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) 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? 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 (, 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 () and characterized by pre-treatment anhedonic behaviors will preferentially benefit from treatment (-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 -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 ([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

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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

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r P 1 High PE P 1 High DA release Percentage Xchange = 1 from2 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 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 Hamilton Snaith

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” approach: • Target engagement approach • Pre-screening of patients (transdiagnostic) • Probe (e.g., fMRI tasks) selected based on hypothesized mechanisms of the drug (KOR antagonism → reduction of inhibition on DA neurons → potentiated ventral striatal reactivity to reward) • If failing, fail fast… (and provide interpretable null findings) Outstanding Questions/Future Directions 1) Pre-selecting/stratifying/enriching using self-report measures (e.g., SHAPS) likely does not yield neurobiologically homogenous phenotypes → Identify “biotypes” using cluster analyses/machine learning? • Practical considerations of using behavioral batteries in clinical trials/clinics?

2) “Capitalization” rather than “compensatory” model of change? • Strategies for non-responders? Acknowledgments fMRI studies

Roee Rosi Michael Admon Kaiser Treadway PET studies

Georges El Fakhri Preclinical studies

R37 MH068376 R01 MH101521 UH3 MH109334 Andre Athina Dana Foundation Der-Avakian Markou NARSAD Distinguished Inv. Award

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(1,53)=3.44, p=0.030; Hedges’ g=0.49 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 Frontostriatal Resting-state Functional Connectivity Mediates the Relationship Between Striatal DAT Binding Potential and Individual Differences in Reward Learning Behavior

Rosi Kaiser et al., Cerebral Cortex, 2018 Kaiser Snaith Hamilton Pleasure Scale I would enjoy my favourite television or radio programme I would enjoy being with family or close friends I would find pleasure in my hobbies and pastimes

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Liu et al., 2012 Franken et al., 2007 Role of Dopamine in Depression and Anhedonia? 1) Impairments in behaviors known to rely on DA: reward learning (Pizzagalli et al., 2005), effort-based decision making (Treadway et al., 2012), and reward prediction error coding (Kumar et al., 2008, 2018). 2) Reduced reward-related activation within DA-rich ventral (e.g., nucleus accumbens) and dorsal (caudate, putamen) striatal regions (Keedwell et al., 2005; Pizzagalli et al., 2009; Kumar et al., 2008, 2018). 3) Rapid increases in depressive symptoms after catecholamine depletion among remitted MDD

Direct Evidence Direct individuals (Hasler et al., 2008, 2009; Homan et al., 2015). 4) Animal models relevant to depression reliably induce anhedonic phenotypes and dysfunction within the mesolimbic DA system (Cabib and Puglisi-Allegra, 2012). How?

Presynaptic Autoreceptor (inhibitory)

Strategy 2: Autoreceptor Blockage (in MDD)

Disinhibition of Presynaptic Neuron (↑DA) Rhodes et al., 2005 Hypothesis: Pharmacological manipulations that increase phasic DA signaling will “rescue” blunted striatal responses in MDD

Single, low doses of D2/3 antagonists (e.g., amisulpride)*: In rodents: → ↑ DA synthesis and release and have prohedonic effects (Coukell et al 1996; Papp and Wieronska 2000; Schoemaker et al 1997). In humans: →↑ ventral striatal fMRI responses to rewards [Jocham et al., 2011] → in MDD, dysthymia: low doses of amisulpride (50 mg/day) have antidepressant effects (e.g., Amore et al 2001; Boyer et al 1999; Rocca et al 2002; Smeraldi 1998; Zanardi and Smeraldi 2006). *Mechanisms: Presynaptic autoreceptor blockade Hypothesized Mechanisms? Single low doses of D2/3 antagonists block presynaptic autoreceptors (inhibitory) → Increases of phasic DA

Increased DA striatal Increased ventral striatal concentrations responses to rewards (200 mg)

Schoemaker et al., 1997 Jocham et al. , 2011 Study Design N = 89 (all unmedicated): 23 MDD + Amisulpride 23 MDD + Placebo 23 HC + Amisulpride 20 HC + Placebo

Amisulpride

pharmacokinetics g/L) μ Peak 1: ~1.5 hrs (fMRI with MID) Peak 2: 3-6 hrs (Reward

Learning Task) Plasma level ( level Plasma

Time (h) Coukell et al., 1996 Low Amisulpride Dose “Rescues” Reward Dysfunction in MDD

Striatal Response to Reward Outcome

1 )

β * 0.6 Caudate 0.2 Placebo -0.2

Activation ( Activation Amisulpride -0.6

1.4 (50 mg) )

β * 1 * Nacc 0.6 0.2

-0.2 Activation ( Activation -0.6

Rosi 1 )

Kaiser β * * 0.6 Putamen 0.2

-0.2 Activation ( Activation -0.6 Admon*, Kaiser* et al., Roee MDD HC Am. J. Psychiatry, 2017 Admon Low Amisulpride Dose “Rescues” Reward Dysfunction in MDD

Striatal connectivity during reward outcome

Placebo Nacc- Amisulpride MidCingulate (50 mg)

X = 6 0.8 * * t = 8

) 0.6 β t = -8 0.4

Connectivity ( Connectivity 0.2

Caudate-ACC 0 connectivity MDD HC Low Amisulpride Dose “Rescues” Reward Dysfunction in MDD

Striatal connectivity during reward outcome

Placebo Nacc- Amisulpride MidCingulate (50 mg)

X = 6

2

) β t = 8 r = 0.65 1 For MDD t = -8 only 0 r = -0.24

Connectivity ( Connectivity -1 0.4 0.6 0.8 1

Admon*, Kaiser* et al., Reward learning Am. J. Psychiatry, 2017 (Choose A) STUDY 2

Question: If MDD is associated with blunted DA striatal signaling, can we detect evidence of this abnormality using positron emission tomography? One Target (Among Several…)

Reduced DA DAT synthesis/ release

Rationale: Preclinical models (depletions, chronic stress) eliciting downregulation of mesolimbic DA lead to reduced DAT levels in dorsal and ventral striatum (compensatory downregulation) (Brake et al., 2004; Lucas et al., 2004, 2007; Jiao et al. 2003). (DAT) Abnormalities in MDD? 1) Post-mortem: Reduced dopamine transporter in MDD in the amygdala (Klimek et al., 2002) and reduced DA turnover in the striatum (Bowden et al., 1997;). 2) In vivo molecular imaging: Inconsistent!

12 studies: No significant effects - 5 studies: ↑DAT density in MDD - 2 studies: ↓DAT density in MDD - 5 studies: no differences BUT: - High heterogeneity (clinical heterogeneity?) - 11 of 12 studies used SPECT and unspecific DAT tracers (e.g., [123]b-CIT) PET study with the highly selective DAT tracer 11C altropane

Dynamic PET scans acquired with an ECAT EXACT HR+ and bolus injection of [11C]Altropane

Advantages of altropane [Fischman et al 2001; Madras et al., 1998a,b,c]: 1) Rapid and specific striatal binding [max binding within 30 min in DA-rich striatal regions, including the caudate, putamen, NAc]; 2) High selectivity for DAT [28x selectivity for DAT over SERT]; 3) Low level of nonspecific binding [e.g., putamen:cerebellum: 120:1] Dopamine Transporter (DAT) Abnormalities in MDD? I. Reduced striatal DAT binding in MDD

0.3 HC

0.2 * MDD

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-0.2 Binding Potential Binding

-0.3 Caudate Putamen NAc Group x Region: Wilks’ Lambda (2,44) = 4.14 HC: n = 23 p < 0.025 MDD: n = 25 [covariate: age] Pizzagalli et al., under review Dopamine Transporter (DAT) Abnormalities in MDD? II. Reduced VTA DAT binding in MDD

0.06 HC 0.04 * MDD 0.02

0.00

-0.02 Binding Potential Binding -0.04 Ventral Tegmental Area

VTA: Main effect of Group (VTA) F(1,45)= 6.04 HC: n = 23 p<0.018 MDD: n = 25 [covariate: age] Pizzagalli et al., under review Dopamine Transporter (DAT) Abnormalities in MDD? III. Reduced striatal and VTA DAT binding in MDD is exacerbated by numbers of MDE BP & # MDEs: 0.4 Putamen: r = -0.36

0.2 VTA: r = -0.36 (ps<0.014, N=47)

0.0

-0.2 Binding Potential Binding

-0.4 HC 1 MDE 2-4 MDEs 5+ MDEs

Pizzagalli et al., under review Dopamine Transporter (DAT) Abnormalities in MDD? IV. Reduced VTA DAT binding with perceived “entrapment” r = -0.43 p<0.032 Two clinical constructs hypothesized to be linked to DA: - Anhedonia: ns - Feelings of Entrapment: r = -0.43, p < 0.032

External Entrapment Scale (Gilbert et al., 1998) (// preclinical literature) “I am in a situation I feel trapped in” “I can see no way out of my current situation” “I feel trapped by my obligations” → Overlap with the concept of helplessness Pizzagalli et al., under review Dopamine Transporter (DAT) Abnormalities in MDD? V. Reduced striatal 40 kDa 50 kDa 60 kDa DAT binding in post-mortem tissue

