Precision medicine for treating and preventing suicidality
Inventors
Assignees
United States Government Reprecented By Department Of Veterans Affairs AS • Indiana University Research and Technology Corp • US Department of Veterans Affairs
Publication Number
US-11608532-B2
Publication Date
2023-03-21
Expiration Date
2038-05-14
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Abstract
The present disclosure relates generally to discovery of novel compounds involved in the treatment and prevention of suicidality by bioinformatics drug repurposing using novel genes expression biomarkers involved in suicidality. Disclosed are methods for assessing severity, determining future risk, matching with a drug treatment, and measuring response to treatment, for suicidality. Also disclosed are new methods of use for drugs and natural compounds repurposed for use in preventing and treating suicidality. These methods include computer-assisted methods analyzing the expression of panels of genes, clinical measures, and drug databases. Detailed herein are methods using a universal approach, in everybody, as well as personalized approaches by gender, and by diagnosis. The discovery describes compounds for use in everybody (universal), as well as personalized by gender (males, females), diagnosis (bipolar, depression), gender and diagnosis combined (male bipolar, male depression), male PTSD, male SZ/SZA), and subtypes of suicidality (high anxiety, low mood, combined (affective), and high psychosis (non-affective). Also disclosed are methods for identifying which subjects should be receiving which treatment, using genes expression biomarkers for patient stratification and measuring response to treatment. The disclosure also relates to algorithms, universal and personalized by gender and diagnosis. The algorithms combine biomarkers as well as clinical measures for suicidality and for mental state, in order to identify subjects who are at risk of committing suicide, as well as to track responses to treatments. The disclosure further relates to determining subtypes of suicidality. Such subtypes may delineate groups of individuals that are more homogenous in terms of biology, behavior, and response to treatment.
Core Innovation
The invention provides novel methods and compounds for treating and preventing suicidality by utilizing bioinformatics drug repurposing and novel gene expression biomarkers linked to suicidality. The disclosed methods include assessing severity, predicting future risk, matching patients with drug treatments, and measuring treatment responses for suicidality through computer-assisted analyses of gene expression panels, clinical measures, and drug databases. These methods offer both a universal approach applicable to all individuals and personalized approaches tailored by gender, psychiatric diagnosis, gender and diagnosis combinations, and suicidality subtypes.
The problem being addressed relates to the lack of objective, reliable predictors and tools for assessing and tracking suicidal risk without direct reliance on patient self-reporting. Given that individuals at risk often choose not to disclose suicidal ideation or plans due to stigma or fear of intervention, traditional subjective methods are insufficient. Suicide remains a leading cause of death globally, with limitations in intervention owing to the absence of objective biomarkers or assessments that can effectively predict or monitor suicidality.
The disclosure presents discoveries of compounds and biomarkers that can be used universally or personalized by patient characteristics such as gender and diagnosis. A convergent functional genomics approach integrates gene expression biomarkers with clinical information measures and algorithms to identify risk and stratify patients, and to track responses to treatments. Additionally, subtypes of suicidality based on concurrent mental states (e.g., anxiety, mood, psychosis) are identified to enhance homogeneity in biology and behavior for improved diagnostics and therapeutics.
Claims Coverage
The patent claims several inventive features focusing on methods for treating suicidality through biomarker analysis and personalized medicine approaches.
Method for treating suicidality using biomarker expression levels
A method comprising determining expression levels of panels of blood biomarkers in a subject's sample to assess suicidality risk or presence, including analysis of changes in biomarker levels over multiple occasions.
Use of various biological samples for biomarker quantification
The biomarkers can be quantified from diverse biological samples including tissues, bodily fluids such as cerebrospinal fluid, whole blood, serum, plasma, saliva, or extracts thereof.
Treatment with therapeutic agents selected based on biomarker profiles
Administering therapeutic agents encompassing dissociatives, mood stabilizers, antipsychotics, antidepressants, omega-3 fatty acids, anxiolytics, or cognitive behavioral therapy, targeted based on identified changes in specific biomarkers.
Personalized treatment based on biomarker changes
Specific treatments are matched to subjects exhibiting biomarker changes, such as mood stabilizers for subjects with changes in a defined set of genes including ACP1, BCL2, CRYAB, lithium target genes; antipsychotics for another gene subset; omega-3 fatty acids or antidepressants for other biomarker profiles; anxiolytics or cognitive behavioral therapy for additional markers.
Treatment with repurposed drugs and natural compounds
Treatment may include administration of identified repurposed drugs and natural compounds like chlorogenic acid, ebselen, metformin, piracetam, and others discovered via bioinformatics drug repurposing analyses targeted to the biomarker gene expression signature linked to suicidality.
The claims collectively cover methods for assessing suicidality risk and mitigating suicidality in subjects by quantifying expression levels of specific blood biomarker panels from various biological samples, employing personalized pharmacotherapeutic approaches based on biomarker profiles, and utilizing a wide range of known and repurposed pharmacological agents to tailor treatment.
Stated Advantages
Provides objective and precise identification of individuals at risk for suicidality and methods to monitor treatment response.
Enables prediction of future suicide risk and hospitalization using gene expression biomarkers combined with clinical measures.
Facilitates personalized and universal approaches for treatment tailored by gender, diagnosis, and suicidality subtypes.
Supports discovery and repurposing of novel therapeutics with minimal side effects, including omega-3 fatty acids.
Permits non-invasive, biomarker-based risk stratification without reliance on direct patient self-report, overcoming limitations of subjective assessments.
Documented Applications
Assessment of suicidality severity and early identification of future suicidal risk through gene expression biomarker panels.
Stratification of patients to match with suitable drug treatments and measurement of treatment response in suicidality prevention.
Use of personalized medicine approaches in treating suicidality by gender, psychiatric diagnosis, and specific suicidality subtypes including high anxiety, low mood, combined affective, and psychotic subtypes.
Development of algorithms combining biomarkers and clinical measures (e.g., SASS, CFI-S) for predicting suicidal ideation and hospitalizations due to suicidality.
Bioinformatics drug repurposing and discovery methods for identifying and deploying novel drugs and natural compounds effective for suicidality mitigation.
Generation of risk scores and personalized treatment reports via computer-implemented systems or applications for clinical use in managing suicidality.
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