Cargando…
Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis
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...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440381/ https://www.ncbi.nlm.nih.gov/pubmed/36065290 http://dx.doi.org/10.1016/j.bbrep.2022.101328 |
_version_ | 1784782336543424512 |
---|---|
author | Yahara, Hiroko Yanamoto, Souichi Takahashi, Miho Hamada, Yuji Sakamoto, Haruo Asaka, Takuya Kitagawa, Yoshimasa Moridera, Kuniyasu Noguchi, Kazuma Sugiyama, Masaya Maruoka, Yutaka Yahara, Koji |
author_facet | Yahara, Hiroko Yanamoto, Souichi Takahashi, Miho Hamada, Yuji Sakamoto, Haruo Asaka, Takuya Kitagawa, Yoshimasa Moridera, Kuniyasu Noguchi, Kazuma Sugiyama, Masaya Maruoka, Yutaka Yahara, Koji |
author_sort | Yahara, Hiroko |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9440381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94403812022-09-04 Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis Yahara, Hiroko Yanamoto, Souichi Takahashi, Miho Hamada, Yuji Sakamoto, Haruo Asaka, Takuya Kitagawa, Yoshimasa Moridera, Kuniyasu Noguchi, Kazuma Sugiyama, Masaya Maruoka, Yutaka Yahara, Koji Biochem Biophys Rep Short Communication 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. Elsevier 2022-08-27 /pmc/articles/PMC9440381/ /pubmed/36065290 http://dx.doi.org/10.1016/j.bbrep.2022.101328 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Short Communication Yahara, Hiroko Yanamoto, Souichi Takahashi, Miho Hamada, Yuji Sakamoto, Haruo Asaka, Takuya Kitagawa, Yoshimasa Moridera, Kuniyasu Noguchi, Kazuma Sugiyama, Masaya Maruoka, Yutaka Yahara, Koji Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
title | Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
title_full | Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
title_fullStr | Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
title_full_unstemmed | Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
title_short | Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
title_sort | whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440381/ https://www.ncbi.nlm.nih.gov/pubmed/36065290 http://dx.doi.org/10.1016/j.bbrep.2022.101328 |
work_keys_str_mv | AT yaharahiroko wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT yanamotosouichi wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT takahashimiho wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT hamadayuji wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT sakamotoharuo wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT asakatakuya wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT kitagawayoshimasa wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT moriderakuniyasu wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT noguchikazuma wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT sugiyamamasaya wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT maruokayutaka wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis AT yaharakoji wholebloodtranscriptomeprofilingidentifiesgeneexpressionsubnetworksandakeygenecharacteristicoftheraretypeofosteomyelitis |