The Central Biobank and Virtual Biobank of BIOMARKAPD: A Resource for Studies on Neurodegenerative Diseases.
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ABSTRACT:
SUBMITTER: Reijs BL
PROVIDER: S-EPMC4606063 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
The Central Biobank and Virtual Biobank of BIOMARKAPD: A Resource for Studies on Neurodegenerative Diseases.
Reijs Babette L R BL Teunissen Charlotte E CE Goncharenko Nikolai N Betsou Fay F Blennow Kaj K Baldeiras Inês I Brosseron Frederic F Cavedo Enrica E Fladby Tormod T Froelich Lutz L Gabryelewicz Tomasz T Gurvit Hakan H Kapaki Elisabeth E Koson Peter P Kulic Luka L Lehmann Sylvain S Lewczuk Piotr P Lleó Alberto A Maetzler Walter W de Mendonça Alexandre A Miller Anne-Marie AM Molinuevo José L JL Mollenhauer Brit B Parnetti Lucilla L Rot Uros U Schneider Anja A Simonsen Anja Hviid AH Tagliavini Fabrizio F Tsolaki Magda M Verbeek Marcel M MM Verhey Frans R J FR Zboch Marzena M Winblad Bengt B Scheltens Philip P Zetterberg Henrik H Visser Pieter Jelle PJ
Frontiers in neurology 20151015
Biobanks are important resources for biomarker discovery and assay development. Biomarkers for Alzheimer's and Parkinson's disease (BIOMARKAPD) is a European multicenter study, funded by the EU Joint Programme-Neurodegenerative Disease Research, which aims to improve the clinical use of body fluid markers for the diagnosis and prognosis of Alzheimer's disease (AD) and Parkinson's disease (PD). The objective was to standardize the assessment of existing assays and to validate novel fluid biomarke ...[more]
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Project description:BackgroundNeurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis, Parkinson's disease (PD), spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective degeneration of neurons and axons in the central nervous system (CNS) and constitute one of the major challenges of modern medicine. Computeraided or in silico drug design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays.MethodsIn the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches.ResultsDetailed analysis of the recently reported case studies revealed that the majority of them use a sequential combination of ligand and structure-based virtual screening techniques, with particular focus on pharmacophore models and the docking approach.ConclusionNeurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future.
| S-EPMC6080098 | biostudies-literature
Project description:BackgroundCertain viral infections have been linked to the development of neurodegenerative diseases. This study aimed to investigate the association between cytomegalovirus (CMV) infection and five neurodegenerative diseases, spinal muscular atrophy (SMA) and related syndromes, Parkinson's disease (PD), Alzheimer's disease (AD), multiple sclerosis (MS), and disorders of the autonomic nervous system (DANS).MethodsThis prospective cohort included white British individuals who underwent CMV testing in the UK Biobank from January 1, 2006 to December 31, 2021. A Cox proportional hazard model was utilized to estimate the future risk of developing five neurodegenerative diseases in individuals with or without CMV infection, adjusted for batch effect, age, sex, and Townsend deprivation index in Model 1, and additionally for type 2 diabetes, cancer, osteoporosis, vitamin D, monocyte count and leukocyte count in Model 2. Bidirectional Mendelian randomization was employed to validate the potential causal relationship between CMV infection and PD.FindingsA total of 8346 individuals, consisting of 4620 females (55.4%) and 3726 males (44.6%) who were white British at an average age of 56.74 (8.11), were included in this study. The results showed that CMV infection did not affect the risk of developing AD (model 1: HR [95% CI] = 1.01 [0.57, 1.81], P = 0.965; model 2: HR = 1.00 [0.56, 1.79], P = 0.999), SMA and related syndromes (model 1: HR = 3.57 [0.64, 19.80], P = 0.146; model 2: HR = 3.52 [0.63, 19.61], P = 0.152), MS (model 1: HR = 1.16 [0.45, 2.97], P = 0.756; model 2: HR = 1.16 [0.45, 2.97], P = 0.761) and DANS (model 1: HR = 0.65 [0.16, 2.66], P = 0.552; model 2: HR = 0.65 [0.16, 2.64], P = 0.543). Interestingly, it was found that participants who were CMV seronegative had a higher risk of developing PD compared to those who were seropositive (model 1: HR = 2.37 [1.25, 4.51], P = 0.009; model 2: HR = 2.39 [1.25, 4.54], P = 0.008) after excluding deceased individuals. This association was notably stronger in males (model 1: HR = 3.16 [1.42, 7.07], P = 0.005; model 2: HR = 3.41 [1.50, 7.71], P = 0.003), but no significant difference was observed in the female subgroup (model 1: HR = 1.28 [0.40, 4.07], P = 0.679; model 2: HR = 1.27 [0.40, 4.06], P = 0.684). However, a bidirectional Mendelian randomization analysis did not find a genetic association between CMV infection and PD.InterpretationThe study found that males who did not have a CMV infection were at a higher risk of developing PD. The findings provided a new viewpoint on the risk factors for PD and may potentially influence public health approaches for the disease.FundingNational Natural Science Foundation of China (81873776), Natural Science Foundation of Guangdong Province, China (2021A1515011681, 2023A1515010495).
