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Genetics of Opioid Dependence: A Review of the Genetic Contribution to Opioid Dependence

Overview of attention for article published in Current Psychiatry Research and Reviews, May 2014
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Title
Genetics of Opioid Dependence: A Review of the Genetic Contribution to Opioid Dependence
Published in
Current Psychiatry Research and Reviews, May 2014
DOI 10.2174/1573400510666140320000928
Pubmed ID
Authors

Chetna J Mistry, Monica Bawor, Dipika Desai, David C Marsh, Zainab Samaan

Abstract

This narrative review aims to provide an overview of the impact of opioid dependence and the contribution of genetics to opioid dependence. Epidemiological data demonstrate that opioid dependence is a global trend with far-reaching effects on the social, economic, and health care systems. A review of classical genetic studies of opioid use suggests significant heritability of drug use behavior, however the evidence from molecular genetic studies is inconclusive. Nonetheless, certain genetic variants are important to consider given their role in the pathophysiology of addictive behavior. We undertook a literature review to identify the current state of knowledge regarding the role of genes in opioid dependence. Determining the association of genetic markers could change the current understanding of the various factors contributing to opioid dependence and therefore may improve recognition of individuals at risk for the disorder and prevention and treatment strategies.

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X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Unknown 167 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 28 17%
Researcher 26 15%
Student > Master 20 12%
Student > Ph. D. Student 19 11%
Other 12 7%
Other 24 14%
Unknown 40 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 15%
Medicine and Dentistry 24 14%
Psychology 16 9%
Neuroscience 11 7%
Agricultural and Biological Sciences 10 6%
Other 37 22%
Unknown 46 27%