Evidence map›Paper›PMID 28761808›Full record

ArticleNeuroImage. Clinical2017

Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study.

Daniel S Tylee, Zora Kikinis, Thomas P Quinn, Kevin M Antshel, Wanda Fremont, Muhammad A Tahir, Anni Zhu, Xue Gong, Stephen J Glatt, Ioana L Coman and 3 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

13 citing papers in PubMed, 26 citations in OpenAlex.

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  4. A cross-comparison of cognitive ability across 8 genomic disorders.Current opinion in genetics & development · 2021
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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

13 authors at 5 institutions in 2 countries.

Daniel S TyleeDepartment of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.
Zora KikinisDepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: zora@bwh.harvard.edu.
Thomas P QuinnBioinformatics Core Research Group, Deakin University, Geelong, Victoria, Australia.
Kevin M AntshelSyracuse University, Syracuse, NY, USA. Electronic address: kmantshe@syr.edu.
Wanda FremontDepartment of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: fremontw@upstate.edu.
Muhammad A TahirDepartment of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.
Anni ZhuDepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Xue GongDepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Stephen J GlattDepartment of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: stephen.glatt@psychgenelab.com.
Ioana L ComanDepartment of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: comani@upstate.edu.
Martha E ShentonDepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Harvard Medical School, Brockton, MA, USA. Electronic address: shenton@bwh.harvard.edu.
Wendy R KatesDepartment of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: katesw@upstate.edu.
Nikos MakrisDepartment of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: nikos@nmr.mgh.harvard.edu.
SUNY Upstate Medical University · USBrigham and Women's Hospital · USDeakin University · AUHarvard University · USSyracuse University · US

Funding

Biomarkers for Psychosis in Velocardiofacial SyndromeR01MH064824 · NIMH · UPSTATE MEDICAL UNIVERSITY · PI KATES, WENDY · 2002 to 2015
$7.3M
Neural substrates of diffusion imaging in cognitively aging rhesus monkeysR01AG042512 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI KUBICKI, MAREK, MAKRIS, NIKOLAOS · 2013 to 2023
$6.5M
Effects of Curcumin on Frontal Circuitry in Aging Monkeys using MRI ConnectomeR21AT008865 · NCCIH · MASSACHUSETTS GENERAL HOSPITAL · PI KUBICKI, MAREK, MAKRIS, NIKOLAOS · 2016 to 2017
$484k
Structural Connectivity Biomarkers in Prodromes and 22q11.2 Deletion Syndrome.R21MH106793 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI KIKINIS, ZORA · 2016 to 2017
$481k
NCCIH NIH HHS R21 AT008865NIA NIH HHS R01 AG042512NIMH NIH HHS R01 MH064824NIMH NIH HHS R21 MH106793
6 · The paper itself

Abstract

Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic neurodevelopmental syndrome that has been studied intensively in order to understand relationships between the genetic microdeletion, brain development, cognitive function, and the emergence of psychiatric symptoms. White matter microstructural abnormalities identified using diffusion tensor imaging methods have been reported to affect a variety of neuroanatomical tracts in 22q11.2DS. In the present study, we sought to combine two discovery-based approaches: (1) white matter query language was used to parcellate the brain's white matter into tracts connecting pairs of 34, bilateral cortical regions and (2) the diffusion imaging characteristics of the resulting tracts were analyzed using a machine-learning method called support vector machine in order to optimize the selection of a set of imaging features that maximally discriminated 22q11.2DS and comparison subjects. With this unique approach, we both confirmed previously-recognized 22q11.2DS-related abnormalities in the inferior longitudinal fasciculus (ILF), and identified, for the first time, 22q11.2DS-related anomalies in the middle longitudinal fascicle and the extreme capsule, which may have been overlooked in previous, hypothesis-guided studies. We further observed that, in participants with 22q11.2DS, ILF metrics were significantly associated with positive prodromal symptoms of psychosis.

Indexed as

AdultDiffusion Tensor ImagingDiGeorge SyndromeFemaleHumansMachine LearningMaleNerve Fibers, MyelinatedNerve NetNeuropsychological TestsWhite MatterYoung Adult22q11.2 deletion syndrome(22q11.2DS), 22q11.2 deletion syndrome(AD), axial diffusivityCallosal asymmetryDiffusion tensor imaging(DTI), diffusion tensor imaging(dTP), dorsal temporal pole(DWI), diffusion weighted image(EmC), extreme capsuleExtreme capsule(FA), fractional anisotropy(FOV), field of view(-fp), fronto-parietal aspect(GDS), Gordon Diagnostic Systems(ILF), inferior longitudinal fasciculusInferior longitudinal fasciculusMachine-learning(MdLF), middle longitudinal fascicleMiddle longitudinal fascicle(RD), radial diffusivity(ROI), region of interest(SIPS), Structured Interview for Prodromal Syndromes(SRS), Social Responsiveness Scale(STG), superior temporal gyrusSupport vector machine(SVM), support vector machine(-to), temporo-occipital aspect(-tp), temporo-parietal aspect(UKF), Unscented Kalman FilterVelocardiofacial syndrome(WAIS-III), Wechsler Adult Intelligence Scale – 3rd editionWhite matter query language(WMQL), white matter query language

Identifiers

PMID28761808
PMCPMC5522376
OpenAlexW2612794192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.