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Abstract Inflammation is an important factor in Alzheimer’s disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman’s correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer’s Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman’s correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3–9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.

Abstract Background Early evidence that patients with (multiple) pre-existing diseases are at highest risk for severe COVID-19 has been instrumental in the pandemic to allocate critical care resources and later vaccination schemes. However, systematic studies exploring the breadth of medical diagnoses are scarce but may help to understand severe COVID-19 among patients at supposedly low risk. Methods We systematically harmonized >12 million primary care and hospitalisation health records from ~500,000 UK Biobank participants into 1448 collated disease terms to systematically identify diseases predisposing to severe COVID-19 (requiring hospitalisation or death) and its post-acute sequalae, Long COVID. Results Here we identify 679 diseases associated with an increased risk for severe COVID-19 (n = 672) and/or Long COVID (n = 72) that span almost all clinical specialties and are strongly enriched in clusters of cardio-respiratory and endocrine-renal diseases. For 57 diseases, we establish consistent evidence to predispose to severe COVID-19 based on survival and genetic susceptibility analyses. This includes a possible role of symptoms of malaise and fatigue as a so far largely overlooked risk factor for severe COVID-19. We finally observe partially opposing risk estimates at known risk loci for severe COVID-19 for etiologically related diseases, such as post-inflammatory pulmonary fibrosis or rheumatoid arthritis, possibly indicating a segregation of disease mechanisms. Conclusions Our results provide a unique reference that demonstrates how 1) complex co-occurrence of multiple – including non-fatal – conditions predispose to increased COVID-19 severity and 2) how incorporating the whole breadth of medical diagnosis can guide the interpretation of genetic risk loci.

Abstract In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. We predicted microbial formate as well as other microbial metabolites, which could alter urine formate production in the host-microbiome personalised models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

Summary: Metabolism oscillates between catabolic and anabolic states depending on food intake, exercise, or stresses that change a multitude of metabolic pathways simultaneously. We present the HuMet Repository for exploring dynamic metabolic responses to oral glucose/lipid loads, mixed meals, 36-h fasting, exercise, and cold stress in healthy subjects. Metabolomics data from blood, urine, and breath of 15 young, healthy men at up to 56 time points are integrated and embedded within an interactive web application, enabling researchers with and without computational expertise to search, visualize, analyze, and contextualize the dynamic metabolite profiles of 2,656 metabolites acquired on multiple platforms. With examples, we demonstrate the utility of the resource for research into the dynamics of human metabolism, highlighting differences and similarities in systemic metabolic responses across challenges and the complementarity of metabolomics platforms. The repository, providing a reference for healthy metabolite changes to six standardized physiological challenges, is freely accessible through a web portal.

Abstract Sex disparities in serum bile acid (BA) levels and Alzheimer's disease (AD) prevalence have been established. However, the precise link between changes in serum BAs and AD development remains elusive. Here, authors quantitatively determined 33 serum BAs and 58 BA features in 4 219 samples collected from 1 180 participants from the Alzheimer's Disease Neuroimaging Initiative. The findings revealed that these BA features exhibited significant correlations with clinical stages, encompassing cognitively normal (CN), early and late mild cognitive impairment, and AD, as well as cognitive performance. Importantly, these associations are more pronounced in men than women. Among participants with progressive disease stages (n = 660), BAs underwent early changes in men, occurring before AD. By incorporating BA features into diagnostic and predictive models, positive enhancements are achieved for all models. The area under the receiver operating characteristic curve improved from 0.78 to 0.91 for men and from 0.76 to 0.83 for women for the differentiation of CN and AD. Additionally, the key findings are validated in a subset of participants (n = 578) with cerebrospinal fluid amyloid‐beta and tau levels. These findings underscore the role of BAs in AD progression, offering potential improvements in the accuracy of AD prediction.

Abstract Integration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimer’s disease. Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain. In the current manuscript, using metabolomics-proteomics data integration, we describe new associations between peripheral and central lipid mediators, with the above-described CSF protein panels. Particularly strong associations were observed between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and proteins involved in glycolysis, blood coagulation, and vascular inflammation and the regulators of extracellular matrix. Those metabolic associations were not observed at the gene-co-expression level in the central nervous system. In summary, this manuscript provides new information regarding Alzheimer’s disease, linking both central and peripheral metabolism, and illustrates the necessity for the “omics” data integration to uncover associations beyond gene co-expression.

