A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle.

Background: The understanding of changes in temporal processes related to human carcinogenesis is limited. One approach for prospective functional genomic studies is to compile trajectories of differential expression of genes, based on measurements from many case-control pairs. We propose a new stat...

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Publicado en:BMC Medical Research Methodology Vol. 16; pp. 1 - 13
Autores principales: Lund, Eiliv, Holden, Lars, Bøvelstad, Hege, Plancade, Sandra, Mode, Nicolle, Günther, Clara-Cecilie, Nuel, Gregory, Thalabard, Jean-Christophe, Holden, Marit
Formato: research tables/charts Journal Article
Publicado: BioMed Central 3/5/2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 3/5/2016
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      pub: BioMed Central
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        atl: A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle.
      aug:
        au:
          Lund, Eiliv
          Holden, Lars
          Bøvelstad, Hege
          Plancade, Sandra
          Mode, Nicolle
          Günther, Clara-Cecilie
          Nuel, Gregory
          Thalabard, Jean-Christophe
          Holden, Marit
        affil: Department of Community Medicine, Pb. 5060, UiT The Arctic University of Norway, 9037 Tromsø, Norway
      sug:
        subj:
          Data Collection
          Models, Statistical
          Early Detection of Cancer Methods
          Disease Susceptibility Epidemiology
          Breast Neoplasms
          Gene Expression Profiling Statistics and Numerical Data
          Breast Neoplasms Epidemiology
          Prospective Studies
          Sensitivity and Specificity
          Incidence
          Gene Expression Profiling Methods
          Female
          Adult
          Human
          Reference Values
          Norway
          Age Factors
          Genes
          Middle Age
          Aged
          Risk Assessment
          Case Control Studies
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Clinical Assessment Tools
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Female
      ab: Background: The understanding of changes in temporal processes related to human carcinogenesis is limited. One approach for prospective functional genomic studies is to compile trajectories of differential expression of genes, based on measurements from many case-control pairs. We propose a new statistical method that does not assume any parametric shape for the gene trajectories.Methods: The trajectory of a gene is defined as the curve representing the changes in gene expression levels in the blood as a function of time to cancer diagnosis. In a nested case-control design it consists of differences in gene expression levels between cases and controls. Genes can be grouped into curve groups, each curve group corresponding to genes with a similar development over time. The proposed new statistical approach is based on a set of hypothesis testing that can determine whether or not there is development in gene expression levels over time, and whether this development varies among different strata. Curve group analysis may reveal significant differences in gene expression levels over time among the different strata considered. This new method was applied as a "proof of concept" to breast cancer in the Norwegian Women and Cancer (NOWAC) postgenome cohort, using blood samples collected prospectively that were specifically preserved for transcriptomic analyses (PAX tube). Cohort members diagnosed with invasive breast cancer through 2009 were identified through linkage to the Cancer Registry of Norway, and for each case a random control from the postgenome cohort was also selected, matched by birth year and time of blood sampling, to create a case-control pair. After exclusions, 441 case-control pairs were available for analyses, in which we considered strata of lymph node status at time of diagnosis and time of diagnosis with respect to breast cancer screening visits.Results: The development of gene expression levels in the NOWAC postgenome cohort varied in the last years before breast cancer diagnosis, and this development differed by lymph node status and participation in the Norwegian Breast Cancer Screening Program. The differences among the investigated strata appeared larger in the year before breast cancer diagnosis compared to earlier years.Conclusions: This approach shows good properties in term of statistical power and type 1 error under minimal assumptions. When applied to a real data set it was able to discriminate between groups of genes with non-linear similar patterns before diagnosis.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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