplasia and no dysplasia was significant for predicting MT (Hazard Ratio = 6.4, 95% CI: 1.5 - 27.5, p = 0.013)., Conclusion: Since annual MT rate of OL remains stable during follow-up, regular long-term or even life-long follow-up is advocated. Specific oral subsites and epithelial dysplasia are predictors for MT of OL., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tumors, which may be captured by a variety of quantitative features extracted from diagnostic images, termed radiomics. The aim of this study was to develop and validate MRI-based radiomic prognostic models in oral and oropharyngeal cancer., Materials and Methods: Native T1-weighted images of four independent, retrospective (2005-2013), patient cohorts (n = 102, n = 76, n = 89, and n = 56) were used to delineate primary tumors, and to extract 545 quantitative features from. Subsequently, redundancy filtering and factor analysis were performed to handle collinearity in the data. Next, radiomic prognostic models were trained and validated to predict overall survival (OS) and relapse-free survival (RFS). Radiomic features were compared to and combined with prognostic models based on standard clinical parameters. Performance was assessed by integrated area under the curve (iAUC)., Results: In oral cancer, the radiomic model showed an iAUC of 0.69 (OS) and 0.70 (RFS) in the validation cohort, whereas the iAUC in the oropharyngeal cancer validation cohort was 0.71 (OS) and 0.74 (RFS). By integration of radiomic and clinical variables, the most accurate models were defined (iAUC oral cavity, 0.72 (OS) and 0.74 (RFS); iAUC oropharynx, 0.81 (OS) and 0.78 (RFS)), and these combined models outperformed prognostic models based on standard clinical variables only (p < 0.001)., Conclusions: MRI radiomics is feasible in HNSCC despite the known variability in MRI vendors and acquisition protocols, and radiomic features added information to prognostic models based on clinical parameters., Key Points: • MRI radiomics can predict overall survival and relapse-free survival in oral and HPV-negative oropharyngeal cancer. • MRI radiomics provides additional prognostic information to known clinical variables, with the best performance of the combined models. • Variation in MRI vendors and acquisition protocols did not influence performance of radiomic prognostic models.

Background: Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose ( 18 F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy., Methods: Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent 18 F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order 18 F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with 18 F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome., Results: Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764)., Conclusions: Combining HPV-status, first-order 18 F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care., Trial Registration: Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.

Purpose: Children with visual impairment often experience more difficulties regarding participation compared to sighted peers. The Participation and Activity Inventory for Children and Youth (PAI-CY) has recently been developed to assess their participation needs. A novel application in the field of questionnaires is the use of network analysis to explore interrelations between items in order to capture their complex interactions as a reflection of the overall construct of measurement. This study aimed to apply network modeling for the PAI-CY 7-12 from the perspectives of children and their parents., Methods: Children and their parents ( n = 195) completed the 55-item PAI-CY via face-to-face interviews and a web-based survey, respectively. Internal consistency, test-retest reliability, and concordance between children and parents were investigated. Two networks were created, along with visualizations of shared and differential connections between children and parents., Results: Eight items were deleted. Network structures were dissimilar; for children, connections evolved around social contacts and school items, whereas for parents, mobility, leisure time, acceptance, self-reliance, and communication items prevailed. In the children's network, playing imaginary games, inviting a friend to play at home, and estimating the distance from others were most connected to other items., Conclusions: This study uniquely identifies connections between items of the PAI-CY 7-12, highlighting the different perspectives parents and children have on what defines participation, possibly implying that they perceive the relevance of various rehabilitation programs differently., Translational Relevance: Rehabilitation programs aimed at improving the most connected items might positively affect other items in the network, possibly improving children's participation., Competing Interests: Disclosure: E.B.M. Elsman, None; C.F.W. Peeters, None; R.M.A. van Nispen, None; G.H.M.B. van Rens, None, (Copyright 2020 The Authors.)

