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Plasma metabolic disturbances during pregnancy and postpartum in women with depression
Examining plasma metabolic profiling during pregnancy and postpartum could help clinicians understand the risk factors for postpartum depression (PPD) development. This analysis targeted paired plasma metabolites in mid-late gestational and 1 month postpartum periods in women with (n = 209) or witho...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732390/ https://www.ncbi.nlm.nih.gov/pubmed/36505921 http://dx.doi.org/10.1016/j.isci.2022.105666 |
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author | Yu, Zhiqian Matsukawa, Naomi Saigusa, Daisuke Motoike, Ikuko N. Ono, Chiaki Okamura, Yasunobu Onuma, Tomomi Takahashi, Yuta Sakai, Mai Kudo, Hisaaki Obara, Taku Murakami, Keiko Shirota, Matusyuki Kikuchi, Saya Kobayashi, Natsuko Kikuchi, Yoshie Sugawara, Junichi Minegishi, Naoko Ogishima, Soichi Kinoshita, Kengo Yamamoto, Masayuki Yaegashi, Nobuo Kuriyama, Shinichi Koshiba, Seizo Tomita, Hiroaki |
author_facet | Yu, Zhiqian Matsukawa, Naomi Saigusa, Daisuke Motoike, Ikuko N. Ono, Chiaki Okamura, Yasunobu Onuma, Tomomi Takahashi, Yuta Sakai, Mai Kudo, Hisaaki Obara, Taku Murakami, Keiko Shirota, Matusyuki Kikuchi, Saya Kobayashi, Natsuko Kikuchi, Yoshie Sugawara, Junichi Minegishi, Naoko Ogishima, Soichi Kinoshita, Kengo Yamamoto, Masayuki Yaegashi, Nobuo Kuriyama, Shinichi Koshiba, Seizo Tomita, Hiroaki |
author_sort | Yu, Zhiqian |
collection | PubMed |
description | Examining plasma metabolic profiling during pregnancy and postpartum could help clinicians understand the risk factors for postpartum depression (PPD) development. This analysis targeted paired plasma metabolites in mid-late gestational and 1 month postpartum periods in women with (n = 209) or without (n = 222) PPD. Gas chromatogram-mass spectrometry was used to analyze plasma metabolites at these two time points. Among the 170 objected plasma metabolites, principal component analysis distinguished pregnancy and postpartum metabolites but failed to discriminate women with and without PPD. Compared to women without PPD, those with PPD exhibited 37 metabolites with disparate changes during pregnancy and the 1-month postpartum period and an enriched citrate cycle. Machine learning and multivariate statistical analysis identified two or three compounds that could be potential biomarkers for PPD prediction during pregnancy. Our findings suggest metabolic disturbances in women with depression and may help to elucidate metabolic processes associated with PPD development. |
format | Online Article Text |
id | pubmed-9732390 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97323902022-12-10 Plasma metabolic disturbances during pregnancy and postpartum in women with depression Yu, Zhiqian Matsukawa, Naomi Saigusa, Daisuke Motoike, Ikuko N. Ono, Chiaki Okamura, Yasunobu Onuma, Tomomi Takahashi, Yuta Sakai, Mai Kudo, Hisaaki Obara, Taku Murakami, Keiko Shirota, Matusyuki Kikuchi, Saya Kobayashi, Natsuko Kikuchi, Yoshie Sugawara, Junichi Minegishi, Naoko Ogishima, Soichi Kinoshita, Kengo Yamamoto, Masayuki Yaegashi, Nobuo Kuriyama, Shinichi Koshiba, Seizo Tomita, Hiroaki iScience Article Examining plasma metabolic profiling during pregnancy and postpartum could help clinicians understand the risk factors for postpartum depression (PPD) development. This analysis targeted paired plasma metabolites in mid-late gestational and 1 month postpartum periods in women with (n = 209) or without (n = 222) PPD. Gas chromatogram-mass spectrometry was used to analyze plasma metabolites at these two time points. Among the 170 objected plasma metabolites, principal component analysis distinguished pregnancy and postpartum metabolites but failed to discriminate women with and without PPD. Compared to women without PPD, those with PPD exhibited 37 metabolites with disparate changes during pregnancy and the 1-month postpartum period and an enriched citrate cycle. Machine learning and multivariate statistical analysis identified two or three compounds that could be potential biomarkers for PPD prediction during pregnancy. Our findings suggest metabolic disturbances in women with depression and may help to elucidate metabolic processes associated with PPD development. Elsevier 2022-11-24 /pmc/articles/PMC9732390/ /pubmed/36505921 http://dx.doi.org/10.1016/j.isci.2022.105666 Text en © 2022 The Author(s) 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 | Article Yu, Zhiqian Matsukawa, Naomi Saigusa, Daisuke Motoike, Ikuko N. Ono, Chiaki Okamura, Yasunobu Onuma, Tomomi Takahashi, Yuta Sakai, Mai Kudo, Hisaaki Obara, Taku Murakami, Keiko Shirota, Matusyuki Kikuchi, Saya Kobayashi, Natsuko Kikuchi, Yoshie Sugawara, Junichi Minegishi, Naoko Ogishima, Soichi Kinoshita, Kengo Yamamoto, Masayuki Yaegashi, Nobuo Kuriyama, Shinichi Koshiba, Seizo Tomita, Hiroaki Plasma metabolic disturbances during pregnancy and postpartum in women with depression |
title | Plasma metabolic disturbances during pregnancy and postpartum in women with depression |
title_full | Plasma metabolic disturbances during pregnancy and postpartum in women with depression |
title_fullStr | Plasma metabolic disturbances during pregnancy and postpartum in women with depression |
title_full_unstemmed | Plasma metabolic disturbances during pregnancy and postpartum in women with depression |
title_short | Plasma metabolic disturbances during pregnancy and postpartum in women with depression |
title_sort | plasma metabolic disturbances during pregnancy and postpartum in women with depression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732390/ https://www.ncbi.nlm.nih.gov/pubmed/36505921 http://dx.doi.org/10.1016/j.isci.2022.105666 |
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