The ReCoDe addiction research consortium: Losing and regaining control over drug intake-Findings and future perspectives.
addiction
alcohol
alternative rewards
ambulatory assessment (AA)
animal models
behavioural control
cocaine
cognitive control
computational models
craving
decision‐making
ecological momentary assessment (EMA)
habit formation
relapse
tobacco
Journal
Addiction biology
ISSN: 1369-1600
Titre abrégé: Addict Biol
Pays: United States
ID NLM: 9604935
Informations de publication
Date de publication:
Jul 2024
Jul 2024
Historique:
revised:
15
05
2024
received:
05
03
2024
accepted:
21
05
2024
medline:
1
7
2024
pubmed:
1
7
2024
entrez:
1
7
2024
Statut:
ppublish
Résumé
Substance use disorders (SUDs) are seen as a continuum ranging from goal-directed and hedonic drug use to loss of control over drug intake with aversive consequences for mental and physical health and social functioning. The main goals of our interdisciplinary German collaborative research centre on Losing and Regaining Control over Drug Intake (ReCoDe) are (i) to study triggers (drug cues, stressors, drug priming) and modifying factors (age, gender, physical activity, cognitive functions, childhood adversity, social factors, such as loneliness and social contact/interaction) that longitudinally modulate the trajectories of losing and regaining control over drug consumption under real-life conditions. (ii) To study underlying behavioural, cognitive and neurobiological mechanisms of disease trajectories and drug-related behaviours and (iii) to provide non-invasive mechanism-based interventions. These goals are achieved by: (A) using innovative mHealth (mobile health) tools to longitudinally monitor the effects of triggers and modifying factors on drug consumption patterns in real life in a cohort of 900 patients with alcohol use disorder. This approach will be complemented by animal models of addiction with 24/7 automated behavioural monitoring across an entire disease trajectory; i.e. from a naïve state to a drug-taking state to an addiction or resilience-like state. (B) The identification and, if applicable, computational modelling of key molecular, neurobiological and psychological mechanisms (e.g., reduced cognitive flexibility) mediating the effects of such triggers and modifying factors on disease trajectories. (C) Developing and testing non-invasive interventions (e.g., Just-In-Time-Adaptive-Interventions (JITAIs), various non-invasive brain stimulations (NIBS), individualized physical activity) that specifically target the underlying mechanisms for regaining control over drug intake. Here, we will report on the most important results of the first funding period and outline our future research strategy.
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
e13419Subventions
Organisme : German Research Foundation
Informations de copyright
© 2024 The Author(s). Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.
Références
Heinz A, Kiefer F, Smolka MN, et al. Addiction research consortium: losing and regaining control over drug intake (ReCoDe)—from trajectories to mechanisms and interventions. Addict Biol. 2020;25(2):e12866. doi:10.1111/adb.12866
Reichert M, Gan G, Renz M, et al. Ambulatory assessment for precision psychiatry: foundations, current developments and future avenues. Exp Neurol. 2021;345:113807. doi:10.1016/j.expneurol.2021.113807
Heinz A, Beck A, Halil MG, Pilhatsch M, Smolka MN, Liu S. Addiction as learned behavior patterns. J Clin Med. 2019;8(8):1086. doi:10.3390/jcm8081086
Spanagel R. Animal models of addiction. Dialogues Clin Neurosci. 2017;19(3):247‐258. doi:10.31887/DCNS.2017.19.3/rspanagel
Foo JC, Meinhardt MW, Skorodumov I, Spanagel R. Alcohol solution strength preference predicts compulsive‐like drinking behavior in rats. Alcohol Clin Exp Res. 2022;46(9):1710‐1719. doi:10.1111/acer.14910
Foo JC, Noori HR, Yamaguchi I, et al. Dynamical state transitions into addictive behaviour and their early‐warning signals. Proc: Biol Sci. 2017;284(1860):20170882. doi:10.1098/rspb.2017.0882
Durstewitz D, Koppe G, Meyer‐Lindenberg A. Deep neural networks in psychiatry. Mol Psychiatry. 2019;24(11):1583‐1598. doi:10.1038/s41380‐019‐0365‐9
Yücel M, Oldenhof E, Ahmed SH, et al. A transdiagnostic dimensional approach towards a neuropsychological assessment for addiction: an international Delphi consensus study. Addiction. 2019;114(6):1095‐1109. doi:10.1111/add.14424
