Article in Journal of the National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
0numbers the graph read from it
0cells of the map it votes in
5citing 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.
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
21 authors.
Jonathan M DownieClinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0002-5424-4401
Amit D JoshiClinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.
Connor M GeraghtyClinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.
Brendan J GuercioDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.ORCID 0000-0001-6296-2473
Oana A ZeleznikChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-8705-1163
Mingyang SongClinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0002-1324-0316
Alaina M BeverDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0003-3004-8497
David A DrewClinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0002-8813-0816
Fred K TabungDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0001-8193-7150
Xuehong ZhangDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0002-8260-8508
Lina JinChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-8961-2809
A Heather EliassenDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0002-3961-6609
Walter C WillettDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0003-1458-7597
Kana WuDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0001-7300-1694
Peter KraftDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0002-4472-8103
Rulla TamimiDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.
Clary ClishBroad Institute of MIT and Harvard, Cambridge, MA, United States.ORCID 0000-0001-8259-9245
Charles S FuchsYale Cancer Center, New Haven, CT, United States.
Edward GiovannucciDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0002-6123-0219
Jeffrey A MeyerhardtDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-1120-0898
Andrew T ChanClinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0001-7284-6767
Funding
Statistical MethodsP01CA087969 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ROSNER, BERNARD A · 2000 to 2019
$77.8M
ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Elizabeth Austen Lawson, Takara Leah Stanley · 1994 to 2026
$31.6M
Life Course Cancer Epidemiology Cohort in WomenU01CA176726 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 2018 to 2025
$22.4M
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
Training Program in Cancer EpidemiologyT32CA009001 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI A. Heather Eliassen, Meir Stampfer · 1985 to 2026
$17.3M
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
Medical Scientist Training ProgramT32GM144273 · NIGMS · HARVARD MEDICAL SCHOOL · PI David Shumway Jones, Jacqueline A. Lees · 2022 to 2026
$14.7M
Premonopausal Hormone Levels and Risk of Breast CancerR01CA067262 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HANKINSON, SUSAN E · 2002 to 2011
$11.9M
Precision Prevention Research ProgramR35CA253185 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Andrew T Chan · 2020 to 2026
$6.9M
Coffee and metabolites modulating the gut microbiome for improved colorectal cancer survivalR01CA263776 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Mingyang Song · 2022 to 2026
$3.3M
The Gut Microbiome, Lifestyle, and Colorectal NeoplasiaU01CA261961 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Mingyang Song · 2022 to 2026
$3.0M
Harnessing DNA methylation in peripheral blood for improved colorectal cancer preventionR01CA285851 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Marios Giannakis, Mingyang Song · 2024 to 2026
$2.0M
American Cancer Society Clinical Research Professor CRP-23-1014041American Cancer Society Mentored Research Scholar MRSG-17-220-01-NECAmerican Cancer Society Research ProfessorAmerican Cancer Society Research Scholar RSG-17-190-01-NECNCI NIH HHS F30 CA265012NCI NIH HHS P01 CA087969NCI NIH HHS R00 CA207736NCI NIH HHS R01 CA067262NCI NIH HHS R01 CA263776NCI NIH HHS R01 CA285851NCI NIH HHS R21 CA252962NCI NIH HHS R35 CA253185NCI NIH HHS T32 CA009001NCI NIH HHS U01 CA167552NCI NIH HHS U01 CA176726NCI NIH HHS U01 CA261961NCI NIH HHS UM1 CA186107NIDDK NIH HHS K01 DK110267NIDDK NIH HHS L30 DK137289NIDDK NIH HHS P30 DK040561NIDDK NIH HHS R03 DK127148NIGMS NIH HHS T32 GM144273NIH HHS UM1 CA186107
6 · The paper itself
Abstract
backgroundMetabolomic profiles may influence colorectal cancer (CRC) development. Few studies have performed prediagnostic metabolome-wide analyses with CRC risk.
methodsWe conducted a nested case-control study among women (Nurses' Health Study) and men (Health Professionals Follow-Up Study) who provided blood between 1989 and 1995. Over 22.9 years, 684 (409 Nurses' Health Study, 275 Health Professionals Follow-Up Study) individuals developed CRC and were matched 1:1 to unaffected participants. Liquid chromatography-mass spectrometry identified 255 plasma metabolites after quality control. Cohort-specific and combined metabolite association analyses were performed using conditional logistic regression. Metabolite set enrichment analysis was used to identify differential abundance in metabolite classes. The R Weighted Correlation Network Analysis package provided modules of covarying metabolites, which were tested for CRC association.
resultsMetabolite set enrichment analysis identified specific acylcarnitines associated with higher CRC risk and triacylglycerols with lower CRC risk among women and men. Further, phosphatidylcholines were associated with a higher risk of CRC among men. In an analysis restricted to CRC diagnosed 2 years after blood draw, myristoleic acid (odds ratio = 1.37 [95% CI = 1.15 to 1.62]; false discovery rate = 0.072) and C60:12 triacylglycerol (odds ratio = 0.75 [95% CI = 0.64 to 0.88]; false discovery rate = 0.072) were associated with CRC risk in women. Weighted correlation network analysis identified amino acids associated with CRC in men, fatty acid esters (carnitines) with distal CRC in men, and triradylcglycerols inversely associated with CRC in women.
conclusionsWe identified prediagnostic CRC-associated metabolites with distinct sex-specific profiles. These results provide insight into CRC etiopathogenesis and have implications for risk prediction strategies.
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.
Novel metabolomic predictors of incident colorectal cancer in men and women. · full record | OpenQuestion