Identifying individuals at-risk of developing Parkinson's disease using a population-based recruitment strategy: The Healthy Brain Ageing Kassel Study.

Neurodegeneration in Parkinson's disease (PD) occurs before motor features develop: assessing risk factors and identifying prodromal markers is necessary to recruit prodromal cohorts, improve early diagnosis, and develop preventive therapies. As part of Healthy Brain Ageing (HeBA), we implemented a stepwise, population-based screening to identify people at high risk of developing PD. Residents (n = 158,818; 50-80 years) in and around Kassel, Germany were invited to complete an online survey with questions for prodromal symptoms and risk factors.

Deciphering shared molecular dysregulation across Parkinson's disease variants using a multi-modal network-based data integration and analysis.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with no effective treatment. Advances in neuroscience and systems biomedicine now enable the use of complex patient-specific in vitro disease models and cutting-edge computational tools for data integration, enhancing our understanding of complex PD mechanisms. To explore common biomedical features across monogenic PD forms, we developed a knowledge graph (KG) by integrating previously published high-content imaging and RNA sequencing data of PD patient-specific midbrain organoids harbouring LRRK2-G2019S, SNCA triplication, GBA-N370S or MIRO1-R272Q mutations with publicly available biological data.

COBREXA 2: tidy and scalable construction of complex metabolic models.

Summary: Constraint-based metabolic models offer a scalable framework to investigate biological systems using optimality principles. Construction and simulation of detailed models that utilize multiple kinds of constraint systems pose a significant coding overhead, complicating implementation of new types of analyses. We present an improved version of the constraint-based metabolic modeling package COBREXA, which utilizes a hierarchical model construction framework that decouples the implemented analysis algorithms into independent, yet re-combinable, building blocks.

Lessons learned from the COVID-19 pandemic: identifying hesitant groups and exploring reasons for vaccination hesitancy, from adolescence to late adulthood.

Introduction: The COVID-19 (COronaVIrus Disease-2019) pandemic highlighted the importance of assessing the rationales behind vaccine hesitancy for the containment of pandemics. In this nationwide study, representative of the Luxembourgish population, we identified hesitant groups from adolescence to late adulthood and explored motivations both for and against vaccination.

Methods: We combined data collected via online surveys for the CON-VINCE (COvid-19 National survey for assessing VIral spread by Non-affected CarriErs) study, 1865 respondents aged 18-84, and for the YAC (Young people And Covid-19) study, 3740 respondents aged 12-29.

Preferences regarding Disclosure of Risk for Parkinson's Disease in a Population-based Study.

Background: Preferences for risk disclosure in population-based studies assessing Parkinson's disease (PD) risk have not been assessed so far.

Objectives: To examine preferences for risk disclosure in a subset of the European Healthy Brain Aging (HeBA) multicenter study.

Methods: After a remote PD risk assessment, a structured pilot-questionnaire on risk disclosure was first presented to participants (≥50 years, without neurodegenerative diseases) during in-person visits at the Innsbruck study site.

Bridging therapy-induced phenotypes and genetic immune dysregulation to study interleukin-2-induced immunotoxicology.

Interleukin-2 (IL-2) holds promise for the treatment of cancer and autoimmune diseases, but its high-dose usage is associated with systemic immunotoxicity. Differential IL-2 receptor (IL-2R) regulation might impact function of cells upon IL-2 stimulation, possibly inducing cellular changes similar to patients with hypomorphic IL2RB mutations, presenting with multiorgan autoimmunity. Here, we show that sustained high-dose IL-2 stimulation of human lymphocytes drastically reduces IL-2Rβ surface expression especially on T cells, resulting in impaired IL-2R signaling which correlates with high IL-2Rα baseline expression.

Luxembourg Parkinson's study -comprehensive baseline analysis of Parkinson's disease and atypical parkinsonism.

Background: Deep phenotyping of Parkinson's disease (PD) is essential to investigate this fastest-growing neurodegenerative disorder. Since 2015, over 800 individuals with PD and atypical parkinsonism along with more than 800 control subjects have been recruited in the frame of the observational, monocentric, nation-wide, longitudinal-prospective Luxembourg Parkinson's study.

Objective: To profile the baseline dataset and to explore risk factors, comorbidities and clinical profiles associated with PD, atypical parkinsonism and controls.

Visualization of automatically combined disease maps and pathway diagrams for rare diseases.

Investigation of molecular mechanisms of human disorders, especially rare diseases, require exploration of various knowledge repositories for building precise hypotheses and complex data interpretation. Recently, increasingly more resources offer diagrammatic representation of such mechanisms, including disease-dedicated schematics in pathway databases and disease maps. However, collection of knowledge across them is challenging, especially for research projects with limited manpower.

ImmUniverse Consortium: Multi-omics integrative approach in personalized medicine for immune-mediated inflammatory diseases.

Immune mediated inflammatory diseases (IMIDs) are a heterogeneous group of debilitating, multifactorial and unrelated conditions featured by a dysregulated immune response leading to destructive chronic inflammation. The immune dysregulation can affect various organ systems: gut (e.g.