Abstract A meteorologically challenging situation that represents a demanding control task (rotational speed, pitch and yaw) for a wind turbine is presented and its implementation in a simulation is described. A high‐fidelity numerical process chain, consisting of the computational fluid dynamics (CFD) solver FLOWer, the multi‐body system (MBS) software SIMPACK and the Ffowcs Williams‐Hawkings code ACCO, is used. With it, the aerodynamic, servoelastic and aeroacoustic (

Abstract INTRODUCTION In September 2022, The Jackson Laboratory Center for Alzheimer's and Dementia Research (JAX CADR) hosted a workshop with leading researchers in the Alzheimer's disease and related dementias (ADRD) field. METHODS During the workshop, the participants brainstormed new directions to overcome current barriers to providing patients with effective ADRD therapeutics. The participants outlined specific areas of focus. Following the workshop, each group used standard literature search methods to provide background for each topic. RESULTS The team of invited experts identified four key areas that can be collectively addressed to make a significant impact in the field: (1) Prioritize the diversification of disease targets, (2) enhance factors promoting resilience, (3) de‐risk clinical pipeline, and (4) centralize data management. DISCUSSION In this report, we review these four objectives and propose innovations to expedite ADRD therapeutic pipelines.

Complementary multi-omics approach, in silico metabolic flux, and neuroimaging analyses link the sphingolipid pathway to Alzheimer’s disease pathogenesis with therapeutic targets validated using behavioral assessments in amyloidogenic APP/PS1 mice.

Summary: SORL1 is implicated in the pathogenesis of Alzheimer’s disease (AD) through genetic studies. To interrogate the roles of SORL1 in human brain cells, SORL1-null induced pluripotent stem cells (iPSCs) were differentiated to neuron, astrocyte, microglial, and endothelial cell fates. Loss of SORL1 leads to alterations in both overlapping and distinct pathways across cell types, with the greatest effects in neurons and astrocytes. SORL1 loss induces a neuron-specific reduction in apolipoprotein E (APOE) and clusterin (CLU) and altered lipid profiles. Analyses of iPSCs derived from a large cohort reveal a neuron-specific association between SORL1, APOE, and CLU levels, a finding validated in postmortem brain. Enhancement of retromer-mediated trafficking rescues tau phenotypes observed in SORL1-null neurons but does not rescue APOE levels. Pathway analyses implicate transforming growth factor β (TGF-β)/SMAD signaling in SORL1 function, and modulating SMAD signaling in neurons alters APOE RNA levels in a SORL1-dependent manner. Taken together, these data provide a mechanistic link between strong genetic risk factors for AD.

This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. In this study, GBR and an unmanned aerial vehicle (UAV) monitor a two-span bridge in Germany to gather ground-truth data. Based on the UAV data, we determine vehicle type, lane, locus, speed, axle count, and axle spacing for single-presence vehicle crossings. Since displacement is a global response, using peak detection like conventional strain-based BWIMs is challenging. Therefore, we investigate data-driven machine learning approaches to extract the vehicle configurations directly from the displacement data. Despite a small and imbalanced real-world dataset, the proposed approaches classify, e.g., the axle count for trucks with a balanced accuracy of 76.7% satisfyingly. Additionally, we demonstrate that, for the selected bridge, high-frequency vibrations can coincide with axles crossing the junction between the street and the bridge. We evaluate whether filtering approaches via bandpass filtering or wavelet transform can be exploited for axle count and axle spacing identification. Overall, we can show that GBR is a serious contender for BWIM systems.

Dysregulation of lipid metabolism is associated with coronary artery disease (CAD). Here, the authors perform GWAS of the serum lipidome to identify variants associated with lipid species that are putatively in the mechanistic pathway to CAD.

