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This study aims to better understand the mechanisms of action of antidepressants, but also the neural correlates of motivation deficits. One hundred patients with a moderate to severe major depressive episode will be enrolled in this prospective multicenter study. The objective will be to predict the therapeutic response to two first-line antidepressants on the basis of an early neurocomputational assessment of motivation. Antidepressant treatment will be administered as monotherapy after randomization between two drugs: escitalopram and vortioxetine. Patients will undergo six visits and follow-up for one year. The investigators will combine computer modeling and functional MRI to identify motivational deficits and elucidate their brain correlates before initiation, after 7 days and after 6 months of treatment. 36 healthy volunteers will also be included to allow comparison with patients with depression. They will not receive any treatment.
One hundred patients with a moderate to severe major depressive episode will be enrolled in this prospective multicenter study. Six visits will be scheduled within a year:
V0 (inclusion visit): verification of inclusion and exclusion criteria, information, and consent.
V1 (before randomization - baseline state):
V2 (7 days after the beginning of the new antidepressant - 'early response visit'):
o Similar to V1.
V3 (28 days after the beginning of the new antidepressant - 'conventional response visit'):
V4 (6 months after the beginning of the new antidepressant - 'remission visit'):
V5 (one year after the beginning of the new antidepressant - 'functional remission visit'):
Clinical evaluation using validated questionnaires for the severity of depression, quality of life, anhedonia, apathy, and cognitive dysfunction.
36 healthy volunteers without a history of neurologic or psychiatric disorder, matched for age, gender, and education will be included. They will perform V0-V2 (without MRI and blood sample at V2). Healthy volunteers will not receive any treatment as part of the research.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| escitalopram strategy | Other | The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist. |
|
| vortioxetine strategy | Other | The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| escitalopram | Other | Patients will receive an antidepressant strategy : escitalopram. The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist. After 4 weeks, the strategy can be adapted by the refeering psychiatrist exactly as if the patient had not been included in the trial. |
| Measure | Description | Time Frame |
|---|---|---|
| Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the early changes (differences between V1 and V2) of the computational phenotype of depressed patients. | The therapeutic response will be measured with the Montgomery-Asberg Depression Rating Scale (MADRS). The MADRS is a 10- item scale widely used in depression research to assess the severity of depression. Response will be defined by a score divided by 2 compared to baseline MADRS score, while remission will be defined by a score < 7 (symptom absent) 28 days after the initiation of the antidepressant strategy. The "computational phenotype" is the outcome of the computationnal analysis of behavior. It is expressed in abstract unit. The change in computationnal phenotype between V1 and V2 will be entered in logistic regression aiming to predict clinical response at 28 days, measured with the MADRS score. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) and V3 (after 28 days of antidepressant) |
| Measure | Description | Time Frame |
|---|---|---|
| Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the early changes (differences between V1 and V2) of the neuro-computational phenotype of depressed patients | Same than outcome 1 but using brain imaging on top of behavior (neurocomputational modeling) to predict clinical response. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) and V3 (after 28 days of antidepressant) |
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Patients with major depressive disorder
Inclusion Criteria:
Exclusion Criteria:
Healthy volunteers
Inclusion Criteria:
- Valid health care insurance
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Fabien Vinckier | Contact | 0033683714083 | f.vinckier@ghu-paris.fr | |
| Claire Jaffré | Contact | 0033650557373 | claire.jaffre@yahoo.fr |
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Groupe hospitalo-universitaire de Grenoble Alpes | Not yet recruiting | La Tronche | Isère | 38700 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23879318 | Background | Bauer M, Pfennig A, Severus E, Whybrow PC, Angst J, Moller HJ; World Federation of Societies of Biological Psychiatry. Task Force on Unipolar Depressive Disorders. World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for biological treatment of unipolar depressive disorders, part 1: update 2013 on the acute and continuation treatment of unipolar depressive disorders. World J Biol Psychiatry. 2013 Jul;14(5):334-85. doi: 10.3109/15622975.2013.804195. Epub 2013 Jul 3. | |
| 19674794 |
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The data obtained from medical visits (clinical informations, biological assessments, cognitive data) and brain MRIs will be kept, coded and archived for a period of two years after the last publication of the research results or until the final research report is signed. These can be used later for collaborative research (academic and/or industrial partners) in the European Union (EU) and/or abroad exclusively for scientific purposes.
