. 2024 May 2;5(7):100987.

doi: 10.1016/j.patter.2024.100987. eCollection 2024 Jul 12.

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

Kelly Rootes-Murdy¹, Sandeep Panta¹, Ross Kelly¹, Javier Romero¹, Yann Quidé^{2

3}, Murray J Cairns^{4

5

6}, Carmel Loughland^{5

6}, Vaughan J Carr^{3

7

8}, Stanley V Catts⁹, Assen Jablensky¹⁰, Melissa J Green^{3

7}, Frans Henskens^{6

11

12}, Dylan Kiltschewskij^{4

5

6}, Patricia T Michie^{6

13}, Bryan Mowry^{14

15}, Christos Pantelis^{16

17}, Paul E Rasser^{6

12}, William R Reay^{4

5

6}, Ulrich Schall^{5

6}, Rodney J Scott⁴, Oliver J Watkeys^{3

7}, Gloria Roberts⁷, Philip B Mitchell⁷, Janice M Fullerton^{3

18}, Bronwyn J Overs³, Masataka Kikuchi¹⁹, Ryota Hashimoto²⁰, Junya Matsumoto²⁰, Masaki Fukunaga²¹, Perminder S Sachdev^{22

23}, Henry Brodaty²², Wei Wen²², Jiyang Jiang²², Negar Fani²⁴, Timothy D Ely²⁴, Adriana Lorio²⁵, Jennifer S Stevens^{24

26}, Kerry Ressler^{27

28}, Tanja Jovanovic²⁹, Sanne J H van Rooij²⁴, Lydia M Federmann^{30

31}, Christiane Jockwitz^{30

32}, Alexander Teumer³³, Andreas J Forstner^{30

31}, Svenja Caspers^{30

32}, Sven Cichon^{30

34

35}, Sergey M Plis¹, Anand D Sarwate³⁶, Vince D Calhoun¹

Affiliations

¹ Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
² School of Psychology, University of New South Wales, Sydney, NSW, Australia.
³ Neuroscience Research Australia, Sydney, NSW, Australia.
⁴ School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia.
⁵ Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia.
⁶ Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
⁷ Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia.
⁸ Department of Psychiatry, Monash University, Clayton, VIC, Australia.
⁹ School of Medicine, University of Queensland, Brisbane, QLD, Australia.
¹⁰ University of Western Australia, Perth, WA, Australia.
¹¹ School of Medicine & Public Health, University of Newcastle, Newcastle, NSW, Australia.
¹² Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, NSW, Australia.
¹³ School of Psychological Sciences, University of Newcastle, Callaghan, NSW, Australia.
¹⁴ Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.
¹⁵ Queensland Centre for Mental Health Research, University of Queensland, Brisbane, QLD, Australia.
¹⁶ Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Carlton South, VIC, Australia.
¹⁷ Florey Institute of Neuroscience & Mental Health, Parkville, VIC, Australia.
¹⁸ School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia.
¹⁹ Department of Computational Biology and Medical Sciences, University of Tokyo, Chiba, Japan.
²⁰ Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan.
²¹ Section of Brain Function Information, National Institute for Physiological Sciences, Aichi, Japan.
²² Centre for Healthy Brain Aging, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia.
²³ Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.
²⁴ Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA.
²⁵ American Cancer Institute, Kennesaw, GA, USA.
²⁶ Atlanta VA Medical Center, Decatur, GA, USA.
²⁷ McLean Hospital, Harvard Medical School, Belmont, MA, USA.
²⁸ Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
²⁹ Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA.
³⁰ Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.
³¹ Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany.
³² Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany.
³³ Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
³⁴ Department of Biomedicine, University of Basel, Basel, Switzerland.
³⁵ Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland.
³⁶ Department of Electrical and Computer Engineering, Rutgers University-New Brunswick, Piscataway, NJ, USA.

PMID: 39081570
PMCID: PMC11284501
DOI: 10.1016/j.patter.2024.100987

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

Kelly Rootes-Murdy et al. Patterns (N Y). 2024.

. 2024 May 2;5(7):100987.

doi: 10.1016/j.patter.2024.100987. eCollection 2024 Jul 12.

Authors

Affiliations

¹ Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
² School of Psychology, University of New South Wales, Sydney, NSW, Australia.
³ Neuroscience Research Australia, Sydney, NSW, Australia.
⁴ School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia.
⁵ Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia.
⁶ Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
⁷ Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia.
⁸ Department of Psychiatry, Monash University, Clayton, VIC, Australia.
⁹ School of Medicine, University of Queensland, Brisbane, QLD, Australia.
¹⁰ University of Western Australia, Perth, WA, Australia.
¹¹ School of Medicine & Public Health, University of Newcastle, Newcastle, NSW, Australia.
¹² Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, NSW, Australia.
¹³ School of Psychological Sciences, University of Newcastle, Callaghan, NSW, Australia.
¹⁴ Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.
¹⁵ Queensland Centre for Mental Health Research, University of Queensland, Brisbane, QLD, Australia.
¹⁶ Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Carlton South, VIC, Australia.
¹⁷ Florey Institute of Neuroscience & Mental Health, Parkville, VIC, Australia.
¹⁸ School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia.
¹⁹ Department of Computational Biology and Medical Sciences, University of Tokyo, Chiba, Japan.
²⁰ Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan.
²¹ Section of Brain Function Information, National Institute for Physiological Sciences, Aichi, Japan.
²² Centre for Healthy Brain Aging, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia.
²³ Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.
²⁴ Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA.
²⁵ American Cancer Institute, Kennesaw, GA, USA.
²⁶ Atlanta VA Medical Center, Decatur, GA, USA.
²⁷ McLean Hospital, Harvard Medical School, Belmont, MA, USA.
²⁸ Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
²⁹ Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA.
³⁰ Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.
³¹ Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany.
³² Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany.
³³ Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
³⁴ Department of Biomedicine, University of Basel, Basel, Switzerland.
³⁵ Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland.
³⁶ Department of Electrical and Computer Engineering, Rutgers University-New Brunswick, Piscataway, NJ, USA.

