Evidence mapPaperPMID 41514346Full record

ArticleBreast cancer research : BCR2026

Distinct genetic profiles of obesity have different effects on breast cancer risk: leveraging Mendelian randomisation to interrogate causal pathways and identify mediating proteins.

Marina Isabel Marchal, Pascal M Mutie, Tayebeh Azimi, Yaqi Alexandra Deng, Torgny Karlsson, Åsa Johansson

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Article in Breast cancer research : BCR, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2 citing papers in PubMed.

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5 · Who and what money

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6 authors.

Marina Isabel MarchalDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden.
Pascal M MutieDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden.
Tayebeh AzimiDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden.
Yaqi Alexandra DengDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden.
Torgny KarlssonDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden.
Åsa JohanssonDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden. asa.johansson@igp.uu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity is a well-established risk factor for many cancers, but its association with breast cancer remains inconsistent. Obesity is a highly complex and polygenic condition, driven by multiple biological pathways, some of which have been linked to beneficial health effects, defining a metabolically healthy obese phenotype. We hypothesise that this heterogeneity may partly underlie the variable association with breast cancer, where different biological pathways may play divergent roles in disease risk.

methodsWe applied an approach in two parts to explore the heterogeneous effects of high body mass index (BMI) on breast cancer risk. First, we applied Mendelian randomisation (MR)-based clustering on genetic data (FinnGen, GIANT, BCAC) to identify clusters of BMI-increasing SNPs with differential effects on breast cancer, and the cluster-specific MR results were replicated in the UK Biobank. Second, we integrated proteomic data to estimate the cluster-specific effects of BMI on protein levels and the effect of these proteins on breast cancer risk, using two-sample MR. Mediation analyses were then carried out using the product-of-coefficient method.

resultsWe identified three clusters of SNPs associated with increased BMI while having differential effects on breast cancer risk: one risk-increasing (inverse variance weighted MR estimate: 1.27 [1.10, 1.44]), one medium protective (− 0.75 [− 0.82, − 0.68]), and one highly protective (− 1.92 [− 2.21, − 1.62]), comprising 24, 73, and 7 SNPs respectively, with similar magnitude of effects in the UK Biobank. In the two-sample MR, each cluster was associated with many proteins (70, 369 and 44 respectively, FDR q-value < 0.05), and the mediation analysis identified that three proteins significantly mediate cluster-specific effects on breast cancer risk. Among these proteins, MET is known to be involved in breast cancer, while little is known about the roles of CPM and CST6.

conclusionsThese findings suggest that the effect of obesity on breast cancer is mediated through multiple distinct biological pathways. The identified proteins provide a first insight into the mechanisms underlying these pathways. With further investigation, these results could provide a basis for developing personalised treatment strategies.

Indexed as

Breast NeoplasmsObesityBody Mass IndexFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMendelian Randomization AnalysisPolymorphism, Single NucleotideProteomicsRisk FactorsBMIBreast cancerClusteringMediationMendelian randomisationObesityProteomic

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PMID41514346
PMCPMC12849277

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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.