Differential Baseline Expression of Inflammatory Markers in Patients with Severe Depression and Variable Response to Intermittent Theta Burst Stimulation
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Background
Major depressive disorder (MDD) is biologically heterogeneous. A subset of patients shows elevated inflammatory markers associated with greater symptom burden and reduced responsiveness to antidepressants. As with pharmacotherapy and electroconvulsive therapy, outcomes with repetitive transcranial magnetic stimulation (rTMS) vary widely, and inflammation may impair neuroplasticity and modulate effects. This exploratory study examined whether baseline inflammatory protein signatures could identify subgroups of patients with severe MDD undergoing intermittent theta-burst stimulation (iTBS) that differ in response.
Methods
Baseline inflammatory protein levels (Olink® Target 96 Inflammation panel) were clustered using k-means in patients with severe MDD receiving iTBS. Demographic and clinical characteristics were compared across clusters. Differential protein expression was assessed using volcano plots with false discovery rate (FDR) correction. Kyoto Encyclopedia of Genes and Genomes and Reactome pathway enrichment analyses identified biological processes associated with the clustering solution.
Results
A two-cluster solution was identified. Cluster 2 showed the highest proportion of responders, whereas Cluster 1 showed the lowest. Clusters did not differ significantly in age, sex, medication status, randomization arm, or BMI. Volcano analysis identified 10 differentially expressed proteins between clusters (FDR < 0.05 and |ΔNPX| ≥ 1). Enrichment analyses implicated cytokine–cytokine receptor interaction, chemokine signaling, and interleukin signaling pathways as characteristic of the lower-response subgroup.
Limitations
The exploratory design, modest sample size, and lack of a treatment control group limit generalizability.
Conclusions
Baseline inflammatory signatures may help differentiate responsiveness to iTBS treatment in severe MDD and support inflammation-based stratification as a potential avenue for personalized psychiatry.