COBREXA.jl: constraint-based reconstruction and exascale analysis.

Summary: COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity.

Road to effective data curation for translational research.

Translational research today is data-intensive and requires multi-stakeholder collaborations to generate and pool data together for integrated analysis. This leads to the challenge of harmonization of data from different sources with different formats and standards, which is often overlooked during project planning and thus becomes a bottleneck of the research progress. We report on our experience and lessons learnt about data curation for translational research garnered over the course of the European Translational Research Infrastructure & Knowledge management Services (eTRIKS) program (https://www.

GigaSOM.jl: High-performance clustering and visualization of huge cytometry datasets.

Background: The amount of data generated in large clinical and phenotyping studies that use single-cell cytometry is constantly growing. Recent technological advances allow the easy generation of data with hundreds of millions of single-cell data points with >40 parameters, originating from thousands of individual samples. The analysis of that amount of high-dimensional data becomes demanding in both hardware and software of high-performance computational resources.

Genetic Architecture of Parkinson's Disease in the Indian Population: Harnessing Genetic Diversity to Address Critical Gaps in Parkinson's Disease Research.

Over the past two decades, our understanding of Parkinson's disease (PD) has been gleaned from the discoveries made in familial and/or sporadic forms of PD in the Caucasian population. The transferability and the clinical utility of genetic discoveries to other ethnically diverse populations are unknown. The Indian population has been under-represented in PD research.

The Luxembourg Parkinson's Study: A Comprehensive Approach for Stratification and Early Diagnosis.

While genetic advances have successfully defined part of the complexity in Parkinson's disease (PD), the clinical characterization of phenotypes remains challenging. Therapeutic trials and cohort studies typically include patients with earlier disease stages and exclude comorbidities, thus ignoring a substantial part of the real-world PD population. To account for these limitations, we implemented the Luxembourg PD study as a comprehensive clinical, molecular and device-based approach including patients with typical PD and atypical parkinsonism, irrespective of their disease stage, age, comorbidities, or linguistic background.

Confronting the catalytic dark matter encoded by sequenced genomes.

The post-genomic era has provided researchers with a deluge of protein sequences. However, a significant fraction of the proteins encoded by sequenced genomes remains without an identified function. Here, we aim at determining how many enzymes of uncertain or unknown function are still present in the Saccharomyces cerevisiae and human proteomes.

nala: text mining natural language mutation mentions.

Motivation: The extraction of sequence variants from the literature remains an important task. Existing methods primarily target standard (ST) mutation mentions (e.g.

The oncogenic FIP1L1-PDGFRα fusion protein displays skewed signaling properties compared to its wild-type PDGFRα counterpart.

Aberrant activation of oncogenic kinases is frequently observed in human cancers, but the underlying mechanism and resulting effects on global signaling are incompletely understood. Here, we demonstrate that the oncogenic FIP1L1-PDGFRα kinase exhibits a significantly different signaling pattern compared to its PDGFRα wild type counterpart. Interestingly, the activation of primarily membrane-based signal transduction processes (such as PI3-kinase- and MAP-kinase- pathways) is remarkably shifted toward a prominent activation of STAT factors.

A draft network of ligand-receptor-mediated multicellular signalling in human.

Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand-receptor paths.

Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks.

Background: Mixed microbial communities underpin important biotechnological processes such as biological wastewater treatment (BWWT). A detailed knowledge of community structure and function relationships is essential for ultimately driving these systems towards desired outcomes, e.g.

Constitutive activation of oncogenic PDGFRα-mutant proteins occurring in GIST patients induces receptor mislocalisation and alters PDGFRα signalling characteristics.

Background: Gastrointestinal stromal tumours (GIST) are mainly characterised by the presence of activating mutations in either of the two receptor tyrosine kinases c-KIT or platelet-derived growth factor receptor-α (PDGFRα). Most mechanistic studies dealing with GIST mutations have focused on c-KIT and far less is known about the signalling characteristics of the mutated PDGFRα proteins. Here, we study the signalling capacities and corresponding transcriptional responses of the different PDGFRα proteins under comparable genomic conditions.

siRNA screen identifies QPCT as a druggable target for Huntington's disease.

Huntington's disease (HD) is a currently incurable neurodegenerative condition caused by an abnormally expanded polyglutamine tract in huntingtin (HTT). We identified new modifiers of mutant HTT toxicity by performing a large-scale 'druggable genome' siRNA screen in human cultured cells, followed by hit validation in Drosophila. We focused on glutaminyl cyclase (QPCT), which had one of the strongest effects on mutant HTT-induced toxicity and aggregation in the cell-based siRNA screen and also rescued these phenotypes in Drosophila.

The HIV mutation browser: a resource for human immunodeficiency virus mutagenesis and polymorphism data.

Huge research effort has been invested over many years to determine the phenotypes of natural or artificial mutations in HIV proteins--interpretation of mutation phenotypes is an invaluable source of new knowledge. The results of this research effort are recorded in the scientific literature, but it is difficult for virologists to rapidly find it. Manually locating data on phenotypic variation within the approximately 270,000 available HIV-related research articles, or the further 1,500 articles that are published each month is a daunting task.