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

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.

SUBMITTER: Greco I

PROVIDER: S-EPMC3508881 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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

Greco Ines I Day Nicola N Riddoch-Contreras Joanna J Reed Jane J Soininen Hilkka H Kłoszewska Iwona I Tsolaki Magda M Vellas Bruno B Spenger Christian C Mecocci Patrizia P Wahlund Lars-Olof LO Simmons Andrew A Barnes Julie J Lovestone Simon S

Journal of translational medicine 20121031

<h4>Background</h4>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 bioma ...[more]

PMID: 23113945

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Project description:BackgroundFor selection and evaluation of potential biomarkers, inclusion of already published information is of utmost importance. In spite of significant advancements in text- and data-mining techniques, the vast knowledge space of biomarkers in biomedical text has remained unexplored. Existing named entity recognition approaches are not sufficiently selective for the retrieval of biomarker information from the literature. The purpose of this study was to identify textual features that enhance the effectiveness of biomarker information retrieval for different indication areas and diverse end user perspectives.MethodsA biomarker terminology was created and further organized into six concept classes. Performance of this terminology was optimized towards balanced selectivity and specificity. The information retrieval performance using the biomarker terminology was evaluated based on various combinations of the terminology's six classes. Further validation of these results was performed on two independent corpora representing two different neurodegenerative diseases.ResultsThe current state of the biomarker terminology contains 119 entity classes supported by 1890 different synonyms. The result of information retrieval shows improved retrieval rate of informative abstracts, which is achieved by including clinical management terms and evidence of gene/protein alterations (e.g. gene/protein expression status or certain polymorphisms) in combination with disease and gene name recognition. When additional filtering through other classes (e.g. diagnostic or prognostic methods) is applied, the typical high number of unspecific search results is significantly reduced. The evaluation results suggest that this approach enables the automated identification of biomarker information in the literature. A demo version of the search engine SCAIView, including the biomarker retrieval, is made available to the public through http://www.scaiview.com/scaiview-academia.html.ConclusionsThe approach presented in this paper demonstrates that using a dedicated biomarker terminology for automated analysis of the scientific literature maybe helpful as an aid to finding biomarker information in text. Successful extraction of candidate biomarkers information from published resources can be considered as the first step towards developing novel hypotheses. These hypotheses will be valuable for the early decision-making in the drug discovery and development process.

Project description:IntroductionIn the Investigating the Impact of Alzheimer's Disease Diagnostics in British Columbia (IMPACT-AD BC) study, we aimed to understand how Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing-used in medical care-impacted medical decision-making (medical utility), personal decision-making (personal utility), and health system economics.MethodsThe study was designed as an observational, longitudinal cohort study. A total of 149 patients were enrolled between February 2019 and July 2021. Patients referred to memory clinics were approached to participate if their dementia specialist ordered AD CSF biomarker testing as part of their routine medical care, and the clinical scenario met the appropriate use criteria for lumbar puncture and AD CSF biomarker testing. For the medical utility pillar, detailed clinical management plans were collected via physician questionnaires pre- and post-biomarker disclosure.ResultsPatients with completed management questionnaires (n = 142) had a median age of 64 (interquartile range: 59-69) years, 48% were female, and 60% had CSF biomarker profiles on the AD continuum. Clinical management changed in 89.4% of cases. AD biomarker testing was associated with decreased need for other diagnostic procedures, including brain imaging (-52.0%) and detailed neuropsychological assessments (-63.2%), increased referrals and counseling (57.0%), and guided AD-related drug prescriptions (+88.4% and -50.0% in biomarker-positive and -negative cases, respectively).DiscussionAD biomarker testing was associated with significant and positive changes in clinical management, including decreased health care resource use, therapy optimization, and increased patient and family member counseling. While certain changes in management were linked to the AD biomarker profile (e.g., referral to clinical trials), the majority of changes were independent of baseline clinical presentation and level of cognitive impairment, demonstrating a broad value for AD biomarker testing in individuals meeting the appropriate use criteria for testing.

Dataset Information

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

Publications

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

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