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Anhedonia: Circuitry and Relevance to Drug Development & Patient Stratification

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Anhedonia: Circuitry and Relevance to Drug Development & Patient Stratification The Neurobiology of Anhedonia: Circuitry and Relevance to Drug Development & Patient Stratification Diego A. Pizzagalli, Ph.D. Professor of Psychiatry Harvard Medical School McLean Hospital ISCTM Reward Processing February 21, 2020 Disclosures • Grant/Research Support: • NIH, NARSAD, Dana Foundation • Speaker’s Bureau: • None • Consultant: • Akili, BlackThorn Therapeutics (licensed Probabilistic Reward Task), Boehringer Ingelheim, Compass Pathway, Otsuka, Takeda • Stock Options: • BlackThorn Therapeutics • Patents: • None Role of Anhedonia in MDD & Antidepressant Response 1) Anhedonia predicts: • Depression two years later (e.g., Wardenaar et al. 2012); • Poor outcome (e.g., Spijker et al. 2001; Uher et al. 2012); • Chronic course over 10 years (Moos & Cronkite 1999). 2) Anhedonia and amotivation are poorly addressed by first- line treatments (Calabrese et al., 2014; Craske et al., 2019). 3) Anhedonia predicts poor response to first-line pharmacological (e.g., SSRI; Vrieze et al., 2013) and psychological (e.g., CBT; McMakin et al. 2012) treatments as well as TMS (e.g., Downar et al., 2014). Borrowing from the “Traditional” Approach…. 1) Since anhedonia has been associated with: • Reduced functional, structural, and neurochemical markers within DA-rich regions along the mesocorticolimbic pathways (e.g., ventral and dorsal striatum) (e.g., Auerbach et al., 2017; Gabbay et al., 2017; Keedwell et al., 2005; Pecina et al., 2017); 2) Dopamine plays a key role in several reward-related functions (incentive motivation, reinforcement learning) 1) + 2) Patients with anhedonic phenotypes might preferentially benefit from treatments hypothesized to increase DA signaling. Parsing Reward Processing: From Hedonics to Motivated Behavior Barch et al., 2015 Barch et al., 2015 Reward Learning Barch et al., 2015 Reward Learning As a DA-sensitive Phenotype Probabilistic Reward Task 11.5 vs. 13 mm Athina Markou 0.9 vs. 1.6 sec tone Andre Der-Avakian Decreased Dopamine Suppresses Reward Learning in Humans and Rats Response Bias Response [Single 0.5 mg dose] [Single 0.1 mg/kg dose] Hypothesized mechanism: Presynaptic autoreceptor activation→ ↓DA Psychostimulant Exposure Enhances Reward Learning in Humans and Rats Humans Rats N = 30 (14 mg) Response Bias Response Block 1 Block 2 Block 3 Barr etBarr al. et Biological al. Biological Psychiatry Psychiatry 2008 2008 Der-AvakianDer-Avakianet al. Translational et al. Translational Psychiatry Psychiatry 20132017 [14 mg path in non-smokers] [Single 0.5 mg/kg dose] Hypothesized mechanism: ↑ striatal DA transmission? Nicotine Withdrawal Suppresses Reward Learning in Humans and Rats Humans Rats PergadiaBarr et al. Biologicalet al. JAMA Psychiatry Psychiatry 2008 2014 Hypothesized mechanism: ↓ striatal DA transmission? Reward Learning is Associated with Frontostriatal and Dopamine Markers Better reward learning: ↓ DAT availability (i.e., higher DA?) r(31)= -0.43 C]Altropane (PET) C]Altropane 11 [ p=0.01 Worse Better Learning Reward Learning is Associated with Frontostriatal and Dopamine Markers Better reward learning: ↑ resting state FC between accumbens and vmPFC r(31)= 0.69 p<0.001 Interim Summary Reward learning: 1) Is associated with individual differences in frontostriatal and dopamine markers (healthy controls); 2) Is potentiated by pharmacological challenges hypothesized to increase striatal DA transmission (amphetamine, nicotine); 3) Is reduced by challenges hypothesized to decrease striatal DA transmission (single low dose of pramipexole, nicotine withdrawal, chronic social defeat); 4) Is reduced in individuals with MDD, especially with elevated anhedonia or melancholia (not shown; Pizzagalli et al., 2008; Liu et al., 2011; Vrieze et al., 2013; Fletcher et al., 2015) STUDY 1 Hypothesis: Patients with MDD failing to respond to SSRI treatment (sertraline) and characterized by pre-treatment anhedonic behaviors will preferentially benefit from bupropion treatment (norepinephrine-dopamine reuptake inhibitor, NDRI). STUDY 1: Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) Wk 0 (completed MDD Patients N = 262 PRT) Wks 1 - 8 Sertraline N = 127 Placebo N = 135 Non- Non- Responders Responders responders responders Wks 9 - 16 Sertraline Bupropion XL Sertraline Placebo N = 60 N = 52 N = 73 N = 46 Does pre-treatment reward learning differentiate between eventual responders and non-responders to sertraline and bupropion in Phase 2? Yuen Ang STUDY 1: Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) ANCOVA (Phase 2): • Drug (SER, BUP) x Response (yes, no) x Site (CU, MG, TX, UM) [covariates: age, gender and education]. Results (Phase 