An Exploratory Study Examining Biopsychosocial Markers of Anxiety and Depression
NCT ID: NCT05466851
Last Updated: 2024-04-17
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
RECRUITING
Total Enrollment
200 participants
Study Classification
OBSERVATIONAL
Study Start Date
2023-03-01
Study Completion Date
2032-03-31
Brief Summary
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This research study is studying how thoughts, feelings, surroundings, and individual biology may contribute to why and how people experience anxiety or depression.
We are trying to find out the wide variety of reasons that people may experience anxiety or depression, and why different people are helped by different forms of treatment. We are trying to determine why people stay in treatment, and what factors contribute to a positive or negative response to treatment. These reasons may be due to thoughts, feelings, beliefs, personality, biology, social support network, life events, and barriers to treatment.
A wide range of information about factors that impact anxiety and depression will be included. These include, among others, measures of inflammation, hormone levels, behavior, spoken language, personality, medical history, social determinants of health, and attitudes toward mental health and its treatment.
The study involves psychological and psychiatric treatments in the form of psychotherapy and medication management. The participant will be asked to set specific goals for study treatment, and to provide videos between sessions about relevant medication, emotional, and sleep factors in their life.
In summary, this study will collect biological, psychological, and social factors that may play a role in anxiety and depression. This will inform both individual's diagnosis and treatment and will be used in a later set of analyses that can inform diagnosis and treatment for other individuals who share similar characteristics.
We are trying to find out the wide variety of reasons that people may experience anxiety or depression, and why different people are helped by different forms of treatment. We are trying to determine why people stay in treatment, and what factors contribute to a positive or negative response to treatment. These reasons may be due to thoughts, feelings, beliefs, personality, biology, social support network, life events, and barriers to treatment.
A wide range of information about factors that impact anxiety and depression will be included. These include, among others, measures of inflammation, hormone levels, behavior, spoken language, personality, medical history, social determinants of health, and attitudes toward mental health and its treatment.
The study involves psychological and psychiatric treatments in the form of psychotherapy and medication management. The participant will be asked to set specific goals for study treatment, and to provide videos between sessions about relevant medication, emotional, and sleep factors in their life.
In summary, this study will collect biological, psychological, and social factors that may play a role in anxiety and depression. This will inform both individual's diagnosis and treatment and will be used in a later set of analyses that can inform diagnosis and treatment for other individuals who share similar characteristics.
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Detailed Description
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A Biopsychosocial Approach to Diagnosing and Treating AD and MDD in a Learning Health System
Biochemically-mediated changes related to the stress response and immune system may selectively impact susceptible brain regions or functional networks that correspond with many of the cognitive functions that are often affected clinically during depressive episodes \[1, 2\]. Although MRI-based studies have paved a path toward biological validation of Major Depressive Disorder (MDD), particularly in large-scale studies that have shown promise to detect biological subgroups \[3\], financially prohibitive costs, practical inconveniences related to scanning time and frequency, and a lack of ability to translate a patient's image into a clinically meaningful tool (e.g. aid in clinical diagnosis or treatment prediction) \[4\] are impediments toward clinical application. As a consolation, the next steps in research would be to identify individuals with MDD who have abnormal biochemical profiles, trait-like risk symptoms, or persistent cognitive deficits to establish clearer profiles of overall risk for depression. To make precise estimations of illness risk, the patient's clinical status in the course of illness, and treatment progress through a course of treatment, one must collect data across biopsychosocial dimensions of human behavior utilizing tools that can measure specific behavioral patterns alongside an implementation of statistical methods that can measure subtle changes in stress and immune physiology. This can be achieved through a Learning Health System (LHS) \[5-11\] in order to "harness the power of data and analytics to learn from every patient and feed the knowledge of 'what works best' back to clinicians, public health professionals, patients, and other stakeholders to create cycles of continuous improvement" \[10\]. Compared to traditional approaches to clinical research and medical care delivery, LHSs can provide individualized, streamlined, scalable solutions based on cutting-edge science in real-time.