15 depressed individuals (all by suicide) (38.9 y., 12 m) 15 HC (40.6 y., 13 m) [Douglas-Bell Canada Brain Bank]

80 kDa hydroxylase MDD: ↓ putamen expression: • TH (d = -1.06) • Mature form of DAT (80 kDa) (d = -1.15) • Intermediate forms (50 kDa: d = -0.92; 60 kDa: d = -0.99)

Pizzagalli et al., under review Conclusion 1) Reward learning (one form of anhedonic behavior): • Is associated with individual differences in frontostriatal and dopamine markers • Can be bi-directionally perturbated by challenges affecting striatal DA transmission (D2/3 ago/antagonists, amphetamine, nicotine, stress), including stress-induced inflammation (IL-6) [not shown, see Treadway et al., Biological Psychiatry, 2017] 2) Depression: impaired ability to modulate behavior as a function of rewards • Dysfunctions in striatal regions implicated in reinforcement learning (caudate) and reward prediction error (accumbens) • DA downregulation (PET + post-mortem DAT finding) • It can be “rescued” by a pharmacological challenge hypothesized to transiently increase DA (amisulpride) Acknowledgments fMRI studies

Roee Rosi Admon Kaiser

PET studies

Michael Treadway

Georges El Fakhri Preclinical studies Post-mortem studies

R01 MH095809 R01 MH101521 R01 MH102279 R01 MH108602 R37 MH068376 UH3 MH109334 Andre Athina Sabina Gustavo Dana Foundation Der-Avakian Markou Berretta Turecki NARSAD Distinguished Inv. Award

Dopamine Transporter (DAT) Abnormalities in MDD? V. Abnormal age-related DAT effects in MDD

Pizzagalli et al., under review Dopamine Transporter (DAT) Abnormalities in MDD?

Pizzagalli et al., under review Environmental Factors

Decreased Reward Blunted Mesolimbic Depression Responsiveness DA System

Biological Exaggerated Stress Vulnerability Responsiveness

Does uncontrollable stress reduce reward learning? Three independent human studies: Healthy subjects performing the task under an acute laboratory stressor or a naturalistic stressor displayed reduced reward learning [Bogdan & Pizzagalli, 2006; Bogdan et al., 2011; Nikolova et al., 2012] • Acute Stressor* Reduces Reward Learning

No-stress 0.20 Stress * Threat-of- Condition: Shock 0.10 F(1,78) = 5.39

p < .030 ResponseBias 0.00 N = 80 women Block 1 Block 2 Block 3 Bogdan and Pizzagalli, Biol. Psychiatry, 2006

0.20

0.15 Condition: 0.10 F(1,74) = 5.88 p < .020 0.05

Response Bias Response N = 75 women Ryan 0.00 Bogdan Block 1 Block 2 Block 3 Bogdan et al., J. Neurosci, 2011 • HOW Does Stress Affect Reward Learning?

• Potential mechanisms?

• Study 1 (humans): Disruption of ventral striatal prediction error signaling during reinforcement learning (via increased inflammatory responses)?

• Study 2 (rats): Disruption of stress peptides (Nociceptin/orphanin FQ)? • Study 1

Michael Roee Treadway Admon Design:

• Healthy females (N=88)

• Stressor for behavioral session: Maastricht Acute Stress Task (MAST; Smeets et al, 2012)

• Stressor for imaging session: Montreal Imaging Stress Task (MIST; Dedovic et al, 2005)

• fMRI task: Instrumental Reinforcement Task (Pessiglione et al, 2006) • Session 1: Behavior (MAST)

Time (quadratic): All Fs > 66 ps < 10-12 Smeets et al., 2013

Time: F(2, 92) = 17.89 N = 88 women p = 8.0 x 10-6 • Session 2: fMRI (MIST)

Time (quadratic): All Fs > 24 ps < 10-6

Dedovic et al., 2005

fMRI Task

Outcome Phase Pessiglione et al., Nature, 2006 Reward Prediction Error • Session 2: fMRI Larger increases in IL-6 following stress (session 1) ↔ Larger decreases in NAcc RPE following stress (session 2)

) r = -0.42

p < 0.01 RPE Change RPE Change

PreStress r = -0.36 – p < 0.05

NAc Accumbens

PostStress (

Left N. N. Left IL-6 Change (PostStress – PreStress)

Treadway et al., Biol. Psychiatry, 2017 Admon et al., J. Neurosci, 2017