Evidence map›Paper›PMID 40172866›Full record

ArticleJAMA psychiatry2025

Functional vs Structural Cortical Deficit Pattern Biomarkers for Major Depressive Disorder.

Peter Kochunov, Bhim M Adhikari, David Keator, Daniel Amen, Si Gao, Nicole R Karcher, Demetrio Labate, Robert Azencott, Yewen Huang, Hussain Syed and 14 more

Abstract read
In one paragraph

Article in JAMA psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Transdiagnostic mapping of common and specific regional homogeneity alterations across affective and psychotic disorders.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Pooled it
  2. Article
  3. Article
  4. Brainwide Structural Markers of Familial and Clinical Risk for Bipolar Disorder in Youth.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Molecular, Structural, and Functional Neuroimaging in Major Depression.Advances in experimental medicine and biology · 2026
    Review
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Peter KochunovDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
Bhim M AdhikariDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
David KeatorAmen Clinics Inc, Costa Mesa, California.
Daniel AmenAmen Clinics Inc, Costa Mesa, California.
Si GaoDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
Nicole R KarcherDepartment of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri.
Demetrio LabateDepartments of Mathematics, University of Houston, Houston, Texas.
Robert AzencottDepartments of Mathematics, University of Houston, Houston, Texas.
Yewen HuangDepartments of Mathematics, University of Houston, Houston, Texas.
Hussain SyedDepartments of Mathematics, University of Houston, Houston, Texas.
Hongjie KeDepartment of Biostatistics, University of Maryland College Park, College Park.
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey.
Danny J J WangLaboratory of Functional MRI Technology, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles.
Braxton D MitchellDepartment of Medicine, University of Maryland School of Medicine, Baltimore.
Jessica A TurnerDepartment of Psychiatry and Behavioral Science, The Ohio State University College of Medicine, Columbus.
Theo G M van ErpClinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine.
Neda JahanshadImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey.
Yizhou MaDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
Xiaoming DuDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
William BurroughsDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
Shuo ChenDepartment of Psychiatry, University of Maryland School of Medicine, Baltimore.
Tianzhou MaDepartment of Biostatistics, University of Maryland College Park, College Park.
Jair C SoaresDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.
L Elliot HongDepartment of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston.

Funding

SOLAR-Eclipse Computational Tools for Imaging GeneticsR01EB015611 · NIBIB · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KOCHUNOV, PETER V. · 2012 to 2024
$5.0M
ENIGMA-COINSTAC-APOE2 Functional and structural connectome protective mechanisms for Alzheimer’s disease and mood disorders: Request for supplemental funds for NIH R01:1R01MH121246R01MH121246 · NIMH · OHIO STATE UNIVERSITY · PI CALHOUN, VINCE D, TURNER, JESS · 2019 to 2023
$5.0M
Amish Connectome Project on Mental IllnessU01MH108148 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI HONG, L ELLIOT ELLIOT, KOCHUNOV, PETER V. · 2015 to 2018
$4.3M
Towards Multisystem-Brain Successful Aging in Schizophrenia SpectrumR01MH116948 · NIMH · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HONG, L ELLIOT ELLIOT · 2018 to 2022
$3.7M
Lifespan Vascular Biology on White MatterRF1NS114628 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HONG, L ELLIOT ELLIOT, KOCHUNOV, PETER V. · 2020 to 2020
$3.1M
Global studies into the Genetic Architecture of the Brain's White Matter Network through Harmonized and Coordinated Analyses in the ENIGMA-ConsortiumR01MH134004 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Neda Jahanshad · 2023 to 2026
$2.6M
Global Deep Learning Initiative to Understand Outcomes in Major DepressionR01MH131806 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Roberto Goya-Maldonado, PAUL M THOMPSON · 2023 to 2026
$2.6M
The Vascular Axis in Schizophrenia Brain-Body AgingR01MH133812 · NIMH · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI L Elliot Elliot Hong · 2024 to 2026
$2.2M
Redefine Trans-Neuropsychiatric Disorder Brain Patterns through Big-Data and Machine LearningRF1MH123163 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI KOCHUNOV, PETER V., THOMPSON, PAUL M · 2021 to 2021
$1.2M
Lifespan Vascular Biology on White MatterR01NS114628 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HONG, L ELLIOT ELLIOT, KOCHUNOV, PETER V. · 2024 to 2024
$770k
Hybrid GPU/CPU Computing Resource to Support Connectomic and GenomicsS10OD023696 · OD · UNIVERSITY OF MARYLAND BALTIMORE · PI KOCHUNOV, PETER V. · 2018 to 2018
$593k
A novel transcriptome-connectome approach to study the neurogenetic mechanism of nicotine and cannabis addictionK01DA059603 · NIDA · UNIV OF MARYLAND, COLLEGE PARK · PI Tianzhou MA · 2024 to 2026
$579k
NIBIB NIH HHS R01 EB015611NIDA NIH HHS K01 DA059603NIH HHS S10 OD023696NIMH NIH HHS R01 MH116948NIMH NIH HHS R01 MH121246NIMH NIH HHS R01 MH131806NIMH NIH HHS R01 MH133812NIMH NIH HHS R01 MH134004NIMH NIH HHS RF1 MH123163NIMH NIH HHS U01 MH108148NINDS NIH HHS R01 NS114628NINDS NIH HHS RF1 NS114628
6 · The paper itself

