title: 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.
abstract: 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.
authors.affiliation: Department of Community Medicine, Pb. 5060, UiT The Arctic University of Norway, 9037, Tromsø, Norway. Eiliv.Lund@uit.no.
authors.forename: Eiliv
authors.initials: E
authors.lastname: Lund
authors.affiliation: Norsk Regnesentral, Oslo, Norway. Lars.Holden@nr.no.
authors.forename: Lars
authors.initials: L
authors.lastname: Holden
authors.affiliation: Department of Community Medicine, Pb. 5060, UiT The Arctic University of Norway, 9037, Tromsø, Norway. Hege.M.Bovelstad@uit.no.
authors.forename: Hege
authors.initials: H
authors.lastname: Bøvelstad
authors.affiliation: INRA, UR1404 Unité Mathématiques et Informatique Appliquées du Génome à l'Environnement, Jouy-en-Josas, France. Sandra.Plancade@jouy.inra.fr.
authors.forename: Sandra
authors.initials: S
authors.lastname: Plancade
authors.affiliation: Department of Community Medicine, Pb. 5060, UiT The Arctic University of Norway, 9037, Tromsø, Norway. svdnam@gmail.com.
authors.forename: Nicolle
authors.initials: N
authors.lastname: Mode
authors.affiliation: Norsk Regnesentral, Oslo, Norway. Clara-Cecilie.Gunther@nr.no.
authors.forename: Clara-Cecilie
authors.initials: CC
authors.lastname: Günther
authors.affiliation: CNRS, INSMI Stochastics and Biology Group (PSB) LPMA, UPMC, Sorbonne University, Paris, France. Nuel@math.cnrs.fr.
authors.forename: Gregory
authors.initials: G
authors.lastname: Nuel
authors.affiliation: MAP 5, Université Paris Descartes, Sorbonne Paris Cité, Paris, France. Jean-Christophe.Thalabard@mi.parisdescartes.fr.
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Thalabard
authors.affiliation: Norsk Regnesentral, Oslo, Norway. Marit.Holden@nr.no.
authors.forename: Marit
authors.initials: M
authors.lastname: Holden
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001943:Breast Neoplasms / Q000453:epidemiology / Q000235:genetics*; D016022:Case-Control Studies; D015331:Cohort Studies; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data*; D015972:Gene Expression Regulation, Neoplastic; D020022:Genetic Predisposition to Disease / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008875:Middle Aged; D015233:Models, Statistical; D009664:Norway; D012016:Reference Values; D012042:Registries; D018570:Risk Assessment; D012680:Sensitivity and Specificity