Heinz A, Gutwinski S, Bahr NS, Spanagel R, Di Chiara G. Does compulsion explain addiction? Addict Biol. 2024;29(4):e13379. doi:10.1111/adb.13379
Hagman BT, Falk D, Litten R, Koob GF. Defining recovery from alcohol use disorder: development of an NIAAA research definition. Am J Psychiatry. 2022;179(11):807‐813. doi:10.1176/appi.ajp.21090963
Witkiewitz K, Pfund RA, Tucker JA. Mechanisms of behavior change in substance use disorder with and without formal treatment. Annu Rev Clin Psychol. 2022;18(1):497‐525. doi:10.1146/annurev‐clinpsy‐072720‐014802
Ersche KD, Gillan CM, Jones PS, et al. Carrots and sticks fail to change behavior in cocaine addiction. Science. 2016;352(6292):1468‐1471. doi:10.1126/science.aaf3700
Benedyk A, Reichert M, Giurgiu M, et al. Real‐life behavioral and neural circuit markers of physical activity as a compensatory mechanism for social isolation. Nat Mental Health. 2024;2(3):337‐342. doi:10.1038/s44220‐024‐00204‐6
Deeken F, Reichert M, Zech H, et al. Patterns of alcohol consumption among individuals with alcohol use disorder during the COVID‐19 pandemic and lockdowns in Germany. JAMA Netw Open. 2022;5(8):e2224641. doi:10.1001/jamanetworkopen.2022.24641
Gan G, Ma R, Reichert M, et al. Neural correlates of affective benefit from real‐life social contact and implications for psychiatric resilience. JAMA Psychiatry. 2021;78(7):790‐792. doi:10.1001/jamapsychiatry.2021.0560
Tost H, Reichert M, Braun U, et al. Neural correlates of individual differences in affective benefit of real‐life urban green space exposure. Nat Neurosci. 2019;22(9):1389‐1393. doi:10.1038/s41593‐019‐0451‐y
Zech HG, Reichert M, Ebner‐Priemer UW, et al. Mobile data collection of cognitive‐behavioral tasks in substance use disorders: where are we now? Neuropsychobiology. 2022;29(5):1‐13. doi:10.1159/000523697
Zech H, Waltmann M, Lee Y, et al. Measuring self‐regulation in everyday life: reliability and validity of smartphone‐based experiments in alcohol use disorder. Behav Res Methods. 2023;55(8):4329‐4342. doi:10.3758/s13428‐022‐02019‐8
Eldar E, Roth C, Dayan P, Dolan RJ. Decodability of reward learning signals predicts mood fluctuations. Curr Biol. 2018;28(9):1433‐1439.e7. doi:10.1016/j.cub.2018.03.038
Thome J, Pinger M, Halli P, et al. A model guided approach to evoke homogeneous behavior during temporal reward and loss discounting. Front Psych. 2022;13:846119. doi:10.3389/fpsyt.2022.846119
Thome J, Pinger M, Durstewitz D, Sommer WH, Kirsch P, Koppe G. Model‐based experimental manipulation of probabilistic behavior in interpretable behavioral latent variable models. Front Neurosci. 2023;16:1077735. doi:10.3389/fnins.2022.1077735
Spanagel R. Ten points to improve reproducibility and translation of animal research. Front Behav Neurosci. 2022;16:869511. doi:10.3389/fnbeh.2022.869511
Deeken F, Banaschewski T, Kluge U, Rapp MA. Risk and protective factors for alcohol use disorders across the lifespan. Curr Addict Rep. 2020;7(3):245‐251. doi:10.1007/s40429‐020‐00313‐z
Henssler J, Stock F, van Bohemen J, Walter H, Heinz A, Brandt L. Mental health effects of infection containment strategies: quarantine and isolation—a systematic review and meta‐analysis. Eur Arch Psychiatry Clin Neurosci. 2021;271(2):223‐234. doi:10.1007/s00406‐020‐01196‐x
Jones EAK, Mitra AK, Bhuiyan AR. Impact of COVID‐19 on mental health in adolescents: a systematic review. Int J Environ Res Public Health. 2021;18(5):2470. doi:10.3390/ijerph18052470
Acuff SF, Strickland JC, Tucker JA, Murphy JG. Changes in alcohol use during COVID‐19 and associations with contextual and individual difference variables: a systematic review and meta‐analysis. Psychol Addict Behav. 2022;36(1):1‐19. doi:10.1037/adb0000796
Friske MM, Spanagel R. Chronic alcohol consumption and COVID‐19 infection risk: a narrative review. Alcohol Clin Exp Res (Hoboken). 2023;47(4):629‐639. doi:10.1111/acer.15041
Kim JU, Majid A, Judge R, et al. Effect of COVID‐19 lockdown on alcohol consumption in patients with pre‐existing alcohol use disorder. Lancet Gastroenterol Hepatol. 2020;5(10):886‐887. doi:10.1016/S2468‐1253(20)30251‐X
Meinhardt MW, Hansson AC, Perreau‐Lenz S, et al. Rescue of infralimbic mGluR2 deficit restores control over drug‐seeking behavior in alcohol dependence. J Neurosci. 2013;33(7):2794‐2806. doi:10.1523/JNEUROSCI.4062‐12.2013