The effectiveness of the multimodal Telemedical Lifestyle Intervention Program (TeLIPro) was proven in the advanced stages of type 2 diabetes mellitus (T2DM). Since its therapeutic potential focusing on telemedical coaching without using a formula diet is unknown, we evaluated improvements in HbA1c, HbA1c normalisation rate, cardiometabolic risk factors, quality-of-life, and eating behaviour in real life. In this randomized-controlled trial, AOK Rhineland/Hamburg insured T2DM patients (n = 1163) were randomized (1:1) into two parallel groups, and 817 received the allocated intervention. In addition to routine care, all participants got scales, step counters, and access to an online portal. The TeLIPro group additionally received equipment for self-monitoring of blood glucose and telemedical coaching. Data were collected at baseline, after 6 and 12 months of intervention as well as after a 6-month follow-up. The primary endpoint after 12 months was (i) the estimated treatment difference (ETD) in HbA1c change and (ii) the HbA1c normalisation rate in those with diabetes duration < 5 years. The TeLIPro group demonstrated significantly stronger improvements in HbA1c (ETD −0.4% (−0.5; −0.2); p < 0.001), body weight, body-mass-index, quality-of-life, and eating behaviour, especially in T2DM patients with diabetes duration ≥ 5 years (ETD −0.5% (−0.7; −0.3); p < 0.001). The HbA1c normalisation rate did not significantly differ between groups (25% vs. 18%). Continuous addition of TeLIPro to routine care is effective in improving HbA1c and health-related lifestyle in T2DM patients with longer diabetes duration in real life.

This paper introduces the Early Chinese Periodicals Online database (ECPO), based at the University of Heidelberg. It offers a short overview of the development of this research-driven database as it grew to incorporate additional projects. Today, the ECPO hosts a variety of textual and visual sources from the Republican period (1912 – 1949), as well as biographical data of twentieth-century academic and political elites. We aim to show how this database can be used and extended to pursue historical network research, even for scholars previously unfamiliar with digital infrastructures. The concluding part discusses privacy concerns in data curation and management, which are increasingly relevant for studies of twentieth-century actors and limit the potential to release and reuse these datasets, especially if they pertain to the People’s Republic of China’s political history.

Abstract Cognitive decline is associated with both normal aging and early pathologies leading to dementia. Here we used quantitative profiling of metabolites involved in the regulation of inflammation, vascular function, neuronal function and energy metabolism, including oxylipins, endocannabinoids, bile acids, and steroid hormones to identify metabolic biomarkers of mild cognitive impairment (MCI). Serum samples (n = 212) were obtained from subjects with or without MCI opportunistically collected with incomplete fasting state information. To maximize power and stratify the analysis of metabolite associations with MCI by the fasting state, we developed an algorithm to predict subject fasting state when unknown (n = 73). In non-fasted subjects, linoleic acid and palmitoleoyl ethanolamide levels were positively associated with perceptual speed. In fasted subjects, soluble epoxide hydrolase activity and tauro-alpha-muricholic acid levels were negatively associated with perceptual speed. Other cognitive domains showed associations with bile acid metabolism, but only in the non-fasted state. Importantly, this study shows unique associations between serum metabolites and cognitive function in the fasted and non-fasted states and provides a fasting state prediction algorithm based on measurable metabolites.

