Profiling patients on a proposed ‘immunometabolic depression’ (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment.

To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants.

Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses.

Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, βpooled = 0.06, P = 0.049, 95% CI 0.0001–0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, βpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01–0.22, I2 = 23.91%), with a higher – but still small – effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (βpooled = 0.16) and the IMD index (βpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission.

Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

根据提议的“免疫代谢抑郁”（IMD）维度对患者进行分析，该维度被描述为与能量调节和免疫代谢失调相关的一系列非典型抑郁症状，可能会优化个性化治疗。

检验基线 IMD 特征预测抗抑郁药物治疗效果较差的假设。

使用iSPOT-D ( n = 967)、CO-MED ( n = 665)、GENDEP ( n = 773) 和 EMBARC ( n = 146) 临床试验中 2551 名抑郁症患者的数据。预测因素包括非典型能量相关症状 (AES) 的基线严重程度、体重指数 (BMI) 和 C 反应蛋白水平 (CRP，仅三项试验)，并汇总为 IMD 指数。对各个试验数据集进行主要结局（抑郁症状严重程度的变化）和次要结局（反应和缓解）的逻辑回归的混合模型，并使用随机效应荟萃分析进行汇总。

尽管 AES 严重程度和 BMI 并不能预测抑郁症状严重程度的变化，但较高的基线 CRP 预测抑郁症状的减轻幅度较小（n = 376，β合并= 0.06，P = 0.049，95% CI 0.0001–0.12，I 2 = 3.61%） ; 结合这些特征的 IMD 指数（ n = 372，β pooled = 0.12，se = 0.12，P = 0.031，95% CI 0.01–0.22，I 2 = 23.91%）也发现了这一点，具有较高但仍然很小– 与 CRP 相比的效应大小。对选择性血清素再摄取抑制剂使用者的限制分析表明，CRP（β汇总= 0.16）和 IMD 指数（β汇总= 0.20）的影响更大。基线 IMD 特征，无论是单独的还是组合的，都不能预测反应或缓解。

具有较多 IMD 特征的人在接受抗抑郁药物治疗时抑郁症状改善较少。然而，由于不一致的关联效应较小，临床相关性有限。这些患者是否会从针对免疫代谢途径的治疗中获得更多益处仍有待研究。