Evidence map›Paper›PMID 30516811›Full record

ArticleJAMA dermatology2019

Use of Big Data to Estimate Prevalence of Defective DNA Repair Variants in the US Population.

Jennifer Pugh, Sikandar G Khan, Deborah Tamura, Alisa M Goldstein, Maria Teresa Landi, John J DiGiovanna, Kenneth H Kraemer

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in JAMA dermatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.4field-weighted citation impact, top 38% 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

13 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
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  7. Deep intronic founder mutations identified in theProceedings of the National Academy of Sciences of the United States of America · 2023
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  12. Human XPG nuclease structure, assembly, and activities with insights for neurodegeneration and cancer from pathogenic mutations.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  13. Review
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.

Jennifer PughLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Sikandar G KhanLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Deborah TamuraLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Alisa M GoldsteinHuman Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland.
Maria Teresa LandiHuman Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland.
John J DiGiovannaLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Kenneth H KraemerLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
National Cancer Institute · USDivision of Cancer Epidemiology and GeneticsOffice of the Director · US

Funding

Family Studies ZIACP004410 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI SAVAGE, SHARON A. · 2009 to 2025
$56.1M
DNA Repair in Human Cancer-Prone Genetic DiseasesZIABC004517 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI KRAEMER, KENNETH H · 2009 to 2024
$26.5M
6 · The paper itself

Abstract

Importance: Wide use of genomic sequencing to diagnose disease has raised concern about the extent of genotype-phenotype correlations. Objective: To correlate disease-associated allele frequencies with expected and reported prevalence of clinical disease. Design, Setting, and Participants: Xeroderma pigmentosum (XP), a recessive, cancer-prone, neurocutaneous disorder, was used as a model for this study. From January 1, 2017, to May 4, 2018, the Human Gene Mutation Database and a cohort of patients at the National Institutes of Health were searched and screened to identify reported mutations associated with XP. The clinical phenotype of these patients was confirmed from reports in the literature and National Institutes of Health medical records. The genetically predicted prevalence of disease based on frequency of known pathogenic mutations was compared with the prevalence of patients clinically diagnosed with phenotypic XP. Exome sequencing of more than 200 000 alleles from the Genome Aggregation Database, the National Cancer Institute Division of Cancer Epidemiology and Genetics database of healthy controls, and an Inova Hospital Study database was used to investigate the frequencies of these mutations in the general population. Main Outcomes and Measures: Listing of all reported mutations associated with XP, their frequencies in 3 large exome sequence databases, determination of the number of patients in the United States with XP using modeling equations, and comparison of the observed and reported numbers of patients with XP with specific mutations. Results: A total of 156 pathogenic missense and nonsense mutations associated with XP were identified in the National Institutes of Health cohort and the Human Gene Mutation Database. The Genome Aggregation Database provided frequency data for 65 of these mutations, with a total allele frequency of 1.13%. The XPF (ERCC4) mutation, p.P379S, had an allele frequency of 0.4%, and the XPC mutation, p.P334H, had an allele frequency of 0.3%. With the Hardy-Weinberg equation, it was determined that there should be more than 8000 patients who are homozygous for these mutations in the United States. In contrast, only 3 patients with XP were reported as having the XPF mutation, and 1 patient was reported as having the XPC mutation. Conclusions and Relevance: The findings from this study suggest that clinicians should approach large genomic databases with caution when trying to correlate the clinical implications of genetic variants with the prevalence of disease risk. Unsuspected mutations in known genes with a predisposition for skin cancer may be responsible for some of the high frequency of skin cancers in the general population.

Indexed as

Big DataMutationAdultDNA Mutational AnalysisDNA RepairFemaleGene FrequencyGenotypeHumansMalePhenotypePrevalenceRetrospective StudiesUnited StatesXeroderma PigmentosumXeroderma Pigmentosum Group A ProteinXeroderma Pigmentosum Group A Protein

Identifiers

PMID30516811
PMCPMC6439575
OpenAlexW2902268968

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.