Evidence map›Paper›PMID 28166811›Full record

ArticleGenome medicine2017

Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation.

Yuya Kobayashi, Shan Yang, Keith Nykamp, John Garcia, Stephen E Lincoln, Scott E Topper

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
105citing papers in PubMed, 1 pooled it
23.6field-weighted citation impact, top 1% 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

105 citing papers in PubMed, 1 synthesis or guideline pooled it, 239 citations in OpenAlex.

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45 more citing papers are in PubMed but not listed here.

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

6 authors at 1 institution in 1 country.

Yuya KobayashiInvitae Corporation, 1400 16th St., San Francisco, CA, 94103, USA. yuya.kobayashi@invitae.com.ORCID 0000-0002-8202-2101
Shan YangInvitae Corporation, 1400 16th St., San Francisco, CA, 94103, USA.
Keith NykampInvitae Corporation, 1400 16th St., San Francisco, CA, 94103, USA.
John GarciaInvitae Corporation, 1400 16th St., San Francisco, CA, 94103, USA.
Stephen E LincolnInvitae Corporation, 1400 16th St., San Francisco, CA, 94103, USA.
Scott E TopperInvitae Corporation, 1400 16th St., San Francisco, CA, 94103, USA.
Invitae (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe frequency of a variant in the general population is a key criterion used in the clinical interpretation of sequence variants. With certain exceptions, such as founder mutations, the rarity of a variant is a prerequisite for pathogenicity. However, defining the threshold at which a variant should be considered "too common" is challenging and therefore diagnostic laboratories have typically set conservative allele frequency thresholds.

methodsRecent publications of large population sequencing data, such as the Exome Aggregation Consortium (ExAC) database, provide an opportunity to characterize with accuracy and precision the frequency distributions of very rare disease-causing alleles. Allele frequencies of pathogenic variants in ClinVar, as well as variants expected to be pathogenic through the nonsense-mediated decay (NMD) pathway, were analyzed to study the burden of pathogenic variants in 79 genes of clinical importance.

resultsOf 1364 BRCA1 and BRCA2 variants that are well characterized as pathogenic or that are expected to lead to NMD, 1350 variants had an allele frequency of less than 0.0025%. The remaining 14 variants were previously published founder mutations. Importantly, we observed no difference in the distributions of pathogenic variants expected to be lead to NMD compared to those that are not. Therefore, we expanded the analysis to examine the distributions of NMD expected variants in 77 additional genes. These 77 genes were selected to represent a broad set of clinical areas, modes of inheritance, and penetrance. Among these variants, most (97.3%) had an allele frequency of less than 0.01%. Furthermore, pathogenic variants with allele frequencies greater than 0.01% were well characterized in publications and included many founder mutations.

conclusionsThe observations made in this study suggest that, with certain caveats, a very low allele frequency threshold can be adopted to more accurately interpret sequence variants.

Indexed as

Databases, GeneticGene FrequencyGenetic VariationMutationDNA Mutational AnalysisExomeHumansRare DiseasesACMG ISV guidelinesAllele-frequency thresholdExACVariant interpretation

Identifiers

PMID28166811
PMCPMC5295186
OpenAlexW2587204086

What OpenQuestion holds

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LicenceCC BY
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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.