Evidence map›Paper›PMID 37364297›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2023

Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci.

John Lai, Chi Kuen Wong, Daniel F Schmidt, Miroslaw K Kapuscinski, Karen Alpen, Robert J MacInnis, Daniel D Buchanan, Aung K Win, Jane C Figueiredo, Andrew T Chan and 9 more

Open access · greenAbstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2023. 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
0.5field-weighted citation impact, top 32% 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, 2 citations in OpenAlex.

  1. Article
  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

19 authors at 9 institutions in 3 countries.

John LaiCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-8019-7012
Chi Kuen WongCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0001-9792-4792
Daniel F SchmidtCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-1788-2375
Miroslaw K KapuscinskiCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-4561-2719
Karen AlpenCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0001-8283-2422
Robert J MacInnisCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-1627-5047
Daniel D BuchananColorectal Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0003-2225-6675
Aung K WinCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-2794-5261
Jane C FigueiredoSamuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.ORCID 0000-0001-8040-3341
Andrew T ChanDivision of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.ORCID 0000-0001-7284-6767
Tabitha A HarrisonPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0002-4173-7530
Michael HoffmeisterDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0002-8307-3197
Emily WhitePublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0003-0544-1633
Loic Le MarchandEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.ORCID 0000-0001-5013-980X
Rish K PaiDepartment of Pathology and Laboratory Medicine, Mayo Clinic Arizona, Scottsdale, Arizona.ORCID 0000-0002-2692-221X
Ulrike PetersPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0001-5666-9318
John L HopperCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-8567-173X
Mark A Jenkins *Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-8964-6160
Enes Makalic *Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0003-3017-0871
The University of Melbourne · AUFred Hutch Cancer Center · USThe Royal Melbourne Hospital · AUBroad Institute · USCancer Center of Hawaii · USCedars-Sinai Medical Center · USGerman Cancer Research Center · DEMayo Clinic in Arizona · USUniversity of Washington · US

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
Translational Therapeutics Research Program (TT)P30CA016058 · NCI · OHIO STATE UNIVERSITY · PI Jennifer A. Woyach · 1985 to 2026
$132.3M
Statistical MethodsP01CA087969 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ROSNER, BERNARD A · 2000 to 2019
$77.8M
Validity of Diet and Activity Measures in WomenP01CA055075 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI RIMM, ERIC B · 1991 to 2009
$41.8M
Tissue and Pathology ResourcesP50CA127003 · NCI · DANA-FARBER CANCER INST · PI BASS, ADAM JOEL · 2007 to 2023
$33.2M
GENETIC SUSCEPTIBILITY TO CANCER IN MULTIETHNIC COHORTSR01CA063464 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HENDERSON, BRIAN E · 2001 to 2005
$23.2M
Multiethnic Cohort Study of Diet and CancerR37CA054281 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI KOLONEL, LAURENCE N. · 2003 to 2012
$23.2M
Long Term Multidisciplinary Study of Cancer in Women: The Nurses Health StudyUM1CA186107 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIASSEN, A. HEATHER, STAMPFER, MEIR · 2014 to 2023
$22.3M
Molecular pathological epidemiology of colorectal cancerU01CA137088 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETERS, ULRIKE · 2009 to 2018
$21.8M
VALIDATION OF A DIET HISTORY METHOD FOR EPIDEMIOLOGIC STUDIES OF CANCERP01CA033619 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI KOLONEL, LAURENCE N. · 1985 to 2010
$18.5M
Cancer Epidemiology Cohort in Male Health ProfessionalsU01CA167552 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Lorelei Mucci, Walter C. Willett · 2017 to 2026
$17.0M
Data sharing: the Colon Cancer Family Registry CohortU01CA167551 · NCI · UNIVERSITY OF MELBOURNE · PI Daniel David BUCHANAN, Steven Gallinger · 2018 to 2026
$16.8M
NCI NIH HHS K05 CA154337NCI NIH HHS K07 CA190673NCI NIH HHS P01 CA033619NCI NIH HHS P01 CA055075NCI NIH HHS P01 CA087969NCI NIH HHS P30 CA015704NCI NIH HHS P30 CA016058NCI NIH HHS P50 CA127003NCI NIH HHS R01 CA042182NCI NIH HHS R01 CA059045NCI NIH HHS R01 CA063464NCI NIH HHS R01 CA067941NCI NIH HHS R01 CA076366NCI NIH HHS R01 CA081488NCI NIH HHS R01 CA137178NCI NIH HHS R01 CA151993NCI NIH HHS R35 CA197735NCI NIH HHS R37 CA054281NCI NIH HHS U01 CA067941NCI NIH HHS U01 CA074783NCI NIH HHS U01 CA074794NCI NIH HHS U01 CA074806NCI NIH HHS U01 CA097735NCI NIH HHS U01 CA122839NCI NIH HHS U01 CA137088NCI NIH HHS U01 CA164930NCI NIH HHS U01 CA167551NCI NIH HHS U01 CA167552NCI NIH HHS U19 CA148107NCI NIH HHS U24 CA074783NCI NIH HHS U24 CA074794NCI NIH HHS UM1 CA167551NCI NIH HHS UM1 CA167552NCI NIH HHS UM1 CA186107NHLBI NIH HHS HHSN268201100001INHLBI NIH HHS HHSN268201100002INHLBI NIH HHS HHSN268201100003INHLBI NIH HHS HHSN268201100004INHLBI NIH HHS HHSN268201100046CNHLBI NIH HHS HHSN268201200008CNHLBI NIH HHS HHSN268201200008INIA NIH HHS HHSN271201100004CWHI NIH HHS HHSN268201100001CWHI NIH HHS HHSN268201100002CWHI NIH HHS HHSN268201100003CWHI NIH HHS HHSN268201100004C
6 · The paper itself

Abstract

backgroundDEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate susceptibility regions by considering the risk signals from overlapping groups of sequential variants across the genome.

methodsWe applied a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer data from the Colon Cancer Family Registry (CCFR; 5,735 cases and 3,688 controls), and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO; 8,865 cases and 10,285 controls) studies. A DEPTH score > 1 was used to identify candidate susceptibility regions common to both analyses. We compared DEPTH results against those from conventional genome-wide association study (GWAS) analyses of these two studies as well as against 132 published susceptibility regions.

resultsInitial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) candidate susceptibility regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 candidate susceptibility regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 regions that would not be detected using conventional GWAS methods, nor had they been identified by previous colorectal cancer GWASs. We found four reproducible candidate susceptibility regions (2q22.2, 2q33.1, 6p21.32, 13q14.3). The highest DEPTH scores were in the human leukocyte antigen locus at 6p21 where the strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data.

conclusionsDEPTH can identify candidate susceptibility regions for colorectal cancer not identified using conventional analyses of larger datasets. IMPACT: DEPTH has potential as a powerful complementary tool to conventional GWAS analyses for discovering susceptibility regions within the genome.

Indexed as

Colorectal NeoplasmsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideProteinsRisk FactorsProteins

Identifiers

PMID37364297
PMCPMC10529807
OpenAlexW4382047191

What OpenQuestion holds

Textmetadata
LicenceTDM
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.