Anti-inflmmation Treatment in Mood Disorder and Deep Learning Prediction Model

This three-year study will enroll 180 patients with mood disorders (90 patients with major depressive disorder and 90 patients with bipolar disorder) and high pro-inflammatory cytokine levels. They will be randomly assigned to three groups of aspirin, statin and control groups for 12 weeks according to the disease group. The first aim of the study is to compare the efficacy of aspirin and statin in mood disorders. The second aim is to establish a gene-immuno-brain imaging treatment prediction model by deep learning technology, using pretreatment cytokines, neurocognitive function, brain structural/functional connectivity, and telomere length as the predictors.

Study Overview

• Status: Recruiting
• Conditions: Mood Disorder
• Intervention / Treatment: Drug: Aspirin; Drug: Atorvastatin

Detailed Description

Multiple lines of evidence support the pathogenic role of neuro-inflammation in mood disorders. Our team has published a series of papers showing the inflammatory cytokines are related to severity of depressive symptoms, could be biomarkers of clinical outcomes, subtype and mood phase of bipolar disorder. Compared with depressive disorder, bipolar disorder is with more severe inflammatory dysregulation, which correlated to brain structure and functional connectivity abnormality. Treatment non-responders tended to have higher baseline inflammatory markers, suggesting that increased levels of inflammation are contributory to treatment resistance. The clinical studies showed that anti-inflammatory drugs combined with traditional treatments, can improve clinical outcomes, including N-Acetylcysteine, infliximab, pioglitazone, celecoxib, aspirin, omega-3 polyunsaturated fatty acids, minocyclin, statin, aspirin. Among them, aspirin and statin have been used for treatment and prevention of cardiovascular metabolic disorders, which are associated with inflammation dysregulation. The clinical and meta-analysis studies of aspirin and statin have shown significant efficacy and good safety. Therefore, aspirin and statin have better clinical feasibility and rationality for augmentation treatment in mood disorders. However, previous anti-inflammatory research is mostly for individual drug studies, comparative research is still quite lacking. In addition, many studies have suggested anti-inflammatory agents will likely be most useful for the subpopulation of patients whose immune dysfunction is a driving pathogenic factor.

In this study, we will establish a prediction model of anti-inflammatory drugs for mood disorder. Recent advances in deep learning have demonstrated its power to learn and recognize complex nonlinear hierarchical patterns based on largescale empirical data. A deep learning algorithm for classification applications such as medical treatment in personalized medicine is a procedure for choosing the best hypothesis from a set of alternatives that fit a set of observations. Our series of studies have shown that the severity of inflammation related with brain structure and functional connectivity abnormalities; which may be the outcome predictors. Another possible predictor may be the chromosome telomere length. Telomeres are located at the end of chromosomes and maintain normal function of chromosomes. Previous studies have found that short telomere length is associated with mood disorder, as well as the inflammatory dysregulation. Therefore, telomere length may be a predictor of anti-inflammatory treatment. The study will be the first comparative study of anti-inflammatory treatment, and establish gene-immuno-brain imaging individualized treatment prediction model. The results will provide important scientific and clinical empirical data for the inflammatory pathophysiology and treatment of mood disorders.

• Study Type: Interventional
• Enrollment (Anticipated): 180
• Phase: Phase 4

Contacts and Locations

• Study Contact: Name: Ya Mei Bai, M.D. Ph.D.; Phone Number: 279 886-2-28757027; Email: ymbi@mail2000.com.tw

Study Locations

• Taiwan
  • Taipei, Taiwan, 11217
    • Recruiting
    • Taipei Veterans General Hospital
    • Contact: YA-MEI BAI, PhD; Phone Number: 201 28757027; Email: ymbai@vghtpe.gov.tw

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 20 years to 65 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

1. Age between 20 to 65 years old.
2. The baseline pro-inflammatory cytokines level: soluble IL6 receptor (sIL-6)>35,000pg/ml, or CRP>1,500ng/ml, or sTNF-R1>1,000pg/ml.
3. Maintain psychiatric medication for more than three months.
4. Voluntary patients and controls with signed informed consent proved by institutional review board (IRB).

Exclusion Criteria:

1. Patients have used aspirin, statin previously .
2. Patients have gastrointestinal disease, history of gastrointestinal bleeding, hematology coagulation disease, sever liver and renal disease.
3. Patients with schizophrenia, organic brain diseases, mental retardation.
4. Patients with symptoms of substance abuse/dependence (except nicotine dependence) within 3 months.
5. Patients with autoimmune, acute infection and critical medical illnesses .
6. Patients who cannot cooperate the study protocol.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Aspirin	Drug: Aspirin; Aspirin (100mg/day)
No Intervention: non-drug
Active Comparator: Statin	Drug: Atorvastatin; Atorvastatin (20mg/day)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Reduction rate the clinical symptoms after original treatment combined aspirin or atorvastatin.	Treatment Efficacy	baseline, week 4, week 8, week 12

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The T1-weight	The T1-weight will be taken on a 3T MR scanner (Discovery 750, GE).	Once on baseline.
The resting fMRI	The resting fMRI will be taken on a 3T MR scanner (Discovery 750, GE).	Once on baseline.

Collaborators and Investigators

• Sponsor: Taipei Veterans General Hospital, Taiwan
• Investigators: Principal Investigator: Ya Mei Bai, M.D. Ph.D., Taipei Veterans General Hospital, Taiwan

Study record dates

Study Major Dates

• Study Start (Actual): August 24, 2020
• Primary Completion (Anticipated): July 31, 2023
• Study Completion (Anticipated): July 31, 2023

Study Registration Dates

• First Submitted: December 6, 2020
• First Submitted That Met QC Criteria: December 24, 2020
• First Posted (Actual): December 28, 2020

Study Record Updates

• Last Update Posted (Actual): December 28, 2020
• Last Update Submitted That Met QC Criteria: December 24, 2020
• Last Verified: December 1, 2020

More Information

Terms related to this study

• Keywords: depression; bipolar disorder; telomere length; brain imaging; Anti-inflammatory treatment
• Additional Relevant MeSH Terms: Mental Disorders; Pathologic Processes; Disease; Mood Disorders; Physiological Effects of Drugs; Molecular Mechanisms of Pharmacological Action; Peripheral Nervous System Agents; Enzyme Inhibitors; Analgesics; Sensory System Agents; Anti-Inflammatory Agents, Non-Steroidal; Analgesics, Non-Narcotic; Anti-Inflammatory Agents; Antirheumatic Agents; Fibrinolytic Agents; Fibrin Modulating Agents; Platelet Aggregation Inhibitors; Cyclooxygenase Inhibitors; Antipyretics; Antimetabolites; Anticholesteremic Agents; Hypolipidemic Agents; Lipid Regulating Agents; Hydroxymethylglutaryl-CoA Reductase Inhibitors; Aspirin; Atorvastatin
• Other Study ID Numbers: 109-2314-B-010 -050 -MY3

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No