Evidence map›Paper›PMID 39366959›Full record

SynthesisNature communications2024

Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk.

Bryan R Gorman, Sun-Gou Ji, Michael Francis, Anoop K Sendamarai, Yunling Shi, Poornima Devineni, Uma Saxena, Elizabeth Partan, Andrea K DeVito, Jinyoung Byun and 14 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
–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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

24 authors.

Bryan R GormanCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.ORCID 0000-0002-4239-4672
Sun-Gou JiCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.ORCID 0000-0001-8652-6318
Michael FrancisCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.ORCID 0000-0002-1320-7161
Anoop K SendamaraiCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.ORCID 0000-0002-0476-5428
Yunling ShiCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.
Poornima DevineniCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.
Uma SaxenaCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.
Elizabeth PartanCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.ORCID 0000-0002-3995-6742
Andrea K DeVitoCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA.
Jinyoung ByunInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0001-8579-1435
Younghun HanInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0001-5048-8479
Xiangjun XiaoInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.
Don D SinThe University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada.ORCID 0000-0002-0756-6643
Wim TimensUniversity Medical Centre Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), University of Groningen, Groningen, Netherlands.ORCID 0000-0002-4146-6363
Jennifer MoserOffice of Research and Development, Department of Veterans Affairs, Washington, DC, USA.
Sumitra MuralidharOffice of Research and Development, Department of Veterans Affairs, Washington, DC, USA.ORCID 0000-0001-8417-9068
Rachel RamoniOffice of Research and Development, Department of Veterans Affairs, Washington, DC, USA.
Rayjean J HungLunenfeld-Tanenbaum Research Institute, Sinai Health System, University of Toronto, Toronto, ON, Canada.
James D McKaySection of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Yohan BosséInstitut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Quebec City, QC, Canada.ORCID 0000-0002-3067-3711
Ryan SunDepartment of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Christopher I AmosInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0002-8540-7023
VA Million Veteran Program
Saiju PyarajanCenter for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA. saiju.pyarajan@va.gov.ORCID 0000-0002-9047-3762

Funding

Sequencing Familial Lung CancerR01CA243483 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos, DIPTASRI M MANDAL · 2023 to 2026
$4.2M
Sequencing Familial Lung CancerU01CA243483 · NCI · BAYLOR COLLEGE OF MEDICINE · PI AMOS, CHRISTOPHER I., PINNEY, SUSAN MENGEL · 2020 to 2022
$2.0M
High Memory High-Performance Computer Cluster for Biomedical ResearchS10OD032185 · OD · BAYLOR COLLEGE OF MEDICINE · PI HILSENBECK, SUSAN G. · 2022 to 2022
$596k
Biomedical Laboratory Research and Development, VA Office of Research and Development (VA Biomedical Laboratory Research and Development) MVP000NCI NIH HHS R01 CA243483NCI NIH HHS U01 CA243483NIH HHS S10 OD032185World Health Organization 001
6 · The paper itself

Abstract

Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.

Indexed as

Genetic Predisposition to DiseaseLung NeoplasmsSmokingAdenocarcinoma of LungAgedCarcinoma, Squamous CellCase-Control StudiesEthnicityFemaleGenetic LociGenetic Risk ScoreGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single Nucleotide

Identifiers

PMID39366959
PMCPMC11452618

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.