Evidence map›Paper›PMID 25502226›Full record

ArticlePLoS genetics2014

Identification of rare causal variants in sequence-based studies: methods and applications to VPS13B, a gene involved in Cohen syndrome and autism.

Iuliana Ionita-Laza, Marinela Capanu, Silvia De Rubeis, Kenneth McCallum, Joseph D Buxbaum

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 5% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Impact of genetic test interpretation on aFrontiers in neuroscience · 2024
    Article
  4. Machine learning in rare disease.Nature methods · 2023
    Review
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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

5 authors at 4 institutions in 1 country.

Iuliana Ionita-LazaDepartment of Biostatistics, Columbia University, New York, New York, United States of America.
Marinela CapanuMemorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Silvia De RubeisSeaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America; Departments of Psychiatry, Mount Sinai School of Medicine, New York, New York, United States of America.
Kenneth McCallumDepartment of Biostatistics, Columbia University, New York, New York, United States of America.
Joseph D BuxbaumSeaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America; Departments of Psychiatry, Mount Sinai School of Medicine, New York, New York, United States of America; Departments of Genetics and Genomic Sciences, and Neuroscience, and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America; Mindich Child Health and Development Institute, Mount Sinai School of Medicine, New York, New York, United States of America.
Columbia University · USChild Health and Development Institute · USIcahn School of Medicine at Mount Sinai · USMemorial Sloan Kettering Cancer Center · US

Funding

Novel Statistical methods for DNA Sequencing Data, and applications to Autism.R01MH095797 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI IONITA, IULIANA · 2012 to 2022
$3.1M
1/4-The Autism Sequencing Consortium: Autism gene discovery in >20,000 exomesU01MH100233 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BUXBAUM, JOSEPH D. · 2013 to 2015
$2.5M
NIMH NIH HHS MH100233NIMH NIH HHS R01 MH095797NIMH NIH HHS R01MH095797NIMH NIH HHS U01 MH100233
6 · The paper itself

Abstract

Pinpointing the small number of causal variants among the abundant naturally occurring genetic variation is a difficult challenge, but a crucial one for understanding precise molecular mechanisms of disease and follow-up functional studies. We propose and investigate two complementary statistical approaches for identification of rare causal variants in sequencing studies: a backward elimination procedure based on groupwise association tests, and a hierarchical approach that can integrate sequencing data with diverse functional and evolutionary conservation annotations for individual variants. Using simulations, we show that incorporation of multiple bioinformatic predictors of deleteriousness, such as PolyPhen-2, SIFT and GERP++ scores, can improve the power to discover truly causal variants. As proof of principle, we apply the proposed methods to VPS13B, a gene mutated in the rare neurodevelopmental disorder called Cohen syndrome, and recently reported with recessive variants in autism. We identify a small set of promising candidates for causal variants, including two loss-of-function variants and a rare, homozygous probably-damaging variant that could contribute to autism risk.

Indexed as

Evolution, MolecularGenetic VariationAngiopoietin-Like Protein 4AngiopoietinsAutistic DisorderComputational BiologyComputer SimulationDevelopmental DisabilitiesFingersGene FrequencyGenome-Wide Association StudyHumansIntellectual DisabilityMicrocephalyModels, GeneticMuscle HypotoniaAngiopoietin-Like Protein 4AngiopoietinsANGPTL4 protein, humanVesicular Transport ProteinsVPS13B protein, human

Identifiers

PMID25502226
PMCPMC4263785
OpenAlexW1980746559

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.