Mamoun Michael, Bergen Andrew W, Shieh Jennifer, Wiggins Anna, Brody Arthur L
Departments of Research and Psychiatry, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
Center for Health Sciences, SRI International, Menlo Park, CA, USA.
CNS Drugs. 2015 May;29(5):359-69. doi: 10.1007/s40263-015-0243-1.
For the past 30 years, research examining predictors of successful smoking cessation treatment response has focused primarily on clinical variables, such as levels of tobacco dependence, craving, and self-efficacy. However, recent research has begun to determine biomarkers (such as genotype, nicotine and metabolite levels, and brain imaging findings) that may have utility in predicting smoking cessation. For genotype, genes associated with nicotinic acetylcholine receptors (nAChRs) and related proteins have been found to predict response to first-line medications (e.g. nicotine replacement therapy [NRT], bupropion, or varenicline) or quitting over time without a controlled treatment trial. For nicotine and metabolite levels, function of the cytochrome P450 2A6 liver enzyme, which can be assessed with the nicotine metabolite ratio or via genotype, has been found to predict response, with slow nicotine metabolizers having less severe nicotine dependence and a greater likelihood of quitting with NRT than normal metabolizers. For brain imaging, decreased activation of brain regions associated with emotion regulation and increased connectivity in emotion regulation networks, increased responsiveness to pleasant cues, and altered activation with the Stroop effect have been found in smokers who quit with the first-line medications listed above or counseling. In addition, our group recently demonstrated that lower pre-treatment brain nAChR density is associated with a greater chance of quitting smoking with NRT or placebo. Several of these studies found that specific biomarkers may provide additional information for predicting response beyond subjective symptom or rating scale measures, thereby giving an initial indication that biomarkers may, in the future, be useful for guiding smoking cessation treatment intensity, duration, and type.
在过去30年里，研究戒烟治疗成功反应预测因素的研究主要集中在临床变量上，如烟草依赖程度、渴望程度和自我效能感。然而，最近的研究已开始确定可能有助于预测戒烟情况的生物标志物（如基因型、尼古丁和代谢物水平以及脑成像结果）。对于基因型，已发现与烟碱型乙酰胆碱受体（nAChRs）及相关蛋白有关的基因可预测对一线药物（如尼古丁替代疗法[NRT]、安非他酮或伐尼克兰）的反应，或在未经对照治疗试验的情况下随时间推移戒烟的情况。对于尼古丁和代谢物水平，可通过尼古丁代谢物比率或基因型评估的细胞色素P450 2A6肝酶功能已被发现可预测反应，尼古丁代谢缓慢者的尼古丁依赖程度较轻，与正常代谢者相比，使用NRT戒烟的可能性更大。对于脑成像，在通过上述一线药物或咨询戒烟的吸烟者中，发现与情绪调节相关的脑区激活减少、情绪调节网络中的连通性增加、对愉快线索的反应性增强以及在Stroop效应下激活发生改变。此外，我们小组最近证明，治疗前较低的脑nAChR密度与使用NRT或安慰剂戒烟的可能性更大有关。这些研究中有几项发现，特定的生物标志物可能为预测反应提供主观症状或评分量表测量之外更多的信息，从而初步表明生物标志物未来可能有助于指导戒烟治疗的强度、持续时间和类型。