In case of transfer of the anonymized database resulting from this research abroad (outside the EU), the sponsor undertakes to ensure a level of security equivalent to French or European Union law.
The data obtained from medical visits (clinical informations, biological assessments, neurocognitive data)and brain MRIs will be kept, coded and archived for a period of two years after the last publication of the research results or until the final research report is signed.
The data can be used for collaborative research (academic and/or industrial partners) in the European Union (EU) and/or abroad exclusively for scientific purposes.
In case of transfer of the anonymized database resulting from this research abroad (outside the EU), the sponsor undertakes to ensure a level of security equivalent to French or European Union law.
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| ID | Term |
|---|---|
| D003865 | Depressive Disorder, Major |
| ID | Term |
|---|---|
| D003866 | Depressive Disorder |
| D019964 | Mood Disorders |
| D001523 | Mental Disorders |
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| ID | Term |
|---|---|
| D000089983 | Escitalopram |
| D000078784 | Vortioxetine |
| ID | Term |
|---|---|
| D011437 | Propylamines |
| D000588 | Amines |
| D009930 | Organic Chemicals |
| D009570 | Nitriles |
| D001572 |
Not provided
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Randomization and introduction of the new antidepressant will occur immediately after V1. Patients will receive an antidepressant as monotherapy after randomization between two strategies: escitalopram and vortioxetine. To maximize acceptability by referring psychiatrists, dosage and co-prescriptions will be at the discretion of the psychiatrist in charge, but the allocated treatment will not be changed for 4 weeks (until V3).
After 4 weeks, the treatment can be adapted by the refeering psychiatrist exactly as if the patient had not been included in the trial.
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|
| vortioxetine | Other | Patients will receive an antidepressant strategy : vortioxetine. The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist. After 4 weeks, the treatment strategy can be adapted by the refeering psychiatrist exactly as if the patient had not been included in the trial. |
|
| Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the initial (baseline state- V1) neuro-computational phenotype of depressed patients | Same than Outcome 2 but using only V1 instead of the change between V1 and V2 to predict clinical response. | Baseline state (before the start of antidepressant strategy), and V3 (after 28 days of antidepressant) |
| Prediction of long-term remission (V4) based on the early changes (differences between V1 and V2) of the neuro-computationnal phenotype of depressed patients | Same than Outcome 2 but to predict clinical remission at V4 instead of clinical response at V3. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant), V4 (6 months after the start of antidepressant) |
| Prediction functional remission (V5) based on the early changes (differences between V1 and V2) of the neuro-computationnal phenotype of depressed patients | Same than Outcome 2 but to predict functional remission at V5 instead of clinical response at V3. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant), V5 (1 year after the start of antidepressant) |
| Prediction of relapse at one year (V5) based on the computationnal phenotype of remitted patients at 6 months (V4). | Same than Outcome 1 but using computational phenotype at V4 to predict predict functional remission at V5. | V4 (6 months after the start of antidepressant), V5 (1 year after the start of antidepressant) |
| Description of the motivational deficit of depressed patients at baseline (V1). | Comparison of the computational phenotype of patients with depression and healthy volunteers at V1. | Baseline state (before the start of antidepressant strategy) |
| Description of the neural correlates of motivation deficits of depressed patients at baseline (V1). | Comparison of the brain functional statistical maps of patient with depression and healthy volunteers at V1. | Baseline state (before the start of antidepressant strategy) |
| Description of the evolution of motivation deficit of depressed patients after one week of antidepressant treatment | Comparison of the computational phenotype of patients with depression at V1 and V2. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) |
| Description of the evolution of the neural correlates of motivation deficits after one week of antidepressant treatment | Comparison of the brain functional statistical maps of patient with depression at V1 and V2. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) |
| Description of the evolution of motivation deficit of depressed patients at 6 months | Comparison of the computational phenotype of patients with depression at V1 and V4. | Baseline state (before the start of antidepressant strategy), V4 (6 months after the start of antidepressant) |
| Description of the evolution of the structural neural correlates of depression after 6 months of treatment | Comparison of the structural brain imaging of patients with depression at V1 and V4. | Baseline state (before the start of antidepressant strategy), V4 (6 months after the start of antidepressant) |
| Description of the evolution of the functional neural correlates of depression after 6 months of treatment | Comparison of the function brain imaging (ASL) of patients with depression at V1 and V4. | Baseline state (before the start of antidepressant strategy) V4 (6 months after the start of antidepressant) |
| Construction of a bio-bank | Serum tubes will be drowned along the study (V1, V2, V3 and V4 for patients - V1 for healthy volunteers) prepared and stored. | Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) and V3 (after 28 days of antidepressant), V4 (6 months after the start of antidepressant) |
| Centre hospitalier Universitaire de Lille | Not yet recruiting | Lille | Nord | 59000 | France |
|
| Centre hospitalier Universitaire de Saint-Etienne | Not yet recruiting | Saint-Priest-en-Jarez | Pays de la Loire Region | 42270 | France |
|
| Groupe hospitalo-universitaire Assistance Publique, hôpital Pitié Salpêtrière - Hôpitaux de Paris Sorbonne Université | Not yet recruiting | Paris | 75013 | France |
|
| - Groupe hospitalo-universitaire Paris Psychiatrie et Neurosciences | Recruiting | Paris | 75014 | France |
|
| Background |
| Lam RW, Kennedy SH, Grigoriadis S, McIntyre RS, Milev R, Ramasubbu R, Parikh SV, Patten SB, Ravindran AV; Canadian Network for Mood and Anxiety Treatments (CANMAT). Canadian Network for Mood and Anxiety Treatments (CANMAT) clinical guidelines for the management of major depressive disorder in adults. III. Pharmacotherapy. J Affect Disord. 2009 Oct;117 Suppl 1:S26-43. doi: 10.1016/j.jad.2009.06.041. Epub 2009 Aug 11. |
| 21929846 | Background | Uher R, Perlis RH, Henigsberg N, Zobel A, Rietschel M, Mors O, Hauser J, Dernovsek MZ, Souery D, Bajs M, Maier W, Aitchison KJ, Farmer A, McGuffin P. Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms. Psychol Med. 2012 May;42(5):967-80. doi: 10.1017/S0033291711001905. Epub 2011 Sep 20. |
| 29194534 | Background | Pessiglione M, Vinckier F, Bouret S, Daunizeau J, Le Bouc R. Why not try harder? Computational approach to motivation deficits in neuro-psychiatric diseases. Brain. 2018 Mar 1;141(3):629-650. doi: 10.1093/brain/awx278. |