2): • Drug x Response: p<0.05 • Bupropion responders have significantly greater response bias than non-responders (SERT: ns). • Phase 2 bupropion responders and non-responders: no Week 0 or Week 8 HAMD differences Ang et al., under review STUDY 1: Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) ANCOVA (Phase 1): • Drug (SER, PLA) x Response (yes, no) x Site (CU, MG, TX, UM) [covariates: age, gender and education]. Results (Phase 1): • Drug x Response: p>0.45 Ang et al., under review STUDY 2 Hypothesis: Patients with MDD and characterized by pre- treatment anhedonic behaviors will preferentially benefit from pramipexole treatment (D2/3 DA agonist) STUDY 2: Ventrostriatal Dopamine Release and Reward Motivation in MDD (PI: F. Schneier, Columbia) Study Design: • 26 medication-naïve MDD patients and 26 controls • Patients received open-label treatment with pramipexole (ranging 0.5-2.5 mg/day) for 6 weeks • Before and after treatment: • Probabilistic reward task (behavior) • Ventral striatal reward prediction error signals (fMRI) • Before treatment: Ventral striatal DA release in response to oral dextroamphetamine ([11C]-(+)-PHNO PET) • A priori outcome measures (administered weekly) • Depressive symptom severity (HAM-D) • Anhedonia severity (SHAPS) • Improvement in global illness severity (CGI-Change Scale) STUDY 2: I. Significant symptomatic improvement following six weeks of treatment with pramipexole • 72.7% classified as responders at week 6 • Largest effect sizes for depressive symptoms (HAM-D: d=2.2; MASQ depressive distress subscale: d=1.4) and anhedonia (MASQ anhedonic depression subscale: d=1.3) STUDY 2: II. Abnormal reward learning, VS reward PE signaling and VS DA release in MDD at baseline C C Franklin Alexis Schneier Whitton STUDY 2: III. Better (i.e., more normative) reward learning and stronger reward sensitivity predicts lower post-treatment anhedonia PI: Franklin Schneier, Columbia University Whitton et al., Brain, 2020 STUDY 2: IV. Stronger (i.e., more normative) VS reward PE signals predict greater improvement in global illness severity A VS gain PE B VS DA D2/3 availability C VS DA release 3.5 3.5 3 3 s s e e r r o o c 2.5 c 2.5 s s I I G 2 G 2 C C d d e e t t c 1.5 c 1.5 i X=-12 i d d e e r r P X = 12 1 High PE P 1 High DA release Prediction-error signal Mean Mean extracted from ventral striatum 0.5 Low PE 0.5 Low DA release (HC group mean) (HC group mean) 0 0 1 2 3 4 5 6 1 2 3 4 5 6 Week Week PI: Franklin Schneier, Columbia University Whitton et al., Brain, 2020 STUDY 2: V. Less (i.e., more normative) VS DA release predicts greater improvement in global illness severity A VS gain PE B VS DA D2/3 availability C VS DA release 3.5 3.5 3 3 s s e e r r o o c 2.5 c 2.5 s s I I G 2 G 2 C C d d e e t t c 1.5 X=-12 c 1.5 i i d d e e r r P 1 High PE P 1 High DA release Percentage changeX = from 12 baseline Mean Mean 0.5 Low PE binding potential relative to 0.5 Low DA release (HC group mean)nondisplaceable compartment (HC group mean) 0 0 (∆BPND) computed from ventral 1 2 3 4 5 6 striatum 1 2 3 4 5 6 Week Week PI: Franklin Schneier, Columbia University Whitton et al., Brain, 2020 STUDY 3: FAST-MAS Study (PI: A. Krystal, Duke/UCSF) Kappa Opioid Antagonist for Anhedonia? B) Monetary Incentive Delay Task Reward Cue Target Feedback Loss Cue No-incentive Cue (500 ms ) (150 ms ) (1,230 ms ) You won You lost No +$ $5 -$ $1 0$ change STUDY 3: FAST-MAS Study (PI: A. Krystal, Duke/UCSF) Intent-to-treat sample: JNJ-67953964 (Kappa Opioid Antagonist, 10 mg) [N=45] Placebo [N=44] Snaith Hamilton Pleasure Scale Pleasure Snaith Hamilton Baseline-adjusted post-treatment scores: (F(1,86)=3.35; p=0.035; Hedges’ g=0.44 Krystal et al., Nature Medicine, in press STUDY 3: FAST-MAS Study (PI: A. Krystal, Duke/UCSF) Primary Measure: Nucleus Accumbens Secondary Measures: Activation to Reward-predicting Cues Self-reported anhedonia (SHAPS) Behavior: Response Bias Baseline-adjusted post-treatment scores: Treatment Arm x Time: F(1,86)=5.58; p<0.01; Hedges’ g=0.58 F(1,52)=4.69, p=0.035 [covariate: baseline SHAPS] Summary 1) As hypothesized, behavioral and neural markers of DA-rich regions within the brain reward system predicted response to pharmacological treatments with DA effects; 2) The direction of the findings was, however, OPPOSITE: More normative Response Bias, Reward Prediction Error, DA release predicted better response to bupropion and pramipexole. → Is a better functioning brain reward system needed to be able to benefit from DA treatments? 3) Prior precedence? 3 of 4 fMRI studies found that MDD individuals with pre-treatment neural patterns more closely resembling controls’ brain function (e.g., during the MID) had a greater response to Behavioral Activation Treatment (Carl et al., 2016; Crowther et al., 2015; Dichter et al., 2009). Summary 4) The NIMH “Fast-Fail”
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