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AbstractIntroductionTobacco use disorder (TUD) is a major worldwide healthcare burden resulting in 7 million deaths annually. TUD has few approved cessation aids, all of which are associated a high rate of relapse within one year. Biomarkers of TUD severity, treatment response, and risk of relapse have high potential clinical utility to identify ideal responders and guide additional treatment resources.MethodsA MEDLINE search was performed using the terms biomarkers, dihydroxyacetone phosphate, bilirubin, inositol, cotinine, adrenocorticotropic hormone, cortisol, pituitary-adrenal system, homovanillic acid, dopamine, pro-opiomelanocortin, lipids, lipid metabolism all cross-referenced with tobacco-use disorder.ResultsThe search yielded 424 results, of which 57 met inclusion criteria. The most commonly studied biomarkers were those related to nicotine metabolism, the hypothalamic-pituitary-adrenal (HPA) axis, and cardiovascular (CVD) risk. Nicotine metabolism was most associated with severity of dependence and treatment response, where as HPA axis and CVD markers showed less robust associations with dependence and relapse risk.ConclusionsNicotine-metabolite ratio, cortisol, and atherogenicity markers appear to be the most promising lead biomarkers for further investigation, though the body of literature is still preliminary. Longitudinal, repeated-measures studies are required to determine the directionality of the observed associations and determine true predictive power of these biomarkers. Future studies should also endeavour to study populations with comorbid psychiatric disorders to determine differences in utility of certain biomarkers.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |