Evidence map›Paper›PMID 37577579›Full record

ArticleResearch square2023

CAGI6 ID-Challenge: Assessment of phenotype and variant predictions in 415 children with Neurodevelopmental Disorders (NDDs).

Maria Cristina Aspromonte, Alessio Del Conte, Shaowen Zhu, Wuwei Tan, Yang Shen, Yexian Zhang, Qi Li, Maggie Haitian Wang, Giulia Babbi, Samuele Bovo and 19 more

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

29 authors at 10 institutions in 6 countries.

Maria Cristina AspromonteDepartment of Biomedical Sciences, University of Padova.
Alessio Del ConteDepartment of Biomedical Sciences, University of Padova.
Shaowen ZhuDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843.
Wuwei TanDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843.
Yang ShenDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843.
Yexian ZhangCUHK Shenzhen Research Institute, Shenzhen.
Qi LiCUHK Shenzhen Research Institute, Shenzhen.
Maggie Haitian WangCUHK Shenzhen Research Institute, Shenzhen.
Giulia BabbiBiocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna.
Samuele BovoDepartment of Agricultural and Food Sciences, University of Bologna.
Pier Luigi MartelliBiocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna.
Rita CasadioBiocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna.
Azza AlthagafiComputational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
Sumyyah ToonsiComputational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
Maxat KulmanovComputational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
Robert HoehndorfComputational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
Panagiotis KatsonisDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030.
Amanda WilliamsDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030.
Olivier LichtargeDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030.
Su XianDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195.
Wesley SurentoDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195.
Vikas PejaverInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029.
Sean D MooneyDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195.
Uma SunderamInnovation Labs, Tata Consultancy Services, Hyderabad.
Rajgopal SrinivasanInnovation Labs, Tata Consultancy Services, Hyderabad.
Alessandra MurgiaDepartment of Women's and Children's Health, University of Padova.
Damiano PiovesanDepartment of Biomedical Sciences, University of Padova.
Silvio C E TosattoDepartment of Biomedical Sciences, University of Padova.
Emanuela LeonardiDepartment of Biomedical Sciences, University of Padova.
University of Padua · ITKing Abdullah University of Science and Technology · SABaylor College of Medicine · USBiocom · USCity University of Hong Kong, Shenzhen Research Institute · CNTexas A&M University · USUniversity of Washington Medical Center · USTata Consultancy Services (India) · INGenomic Health (United States) · USUniversity of Bologna · IT

Funding

Center for Critical Assessment of Genome InterpretationU24HG007346 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E, IOANNIDIS, NILAH MONNIER · 2020 to 2025
$3.8M
Unraveling molecular and system-level mechanisms of human disease-associated protein mutationsR35GM124952 · NIGMS · TEXAS ENGINEERING EXPERIMENT STATION · PI Yang Shen · 2017 to 2026
$2.9M
Integrative data science approaches for rare disease discovery in health recordsR00LM012992 · NLM · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI PEJAVER, VIKAS RAO · 2022 to 2024
$709k
NHGRI NIH HHS U24 HG007346NIGMS NIH HHS R35 GM124952NLM NIH HHS R00 LM012992
6 · The paper itself

Abstract

In the context of the Critical Assessment of the Genome Interpretation, 6th edition (CAGI6), the Genetics of Neurodevelopmental Disorders Lab in Padua proposed a new ID-challenge to give the opportunity of developing computational methods for predicting patient's phenotype and the causal variants. Eight research teams and 30 models had access to the phenotype details and real genetic data, based on the sequences of 74 genes (VCF format) in 415 pediatric patients affected by Neurodevelopmental Disorders (NDDs). NDDs are clinically and genetically heterogeneous conditions, with onset in infant age. In this study we evaluate the ability and accuracy of computational methods to predict comorbid phenotypes based on clinical features described in each patient and causal variants. Finally, we asked to develop a method to find new possible genetic causes for patients without a genetic diagnosis. As already done for the CAGI5, seven clinical features (ID, ASD, ataxia, epilepsy, microcephaly, macrocephaly, hypotonia), and variants (causative, putative pathogenic and contributing factors) were provided. Considering the overall clinical manifestation of our cohort, we give out the variant data and phenotypic traits of the 150 patients from CAGI5 ID-Challenge as training and validation for the prediction methods development.

Indexed as

CAGIgene-panelNeurodevelopmental Disordersphenotype predictionvariants interpretation

Identifiers

PMID37577579
PMCPMC10418555
OpenAlexW4385483169

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.