Meinhardt MW, Pfarr S, Fouquet G, et al. Psilocybin targets a common molecular mechanism for cognitive impairment and increased craving in alcoholism. Sci Adv. 2021;7(47):eabh2399. doi:10.1126/sciadv.abh2399
Domanegg K, Sommer WH, Meinhardt MW. Psychedelic targeting of metabotropic glutamate receptor 2 and its implications for the treatment of alcoholism. Cells. 2023;12(6):963. doi:10.3390/cells12060963
Vengeliene V, Spanagel R. mGlu2 mechanism‐based interventions to treat alcohol relapse. Front Pharmacol. 2022;13:985954. doi:10.3389/fphar.2022.985954
Ghin F, Beste C, Stock AK. Neurobiological mechanisms of control in alcohol use disorder—moving towards mechanism‐based non‐invasive brain stimulation treatments. Neurosci Biobehav Rev. 2022;133:104508. doi:10.1016/j.neubiorev.2021.12.031
Nasr K, Haslacher D, Dayan E, Censor N, Cohen LG, Soekadar SR. Breaking the boundaries of interacting with the human brain using adaptive closed‐loop stimulation. Prog Neurobiol. 2022;216:102311. doi:10.1016/j.pneurobio.2022.102311
Weiss F, Zhang J, Aslan A, Kirsch P, Gerchen MF. Feasibility of training the dorsolateral prefrontal‐striatal network by real‐time fMRI neurofeedback. Sci Rep. 2022;12(1):1669. doi:10.1038/s41598‐022‐05675‐0
Nardo T, Batchelor J, Berry J, Francis H, Jafar D, Borchard T. Cognitive remediation as an adjunct treatment for substance use disorders: a systematic review. Neuropsychol Rev. 2022;32(1):161‐191. doi:10.1007/s11065‐021‐09506‐3
Atherton M, Zhuang J, Bart WM, Hu X, He S. A functional MRI study of high‐level cognition. I. The game of chess. Brain Res Cogn Brain Res. 2013;16(1):26‐31. doi:10.1016/s0926‐6410(02)00207‐0
Gerhardt S, Lex G, Holzammer J, Karl D, Wieland A, Schmitt R, Recuero AJ, Montero JA, Weber T, Vollstädt‐Klein S (2022) Effects of chess‐based cognitive remediation training as therapy add‐on in alcohol and tobacco use disorders: protocol of a randomised, controlled clinical fMRI trial. BMJ Open 2022 12(9):e057707. 10.1136/bmjopen‐2021‐057707.
Bach P, Zaiser J, Zimmermann S, et al. Stress‐induced sensitization of insula activation predicts alcohol craving and alcohol use in alcohol use disorder. Biol Psychiatry. 2024;95(3):245‐255. doi:10.1016/j.biopsych.2023.08.024
Hoffmann S, Gerhardt S, Mühle C, et al. Associations of menstrual cycle and progesterone‐to‐estradiol ratio with alcohol consumption in alcohol use disorder: a sex‐separated multicenter longitudinal study. Am J Psychiatry. 2024;181(5):445‐456. doi:10.1176/appi.ajp.20230027
Hildebrandt MK, Schwarz K, Dieterich R, Endrass T. Dissociating the link of neural correlates of inhibition to the degree of substance use and substance‐related problems: a preregistered, multimodal, combined cross‐sectional and longitudinal study. Biol Psychiatry. 2023;94(11):898‐905. doi:10.1016/j.biopsych.2023.06.017
Chen H, Mojtahedzadeh N, Belanger MJ, et al. Model‐based and model‐free control predicts alcohol consumption developmental trajectory in young adults: a 3‐year prospective study. Biol Psychiatry. 2021;89(10):980‐989. doi:10.1016/j.biopsych.2021.01.009
Garbusow M, Schad DJ, Sebold M, et al. Pavlovian‐to‐instrumental transfer effects in the nucleus accumbens relate to relapse in alcohol dependence. Addict Biol. 2016;21:719‐731. doi:10.1111/adb.12243
Rane RP, de Man EF, Kim J, et al. Structural differences in adolescent brains can predict alcohol misuse. Elife. 2022;11:e77545. doi:10.7554/eLife.77545
Hasanpour M, Mitricheva E, Logothetis N, Noori HR. Intensive longitudinal characterization of multidimensional biobehavioral dynamics in laboratory rats. Cell Rep. 2021;13(2):108987. doi:10.1016/j.celrep.2021.108987
Durstewitz D, Koppe G, Thurm MI. Reconstructing computational system dynamics from neural data with recurrent neural networks. Nat Rev Neurosci. 2023;24(11):693‐710. doi:10.1038/s41583‐023‐00740‐7
Holz NE, Berhe O, Sacu S, et al. Early social adversity, altered brain functional connectivity, and mental health. Biol Psychiatry. 2023;93(5):430‐441. doi:10.1016/j.biopsych.2022.10.019
Giannone F, Ebrahimi C, Endrass T, Hansson AC, Schlagenhauf F, Sommer WH (2024) Bad habits – good goals? Meta‐analysis and translation of the habit construct to alcoholism. Transl Psychiatry (in press).