PMID: 39081570
PMCID: PMC11284501
DOI: 10.1016/j.patter.2024.100987

Abstract

Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns (n = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders.

Keywords: COINSTAC; PTSD; decentralized; federated analysis; gray matter; mild cognitive impairment; mood disorders; psychiatric disorders; regression; transdiagnostic.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

**Figure 1**
Gray matter alteration in schizophrenia Alterations in the gray matter of individuals with schizophrenia when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 2**
Gray matter alteration in bipolar disorder Alterations in the gray matter of individuals with bipolar disorder when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 3**
Gray matter alteration in major depressive disorder Alterations in the gray matter of individuals with major depressive disorder when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 4**
Gray matter alteration in post-traumatic stress disorder Alterations in the gray matter of individuals with post-traumatic stress disorder when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 5**
Gray matter alteration in autism spectrum disorder Alterations in the gray matter of individuals with autism spectrum disorder when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 6**
Gray matter alteration in mild cognitive impairment Alterations in the gray matter of individuals with mild cognitive impairment when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 7**
Gray matter alteration in spectrum Alterations in the gray matter of individuals identified with a spectrum disorder when compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 8**
Gray matter alteration in unaffected first-degree relatives Alterations in the gray matter of unaffected relatives compared to healthy volunteers. The colormap shows the -log(p) value; warm colors are used for positive values and cool colors for negative values.

**Figure 9**
Heatmap of spatial correlations Correlations for each pair of diagnostic group comparisons. Rel, unaffected relatives; PTSD, post-traumatic stress disorder; MCI, mild cognitive impairment; BP, bipolar disorder; ASD, autism spectrum disorder; MD, major depressive disorder; SZ, schizophrenia; Spect, spectrum.

**Figure 10**
Heatmap of spatial correlations with MCI correlated out of comparisons Correlations for each pair of diagnostic group comparisons. Rel, unaffected relatives; PTSD, post-traumatic stress disorder; MCI, mild cognitive impairment; BP, bipolar disorder; ASD, autism spectrum disorder; MD, major depressive disorder; SZ, schizophrenia; Spect, spectrum.

**Figure 11**
The COINSTAC architecture A diagram of the COINSTAC architecture, including both client nodes and remote services. The COINSTAC application uses standard web communication protocols to transfer (meta-)data between each client node and a publicly accessible remote node via an API gateway. Client nodes and the remote node run computations in a pipeline, with client nodes sending meta-data derived from local data and the remote node aggregating and running required computations, sending results back to client nodes for either final output or iteration if required. Pipeline results are stored in a noSQL data store provided by MongoDB.

See this image and copyright information in PMC

References

1. American Psychiatric Association . American Psychiatric Association; 2013. Diagnostic and Statistical Manual of Mental Disorders: DSM-5. - DOI
1. Forbes M.K., Neo B., Nezami O.M., Fried E.I., Faure K., Michelsen B., Twose M., Dras M. OSF; 2023. Elemental Psychopathology: Distilling Constituent Symptoms and Patterns of Repetition in the Diagnostic Criteria of the DSM-5. - DOI - PubMed
1. Gupta C.N., Calhoun V.D., Rachakonda S., Chen J., Patel V., Liu J., Segall J., Franke B., Zwiers M.P., Arias-Vasquez A., et al. Patterns of gray matter abnormalities in schizophrenia based on an international mega-analysis. Schizophr. Bull. 2015;41:1133–1142. doi: 10.1093/schbul/sbu177. - DOI - PMC - PubMed
1. Long J., Qin K., Wu Y., Li L., Zhou J. Gray matter abnormalities and associated familial risk endophenotype in individuals with first-episode bipolar disorder: Evidence from whole-brain voxel-wise meta-analysis. Asian J. Psychiatr. 2022;74 doi: 10.1016/j.ajp.2022.103179. - DOI - PubMed
1. Lee D.-K., Lee H., Park K., Joh E., Kim C.-E., Ryu S. Common gray and white matter abnormalities in schizophrenia and bipolar disorder. PLoS One. 2020;15 doi: 10.1371/journal.pone.0232826. - DOI - PMC - PubMed

Grants and funding

R33 NS120249/NS/NINDS NIH HHS/United States

LinkOut - more resources

Full Text Sources
- Elsevier Science
- PubMed Central

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

Affiliations

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Similar articles

References

Grants and funding

LinkOut - more resources

Full Text Sources

Abstract

Conflict of interest statement

Figures

Similar articles

References

Related information

Grants and funding

LinkOut - more resources

Full Text Sources