Evidence map›Paper›PMID 31695168›Full record

Trial reportMolecular psychiatry2020

Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder.

Mayuresh S Korgaonkar, Andrea N Goldstein-Piekarski, Alexander Fornito, Leanne M Williams

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Molecular psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 3 pooled it
8.7field-weighted citation impact, top 2% of its field
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

82 citing papers in PubMed, 3 syntheses or guidelines pooled it, 160 citations in OpenAlex.

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  19. Intranasal (R)-ketamine modulates depression symptom and neurotransmitters-associated human brain connectivity.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
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  20. Article

22 more citing papers are in PubMed but not listed here.

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

4 authors at 3 institutions in 2 countries.

Mayuresh S KorgaonkarThe Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia. m.korgaonkar@sydney.edu.au.
Andrea N Goldstein-PiekarskiDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA.
Alexander FornitoBrain and Mental Health Research Hub, Turner Institute for Brain and Mental Health & Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Leanne M WilliamsThe Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia. leawilliams@stanford.edu.ORCID http://orcid.org/0000-0001-9987-7360
VA Palo Alto Health Care System · USMonash University · AUThe University of Sydney · AU

Funding

Mapping connectomes for disordered emotional statesU01MH109985 · NIMH · STANFORD UNIVERSITY · PI WILLIAMS, LEANNE · 2017 to 2020
$3.1M
NIMH NIH HHS U01 MH109985
6 · The paper itself

Abstract

Although major depressive disorder (MDD) is associated with altered functional coupling between disparate neural networks, the degree to which such measures are ameliorated by antidepressant treatment is unclear. It is also unclear whether functional connectivity can be used as a predictive biomarker of treatment response. Here, we used whole-brain functional connectivity analysis to identify neural signatures of remission following antidepressant treatment, and to identify connectomic predictors of treatment response. 163 MDD and 62 healthy individuals underwent functional MRI during pre-treatment baseline and 8-week follow-up sessions. Patients were randomized to escitalopram, sertraline or venlafaxine-XR antidepressants and assessed at follow-up for remission. Baseline measures of intrinsic functional connectivity between each pair of 333 regions were analyzed to identify pre-treatment connectomic features that distinguish remitters from non-remitters. We then interrogated these connectomic differences to determine if they changed post-treatment, distinguished patients from controls, and were modulated by medication type. Irrespective of medication type, remitters were distinguished from non-remitters by greater connectivity within the default mode network (DMN); specifically, between the DMN, fronto-parietal and somatomotor networks, the DMN and visual, limbic, auditory and ventral attention networks, and between the fronto-parietal and somatomotor networks with cingulo-opercular and dorsal attention networks. This baseline hypo-connectivity for non-remitters also distinguished them from controls and increased following treatment. In contrast, connectivity for remitters was higher than controls at baseline and also following remission, suggesting a trait-like connectomic characteristic. Increased functional connectivity within and between large-scale intrinsic brain networks may characterize acute recovery with antidepressants in depression.

Indexed as

ConnectomeNeural PathwaysRemission InductionAdultAntidepressive AgentsBiomarkersBrainCitalopramFemaleHumansMagnetic Resonance ImagingMajor Depressive DisorderMaleSertralineVenlafaxine HydrochlorideYoung AdultAntidepressive AgentsBiomarkersCitalopramSertralineVenlafaxine Hydrochloride

Identifiers

PMID31695168
PMCPMC7303006
OpenAlexW2986842001

What OpenQuestion 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 OpenQuestion graph.