Background: To assess cross-cultural validity between Dutch and English versions of the FVQ&#95;CYP, a patient-reported outcome measure developed in the United Kingdom (UK) for children and adolescents with (severe) visual impairment or blindness (VI for brevity) to measure functional vision., Methods: The 36-item FVQ&#95;CYP was translated and adapted into Dutch using standard guidelines. The questionnaire was administered to Dutch children and adolescents aged 7-17 years (N = 253) with impaired vision (no restrictions regarding acuity). Data were compared to existing UK data of children and adolescents aged 10-15 years (N = 91) with VI (acuity LogMar worse than 0.48). As with the original UK FVQ&#95;CYP validation, a rating scale model (RSM) was applied to the Dutch data., Results: Minor adaptations were needed in translation-rounds. Significant differences in item responses were found between the Dutch and UK data. Item response theory assumptions were met, but fit to the RSM was unsatisfactory. Therefore, psychometric properties of the Dutch FVQ&#95;CYP were analysed irrespective of the original model and criteria used. A graded response model led to the removal of 12 items due to missing data, low information, overlapping content and limited relevance to Dutch children. Fit indices for the remaining 24 items were adequate., Conclusions: Differences in population characteristics, distribution of responses, non-invariance at the model level and small sample sizes challenged the cross-cultural validation process. However, the Dutch adapted FVQ&#95;CYP showed high measurement precision and broad coverage of items measuring children's functional vision. The underlying reasons for differences between countries in instrument performance are discussed with implications for future studies.

Purpose: During resections of brain tumors, neurosurgeons have to weigh the risk between residual tumor and damage to brain functions. Different perspectives on these risks result in practice variation. We present statistical methods to localize differences in extent of resection between institutions which should enable to reveal brain regions affected by such practice variation., Methods: Synthetic data were generated by simulating spheres for brain, tumors, resection cavities, and an effect region in which a likelihood of surgical avoidance could be varied between institutions. Three statistical methods were investigated: a non-parametric permutation based approach, Fisher's exact test, and a full Bayesian Markov chain Monte Carlo (MCMC) model. For all three methods the false discovery rate (FDR) was determined as a function of the cut-off value for the q-value or the highest density interval, and receiver operating characteristic and precision recall curves were created. Sensitivity to variations in the parameters of the synthetic model were investigated. Finally, all these methods were applied to retrospectively collected data of 77 brain tumor resections in two academic hospitals., Results: Fisher's method provided an accurate estimation of observed FDR in the synthetic data, whereas the permutation approach was too liberal and underestimated FDR. AUC values were similar for Fisher and Bayes methods, and superior to the permutation approach. Fisher's method deteriorated and became too liberal for reduced tumor size, a smaller size of the effect region, a lower overall extent of resection, fewer patients per cohort, and a smaller discrepancy in surgical avoidance probabilities between the different surgical practices. In the retrospective patient data, all three methods identified a similar effect region, with lower estimated FDR in Fisher's method than using the permutation method., Conclusions: Differences in surgical practice may be detected using voxel statistics. Fisher's test provides a fast method to localize differences but could underestimate true FDR. Bayesian MCMC is more flexible and easily extendable, and leads to similar results, but at increased computational cost., Competing Interests: The authors have declared that no competing interests exist.

Despite treatment, immune activation is thought to contribute to cerebral injury in children perinatally infected with human immunodeficiency virus (HIV). We aimed to characterize immune activation in relation to neuroimaging and cognitive outcomes. We therefore measured immunological, coagulation, and neuronal biomarkers in plasma and cerebrospinal fluid (CSF) samples of 34 perinatally HIV-infected children aged 8-18 years, and in plasma samples of 37 controls of comparable age, sex, ethnicity, and socio-economic status. We then compared plasma biomarker levels between groups, and explored associations between plasma/CSF biomarkers and neuroimaging and cognitive outcomes using network analysis. HIV-infected children showed higher plasma levels of C-reactive protein, interferon-gamma, interferon-gamma-inducible protein-10, and monocyte chemoattractant protein-1 than controls. In HIV-infected participants, plasma soluble CD14 was positively associated with microstructural white matter (WM) damage, and plasma D-dimer was negatively associated with WM blood flow. In CSF, IL-6 was negatively associated with WM volume, and neurofilament heavy-chain (NFH) was negatively associated with intelligence quotient and working memory. These markers of ongoing inflammation, immune activation, coagulation, and neuronal damage could be used to further evaluate the pathophysiology and clinical course of cerebral and cognitive deficits in perinatally acquired HIV.

