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White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging

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Abstract

Identifying data-driven biotypes of major depressive disorder (MDD) has promise for the clarification of diagnostic heterogeneity. However, few studies have focused on white-matter abnormalities for MDD subtyping. This study included 116 patients with MDD and 118 demographically-matched healthy controls assessed by diffusion tensor imaging and neurocognitive evaluation. Hierarchical clustering was applied to the major fiber tracts, in conjunction with tract-based spatial statistics, to reveal white-matter alterations associated with MDD. Clinical and neurocognitive differences were compared between identified subgroups and healthy controls. With fractional anisotropy extracted from 20 fiber tracts, cluster analysis revealed 3 subgroups based on the patterns of abnormalities. Patients in each subgroup versus healthy controls showed a stepwise pattern of white-matter alterations as follows: subgroup 1 (25.9% of patient sample), widespread white-matter disruption; subgroup 2 (43.1% of patient sample), intermediate and more localized abnormalities in aspects of the corpus callosum and left cingulate; and subgroup 3 (31.0% of patient sample), possible mild alterations, but no statistically significant tract disruption after controlling for family-wise error. The neurocognitive impairment in each subgroup accompanied the white-matter alterations: subgroup 1, deficits in sustained attention and delayed memory; subgroup 2, dysfunction in delayed memory; and subgroup 3, no significant deficits. Three subtypes of white-matter abnormality exist in individuals with major depression, those having widespread abnormalities suffering more neurocognitive impairments, which may provide evidence for parsing the heterogeneity of the disorder and help optimize type-specific treatment approaches.

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Acknowledgements

All participants in the study are most warmly thanked. This work was supported by the National Natural Science Foundation of China (81630030, 81130024, 81801326, and 81571320), the National Natural Science Foundation of China/Research Grants Council of Hong Kong Joint Research Scheme (81461168029), the National Basic Research Development Program of China (2016YFC0904300), the 1.3.5 Project for Disciplines of Excellence, West China Hospital of Sichuan University, the National High-Technology Research and Development Project (863 Project) of China (2015AA020513), and a Scientific Project of Sichuan Science and Technology Department, China (2015JY0173).

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Authors and Affiliations

  1. Mental Health Centre, West China Hospital, Sichuan University, Chengdu, 610041, China

    Sugai Liang, Qiang Wang, Wei Deng, Xiao Yang, Xiaojing Li, Jian Zhang, Chengcheng Zhang, Xiaohong Ma & Tao Li

  2. Huaxi Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China

    Sugai Liang, Wei Deng, Xiao Yang & Tao Li

  3. Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 XD, Nijmegen, Netherlands

    Xiangzhen Kong

  4. Big Data Research Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Zhong Zhang & Junming Shao

  5. Department of Psychiatry, University of Alberta, Edmonton, T6G 2B7, Canada

    Xin-min Li & Andrew J. Greenshaw

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  1. Sugai Liang
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  2. Qiang Wang
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Liang, S., Wang, Q., Kong, X. et al. White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging. Neurosci. Bull. 35, 867–876 (2019). https://doi.org/10.1007/s12264-019-00381-w

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  • DOI: https://doi.org/10.1007/s12264-019-00381-w

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