Benzodiazepines use and breast cancer risk: A population-based study and gene expression profiling evidence

Usman Iqbal, Tzu Hao Chang, Phung Anh Nguyen, Shabbir Syed-Abdul, Hsuan Chia Yang, Chih Wei Huang, Suleman Atique, Wei Chung Yang, Max Moldovan, Wen Shan Jian, Min Huei Hsu, Yun Yen, Yu Chuan (Jack) Li

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)85-91
Number of pages7
JournalJournal of Biomedical Informatics
Publication statusPublished or Issued - Oct 2017


  • Benzodiazepines
  • Bioinformatics
  • Breast cancer
  • Gene profiling data
  • Observational health data
  • Pharmacoepidemiology
  • Precision medicine

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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