Background: Home-based care networks differ in size and composition, but little is known about the characteristics of care networks for those nearing the end of their lives. This study aimed to identify different types of home-based care networks of community-dwelling older adults in the Netherlands and to assess the association between care network type and the health status and socio-demographic characteristics of care recipients., Methods/design: We used data from participants of the Longitudinal Aging Study Amsterdam (2001-2013) with chronic diseases or functional limitations who died within 12 months of their last interview and received home based personal and/or household care (n = 146). Latent Class Analysis was used to model distinct end-of-life care networks among this pooled cross-section of older people whose characteristics imply care needs. The Akaike information criterion was used to determine the optimal model. Associations between network type and care recipient characteristics were explored using conditional inference trees., Results: We identified four types of care networks; a partner network (19%) in which care was mainly provided by partners, with little care from private caregivers or professionals, a mixed network (25%) in which care was provided by a combination of children, professionals and/or other family members, a private network (15%) in which only privately paid care was provided, and a professional network (40%) in which care was mainly provided by publicly paid professionals, sometimes with additional care from family or privately paid caregivers. Care networks near the end of life showed similar characteristics to those identified for older people more generally, but care seemed to be more intensive in the last year of life compared to the years preceding it. End-of-life care networks were mostly related to age, educational level and partner status. Formal care substitutes informal care whenever there is no partner or child present and able to provide care., Conclusion: Our findings indicate that personal and household care can be quite intensive in the last year of life, especially for partner caregivers. To prevent caregiver burden, it is important that professionals make sure partner caregivers receive adequate and timely support to cope with the care situation.

Background & Aims: Intestinal microbiota is considered to play a crucial role in the aetiology of inflammatory bowel disease (IBD). We aimed to describe faecal microbiota composition and dynamics in a large cohort of children with de novo (naïve) IBD, in comparison to healthy paediatric controls (HC)., Methods: In this prospective study, performed at two tertiary centres, faecal samples from newly diagnosed, treatment-naïve paediatric IBD patients were collected prior to bowel cleansing for colonoscopy (t0) and 1, 3 and 6 weeks and 3 months after initiation of therapy. The microbial profiles of Crohn's disease (CD) and Ulcerative colitis (UC) patients were compared with HC and linked to therapeutic response. Microbiota composition was analysed by IS-pro technology., Results: Microbial profiles of 104 new IBD-patients (63 CD, 41 UC, median age 14.0 years) were compared to 61 HC (median 7.8 years). IBD was mainly characterised by decreased abundance of Alistipes finegoldii and Alistipes putredinis, which characterize a healthy state microbial core. The classifier including these core species as predictors achieved an AUC of the ROC curve of .87. Core bacteria tended to regain abundance during treatment, but did not reach healthy levels., Conclusion: Faecal microbiota profiles of children with de novo CD and UC can be discriminated from HC with high accuracy, mainly driven by a decreased abundance of species shaping the microbial core in the healthy state. Paediatric IBD can therefore be characterized by decreased abundance of certain bacterial species reflecting the healthy state rather than by the introduction of pathogens., Competing Interests: P.H.M. Savelkoul and A.E. Budding have proprietary rights on the IS-pro platform technology and are co-founders of a spin-off company developing this technique into a clinical diagnostic product. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Purpose: Offering self-sampling of cervico-vaginal material for high-risk human papillomavirus (hrHPV) testing is an effective method to increase the coverage in cervical screening programs. Molecular triage directly on hrHPV-positive self-samples for colposcopy referral opens the way to full molecular cervical screening. Here, we set out to identify a DNA methylation classifier for detection of cervical precancer (CIN3) and cancer, applicable to lavage and brush self-samples. Experimental Design: We determined genome-wide DNA methylation profiles of 72 hrHPV-positive self-samples, using the Infinium Methylation 450K Array. The selected DNA methylation markers were evaluated by multiplex quantitative methylation-specific PCR (qMSP) in both hrHPV-positive lavage ( n = 245) and brush ( n = 246) self-samples from screening cohorts. Subsequently, logistic regression analysis was performed to build a DNA methylation classifier for CIN3 detection applicable to self-samples of both devices. For validation, an independent set of hrHPV-positive lavage ( n = 199) and brush ( n = 287) self-samples was analyzed. Results: Genome-wide DNA methylation profiling revealed 12 DNA methylation markers for CIN3 detection. Multiplex qMSP analysis of these markers in large series of lavage and brush self-samples yielded a 3-gene methylation classifier ( ASCL1, LHX8, and ST6GALNAC5 ). This classifier showed a very good clinical performance for CIN3 detection in both lavage (AUC = 0.88; sensitivity = 74%; specificity = 79%) and brush (AUC = 0.90; sensitivity = 88%; specificity = 81%) self-samples in the validation set. Importantly, all self-samples from women with cervical cancer scored DNA methylation-positive. Conclusions: By genome-wide DNA methylation profiling on self-samples, we identified a highly effective 3-gene methylation classifier for direct triage on hrHPV-positive self-samples, which is superior to currently available methods. Clin Cancer Res; 24(14); 3456-64. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Introduction: Identifying circulating metabolites that are associated with cognition and dementia may improve our understanding of the pathogenesis of dementia and provide crucial readouts for preventive and therapeutic interventions., Methods: We studied 299 metabolites in relation to cognition (general cognitive ability) in two discovery cohorts (N total = 5658). Metabolites significantly associated with cognition after adjusting for multiple testing were replicated in four independent cohorts (N total = 6652), and the associations with dementia and Alzheimer's disease (N = 25,872) and lifestyle factors (N = 5168) were examined., Results: We discovered and replicated 15 metabolites associated with cognition including subfractions of high-density lipoprotein, docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. These associations were independent of classical risk factors including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and apolipoprotein E (APOE) genotypes. Six of the cognition-associated metabolites were related to the risk of dementia and lifestyle factors., Discussion: Circulating metabolites were consistently associated with cognition, dementia, and lifestyle factors, opening new avenues for prevention of cognitive decline and dementia., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Identification of blood-based metabolic changes might provide early and easy-to-obtain biomarkers., Methods: We included 127 Alzheimer's disease (AD) patients and 121 control subjects with cerebrospinal fluid biomarker-confirmed diagnosis (cutoff tau/amyloid β peptide 42: 0.52). Mass spectrometry platforms determined the concentrations of 53 amine compounds, 22 organic acid compounds, 120 lipid compounds, and 40 oxidative stress compounds. Multiple signatures were assessed: differential expression (nested linear models), classification (logistic regression), and regulatory (network extraction)., Results: Twenty-six metabolites were differentially expressed. Metabolites improved the classification performance of clinical variables from 74% to 79%. Network models identified five hubs of metabolic dysregulation: tyrosine, glycylglycine, glutamine, lysophosphatic acid C18:2, and platelet-activating factor C16:0. The metabolite network for apolipoprotein E ( APOE ) ε4 negative AD patients was less cohesive compared with the network for APOE ε4 positive AD patients., Discussion: Multiple signatures point to various promising peripheral markers for further validation. The network differences in AD patients according to APOE genotype may reflect different pathways to AD.