| 21853083 | Background | Clery-Melin ML, Schmidt L, Lafargue G, Baup N, Fossati P, Pessiglione M. Why don't you try harder? An investigation of effort production in major depression. PLoS One. 2011;6(8):e23178. doi: 10.1371/journal.pone.0023178. Epub 2011 Aug 10. |
| 27337420 | Background | Mauras T, Masson M, Fossati P, Pessiglione M. Incentive Sensitivity as a Behavioral Marker of Clinical Remission From Major Depressive Episode. J Clin Psychiatry. 2016 Jun;77(6):e697-703. doi: 10.4088/JCP.15m09995. |
| 29672668 | Background | Le Heron C, Plant O, Manohar S, Ang YS, Jackson M, Lennox G, Hu MT, Husain M. Distinct effects of apathy and dopamine on effort-based decision-making in Parkinson's disease. Brain. 2018 May 1;141(5):1455-1469. doi: 10.1093/brain/awy110. |
| 22090487 | Background | Wardle MC, Treadway MT, Mayo LM, Zald DH, de Wit H. Amping up effort: effects of d-amphetamine on human effort-based decision-making. J Neurosci. 2011 Nov 16;31(46):16597-602. doi: 10.1523/JNEUROSCI.4387-11.2011. |
| 22553023 | Background | Treadway MT, Buckholtz JW, Cowan RL, Woodward ND, Li R, Ansari MS, Baldwin RM, Schwartzman AN, Kessler RM, Zald DH. Dopaminergic mechanisms of individual differences in human effort-based decision-making. J Neurosci. 2012 May 2;32(18):6170-6. doi: 10.1523/JNEUROSCI.6459-11.2012. |
| 17050654 | Background | Nutt D, Demyttenaere K, Janka Z, Aarre T, Bourin M, Canonico PL, Carrasco JL, Stahl S. The other face of depression, reduced positive affect: the role of catecholamines in causation and cure. J Psychopharmacol. 2007 Jul;21(5):461-71. doi: 10.1177/0269881106069938. Epub 2006 Oct 18. |
| 15014711 | Background | Culpepper L. Escitalopram: A New SSRI for the Treatment of Depression in Primary Care. Prim Care Companion J Clin Psychiatry. 2002 Dec;4(6):209-214. doi: 10.4088/pcc.v04n0601. |
| 25016186 | Background | Sanchez C, Asin KE, Artigas F. Vortioxetine, a novel antidepressant with multimodal activity: review of preclinical and clinical data. Pharmacol Ther. 2015 Jan;145:43-57. doi: 10.1016/j.pharmthera.2014.07.001. Epub 2014 Jul 9. |
| 24850369 | Background | Fervaha G, Foussias G, Agid O, Remington G. Motivational and neurocognitive deficits are central to the prediction of longitudinal functional outcome in schizophrenia. Acta Psychiatr Scand. 2014 Oct;130(4):290-9. doi: 10.1111/acps.12289. Epub 2014 May 22. |
| 26995233 | Background | Fervaha G, Foussias G, Takeuchi H, Agid O, Remington G. Motivational deficits in major depressive disorder: Cross-sectional and longitudinal relationships with functional impairment and subjective well-being. Compr Psychiatry. 2016 Apr;66:31-8. doi: 10.1016/j.comppsych.2015.12.004. Epub 2015 Dec 18. |
| 32074255 | Background | Berwian IM, Wenzel JG, Collins AGE, Seifritz E, Stephan KE, Walter H, Huys QJM. Computational Mechanisms of Effort and Reward Decisions in Patients With Depression and Their Association With Relapse After Antidepressant Discontinuation. JAMA Psychiatry. 2020 May 1;77(5):513-522. doi: 10.1001/jamapsychiatry.2019.4971. |
| 22363208 | Background | Schmidt L, Lebreton M, Clery-Melin ML, Daunizeau J, Pessiglione M. Neural mechanisms underlying motivation of mental versus physical effort. PLoS Biol. 2012 Feb;10(2):e1001266. doi: 10.1371/journal.pbio.1001266. Epub 2012 Feb 21. |
| 25411490 | Background | Skvortsova V, Palminteri S, Pessiglione M. Learning to minimize efforts versus maximizing rewards: computational principles and neural correlates. J Neurosci. 2014 Nov 19;34(47):15621-30. doi: 10.1523/JNEUROSCI.1350-14.2014. |
| 17431137 | Background | Pessiglione M, Schmidt L, Draganski B, Kalisch R, Lau H, Dolan RJ, Frith CD. How the brain translates money into force: a neuroimaging study of subliminal motivation. Science. 2007 May 11;316(5826):904-6. doi: 10.1126/science.1140459. Epub 2007 Apr 12. |
