Evidence map›Paper›PMID 26185613›Full record

ArticleMolecular autism2015

Targeted massively parallel sequencing of autism spectrum disorder-associated genes in a case control cohort reveals rare loss-of-function risk variants.

Anthony J Griswold, Nicole D Dueker, Derek Van Booven, Joseph A Rantus, James M Jaworski, Susan H Slifer, Michael A Schmidt, William Hulme, Ioanna Konidari, Patrice L Whitehead and 6 more

Open access · goldAbstract read
In one paragraph

Article in Molecular autism, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

36 citing papers in PubMed, 68 citations in OpenAlex.

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  10. Pleiotropic contribution ofbioRxiv : the preprint server for biology · 2023
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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

16 authors at 3 institutions in 1 country.

Anthony J GriswoldJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Nicole D DuekerJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Derek Van BoovenJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Joseph A RantusJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
James M JaworskiJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Susan H SliferJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Michael A SchmidtJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
William HulmeJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Ioanna KonidariJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Patrice L WhiteheadJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Michael L CuccaroJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA ; Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Eden R MartinJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA ; Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
Jonathan L HainesDepartment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106 USA.
John R GilbertJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA ; Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
John P HussmanHussman Institute for Autism, Baltimore, MD 21201 USA.
Margaret A Pericak-VanceJohn P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA ; Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL 33136 USA.
University of Miami · USCase Western Reserve University · USHussman Institute for Autism · US

Funding

USE OF DNA PROBE FOR CHOLINERGIC AND NON-CHOLINERGIC MG ANTIGENP01NS026630 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI PERICAK-VANCE, MARGARET A. · 1989 to 2009
$12.6M
Center for Genomic and Phenomic Studies in AutismU24MH081810 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LAJONCHERE, CLARA M · 2007 to 2011
$8.3M
Molecular and Genetic Epidemiology of AutismR01MH080647 · NIMH · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI PERICAK-VANCE, MARGARET A. · 2007 to 2011
$5.9M
NIMH NIH HHS R01 MH080647NIMH NIH HHS U24 MH081810NINDS NIH HHS P01 NS026630
6 · The paper itself

Abstract

backgroundAutism spectrum disorder (ASD) is highly heritable, yet genome-wide association studies (GWAS), copy number variation screens, and candidate gene association studies have found no single factor accounting for a large percentage of genetic risk. ASD trio exome sequencing studies have revealed genes with recurrent de novo loss-of-function variants as strong risk factors, but there are relatively few recurrently affected genes while as many as 1000 genes are predicted to play a role. As such, it is critical to identify the remaining rare and low-frequency variants contributing to ASD.

methodsWe have utilized an approach of prioritization of genes by GWAS and follow-up with massively parallel sequencing in a case-control cohort. Using a previously reported ASD noise reduction GWAS analyses, we prioritized 837 RefSeq genes for custom targeting and sequencing. We sequenced the coding regions of those genes in 2071 ASD cases and 904 controls of European white ancestry. We applied comprehensive annotation to identify single variants which could confer ASD risk and also gene-based association analysis to identify sets of rare variants associated with ASD.

resultsWe identified a significant over-representation of rare loss-of-function variants in genes previously associated with ASD, including a de novo premature stop variant in the well-established ASD candidate gene RBFOX1. Furthermore, ASD cases were more likely to have two damaging missense variants in candidate genes than controls. Finally, gene-based rare variant association implicates genes functioning in excitatory neurotransmission and neurite outgrowth and guidance pathways including CACNAD2, KCNH7, and NRXN1.

conclusionsWe find suggestive evidence that rare variants in synaptic genes are associated with ASD and that loss-of-function mutations in ASD candidate genes are a major risk factor, and we implicate damaging mutations in glutamate signaling receptors and neuronal adhesion and guidance molecules. Furthermore, the role of de novo mutations in ASD remains to be fully investigated as we identified the first reported protein-truncating variant in RBFOX1 in ASD. Overall, this work, combined with others in the field, suggests a convergence of genes and molecular pathways underlying ASD etiology.

Identifiers

PMID26185613
PMCPMC4504419
OpenAlexW2104493560

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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.