Community Series in Neurobiological Biomarkers for Developing Novel Treatments of Substance and Non-Substance Addiction, volume II

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Community Series in Neurobiological Biomarkers for Developing Novel Treatments of Substance and Non-Substance Addiction, volume II is written by Yanhui Liao and published by Frontiers Media SA. It's available with International Standard Book Number or ISBN identification 2832522866 (ISBN 10) and 9782832522868 (ISBN 13).

This Research Topic is the second volume of the 'Community Series in Neurobiological Biomarkers for Developing Novel Treatments of Substance and Non-Substance Addiction'. Please see the first volume here. Many people suffer from substance (from nicotine or alcohol to heroin, methamphetamine, cocaine, etc) or non-substance (from gaming/gambling to shopping, internet, smartphone, etc) addiction. Both types of addiction are associated with severe health, economic and social consequences and are far too often result in both familial and personal tragedies. Unfortunately, current treatments are not very effective for either substance or non-substance addiction so novel treatments are desperately needed. For example, for nicotine addiction, despite very well-documented health risks of cigarette smoking and its economic and societal costs, globally, more than 30% of males still smoke, and although many smokers desire to quit, only approximately 5-30% will achieve abstinence with 6 months or more of the best available current treatments. And the story for nicotine addiction is far from unique, presenting a huge challenge for the entire addiction field. Therefore, there is a vital need to improve outcomes for the treatment of both substance and non-substance addictions. Recent work exploring neurobiological mechanisms of the treatment response at the molecular, cellular and systems levels with a broad range of technologies, such as Magnetic Resonance Imaging (MRI), genetics and genomics, have opened new avenues for developing novel treatments through the detection of neurobiological biomarkers predicting efficacious outcomes in addicted patients.