Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study

Bayer, J. M. M.; van Velzen, L. S.; Pozzi, E.; Davey, C.; Han, L. K. M.; Bauduin, S. E. E. C.; Bauer, J.; Benedetti, F.; Berger, K.; Bonnekoh, L. M.; Brosch, K.; Buelow, R.; Couvy-Duchesne, B.; Cullen, K. R.; Dannlowski, U.; Dima, D.; Dohm, K.; Evans, J. W.; Fu, C. H. Y.; Fuentes-Claramonte, P.; Godlewska, B. R.; Goltermann, J.; Gonul, A. S.; Gotlib, I. H.; Goya-Maldonado, R.; Grabe, H. J.; Groenewold, N. A.; Grotegerd, D.; Gruber, O.; Hahn, T.; Hall, G. B.; Hamilton, J. P.; Harrison, B. J.; Hatton, S. N.; Hermesdorf, M.; Hickie, I. B.; Ho, T. C.; Jahanshad, N.; Jamieson, A. J.; Jansen, A.; Ka

doi:10.1101/2025.03.17.643677

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bioRxiv · 10.1101/2025.03.17.643677

Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study

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Abstract

ImportanceMajor depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients. ObjectiveTo use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics. Design, setting, and participantsA normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices). Main outcome measuresZ-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC. ResultsZ-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms. Conclusions and relevanceOur study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture. Key points QuestionCan z-scores derived from normative modelling shed light on the heterogeneous group-level findings of cortical thickness abnormalities in major depression and what characterises individuals at the extreme ends of cortical thickness abnormalities? FindingWe confirmed a large overlap in z-score distributions between depressed individuals and healthy controls and a heterogeneous spatial distribution of extreme z-deviations across brain regions across individual patients. Lower z-scores for cortical thickness were related to more severe clinical characteristics. MeaningOur findings confirm the heterogeneity in individual variation in the location and extent of CT abnormalities across patients with MDD and stress the importance of individualised predictions when examining cortical thickness abnormalities.

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Bayer, J. M. M., van Velzen, L. S., Pozzi, E., Davey, C., Han, L. K. M., Bauduin, S. E. E. C., Bauer, J., Benedetti, F., Berger, K., Bonnekoh, L. M., Brosch, K., Buelow, R., Couvy-Duchesne, B., Cullen, K. R., Dannlowski, U., Dima, D., Dohm, K., Evans, J. W., Fu, C. H. Y., Fuentes-Claramonte, P., Godlewska, B. R., Goltermann, J., Gonul, A. S., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Groenewold, N. A., Grotegerd, D., Gruber, O., Hahn, T., Hall, G. B., Hamilton, J. P., Harrison, B. J., Hatton, S. N., Hermesdorf, M., Hickie, I. B., Ho, T. C., Jahanshad, N., Jamieson, A. J., Jansen, A., Ka. 2025-03-18. Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study. https://doi.org/10.1101/2025.03.17.643677

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