| S-EPMC11327475 | biostudies-literature
Project description:Carefully designed and established biobanks are considered one of the most essential resources to foster biomedical research as they provide cost-effective and rapid access to a vast variety of biological materials and related anthropometrics allowing for testing of various biomarkers as well as numerous original and pertinent bioclinical hypotheses related to human disease etiology and prognosis. The objective of the present study was to present the baseline data, design, and methods used for the establishment of the Vejle Diabetes Biobank. Further aims included assessment of the prevalence of diabetes and quality of diabetes treatment in a specified Danish region.The Vejle Diabetes Biobank was established from 2007 to 2010 as a regional Biobank containing blood, DNA, and urine samples from patients with diabetes and a gender- and age-matched control population aged 25-75 years. Anthropometrics were obtained by physical examination, questionnaires, and interviews at the time of inclusion into the Biobank. The cohort was linked to the Danish Civil Registration System, the Danish National Patient Registry, and the Danish National Prescription Registry.In total, 4,255 nondiabetic individuals and 3,320 patients with diabetes were included. Type 2 diabetes (T2D) patients had a higher body mass index (30 kg/m2) than type 1 diabetes (T1D) patients (25 and 26 kg/m2 in women and men, respectively) and control subjects (25 and 27 kg/m2 in women and men, respectively). Fasting levels of plasma triglycerides and blood pressure were higher in T2D patients (1.5 mmol/L and 148/85 mmHg, respectively) compared with T1D patients (0.9 mmol/L and 139/81 mmHg, respectively), whereas glycated hemoglobin (HbA1c), plasma high density lipoprotein, low density lipoprotein, and total cholesterol were lower in T2D patients (51 mmol/mol, 1.2 mmol/L, 2.2 mmol/L, and 4.2 mmol/L, respectively) compared with findings in T1D patients (61 mmol/mol, 1.6 mmol/L, 2.3 mmol/L, and 4.4 mmol/L, respectively). At the time of inclusion into the Biobank, 56% of the T2D patients and 25% of T1D patients had an HbA1c <7% (53 mmol/mol). Only 28% and 34% of the T2D patients, respectively, reached treatment target for blood pressure and lipids.The Vejle Diabetes Biobank represents one of the largest open diabetes case-control cohorts in Denmark. The Biobank invites collaborative investigations of diabetes and diabetes complication etiologies as well as studies of prognostic or predictive biomarkers.
| S-EPMC5085288 | biostudies-other
Project description:The Generation R Study is a population-based prospective cohort study from fetal life until young adulthood. The study is designed to identify early environmental and genetic causes of normal and abnormal growth, development and health from fetal life until young adulthood. In total, 9,778 mothers were enrolled in the study. Prenatal and postnatal data collection is conducted by physical examinations, questionnaires, interviews, ultrasound examinations and biological samples. Major efforts have been conducted for collecting biological specimens including DNA, blood for phenotypes and urine samples. In this paper, the collection, processing and storage of these biological specimens are described. Together with detailed phenotype measurements, these biological specimens form a unique resource for epidemiological studies focused on environmental exposures, genetic determinants and their interactions in relation to growth, health and development from fetal life onwards.