Academic research about digital non-Latin script (hereafter: NLS) research data can pose a number of challenges just because the material is from a region where the Latin alphabet was not used. Not all of them are easy to spot. In this paper, I introduce two use cases to demonstrate different aspects of the complex tasks that may be related to NLS material. The first use case focuses on metadata standards used to describe NLS material. Taking the VRA Core 4 XML as example, I will show where we found limitations for NLS material and how we were able to overcome them by expanding the standard. In the second use case, I look at the research data itself. Although the full-text digitization of western newspapers from the 20th century usually is not problematic anymore, this is not the case for Chinese newspapers from the Republican era (1912–1949). A major obstacle here is the dense and complex layout of the pages, which prevents OCR solutions from getting to the character recognition part. In our approach, we are combining different manual and computational methods like crowdsourcing, pattern recognition, and neural networks to be able to process the material in a more efficient way. The two use cases illustrate that data standards or processing methods that are established and stable for Latin script material may not always be easily adopted to non-Latin script research data.Des recherches académiques sur les recherches de textes numériques qui ne sont pas en alphabet latin (désormais NLS) peuvent poser plusieurs défis, car le matériel vient d’une région où l’alphabet latin n’était pas utilisé. Ils ne sont pas tous faciles à trouver. Dans cet article, je vais présenter deux cas d’utilisation pour démontrer les différents aspects des tâches complexes qui pourraient être reliées au matériel NLS. Le premier cas d’utilisation focus sur les standards de métadonnées utilisés pour décrire le matériel NLS. En prenant comme exemple le VRA Core 4 XML, je montre où se trouvent les limitations pour le matériel NLS et comment nous sommes capables de les surmonter en augmentant les standards. Pour le deuxième cas d’utilisation, je regarde les données de recherches elles-mêmes. Même si la numérisation de textes complets de journaux occidentaux du 20e siècle n’est plus problématique, ce n’est pas le cas pour les journaux chinois de l’ère républicaine (1912-1949). Un obstacle majeur est la densité et la complexité de la mise en page, ce qui empêche les solutions OCR (reconnaissance optique de caractères) de se rendre à la partie de reconnaissance des caractères. Dans notre approche, nous avons combiné des méthodes manuelles et computationnelles différentes comme l’externalisation ouverte (crowdsourcing), la reconnaissance de motifs, et le réseau neuronal pour procéder au matériel de manière plus efficace. Les deux cas d’utilisations démontrent que les données standards ou les méthodes de traitement qui sont établies et stables pour le matériel en alphabet latin ne peuvent être utilisées facilement pour des données qui ne sont pas en alphabet latin.

# Background Timely diagnosis of HIV in infants and children is an urgent priority. In Malawi, 40,000 infants annually are HIV exposed. However, gold standard polymerase-chain-reaction (PCR) based testing requires centralised laboratories, causing turn-around times (TAT) of 2 to 3 months and significant loss to follow-up. If feasible and acceptable, minimising diagnostic delays through HIV Point-of-care-testing (POCT) may be cost-effective. We assessed whether POCT Cepheid Xpert HIV-1 Qual assay whole blood (XpertHIV) was more cost-effective than PCR. # Methods From July-August 2018, 700 PCR Abbott tests using dried blood spots (DBS) were performed on 680 participants who enrolled on the feasibility, acceptability and performance of the XpertHIV study. Newly identified HIV-positive DBS from the 680 participants were retested, so with confirmatory testing of the HIV-positive cases, 700 tests were performed. We conducted a cost-minimisation and cost-effectiveness analysis of XpertHIV against PCR, as the standard of care. A random sample of 200 caregivers from the 680 participants had semi-structured interviews to explore costs from a societal perspective of XpertHIV at Mulanje District Hospital, Malawi. Analysis used TAT as the primary outcome measure. Results were extrapolated from the study period (29 days) to a year (240 working days). Sensitivity analyses characterised individual and joint parameter uncertainty and estimated patient cost per test. # Results During the study period, XpertHIV was cost-minimising at \$42.34 per test compared to \$66.66 for PCR. Over a year, XpertHIV remained cost-minimising at \$16.12 compared to PCR at \$27.06. From the patient perspective (travel, food, lost productivity), the cost per test of XpertHIV was \$2.45. XpertHIV had a mean TAT of 7.10 hours compared to 153.15 hours for PCR. Extrapolates accounting for equipment costs, lab consumables and losses to follow up estimated annual savings of \$2,193,538.88 if XpertHIV is used nationally, as opposed to PCR. # Conclusions This preliminary evidence suggests that adopting POCT XpertHIV will save time, allowing HIV-exposed infants to receive prompt care and may improve outcomes. The Malawi government will pay less due to XpertHIV's cost savings and associated benefits.

Abstract Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines—including arginine, proline, and methionine sulfoxide—were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (

