In iScience
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.
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
2022-Dec-22
Biological sciences, Metabolomics, Physiology
