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| Name | Class |
|---|---|
| University of Oklahoma | OTHER |
| Rutgers University | OTHER |
| University of California, San Diego | OTHER |
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In this study the investigators will seek to improve our understanding of how positive and negative valence systems, cognition, and arousal/interoception are inter-related in disorders of mood, substance use, and eating behavior. The investigators will recruit 1000 individuals and use a wide range of assessment tools, neuroimaging measures, blood and microbiome collections and behavioral tasks to complete the baseline and follow-up study visits. Upon completion, the investigators aim to have robust and reliable dimensional measures that quantify these systems and a set of assessments that should be recommended as a clinical tool to enhance outcome prediction for the clinician and assist in determining who will likely benefit from what type of intervention.
Neuroscience has made tremendous progress in understanding the basic neural circuitry that underlies important processes such as attention, memory, and basic emotion processing. Yet, little progress has been made to utilize these insights to apply them to psychiatric populations in order to make clinically meaningful predictions. The connection between psychiatric disorders and their underlying neurobiology has been difficult to establish. The overarching theme of this study is to determine how biological and objective behavioral measures can contribute to improving assessment and treatment of psychiatric patients. The investigators will use the National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) framework as a heuristic approach that integrates neuroscience and psychopathology to study the positive and negative valence systems, cognition and arousal/interoception domains. Within this framework we will study a group of treatment seeking individuals with mental health conditions to determine how dysfunctions of affect, substance use, and eating behavior organize across different levels and whether these latent factors can be used to generate clinically useful prediction.
Using self-report, behavior, physiology, neural circuit, cell, molecule, and gene unit of analysis measures, the investigators propose to enroll 1000 individuals from four different cohorts over 5 years: (1) anxiety and/or depression; (2) eating problems; (3) substance use problems; and (4) healthy controls. Each individual will undergo a multi-level assessment that consists of (a) a standardized diagnostic assessment, (b) self-report questionnaires, (c) behavioral tasks, (d) physiological measurements, (e) structural and functional magnetic resonance imaging (fMRI) and EEG, (f) biomarker and microbiome assessments, (g) blood to derive induced pluripotent stem cells, (h) and genetic and epigenetic assessments. These individuals will be followed up for one year and will be re-assessed using a multi-domain assessment of functioning, which will include: (a) symptom severity and duration, (b) subjective well-being, (c) psychosocial function, (c) occupational function, (d) physical health, (e) utilization of mental health resources (treatment), and (f) compliance with treatment.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Depression and Anxiety Disorders | 350 subjects who screen positive for anxiety or depressive symptoms on the Patient Health Questionnaire (PHQ-9) ≥ 10 and/or Overall Anxiety Severity and Impairment Scale (OASIS) ≥ 8. Interventions: (1) standardized diagnostic assessment, (2) self-report questionnaires, (3) behavioral tasks, (4) physiological measurements, 5) structural and functional magnetic resonance imaging and EEG, (6) biomarker and microbiome assessments, (h) blood to derive induced pluripotent stem cells, (8) and genetic and epigenetic assessments. |
| |
| Eating Disorders | 350 subjects who screen positive for problems related to eating behavior on the Eating Disorder Screen (SCOFF), score ≥ 2. Interventions: (1) standardized diagnostic assessment, (2) self-report questionnaires, (3) behavioral tasks, (4) physiological measurements, 5) structural and functional magnetic resonance imaging and EEG, (6) biomarker and microbiome assessments, (h) blood to derive induced pluripotent stem cells, (8) and genetic and epigenetic assessments. |
| |
| Substance Use Disorders |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| standardized diagnostic assessment | Behavioral |
|
| Measure | Description | Time Frame |
|---|---|---|
| Change from Baseline in Clinical Diagnosis | Test the predictive effects of endophenotypes (genetic, imaging and behavioral factors) on clinical diagnosis at baseline compared to one year later using the Mini International Psychiatric Interview in patients and healthy controls | Baseline and 1 year |
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Inclusion Criteria:
Referred or seeking treatment, as defined by answering yes to "have you sought help for problems with":
Screened positive for problems in (1) as indicated by:
Have a body mass index between 17 to 38 kg/m²
Able to provide written informed consent.
Have sufficient proficiency in English language to understand and complete interviews, questionnaires, and all other study procedures.
Exclusion Criteria:
No telephone or easy access to telephone.
Has a history of unstable liver or renal insufficiency; glaucoma; significant and unstable cardiac, vascular, pulmonary, gastrointestinal, endocrine, neurologic, hematologic, rheumatologic, or metabolic disturbance; or any other condition that, in the opinion of the investigator, would make participation not be in the best interest (e.g., compromise the well-being) of the subject or that could prevent, limit, or confound the protocol-specified assessments.
A positive test for drugs of abuse, including alcohol (breath test), cocaine, marijuana, opiates, amphetamines, methamphetamines, phencyclidine, benzodiazepines, barbiturates, methadone, and oxycodone.
Has any of the following DSM-V disorders:
Moderate to severe traumatic brain injury or other neurocognitive disorder
Active suicidal ideation with intent or plan.
Change in the dose or prescription of a medication within the 6 weeks before enrolling in the study that could affect brain functioning
Prescription of a medication outside of the accepted range, as determined by the best clinical practices and current research.
Taking drugs that affect the fMRI hemodynamic response (e.g., methylphenidate, acetazolamide, excessive caffeine intake > 1000 mg/day)
MRI contraindications
Unwillingness or inability to complete any of the major aspects of the study protocol
Non-correctable vision or hearing problems
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Community Sample
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| Name | Affiliation | Role |
|---|---|---|
| Martin P Paulus, M.D. | Laureate Institute for Brain Research | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Laureate Institute for Brain Research | Tulsa | Oklahoma | 74136 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 20939653 | Background | Sanislow CA, Pine DS, Quinn KJ, Kozak MJ, Garvey MA, Heinssen RK, Wang PS, Cuthbert BN. Developing constructs for psychopathology research: research domain criteria. J Abnorm Psychol. 2010 Nov;119(4):631-9. doi: 10.1037/a0020909. | |
| 20595427 | Background | Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, Sanislow C, Wang P. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010 Jul;167(7):748-51. doi: 10.1176/appi.ajp.2010.09091379. No abstract available. |
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Whole Blood, Serum, Plasma, Microbiome
350 subjects who screen positive for problems related to substance use on the Drug Abuse Screening Test (DAST-10), score > 2.
Interventions: (1) standardized diagnostic assessment, (2) self-report questionnaires, (3) behavioral tasks, (4) physiological measurements, 5) structural and functional magnetic resonance imaging and EEG, (6) biomarker and microbiome assessments, (h) blood to derive induced pluripotent stem cells, (8) and genetic and epigenetic assessments.
|
| Healthy Controls | 150 subjects who do not screen positive for anxiety and depression symptoms or problems related to eating behavior and/or substance use. Interventions: (1) standardized diagnostic assessment, (2) self-report questionnaires, (3) behavioral tasks, (4) physiological measurements, 5) structural and functional magnetic resonance imaging and EEG, (6) biomarker and microbiome assessments, (h) blood to derive induced pluripotent stem cells, (8) and genetic and epigenetic assessments. |
|
| self-report questionnaires | Behavioral |
|
| behavioral tasks | Behavioral |
|
| physiological measurements | Other |
|
| structural and functional magnetic resonance imaging and EEG | Other |
|
| biomarker and microbiome assessments | Other |
|
| blood to derive induced pluripotent stem cells | Other |
|
| genetic and epigenetic assessments | Other |
|
| 37717543 | Derived | Park H, Forthman KL, Kuplicki R, Victor TA, Yeh HW, Thompson WK, Howlett JR, Guinjoan S, Paulus MP. Polygenic risk for neuroticism is associated with less efficient control in more difficult situations. Psychiatry Res Neuroimaging. 2023 Oct;335:111716. doi: 10.1016/j.pscychresns.2023.111716. Epub 2023 Sep 14. |