Abstract Background The health care situation of geriatric patients is often multifaceted, complex and often overlaps with social living conditions. Due to the lack of cross-sectoral and interprofessional health care geriatric patients often, receive insufficient care. Only a holistic view enables a comprehensive evaluation of the complex health risks, but also the potential to preserve the health of geriatric patients. The implementation of cross-sectoral, multi-professional case management could reduce the gaps in care, improve the autonomy of the geriatric patients in their own homes, and allow them to retain it as long as possible. The “RubiN” project examines the effects of multi-professional, cross-sectoral and assessment-based case management on the quality of the care of geriatric patients. The results of the study aim to show whether geriatric patients receive better care using case management than patients who receive standard health care. In addition, data on the effects of case management on practices of general practitioners (GP), the satisfaction with the care concept amongst the case managers, patients and relatives will be collected. Furthermore, a health economic analysis will be carried out. Methods The project is designed as a prospective controlled study and compares geriatric patients from practice networks in different regions in Germany. Inclusion criteria are: Age ≥ 70 years and care requirements from two different care complexes (identified with the screening instrument ‘Angelina’-questionnaire). The intervention is the use of a geriatric case management, where health care is organised based on patient-specific care requirements. Five practice networks of physicians will implement the intervention (n = 3200 patients) and three practice networks will serve as the control group (n = 1200 patients). The primary endpoint is the ability to manage activities of daily living, measured using the Barthel Index. The patients in the intervention group receive geriatric case management and the patients in the control networks receive standard care (“care as usual”). The analysis of the primary data, which is pseudonymised, occurs according to the intention-to-treat principle. For this purpose, the endpoints will be analysed using a group comparison after 12 months. For the health economic analysis, secondary data from the statutory health insurance providers will be included in the analysis, in addition to the primary data. Data for the analysis of the effects the concept has on the GP practices as well as on the satisfaction of the project participants will be collected with questionnaires and interviews with experts. Discussion The implementation of cross-sectoral and interdisciplinary geriatric case management has been a topic of discussion for years, whereby positive effects have already been-shown. This planned study will be the first evaluation of the effect of case management for geriatric patients with a very large sample. In addition, the effects of case management on the GP practices and also on the relatives of the geriatric patients will be shown. It is intended that the study results pave the way for a widespread implementation of this concept. Trial registration German Clinical Trials Register, ID: DRKS00016642 . Registered on 29 October 2019 - Retrospectively registered.

The onset and pathology of Alzheimer’s disease (AD) is associated with changes to lipid metabolism. Here, the authors analysed 569 lipids from 32 classes and subclasses in two independent patient cohorts to identify key lipid pathways to link the plasma lipidome with AD and the future onset of AD.

Sex and the APOE ε4 genotype are important risk factors for late-onset Alzheimer’s disease. In the current study, the authors investigate how sex and APOE ε4 genotype modify the association between Alzheimer’s disease biomarkers and metabolites in serum.

Abstract Introduction Comorbidity with metabolic diseases indicates that lipid metabolism plays a role in the etiology of Alzheimer's disease (AD). Comprehensive lipidomic analysis can provide new insights into the altered lipid metabolism in AD. Method In this study, a total 349 serum lipids were measured in 806 participants enrolled in the Alzheimer's Disease Neuroimaging Initiative Phase 1 cohort and analyzed using lipid‐set enrichment statistics, a data mining method to find coregulated lipid sets. Results We found that sets of blood lipids were associated with current AD biomarkers and with AD clinical symptoms. AD diagnosis was associated with 7 of 28 lipid sets of which four also correlated with cognitive decline, including polyunsaturated fatty acids. Cerebrospinal fluid amyloid beta (Aβ1‐42) correlated with glucosylceramides, lysophosphatidylcholines and unsaturated triacylglycerides; cerebrospinal fluid total tau and brain atrophy correlated with monounsaturated sphingomyelins and ceramides, in addition to EPA‐containing lipids. Discussion AD‐associated lipid sets indicated that lipid desaturation, elongation, and acyl chain remodeling processes are disturbed in AD subjects. Monounsaturated lipid metabolism was important in early stages of AD, whereas the polyunsaturated lipid metabolism was associated with later stages of AD. Our study provides several new hypotheses for studying the role of lipid metabolism in AD.

Abstract Setting out a health benefits package (HBP) of interventions to be prioritised for funding is an important step towards achieving universal health coverage in low and middle income countries. The 3rd version of the Disease Control Priorities (DCP3) database, and other similar databases, aim to establishing a single point of reference (“one stop shop”) for cost effectiveness evidence to inform HBP design and other policy making. We reflect upon our experiences in using DCP3 for HBP design and offer suggestions for improving the future reporting of cost-effectiveness evidence. We appraise DCP3 based on generalisability, level of detail, and accessibility. We find that DCP and similar initiatives should be commended for the systematic assessment of a vast array of cost-effectiveness studies—the magnitude of such an endeavour is impressive in its own right. However, there are flaws. In future, providing disaggregated estimates of costs and effects, quantifying uncertainty, and systematically assessing the context in which estimates apply would make this evidence more useful for decision makers.

