Evidence map›Paper›PMID 36586213›Full record

ArticleJournal of psychiatric research2023

Data driven clusters derived from resting state functional connectivity: Findings from the EMBARC study.

Cherise R Chin Fatt, Abu Minhajuddin, Manish K Jha, Taryn Mayes, A John Rush, Madhukar H Trivedi

Abstract read
In one paragraph

Article in Journal of psychiatric research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Trial
  2. 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

6 authors.

Cherise R Chin FattCenter for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Abu MinhajuddinDepartment of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Manish K JhaCenter for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Taryn MayesCenter for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
A John RushDepartment of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Duke-National University of Singapore, Singapore.
Madhukar H TrivediCenter for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA. Electronic address: madhukar.trivedi@utsouthwestern.edu.

Funding

Establishing Moderators/Biosignatures of Antidepressant Response- Clinical CareU01MH092221 · NIMH · UT SOUTHWESTERN MEDICAL CENTER · PI TRIVEDI, MADHUKAR H. · 2010 to 2015
$9.7M
Biosignatures of Treatment Remission in Major DepressionU01MH092250 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MCGRATH, PATRICK J, PARSEY, RAMIN V. · 2010 to 2015
$8.9M
UT Southwestern Center for Translational MedicineKL2TR003981 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI ARGENBRIGHT, KEITH EDWARD, TRIVEDI, MADHUKAR H. · 2021 to 2025
$5.9M
NCATS NIH HHS KL2 TR003981NIMH NIH HHS U01 MH092221NIMH NIH HHS U01 MH092250
6 · The paper itself

Abstract

backgroundTo address the clinical heterogeneity of Major Depressive Disorder (MDD), this investigation determined whether resting state functional magnetic resonance imaging (fMRI) could be deployed to identify circuit based homogeneous subgroups, and whether subgroups identified show differential treatment outcomes.

methodsPretreatment resting state fMRIs obtained from 278 outpatients with nonpsychotic MDD from Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression Study were used to create data-driven subgroups using CLICK clustering. These subgroups were then compared using baseline clinical data, as well as baseline-to-week 8 changes in depression severity measured using the 17-item Hamilton Rating Scale for Depression (HAMD

resultsThree subgroups were identified. Cluster-1 was characterized by overallhyperconnectivity coupled with profound hypoconnectivity between the supramarginal gyrus (executive control network; ECN) and the superior frontal cortex (dorsal attention network; DAN). Cluster-2 was characterized by overall hypoconnectivity coupled with hyperconnectivity between supramarginal gyrus (ECN) and superior frontal cortex (DAN). Cluster-3 showed hypoconnectivity, especially profound between the angular cortex (default mode network; DMN) and middle frontal cortex (ECN). While baseline clinical measures did not differentiate the three clusters, Cluster-3 had the remission rate (51.6%) compared to Cluster-1 and Cluster-2 (32.7% and 31.9%) when treated with sertraline. LIMITATIONS: Due to the exploratory nature of these analyses, there were no adjustments for multiple comparisons.

conclusionsBaseline functional connectivity can be used to subgroup patients with MDD that differ in acute phase treatment outcomes. Measures of connectivity may address the heterogeneity of MDD.

Indexed as

Major Depressive DisorderBrainCalcium PhosphatesCerebral CortexHumansMagnetic Resonance ImagingSertralineCalcium PhosphatesEmbarcSertralineCLICKData drivenEMBARCFunctional connectivityMajor depressive disorderRemission

Identifiers

PMID36586213
PMCPMC10177663

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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 OpenQuestion graph.