| 37178517 | Derived | Forthman KL, Kuplicki R, Yeh HW, Khalsa SS, Paulus MP, Guinjoan SM. Transdiagnostic behavioral and genetic contributors to repetitive negative thinking: A machine learning approach. J Psychiatr Res. 2023 Jun;162:207-213. doi: 10.1016/j.jpsychires.2023.05.039. Epub 2023 May 5. |
| 36965550 | Derived | Sanchez SM, Tsuchiyagaito A, Kuplicki R, Park H, Postolski I, Rohan M, Paulus MP, Guinjoan SM. Repetitive Negative Thinking-Specific and -Nonspecific White Matter Tracts Engaged by Historical Psychosurgical Targets for Depression. Biol Psychiatry. 2023 Oct 15;94(8):661-671. doi: 10.1016/j.biopsych.2023.03.012. Epub 2023 Mar 23. |
| 36270063 | Derived | Park H, Sanchez SM, Kuplicki R, Tsuchiyagaito A, Khalsa SS, Paulus MP, Guinjoan SM. Attenuated interoceptive processing in individuals with major depressive disorder and high repetitive negative thinking. J Psychiatr Res. 2022 Dec;156:237-244. doi: 10.1016/j.jpsychires.2022.10.020. Epub 2022 Oct 10. |
| 35679785 | Derived | Kirlic N, Kuplicki R, Touthang J, Cohen ZP, Stewart JL; Tulsa 1000 Investigators; Paulus MP, Aupperle RL. Behavioral and neural responses during fear conditioning and extinction in a large transdiagnostic sample. Neuroimage Clin. 2022;35:103060. doi: 10.1016/j.nicl.2022.103060. Epub 2022 May 25. |
| 35065290 | Derived | Park H, Kirlic N, Kuplicki R; Tulsa 1000 Investigators; Paulus M, Guinjoan S. Neural Processing Dysfunctions During Fear Learning but Not Reward-Related Processing Characterize Depressed Individuals With High Levels of Repetitive Negative Thinking. Biol Psychiatry Cogn Neurosci Neuroimaging. 2022 Jul;7(7):716-724. doi: 10.1016/j.bpsc.2022.01.002. Epub 2022 Jan 20. |
| 33508469 | Derived | Burrows K, Stewart JL, Kuplicki R, Figueroa-Hall L, Spechler PA, Zheng H, Guinjoan SM; Tulsa 1000 Investigators; Savitz JB, Kent Teague T, Paulus MP. Elevated peripheral inflammation is associated with attenuated striatal reward anticipation in major depressive disorder. Brain Behav Immun. 2021 Mar;93:214-225. doi: 10.1016/j.bbi.2021.01.016. Epub 2021 Jan 26. |
| 33503481 | Derived | White EJ, Kuplicki R, Stewart JL, Kirlic N, Yeh HW; T1000 Investigators; Paulus MP, Aupperle RL. Latent variables for region of interest activation during the monetary incentive delay task. Neuroimage. 2021 Apr 15;230:117796. doi: 10.1016/j.neuroimage.2021.117796. Epub 2021 Jan 24. |
| 33002704 | Derived | Spechler PA, Stewart JL, Kuplicki R, Paulus MP; Tulsa 1000 Investigators. Parsing impulsivity in individuals with anxiety and depression who use Cannabis. Drug Alcohol Depend. 2020 Dec 1;217:108289. doi: 10.1016/j.drugalcdep.2020.108289. Epub 2020 Sep 16. |
| 32107167 | Derived | Howlett JR, Thompson WK, Paulus MP. Computational Evidence for Underweighting of Current Error and Overestimation of Future Error in Anxious Individuals. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 Apr;5(4):412-419. doi: 10.1016/j.bpsc.2019.12.011. Epub 2019 Dec 24. |
| 32056939 | Derived | Howlett JR, Paulus MP. Where perception meets belief updating: Computational evidence for slower updating of visual expectations in anxious individuals. J Affect Disord. 2020 Apr 1;266:633-638. doi: 10.1016/j.jad.2020.02.012. Epub 2020 Feb 3. |
| 29371263 | Derived | Victor TA, Khalsa SS, Simmons WK, Feinstein JS, Savitz J, Aupperle RL, Yeh HW, Bodurka J, Paulus MP. Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample. BMJ Open. 2018 Jan 24;8(1):e016620. doi: 10.1136/bmjopen-2017-016620. |
| ID | Term |
|---|---|
| D003863 | Depression |
| D001008 | Anxiety Disorders |
| D001068 | Feeding and Eating Disorders |
| D019966 | Substance-Related Disorders |
| D001519 | Behavior |
| D000092862 | Psychological Well-Being |
| ID | Term |
|---|---|
| D001526 | Behavioral Symptoms |
| D001523 | Mental Disorders |
| D012817 | Signs and Symptoms, Digestive |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D064419 | Chemically-Induced Disorders |
| D010549 | Personal Satisfaction |
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| ID | Term |
|---|---|
| D015415 | Biomarkers |
| ID | Term |
|---|---|
| D001685 | Biological Factors |
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