Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis

Hiroko Yahara; Souichi Yanamoto; Miho Takahashi; Yuji Hamada; Haruo Sakamoto; Takuya Asaka; Yoshimasa Kitagawa; Kuniyasu Moridera; Kazuma Noguchi; Masaya Sugiyama; Yutaka Maruoka; Koji Yahara

doi:10.1016/j.bbrep.2022.101328

Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis

Biochem Biophys Rep. 2022 Aug 27:32:101328. doi: 10.1016/j.bbrep.2022.101328. eCollection 2022 Dec.

Authors

Affiliations

¹ Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Toyama, Shinjuku-ku, Tokyo, Japan.
² Department of Clinical Oral Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan.
³ Department of Oral and Maxillofacial Surgery, Tokai University Hachioji Hospital, Japan.
⁴ Department of Oral Diagnosis and Medicine, Hokkaido University Graduate School of Dental Medicine, Sapporo, Japan.
⁵ Department of Oral and Maxillofacial Surgery, Hyogo College of Medicine, Nishinomiya, Hyogo, Japan.
⁶ Department of Oral and Maxillofacial Surgery, Center Hospital of the National Center for Global Health and Medicine, Tokyo, Japan.
⁷ Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Abstract

Chronic non-bacterial osteomyelitis (CNO) is a rare and severe inflammatory bone disorder that can occur in the jaw. It is often associated with systemic conditions including autoimmune deficiency. Medical management of patients and establishment of a correct diagnosis are difficult as the etiology of the disease remains unknown. Therefore, little is known about the disease characteristics at the gene expression level. Here, we explored aspects of CNO based on whole blood RNA sequencing (>6 Gb per sample) of 11 patients and 9 healthy controls in Japan and on a recently developed method that is applicable to small datasets, can estimate a directed gene network, and extract a subnetwork of genes underlying patient characteristics. We identified nine subnetworks, comprising 26 differentially regulated edges and 36 genes, with the gene encoding glycophorin C (GYPC) presenting the highest discrimination ability. The expression of the gene was mostly lower in patients with CNO than in the healthy controls, suggesting an abnormal status of red cells in patients with CNO. This study enhances our understanding of CNO at the transcriptome level and further provides a framework for whole blood RNA sequencing and analysis of data obtained for a better diagnosis of the disease.

Keywords: CNO; CNO, chronic non-bacterial osteomyelitis; Differentially regulated genes; Gene expression; Network; Osteomyelitis; RNA-Seq; TPM, transcripts per million.