Recurrent major depressive disorder (rMDD) is a relapsing-remitting disease with high morbidity and a 5-year risk of recurrence of up to 80%. This was a prospective pilot study to examine the potential diagnostic and prognostic value of targeted plasma metabolomics in the care of patients with rMDD in remission. We used an established LC-MS/MS platform to measure 399 metabolites in 68 subjects with rMDD (n = 45 females and 23 males) in antidepressant-free remission and 59 age- and sex-matched controls (n = 40 females and 19 males). Patients were then followed prospectively for 2.5 years. Metabolomics explained up to 43% of the phenotypic variance. The strongest biomarkers were gender specific. 80% of the metabolic predictors of recurrence in both males and females belonged to 6 pathways: (1) phospholipids, (2) sphingomyelins, (3) glycosphingolipids, (4) eicosanoids, (5) microbiome, and (6) purines. These changes traced to altered mitochondrial regulation of cellular redox, signaling, energy, and lipid metabolism. Metabolomics identified a chemical endophenotype that could be used to stratify rrMDD patients at greatest risk for recurrence with an accuracy over 0.90 (95%CI = 0.69–1.0). Power calculations suggest that a validation study of at least 198 females and 198 males (99 cases and 99 controls each) will be needed to confirm these results. Although a small study, these results are the first to show the potential utility of metabolomics in assisting with the important clinical challenge of prospectively identifying the patients at greatest risk of recurrence of a depressive episode and those who are at lower risk.

复发性重度抑郁症 (rMDD) 是一种复发缓解型疾病，发病率很高，5 年复发风险高达 80%。这是一项前瞻性试点研究，旨在检验靶向血浆代谢组学在缓解 rMDD 患者护理中的潜在诊断和预后价值。我们使用已建立的 LC-MS/MS 平台测量了 68 名 rMDD 受试者（n  = 45 名女性和 23 名男性）在无抗抑郁药物缓解期和 59 名年龄和性别匹配的对照受试者（ n  = 40 名女性和 19 名男性）的 399 种代谢物。）。然后对患者进行了 2.5 年的前瞻性随访。代谢组学解释了高达 43% 的表型变异。最强的生物标志物具有性别特异性。男性和女性复发的代谢预测因子中 80% 属于 6 种途径：(1) 磷脂、(2) 鞘磷脂、(3) 鞘糖脂、(4) 类二十烷酸、(5) 微生物组和 (6) 嘌呤。这些变化可追溯到细胞氧化还原、信号传导、能量和脂质代谢的线粒体调节的改变。代谢组学确定了一种化学内表型，可用于对复发风险最大的 rrMDD 患者进行分层，准确度超过 0.90 (95% CI = 0.69–1.0)。功效计算表明，需要对至少 198 名女性和 198 名男性（各 99 名病例和 99 名对照）进行验证研究来证实这些结果。虽然是一项小型研究，但这些结果首次表明代谢组学在协助应对重要的临床挑战方面的潜在效用，即前瞻性地识别抑郁发作复发风险最大的患者和风险较低的患者。