A multivariate approach to reveal biomarker signatures for disease classification: application to mass spectral profiles of cerebrospinal fluid from patients with multiple sclerosis.
J Proteome Res
; 9(7): 3608-20, 2010 Jul 02.
Article
em En
| MEDLINE
| ID: mdl-20499859
Mass spectral profiles from cerebrospinal fluid (CSF) are used as input to a novel multivariate approach to select features responsible for the separation of patients with multiple sclerosis (MS) from control groups. Our targeted statistical approach makes it possible to systematically remove features in the spectral fingerprints masking the components expressing the disease pattern. The low molecular weight CSF proteome from 54 patients with MS and a range of other neurological diseases (OND), as well as neurological healthy controls (NHC), is analyzed in replicates using mass spectral profiling. Statistically validated partial least-squares discriminant analysis (PLS-DA) models are created as a first step to separate the groups. Using the group membership as a target, the most discriminatory projection in the multivariate space spanned by the spectral profiles is revealed. From the resulting target-projected component, the spectral regions most significantly contributing to group separation are identified using the nonparametric discriminating variable (DIVA) test together with the so-called selectivity ratio (SR) plot. Our approach is general and can be applied for other diseases and instrumental techniques as well.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Biomarcadores
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Análise Multivariada
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Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz
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Técnicas e Procedimentos Diagnósticos
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Esclerose Múltipla
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2010
Tipo de documento:
Article