Evidence map›Paper›PMID 31821614›Full record

ArticleGenetic epidemiology2020

Integrating germline and somatic genetics to identify genes associated with lung cancer.

Jack Pattee, Xiaowei Zhan, Guanghua Xiao, Wei Pan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genetic epidemiology, 2020. 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
–field-weighted citation impact
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.

  1. Recent advances in hydrogels-based osteosarcoma therapy.Frontiers in bioengineering and biotechnology · 2022
    Review
  2. 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

4 authors.

Jack PatteeDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota.
Xiaowei ZhanQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Guanghua XiaoQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Wei PanDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota.ORCID 0000-0002-1159-0582

Funding

Association analysis of rare variants with sequencing dataR01HL116720 · NHLBI · UNIVERSITY OF MINNESOTA · PI PAN, WEI, WEI, PENG · 2013 to 2020
$3.3M
Powerful Inference and Prediction for Genetic AssociationR01HL105397 · NHLBI · UNIVERSITY OF MINNESOTA · PI PAN, WEI, SHEN, XIAOTONG TOM · 2011 to 2018
$2.9M
Statistical Methods for Genomic and Proteomic DataR01HL065462 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI PAN, WEI · 2002 to 2012
$1.5M
Estimation and Inference of Gene Regulatory NetworksR01GM126002 · NIGMS · UNIVERSITY OF MINNESOTA · PI PAN, WEI, SHEN, XIAOTONG TOM · 2017 to 2020
$1.4M
Statistical Methods for Genomic DataR01GM113250 · NIGMS · UNIVERSITY OF MINNESOTA · PI PAN, WEI · 2014 to 2017
$702k
Biostatistics in Genetics and Genomics Training ProgramT32GM108557 · NIGMS · UNIVERSITY OF MINNESOTA · PI PAN, WEI · 2014 to 2018
$583k
Integrating genomic and imaging endophenotypes in GWASR21AG057038 · NIA · UNIVERSITY OF MINNESOTA · PI PAN, WEI · 2017 to 2018
$405k
NHLBI NIH HHS R01 HL065462NHLBI NIH HHS R01 HL105397NHLBI NIH HHS R01 HL116720NIA NIH HHS R21 AG057038NIGMS NIH HHS R01 GM113250NIGMS NIH HHS R01 GM126002NIGMS NIH HHS T32 GM108557
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of association tests and illuminate the biological mechanisms by which genetic variants modulate complex traits. We extend the TWAS methodology to incorporate somatic information from tumors. By integrating germline and somatic data we are able to leverage information from the nuanced somatic landscape of tumors. Thus we can augment the power of TWAS-type tests to detect germline genetic variants associated with cancer phenotypes. We use somatic and germline data on lung adenocarcinomas from The Cancer Genome Atlas in conjunction with a meta-analyzed lung cancer GWAS to identify novel genes associated with lung cancer.

Indexed as

Genes, NeoplasmGenetic Association StudiesGenetic Predisposition to DiseaseGene Expression Regulation, NeoplasticGenome-Wide Association StudyGerm CellsHumansLung NeoplasmsMeta-Analysis as TopicMutationPolymorphism, Single NucleotideQuantitative Trait LociReproducibility of ResultsaSPU testeQTLPrediXcanSSU testsum testTWAS

Identifiers

PMID31821614
PMCPMC7064390

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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.