TY - JOUR
T1 - Benzodiazepines use and breast cancer risk
T2 - A population-based study and gene expression profiling evidence
AU - Iqbal, Usman
AU - Chang, Tzu Hao
AU - Nguyen, Phung Anh
AU - Syed-Abdul, Shabbir
AU - Yang, Hsuan Chia
AU - Huang, Chih Wei
AU - Atique, Suleman
AU - Yang, Wei Chung
AU - Moldovan, Max
AU - Jian, Wen Shan
AU - Hsu, Min Huei
AU - Yen, Yun
AU - Li, Yu Chuan (Jack)
N1 - Publisher Copyright:
© 2017
PY - 2017/10
Y1 - 2017/10
N2 - The aim of this study was to investigate whether long-term use of Benzodiazepines (BZDs) is associated with breast cancer risk through the combination of population-based observational and gene expression profiling evidence. We conducted a population-based case-control study by using 1998 to 2009 year Taiwan National Health Insurance Research Database and investigated the association between BZDs use and breast cancer risk. We selected subjects age of >20 years old and six eligible controls matched for age, sex and the index date (i.e., free of any cancer at the case diagnosis date) by using propensity scores. A bioinformatics analysis approach was also performed for the identification of oncogenesis effects of BZDs on breast cancer. We used breast cancer gene expression data from the Cancer Genome Atlas and perturbagen signatures of BZDs from the Library of Integrated Cellular Signatures database in order to identify the oncogenesis effects of BZDs on breast cancer. We found evidence of increased breast cancer risk for diazepam (OR, 1.16; 95%CI, 0.95–1.42; connectivity score [CS], 0.3016), zolpidem (OR, 1.11; 95%CI, 0.95–1.30; CS, 0.2738), but not for lorazepam (OR, 1.04; 95%CI, 0.89–1.23; CS, -0.2952) consistently in both methods. The finding for alparazolam was contradictory from the two methods. Diazepam and zolpidem trends showed association, although not statistically significant, with breast cancer risk in both epidemiological and bioinformatics analyses outcomes. The methodological value of our study is in introducing the way of combining epidemiological and bioinformatics approaches in order to answer a common scientific question. Combining the two approaches would be a substantial step towards uncovering, validation and further application of previously unknown scientific knowledge to the emerging field of precision medicine informatics.
AB - The aim of this study was to investigate whether long-term use of Benzodiazepines (BZDs) is associated with breast cancer risk through the combination of population-based observational and gene expression profiling evidence. We conducted a population-based case-control study by using 1998 to 2009 year Taiwan National Health Insurance Research Database and investigated the association between BZDs use and breast cancer risk. We selected subjects age of >20 years old and six eligible controls matched for age, sex and the index date (i.e., free of any cancer at the case diagnosis date) by using propensity scores. A bioinformatics analysis approach was also performed for the identification of oncogenesis effects of BZDs on breast cancer. We used breast cancer gene expression data from the Cancer Genome Atlas and perturbagen signatures of BZDs from the Library of Integrated Cellular Signatures database in order to identify the oncogenesis effects of BZDs on breast cancer. We found evidence of increased breast cancer risk for diazepam (OR, 1.16; 95%CI, 0.95–1.42; connectivity score [CS], 0.3016), zolpidem (OR, 1.11; 95%CI, 0.95–1.30; CS, 0.2738), but not for lorazepam (OR, 1.04; 95%CI, 0.89–1.23; CS, -0.2952) consistently in both methods. The finding for alparazolam was contradictory from the two methods. Diazepam and zolpidem trends showed association, although not statistically significant, with breast cancer risk in both epidemiological and bioinformatics analyses outcomes. The methodological value of our study is in introducing the way of combining epidemiological and bioinformatics approaches in order to answer a common scientific question. Combining the two approaches would be a substantial step towards uncovering, validation and further application of previously unknown scientific knowledge to the emerging field of precision medicine informatics.
KW - Benzodiazepines
KW - Bioinformatics
KW - Breast cancer
KW - Gene profiling data
KW - Observational health data
KW - Pharmacoepidemiology
KW - Precision medicine
UR - http://www.scopus.com/inward/record.url?scp=85029383035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85029383035&partnerID=8YFLogxK
U2 - 10.1016/j.jbi.2017.08.008
DO - 10.1016/j.jbi.2017.08.008
M3 - Article
C2 - 28851658
AN - SCOPUS:85029383035
SN - 1532-0464
VL - 74
SP - 85
EP - 91
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
ER -