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Genome-Wide Association Study of Medication Adherence in Chronic Diseases in the Korean Population

  • Seo, Incheol (Department of Microbiology, Keimyung University School of Medicine) ;
  • Suh, Seong-Il (Department of Microbiology, Keimyung University School of Medicine) ;
  • Suh, Min-Ho (Department of Microbiology, Keimyung University School of Medicine) ;
  • Baek, Won-Ki (Department of Microbiology, Keimyung University School of Medicine)
  • Received : 2014.06.30
  • Accepted : 2014.07.20
  • Published : 2014.09.30

Abstract

Medication adherence is generally defined as the extent of voluntary cooperation of a patient in taking medicine as prescribed. Adherence to long-term treatment with chronic disease is essential for reducing disease comorbidity and mortality. However, medication non-adherence in chronic disease averages 50%. This study was conducted a genome-wide association study to identify the genetic basis of medication adherence. A total of 235 medication non-adherents and 1,067 medication adherents with hypertension or diabetes were used from the Korean Association Resource project data according to the self-reported treatment status of each chronic disease, respectively. We identified four single nucleotide polymorphisms with suggestive genome-wide association. The most significant single nucleotide polymorphism was rs6978712 (chromosome 7, $p=4.87{\times}10^{-7}$), which is located proximal to the GCC1 gene, which was previously implicated in decision-making capability in drug abusers. Two suggestive single nucleotide polymorphisms were in strong linkage disequilibrium ($r^2$ > 0.8) with rs6978712. Thus, in the aspect of decision-making in adherence behavior, the association between medication adherence and three loci proximal to the GCC1 gene seems worthy of further research. However, to overcome a few limitations in this study, defining the standardized phenotype criteria for self-reported adherence should be performed before replicating association studies.

Keywords

References

  1. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005;353:487-497. https://doi.org/10.1056/NEJMra050100
  2. Zwikker HE, van den Bemt BJ, Vriezekolk JE, van den Ende CH, van Dulmen S. Psychosocial predictors of non-adherence to chronic medication: systematic review of longitudinal studies. Patient Prefer Adherence 2014;8:519-563.
  3. Jin J, Sklar GE, Min Sen Oh V, Chuen Li S. Factors affecting therapeutic compliance: A review from the patient's perspective. Ther Clin Risk Manag 2008;4:269-286. https://doi.org/10.2147/TCRM.S1458
  4. World Health Organization. Adherence to long-term therapies: evidence for action. Geneva: World Health Organization, 2003. Accessed 2014 May 1. Available from: http://www.who.int/chp/knowledge/publications/adherence_full_report.pdf.
  5. McCrae RR, Costa PT Jr. Personality in Adulthood: A Five-Factor Theory Perspective. New York: Guilford Press, 2003.
  6. Jerant A, Chapman B, Duberstein P, Robbins J, Franks P. Personality and medication non-adherence among older adults enrolled in a six-year trial. Br J Health Psychol 2011;16(Pt 1): 151-169. https://doi.org/10.1348/135910710X524219
  7. Axelsson M, Brink E, Lundgren J, Lotvall J. The influence of personality traits on reported adherence to medication in individuals with chronic disease: an epidemiological study in West Sweden. PLoS One 2011;6:e18241. https://doi.org/10.1371/journal.pone.0018241
  8. Kim HN, Roh SJ, Sung YA, Chung HW, Lee JY, Cho J, et al. Genome-wide association study of the five-factor model of personality in young Korean women. J Hum Genet 2013;58: 667-674. https://doi.org/10.1038/jhg.2013.75
  9. Terracciano A, Sanna S, Uda M, Deiana B, Usala G, Busonero F, et al. Genome-wide association scan for five major dimensions of personality. Mol Psychiatry 2010;15:647-656. https://doi.org/10.1038/mp.2008.113
  10. Cho YS, Go MJ, Kim YJ, Heo JY, Oh JH, Ban HJ, et al. A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. Nat Genet 2009;41:527-534. https://doi.org/10.1038/ng.357
  11. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-575. https://doi.org/10.1086/519795
  12. Turner S. Qqman: Q-Q and manhattan plots for GWAS data. The Comprehensive R Archive Network, 2014. Accessed 2014 May 1. Available from: http://cran.r-project.org/web/packages/qqman/.
  13. Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 2010;26:2336-2337. https://doi.org/10.1093/bioinformatics/btq419
  14. Briesacher BA, Andrade SE, Fouayzi H, Chan KA. Comparison of drug adherence rates among patients with seven different medical conditions. Pharmacotherapy 2008;28:437-443. https://doi.org/10.1592/phco.28.4.437
  15. Lehrmann E, Colantuoni C, Deep-Soboslay A, Becker KG, Lowe R, Huestis MA, et al. Transcriptional changes common to human cocaine, cannabis and phencyclidine abuse. PLoS One 2006;1:e114. https://doi.org/10.1371/journal.pone.0000114
  16. Malhotra AK, Zhang JP, Lencz T. Pharmacogenetics in psychiatry: translating research into clinical practice. Mol Psychiatry 2012;17:760-769. https://doi.org/10.1038/mp.2011.146
  17. Bush WS, Moore JH. Chapter 11: Genome-wide association studies. PLoS Comput Biol 2012;8:e1002822. https://doi.org/10.1371/journal.pcbi.1002822
  18. Pearson TA, Manolio TA. How to interpret a genome-wide association study. JAMA 2008;299:1335-1344. https://doi.org/10.1001/jama.299.11.1335
  19. Horne R, Weinman J. Self-regulation and self-management in asthma: exploring the role of illness perceptions and treatment beliefs in explaining non-adherence to preventer medication. Psychol Health 2002;17:17-32. https://doi.org/10.1080/08870440290001502
  20. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich) 2008;10:348-354. https://doi.org/10.1111/j.1751-7176.2008.07572.x
  21. Kjer-Nielsen L, Teasdale RD, van Vliet C, Gleeson PA. A novel Golgilocalisation domain shared by a class of coiled-coil peripheral membrane proteins. Curr Biol 1999;9:385-388. https://doi.org/10.1016/S0960-9822(99)80168-7

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