Plasma metabolic disturbances during pregnancy and postpartum in women with depression

Zhiqian Yu; Naomi Matsukawa; Daisuke Saigusa; Ikuko N. Motoike; Chiaki Ono; Yasunobu Okamura; Tomomi Onuma; Yuta Takahashi; Mai Sakai; Hisaaki Kudo; Taku Obara; Keiko Murakami; Matusyuki Shirota; Saya Kikuchi; Natsuko Kobayashi; Yoshie Kikuchi; Junichi Sugawara; Naoko Minegishi; Soichi Ogishima; Kengo Kinoshita; Masayuki Yamamoto; Nobuo Yaegashi; Shinichi Kuriyama; Seizo Koshiba; Hiroaki Tomita

doi:10.1016/j.isci.2022.105666

Plasma metabolic disturbances during pregnancy and postpartum in women with depression

Zhiqian Yu, Naomi Matsukawa, Daisuke Saigusa, Ikuko N. Motoike, Chiaki Ono, Yasunobu Okamura, Tomomi Onuma, Yuta Takahashi, Mai Sakai, Hisaaki Kudo, Taku Obara, Keiko Murakami, Matusyuki Shirota, Saya Kikuchi, Natsuko Kobayashi, Yoshie Kikuchi, Junichi Sugawara, Naoko Minegishi, Soichi Ogishima, Kengo KinoshitaMasayuki Yamamoto, Nobuo Yaegashi, Shinichi Kuriyama, Seizo Koshiba, Hiroaki Tomita

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

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.

Original language	English
Article number	105666
Journal	iScience
Volume	25
Issue number	12
DOIs	https://doi.org/10.1016/j.isci.2022.105666
State	Published - 22 Dec 2022
Externally published	Yes

Keywords

Biological sciences
Metabolomics
Physiology

Access to Document

10.1016/j.isci.2022.105666

Cite this

Yu, Z., Matsukawa, N., Saigusa, D., Motoike, I. N., Ono, C., Okamura, Y., Onuma, T., Takahashi, Y., Sakai, M., Kudo, H., Obara, T., Murakami, K., Shirota, M., Kikuchi, S., Kobayashi, N., Kikuchi, Y., Sugawara, J., Minegishi, N., Ogishima, S., ... Tomita, H. (2022). Plasma metabolic disturbances during pregnancy and postpartum in women with depression. iScience, 25(12), Article 105666. https://doi.org/10.1016/j.isci.2022.105666

@article{4c735c9a5d344cd0993b0d99ab7f1017,

title = "Plasma metabolic disturbances during pregnancy and postpartum in women with depression",

abstract = "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.",

keywords = "Biological sciences, Metabolomics, Physiology",

author = "Zhiqian Yu and Naomi Matsukawa and Daisuke Saigusa and Motoike, {Ikuko N.} and Chiaki Ono and Yasunobu Okamura and Tomomi Onuma and Yuta Takahashi and Mai Sakai and Hisaaki Kudo and Taku Obara and Keiko Murakami and Matusyuki Shirota and Saya Kikuchi and Natsuko Kobayashi and Yoshie Kikuchi and Junichi Sugawara and Naoko Minegishi and Soichi Ogishima and Kengo Kinoshita and Masayuki Yamamoto and Nobuo Yaegashi and Shinichi Kuriyama and Seizo Koshiba and Hiroaki Tomita",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s)",

year = "2022",

month = dec,

day = "22",

doi = "10.1016/j.isci.2022.105666",

language = "英語",

volume = "25",

journal = "iScience",

issn = "2589-0042",

publisher = "Elsevier Inc.",

number = "12",

}

Yu, Z, Matsukawa, N, Saigusa, D, Motoike, IN, Ono, C, Okamura, Y, Onuma, T, Takahashi, Y, Sakai, M, Kudo, H, Obara, T, Murakami, K, Shirota, M, Kikuchi, S, Kobayashi, N, Kikuchi, Y, Sugawara, J, Minegishi, N, Ogishima, S, Kinoshita, K, Yamamoto, M, Yaegashi, N, Kuriyama, S, Koshiba, S & Tomita, H 2022, 'Plasma metabolic disturbances during pregnancy and postpartum in women with depression', iScience, vol. 25, no. 12, 105666. https://doi.org/10.1016/j.isci.2022.105666

TY - JOUR

T1 - Plasma metabolic disturbances during pregnancy and postpartum in women with depression

AU - Yu, Zhiqian

AU - Matsukawa, Naomi

AU - Saigusa, Daisuke

AU - Motoike, Ikuko N.

AU - Ono, Chiaki

AU - Okamura, Yasunobu

AU - Onuma, Tomomi

AU - Takahashi, Yuta

AU - Sakai, Mai

AU - Kudo, Hisaaki

AU - Obara, Taku

AU - Murakami, Keiko

AU - Shirota, Matusyuki

AU - Kikuchi, Saya

AU - Kobayashi, Natsuko

AU - Kikuchi, Yoshie

AU - Sugawara, Junichi

AU - Minegishi, Naoko

AU - Ogishima, Soichi

AU - Kinoshita, Kengo

AU - Yamamoto, Masayuki

AU - Yaegashi, Nobuo

AU - Kuriyama, Shinichi

AU - Koshiba, Seizo

AU - Tomita, Hiroaki

PY - 2022/12/22

Y1 - 2022/12/22

N2 - 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.

AB - 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.

KW - Biological sciences

KW - Metabolomics

KW - Physiology

UR - http://www.scopus.com/inward/record.url?scp=85144031760&partnerID=8YFLogxK

U2 - 10.1016/j.isci.2022.105666

DO - 10.1016/j.isci.2022.105666

M3 - 記事

AN - SCOPUS:85144031760

SN - 2589-0042

VL - 25

JO - iScience

JF - iScience

IS - 12

M1 - 105666

ER -

Plasma metabolic disturbances during pregnancy and postpartum in women with depression

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this