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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
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.
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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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