Evidence map›Paper›PMID 34216550›Full record

ArticleAmerican journal of human genetics2021

Nonsense-mediated decay is highly stable across individuals and tissues.

Nicole A Teran, Daniel C Nachun, Tiffany Eulalio, Nicole M Ferraro, Craig Smail, Manuel A Rivas, Stephen B Montgomery

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

30 citing papers in PubMed, 42 citations in OpenAlex.

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  18. RNA Sequencing in Disease Diagnosis.Annual review of genomics and human genetics · 2024
    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

7 authors at 3 institutions in 1 country.

Nicole A TeranDepartment of Pathology, School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA.
Daniel C NachunDepartment of Pathology, School of Medicine, Stanford University, Stanford, CA 94305, USA.
Tiffany EulalioDepartment of Pathology, School of Medicine, Stanford University, Stanford, CA 94305, USA; Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA.
Nicole M FerraroDepartment of Pathology, School of Medicine, Stanford University, Stanford, CA 94305, USA; Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA.
Craig SmailDepartment of Pathology, School of Medicine, Stanford University, Stanford, CA 94305, USA; Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA; Genomic Medicine Center, Children's Mercy Research Institute and Children's Mercy Kansas City, Kansas City, MO 64108, USA.
Manuel A RivasDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
Stephen B MontgomeryDepartment of Pathology, School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA. Electronic address: smontgom@stanford.edu.
Stanford University · USMercy Research · USStanford Medicine · US

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Stanford/Salk MoTrPAC Site for Genomes, Epigenomes and TranscriptomesU24DK112348 · NIDDK · STANFORD UNIVERSITY · PI Stephen Montgomery, MICHAEL P. SNYDER · 2017 to 2026
$18.4M
Optimizing imputation for diverse populations in a distributed frameworkU01HG009080 · NHGRI · STANFORD UNIVERSITY · PI KENNY, EIMEAR ELIZABETH · 2016 to 2020
$5.2M
Stanford Training Program in Aging ResearchT32AG047126 · NIA · STANFORD UNIVERSITY · PI VYJEYANTHI S PERIYAKOIL, TONY WYSS-CORAY · 2014 to 2026
$4.3M
Mapping Molecular and Phenotypic Interactions in Alzheimers DiseaseR01AG066490 · NIA · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2020 to 2024
$3.6M
Decoding the regulatory architecture of the human genome across cell types, individuals and diseaseU01HG009431 · NHGRI · STANFORD UNIVERSITY · PI PRITCHARD, JONATHAN K · 2017 to 2021
$3.5M
Identifying causal genetic variants and molecular mechanisms impacting mental healthR01MH125244 · NIMH · STANFORD UNIVERSITY · PI KUNDAJE, ANSHUL, MONTGOMERY, STEPHEN · 2021 to 2025
$3.0M
Molecular Mechanisms of Insulin Resistance Associated LociR01DK107437 · NIDDK · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2016 to 2019
$2.2M
SOFTWARE FOR LARGE-SCALE INFERENCE OF THE GENETICS OF LIFESTYLE MEASURES, BIOMARKERS, AND COMMON AND RARE DISEASESR01HG010140 · NHGRI · STANFORD UNIVERSITY · PI KUNDAJE, ANSHUL, MONTGOMERY, STEPHEN · 2018 to 2022
$2.0M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
Predicting causal non-coding variants in a founder populationR01HG008150 · NHGRI · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2015 to 2017
$1.4M
Integrative multi-omics in whole genome studies of HLBS disordersR01HL142015 · NHLBI · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2018 to 2019
$882k
NHGRI NIH HHS R01 HG008150NHGRI NIH HHS R01 HG010140NHGRI NIH HHS U01 HG009080NHGRI NIH HHS U01 HG009431NHLBI NIH HHS R01 HL142015NIA NIH HHS R01 AG066490NIA NIH HHS T32 AG047126NIDDK NIH HHS R01 DK107437NIDDK NIH HHS U24 DK112348NIH HHS S10 OD023452NIMH NIH HHS R01 MH125244NLM NIH HHS T15 LM007033NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

Precise interpretation of the effects of rare protein-truncating variants (PTVs) is important for accurate determination of variant impact. Current methods for assessing the ability of PTVs to induce nonsense-mediated decay (NMD) focus primarily on the position of the variant in the transcript. We used RNA sequencing of the Genotype Tissue Expression v.8 cohort to compute the efficiency of NMD using allelic imbalance for 2,320 rare (genome aggregation database minor allele frequency ≤ 1%) PTVs across 809 individuals in 49 tissues. We created an interpretable predictive model using penalized logistic regression in order to evaluate the comprehensive influence of variant annotation, tissue, and inter-individual variation on NMD. We found that variant position, allele frequency, the inclusion of ultra-rare and singleton variants, and conservation were predictive of allelic imbalance. Furthermore, we found that NMD effects were highly concordant across tissues and individuals. Due to this high consistency, we demonstrate in silico that utilizing peripheral tissues or cell lines provides accurate prediction of NMD for PTVs.

Indexed as

Gene Expression RegulationGenetic VariationMutationNonsense Mediated mRNA DecayCodon, NonsenseGene FrequencyGenetic Diseases, InbornHumansRNA, MessengerCodon, NonsenseRNA, Messengernonsense-mediated decayrare variantsvariant annotation

Identifiers

PMID34216550
PMCPMC8387471
OpenAlexW3177303035

What OpenQuestion holds

Textmetadata
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.