Evidence map›Paper›PMID 27930734›Full record

ArticlePloS one2016

Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records.

Karen Y He, Yiqing Zhao, Elizabeth W McPherson, Quan Li, Fan Xia, Chunhua Weng, Kai Wang, Max M He

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Big Data Analytics for Genomic Medicine.International journal of molecular sciences · 2017
    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

8 authors at 5 institutions in 1 country.

Karen Y HeDepartment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Yiqing ZhaoCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, United States of America.ORCID http://orcid.org/0000-0003-2874-8136
Elizabeth W McPhersonCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, United States of America.
Quan LiZilkha Neurogenetic Institute, University of Southern California, Los Angeles, California, United States of America.
Fan XiaDeparment of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America.
Chunhua WengDepartment of Biomedical Informatics, Columbia University Medical Center, New York, New York, United States of America.
Kai WangZilkha Neurogenetic Institute, University of Southern California, Los Angeles, California, United States of America.
Max M HeCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, United States of America.ORCID http://orcid.org/0000-0002-5347-6374
Marshfield Clinic · USUniversity of Southern California · USBaylor College of Medicine · USCase Western Reserve University · USColumbia University Irving Medical Center · US

Funding

Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
OMOP information model for eMERGE phenotypingU01HG008680 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, GEORGE M HRIPCSAK · 2015 to 2026
$13.3M
BIOMETRIC-GENETIC ANALYSIS OF CARDIOVASCULAR DISEASET32HL007567 · NHLBI · LOUISIANA STATE UNIV HSC NEW ORLEANS · PI ZHU, XIAOFENG · 1985 to 2021
$6.0M
Integrated variation detection annotation and analysis for high-throughout sequeR01HG006465 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, KAI · 2012 to 2016
$1.8M
NCATS NIH HHS UL1 TR000427NHGRI NIH HHS R01 HG006465NHGRI NIH HHS U01 HG008680NHLBI NIH HHS T32 HL007567
6 · The paper itself

Abstract

backgroundIt is unclear whether and how whole-genome sequencing (WGS) data can be used to implement genomic medicine. Our objective is to retrospectively evaluate whether WGS can facilitate improving prevention and care for patients with susceptibility to cancer syndromes. METHODS AND

findingsWe analyzed genetic mutations in 60 autosomal dominant cancer-predisposition genes in 300 deceased patients with WGS data and nearly complete long-term (over 30 years) medical records. To infer biological insights from massive amounts of WGS data and comprehensive clinical data in a short period of time, we developed an in-house analysis pipeline within the SeqHBase software framework to quickly identify pathogenic or likely pathogenic variants. The clinical data of the patients who carried pathogenic and/or likely pathogenic variants were further reviewed to assess their clinical conditions using their lifetime EHRs. Among the 300 participants, 5 (1.7%) carried pathogenic or likely pathogenic variants in 5 cancer-predisposing genes: one in APC, BRCA1, BRCA2, NF1, and TP53 each. When assessing the clinical data, each of the 5 patients had one or more different types of cancers, fully consistent with their genetic profiles. Among these 5 patients, 2 died due to cancer while the others had multiple disorders later in their lifetimes; however, they may have benefited from early diagnosis and treatment for healthier lives, had the patients had genetic testing in their earlier lifetimes.

conclusionsWe demonstrated a case study where the discovery of pathogenic or likely pathogenic germline mutations from population-wide WGS correlates with clinical outcome. The use of WGS may have clinical impacts to improve healthcare delivery.

Indexed as

Electronic Health RecordsGenes, NeoplasmGenetic Predisposition to DiseaseGenome, HumanMutationHumansNeoplasmsSequence Analysis, DNA

Identifiers

PMID27930734
PMCPMC5145192
OpenAlexW2559899005

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.