Evidence map›Paper›PMID 38908657›Full record

ArticleBiological psychiatry2025

Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated With Psychopathology Across Independent Cohorts.

Haley R Wang, Zhen-Qi Liu, Hajer Nakua, Catherine E Hegarty, Melanie Blair Thies, Pooja K Patel, Charles H Schleifer, Thomas P Boeck, Rachel A McKinney, Danielle Currin and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biological psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Temporal stability of functional network configurations and its relationship to cognition and psychopathology in early psychoses.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Haley R WangDepartment of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California.
Zhen-Qi LiuMontréal Neurological Institute, McGill University, Montréal, Québec, Canada.
Hajer NakuaCampbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada.
Catherine E HegartyDepartment of Psychology, University of California, Los Angeles, Los Angeles, California.
Melanie Blair ThiesDepartment of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York.
Pooja K PatelDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California; Desert Pacific Mental Illness Research, Education, and Clinical Center Greater Los Angeles VA Healthcare System, Los Angeles, California.
Charles H SchleiferDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California; David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.
Thomas P BoeckDepartment of Psychology, University of California, Los Angeles, Los Angeles, California.
Rachel A McKinneyDepartment of Psychology, University of California, Los Angeles, Los Angeles, California.
Danielle CurrinDepartment of Psychology, University of California, Los Angeles, Los Angeles, California.
Logan LeathemDepartment of Psychology, University of California, Los Angeles, Los Angeles, California.
Pamela DeRosseDepartment of Psychology, Stony Brook University, Stony Brook, New York.
Carrie E BeardenDepartment of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California.
Bratislav MisicMontréal Neurological Institute, McGill University, Montréal, Québec, Canada.
Katherine H KarlsgodtDepartment of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California. Electronic address: kkarlsgo@ucla.edu.

Funding

Human Connectome Project for Early PsychosisU01MH109977 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI BREIER, ALAN, SHENTON, MARTHA E. · 2016 to 2020
$5.5M
Multimodal Imaging of Executive and Reward Networks Across the Psychosis SpectrumR01MH101506 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KARLSGODT, KATHERINE HELEN · 2013 to 2017
$2.5M
Doctoral Training in Brain and Behavioral Development During Adolescence (UCLA BBDA)T32HD091059 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Mirella Dapretto, ANDREW J FULIGNI · 2018 to 2026
$1.7M
Microstructural Neuroimaging of Synaptic Pruning and Myelination in Adolescent PsychosisR21MH116433 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KARLSGODT, KATHERINE HELEN · 2019 to 2020
$429k
NICHD NIH HHS T32 HD091059NIMH NIH HHS R01 MH101506NIMH NIH HHS R21 MH116433NIMH NIH HHS U01 MH109977
6 · The paper itself

Abstract

backgroundPatients with early psychosis (EP) (within 3 years after psychosis onset) show significant variability, which makes predicting outcomes challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, which limits the development of early interventions.

methodsA data-driven approach, partial least squares correlation, was used across 2 independent datasets to examine multivariate relationships between white matter properties and symptomatology and to identify stable and generalizable signatures in EP. The primary cohort included patients with EP from the Human Connectome Project for Early Psychosis (n = 124). The replication cohort included patients with EP from the Feinstein Institute for Medical Research (n = 78) as part of the MEND (Multimodal Evaluation of Neural Disorders) Project. Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders.

resultsIn both cohorts, a significant latent component corresponded to a symptom profile that combined negative symptoms, primarily diminished expression, with specific somatic symptoms. Both latent components captured comprehensive features of white matter disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the partial least squares model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use.

conclusionsThis data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural white matter alterations in EP across diagnoses and datasets, showing strong covariance of these alterations with a unique profile of negative and somatic symptoms. These findings suggest the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

Indexed as

Psychotic DisordersWhite MatterAdolescentAdultBrainCohort StudiesConnectomeDiffusion Tensor ImagingFemaleHumansMagnetic Resonance ImagingMaleSchizophreniaYoung AdultClinical heterogeneityDiffusion-weighted imagingEarly psychosisNegative symptomsPartial least squaresPLSPsychopathologyWhite matter microstructure

Identifiers

PMID38908657
PMCPMC13251713

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.