Abstract Background Thoroughly annotated data resources are a key requirement in phenotype dependent analysis and diagnosis of diseases in the area of precision medicine. Recent work has shown that curation and systematic annotation of human phenome data can significantly improve the quality and selectivity for the interpretation of inherited diseases. We have therefore developed PhenoDis, a comprehensive, manually annotated database providing symptomatic, genetic and imprinting information about rare cardiac diseases. Results PhenoDis includes 214 rare cardiac diseases from Orphanet and 94 more from OMIM. For phenotypic characterization of the diseases, we performed manual annotation of diseases with articles from the biomedical literature. Detailed description of disease symptoms required the use of 2247 different terms from the Human Phenotype Ontology (HPO). Diseases listed in PhenoDis frequently cover a broad spectrum of symptoms with 28% from the branch of ‘cardiovascular abnormality’ and others from areas such as neurological (11.5%) and metabolism (6%). We collected extensive information on the frequency of symptoms in respective diseases as well as on disease-associated genes and imprinting data. The analysis of the abundance of symptoms in patient studies revealed that most of the annotated symptoms (71%) are found in less than half of the patients of a particular disease. Comprehensive and systematic characterization of symptoms including their frequency is a pivotal prerequisite for computer based prediction of diseases and disease causing genetic variants. To this end, PhenoDis provides in-depth annotation for a complete group of rare diseases, including information on pathogenic and likely pathogenic genetic variants for 206 diseases as listed in ClinVar. We integrated all results in an online database ( http://mips.helmholtz-muenchen.de/phenodis/ ) with multiple search options and provide the complete dataset for download. Conclusion PhenoDis provides a comprehensive set of manually annotated rare cardiac diseases that enables computational approaches for disease prediction via decision support systems and phenotype-driven strategies for the identification of disease causing genes.

Abstract Background The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. Methods A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Results Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. Conclusion This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.

Individual genetic variation can affect the levels of protein in blood, but detailed data sets linking these two types of data are rare. Here, the authors carry out a genome-wide association study of levels of over a thousand different proteins, and describe many new SNP-protein interactions.

ObjectivesRisk stratification has so far been evaluated under the assumption that women fully adhere to screening recommendations. However, the participation in German cancer screening programs remains low at 54%. The question arises whether risk-stratified screening is economically efficient under the assumption that adherence is not perfect.MethodWe have adapted a micro-simulation Markov model to the German context. Annual, biennial, and triennial routine screening are compared with five risk-adapted strategies using thresholds of relative risk to stratify screening frequencies. We used three outcome variables (mortality reduction, quality-adjusted life years, and false-positive results) under the assumption of full adherence vs. an adherence rate of 54%. Strategies are evaluated using efficiency frontiers and probabilistic sensitivity analysis (PSA).ResultsThe reduced adherence rate affects both performance and cost; incremental cost-effectiveness ratios remain constant. The results of PSA show that risk-stratified screening strategies are more efficient than biennial routine screening under certain conditions. At any willingness-to-pay (WTP), there is a risk-stratified alternative with a higher likelihood of being the best choice. However, without explicit decision criteria and WTP, risk-stratified screening is not more efficient than biennial routine screening. Potential improvements in the adherence rates have significant health gains and budgetary implications.ConclusionIf the participation rate for mammographic screening is as low as in Germany, stratified screening is not clearly more efficient than routine screening but dependent on the WTP. A more promising design for future stratified strategies is the combination of risk stratification mechanisms with interventions to improve the low adherence in selected high-risk groups.

