Na Zhang, Xinyu Liu, Hui Wang, Wen Jiang, Xiaojing Zeng, Xiaoqing He, Qi Li, Xiaolin Wang, Yaorui Ye, Qianlong Zhang, Guowang Xu, Jun Zhang
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Perinatal depressive symptom trajectories were determined through group-based trajectory modelling, and metabolites were identified using elastic net and multinomial logistic regression.</p><p><strong>Results: </strong>Five perinatal depressive symptom trajectories were established: no symptoms (52.1 %, n = 516), low-stable (29.4 %, n = 291), resilient (10.9 %, n = 108), and recurrent (4.0 %, n = 40), and emergent (3.5 %, n = 35). Each unit increase in natural log-transformed FA 24: 0 (odds ratio (OR): 1.26, 95 % confidence interval (CI): 1.07-1.48) and 16,17-didehydropregnenolone (OR: 1.35, 95 % CI: 1.16-1.58) was associated with an elevated risk of a low-stable trajectory, while 16,17-didehydropregnenolone also linked to a higher risk of the recurrent trajectory (OR: 1.73, 95 % CI: 1.22-2.47). Conversely, metabolites such as 3beta,7alpha-Dihydroxy-5-cholestenoate and FA 6:0 were correlated with a reduced risk. No significant interactions were found between the identified metabolites and polygenetic risk.</p><p><strong>Conclusions: </strong>Early-pregnancy maternal metabolites were associated with perinatal depressive symptom trajectories, independent of genetic predisposition. These findings underscore the potential role of metabolic biomarkers in predicting perinatal depression. Future studies are warranted to replicate these findings in diverse cohorts and explore causality.</p>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":" ","pages":"119768"},"PeriodicalIF":4.9000,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Early-pregnancy maternal metabolite signatures, genetic predisposition, and perinatal depressive symptom trajectories: A prospective birth cohort study.\",\"authors\":\"Na Zhang, Xinyu Liu, Hui Wang, Wen Jiang, Xiaojing Zeng, Xiaoqing He, Qi Li, Xiaolin Wang, Yaorui Ye, Qianlong Zhang, Guowang Xu, Jun Zhang\",\"doi\":\"10.1016/j.jad.2025.119768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To identify early-pregnancy maternal circulating metabolites linked to perinatal depressive symptom trajectories, and to assess the potential role of genetic predisposition in these associations.</p><p><strong>Methods: </strong>We included 990 pregnant women from the Shanghai Birth Cohort, enrolled during early pregnancy. Maternal depressive symptoms were assessed during mid-pregnancy and at 42 days and 6 months postpartum using the Center for Epidemiologic Studies Depression Scale and Edinburgh Postnatal Depression Scale. A liquid chromatography-mass spectrometry metabolomics approach was employed to profile maternal serum metabolites. Perinatal depressive symptom trajectories were determined through group-based trajectory modelling, and metabolites were identified using elastic net and multinomial logistic regression.</p><p><strong>Results: </strong>Five perinatal depressive symptom trajectories were established: no symptoms (52.1 %, n = 516), low-stable (29.4 %, n = 291), resilient (10.9 %, n = 108), and recurrent (4.0 %, n = 40), and emergent (3.5 %, n = 35). 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引用次数: 0
摘要
目的:确定与围产期抑郁症状轨迹相关的妊娠早期母体循环代谢物,并评估遗传易感性在这些关联中的潜在作用。方法:我们纳入了990名来自上海出生队列的妊娠早期孕妇。使用流行病学研究中心抑郁量表和爱丁堡产后抑郁量表评估孕妇在妊娠中期和产后42 天和6 个月的抑郁症状。采用液相色谱-质谱代谢组学方法分析母体血清代谢物。通过基于组的轨迹模型确定围产期抑郁症状轨迹,并使用弹性网和多项逻辑回归确定代谢物。结果:五个轨迹建立围产期抑郁症状:没有症状(52.1 % n = 516),低稳态(29.4 % n = 291),弹性(10.9 % n = 108),和复发性(4.0 % n = 40),和紧急(3.5 % n = 35)。自然对数转换FA的每单位增加24.0(优势比(OR): 1.26.95 %可信区间(CI): 1.07-1.48)和16,17-二脱氢孕烯醇酮(OR: 1.35, 95 % CI: 1.16-1.58)与低稳定轨迹的风险升高相关,而16,17-二脱氢孕烯醇酮也与复发轨迹的高风险相关(OR: 1.73, 95 % CI: 1.22-2.47)。相反,代谢产物如3 β、7 α -二羟基-5-胆固醇酸酯和FA 6:0与风险降低相关。鉴定的代谢物与多遗传风险之间没有发现显著的相互作用。结论:妊娠早期母体代谢物与围产期抑郁症状轨迹相关,与遗传易感性无关。这些发现强调了代谢生物标志物在预测围产期抑郁症中的潜在作用。未来的研究有理由在不同的队列中重复这些发现并探索因果关系。
Early-pregnancy maternal metabolite signatures, genetic predisposition, and perinatal depressive symptom trajectories: A prospective birth cohort study.
Objective: To identify early-pregnancy maternal circulating metabolites linked to perinatal depressive symptom trajectories, and to assess the potential role of genetic predisposition in these associations.
Methods: We included 990 pregnant women from the Shanghai Birth Cohort, enrolled during early pregnancy. Maternal depressive symptoms were assessed during mid-pregnancy and at 42 days and 6 months postpartum using the Center for Epidemiologic Studies Depression Scale and Edinburgh Postnatal Depression Scale. A liquid chromatography-mass spectrometry metabolomics approach was employed to profile maternal serum metabolites. Perinatal depressive symptom trajectories were determined through group-based trajectory modelling, and metabolites were identified using elastic net and multinomial logistic regression.
Results: Five perinatal depressive symptom trajectories were established: no symptoms (52.1 %, n = 516), low-stable (29.4 %, n = 291), resilient (10.9 %, n = 108), and recurrent (4.0 %, n = 40), and emergent (3.5 %, n = 35). Each unit increase in natural log-transformed FA 24: 0 (odds ratio (OR): 1.26, 95 % confidence interval (CI): 1.07-1.48) and 16,17-didehydropregnenolone (OR: 1.35, 95 % CI: 1.16-1.58) was associated with an elevated risk of a low-stable trajectory, while 16,17-didehydropregnenolone also linked to a higher risk of the recurrent trajectory (OR: 1.73, 95 % CI: 1.22-2.47). Conversely, metabolites such as 3beta,7alpha-Dihydroxy-5-cholestenoate and FA 6:0 were correlated with a reduced risk. No significant interactions were found between the identified metabolites and polygenetic risk.
Conclusions: Early-pregnancy maternal metabolites were associated with perinatal depressive symptom trajectories, independent of genetic predisposition. These findings underscore the potential role of metabolic biomarkers in predicting perinatal depression. Future studies are warranted to replicate these findings in diverse cohorts and explore causality.
期刊介绍:
The Journal of Affective Disorders publishes papers concerned with affective disorders in the widest sense: depression, mania, mood spectrum, emotions and personality, anxiety and stress. It is interdisciplinary and aims to bring together different approaches for a diverse readership. Top quality papers will be accepted dealing with any aspect of affective disorders, including neuroimaging, cognitive neurosciences, genetics, molecular biology, experimental and clinical neurosciences, pharmacology, neuroimmunoendocrinology, intervention and treatment trials.