Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics

Wenyi Xiao; Rachel D Woodham; Yuhan Cui; Junhao Wen; Mathilde Antoniades; Dhivya Srinivasan; Yong Fan; Guray Erus; Jose A Garcia; Stephen R Arnott; Taolin Chen; Ki Sueng Choi; Cherise Chin Fatt; Benicio N Frey; Vibe G Frokjaer; Melanie Ganz; Beata R Godlewska; Stefanie Hassel; Keith Ho; Andrew M McIntosh; Kun Qin; Susan Rotzinger; Matthew D Sacchet; Jonathan Savitz; Haochang Shou; Ashish Singh; Aleks Stolicyn; Irina Strigo; Stephen C Strother; Duygu Tosun; Dongtao Wei; Ian M Anderson; W Edward Craighead; J F William Deakin; Boadie W Dunlop; Rebecca Elliott; Qiyong Gong; Ian H Gotlib; Catherine J Harmer; Sidney H Kennedy; Gitte M Knudsen; Helen S Mayberg; Martin P Paulus; Jiang Qiu; Madhukar H Trivedi; Heather C Whalley; Chao-Gan Yan; Allan H Young; Christos Davatzikos; Cynthia H Y Fu

doi:10.1038/s43856-025-01219-5

Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics

Wenyi Xiao, Rachel D Woodham, Yuhan Cui, Junhao Wen, Mathilde Antoniades, Dhivya Srinivasan, Yong Fan, Guray Erus, Jose A Garcia, Stephen R Arnott, Taolin Chen, Ki Sueng Choi, Cherise Chin Fatt, Benicio N Frey, Vibe G Frokjaer, Melanie Ganz, Beata R Godlewska, Stefanie Hassel, Keith Ho, Andrew M McIntoshKun Qin, Susan Rotzinger, Matthew D Sacchet, Jonathan Savitz, Haochang Shou, Ashish Singh, Aleks Stolicyn, Irina Strigo, Stephen C Strother, Duygu Tosun, Dongtao Wei, Ian M Anderson, W Edward Craighead, J F William Deakin, Boadie W Dunlop, Rebecca Elliott, Qiyong Gong, Ian H Gotlib, Catherine J Harmer, Sidney H Kennedy, Gitte M Knudsen, Helen S Mayberg, Martin P Paulus, Jiang Qiu, Madhukar H Trivedi, Heather C Whalley, Chao-Gan Yan, Allan H Young, Christos Davatzikos, Cynthia H Y Fu

Abstract

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its diagnosis relies on clinical symptoms alone.

METHODS: Using the semi-supervised machine learning algorithm, Heterogeneity through Discriminative Analysis (HYDRA), we had identified two neuroanatomical dimensions in deeply phenotyped (i.e., comprehensively assessed across neuroimaging, clinical, and behavioural domains), medication-free participants with MDD from the COORDINATE-MDD consortium. In the present study, we apply this pre-trained HYDRA model to the UK Biobank (UKB) to validate these dimensions in a large general population and a subsample with current depressive symptoms.

RESULTS: Dimension 2 (D2), compared to Dimension 1 (D1), is characterized by reduced grey and white matter volumes and limited treatment response to antidepressant and placebo medications. Out-of-sample validation in the UKB general population (n = 37,235) confirms these neuroanatomical features and reveals D2 associations with cognitive impairments, adverse life events, self-harm and suicide attempts, a pro-atherogenic lipid profile, and genetic links to neurodegenerative traits. Similar profiles are observed in the UKB subsample with current depressive symptoms (n = 1455).

CONCLUSIONS: D1 and D2 represent distinct neurobiological mechanisms underlying MDD. The validation in a general population-based cohort and in a cohort sample with depressive symptoms delineates mechanisms underlying heterogeneity in MDD.