BACKGROUND:The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. METHODS AND FINDINGS:Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and "asymptomatic Alzheimer's disease" (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes-sphingolipids and glycerophospholipids-that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer's Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of each metabolite to severity of AD pathology and disease progression (Endophenotype Association Score in Early Alzheimer's Disease [EASE-AD]). Finally, we mapped the main metabolite classes emerging from our analyses to key biological pathways implicated in AD pathogenesis. We found that distinct sphingolipid species including sphingomyelin (SM) with acyl residue sums C16:0, C18:1, and C16:1 (SM C16:0, SM C18:1, SM C16:1) and hydroxysphingomyelin with acyl residue sum C14:1 (SM (OH) C14:1) were consistently associated with severity of AD pathology at autopsy and AD progression across prodromal and preclinical stages. Higher log-transformed blood concentrations of all four sphingolipids in cognitively normal individuals were significantly associated with increased risk of future conversion to incident AD: SM C16:0 (hazard ratio [HR] = 4.430, 95% confidence interval [CI] = 1.703-11.520, p = 0.002), SM C16:1 (HR = 3.455, 95% CI = 1.516-7.873, p = 0.003), SM (OH) C14:1 (HR = 3.539, 95% CI = 1.373-9.122, p = 0.009), and SM C18:1 (HR = 2.255, 95% CI = 1.047-4.855, p = 0.038). The sphingolipid species identified map to several biologically relevant pathways implicated in AD, including tau phosphorylation, amyloid-β (Aβ) metabolism, calcium homeostasis, acetylcholine biosynthesis, and apoptosis. Our study has limitations: the relatively small number of brain tissue samples may have limited our power to detect significant associations, control for heterogeneity between groups, and replicate our findings in independent, autopsy-derived brain samples. CONCLUSIONS:We present a novel framework to identify biologically relevant brain and blood metabolites associated with disease pathology and progression during the prodromal and preclinical stages of AD. Our results show that perturbations in sphingolipid metabolism are consistently associated with endophenotypes across preclinical and prodromal AD, as well as with AD pathology at autopsy. Sphingolipids may be biologically relevant biomarkers for the early detection of AD, and correcting perturbations in sphingolipid metabolism may be a plausible and novel therapeutic strategy in AD.

Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases.

In this paper, we discuss the possibilities as well as the added value of using a web-based databank for video annotation (Pan.do/ra) in cultural studies research on film. The first part demonstrates a variety of potential uses through the example of a music video, and the second part introduces the software on a more general level.

Nature Communications 8: Article number: 14357 (2017); Published 27 February 2017; Updated 11 April 2017 The original version of the Supplementary Information attached to this Article did not include Supplementary Note 1 The HTML has now been updated to include a corrected version of the Supplementary Information.

Genome-wide association studies (GWAS) have become an effective tool to map genes and regions contributing to multifactorial human diseases and traits. A comparably small number of variants identified by GWAS are known to have a direct effect on protein structure whereas the majority of variants is thought to exert their moderate influences on the phenotype through regulatory changes in mRNA expression. MicroRNAs (miRNAs) have been identified as powerful posttranscriptional regulators of mRNAs. Binding to their target sites, which are mostly located within the 3'-untranslated region (3'-UTR) of mRNA transcripts, they modulate mRNA expression and stability. Until today almost all human mRNA transcripts are known to harbor at least one miRNA target site with an average of over 20 miRNA target sites per transcript. Among 5,101 GWAS-identified sentinel single nucleotide polymorphisms (SNPs) that correspond to 18,884 SNPs in linkage disequilibrium (LD) with the sentinels (r2 ≥ 0.8) we identified a significant overrepresentation of SNPs that affect the 3'-UTR of genes (OR = 2.33, 95% CI = 2.12-2.57, P < 10(-52)). This effect was even stronger considering all SNPs in one LD bin a single signal (OR = 4.27, 95% CI = 3.84-4.74, P < 10(-114)). Based on crosslinking immunoprecipitation data we identified four mechanisms affecting miRNA regulation by 3'-UTR mutations: (i) deletion or (ii) creation of miRNA recognition elements within validated RNA-induced silencing complex binding sites, (iii) alteration of 3'-UTR splicing leading to a loss of binding sites, and (iv) change of binding affinity due to modifications of 3'-UTR folding. We annotated 53 SNPs of a total of 288 trait-associated 3'-UTR SNPs as mediating at least one of these mechanisms. Using a qualitative systems biology approach, we demonstrate how our findings can be used to support biological interpretation of GWAS results as well as to provide new experimentally testable hypotheses.