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.
Original language | English |
---|---|
Pages (from-to) | 194-206 |
Number of pages | 13 |
Journal | Human brain mapping |
Volume | 43 |
Issue number | 1 |
Early online date | 16 Apr 2020 |
DOIs | |
Publication status | Published - Jan 2022 |
Keywords
- DTI
- ENIGMA
- RVI
- big data
- cross-disorder
- white matter deficit patterns
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In: Human brain mapping, Vol. 43, No. 1, 01.2022, p. 194-206.
Research output: Contribution to journal › Review article › Academic › peer-review
TY - JOUR
T1 - ENIGMA-DTI
T2 - Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research
AU - Kochunov, Peter
AU - Hong, L Elliot
AU - Dennis, Emily L
AU - Morey, Rajendra A
AU - Tate, David F
AU - Wilde, Elisabeth A
AU - Logue, Mark
AU - Kelly, Sinead
AU - Donohoe, Gary
AU - Favre, Pauline
AU - Houenou, Josselin
AU - Ching, Christopher R K
AU - Holleran, Laurena
AU - Andreassen, Ole A
AU - van Velzen, Laura S
AU - Schmaal, Lianne
AU - Villalón-Reina, Julio E
AU - Bearden, Carrie E
AU - Piras, Fabrizio
AU - Spalletta, Gianfranco
AU - van den Heuvel, Odile A
AU - Veltman, Dick J
AU - Stein, Dan J
AU - Ryan, Meghann C
AU - Tan, Yunlong
AU - van Erp, Theo G M
AU - Turner, Jessica A
AU - Haddad, Liz
AU - Nir, Talia M
AU - Glahn, David C
AU - Thompson, Paul M
AU - Jahanshad, Neda
N1 - Funding Information: National Institute of Mental Health, Grant/Award Numbers: R01085953, R01MH117601, R21 MH116473; National Institutes of Health, Grant/Award Numbers: 5T32MH073526, R01 MH111671, R01 MH116147, R01 NS107739, R01EB015611, R01MH111671, R01MH112180, R01MH116948, R56 AG058854, S10 OD023696, S10OD023696, U01MH108148, U54 EB020403, 1R01MH121246‐01, R01 AG059874, R01 MH117601; Italian Ministry of Health, Grant/Award Numbers: RC 15‐16‐17‐18‐19/A, RC12‐13‐14‐15‐16‐17‐18‐19/A; Fondation pour la recherche médicale Bioinformatics for Biology 2014; South African Medical Research Council; Department of Defense, Chronic Effects of Neurotrauma Consortium (CENC), Grant/Award Numbers: 5 I01 RX002174, W81XWH‐13‐2‐0095; VA BLR&D, Grant/Award Numbers: K99NS096116, R01‐MH111671, I01BX003477; NHMRC, Grant/Award Number: 1140764; ENIGMA‐COINSTAC, Grant/Award Number: R01MH121246; ENIGMA Sex Differences, Grant/Award Number: R01MH116147; ENIGMA's NIH Big Data to Knowledge (BD2K); Health Research Board, Grant/Award Number: CDA‐2018‐001; Science Foundation Ireland, Grant/Award Number: 16ERCS3787; European Research Council, Grant/Award Number: ERC677467; SFARI Explorer Award; NIH/NIMH, Grant/Award Numbers: R01 MH100900, R01 MH085953; Kristian Gerhard Jebsen Stiftelsen, Grant/Award Number: SKGJ‐MED‐008; South‐East Norway Health Authority, Grant/Award Number: 2019108; Research Council of Norway, Grant/Award Numbers: 249711, 248980, 248778, 223273; T32 Postdoctoral Scholar Fellowship Trainee, Grant/Award Numbers: NIA T32AG058507, 5251831121 Funding information Funding Information: P.M.T. and N.J. are MPIs of a research related grant from Biogen, Inc., for research unrelated to the contents of this manuscript. C.R.K.C. has received partial research support from Biogen, Inc. (Boston, USA) for work unrelated to the topic of this manuscript. O.A.A. is a consultant to HealthLytix, Speakers honorarium from Lundbeck. In the past 3 years, D.J.S. has received research grants and/or consultancy honoraria from Lundbeck and Sun. L.E.H. has received or plans to receive research funding or consulting fees on research projects from Mitsubishi, Your Energy Systems LLC, Neuralstem, Taisho, Heptares, Pfizer, Sound Pharma, Takeda, and Regeneron. All other authors have no conflict of interest to declare. Funding Information: Support was received from the National Institutes of Health grants: R01MH111671, R01MH112180, R01MH116948, S10OD023696, 5T32MH073526, R01EB015611, U01MH108148, and NIMH R01085953 (CEB), R21 MH116473 (CEB), and R01MH117601. Core funding for ENIGMA was provided by the NIH Big Data to Knowledge (BD2K) program under consortium grant U54 EB020403 (PI: Thompson). Additional support was provided by grants to the ENIGMA World Aging Center (R56 AG058854; PI: Thompson), the ENIGMA Sex Differences Initiative (R01 MH116147; PI: Thompson), the ENIGMA-PGC PTSD Working Group (R01 MH111671; PI: Morey), the ENIGMA Epilepsy Working Group (R01 NS107739; to McDonald), a Kavli Foundation Neuroscience without Borders seed grant (to Jahanshad and Thompson), an NIH instrumentation grant (S10 OD023696 to Kochunov), and ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits (1R01MH121246-01, to Turner, Calhoun, and van Erp). Support was also provided by the Italian Ministry of Health, grant RC 15-16-17-18-19/A, Fondation pour la recherche médicale “Bioinformatics for Biology 2014” grant. These funding sources provided financial support to enable design and conduct of the study and collection, management, and analysis of the data. None of the funding agencies had a role in the interpretation of the data. None had a role in the preparation, review, or approval of the manuscript. None had a role in the decision to submit the manuscript for publication. N.J. is supported by R01 AG059874 and R01 MH117601 (to N.J. and L.S.). C.R.K.C. is supported by ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, T32 