ArticlebioRxiv : the preprint server for biology2024
Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns.
Xuesong Wang, Kanhao Zhao, Lina Yao, Gregory A Fonzo, Theodore D Satterthwaite, Islem Rekik, Yu Zhang
Abstract readPreprint
In one paragraphArticle in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
7 authors.
Xuesong WangData 61, Commonwealth Scientific and Industrial Research Organisation, New South Wales, Australia.
Kanhao ZhaoDepartment of Bioengineering, Lehigh University, Bethlehem, PA, USA.
Lina YaoData 61, Commonwealth Scientific and Industrial Research Organisation, New South Wales, Australia.
Gregory A FonzoCenter for Psychedelic Research and Therapy, Department of Psychiatry and Behavioral Sciences, Dell Medical School, The University of Texas at Austin, Austin, TX, USA.
Theodore D SatterthwaiteDepartment of Psychiatry, University of Pennsylvania Perelman School of Medicine, PA, USA.ORCID 0000-0001-7072-9399 Islem RekikBASIRA Lab, Imperial-X and Department of Computing, Imperial College London, London, UK.
Yu ZhangDepartment of Bioengineering, Lehigh University, Bethlehem, PA, USA.
Funding
Personalized Functional Network Modeling to Characterize and Predict Psychopathology in YouthR01EB022573 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Yong Fan, Theodore Satterthwaite · 2016 to 2026
$6.0MInter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9MPrecision mapping of individualized executive networks in youthR37MH125829 · NIMH · UNIVERSITY OF MINNESOTA · PI Damien A Fair, Theodore Satterthwaite · 2021 to 2026
$4.7M1/2 Neurodevelopmental and clinical trajectories of youth at risk for bipolar I disorderR01MH125886 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI ALMEIDA, JORGE R C, STRAKOWSKI, STEPHEN M · 2021 to 2025
$4.3MReproducible imaging-based brain growth charts for psychiatryR01MH120482 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI MILHAM, MICHAEL PETER, SATTERTHWAITE, THEODORE · 2019 to 2023
$3.5MEstablishing Multimodal Brain Biomarkers Using Data-driven Analyticsfor Treatment Selection in DepressionR01MH129694 · NIMH · STANFORD UNIVERSITY · PI Yu Zhang · 2023 to 2026
$2.8MThe effects of trauma-focused psychotherapy on reward circuitry function and information encodingR01MH132784 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI Gregory Fonzo · 2024 to 2026
$2.3MAssess Neural Circuits and Subtypes Underlying Dimensions of Neuropsychiatric Symptoms in Alzheimer's DiseaseR21AG080425 · NIA · LEHIGH UNIVERSITY · PI ZHANG, YU · 2023 to 2024
$426kIdentifying Transdiagnostic Functional Connectivity Biomarkers for Cognitive Health and PsychopathologyR21MH130956 · NIMH · LEHIGH UNIVERSITY · PI BERDICHEVSKY, YEVGENY · 2023 to 2024
$409kNIA NIH HHS R21 AG080425NIBIB NIH HHS R01 EB022573NIMH NIH HHS R01 MH112847NIMH NIH HHS R01 MH120482NIMH NIH HHS R01 MH125886NIMH NIH HHS R01 MH129694NIMH NIH HHS R01 MH132784NIMH NIH HHS R21 MH130956NIMH NIH HHS R37 MH125829
6 · The paper itselfAbstract
Neurodevelopmental disorders, such as Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), are characterized by comorbidity and heterogeneity. Identifying distinct subtypes within these disorders can illuminate the underlying neurobiological and clinical characteristics, paving the way for more tailored treatments. We adopted a novel transdiagnostic approach across ADHD and ASD, using cutting-edge contrastive graph machine learning to determine subtypes based on brain network connectivity as revealed by resting-state functional magnetic resonance imaging. Our approach identified two generalizable subtypes characterized by robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the somatomotor network. These subtypes exhibited pronounced differences in major cognitive and behavioural measures. We further demonstrated the generalizability of these subtypes using data collected from independent study sites. Our data-driven approach provides a novel solution for parsing biological heterogeneity in neurodevelopmental disorders.
Identifiers
PMID38496573
PMCPMC10942316
What OpenQuestion holds
Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390