Evidence map›Paper›PMID 26448358›Full record

ArticlePLoS genetics2015

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

Frederick E Dewey, Megan E Grove, James R Priest, Daryl Waggott, Prag Batra, Clint L Miller, Matthew Wheeler, Amin Zia, Cuiping Pan, Konrad J Karzcewski and 8 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PLoS genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.9field-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

12 citing papers in PubMed, 23 citations in OpenAlex.

  1. A concurrent dual analysis of genomic data augments diagnoses: Experiences of 2 clinical sites in the Undiagnosed Diseases Network.Genetics in medicine : official journal of the American College of Medical Genetics · 2023
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. A primer to clinical genome sequencing.Current opinion in pediatrics · 2017
    Review
  7. Exome sequencing identifies de novo pathogenic variants inCold Spring Harbor molecular case studies · 2017
    Article
  8. Early somatic mosaicism is a rare cause of long-QT syndrome.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  9. Article
  10. Towards precision medicine.Nature reviews. Genetics · 2016
    Review
  11. Article
  12. Article
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

18 authors at 2 institutions in 1 country.

Frederick E DeweyStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Cardiovascular Medicine, Stanford University, Stanford, California, United States of America.
Megan E GroveStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Cardiovascular Medicine, Stanford University, Stanford, California, United States of America.
James R PriestStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Pediatric Cardiology, Stanford University, Stanford, California, United States of America.
Daryl WaggottStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America.
Prag BatraStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America.
Clint L MillerStanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Cardiovascular Medicine, Stanford University, Stanford, California, United States of America.
Matthew WheelerStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Cardiovascular Medicine, Stanford University, Stanford, California, United States of America.
Amin ZiaStanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, California, United States of America; Department of Genetics, Stanford University, Stanford, California, United States of America.
Cuiping PanStanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, California, United States of America; Department of Genetics, Stanford University, Stanford, California, United States of America.
Konrad J KarzcewskiStanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, California, United States of America; Department of Genetics, Stanford University, Stanford, California, United States of America; Biomedical Informatics Training Program, Stanford University, Stanford, California, United States of America.
Christina MiyakeDivision of Pediatric Cardiology, Stanford University, Stanford, California, United States of America.
Michelle Whirl-CarrilloDepartment of Genetics, Stanford University, Stanford, California, United States of America.
Teri E KleinDepartment of Genetics, Stanford University, Stanford, California, United States of America.
Somalee DattaStanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, California, United States of America.
Russ B AltmanDepartment of Genetics, Stanford University, Stanford, California, United States of America.
Michael SnyderStanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, California, United States of America; Department of Genetics, Stanford University, Stanford, California, United States of America.
Thomas QuertermousStanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Cardiovascular Medicine, Stanford University, Stanford, California, United States of America.
Euan A AshleyStanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California, United States of America; Stanford Cardiovascular Institute, Stanford University, Stanford, California, United States of America; Division of Cardiovascular Medicine, Stanford University, Stanford, California, United States of America; Department of Genetics, Stanford University, Stanford, California, United States of America.
Stanford University · USCardiovascular Institute of the South · US

Funding

Pediatric Scientist Development Program (PSDP) [K12]K12HD000850 · NICHD · YALE UNIVERSITY · PI Sallie R. Permar · 1987 to 2026
$44.1M
PharmGKB: pharmacogenomics knowledge for precision medicineR24GM061374 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO, KLEIN, TERI ELLEN · 2010 to 2018
$25.2M
Clinically Relevant Genome Variation DatabaseU01HG007436 · NHGRI · STANFORD UNIVERSITY · PI BUSTAMANTE, CARLOS DANIEL, PLON, SHARON E. · 2013 to 2016
$10.5M
Human Induced Pluripotent Stem Cells for Cardiovascular Disease ModelingR01HL113006 · NHLBI · STANFORD UNIVERSITY · PI WU, JOSEPH C. · 2012 to 2025
$6.8M
Training in Myocardial Biology at Stanford (TIMBS)T32HL094274 · NHLBI · STANFORD UNIVERSITY · PI Euan A Ashley, Daniel Bernstein · 2010 to 2026
$5.0M
Epistatic Regulatory Mechanisms of Coronary Heart Disease RiskK99HL125912 · NHLBI · STANFORD UNIVERSITY · PI MILLER, CLINT L · 2015 to 2016
$285k
NHGRI NIH HHS U01 HG007436NHLBI NIH HHS K99 HL125912NHLBI NIH HHS R01 HL113006NHLBI NIH HHS T32 HL094274NICHD NIH HHS K12 HD000850NIGMS NIH HHS R24 GM061374
6 · The paper itself

Abstract

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.

Indexed as

Genetic Predisposition to DiseaseSequence Analysis, DNAArrhythmias, CardiacBase SequenceChromosome MappingGenetic VariationGenome, HumanGenotypeHumansPhenotypePlasma Membrane Calcium-Transporting ATPasesATP2B4 protein, humanPlasma Membrane Calcium-Transporting ATPases

Identifiers

PMID26448358
PMCPMC4598191
OpenAlexW1956401713

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.