Current Proposal
The proposed study is a real-world exploratory clinical trial of the diagnosis and treatment for AD and MDD using a combinatorial analytic approach through three phases of clinical care in an outpatient clinical setting. Treatment engagement (phase I) will consist of diagnostic clarification through traditional diagnostic frameworks with symptom identification and characterization using written symptom inventories and scales, spoken language from patients, and audio/video recordings from patients. During the treatment period (phase II), symptoms, spoken language, and audio/video recordings will be obtained during and between in-person weekly clinical sessions. Biological samples will be obtained at time of clinically suspected acute anxiety and/or depression and weekly thereafter until remission (defined as six months symptomatic free). If acute anxiety and/or depression recurs, biological samples will be obtained again on a weekly basis alongside weekly treatment sessions. Upon remission, the patients will move into the remission-maintenance period (phase III), which will consist of biweekly to monthly treatment sessions during which symptoms, spoken language, and audio/video recordings will be obtained during and between clinical sessions.
Data Storage
Data
Clinical data will be managed according to standard policies. Physical (as opposed to electronic) research data will be coded stored in a locked filing cabinet in the investigator's dedicated locked offices to protect subject anonymity. Electronic research data (including imaging data) and electronic personally-identifiable health information (ePHI) will be stored on secured servers within the firewall with access permitted by study personnel only. Data will be stored using codes assigned by the investigators. The key to the code will be kept in a separate, secure area.
Samples
Biological samples are not kept onsite at Singula Medical. Results will be published as group data without the use of specific identify identifiers.
Data and sample sharing plan
Data will be linked with other protocols and can be shared with other Singula investigators, in accordance with participant authorization under the consent form. Samples and data, including genomic data, will be shared with collaborating laboratories at Singula Medical or outside of Singula Medical and/or submitted to Singula Medical-designated repositories and databases. Genomic data will be submitted to the following designated repositories:
Data and samples may also be shared with collaborating laboratories or outside of Singula Medical and/or submitted to designated repositories and databases if consent for sharing was obtained. Repositories receiving data and/or samples from this protocol may be open-access or restricted access.
Samples and data will be stripped of identifiers and may be coded ("de-identified") or unlinked from an identifying code ("anonymized"). When coded data is shared, the key to the code will not be provided to collaborators, but will remain at Singula. Data and samples may be shared with investigators and institutions with an Federalwide Assurance (FWA) for the Protection of Human Subjects, or operating under the Declaration of Helsinki (DoH) and reported at the time of continuing review. Sharing with investigators without an FWA or not operating under the DoH will be submitted for prospective IRB approval. Submissions to NIH-sponsored or supported databases and repositories will be reported at the time of Continuing Review.
Biochemically-mediated changes related to the stress response and immune system may selectively impact susceptible brain regions or functional networks that correspond with many of the cognitive functions that are often affected clinically during depressive episodes \[1, 2\]. Although MRI-based studies have paved a path toward biological validation of Major Depressive Disorder (MDD), particularly in large-scale studies that have shown promise to detect biological subgroups \[3\], financially prohibitive costs, practical inconveniences related to scanning time and frequency, and a lack of ability to translate a patient's image into a clinically meaningful tool (e.g. aid in clinical diagnosis or treatment prediction) \[4\] are impediments toward clinical application. As a consolation, the next steps in research would be to identify individuals with MDD who have abnormal biochemical profiles, trait-like risk symptoms, or persistent cognitive deficits to establish clearer profiles of overall risk for depression. To make precise estimations of illness risk, the patient's clinical status in the course of illness, and treatment progress through a course of treatment, one must collect data across biopsychosocial dimensions of human behavior utilizing tools that can measure specific behavioral patterns alongside an implementation of statistical methods that can measure subtle changes in stress and immune physiology. This can be achieved through a Learning Health System (LHS) \[5-11\] in order to "harness the power of data and analytics to learn from every patient and feed the knowledge of 'what works best' back to clinicians, public health professionals, patients, and other stakeholders to create cycles of continuous improvement" \[10\]. Compared to traditional approaches to clinical research and medical care delivery, LHSs can provide individualized, streamlined, scalable solutions based on cutting-edge science in real-time.
Current Proposal
The proposed study is a real-world exploratory clinical trial of the diagnosis and treatment for AD and MDD using a combinatorial analytic approach through three phases of clinical care in an outpatient clinical setting. Treatment engagement (phase I) will consist of diagnostic clarification through traditional diagnostic frameworks with symptom identification and characterization using written symptom inventories and scales, spoken language from patients, and audio/video recordings from patients. During the treatment period (phase II), symptoms, spoken language, and audio/video recordings will be obtained during and between in-person weekly clinical sessions. Biological samples will be obtained at time of clinically suspected acute anxiety and/or depression and weekly thereafter until remission (defined as six months symptomatic free). If acute anxiety and/or depression recurs, biological samples will be obtained again on a weekly basis alongside weekly treatment sessions. Upon remission, the patients will move into the remission-maintenance period (phase III), which will consist of biweekly to monthly treatment sessions during which symptoms, spoken language, and audio/video recordings will be obtained during and between clinical sessions.