Abstract

Importance: Major depressive disorder (MDD) is a severe mental illness characterized more by functional rather than structural brain abnormalities. The pattern of regional homogeneity (ReHo) deficits in MDD may relate to underlying regional hypoperfusion. Capturing this functional deficit pattern provides a brain pattern-based biomarker for MDD that is linked to the underlying pathophysiology. Objective: To examine whether cortical ReHo patterns provide a replicable biomarker for MDD that is more sensitive than reduced cortical thickness and evaluate whether the ReHo MDD deficit pattern reflects regional cerebral blood flow (RCBF) deficit patterns in MDD and whether a regional vulnerability index (RVI) thus constructed may provide a concise brain pattern-based biomarker for MDD. Design, Settings, and Participants: The UK Biobank (UKBB) participants had ReHo and structural measurements. Participants from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) Consortium were included for measuring the MDD structural cortical deficit pattern. The UKBB ReHo and ENIGMA cortical thickness effect sizes for MDD were used to test the deficit patterns in the Amish Connectome Project (ACP) with ReHo, structural, and RCBF data. Finally, the Ament Clinic Inc (ACI) sample had RCBF data measured using single-photon emission computed tomography. Data were analyzed from August 2021 to September 2024. Exposures: ReHo and structural measurements. Results: Included in this analysis were 4 datasets: (1) UKBB (N = 4810 participants; 2220 with recurrent MDD and 2590 controls; mean [SD] age, 63.0 [7.5] years; 1121 female [50%]), (2) ENIGMA (N = 10 115 participants; 2148 with MDD and 7957 healthy controls; mean [SD] age, 39.9 [10.0] years; 5927 female [59%]), (3) ACP (N = 204 participants; 68 with a lifetime diagnosis of MDD and 136 controls; mean [SD] age, 41.0 [14.5] years; 104 female [51%]), and (4) ACI (N = 372 participants; 296 with recurrent MDD and 76 controls; mean [SD] age, 45.3 [17.2] years; 189 female [51%]). MDD participants had lower cortical ReHo in the cingulum, superior temporal lobe, frontal lobe, and several other areas, with no significant differences in cortical thickness. The regional pattern of ReHo MDD effect sizes was significantly correlated with that of RCBF obtained from 2 independent datasets (Pearson r = 0.52 and Pearson r = 0.46; P < 10-4). ReHo and RCBF functional RVIs showed numerically stronger effect sizes (Cohen d = 0.33-0.90) compared with structural RVIs (Cohen d = 0.09-0.20). Elevated ReHo-based RVI-MDD values in individuals with MDD were associated with higher depression symptom severity across cohorts. Conclusions and Relevance: Results of this case-control study suggest that the ReHo MDD deficit pattern reflected cortical hypoperfusion and was regionally specific in MDD. ReHo-based RVI may serve as a sensitive functional biomarker for MDD.

Indexed as

Cerebral CortexCerebrovascular CirculationMajor Depressive DisorderAdultAgedBiomarkersConnectomeFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedBiomarkers

Identifiers

PMID40172866
PMCPMC11966481

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.