Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation. - Archive ouverte HAL Access content directly
Journal Articles Journal of Translational Medicine Year : 2012

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

(1) , (2) , (1) , (2) , (3) , (4) , (5) , (6) , (7) , (8) , (9) , (1) , (10, 2) , (1)
Ines Greco
  • Function : Author
  • PersonId : 933355
Nicola Day
  • Function : Author
  • PersonId : 933356
Joanna Riddoch-Contreras
  • Function : Author
  • PersonId : 933357
Jane Reed
  • Function : Author
  • PersonId : 933358
Hilkka Soininen
  • Function : Author
  • PersonId : 933359
Magda Tsolaki
  • Function : Author
  • PersonId : 933361
Patrizia Mecocci
  • Function : Author
  • PersonId : 873224
Andrew Simmons
  • Function : Author
  • PersonId : 933365
Julie Barnes
  • Function : Author
  • PersonId : 933366
Simon Lovestone
  • Function : Correspondent author
  • PersonId : 933367

Connectez-vous pour contacter l'auteur


UNLABELLED: ABSTRACT: 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.
Fichier principal
Vignette du fichier
1479-5876-10-217.pdf (477.45 Ko) Télécharger le fichier
Vignette du fichier
1479-5876-10-217.xml (87.08 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Format : Other

Dates and versions

inserm-00758566 , version 1 (28-11-2012)



Ines Greco, Nicola Day, Joanna Riddoch-Contreras, Jane Reed, Hilkka Soininen, et al.. Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation.. Journal of Translational Medicine, 2012, 10 (1), pp.217. ⟨10.1186/1479-5876-10-217⟩. ⟨inserm-00758566⟩
185 View
170 Download



Gmail Facebook Twitter LinkedIn More