| 31179377 | Background | Pessiglione M, Delgado MR. The good, the bad and the brain: Neural correlates of appetitive and aversive values underlying decision making. Curr Opin Behav Sci. 2015 Oct;5:78-84. doi: 10.1016/j.cobeha.2015.08.006. Epub 2015 Aug 24. |
| 23217747 | Background | Palminteri S, Justo D, Jauffret C, Pavlicek B, Dauta A, Delmaire C, Czernecki V, Karachi C, Capelle L, Durr A, Pessiglione M. Critical roles for anterior insula and dorsal striatum in punishment-based avoidance learning. Neuron. 2012 Dec 6;76(5):998-1009. doi: 10.1016/j.neuron.2012.10.017. |
| 19914190 | Background | Lebreton M, Jorge S, Michel V, Thirion B, Pessiglione M. An automatic valuation system in the human brain: evidence from functional neuroimaging. Neuron. 2009 Nov 12;64(3):431-9. doi: 10.1016/j.neuron.2009.09.040. |
| 29700303 | Background | Vinckier F, Rigoux L, Oudiette D, Pessiglione M. Neuro-computational account of how mood fluctuations arise and affect decision making. Nat Commun. 2018 Apr 26;9(1):1708. doi: 10.1038/s41467-018-03774-z. |
| 26573970 | Background | Stephan KE, Bach DR, Fletcher PC, Flint J, Frank MJ, Friston KJ, Heinz A, Huys QJM, Owen MJ, Binder EB, Dayan P, Johnstone EC, Meyer-Lindenberg A, Montague PR, Schnyder U, Wang XJ, Breakspear M. Charting the landscape of priority problems in psychiatry, part 1: classification and diagnosis. Lancet Psychiatry. 2016 Jan;3(1):77-83. doi: 10.1016/S2215-0366(15)00361-2. Epub 2015 Nov 11. |
| 26573969 | Background | Stephan KE, Binder EB, Breakspear M, Dayan P, Johnstone EC, Meyer-Lindenberg A, Schnyder U, Wang XJ, Bach DR, Fletcher PC, Flint J, Frank MJ, Heinz A, Huys QJM, Montague PR, Owen MJ, Friston KJ. Charting the landscape of priority problems in psychiatry, part 2: pathogenesis and aetiology. Lancet Psychiatry. 2016 Jan;3(1):84-90. doi: 10.1016/S2215-0366(15)00360-0. Epub 2015 Nov 11. |
| 27346545 | Background | Stephan KE, Schlagenhauf F, Huys QJM, Raman S, Aponte EA, Brodersen KH, Rigoux L, Moran RJ, Daunizeau J, Dolan RJ, Friston KJ, Heinz A. Computational neuroimaging strategies for single patient predictions. Neuroimage. 2017 Jan 15;145(Pt B):180-199. doi: 10.1016/j.neuroimage.2016.06.038. Epub 2016 Jun 22. |
| 26361002 | Background | Corlett PR, Fletcher PC. Computational psychiatry: a Rosetta Stone linking the brain to mental illness. Lancet Psychiatry. 2014 Oct;1(5):399-402. doi: 10.1016/S2215-0366(14)70298-6. Epub 2014 Aug 12. No abstract available. |
| 21550365 | Background | Hasler G. Can the neuroeconomics revolution revolutionize psychiatry? Neurosci Biobehav Rev. 2012 Jan;36(1):64-78. doi: 10.1016/j.neubiorev.2011.04.011. Epub 2011 Apr 29. |
| 26906507 | Background | Huys QJ, Maia TV, Frank MJ. Computational psychiatry as a bridge from neuroscience to clinical applications. Nat Neurosci. 2016 Mar;19(3):404-13. doi: 10.1038/nn.4238. |
| 22177032 | Background | Montague PR, Dolan RJ, Friston KJ, Dayan P. Computational psychiatry. Trends Cogn Sci. 2012 Jan;16(1):72-80. doi: 10.1016/j.tics.2011.11.018. Epub 2011 Dec 14. |
| 27346915 | Background | Keks N, Hope J, Keogh S. Switching and stopping antidepressants. Aust Prescr. 2016 Jun;39(3):76-83. doi: 10.18773/austprescr.2016.039. Epub 2016 Jun 1. |
| 29477251 | Background | Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, Leucht S, Ruhe HG, Turner EH, Higgins JPT, Egger M, Takeshima N, Hayasaka Y, Imai H, Shinohara K, Tajika A, Ioannidis JPA, Geddes JR. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet. 2018 Apr 7;391(10128):1357-1366. doi: 10.1016/S0140-6736(17)32802-7. Epub 2018 Feb 21. |
| 28677828 | Background | Koesters M, Ostuzzi G, Guaiana G, Breilmann J, Barbui C. Vortioxetine for depression in adults. Cochrane Database Syst Rev. 2017 Jul 5;7(7):CD011520. doi: 10.1002/14651858.CD011520.pub2. |