Doñamayor N, Ebrahimi C, Arndt V, Weiss F, Schlagenhauf F, Endrass T. Goal‐directed and habitual control in substance use: state of the art and future directions. Neuropsychobiology. 2022;81(5):403‐417. doi:10.1159/000527663
Zhang Y, Sui X, Pan F, Yu K, Li K, Tian S, Erdengasileng A, Han Q, Wang W, Wang J, Wang J, Sun D, Chung H, Zhou J, Zhou E, Lee B, Zhang P, Qiu X, Zhao T, Zhang J (2023) BioKG: a comprehensive, large‐scale biomedical knowledge graph for AI‐powered, data‐driven biomedical research. bioRxiv 10.1101/2023.10.13.562216.
Calleja‐Conde J, Morales‐García JA, Echeverry‐Alzate V, Bühler KM, Giné E, López‐Moreno JA. Classic psychedelics and alcohol use disorders: a systematic review of human and animal studies. Addict Biol. 2022;27(6):e13229. doi:10.1111/adb.13229
Urban MM, Stingl MR, Meinhardt MW. Mini‐review: the neurobiology of treating substance use disorders with classical psychedelics. Front Neurosci. 2023;17:1156319. doi:10.3389/fnins.2023.1156319.eCollection
Reinwald JR, Schmitz CN, Skorodumov I, et al. Psilocybin‐induced default mode network hypoconnectivity is blunted in alcohol‐dependent rats. Transl Psychiatry. 2023;13(1):392. doi:10.1038/s41398‐023‐02690‐1
Yang L, Du Y, Yang W, Liu J. Machine learning with neuroimaging biomarkers: application in the diagnosis and prediction of drug addiction. Addict Biol. 2023;28(2):e13267. doi:10.1111/adb.13267
Mekonen T, Chan GCK, Connor J, Hall W, Hides L, Leung J. Treatment rates for alcohol use disorders: a systematic review and meta‐analysis. Addiction. 2021;116(10):2617‐2634. doi:10.1111/add.15357
Zillich L, Poisel E, Frank J, et al. Multi‐omics signatures of alcohol use disorder in the dorsal and ventral striatum. Transl Psychiatry. 2022;12(1):190. doi:10.1038/s41398‐022‐01959‐1
Spanagel R, Durstewitz D, Hansson A, et al. A systems medicine research approach for studying alcohol addiction. Addict Biol. 2013;18(6):883‐896. doi:10.1111/adb.12109
Juraeva D, Treutlein J, Scholz H, et al. XRCC5 as a risk gene for alcohol dependence: evidence from a genome‐wide gene‐set‐based analysis and follow‐up studies in drosophila and humans. Neuropsychopharmacology. 2015;40(2):361‐371. doi:10.1038/npp.2014.178
Knabbe J, Protzmann J, Schneider N, et al. Single‐dose ethanol intoxication causes acute and lasting neuronal changes in the brain. Proc Natl Acad Sci U S A. 2022;119(25):e2122477119. doi:10.1073/pnas.2122477119
Velo Escarcena L, Neufeld M, Rietschel M, Spanagel R, Scholz H. ERR and dPECR suggest a link between neuroprotection and the regulation of ethanol consumption preference. Front Psych. 2021;12:655816. doi:10.3389/fpsyt.2021.655816
Strech D, Dirnagl U. 3Rs missing: animal research without scientific value is unethical. BMJ Open Sci. 2019;3:e000035. doi:10.1136/bmjos‐2018‐000048
Collins FS, Tabak LA. Policy: NIH plans to enhance reproducibility. Nature. 2014;505(7485):612‐613. doi:10.1038/505612a
Meinhardt MW, Gerlach B, Spanagel R. Good practice guideline for preclinical alcohol research: the STRINGENCY framework. Curr Top Behav Neurosci. 2024. in press.
Potretzke S, Zhang Y, Li J, et al. Male‐selective effects of oxytocin agonism on alcohol intake: behavioral assessment in socially housed prairie voles and involvement of RAGE. Neuropsychopharmacology. 2023;48(6):920‐928. doi:10.1038/s41386‐022‐01490‐3
Bogenschutz MP, Ross S, Bhatt S, et al. Percentage of heavy drinking days following psilocybin‐assisted psychotherapy vs placebo in the treatment of adult patients with alcohol use disorder: a randomized clinical trial. JAMA Psychiatry. 2022;79(10):953‐962. doi:10.1001/jamapsychiatry.2022.2096