Originalsprog	Engelsk
Artikelnummer	502
Tidsskrift	Communications medicine
Vol/bind	5
Udgave nummer	1
ISSN	2730-664X
DOI	https://doi.org/10.1038/s43856-025-01219-5
Status	Udgivet - 15 nov. 2025

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Xiao, W., Woodham, R. D., Cui, Y., Wen, J., Antoniades, M., Srinivasan, D., Fan, Y., Erus, G., Garcia, J. A., Arnott, S. R., Chen, T., Choi, K. S., Chin Fatt, C., Frey, B. N., Frokjaer, V. G., Ganz, M., Godlewska, B. R., Hassel, S., Ho, K., ... Fu, C. H. Y. (2025). Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics. Communications medicine, 5(1), Artikel 502. https://doi.org/10.1038/s43856-025-01219-5

Xiao, W, Woodham, RD, Cui, Y, Wen, J, Antoniades, M, Srinivasan, D, Fan, Y, Erus, G, Garcia, JA, Arnott, SR, Chen, T, Choi, KS, Chin Fatt, C, Frey, BN, Frokjaer, VG , Ganz, M, Godlewska, BR, Hassel, S, Ho, K, McIntosh, AM, Qin, K, Rotzinger, S, Sacchet, MD, Savitz, J, Shou, H, Singh, A, Stolicyn, A, Strigo, I, Strother, SC, Tosun, D, Wei, D, Anderson, IM, Craighead, WE, Deakin, JFW, Dunlop, BW, Elliott, R, Gong, Q, Gotlib, IH, Harmer, CJ, Kennedy, SH, Knudsen, GM, Mayberg, HS, Paulus, MP, Qiu, J, Trivedi, MH, Whalley, HC, Yan, C-G, Young, AH, Davatzikos, C & Fu, CHY 2025, 'Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics', Communications medicine, bind 5, nr. 1, 502. https://doi.org/10.1038/s43856-025-01219-5

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title = "Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics",

abstract = "BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its diagnosis relies on clinical symptoms alone.METHODS: Using the semi-supervised machine learning algorithm, Heterogeneity through Discriminative Analysis (HYDRA), we had identified two neuroanatomical dimensions in deeply phenotyped (i.e., comprehensively assessed across neuroimaging, clinical, and behavioural domains), medication-free participants with MDD from the COORDINATE-MDD consortium. In the present study, we apply this pre-trained HYDRA model to the UK Biobank (UKB) to validate these dimensions in a large general population and a subsample with current depressive symptoms.RESULTS: Dimension 2 (D2), compared to Dimension 1 (D1), is characterized by reduced grey and white matter volumes and limited treatment response to antidepressant and placebo medications. Out-of-sample validation in the UKB general population (n = 37,235) confirms these neuroanatomical features and reveals D2 associations with cognitive impairments, adverse life events, self-harm and suicide attempts, a pro-atherogenic lipid profile, and genetic links to neurodegenerative traits. Similar profiles are observed in the UKB subsample with current depressive symptoms (n = 1455).CONCLUSIONS: D1 and D2 represent distinct neurobiological mechanisms underlying MDD. The validation in a general population-based cohort and in a cohort sample with depressive symptoms delineates mechanisms underlying heterogeneity in MDD.",

author = "Wenyi Xiao and Woodham, {Rachel D} and Yuhan Cui and Junhao Wen and Mathilde Antoniades and Dhivya Srinivasan and Yong Fan and Guray Erus and Garcia, {Jose A} and Arnott, {Stephen R} and Taolin Chen and Choi, {Ki Sueng} and {Chin Fatt}, Cherise and Frey, {Benicio N} and Frokjaer, {Vibe G} and Melanie Ganz and Godlewska, {Beata R} and Stefanie Hassel and Keith Ho and McIntosh, {Andrew M} and Kun Qin and Susan Rotzinger and Sacchet, {Matthew D} and Jonathan Savitz and Haochang Shou and Ashish Singh and Aleks Stolicyn and Irina Strigo and Strother, {Stephen C} and Duygu Tosun and Dongtao Wei and Anderson, {Ian M} and Craighead, {W Edward} and Deakin, {J F William} and Dunlop, {Boadie W} and Rebecca Elliott and Qiyong Gong and Gotlib, {Ian H} and Harmer, {Catherine J} and Kennedy, {Sidney H} and Knudsen, {Gitte M} and Mayberg, {Helen S} and Paulus, {Martin P} and Jiang Qiu and Trivedi, {Madhukar H} and Whalley, {Heather C} and Chao-Gan Yan and Young, {Allan H} and Christos Davatzikos and Fu, {Cynthia H Y}",

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doi = "10.1038/s43856-025-01219-5",

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T1 - Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics

