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Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome
BACKGROUND: Imprinting disorders (IDs) show overlapping phenotypes, particularly in Silver–Russell syndrome (SRS), Temple syndrome (TS14), and Prader–Willi syndrome (PWS). These three IDs include fetal and postnatal growth failure, feeding difficulty, and muscular hypotonia as major clinical feature...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583213/ https://www.ncbi.nlm.nih.gov/pubmed/33092629 http://dx.doi.org/10.1186/s13148-020-00949-8 |
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author | Hara-Isono, Kaori Matsubara, Keiko Fuke, Tomoko Yamazawa, Kazuki Satou, Kazuhito Murakami, Nobuyuki Saitoh, Shinji Nakabayashi, Kazuhiko Hata, Kenichiro Ogata, Tsutomu Fukami, Maki Kagami, Masayo |
author_facet | Hara-Isono, Kaori Matsubara, Keiko Fuke, Tomoko Yamazawa, Kazuki Satou, Kazuhito Murakami, Nobuyuki Saitoh, Shinji Nakabayashi, Kazuhiko Hata, Kenichiro Ogata, Tsutomu Fukami, Maki Kagami, Masayo |
author_sort | Hara-Isono, Kaori |
collection | PubMed |
description | BACKGROUND: Imprinting disorders (IDs) show overlapping phenotypes, particularly in Silver–Russell syndrome (SRS), Temple syndrome (TS14), and Prader–Willi syndrome (PWS). These three IDs include fetal and postnatal growth failure, feeding difficulty, and muscular hypotonia as major clinical features. However, the mechanism that causes overlapping phenotypes has not been clarified. To investigate the presence or absence of methylation signatures associated with overlapping phenotypes, we performed genome-wide methylation analysis (GWMA). RESULTS: GWMA was carried out on 36 patients with three IDs (SRS [n = 16], TS14 [n = 7], PWS [n = 13]) and 11 child controls using HumanMethylation450 BeadChip including 475,000 CpG sites across the human genome. To reveal an aberrantly methylated region shared by SRS, TS14, and PWS groups, we compared genome-wide methylation data of the three groups with those of control subjects. All the identified regions were known as SRS-, TS14-, and PWS-related imprinting-associated differentially methylated regions (iDMRs), and there was no hypermethylated or hypomethylated region shared by different ID groups. To examine the methylation pattern shared by SRS, TS14, and PWS groups, we performed clustering analysis based on GWMA data. The result focusing on 620 probes at the 62 known iDMRs (except for SRS-, TS14-, and PWS-related iDMRs) classified patients into two categories: (1) category A, grossly normal methylation patterns mainly consisting of SRS group patients; and (2) category B, broad and mild hypermethylation patterns mainly consisting of TS14 and PWS group patients. However, we found no obvious relationship between these methylation patterns and phenotypes of patients. CONCLUSIONS: GWMA in three IDs found no methylation signatures shared by SRS, TS14, and PWS groups. Although clustering analysis showed similar mild hypermethylation patterns in TS14 and PWS groups, further study is needed to clarify the effect of methylation patterns on the overlapping phenotypes. |
format | Online Article Text |
id | pubmed-7583213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75832132020-10-26 Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome Hara-Isono, Kaori Matsubara, Keiko Fuke, Tomoko Yamazawa, Kazuki Satou, Kazuhito Murakami, Nobuyuki Saitoh, Shinji Nakabayashi, Kazuhiko Hata, Kenichiro Ogata, Tsutomu Fukami, Maki Kagami, Masayo Clin Epigenetics Research BACKGROUND: Imprinting disorders (IDs) show overlapping phenotypes, particularly in Silver–Russell syndrome (SRS), Temple syndrome (TS14), and Prader–Willi syndrome (PWS). These three IDs include fetal and postnatal growth failure, feeding difficulty, and muscular hypotonia as major clinical features. However, the mechanism that causes overlapping phenotypes has not been clarified. To investigate the presence or absence of methylation signatures associated with overlapping phenotypes, we performed genome-wide methylation analysis (GWMA). RESULTS: GWMA was carried out on 36 patients with three IDs (SRS [n = 16], TS14 [n = 7], PWS [n = 13]) and 11 child controls using HumanMethylation450 BeadChip including 475,000 CpG sites across the human genome. To reveal an aberrantly methylated region shared by SRS, TS14, and PWS groups, we compared genome-wide methylation data of the three groups with those of control subjects. All the identified regions were known as SRS-, TS14-, and PWS-related imprinting-associated differentially methylated regions (iDMRs), and there was no hypermethylated or hypomethylated region shared by different ID groups. To examine the methylation pattern shared by SRS, TS14, and PWS groups, we performed clustering analysis based on GWMA data. The result focusing on 620 probes at the 62 known iDMRs (except for SRS-, TS14-, and PWS-related iDMRs) classified patients into two categories: (1) category A, grossly normal methylation patterns mainly consisting of SRS group patients; and (2) category B, broad and mild hypermethylation patterns mainly consisting of TS14 and PWS group patients. However, we found no obvious relationship between these methylation patterns and phenotypes of patients. CONCLUSIONS: GWMA in three IDs found no methylation signatures shared by SRS, TS14, and PWS groups. Although clustering analysis showed similar mild hypermethylation patterns in TS14 and PWS groups, further study is needed to clarify the effect of methylation patterns on the overlapping phenotypes. BioMed Central 2020-10-22 /pmc/articles/PMC7583213/ /pubmed/33092629 http://dx.doi.org/10.1186/s13148-020-00949-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Hara-Isono, Kaori Matsubara, Keiko Fuke, Tomoko Yamazawa, Kazuki Satou, Kazuhito Murakami, Nobuyuki Saitoh, Shinji Nakabayashi, Kazuhiko Hata, Kenichiro Ogata, Tsutomu Fukami, Maki Kagami, Masayo Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome |
title | Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome |
title_full | Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome |
title_fullStr | Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome |
title_full_unstemmed | Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome |
title_short | Genome-wide methylation analysis in Silver–Russell syndrome, Temple syndrome, and Prader–Willi syndrome |
title_sort | genome-wide methylation analysis in silver–russell syndrome, temple syndrome, and prader–willi syndrome |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583213/ https://www.ncbi.nlm.nih.gov/pubmed/33092629 http://dx.doi.org/10.1186/s13148-020-00949-8 |
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