Evidence map›Paper›PMID 33724192›Full record

ArticleJournal of medical Internet research2021

Underrepresentation of Phenotypic Variability of 16p13.11 Microduplication Syndrome Assessed With an Online Self-Phenotyping Tool (Phenotypr): Cohort Study.

Jianqiao Li, Margaret A Hojlo, Sampath Chennuri, Nitin Gujral, Heather L Paterson, Kent A Shefchek, Casie A Genetti, Emily L Cohn, Kara C Sewalk, Emily A Garvey and 9 more

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. 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
0.6field-weighted citation impact, top 38% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

19 authors at 2 institutions in 1 country.

Jianqiao Li *Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-6145-424X
Margaret A Hojlo *Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-3757-9776
Sampath ChennuriInnovation and Digital Health Accelerator, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-9141-4468
Nitin GujralInnovation and Digital Health Accelerator, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-7189-7853
Heather L PatersonDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0002-0812-7992
Kent A ShefchekDepartment of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, United States.ORCID 0000-0001-6439-2224
Casie A GenettiDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-4173-9947
Emily L CohnInnovation and Digital Health Accelerator, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-6415-519X
Kara C SewalkComputational Epidemiology Group, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0002-2917-0869
Emily A GarveyDepartment of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-2497-4232
Elizabeth D ButtermoreHuman Neuron Core, Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-3194-5413
Nickesha C AndersonDepartment of Neurology, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-4168-0703
Alan H BeggsDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-8818-0568
Pankaj B AgrawalDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-3255-0456
John S BrownsteinInnovation and Digital Health Accelerator, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0001-8568-5317
Melissa A HaendelCenter for Health Artificial Intelligence, University of Colorado Anschutz, Aurora, CO, United States.ORCID 0000-0001-9114-8737
Ingrid A HolmDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0003-4712-8821
Joseph Gonzalez-Heydrich *The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0002-3073-983X
Catherine A Brownstein *Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, United States.ORCID 0000-0002-7371-0340
Boston Children's Hospital · USOregon State University · US

Funding

Mouse Neurodevelopmental Behavior CoreU54HD090255 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI POMEROY, SCOTT LOREN · 2016 to 2020
$5.2M
NICHD NIH HHS U54 HD090255
6 · The paper itself

Abstract

background16p13.11 microduplication syndrome has a variable presentation and is characterized primarily by neurodevelopmental and physical phenotypes resulting from copy number variation at chromosome 16p13.11. Given its variability, there may be features that have not yet been reported. The goal of this study was to use a patient "self-phenotyping" survey to collect data directly from patients to further characterize the phenotypes of 16p13.11 microduplication syndrome.

objectiveThis study aimed to (1) discover self-identified phenotypes in 16p13.11 microduplication syndrome that have been underrepresented in the scientific literature and (2) demonstrate that self-phenotyping tools are valuable sources of data for the medical and scientific communities.

methodsAs part of a large study to compare and evaluate patient self-phenotyping surveys, an online survey tool, Phenotypr, was developed for patients with rare disorders to self-report phenotypes. Participants with 16p13.11 microduplication syndrome were recruited through the Boston Children's Hospital 16p13.11 Registry. Either the caregiver, parent, or legal guardian of an affected child or the affected person (if aged 18 years or above) completed the survey. Results were securely transferred to a Research Electronic Data Capture database and aggregated for analysis.

resultsA total of 19 participants enrolled in the study. Notably, among the 19 participants, aggression and anxiety were mentioned by 3 (16%) and 4 (21%) participants, respectively, which is an increase over the numbers in previously published literature. Additionally, among the 19 participants, 3 (16%) had asthma and 2 (11%) had other immunological disorders, both of which have not been previously described in the syndrome.

conclusionsSeveral phenotypes might be underrepresented in the previous 16p13.11 microduplication literature, and new possible phenotypes have been identified. Whenever possible, patients should continue to be referenced as a source of complete phenotyping data on their condition. Self-phenotyping may lead to a better understanding of the prevalence of phenotypes in genetic disorders and may identify previously unreported phenotypes.

Indexed as

DNA Copy Number VariationsFamilyBiological Variation, PopulationCohort StudiesHumansPhenotype16p13.11 microduplication syndromecopy number variationdigital healthgeneticshuman phenotype ontologyincomplete penetranceonline surveyphenotypeself-phenotypingvariable presentation

Identifiers

PMID33724192
PMCPMC8074853
OpenAlexW3136843123

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.