Differential Impact of <scp>BMI</scp> ‐Associated Genetic Variants on Breast Cancer Risk: Insights From Mediation Analysis

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.

Authors

Institutions

Publication Details

Journal
Cancer Science
Published
2025-10-29
DOI
https://doi.org/10.1111/cas.70239
Primary Topic
Cancer Risks and Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Fumikata Hara, Yuji Iwashita, Hidemi Ito, Masahiro Nakatochi et al.
Cancer Science
Cancer Risks and Factors
article

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

Fumikata Hara, Yuji Iwashita, Hidemi Ito, Masahiro Nakatochi, Yusuke Ando, Fumihiko Matsuda, Yuriko N. Koyanagi, Yumiko Kasugai, Keitaro Matsuo, Issei Imoto, Isao Oze, Sayaka Yamamoto
article en

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.

Cancer ScienceVol. 117(1)
Kyoto University (JP), Nagoya City University (JP), Aichi Cancer Center (JP), Nagoya University (JP)
Openalex Percentile: Top 58%
Cancer Risks and Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.