Too much sitting (extended sedentary time) is recognized as a public health concern in Europe and beyond. Time spent sedentary is influenced and conditioned by clusters of individual-level and contextual (upstream) factors. Identifying population subgroups that sit too much could help to develop targeted interventions to reduce sedentary time. We explored the relative importance of socio-demographic correlates of sedentary time in adults across Europe. We used data from 26,617 adults who participated in the 2013 Special Eurobarometer 412 "Sport and physical activity". Participants from all 28 EU Member States were randomly selected and interviewed face-to-face. Self-reported sedentary time was dichotomized into sitting less or >7.5h/day. A Chi-squared Automatic Interaction Detection (CHAID) algorithm was used to create a tree that hierarchically partitions the data on the basis of the independent variables (i.e., socio-demographic factors) into homogeneous (sub)groups with regard to sedentary time. This allows for the tentative identification of population segments at risk for unhealthy sedentary behaviour. Overall, 18.5% of the respondents reported sitting >7.5h/day. Occupation was the primary discriminator. The subgroup most likely to engage in extensive sitting were higher educated, had white-collar jobs, reported no difficulties with paying bills, and used the internet frequently. Clear socio-demographic profiles were identified for adults across Europe who engage in extended sedentary time. Furthermore, physically active participants were consistently less likely to engage in longer daily sitting times. In general, those with more indicators of higher wealth were more likely to spend more time sitting., (Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: Detecting functional decline from normal aging to dementia is relevant for diagnostic and prognostic purposes. Therefore, the Amsterdam IADL Questionnaire (A-IADL-Q) was developed: a 70-item proxy-based tool with good psychometric properties. We aimed to design a short version while preserving its psychometric quality., Methods: Study partners of subjects ( n  = 1355), ranging from cognitively normal to dementia subjects, completed the original A-IADL-Q. We selected the short version items using a stepwise procedure combining missing data, Item Response Theory, and input from respondents and experts. We investigated internal consistency of the short version and concordance with the original version. To assess its construct validity, we additionally investigated concordance between the short version and the Mini-Mental State Examination (MMSE) and Disability Assessment for Dementia (DAD). Finally, we investigated differences in instrumental activities of daily living (IADL) scores between diagnostic groups across the dementia spectrum., Results: We selected 30 items covering the entire spectrum of IADL functioning. Internal consistency (0.98) and concordance with the original version (0.97) were very high. Concordance with the MMSE (0.72) and DAD (0.87) scores was high. IADL impairment scores increased across the spectrum from normal cognition to dementia., Discussion: The A-IADL-Q short version (A-IADL-Q-SV) consists of 30 items and has maintained the psychometric quality of the original A-IADL-Q. As such, the A-IADL-Q-SV is a concise measure of functional decline.