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

Autor: Hilkka Soininen, Nicola C. Day, Simon Lovestone, Iwona Kłoszewska, Patrizia Mecocci, Christian Spenger, Lars-Olof Wahlund, Joanna Riddoch-Contreras, Ines Greco, Julie C. Barnes, Andrew Simmons, Bruno Vellas, Jane Z. Reed, Magda Tsolaki
Přispěvatelé: Psychiatry Institute, King‘s College London, BioWisdom Ltd, Harston Mill, Department of Neurology, University of Eastern Finland-University Hospital of Kuopio, Department of Old Age Psychiatry and Psychotic Disorders, Medical University of Łódź (MUL), 3rd Department of Neurology, Aristotle University of Thessaloniki-General Hospital of Thessaloniki George Papanikolaou, Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Clinical Science, Intervention and Technology, Karolinska Institutet [Stockholm], Institute of Gerontology and Geriatrics, Università degli Studi di Perugia = University of Perugia (UNIPG), Department of Neurobiology, Care Sciences and Society, Somaxa Ltd, Abcodia Ltd, BMC, Ed., Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Università degli Studi di Perugia (UNIPG)
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Proteomics
Choline acetyltransferase (ChAt)
Bioinformatics
In silico
[SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health
lcsh:Medicine
Information Storage and Retrieval
Disease
Biology
General Biochemistry
Genetics and Molecular Biology
03 medical and health sciences
0302 clinical medicine
Alzheimer Disease
medicine
Dementia
Humans
Biomarker discovery
030304 developmental biology
Intelligence network
Medicine(all)
0303 health sciences
[SDV.MHEP] Life Sciences [q-bio]/Human health and pathology
Biochemistry
Genetics and Molecular Biology(all)
Research
lcsh:R
General Medicine
Alzheimer's disease
medicine.disease
Urokinase-type plasminogen activator receptor (PLAUR)
3. Good health
in silico
[SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health
Valid Biomarker
Biomarker (medicine)
Alzheimer’s disease
Literature mining
030217 neurology & neurosurgery
Biomarkers
[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
MRI
Zdroj: Journal of Translational Medicine
Journal of Translational Medicine, 2012, 10 (1), pp.217. ⟨10.1186/1479-5876-10-217⟩
Journal of Translational Medicine, BioMed Central, 2012, 10 (1), pp.217. ⟨10.1186/1479-5876-10-217⟩
Journal of Translational Medicine, Vol 10, Iss 1, p 217 (2012)
ISSN: 1479-5876
Popis: Background 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. Methods We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. Results Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. Conclusions These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders.
Databáze: OpenAIRE
Externí odkaz: