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. 2024 Apr 1;81(4):414-425.
doi: 10.1001/jamapsychiatry.2023.5483.

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review

Addiction Cue-Reactivity Initiative (ACRI) Network; Arshiya Sangchooli  1 , Mehran Zare-Bidoky  2   3 , Ali Fathi Jouzdani  3 , Joseph Schacht  4 , James M Bjork  5 , Eric D Claus  6 , James J Prisciandaro  7 , Stephen J Wilson  8 , Torsten Wüstenberg  9 , Stéphane Potvin  10 , Pooria Ahmadi  11 , Patrick Bach  12 , Alex Baldacchino  13 , Anne Beck  14   15 , Kathleen T Brady  7 , Judson A Brewer  16 , Anna Rose Childress  17 , Kelly E Courtney  18 , Mohsen Ebrahimi  3 , Francesca M Filbey  19 , Hugh Garavan  20 , Dara G Ghahremani  21 , Rita Z Goldstein  22 , Anneke E Goudriaan  23   24 , Erica N Grodin  21 , Colleen A Hanlon  25   26 , Amelie Haugg  27 , Markus Heilig  28 , Andreas Heinz  15 , Adrienn Holczer  29 , Ruth J Van Holst  30 , Jane E Joseph  31 , Anthony C Juliano  20 , Marc J Kaufman  32 , Falk Kiefer  12 , Arash Khojasteh Zonoozi  3 , Rayus T Kuplicki  33 , Marco Leyton  34 , Edythe D London  21 , Scott Mackey  20 , F Joseph McClernon  35 , William H Mellick  7 , Kirsten Morley  36 , Hamid R Noori  37 , Mohammad Ali Oghabian  38 , Jason A Oliver  39 , Max Owens  20 , Martin P Paulus  33 , Irene Perini  28 , Parnian Rafei  3 , Lara A Ray  21 , Rajita Sinha  40 , Michael N Smolka  41 , Ghazaleh Soleimani  2 , Rainer Spanagel  42 , Vaughn R Steele  40 , Susan F Tapert  18 , Sabine Vollstädt-Klein  12 , Reagan R Wetherill  17 , Katie Witkiewitz  43 , Kai Yuan  44 , Xiaochu Zhang  45 , Antonio Verdejo-Garcia  46 , Marc N Potenza  41 , Amy C Janes  47 , Hedy Kober  40 , Anna Zilverstand  2 , Hamed Ekhtiari  2   33
Affiliations

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review

Addiction Cue-Reactivity Initiative (ACRI) Network et al. JAMA Psychiatry. .

Abstract

Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers.

Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts.

Evidence review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders.

Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes.

Conclusions and relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.

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Conflict of interest statement

Dr Schacht reported nonfinancial support from Bausch Health outside the submitted work. Dr Bach reported grants from German Research Foundation and German Ministry of Science and Education outside the submitted work. Dr Childress reported grants from the National Institute on Drug Abuse during the conduct of the study. Dr Filbey reported grants from the National Institutes of Health during the conduct of the study. Dr Hanlon reported owning stock in BrainsWay outside the submitted work. Dr Heilig reported grants and materials from BrainsWay and Janssen as well as personal fees from Aelis Farma, Indivior, and Camurus outside the submitted work. Dr Joseph reported grants from the National Institute on Drug Abuse during the conduct of the study. Dr Kaufman reported grants from the National Institutes of Health during the conduct of the study and has patent US9737562B2 issued and patent EU2931291B1 issued. Dr Oliver has patent 11308325 issued. Dr Steele reported grants from the National Institutes of Health during the conduct of the study. Dr Vollstädt-Klein reported grants from the Central Institute of Mental Health German Research Foundation during the conduct of the study. Dr Wetherill reported grants from the National Institutes of Health outside the submitted work. Dr Verdejo-Garcia reported personal fees from Servier, Elsevier, and Springer-Nature outside the submitted work. Dr Potenza reported grants from the National Institutes of Health during the conduct of the study; personal fees from Opiant Pharmaceuticals, Idorsia Pharmaceuticals, Baria-Tek, Game Day Data, and Addiction Policy Forum as well as research support from Mohegan Sun Casino, Children and Screens, and Connecticut Council on Problem Gambling outside the submitted work; patent application support from Novartis; and is a board member for the International Society of Addiction Medicine, Addiction Policy Forum, and National Council on Problem Gambling. No other disclosures were reported.

Figures

Figure 1.
Figure 1.
Task and Study Design Features of Functional Magnetic Resonance Imaging (fMRI) Drug Cue Reactivity (FDCR) Studies A, Number of time points in FDCR studies. A total 327 studies scanned participants at 1 time point, 81 studies at 2 time points, 6 studies at 3 time points, and 1 study at 4 time points. B, Boxplot representing the distribution of median interscan intervals (in days) for FDCR studies with more than 1 scanning session. Ten studies scanned individuals more than once within the same day (interval of 0 days). The midline indicates the median; the box, first and third quartile; whiskers, 1.5-fold the IQR; and points, individual data. C, Main FDCR task design type. D, Boxplot of the distribution of FDCR task durations. E, Paradigms and FDCR tasks of 52 studies in the database. F, FDCR studies by stimulus and substance/behavior type. The multiple category includes studies including more than 1 type of addictive substance/behavior. The other category includes inhalants and betel quid chewing.
Figure 2.
Figure 2.
Seven Functional Magnetic Resonance Imaging Drug Cue Reactivity (FDCR) Study Types A, FDCR studies that, by virtue of their study design, could theoretically support the development of each biomarker type by substance or behavior of interest. Note that all cells do not sum to 415 since some studies do not fit the biomarker framework and some studies fit multiple biomarker types. B, The number of significant and nonsignificant biomarker-related findings. The other category includes inhalants and betel quid chewing.
Figure 3.
Figure 3.
Functional Magnetic Resonance Imaging Drug Cue Reactivity (FDCR) Studies With an Intervention or Manipulation A, Types of interventional FDCR studies by year, including randomized clinical trials (RCTs), nonrandomized controlled trials, single-arm trials, and retrospective studies. B, FDCR studies intervention type. C, Role of FDCR in interventional studies. FDCR can be measured before an intervention to predict intervention results or measured after an intervention to assess impact with or without a comparison with baseline FDCR.
See this image and copyright information in PMC

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