Evidence map›Paper›PMID 38918700›Full record

ArticleJournal of neurodevelopmental disorders2024

Computer-vision analysis of craniofacial dysmorphology in 22q11.2 deletion syndrome and psychosis spectrum disorders.

David R Roalf, Donna M McDonald-McGinn, Joelle Jee, Mckenna Krall, T Blaine Crowley, Paul J Moberg, Christian Kohler, Monica E Calkins, Andrew J D Crow, Nicole Fleischer and 13 more

Abstract read
In one paragraph

Article in Journal of neurodevelopmental disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

23 authors.

David R RoalfBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA. roalf@pennmedicine.upenn.edu.ORCID 0000-0002-1728-9782
Donna M McDonald-McGinn22q and You Center at the Children's Hospital of Philadelphia, Philadelphia, USA.
Joelle JeeBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Mckenna KrallBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
T Blaine Crowley22q and You Center at the Children's Hospital of Philadelphia, Philadelphia, USA.
Paul J MobergBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Christian KohlerBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Monica E CalkinsBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Andrew J D CrowBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Nicole FleischerFDNA, Boston, MA, USA.
R Sean GallagherBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Virgilio GonzenbachPenn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Kelly ClarkPenn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Ruben C GurBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Emily McClellanBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Daniel E McGinn22q and You Center at the Children's Hospital of Philadelphia, Philadelphia, USA.
Arianna MordyBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Kosha RuparelBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Bruce I TuretskyBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Russell T ShinoharaPenn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Lauren WhiteBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Elaine Zackai22q and You Center at the Children's Hospital of Philadelphia, Philadelphia, USA.
Raquel E GurBrain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Funding

Ultra-high field GluCEST MRI and MRS in youth at risk for psychosisR01MH120174 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI ROALF, DAVID R · 2020 to 2024
$3.8M
Evolution of Psychosis in Youth: Multimodal Risk and Resilience MarkersR01MH119219 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RAQUEL E, GUR, RUBEN C. · 2019 to 2023
$3.8M
Olfactory and facial markers of developmental risk for psychosis in 22q11 deletion syndromeR01MH119185 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI ROALF, DAVID R · 2019 to 2024
$3.5M
1/9: Dissecting the effects of genomic variants on nenriched for neuropsychiatric disorderseurobehavioral dimensions in CNVs U01MH119738 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RAQUEL E · 2019 to 2023
$3.2M
Creating an adaptive screening tool for detecting neurocognitive deficits and psychopathology across the lifespanR01MH117014 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RUBEN C. · 2019 to 2022
$2.9M
NIMH NIH HHS MH117014NIMH NIH HHS MH119185NIMH NIH HHS MH119738NIMH NIH HHS MH120174NIMH NIH HHS R01 MH117014NIMH NIH HHS R01 MH119185NIMH NIH HHS R01 MH119219NIMH NIH HHS R01 MH120174NIMH NIH HHS U01 MH119738
6 · The paper itself

Abstract

backgroundMinor physical anomalies (MPAs) are congenital morphological abnormalities linked to disruptions of fetal development. MPAs are common in 22q11.2 deletion syndrome (22q11DS) and psychosis spectrum disorders (PS) and likely represent a disruption of early embryologic development that may help identify overlapping mechanisms linked to psychosis in these disorders.

methodsHere, 2D digital photographs were collected from 22q11DS (n = 150), PS (n = 55), and typically developing (TD; n = 93) individuals. Photographs were analyzed using two computer-vision techniques: (1) DeepGestalt algorithm (Face2Gene (F2G)) technology to identify the presence of genetically mediated facial disorders, and (2) Emotrics-a semi-automated machine learning technique that localizes and measures facial features.

resultsF2G reliably identified patients with 22q11DS; faces of PS patients were matched to several genetic conditions including FragileX and 22q11DS. PCA-derived factor loadings of all F2G scores indicated unique and overlapping facial patterns that were related to both 22q11DS and PS. Regional facial measurements of the eyes and nose were smaller in 22q11DS as compared to TD, while PS showed intermediate measurements.

conclusionsThe extent to which craniofacial dysmorphology 22q11DS and PS overlapping and evident before the impairment or distress of sub-psychotic symptoms may allow us to identify at-risk youths more reliably and at an earlier stage of development.

Indexed as

Craniofacial AbnormalitiesDiGeorge SyndromePsychotic DisordersAdolescentAdultChildFemaleHumansImage Processing, Computer-AssistedMachine LearningMaleYoung Adult22q11.2 deletion syndromeClinical high-risk psychosisComputer-visionFaceMinor physical anomaliesPsychosisSchizophrenia

Identifiers

PMID38918700
PMCPMC11201300

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