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Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation.

Ines Greco | Nicola Day | Joanna Riddoch-Contreras | Jane Reed | Hilkka Soininen | Iwona Kłoszewska | Magda Tsolaki | Bruno Vellas | Christian Spenger | Patrizia Mecocci | Lars-Olof Wahlund | Andrew Simmons | Julie Barnes | Simon Lovestone
Journal of translational medicine | 2012

Alzheimer's Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD.

Pubmed ID: 23113945

Research resources used in this publication

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Antibodies used in this publication

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Associated grants

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Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


Gene Ontology (tool)

RRID:SCR_002811

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

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PubMed (tool)

RRID:SCR_004846

Public bibliographic database that provides access to citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. PubMed citations and abstracts include fields of biomedicine and health, covering portions of life sciences, behavioral sciences, chemical sciences, and bioengineering. Provides access to additional relevant web sites and links to other NCBI molecular biology resources. Publishers of journals can submit their citations to NCBI and then provide access to full-text of articles at journal web sites using LinkOut.

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NEURON (tool)

RRID:SCR_005393

NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything

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OMIM (tool)

RRID:SCR_006437

Online catalog of human genes and genetic disorders, for clinical features, phenotypes and genes. Collection of human genes and genetic phenotypes, focusing on relationship between phenotype and genotype. Referenced overviews in OMIM contain information on all known mendelian disorders and variety of related genes. It is updated daily, and entries contain copious links to other genetics resources.

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_007303

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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Alzheimer Disease and Frontotemporal Dementia Mutation Database (tool)

RRID:SCR_008286

A locus-specific database aimed at collecting known mutations and non-pathogenic coding variations in the genes related to Alzheimer disease (AD) and frontotemporal dementia (FTD), following the guidelines of the Human Genome Variation Society. Mutations can be retrieved based on the gene, phenotype and publication. The database contains mutations reported in the literature and at scientific meetings, and unpublished mutations directly submitted to the database. To date, AD&FTDMDB contains mutations in the genes encoding the Amyloid Beta Precursor Protein (APP), Presenilin 1 (PSEN1), Presenilin 2 (PSEN2), Chromatin Modifying Protein 2B (CHMP2B), fusion (involved in t(12;16) in malignant liposarcoma) (FUS), Granulin (GRN), Microtubule Associated Protein Tau (MAPT), TAR DNA binding protein (TARDBP) and Valosin-containing Protein (VCP) and holds 415 different mutations observed in 1027 patients or families. As of March 2013, the latest publications referenced were from 2008, indicating that this resource may not be up to date.

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