Abstract

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
Volume74
DOIs
Publication statusPublished - Oct 1 2017

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Gene Expression Profiling
Benzodiazepines
Gene expression
Bioinformatics
Breast Neoplasms
Population
Computational Biology
Health insurance
Diazepam
Carcinogenesis
Medicine
Databases
Genes
Lorazepam
Propensity Score
Precision Medicine
Informatics
Atlases
Neoplasm Genes
National Health Programs

Keywords

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

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

Cite this

@article{70a6e820f17a4cc68722889e31e20a35,
title = "Benzodiazepines use and breast cancer risk: A population-based study and gene expression profiling evidence",
abstract = "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.",
keywords = "Benzodiazepines, Bioinformatics, Breast cancer, Gene profiling data, Observational health data, Pharmacoepidemiology, Precision medicine",
author = "Usman Iqbal and Chang, {Tzu Hao} and Nguyen, {Phung Anh} and Shabbir Syed-Abdul and Yang, {Hsuan Chia} and Huang, {Chih Wei} and Suleman Atique and Yang, {Wei Chung} and Max Moldovan and Jian, {Wen Shan} and Hsu, {Min Huei} and Yun Yen and Li, {Yu Chuan (Jack)}",
year = "2017",
month = "10",
day = "1",
doi = "10.1016/j.jbi.2017.08.008",
language = "English",
volume = "74",
pages = "85--91",
journal = "Journal of Biomedical Informatics",
issn = "1532-0464",
publisher = "Academic Press Inc.",

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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)

PY - 2017/10/1

Y1 - 2017/10/1

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

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JO - Journal of Biomedical Informatics

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