| 19578460 | Background | Hartwig V, Giovannetti G, Vanello N, Lombardi M, Landini L, Simi S. Biological effects and safety in magnetic resonance imaging: a review. Int J Environ Res Public Health. 2009 Jun;6(6):1778-98. doi: 10.3390/ijerph6061778. Epub 2009 Jun 10. |
| 29593535 | Background | Felice D, Guilloux JP, Pehrson A, Li Y, Mendez-David I, Gardier AM, Sanchez C, David DJ. Vortioxetine Improves Context Discrimination in Mice Through a Neurogenesis Independent Mechanism. Front Pharmacol. 2018 Mar 12;9:204. doi: 10.3389/fphar.2018.00204. eCollection 2018. |
| 24818074 | Background | Hayakawa YK, Sasaki H, Takao H, Hayashi N, Kunimatsu A, Ohtomo K, Aoki S. Depressive symptoms and neuroanatomical structures in community-dwelling women: A combined voxel-based morphometry and diffusion tensor imaging study with tract-based spatial statistics. Neuroimage Clin. 2014 Mar 12;4:481-7. doi: 10.1016/j.nicl.2014.03.002. eCollection 2014. |
| 27376473 | Background | Colle R, Dupong I, Colliot O, Deflesselle E, Hardy P, Falissard B, Ducreux D, Chupin M, Corruble E. Smaller hippocampal volumes predict lower antidepressant response/remission rates in depressed patients: A meta-analysis. World J Biol Psychiatry. 2018 Aug;19(5):360-367. doi: 10.1080/15622975.2016.1208840. Epub 2016 Aug 15. |
| 32113908 | Background | Osimo EF, Pillinger T, Rodriguez IM, Khandaker GM, Pariante CM, Howes OD. Inflammatory markers in depression: A meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls. Brain Behav Immun. 2020 Jul;87:901-909. doi: 10.1016/j.bbi.2020.02.010. Epub 2020 Feb 27. |
| 31076872 | Background | Kojima M, Matsui K, Mizui T. BDNF pro-peptide: physiological mechanisms and implications for depression. Cell Tissue Res. 2019 Jul;377(1):73-79. doi: 10.1007/s00441-019-03034-6. Epub 2019 May 10. |
| 29608993 | Background | Ogyu K, Kubo K, Noda Y, Iwata Y, Tsugawa S, Omura Y, Wada M, Tarumi R, Plitman E, Moriguchi S, Miyazaki T, Uchida H, Graff-Guerrero A, Mimura M, Nakajima S. Kynurenine pathway in depression: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2018 Jul;90:16-25. doi: 10.1016/j.neubiorev.2018.03.023. Epub 2018 Mar 30. |
| 31255681 | Background | Verdonk F, Petit AC, Abdel-Ahad P, Vinckier F, Jouvion G, de Maricourt P, De Medeiros GF, Danckaert A, Van Steenwinckel J, Blatzer M, Maignan A, Langeron O, Sharshar T, Callebert J, Launay JM, Chretien F, Gaillard R. Microglial production of quinolinic acid as a target and a biomarker of the antidepressant effect of ketamine. Brain Behav Immun. 2019 Oct;81:361-373. doi: 10.1016/j.bbi.2019.06.033. Epub 2019 Jun 28. |
| 26359113 | Background | Harrison NA, Voon V, Cercignani M, Cooper EA, Pessiglione M, Critchley HD. A Neurocomputational Account of How Inflammation Enhances Sensitivity to Punishments Versus Rewards. Biol Psychiatry. 2016 Jul 1;80(1):73-81. doi: 10.1016/j.biopsych.2015.07.018. Epub 2015 Aug 1. |
| 28101340 | Background | Chen G, Bian H, Jiang D, Cui M, Ji S, Liu M, Lang X, Zhuo C. Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naive patients with first-episode major depression. Biomed Rep. 2016 Dec;5(6):675-680. doi: 10.3892/br.2016.796. Epub 2016 Oct 31. |
| 24882178 | Background | Ota M, Noda T, Sato N, Hattori K, Teraishi T, Hori H, Nagashima A, Shimoji K, Higuchi T, Kunugi H. Characteristic distributions of regional cerebral blood flow changes in major depressive disorder patients: a pseudo-continuous arterial spin labeling (pCASL) study. J Affect Disord. 2014 Aug;165:59-63. doi: 10.1016/j.jad.2014.04.032. Epub 2014 Apr 21. |