Data Storage
Data
Clinical data will be managed according to standard policies. Physical (as opposed to electronic) research data will be coded stored in a locked filing cabinet in the investigator's dedicated locked offices to protect subject anonymity. Electronic research data (including imaging data) and electronic personally-identifiable health information (ePHI) will be stored on secured servers within the firewall with access permitted by study personnel only. Data will be stored using codes assigned by the investigators. The key to the code will be kept in a separate, secure area.
Samples
Biological samples are not kept onsite at Singula Medical. Results will be published as group data without the use of specific identify identifiers.
Data and sample sharing plan
Data will be linked with other protocols and can be shared with other Singula investigators, in accordance with participant authorization under the consent form. Samples and data, including genomic data, will be shared with collaborating laboratories at Singula Medical or outside of Singula Medical and/or submitted to Singula Medical-designated repositories and databases. Genomic data will be submitted to the following designated repositories:
Data and samples may also be shared with collaborating laboratories or outside of Singula Medical and/or submitted to designated repositories and databases if consent for sharing was obtained. Repositories receiving data and/or samples from this protocol may be open-access or restricted access.
Samples and data will be stripped of identifiers and may be coded ("de-identified") or unlinked from an identifying code ("anonymized"). When coded data is shared, the key to the code will not be provided to collaborators, but will remain at Singula. Data and samples may be shared with investigators and institutions with an Federalwide Assurance (FWA) for the Protection of Human Subjects, or operating under the Declaration of Helsinki (DoH) and reported at the time of continuing review. Sharing with investigators without an FWA or not operating under the DoH will be submitted for prospective IRB approval. Submissions to NIH-sponsored or supported databases and repositories will be reported at the time of Continuing Review.
Conditions
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Depression
Anxiety Disorders
Stress Related Disorder
Study Design
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Observational Model Type
COHORT
Study Time Perspective
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* 18 to 65 years of age.
* Each subject must have a level of understanding sufficient to agree to all required tests and examinations and sign an informed consent document.
* At the initial study enrollment, subjects must have fulfilled DSM-5 criteria for Major Depression, single episode or recurrent.
* At the initial study enrollment, subjects may have fulfilled DSM-5 criteria for an Anxiety Disorder Comorbid Psychiatric Disorders, specifically Anxiety Disorders (Panic Disorder, Specific Phobia, Social Anxiety Disorder, Generalized Anxiety Disorder), Obsessive Compulsive Disorder, or a prior diagnosis of Post-Traumatic Stress Disorder, and/or Attention Deficit Hyperactivity Disorder may be enrolled as per assessment and agreement of evaluating clinicians.
* Agree to participate in clinical treatment (medication management and psychotherapy)
* Each subject must have a level of understanding sufficient to agree to all required tests and examinations and sign an informed consent document.
* At the initial study enrollment, subjects must have fulfilled DSM-5 criteria for Major Depression, single episode or recurrent.
* At the initial study enrollment, subjects may have fulfilled DSM-5 criteria for an Anxiety Disorder Comorbid Psychiatric Disorders, specifically Anxiety Disorders (Panic Disorder, Specific Phobia, Social Anxiety Disorder, Generalized Anxiety Disorder), Obsessive Compulsive Disorder, or a prior diagnosis of Post-Traumatic Stress Disorder, and/or Attention Deficit Hyperactivity Disorder may be enrolled as per assessment and agreement of evaluating clinicians.
* Agree to participate in clinical treatment (medication management and psychotherapy)
Exclusion Criteria
* Serious, unstable illnesses including hepatic, renal, gastroenterologic, respiratory, cardiovascular (including ischemic heart disease), endocrinologic, neurologic, immunologic, or hematologic disease.
* History of head trauma or stroke (also known as a cerebrovascular accident).
* Clinically significant abnormal laboratory tests.
* Subjects with one or more seizures without a clear and resolved etiology or current use of medication known to lower seizure threshold.
