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  5. ENIGMA‐DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross‐diagnostic psychiatric research

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Article
en
2020

ENIGMA‐DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross‐diagnostic psychiatric research

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en
2020
Vol 43 (1)
Vol. 43
DOI: 10.1002/hbm.24998

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Dan Joseph Stein
Dan Joseph Stein

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Peter Kochunov
L. Elliot Hong
Emily L. Dennis
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Abstract

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.

How to cite this publication

Peter Kochunov, L. Elliot Hong, Emily L. Dennis, Rajendra A. Morey, David F. Tate, Elisabeth A. Wilde, Mark W. Logue, Sinéad Kelly, Gary Donohoe, Pauline Favre, Josselin Houenou, Christopher R. K. Ching, Laurena Holleran, Ole A. Andreassen, Laura S. van Velzen, Lianne Schmaal, Julio E. Villalón‐Reina, Carrie E. Bearden, Fabrizio Piras, Gianfranco Spalletta, Odile A. van den Heuvel, Dick J. Veltman, Dan Joseph Stein, Meghann C. Ryan, Yunlong Tan, Theo G.M. van Erp, Jessica A. Turner, Elizabeth Haddad, Talia M. Nir, David C. Glahn, Paul M. Thompson, Neda Jahanshad (2020). ENIGMA‐DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross‐diagnostic psychiatric research. , 43(1), DOI: https://doi.org/10.1002/hbm.24998.

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Publication Details

Type

Article

Year

2020

Authors

32

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/hbm.24998

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