MDD brain-derived subtypes (San Raffaele)
Multimodal brain-derived subtypes of Major depressive disorder unveil multivariate associations between anergic symptoms, childhood trauma, immune-inflammatory markers and treatment-resistance
Structural and diffusion brain MRI features of 102 inpatients with major depressive disorder, used to cluster patients into neuroimaging subtypes linked to treatment resistance and inflammation. Only regional feature tables and clinical variables are open; the images are not shared.
Overview
A single-centre cohort of 102 adults with major depressive disorder from IRCCS Ospedale San Raffaele in Milan. The study asked whether patients can be split into biologically meaningful subgroups from brain structure alone. Regional cortical thickness, grey matter volumes and white matter fractional anisotropy were harmonized across scanners, reduced in dimension and clustered without labels. The two resulting groups were then compared on treatment resistance, symptom profile, childhood trauma and blood immune-inflammatory markers. The authors deposited the feature tables, clinical variables and cluster labels on Mendeley Data under CC BY-NC 3.0. The MR images are not available.
Composition
102 patients, 69 women and 33 men, aged 23 to 65 years (mean 49.4), counted from the open clinical table. 31 are marked as treatment-resistant. Clustering gave one group of 59 patients with more treatment resistance, more energy-related symptoms, more reported childhood abuse and emotional neglect, and thinner cortex; and one group of 43 patients with cognitive and affective symptoms and thicker cortex. The clinical table also holds education, illness onset, number of episodes, medication load, BMI, HDRS-21, BDI subscales and CTQ subscales.
Acquisition
Structural and diffusion MRI were acquired at San Raffaele. A scanner column in the clinical table separates two scanners (46 patients on the older, 56 on the newer one), which is why the features were harmonized. Field strength, vendor and sequence parameters are in the paper's methods, which are not openly readable, so they are left out here.
Annotations
There are no image annotations. The labels are the data-driven cluster assignment per patient and the clinical variables listed above.
Known limitations
- Images are not shared; only about 400 regional features per patient are open.
- Patients only, no healthy controls in the open files.
- Single centre with a scanner change during recruitment.
- Inflammatory marker values are not part of the open files.
Cohort
Aggregate numbers from the sources below. Bars are relative to the 102 subjects.
Sex
- Female 69 68%
- Male 33 32%
Sex column in clinical_variables.csv from Mendeley Data record dcbmjws425 (CC BY-NC 3.0)
Contrast / sequence
Groups can overlap
- Diffusion-weighted 102 100%
Abstract in Colombo et al. 2024, European Neuropsychopharmacology 85, 45-57 (abstract)
Age
mean 49.4, range 23 to 65
Age column in clinical_variables.csv from Mendeley Data record dcbmjws425 (CC BY-NC 3.0)
Condition
Groups can overlap
- Major depressive disorder 102 100%
Abstract in Colombo et al. 2024, European Neuropsychopharmacology 85, 45-57 (abstract)
License and access
Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer
The data are not available outside the institution or study that holds them
The Mendeley Data record holds three CSV files: about 400 regional grey matter volume, cortical thickness and fractional anisotropy values per patient, clinical variables (age, sex, scanner, symptom and childhood trauma scores, treatment resistance) and the cluster label. They download openly under CC BY-NC 3.0. No route to the MR images is published; the record names the corresponding author for clarifications.
Different parts of the data carry different licenses. The summary on the right shows the most restrictive answer per rule.
No published license or data use terms
The data holder has published no license and no data use terms. Any use, sharing or commercial right has to be agreed with the data holder, and nothing can be assumed to be allowed. Default copyright and data protection law still apply.
Neither the data record nor the paper abstract offers the images or states terms for them.
What you can do
- Commercial use Not stated
- Not stated
- Train ML models Not stated
- Create derived data Not stated
- Publish results Not stated
What you can share
- Share the data Not stated
- Share derived data Not stated
- Share trained models Not stated
What you must do
- Cite or credit Not stated
- Share alike Not stated
- Sign an agreement Not stated
- Ethics approval Not stated
- Manuscript review Not stated
- Release code Not stated
- Return results Not stated
- Delete after use Not stated
Limits
- No re-identification Not stated
- Location limits Not stated
Creative Commons Attribution-NonCommercial 3.0 Unported
Older version of CC BY-NC. Non-commercial use only, with credit. Adapted material may be shared non-commercially under any terms that keep the credit.
What you can do
- No
- Not stated
- Conditional
- Yes
- Yes
What you can share
- Conditional
- Conditional
- Conditional
What you must do
- Yes
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Citation
Colombo F, Calesella F, Bravi B, Fortaner-Uyà L, Monopoli C, Tassi E, Carminati M, Zanardi R, Bollettini I, Poletti S, Lorenzi C, Spadini S, Brambilla P, Serretti A, Maggioni E, Fabbri C, Benedetti F, Vai B. Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance. European Neuropsychopharmacology 85, 45-57 (2024). doi:10.1016/j.euroneuro.2024.05.015
Sources
Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.