PERCIM

Research project

Although depression is recognized as a major public health burden, depression treatments are effective in only around two-thirds of patients. One of the likely causes for these low success rates of treatment, is that depression is not a ‘one-size-fits-all’ concept. Depression is rather a collection of different phenotypes, each with specific pathology, and each potentially requiring different treatment.

The PERCIM project is funded by a ZonMw grant for Personalized Medicine. Our aim is to improve personalized care for depression by focusing on a specific subtype: Immuno-metabolic depression, which is characterized by a unique clinical and biological profile. Clinical characteristics of immuno-metabolic depression are appetite increase, leaden paralysis and fatigue. Biological characteristics of immuno-metabolic depression are increased inflammatory activation and alterations of energy metabolism.

Studies indicate that immuno-metabolic depression is associated with a poor response to antidepressant treatment but with increased effectiveness of lifestyle interventions. However, it is not clear yet which clinical and biological features best capture immuno-metabolic depression, and thereby may explain the poor response to antidepressants. Also, we do not know yet which lifestyle interventions are most effective in immuno-metabolic (IM) depression. The PERCIM project will bridge the gaps between bench and bedside that currently exist.

Central aims of the PERCIM project

1. Improve IM depression profiling in terms of clinical characteristics and biomarkers,
2. Identify personalized treatment modalities for IM depression and
3. Include the patient perspective in personalized medicine for IM depression.

For the first aim, the project will use a large database of over 75.000 persons, including 15.000 with depression. In the second part of the project, data of 4 RCT’s on a variety of treatment modalities will be analyzed: antidepressants, light therapy, running therapy and multi-nutrient supplements. For the last aim we will use focus groups to incorporate the patient’s voice into the recommendations. We will do this in collaboration with the Depressie Vereniging.

The project will lead to recommendations for clinical profiling and treatment of IM depression, facilitating personalized medicine and fueling future clinical guidelines.

Project output

2021

Vreijling, S. R., Penninx, B., Bot, M., Watkins, E., Owens, M., Kohls, E., Hegerl, U., Roca, M., Gili, M., Brouwer, I. A., Visser, M., Beekman, A. T. F., Jansen, R., & Lamers, F. (2021). Effects of dietary interventions on depressive symptom profiles: results from the MooDFOOD depression prevention study. Psychol Med, 1-10. https://doi.org/10.1017/S0033291721000337

Sen, Z. D., Danyeli, L. V., Woelfer, M., Lamers, F., Wagner, G., Sobanski, T., & Walter, M. (2021). Linking atypical depression and insulin resistance-related disorders via low-grade chronic inflammation: Integrating the phenotypic, molecular and neuroanatomical dimensions. Brain Behav Immun, 93, 335-352. https://doi.org/10.1016/j.bbi.2020.12.020

2022

Toenders, Y. J., Schmaal, L., Nawijn, L., Han, L. K. M., Binnewies, J., van der Wee, N. J. A., van Tol, M. J., Veltman, D. J., Milaneschi, Y., Lamers, F., & Penninx, B. (2022). The association between clinical and biological characteristics of depression and structural brain alterations. J Affect Disord, 312, 268-274. https://doi.org/10.1016/j.jad.2022.06.056

2023

van Haeringen, M., Milaneschi, Y., Lamers, F., Penninx, B., & Jansen, R. (2023). Dissection of depression heterogeneity using proteomic clusters. Psychol Med, 53(7), 2904-2912. https://doi.org/10.1017/S0033291721004888

Vreijling, S. R., Penninx, B., Beekman, A. T. F., Jansen, R., & Lamers, F. (2023). The MooDFOOD randomized controlled trial: the data and its implications for the theory – Authors’ reply. Psychol Med, 53(12), 5884-5885. https://doi.org/10.1017/S0033291723001484