| S-EPMC2190786 | biostudies-other
Project description:The TAR DNA Binding Protein (TDP-43) has been implicated in the pathogenesis of human neurodegenerative diseases and exhibits hallmark neuropathology in amyotrophic lateral sclerosis (ALS). Here, we explore its tractability as a plasma biomarker of disease and describe its localization and possible functions in the cytosol of platelets. Novel TDP-43 immunoassays were developed on three different technical platforms and qualified for specificity, signal-noise ratio, detection range, variation, spike recovery and dilution linearity in human plasma samples. Fractionation studies revealed that >95% of plasma TDP-43 protein [RL1] was located within the platelet cytosol, together with numerous RNAs. Platelet-derived TDP-43 exhibits TDP-43 proteoforms detected in neurodegenerative diseases, TARDBP RNA splice variants and TDP-43 RNA targets found in the central nervous system (CNS). We propose that TDP-43 serves similar functional roles in platelets and synapses, suggesting that the study of platelet TDP-43 might provide a window into TDP-43 proteinopathies within the CNS. The restricted compartmentalization of plasma TDP-43 in platelets provides a highly concentrated substrate for further biochemical analyses. Moreover, our results suggest that current plasma biobanking protocols are subject to considerable heterogeneity in platelet recovery and measurements of TDP-43 in plasma.
2024-09-25 | GSE245303 | GEO
Project description:Neurodegenerative diseases of the central nervous system are characterised by pathogenetic cellular and molecular changes in specific areas of the brain that lead to the dysfunction and/or loss of explicit neuronal populations. Despite exhibiting different clinical profiles and selective neuronal loss, common features such as abnormal protein deposition, dysfunctional cellular transport, mitochondrial deficits, glutamate excitotoxicity and inflammation are observed in most, if not all, neurodegenerative disorders, suggesting converging pathways of neurodegeneration. We have generated comparative genome-wide gene expression data for Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, multiple sclerosis, Parkinson’s disease and schizophrenia using an extensive cohort of well characterised post-mortem CNS tissues. The analysis of whole genome expression patterns across these major disorders offers an outstanding opportunity not only to look into exclusive disease specific changes, but more importantly to uncover potential common molecular pathogenic mechanisms that could be targeted for therapeutic gain. Surprisingly, no dysregulated gene that passed our selection criteria was found in common across all 6 diseases using our primary method of analysis. However, 61 dysregulated genes were shared when comparing five and four diseases. Our analysis indicates firstly the involvement of common neuronal homeostatic, survival and synaptic plasticity pathways. Secondly, we report changes to immunoregulatory and immunomodulatory pathways in all diseases. Our secondary method of analysis confirmed significant up-regulation of a number of genes in diseases presenting degeneration and showed that somatostatin was downregulated in all 6 diseases. The latter is supportive of a general role for neuroinflammation in the pathogenesis and/or response to neurodegeneration. Unravelling the detailed nature of the molecular changes regulating inflammation in the CNS is key to the development of novel therapeutic approaches for these chronic conditions. A total of 113 cases were selected retrospectively on the basis of a confirmed clinical and neuropathological diagnosis and snap-frozen brain blocks were provided by various tissue banks within the BrainNet Europe network. Total RNA was extracted from dissected snap-frozen tissue (< 100 mg) by the individual laboratories according to a BNE optimised common protocol using the RNeasy(r) tissue lipid mini kit (Qiagen Ltd, Crawley, UK) according to the manufacturer's instructions, and was stored at -80C until further use. Gene expression analysis was performed on the RNA samples using the Illumina whole genome HumanRef8 v2 BeadChip (Illumina, London, UK). All the labelling and hybridisation of the samples was carried out in a single experiment by the Imperial College group to reduce the technical variability. RNA samples were prepared for array analysis using the Illumina TotalPrep(tm)-96 RNA Amplification Kit (Ambion/Applied Biosystems, Warrington, UK). Finally, the BeadChips we re scanned using the Illumina BeadArray Reader. The data was extracted using BeadStudio 3.2 (Illumina). Data normalisation and gene differential expression analyses were conducted using the Rosetta error models available in the Rosetta Resolver(r) system (Rosetta Biosoftware, Seattle, Wa, USA). Two samples presented very low signal expression most likely due to hybridization problems and did not pass the quality control test. They are not represented here. One of the 2 samples was a replicate, therefore there was loss of only 1 case bringing the grand total of cases used to 112 (total of samples of 118 including 6 replicates).
