title: Biomarker identification and effect estimation on schizophrenia - a high dimensional data analysis.
abstract: Biomarkers have been examined in schizophrenia research for decades. Medical morbidity and mortality rates, as well as personal and societal costs, are associated with schizophrenia patients. The identification of biomarkers and alleles, which often have a small effect individually, may help to develop new diagnostic tests for early identification and treatment. Currently, there is not a commonly accepted statistical approach to identify predictive biomarkers from high dimensional data. We used space decomposition-gradient-regression (DGR) method to select biomarkers, which are associated with the risk of schizophrenia. Then, we used the gradient scores, generated from the selected biomarkers, as the prediction factor in regression to estimate their effects. We also used an alternative approach, classification and regression tree, to compare the biomarker selected by DGR and found about 70% of the selected biomarkers were the same. However, the advantage of DGR is that it can evaluate individual effects for each biomarker from their combined effect. In DGR analysis of serum specimens of US military service members with a diagnosis of schizophrenia from 1992 to 2005 and their controls, Alpha-1-Antitrypsin (AAT), Interleukin-6 receptor (IL-6r) and connective tissue growth factor were selected to identify schizophrenia for males; and AAT, Apolipoprotein B and Sortilin were selected for females. If these findings from military subjects are replicated by other studies, they suggest the possibility of a novel biomarker panel as an adjunct to earlier diagnosis and initiation of treatment.
authors.affiliation: Preventive Medicine Branch, Walter Reed Army Institute of Research (WRAIR) , Silver Spring, MD , USA.
authors.forename: Yuanzhang
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Pediatrics, Johns Hopkins University School of Medicine , Baltimore, MD , USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Yolken
authors.affiliation: Preventive Medicine Branch, Walter Reed Army Institute of Research (WRAIR) , Silver Spring, MD , USA ; ManTech International Corporation, Health and Life Sciences , Herndon, VA , USA.
authors.forename: David N
authors.initials: DN
authors.lastname: Cowan
authors.affiliation: Preventive Medicine Branch, Walter Reed Army Institute of Research (WRAIR) , Silver Spring, MD , USA.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Boivin
authors.affiliation: Department of Statistics, George Washington University , Washington, DC , USA.
authors.forename: Tianqing
authors.initials: T
authors.lastname: Liu
authors.affiliation: Division of Epidemiology and Biostatistics, Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences , Bethesda, MD , USA.
authors.forename: David W
authors.initials: DW
authors.lastname: Niebuhr
keywords: biomarker identification; gradient; high dimensional data; schizophrenia; space decomposition