AU - Xiao, Wenyi

AU - Woodham, Rachel D

AU - Cui, Yuhan

AU - Wen, Junhao

AU - Antoniades, Mathilde

AU - Srinivasan, Dhivya

AU - Fan, Yong

AU - Erus, Guray

AU - Garcia, Jose A

AU - Arnott, Stephen R

AU - Chen, Taolin

AU - Choi, Ki Sueng

AU - Chin Fatt, Cherise

AU - Frey, Benicio N

AU - Frokjaer, Vibe G

AU - Ganz, Melanie

AU - Godlewska, Beata R

AU - Hassel, Stefanie

AU - Ho, Keith

AU - McIntosh, Andrew M

AU - Qin, Kun

AU - Rotzinger, Susan

AU - Sacchet, Matthew D

AU - Savitz, Jonathan

AU - Shou, Haochang

AU - Singh, Ashish

AU - Stolicyn, Aleks

AU - Strigo, Irina

AU - Strother, Stephen C

AU - Tosun, Duygu

AU - Wei, Dongtao

AU - Anderson, Ian M

AU - Craighead, W Edward

AU - Deakin, J F William

AU - Dunlop, Boadie W

AU - Elliott, Rebecca

AU - Gong, Qiyong

AU - Gotlib, Ian H

AU - Harmer, Catherine J

AU - Kennedy, Sidney H

AU - Knudsen, Gitte M

AU - Mayberg, Helen S

AU - Paulus, Martin P

AU - Qiu, Jiang

AU - Trivedi, Madhukar H

AU - Whalley, Heather C

AU - Yan, Chao-Gan

AU - Young, Allan H

AU - Davatzikos, Christos

AU - Fu, Cynthia H Y

PY - 2025/11/15

Y1 - 2025/11/15

N2 - BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its diagnosis relies on clinical symptoms alone.METHODS: Using the semi-supervised machine learning algorithm, Heterogeneity through Discriminative Analysis (HYDRA), we had identified two neuroanatomical dimensions in deeply phenotyped (i.e., comprehensively assessed across neuroimaging, clinical, and behavioural domains), medication-free participants with MDD from the COORDINATE-MDD consortium. In the present study, we apply this pre-trained HYDRA model to the UK Biobank (UKB) to validate these dimensions in a large general population and a subsample with current depressive symptoms.RESULTS: Dimension 2 (D2), compared to Dimension 1 (D1), is characterized by reduced grey and white matter volumes and limited treatment response to antidepressant and placebo medications. Out-of-sample validation in the UKB general population (n = 37,235) confirms these neuroanatomical features and reveals D2 associations with cognitive impairments, adverse life events, self-harm and suicide attempts, a pro-atherogenic lipid profile, and genetic links to neurodegenerative traits. Similar profiles are observed in the UKB subsample with current depressive symptoms (n = 1455).CONCLUSIONS: D1 and D2 represent distinct neurobiological mechanisms underlying MDD. The validation in a general population-based cohort and in a cohort sample with depressive symptoms delineates mechanisms underlying heterogeneity in MDD.

AB - BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its diagnosis relies on clinical symptoms alone.METHODS: Using the semi-supervised machine learning algorithm, Heterogeneity through Discriminative Analysis (HYDRA), we had identified two neuroanatomical dimensions in deeply phenotyped (i.e., comprehensively assessed across neuroimaging, clinical, and behavioural domains), medication-free participants with MDD from the COORDINATE-MDD consortium. In the present study, we apply this pre-trained HYDRA model to the UK Biobank (UKB) to validate these dimensions in a large general population and a subsample with current depressive symptoms.RESULTS: Dimension 2 (D2), compared to Dimension 1 (D1), is characterized by reduced grey and white matter volumes and limited treatment response to antidepressant and placebo medications. Out-of-sample validation in the UKB general population (n = 37,235) confirms these neuroanatomical features and reveals D2 associations with cognitive impairments, adverse life events, self-harm and suicide attempts, a pro-atherogenic lipid profile, and genetic links to neurodegenerative traits. Similar profiles are observed in the UKB subsample with current depressive symptoms (n = 1455).CONCLUSIONS: D1 and D2 represent distinct neurobiological mechanisms underlying MDD. The validation in a general population-based cohort and in a cohort sample with depressive symptoms delineates mechanisms underlying heterogeneity in MDD.

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U2 - 10.1038/s43856-025-01219-5

DO - 10.1038/s43856-025-01219-5

M3 - Journal article

C2 - 41258534

SN - 2730-664X

VL - 5

JO - Communications medicine

JF - Communications medicine

IS - 1

M1 - 502

ER -

Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics

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