Vreijling, S. R., van Haeringen, M., Milaneschi, Y., Huider, F., Bot, M., Amin, N., Beulens, J. W., Bremmer, M. A., Elders, P. J., Galesloot, T. E., Kiemeney, L. A., van Loo, H. M., Picavet, H. S. J., Rutters, F., van der Spek, A., van de Wiel, A. M., van Duijn, C., Feskens, E. J. M., Hartman, C. A., . . . Jansen, R. (2023). Sociodemographic, lifestyle and clinical characteristics of energy-related depression symptoms: A pooled analysis of 13,965 depressed cases in 8 Dutch cohorts. J Affect Disord, 323, 1-9. https://doi.org/10.1016/j.jad.2022.11.005

de Kluiver, H., Jansen, R., Penninx, B., Giltay, E. J., Schoevers, R. A., & Milaneschi, Y. (2023). Metabolomics signatures of depression: the role of symptom profiles. Transl Psychiatry, 13(1), 198. https://doi.org/10.1038/s41398-023-02484-5

Verhoeven, J. E., Han, L. K. M., Lever-van Milligen, B. A., Hu, M. X., Revesz, D., Hoogendoorn, A. W., Batelaan, N. M., van Schaik, D. J. F., van Balkom, A., van Oppen, P., & Penninx, B. (2023). Antidepressants or running therapy: Comparing effects on mental and physical health in patients with depression and anxiety disorders. J Affect Disord, 329, 19-29. https://doi.org/10.1016/j.jad.2023.02.064

2024

Vreijling, S. R., Chin Fatt, C. R., Williams, L. M., Schatzberg, A. F., Usherwood, T., Nemeroff, C. B., Rush, A. J., Uher, R., Aitchison, K. J., Kohler-Forsberg, O., Rietschel, M., Trivedi, M. H., Jha, M. K., Penninx, B., Beekman, A. T. F., Jansen, R., & Lamers, F. (2024). Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials. Br J Psychiatry, 224(3), 89-97. https://doi.org/10.1192/bjp.2023.148

Vreijling, S. R., Neuhaus, L., Brouwer, A., Penninx, B., Beekman, A. T. F., Lamers, F., Jansen, R., & Bremmer, M. (2024). The role of immuno-metabolic depression features in the effects of light therapy in patients with depression and type 2 diabetes mellitus: A randomized controlled trial. J Psychosom Res, 181, 111671. https://doi.org/10.1016/j.jpsychores.2024.111671

Zwiep, J. C., Milaneschi, Y., Giltay, E. J., Vinkers, C. H., Penninx, B., & Lamers, F. (2024). Depression with immuno-metabolic dysregulation: Testing pragmatic criteria to stratify patients. Brain Behav Immun, 124, 115-122. https://doi.org/10.1016/j.bbi.2024.11.033

Jansen, R., Milaneschi, Y., Schranner, D., Kastenmuller, G., Arnold, M., Han, X., Dunlop, B. W., Mood Disorder Precision Medicine, C., Rush, A. J., Kaddurah-Daouk, R., & Penninx, B. (2024). The metabolome-wide signature of major depressive disorder. Mol Psychiatry, 29(12), 3722-3733. https://doi.org/10.1038/s41380-024-02613-6

2025

Vreijling, S. R., Penninx, B., Verhoeven, J. E., Teunissen, C. E., Blujdea, E. R., Beekman, A. T. F., Lamers, F., & Jansen, R. (2025). Running therapy or antidepressants as treatments for immunometabolic depression in patients with depressive and anxiety disorders: A secondary analysis of the MOTAR study. Brain Behav Immun, 123, 876-883. https://doi.org/10.1016/j.bbi.2024.10.033

Penninx, B. W. J. H., Lamers, F., Jansen, R., Berk, M., Khandaker, G. M., De Picker, L., & Milaneschi, Y. (2025). Immuno-metabolic depression: from concept to implementation. The Lancet Regional Health – Europe, 48, 101166. https://doi.org/10.1016/j.lanepe.2024.101166

Poster:

‘Characterization of depression symptoms using large scale questionnaire data in the Dutch population: a BBMRI-BIONIC study’ at the Health RI meeting (January 2021)

Project newsletters (in Dutch):

• 1st edition (December 2020)
• 2nd edition (July 2022)

Analysis plan form/ Access data request form:

Metabolite and inflammatory data that were assayed as part of the PERCIM project can be reused. See also information as provided on the Zorggegevens catalogus. To request data access, please fill out the following form.

Sarah Vreijling, Rick Jansen & Femke Lamers