Evidence map›Paper›PMID 41162332›Full record

ArticleCancer science2026

Differential Impact of BMI-Associated Genetic Variants on Breast Cancer Risk: Insights From Mediation Analysis.

Yuri Ando, Yuriko N Koyanagi, Yuji Iwashita, Sayaka Yamamoto, Yumiko Kasugai, Isao Oze, Masahiro Nakatochi, Fumikata Hara, Fumihiko Matsuda, Issei Imoto and 2 more

Abstract read
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In one paragraph

Article in Cancer science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

12 authors.

Yuri AndoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
Yuriko N KoyanagiDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.ORCID https://orcid.org/0000-0002-5675-3429
Yuji IwashitaDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
Sayaka YamamotoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
Yumiko KasugaiDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
Isao OzeDivision of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan.ORCID https://orcid.org/0000-0002-0762-1147
Masahiro NakatochiPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID https://orcid.org/0000-0002-1838-4837
Fumikata HaraDepartment of Breast Oncology, Aichi Cancer Center Hospital, Nagoya, Japan.
Fumihiko MatsudaCenter for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Issei ImotoAichi Cancer Center Research Institute, Nagoya, Japan.
Hidemi ItoDivision of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan.ORCID https://orcid.org/0000-0002-8023-4581
Keitaro MatsuoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.ORCID https://orcid.org/0000-0003-1761-6314

Funding

Ministry of Education, Culture, Sports, Science and Technology of Japan 17015018Ministry of Education, Culture, Sports, Science and Technology of Japan 221S0001Ministry of Education, Culture, Sports, Science and Technology of Japan JP16H06277 [CoBiA]Ministry of Education, Culture, Sports, Science and Technology of Japan JP23K16316Ministry of Education, Culture, Sports, Science and Technology of Japan JP24K02697Ministry of Education, Culture, Sports, Science and Technology of Japan JP26253041Ministry of Health, Labour and Welfare of Japan
6 · The paper itself

Abstract

Obesity is a known risk factor for breast cancer, particularly in postmenopausal women. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with body mass index (BMI). We conducted a case-control study with 1273 breast cancer cases and 4816 controls to examine whether five BMI-associated SNPs (rs939584 [TMEM18], rs4409766 [BORCS7-ASMT], rs6265 [BDNF], rs1927790 [HS6ST3], rs1421085 [FTO]) influence breast cancer risk through BMI-dependent or -independent pathways using mediation analysis. For postmenopausal breast cancer, rs6265 (C > T) exhibited a carcinogenic direct effect (odds ratio [OR] = 1.18, 95% confidence interval [CI]: 1.04-1.34) along with a protective indirect effect through changes in BMI (OR = 0.98, 95% CI 0.96-0.99), while rs1421085 (T > C) showed a carcinogenic indirect effect (OR = 1.03, 95% CI 1.00-1.05). No significant associations were observed for any SNPs in premenopausal breast cancer. These findings suggest that two BMI-associated genetic variants, rs6265 and rs1421085, influence postmenopausal breast cancer risk through changes in BMI, and that rs6265 also exerts a direct effect through pathways independent of BMI, providing insight into a previously uncharacterized association between obesity-related genetic factors and breast cancer and highlighting the potential utility of genetic profiling in personalized risk assessment.

Indexed as

Body Mass IndexBreast NeoplasmsGenetic Predisposition to DiseaseObesityPolymorphism, Single NucleotideAdultAgedCase-Control StudiesFemaleGenome-Wide Association StudyHumansMediation AnalysisMiddle AgedPostmenopauseRisk Factorsbody mass indexbreast cancercase–control studymediation analysissingle nucleotide polymorphism

Identifiers

PMID41162332
PMCPMC12775586

What Socratic holds

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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.