Diagnostic classification of schizophrenia by neural network analysis of blood-based gene expression signatures

Makoto Takahashi, Hiroshi Hayashi, Yuichiro Watanabe, Kazushi Sawamura, Naoki Fukui, Junzo Watanabe, Tsuyoshi Kitajima, Yoshio Yamanouchi, Nakao Iwata, Katsuyoshi Mizukami, Takafumi Hori, Kazutaka Shimoda, Hiroshi Ujike, Norio Ozaki, Kentarou Iijima, Kazuo Takemura, Hideyuki Aoshima, Toshiyuki Someya

研究成果: Article査読

53 被引用数 (Scopus)

抄録

Gene expression profiling with microarray technology suggests that peripheral blood cells might be a surrogate for postmortem brain tissue in studies of schizophrenia. The development of an accessible peripheral biomarker would substantially help in the diagnosis of this disease. We used a bioinformatics approach to examine whether the gene expression signature in whole blood contains enough information to make a specific diagnosis of schizophrenia. Unpaired t-tests of gene expression datasets from 52 antipsychotics-free schizophrenia patients and 49 normal controls identified 792 differentially expressed probes. Functional profiling with DAVID revealed that eleven of these genes were previously reported to be associated with schizophrenia, and 73 of them were expressed in the brain tissue. We analyzed the datasets with one of the supervised classifiers, artificial neural networks (ANNs). The samples were subdivided into training and testing sets. Quality filtering and stepwise forward selection identified 14 probes as predictors of the diagnosis. ANNs were then trained with the selected probes as the input and the training set for known diagnosis as the output. The constructed model achieved 91.2% diagnostic accuracy in the training set and 87.9% accuracy in the hold-out testing set. On the other hand, hierarchical clustering, a standard but unsupervised classifier, failed to separate patients and controls. These results suggest analysis of a blood-based gene expression signature with the supervised classifier, ANNs, might be a diagnostic tool for schizophrenia.

本文言語English
ページ(範囲)210-218
ページ数9
ジャーナルSchizophrenia Research
119
1-3
DOI
出版ステータスPublished - 06-2010

All Science Journal Classification (ASJC) codes

  • Psychiatry and Mental health
  • Biological Psychiatry

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