Evidence map›Paper›PMID 42050630›Full record

ArticleBreast cancer research : BCR2026

Predictive performance of breast cancer polygenic risk scores from diverse ancestries: a prospective study in Japanese women.

Megumi Hara, Tsuyoshi Hachiya, Takuma Furukawa, Yuichiro Nishida, Keitaro Tanaka, Chisato Shimanoe, Jun Otonari, Hiroaki Ikezaki, Kenji Wakai, Takashi Matsunaga and 22 more

Abstract read
In one paragraph

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. 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

32 authors.

Megumi HaraDepartment of Preventive Medicine, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, 849-8501, Saga, Japan. harameg@cc.saga-u.ac.jp.ORCID http://orcid.org/0000-0002-8708-3237
Tsuyoshi HachiyaDivision of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan.
Takuma FurukawaDepartment of Preventive Medicine, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, 849-8501, Saga, Japan.
Yuichiro NishidaDepartment of Preventive Medicine, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, 849-8501, Saga, Japan.
Keitaro TanakaDepartment of Preventive Medicine, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, 849-8501, Saga, Japan.
Chisato ShimanoeDepartment of Pharmacy, Saga University Hospital, Saga, Japan.
Jun OtonariDepartment of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Hiroaki IkezakiDepartment of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan.
Kenji WakaiDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Takashi MatsunagaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Hidemi ItoDivision of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan.
Sayaka YamamotoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
Nobuaki MichihataCancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan.
Yohko NakamuraCancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan.
Shiroh TanoueDepartment of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.
Yoshifumi HidakaDepartment of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.
Takeshi NishiyamaDepartment of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Hiroko NakagawaDepartment of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Naoyuki TakashimaDepartment of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Daisuke MatsuiDepartment of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kiyonori KurikiLaboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan.
Katsuyuki MiuraNCD Epidemiology Research Center, Shiga University of Medical Science, Otsu, Japan.
Kenji MatsuiNCD Epidemiology Research Center, Shiga University of Medical Science, Otsu, Japan.
Takeshi WatanabeDepartment of Medical Artificial Intelligence and Data Science, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan.
Kengo WatanabeDepartment of Medical Artificial Intelligence and Data Science, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan.
Itsuki KageyamaDepartment of Public Health, Aichi Medical University School of Medicine, Nagakute, Japan.
Masahiro NakatochiPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yukihide MomozawaLaboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Rieko OkadaDepartment of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yuriko N KoyanagiDivision 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.
Keitaro MatsuoDivision of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.

Funding

Grants-in-Aid for Scientific Research for Priority Areas of Cancer No. 17015018Grants-in-Aid for Scientific Research for Priority Areas of Innovative Areas No. 221S0001Japan Society for the Promotion of Science (JSPS) KAKENHI Grant No. 16H06277 and 22H04923 [CoBiA]
6 · The paper itself

Abstract

backgroundPolygenic risk scores (PRSes) have emerged as promising tools for stratifying breast cancer risk on the basis of genomic data. However, PRSes developed in one ancestral population may vary in predictive performance when applied to a different population. This study aimed to evaluate the utility of six breast cancer PRSes developed via European and East Asian genome-wide association studies (GWASes) in a Japanese prospective cohort.

methodsWe analysed data from 7,965 women enrolled in the Japan Multi-Institutional Collaborative Cohort (J-MICC) study, with a mean follow-up of 11.3 years. Six published PRSes were calculated via genome-wide genotype data, and their associations with breast cancer incidence were assessed via Cox proportional hazards models adjusted for age, survey area, and population structure. Hazard ratios (HRs), 95% confidence intervals (CIs), and Harrell’s C statistics are reported.

resultsFive of the six PRSes were significantly associated with breast cancer risk. The European-derived PRS313_BC demonstrated the highest predictive performance (HR per standard deviation (SD) = 1.64; C statistic = 0.69; P < 0.001), particularly among women diagnosed with breast cancer before 50 years of age.

conclusionsDespite cross-ancestry differences, a European-derived PRS demonstrated strong predictive value for breast cancer risk in a Japanese population, likely reflecting the scale and optimization of the original GWAS. These findings indicate that GWAS scale and statistical power may currently outweigh ancestry matching in PRS performance. However, large-scale ancestry-specific GWASes remain essential to improve prediction accuracy in East Asian populations.

Indexed as

Breast NeoplasmsGenetic Predisposition to DiseaseAdultAgedEast Asian PeopleFemaleGenetic Risk ScoreGenome-Wide Association StudyHumansIncidenceJapanMiddle AgedPolymorphism, Single NucleotideProspective StudiesRisk FactorsBreast cancercohort studyPolygenic risk score

Identifiers

PMID42050630
PMCPMC13270709

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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 OpenQuestion graph.