| 31388104 | Background | Cooper CM, Chin Fatt CR, Liu P, Grannemann BD, Carmody T, Almeida JRC, Deckersbach T, Fava M, Kurian BT, Malchow AL, McGrath PJ, McInnis M, Oquendo MA, Parsey RV, Bartlett E, Weissman M, Phillips ML, Lu H, Trivedi MH. Discovery and replication of cerebral blood flow differences in major depressive disorder. Mol Psychiatry. 2020 Jul;25(7):1500-1510. doi: 10.1038/s41380-019-0464-7. Epub 2019 Aug 6. |
| 26826533 | Background | Kaichi Y, Okada G, Takamura M, Toki S, Akiyama Y, Higaki T, Matsubara Y, Okamoto Y, Yamawaki S, Awai K. Changes in the regional cerebral blood flow detected by arterial spin labeling after 6-week escitalopram treatment for major depressive disorder. J Affect Disord. 2016 Apr;194:135-43. doi: 10.1016/j.jad.2015.12.062. Epub 2016 Jan 21. |
| 31158260 | Background | Ruckbeil MV, Hilgers RD, Heussen N. Randomization in survival studies: An evaluation method that takes into account selection and chronological bias. PLoS One. 2019 Jun 3;14(6):e0217946. doi: 10.1371/journal.pone.0217946. eCollection 2019. |
| 444788 | Background | Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979 Apr;134:382-9. doi: 10.1192/bjp.134.4.382. |
| 12946886 | Background | Rush AJ, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, Markowitz JC, Ninan PT, Kornstein S, Manber R, Thase ME, Kocsis JH, Keller MB. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003 Sep 1;54(5):573-83. doi: 10.1016/s0006-3223(02)01866-8. |
| 9626712 | Background | Development of the World Health Organization WHOQOL-BREF quality of life assessment. The WHOQOL Group. Psychol Med. 1998 May;28(3):551-8. doi: 10.1017/s0033291798006667. |
| 21102344 | Background | Sheehan DV, Harnett-Sheehan K, Spann ME, Thompson HF, Prakash A. Assessing remission in major depressive disorder and generalized anxiety disorder clinical trials with the discan metric of the Sheehan disability scale. Int Clin Psychopharmacol. 2011 Mar;26(2):75-83. doi: 10.1097/YIC.0b013e328341bb5f. |
| 7551619 | Background | Snaith RP, Hamilton M, Morley S, Humayan A, Hargreaves D, Trigwell P. A scale for the assessment of hedonic tone the Snaith-Hamilton Pleasure Scale. Br J Psychiatry. 1995 Jul;167(1):99-103. doi: 10.1192/bjp.167.1.99. |
| 1627973 | Background | Starkstein SE, Mayberg HS, Preziosi TJ, Andrezejewski P, Leiguarda R, Robinson RG. Reliability, validity, and clinical correlates of apathy in Parkinson's disease. J Neuropsychiatry Clin Neurosci. 1992 Spring;4(2):134-9. doi: 10.1176/jnp.4.2.134. |
| 30763119 | Background | Brown S, Rittenbach K, Cheung S, McKean G, MacMaster FP, Clement F. Current and Common Definitions of Treatment-Resistant Depression: Findings from a Systematic Review and Qualitative Interviews. Can J Psychiatry. 2019 Jun;64(6):380-387. doi: 10.1177/0706743719828965. Epub 2019 Feb 14. |
| 17055746 | Background | Friston K, Mattout J, Trujillo-Barreto N, Ashburner J, Penny W. Variational free energy and the Laplace approximation. Neuroimage. 2007 Jan 1;34(1):220-34. doi: 10.1016/j.neuroimage.2006.08.035. Epub 2006 Oct 20. |
| 24465198 | Background | Daunizeau J, Adam V, Rigoux L. VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data. PLoS Comput Biol. 2014 Jan;10(1):e1003441. doi: 10.1371/journal.pcbi.1003441. Epub 2014 Jan 23. |
| 17416921 | Background | O'Doherty JP, Hampton A, Kim H. Model-based fMRI and its application to reward learning and decision making. Ann N Y Acad Sci. 2007 May;1104:35-53. doi: 10.1196/annals.1390.022. Epub 2007 Apr 7. |
| 27824554 | Background | Meyniel F, Goodwin GM, Deakin JW, Klinge C, MacFadyen C, Milligan H, Mullings E, Pessiglione M, Gaillard R. A specific role for serotonin in overcoming effort cost. Elife. 2016 Nov 8;5:e17282. doi: 10.7554/eLife.17282. |
| Benzofurans |
| D006574 | Heterocyclic Compounds, 2-Ring |
| D000072471 | Heterocyclic Compounds, Fused-Ring |
| D006571 | Heterocyclic Compounds |
| D010879 | Piperazines |
| D006573 | Heterocyclic Compounds, 1-Ring |