Evidence map›Paper›PMID 40635049›Full record

ArticleHuman genomics2025

Phenome-wide association study identifies multiple traits associated with a polygenic risk score for colorectal cancer.

Elisabeth A Rosenthal, Wei-Qi Wei, Yuan Luo, Bahram Namjou-Khales, Daniel J Schaid, Edward D Esplin, Michael Lape, Leah Kottyan, Jennifer Allen Pacheco, Chunhua Weng and 7 more

Abstract read
In one paragraph

Article in Human genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

17 authors.

Elisabeth A RosenthalDepartment of Medicine, Division of Medical Genetics, University of Washington Medical Center, Seattle, WA, USA. erosen@uw.edu.ORCID http://orcid.org/0000-0001-6042-4487
Wei-Qi WeiDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Yuan LuoFeinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Bahram Namjou-KhalesCenter for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Daniel J SchaidDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Edward D EsplinLabcorp Genetics, San Francisco, CA, USA.
Michael LapeDivision of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Leah KottyanDivision of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Jennifer Allen PachecoCenter for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Chunhua WengDepartment of Biomedical Informatics, Columbia, New York, NY, USA.
Adam Samuel GordonCenter for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Iftikhar J KulloDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
David R CrosslinDivision of Biomedical Informatics and Genomics, School of Medicine, Tulane, New Orleans, LA, USA.
William M GradyTranslational Sciences and Therapeutics Division and Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Li HsuPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Ulrike PetersDivision of Gastroenterology, University of Washington School of Medicine, Seattle, WA, USA.
Gail P JarvikDepartment of Medicine, Division of Medical Genetics, University of Washington Medical Center, Seattle, WA, USA.

Funding

Genomic Basis of Susceptibility to COVID-19 Infection and its ComplicationsU01HG006379 · NHGRI · MAYO CLINIC ROCHESTER · PI Richard R. Sharp · 2011 to 2026
$16.5M
Finding Genomic Profiles of COVID-19 Phenotypes from the EHRU01HG008685 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIZABETH W KARLSON, Matthew S Lebo · 2015 to 2026
$13.6M
Variation, Function, and Disease Supplement ProgramU01HG008657 · NHGRI · UNIVERSITY OF WASHINGTON · PI David Russell Crosslin, Gail Pairitz Jarvik · 2015 to 2026
$13.4M
OMOP information model for eMERGE phenotypingU01HG008680 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, GEORGE M HRIPCSAK · 2015 to 2026
$13.3M
DNA Sequencing Support for the eMERGE NetworkU01HG008664 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2015 to 2019
$10.9M
Global Alliance for Genomic Health (GA4GH)U01HG008676 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI LENNON, NIALL JOHN, REHM, HEIDI L · 2015 to 2019
$8.6M
The Electronic Medical Records and Genomics (eMERGE) Network Phase III Coordinating Center (U01)U01HG008701 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PETERSON, JOSEPH F. · 2015 to 2019
$7.1M
Biomarkers for optimizing risk prediction and early detection of cancers of the colon and esophagusU2CCA271902 · NCI · FRED HUTCHINSON CANCER CENTER · PI Cecilia C Yeung · 2022 to 2026
$5.3M
VGER, the Vanderbilt Genome-Electronic Records ProjectU01HG008672 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI DENNY, JOSHUA C., RODEN, DAN M · 2015 to 2019
$5.1M
The Future of Genomics Medicine in Patient Care: Contributions from CHOPU01HG008684 · NHGRI · CHILDREN'S HOSP OF PHILADELPHIA · PI HAKONARSON, HAKON · 2015 to 2019
$5.0M
OMOP information model for eMERGE phenotypingU01HG008679 · NHGRI · GEISINGER CLINIC · PI WILLIAMS, MARC S. · 2015 to 2019
$4.4M
Better Outcomes for Children: Promoting Excellence in Healthcare Genomics to Inform PolicyU01HG008666 · NHGRI · CINCINNATI CHILDRENS HOSP MED CTR · PI HARLEY, JOHN BARKER · 2015 to 2019
$4.2M
NCI NIH HHS U2C CA271902NHGRI NIH HHS U01 HG006379NHGRI NIH HHS U01 HG008657NHGRI NIH HHS U01HG008657, U01HG008685, U01HG008672, U01HG008666, U01HG006379, U01HG008679 , U01HG008680 , U01HG008684 , U01HG008673 , U01HG008701 , U01HG008676 , U01HG008664 , U54MD007593NHGRI NIH HHS U01 HG008664NHGRI NIH HHS U01 HG008666NHGRI NIH HHS U01 HG008672NHGRI NIH HHS U01 HG008673NHGRI NIH HHS U01 HG008676NHGRI NIH HHS U01 HG008679NHGRI NIH HHS U01 HG008680NHGRI NIH HHS U01 HG008684NHGRI NIH HHS U01 HG008685NHGRI NIH HHS U01 HG008701
6 · The paper itself

Abstract

backgroundMany factors, including environmental and genetic variables, contribute to Colorectal Cancer (CRC) risk. The genetic components of risk can be divided into monogenic and polygenic factors. Just as monogenic factors can increase risk for more than one condition, polygenic factors may also underlie multiple phenotypes, including behavioral traits. In order to understand the biology of CRC risk better, it is important to understand the shared polygenic genetic architecture contributing to CRC risk and other phenotypes, including CRC associated risk factors.

methodsWe investigated potential shared genetics by performing a Phenome-wide association study (PheWAS) with a multi-ancestry CRC polygenic risk score (PRS). The discovery cohort (N = 426,464) consisted of ancestrally diverse participants from the United Kingdom Biobank. The replication cohort (N = 87,271) consisted of ancestrally diverse participants from the electronic Medical Records and Genomics Network phase 3. We used a mixed-effects model to adjust for the presence of related individuals. To preserve power, we limited the number of tests by restricting analysis to ancestor phecodes derived from the electronic health record (EHR) that were not likely to be a result of CRC or its treatment.

resultsWe discovered and replicated associations between the CRC PRS and breast cancer, prostate cancer, obesity, smoking and alcohol use (discovery p < 1.1e-4; replication p < 0.0019). The association between CRC risk and prostate cancer may be a novel finding, whereas the association with breast cancer has been previously observed using orthogonal methods. The association between CRC risk and behavioral risk factors corroborate previous studies, also using orthogonal methods, and may reveal potential prevention or treatment strategies.

conclusionsAs these results corroborate findings from other studies using orthogonal methods, we demonstrate that a CRC PRS can be used as a proxy for genetic risk for CRC when investigating shared genetics between CRC and other phenotypes. Further study of the relationship between PRS from multiple traits with EHR data may reveal additional shared genetic factors. Ultimately, understanding these underlying genetic correlations may identify prevention and treatment strategies for CRC.

Indexed as

Colorectal NeoplasmsGenetic Predisposition to DiseaseMultifactorial InheritanceAgedFemaleGenetic Risk ScoreGenome-Wide Association StudyHumansMaleMiddle AgedPhenomicsPhenotypePolymorphism, Single NucleotideRisk FactorsUnited KingdomColorectal cancerCross-trait genetic correlationeMERGEPheWASPolygenic riskUK Biobank

Identifiers

PMID40635049
PMCPMC12239365

What Socratic holds

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LicenceCC BY-NC-ND
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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.