* Any use of opioid medication in the past 12 months
* Positive HIV test
* Current psychotic features or a diagnosis of Schizophrenia or any other psychotic disorder as defined in the DSM-IV.
* Subjects with a history of DSM-IV drug or alcohol dependency or abuse (except for caffeine or nicotine dependence) within the preceding 12 months. In addition, subjects who currently are using drugs (except for caffeine or nicotine) must not have used illicit substances or known drugs of abuse in the 2 weeks prior to screen
* Subjects who, in the investigator's judgment, pose a current serious suicidal or homicidal risk.
* History of head trauma or stroke (also known as a cerebrovascular accident).
* Clinically significant abnormal laboratory tests.
* Subjects with one or more seizures without a clear and resolved etiology or current use of medication known to lower seizure threshold.
* Any use of opioid medication in the past 12 months
* Positive HIV test
* Current psychotic features or a diagnosis of Schizophrenia or any other psychotic disorder as defined in the DSM-IV.
* Subjects with a history of DSM-IV drug or alcohol dependency or abuse (except for caffeine or nicotine dependence) within the preceding 12 months. In addition, subjects who currently are using drugs (except for caffeine or nicotine) must not have used illicit substances or known drugs of abuse in the 2 weeks prior to screen
* Subjects who, in the investigator's judgment, pose a current serious suicidal or homicidal risk.
Minimum Eligible Age
18 Years
Maximum Eligible Age
65 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
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Storyline Health
UNKNOWN
Sponsor Role
collaborator
Bruin Health
UNKNOWN
Sponsor Role
collaborator
Singula Institute
OTHER
Sponsor Role
lead
Responsible Party
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Marc Lener
CEO
Responsibility Role
PRINCIPAL_INVESTIGATOR
Principal Investigators
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Marc S Lener, M.D.
Role: PRINCIPAL_INVESTIGATOR
CEO
Locations
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Singula Institute, 353 Lexington Avenue (Room 600)
New York, New York, United States
Site Status
RECRUITING
Countries
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United States
Central Contacts
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Facility Contacts
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References
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Keller AS, Leikauf JE, Holt-Gosselin B, Staveland BR, Williams LM. Paying attention to attention in depression. Transl Psychiatry. 2019 Nov 7;9(1):279. doi: 10.1038/s41398-019-0616-1.
Reference Type
BACKGROUND
Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Casey BJ, Dubin MJ, Liston C. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38. doi: 10.1038/nm.4246. Epub 2016 Dec 5.
Reference Type
BACKGROUND
Zhuo C, Li G, Lin X, Jiang D, Xu Y, Tian H, Wang W, Song X. The rise and fall of MRI studies in major depressive disorder. Transl Psychiatry. 2019 Dec 9;9(1):335. doi: 10.1038/s41398-019-0680-6.
Reference Type
BACKGROUND
Stein BD, Adams AS, Chambers DA. A Learning Behavioral Health Care System: Opportunities to Enhance Research. Psychiatr Serv. 2016 Sep 1;67(9):1019-22. doi: 10.1176/appi.ps.201500180. Epub 2016 May 2.
Reference Type
BACKGROUND
Boes S, Mantwill S, Kaufmann C, Brach M, Bickenbach J, Rubinelli S, Stucki G. Swiss Learning Health System: A national initiative to establish learning cycles for continuous health system improvement. Learn Health Syst. 2018 Jun 21;2(3):e10059. doi: 10.1002/lrh2.10059. eCollection 2018 Jul.
Reference Type
BACKGROUND
Posnack, S., Connecting health and care for the nation: a shared nationwide interoperability roadmap. 2015.
Reference Type
BACKGROUND
Friedman C, Rubin J, Brown J, Buntin M, Corn M, Etheredge L, Gunter C, Musen M, Platt R, Stead W, Sullivan K, Van Houweling D. Toward a science of learning systems: a research agenda for the high-functioning Learning Health System. J Am Med Inform Assoc. 2015 Jan;22(1):43-50. doi: 10.1136/amiajnl-2014-002977. Epub 2014 Oct 23.
Reference Type
BACKGROUND
Related Links
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http://singulainstitute.org/learning-health-system/
The homepage for Singula Institute.
Other Identifiers
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Pro00059104
Identifier Type: -
Identifier Source: org_study_id
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