Advancing Personalized Antidepressant Treatment Using PET/MRI



Status:Recruiting
Conditions:Depression
Therapuetic Areas:Psychiatry / Psychology
Healthy:No
Age Range:21 - 55
Updated:4/21/2016
Start Date:May 2015
End Date:May 2019
Contact:Qurat-ul-ain Gulamhussein, BA
Email:qurat-ul-ain.gulamhussein@stonybrookmedicine.edu
Phone:631-638-1545

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Despite current medications, morbidity and mortality of Major Depressive Disorder (MDD)
remain high. According to the World Health Organization, MDD affects 121 million people
worldwide, and is projected to be the second leading cause of global disability by 2020.
Monotherapy with SSRIs is the most widely used treatment for MDD. However, on average, SSRIs
require six weeks for onset of action, and two-thirds of those on SSRIs fail to achieve
remission.Compounding this problem, patients with residual symptoms are significantly more
likely to discontinue treatment or relapse, be hospitalized for medical and psychiatric
conditions, or die of suicide and other causes. Although eliminating ineffective treatment
trials would significantly reduce patient suffering and healthcare costs,clinicians
currently do not have the tools to objectively select treatment based on an individual's
likelihood of remission. Therefore, there is an urgent need to identify markers predictive
of an individual's SSRI treatment outcome. Developing this personalized treatment requires
increased understanding of the relationship between pretreatment neurobiology, SSRI-induced
biological changes, and the corresponding symptom improvements.

Aim 1: Determine a Pretreatment Marker of SSRI Effectiveness Using PET. With the goal of
reducing MDD burden, many studies have assessed the utility of FDG-PET in antidepressant
treatment prediction. However, due to the limitations listed above, there is no consensus on
which brain regions are predictive of treatment efficacy. In addition to serving as a
biomarker of SSRI effectiveness, only conclusive determination of these regions will provide
insight into depression pathophysiology, helping uncover SSRI mechanism of action, and
aiding in the search of novel therapeutics. Based on the investigators' preliminary data and
other, similar studies, the investigators hypothesize that SSRI-induced change in the
Hamilton Depression Rating Scale (deltaHDRS) will be correlated with pretreatment metabolic
rate of glucose (MRGlu, quantified using arterial blood analysis) in three potential
regions: (1) midbrain, (2) right anterior insula, and/or (3) left ventral prefrontal cortex.

Aim 2: Isolate the Neurobiological Basis of the "Loss" Research Domain Criteria (RDoc) and
the Change Associated with Treatment. Using a factor analysis of the HDRS, the investigators
have previously demonstrated that the "loss" RDoC criteria is significantly correlated to
MRGlu in frontal cortical areas. The investigators therefore hypothesize that change in
MRGlu (pre to post treatment) in these regions will be correlated with symptom improvement
specifically in "loss" symptoms. As an exploratory extension, the investigators will
determine whether these changes are treatment-specific (i.e. to SSRI or placebo). A
validation of the hypothesis suggests a targeted mechanism of action, and provides a
significant step forward for precision treatment. If regional changes in MRGlu are not
correlated to improvement in this RDoC category, it suggests that SSRI (or placebo) induced
changes may be a downstream effect that should be examined further.

Aim 3: Validate NonInvasive Full Quantification of MRGlu Using Simultaneous Estimation. Full
quantification of brain MRGlu with FDG (as performed in this study) requires measuring FDG
in arterial plasma (input function) from arterial catheter insertion and blood analysis.
This costly and invasive procedure creates a barrier to widespread PET use. The
investigators have developed an innovative method for Simultaneous Estimation (SimE) of
input information and PET outcome measures (e.g. MRGlu). SimE fully quantifies brain MRGlu
without requiring an arterial catheter. In the case of FDG, the investigators' data suggests
that SimE used with a single venous sample can provide accurate results. The investigators
further hypothesize that the venous sample may be entirely replaced by study data (e.g.,
injected dose) and biometrics (e.g., body surface area, lean body mass index). Using two
different approaches (statistical imputation and physiological parametric modeling) and
previously collected data, the investigators will train the SimE for accurate quantification
in the absence of blood data. The rich data collected in this study will then provide a
robust benchmark for validation of the SimE approach.

Aim 4: Validate Noninvasive Estimates of Plasma Radioactivity from a Novel miniPET Scanner.
In parallel to SimE (algorithm/software) development, the investigators will test a
noninvasive method of plasma analysis using hardware. FDG concentration will be measured at
the wrist, arm, ankle or leg with a novel synchronized PET scanner developed by
co-Investigator, Dr. Paul Vaska.

Inclusion Criteria:

1. Age range 21-55 years

2. Capacity to consent

3. Diagnosis of MDD and suffering from a major depressive episode

4. Score of at least 22 on the MADRS

Exclusion Criteria:

1. Significant active physical illness, particularly those that may affect the brain

2. Patients considered at significant risk for suicide

3. Patient is unlikely to be able to tolerate medication washout. Medication washouts
will be supervised by a study physician.

4. For females: Pregnancy, currently lactating; planning to conceive during the course
of study participation, or abortion in the past two months.

5. Blood donation within the past eight weeks.

6. Anticoagulant or anti-platelet treatment, other than aspirin, within 10 days of PET
scanning

7. Current, past, or anticipated significant exposure to radiation, that may include:

- being badged for radiation exposure in the workplace

- participation in nuclear medicine procedures, including research protocols in
the last year*

8. Any MRI contraindications, including history of claustrophobia, metal implants,
pacemaker, metal prostheses, orthodontic appliances, or presence of shrapnel.

9. Bipolar Disorder

10. Lifetime history of psychosis

11. Current drug or alcohol dependence or abuse (excluding nicotine) - within 6 months
for dependence, 2 for abuse; absence of lifetime IV drug use or ecstasy use more than
two times.

12. Currently taking effective antidepressant

13. Prior treatment in current episode with escitalopram (ESC) for ≥ 4 weeks taking ≥ ⅔
PDR maximal dose

14. Prior intolerance of escitalopram (ESC)

15. Use of fluoxetine in past 5 weeks

16. History of head trauma with prolonged loss of consciousness (>10 minutes), or any
neurological condition including stroke or seizure (excluding a single childhood
febrile seizure) or a history of migraine headaches as determined by a physician.

17. Currently on psychoactive medication deemed to be necessary (e.g., anticonvulsants,
antidepressants, antipsychotics, corticosteroids and β-blockers); Use of hypnotics
less than 3X week will be allowed

18. ECT within the past 6 months
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