Displaying all 6 publications

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  1. Yang Y, Shu X, Shu XO, Bolla MK, Kweon SS, Cai Q, et al.
    EBioMedicine, 2019 Oct;48:203-211.
    PMID: 31629678 DOI: 10.1016/j.ebiom.2019.09.006
    BACKGROUND: We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets.

    METHODS: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.

    FINDINGS: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P 

  2. Cai Q, Zhang B, Sung H, Low SK, Kweon SS, Lu W, et al.
    Nat Genet, 2014 Aug;46(8):886-90.
    PMID: 25038754 DOI: 10.1038/ng.3041
    In a three-stage genome-wide association study among East Asian women including 22,780 cases and 24,181 controls, we identified 3 genetic loci newly associated with breast cancer risk, including rs4951011 at 1q32.1 (in intron 2 of the ZC3H11A gene; P=8.82×10(-9)), rs10474352 at 5q14.3 (near the ARRDC3 gene; P=1.67×10(-9)) and rs2290203 at 15q26.1 (in intron 14 of the PRC1 gene; P=4.25×10(-8)). We replicated these associations in 16,003 cases and 41,335 controls of European ancestry (P=0.030, 0.004 and 0.010, respectively). Data from the ENCODE Project suggest that variants rs4951011 and rs10474352 might be located in an enhancer region and transcription factor binding sites, respectively. This study provides additional insights into the genetics and biology of breast cancer.
  3. Jia G, Ping J, Shu X, Yang Y, Cai Q, Kweon SS, et al.
    Am J Hum Genet, 2022 Dec 01;109(12):2185-2195.
    PMID: 36356581 DOI: 10.1016/j.ajhg.2022.10.011
    By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p 
  4. Abe SK, Nishio M, Huang HL, Leung CY, Islam MR, Rahman MS, et al.
    Public Health, 2024 Dec;237:130-134.
    PMID: 39368404 DOI: 10.1016/j.puhe.2024.09.020
    OBJECTIVES: To evaluate changes in the age at menarche in Asian populations.

    STUDY DESIGN: Retrospective cohort study.

    METHODS: We included 548,830 women from six countries in Asia. The data were sourced from 20 cohorts participating in the Asia Cohort Consortium (ACC) and two additional cohort studies: Japan Multi-institutional Collaborative Cohorts (J-MICC), and Japan Nurse Health Study (JNHS) with data on age at menarche. Joinpoint regression was used to evaluate changes in age at menarche by birth year and by country.

    RESULTS: The study includes data from cohorts in six Asian countries namely, China, Iran, Japan, Korea, Malaysia and Singapore. Birth cohorts ranged from 1873 to 1995. The mean age of menarche was 14.0 years with a standard deviation (SD) of 1.4 years, ranged from 12.6 to 15.5 years. Over 100 years age at menarche showed an overall decrease in all six countries. China showed a mixed pattern of decrease, increase, and subsequent decrease from 1926 to 1960. Iran and Malaysia experienced a sharp decline between about 1985 and 1990, with APC values of -4.48 and -1.24, respectively, while Japan, South Korea, and Singapore exhibited a nearly linear decline since the 1980s, notably with an APC of -3.41 in Singapore from 1993 to 1995.

    CONCLUSIONS: Overall, we observed a declining age at menarche, while the pace of the change differed by country. Additional long-term observation is needed to examine the contributing factors of differences in trend across Asian countries. The study could serve as a tool to strengthen global health campaigns.

  5. Shu X, Long J, Cai Q, Kweon SS, Choi JY, Kubo M, et al.
    Nat Commun, 2020 Mar 05;11(1):1217.
    PMID: 32139696 DOI: 10.1038/s41467-020-15046-w
    Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P 
  6. Ho WK, Tai MC, Dennis J, Shu X, Li J, Ho PJ, et al.
    Genet Med, 2022 Mar;24(3):586-600.
    PMID: 34906514 DOI: 10.1016/j.gim.2021.11.008
    PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.

    METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).

    RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.

    CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.

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