Tobacco control in the United States is often presented as a major public health achievement. The claim is certainly justified: the percentage of adults who report regular smoking has been more than halved, from 42% to 19%, in the past 50 years. However, the pace of this decline has stalled in recent years and tobacco remains the leading preventable cause of morbidity and mortality in the United States, resulting in more than 440,000 deaths in the United States each year, with an additional 8.6 million people suffering from a serious smoking-related illness. The fact is that, despite the recognition of its harms, nicotine addiction is notoriously difficult to overcome. This suggests the need for increased efforts to identify those at risk for persistent smoking and to maximize successful quit attempts among current smokers. A new study explored the possibility that the strength of the connections between brain networks implicated in the evaluation of reward, the orchestration of high cognitive functions, and wakeful rest could constitute a useful biomarker of an individual’s state during nicotine withdrawal. To test this hypothesis, NIDA-supported researchers recently developed a new metric – Resource Allocation Index (RAI) – that reflects the combined strength of interactions between those networks. Using this metric, they found that the RAI was significantly lower in the abstinent compared to smoking satiety condition, a result that suggests a deficit in self control. More importantly, weaker inter-network connectivity predicted abstinence-induced craving. The development of this brain based signature may serve as a clinical biomarker for the identification of smokers who are most likely to respond to a particular treatment as well as for the screening of novel treatments for smoking cessation.
For a copy of the article abstract, go to:
https://archpsyc.jamanetwork.com/article.aspx?articleid=1840327