Literature DB >> 25734247

Biomarkers in substance use disorders.

Nora D Volkow1, George Koob1, Ruben Baler1.   

Abstract

The prevention and treatment of substance use disorders (SUDs), including addiction, would benefit from having better biomarkers for the classification of patients into categories that are reproducible and have predictive validity. Direct measurement of drugs or their metabolites in various body fluids constitutes a clinically valuable biomarker but one that can only be used to corroborate acute or relatively recent drug use. Thus, there is an urgent need for biomarkers that reflect chronic drug exposure as well as biomarkers that predict or correlate with disease trajectories and treatment responses. Advances in tools and technologies to investigate genetics, epigenetics and epitranscriptomics, and human brain function and neurochemistry (brain imaging tools including EEG) offer unprecedented opportunities for the development of such biomarkers. Progress in this area will not only enhance our ability to screen and treat patients with SUDs but also accelerate research on the neurobiological processes that underlie SUDs.

Entities:  

Keywords:  Addiction; EEG; MRI; PET; dopamine; endophenotype; epigenetics; genetics

Mesh:

Substances:

Year:  2015        PMID: 25734247     DOI: 10.1021/acschemneuro.5b00067

Source DB:  PubMed          Journal:  ACS Chem Neurosci        ISSN: 1948-7193            Impact factor:   4.418


  40 in total

1.  Subthalamic low-frequency oscillations predict vulnerability to cocaine addiction.

Authors:  Mickael Degoulet; Alix Tiran-Cappello; Etienne Combrisson; Christelle Baunez; Yann Pelloux
Journal:  Proc Natl Acad Sci U S A       Date:  2021-04-06       Impact factor: 11.205

2.  Challenges and promises for translating computational tools into clinical practice.

Authors:  Woo-Young Ahn; Jerome R Busemeyer
Journal:  Curr Opin Behav Sci       Date:  2016-10-01

3.  Intravenous cocaine self-administration in a panel of inbred mouse strains differing in acute locomotor sensitivity to cocaine.

Authors:  Amanda J Roberts; Linzy Casal; Salvador Huitron-Resendiz; Trey Thompson; Lisa M Tarantino
Journal:  Psychopharmacology (Berl)       Date:  2018-01-29       Impact factor: 4.530

4.  Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence.

Authors:  Woo-Young Ahn; Jasmin Vassileva
Journal:  Drug Alcohol Depend       Date:  2016-02-15       Impact factor: 4.492

5.  Evaluating the resource allocation index as a potential fMRI-based biomarker for substance use disorder.

Authors:  Mahdi Moradi; Hamed Ekhtiari; Rayus Kuplicki; Brett McKinney; Jennifer L Stewart; Teresa A Victor; Martin P Paulus
Journal:  Drug Alcohol Depend       Date:  2020-08-09       Impact factor: 4.492

6.  Interactive effects of age and recent substance use on striatal shape morphology at substance use disorder treatment entry.

Authors:  Marc L Copersino; Raihaan Patel; Jenessa S Price; Katherine Frost Visser; Gordana Vitaliano; Eric Plitman; Scott E Lukas; Roger D Weiss; Amy C Janes; M Mallar Chakravarty
Journal:  Drug Alcohol Depend       Date:  2019-11-09       Impact factor: 4.492

Review 7.  Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research.

Authors:  Zachary W Adams; Erin A McClure; Kevin M Gray; Carla Kmett Danielson; Frank A Treiber; Kenneth J Ruggiero
Journal:  J Psychiatr Res       Date:  2016-10-22       Impact factor: 4.791

Review 8.  Rodent models and mechanisms of voluntary binge-like ethanol consumption: Examples, opportunities, and strategies for preclinical research.

Authors:  Brandon M Fritz; Stephen L Boehm
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2015-06-02       Impact factor: 5.067

Review 9.  Event-Related Potentials as Biomarkers of Behavior Change Mechanisms in Substance Use Disorder Treatment.

Authors:  Rebecca J Houston; Nicolas J Schlienz
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2017-09-23

Review 10.  The Utility of Magnetic Resonance Spectroscopy for Understanding Substance Use Disorders: A Systematic Review of the Literature.

Authors:  Tracy Hellem; Xianfeng Shi; Gwen Latendresse; Perry F Renshaw
Journal:  J Am Psychiatr Nurses Assoc       Date:  2015 Jul-Aug       Impact factor: 2.385

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