Addiction, Opioid, Opioid Use Disorder
Conditions
Keywords
genomics, artificial intelligence, microbiome, opioid use disorder, opioid addiction
Brief summary
The primary goal of this proposal is to validate a novel genomic and microbiome predictive model that may be used to assess a person's risk of developing opioid use disorder (OUD). The following will be tested: (1) MODUS (Measuring risk for Opioid use Disorder Using SNPs), which is a genomic panel consisting of a set number of proven single nucleotide polymorphisms (SNP) that utilizes machine learning to determine an individual's risk; and (2) MICROUD (MICRObiome for Opioid Use Disorder), which will be a novel microbiome prediction panel for OUD risk. MODUS and MICROUD will be developed using existing public datasets with genomic and microbiome data (e.g., All of Us, Human Microbiome Project). During development of these predictive models, in parallel, an external prospective validation cohort will be recruited consisting of subjects from the University of California, San Diego, Veteran Affairs of San Diego, and Veteran Affairs of Palo Alto (each site with separate IRB). The hypothesis is that MODUS and MICROUD will have high predictive potential for identifying high risk patients for OUD.
Detailed description
The primary goal of this proposal is to validate a novel genomic and microbiome predictive model that may be used to assess a person's risk of developing opioid use disorder (OUD). The following will be tested: (1) MODUS (Measuring risk for Opioid use Disorder Using SNPs), which is a genomic panel consisting of a set number of proven single nucleotide polymorphisms (SNP) that utilizes machine learning to determine an individual's risk; and (2) MICROUD (MICRObiome for Opioid Use Disorder), which will be a novel microbiome prediction panel for OUD risk. MODUS and MICROUD will be developed using existing public datasets with genomic and microbiome data (e.g., All of Us, Human Microbiome Project). During development of these predictive models, in parallel, an external prospective validation cohort will be recruited consisting of subjects from the University of California, San Diego, Veteran Affairs of San Diego, and Veteran Affairs of Palo Alto (each site with separate IRB). The hypothesis is that MODUS and MICROUD will have high predictive potential for identifying high risk patients for OUD. Specific Aim 1. Validate a novel genomic predictive panel assay - termed MODUS - in a prospective observational study that aims to recruit 300 subjects (\ 200 from UCSD and VA San Diego) with a history of OUD. This genomic panel will be developed separately but then validated on the study population. Healthy control data will be used from a publicly-available de-identified genomic dataset (All of Us Research Program) . Specific Aim 2. Validate a novel microbiome predictive panel assay - termed MICROUD - in a prospective observational study that aims to recruit 300 subjects (\ 200 from UCSD and VA San Diego) with a history of OUD. This microbiome panel will be developed separately but then validated on the study population. Healthy control data will be used from a publicly-available de-identified microbiome dataset (Human Microbiome Project).
Interventions
None listed
Sponsors
University of California, San Diego
VA Palo Alto Health Care System
San Diego Veterans Healthcare System
Study design
Observational model
CASE_ONLY
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* diagnosis of OUD (active or in remission) defined by the DSM-5 criteria * age ≥ 18 years old
Exclusion criteria
* inability to participate independently with the study (i.e. dementia) * chronic opioid use that is not consistent with a diagnosis of OUD * patients that are pregnant * children * institutionalized individuals * non-English speaking subjects as there are several surveys without appropriate translation and with sensitive information (e.g., questions about mental health and history of drug use) that is required to complete the study.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| opioid use disorder at baseline based on the DSM-5 criteria | baseline | risk of opioid use disorder based on genomics, social determinants of health, microbiome, and other clinical data. Patients with OUD will be enrolled and compared to healthy controls using data from external datasets such as NIH All of Us Research Program. Diagnosis of opioid use disorder will be based on the DSM-5 criteria for opioid use disorder |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| response to opioid use disorder treatment after 6 months from baseline based on the DSM-5 criteria | 6 months | prediction of response to opioid use disorder treatment. Remission from opioid use disorder will be based on DSM-5 criteria for remission from substance use disorder |
| opioid use disorder remission after 6 months from baseline based on the DSM-5 criteria for remission | 6 months | prediction of remission of opioid use disorder based on the DSM-5 criteria for remission from substance use disorder |
| severity of opioid use disorder at baseline based on the DSM-5 criteria for opioid use disorder | baseline | prediction of severity of opioid use disorder based on the DSM-5 criteria for opioid use disorder |
| co-substance use at baseline | baseline | risk of developing co-substance use disorder based on DSM-5 criteria for substance use disorders |
| Relapse to opioid use disorder after 6 months from baseline | 6 months | risk of relapse to opioid use disorder based on DSM-5 criteria for opioid use disorder |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORRodney A Gabriel, MD
University of California, San Diego
Outcome results
None listed