Postdoctoral Scholar Fellowship Trainee Grant 5251831121, NIA T32AG058507. O.A.A. is supported by Research Council of Norway (223273, 248778, 248980, 249711), South-East Norway Health Authority (2019108), and the Kristian Gerhard Jebsen Stiftelsen (SKGJ-MED-008). C.E.B. is supported by NIH/NIMH grant R01 MH085953, NIH/NIMH grant R01 MH100900, ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, and SFARI Explorer Award. G.D. is supported by funding from the European Research Council (ERC677467), Science Foundation Ireland (16ERCS3787), and the Health Research Board (CDA-2018-001). T.G.M.v.E. is supported by ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, ENIGMA Sex Differences R01MH116147, and ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits R01MH121246. L.S. is supported by a NHMRC Career Development Fellowship (1140764) and R01 MH117601 (to N.J. and L.S.). M.W.L. is supported by VA BLR&D I01BX003477 (PI: Logue), R01-MH111671 (PI: Morey). E.L.D. is supported by K99NS096116. D.F.T. is supported by Chronic Effects of Neurotrauma Consortium. E.A.W. is supported by the Department of Defense, Chronic Effects of Neurotrauma Consortium (CENC) Award W81XWH-13-2-0095, 5 I01 RX002174. D.J.S. is supported by the South African Medical Research Council. F.P. is supported from the Santa Lucia Foundation in Rome, Italy are funded by the Italian Ministry of Health grants RC12-13-14-15-16-17-18-19/A. J.E.V.-R. is supported by ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403. O.A.v.d.H. is supported by the Dutch Research Council (VIDI grant 91717306). Funding Information: Support was received from the National Institutes of Health grants: R01MH111671, R01MH112180, R01MH116948, S10OD023696, 5T32MH073526, R01EB015611, U01MH108148, and NIMH R01085953 (CEB), R21 MH116473 (CEB), and R01MH117601. Core funding for ENIGMA was provided by the NIH Big Data to Knowledge (BD2K) program under consortium grant U54 EB020403 (PI: Thompson). Additional support was provided by grants to the ENIGMA World Aging Center (R56 AG058854; PI: Thompson), the ENIGMA Sex Differences Initiative (R01 MH116147; PI: Thompson), the ENIGMA‐PGC PTSD Working Group (R01 MH111671; PI: Morey), the ENIGMA Epilepsy Working Group (R01 NS107739; to McDonald), a Kavli Foundation Neuroscience without Borders seed grant (to Jahanshad and Thompson), an NIH instrumentation grant (S10 OD023696 to Kochunov), and ENIGMA‐COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits (1R01MH121246‐01, to Turner, Calhoun, and van Erp). Support was also provided by the Italian Ministry of Health, grant RC 15‐16‐17‐18‐19/A, Fondation pour la recherche médicale “Bioinformatics for Biology 2014” grant. These funding sources provided financial support to enable design and conduct of the study and collection, management, and analysis of the data. None of the funding agencies had a role in the interpretation of the data. None had a role in the preparation, review, or approval of the manuscript. None had a role in the decision to submit the manuscript for publication. N.J. is supported by R01 AG059874 and R01 MH117601 (to N.J. and L.S.). C.R.K.C. is supported by ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, T32 Postdoctoral Scholar Fellowship Trainee Grant 5251831121, NIA T32AG058507. O.A.A. is supported by Research Council of Norway (223273, 248778, 248980, 249711), South‐East Norway Health Authority (2019108), and the Kristian Gerhard Jebsen Stiftelsen (SKGJ‐MED‐008). C.E.B. is supported by NIH/NIMH grant R01 MH085953, NIH/NIMH grant R01 MH100900, ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, and SFARI Explorer Award. G.D. is supported by funding from the European Research Council (ERC677467), Science Foundation Ireland (16ERCS3787), and the Health Research Board (CDA‐2018‐001). T.G.M.v.E. is supported by ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, ENIGMA Sex Differences R01MH116147, and ENIGMA‐COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits R01MH121246. L.S. is supported by a NHMRC Career Development Fellowship (1140764) and R01 MH117601 (to N.J. and L.S.). M.W.L. is supported by VA BLR&D I01BX003477 (PI: Logue), R01‐MH111671 (PI: Morey). E.L.D. is supported by K99NS096116. D.F.T. is supported by Chronic Effects of Neurotrauma Consortium. E.A.W. is supported by the Department of Defense, Chronic Effects of Neurotrauma Consortium (CENC) Award W81XWH‐13‐2‐0095, 5 I01 RX002174. D.J.S. is supported by the South African Medical Research Council. F.P. is supported from the Santa Lucia Foundation in Rome, Italy are funded by the Italian Ministry of Health grants RC12‐13‐14‐15‐16‐17‐18‐19/A. J.E.V.‐R. is supported by ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403. O.A.v.d.H. is supported by the Dutch Research Council (VIDI grant 91717306). Publisher Copyright: © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
KW - DTI
KW - ENIGMA
KW - RVI
KW - big data
KW - cross-disorder
KW - white matter deficit patterns
UR - http://www.scopus.com/inward/record.url?scp=85083785823&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/hbm.24998
DO - https://doi.org/10.1002/hbm.24998
M3 - Review article
C2 - 32301246
SN - 1065-9471
VL - 43
SP - 194
EP - 206
JO - Human brain mapping
JF - Human brain mapping
IS - 1
ER -