2011-01-29 | E-GEOD-26927 | biostudies-arrayexpress
Project description:BackgroundAn increased susceptibility to COVID-19 has been suggested for individuals with neurodegenerative diseases, but data are scarce from longitudinal studies.MethodsIn this community-based cohort study, we included 96,275 participants of the UK Biobank who had available SARS-CoV-2 test results in Public Health England. Of these, 2617 had a clinical diagnosis of neurodegenerative diseases in the UK Biobank inpatient hospital data before the outbreak of COVID-19 (defined as January 31st, 2020), while the remaining participants constituted the reference group. We then followed both groups from January 31st, 2020 to June 14th, 2021 for ascertainment of COVID-19 outcomes, including any COVID-19, inpatient care for COVID-19, and COVID-19 related death. Logistic regression was applied to estimate the association between neurogenerative disease and risks of COVID-19 outcomes, adjusted for multiple confounders and somatic comorbidities.ResultsWe observed an elevated risk of COVID-19 outcomes among individuals with a neurodegenerative disease compared with the reference group, corresponding to a fully adjusted odds ratio of 2.47 (95%CI 2.25-2.71) for any COVID-19, 2.18 (95%CI 1.94-2.45) for inpatient COVID-19, and 3.67 (95%CI 3.11-4.34) for COVID-19 related death. Among individuals with a positive test result for SARS-CoV-2, individuals with neurodegenerative diseases had also a higher risk of COVID-19 related death than others (fully adjusted odds ratio 2.08; 95%CI 1.71-2.53).ConclusionAmong UK Biobank participants who received at least one test for SARS-CoV-2, a pre-existing diagnosis of neurodegenerative disease was associated with a subsequently increased risk of COVID-19, especially COVID-19 related death.
| S-EPMC8739517 | biostudies-literature
Project description:Metabolic syndrome (MetS) is characterized by a constellation of metabolic risk factors, including obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) levels, hypertension, and hyperglycemia, and is associated with stroke and neurodegenerative diseases. This study capitalized on brain structural images and clinical data from the UK Biobank and explored the associations of brain morphology with MetS and brain aging due to MetS. Cortical surface area, thickness, and subcortical volumes were assessed using FreeSurfer. Linear regression was used to examine associations of brain morphology with five MetS components and the MetS severity in a metabolic aging group (N = 23,676, age 62.8 ± 7.5 years). Partial least squares (PLS) were employed to predict brain age using MetS-associated brain morphology. The five MetS components and MetS severity were associated with increased cortical surface area and decreased thickness, particularly in the frontal, temporal, and sensorimotor cortex, and reduced volumes in the basal ganglia. Obesity best explained the variation of brain morphology. Moreover, participants with the most severe MetS had brain age 1-year older than those without MetS. Brain age in patients with stroke (N = 1042), dementia (N = 83), Parkinson's (N = 107), and multiple sclerosis (N = 235) was greater than that in the metabolic aging group. The obesity-related brain morphology had the leading discriminative power. Therefore, the MetS-related brain morphological model can be used for risk assessment of stroke and neurodegenerative diseases. Our findings suggested that prioritizing adjusting obesity among the five metabolic components may be more helpful for improving brain health in aging populations.
| S-EPMC10310693 | biostudies-literature
Project description:Treatments for neurodegenerative disorders remain rare, although recent FDA approvals, such as Lecanemab and Aducanumab for Alzheimer's Disease, highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use Summary-data-based Mendelian Randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer's disease, 3 amyotrophic lateral sclerosis, 5 Lewy body dementia, 46 Parkinson's disease, and 9 Progressive supranuclear palsy target genes passing multiple test corrections (pSMR_multi < 2.95×10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics - classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these 69.8% are expressed in the disease relevant cell type from single nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as Riluzole in AD. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community [https://nih-card-ndd-smr-home-syboky.streamlit.app/].
| S-EPMC10120805 | biostudies-literature
Project description:Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.
| S-EPMC10806756 | biostudies-literature