Predicting suicidality using a combined genomic and clinical risk assessment
Inventors
Assignees
Indiana University Research and Technology Corp • US Department of Veterans Affairs
Publication Number
US-10991449-B2
Publication Date
2021-04-27
Expiration Date
2036-06-10
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Abstract
Biomarkers and methods for screening expression levels of the biomarkers for predicting suicidality (referred herein to suicidal ideation and actions, future hospitalizations and suicide completion) are disclosed. Also disclosed are quantitative questionnaires and mobile applications for assessing affective state and for assessing socio-demographic and psychological suicide risk factors, and their use to compute scores that can predict suicidality. Finally, an algorithm that combines biomarkers and computer apps for identifying subjects who are at risk for committing suicide is disclosed, as well as methods to mitigate and prevent suicidality based on the biomarkers and computer apps.
Core Innovation
The invention discloses biomarkers and methods for screening expression levels of these biomarkers in blood as objective measures for predicting suicidality, which includes suicidal ideation, suicidal acts, future hospitalizations due to suicidality, and suicide completion. The approach includes quantitative questionnaires and mobile applications for assessing affective states and socio-demographic and psychological suicide risk factors, which are used to compute scores predictive of suicidality. An algorithm combining biomarker data and computer app scores is employed to identify individuals at risk for suicide, and methods for mitigating and preventing suicidality based on these biomarkers and apps are also provided.
The problem being addressed is the critical lack of objective, reliable tools to assess and track suicidality without relying on direct self-report from subjects, who often do not disclose suicidal thoughts due to fear of stigma or hospitalization. Current clinical practice relies on subjective assessments and non-systematic methods, which are inadequate. There exists a need for quantitative and objective methods to predict and monitor suicidal risk states, to allow timely intervention before suicide attempts or completions.
The disclosed methods increase predictive accuracy for identifying individuals at risk of suicide and future hospitalizations due to suicidality. They involve obtaining and comparing expression levels of blood biomarkers in a subject's sample against reference levels to detect differences indicative of suicidal risk. Clinical assessments of mood, anxiety, socio-demographic, and psychological suicide risk factors are obtained via computer-implemented methods using questionnaires and mobile apps (such as SASS and CFI-S). The integration of biomarker data with clinical information through an algorithm provides a comprehensive universal predictor for suicidality, facilitating early detection and intervention.
Claims Coverage
The claims include two independent claims directed to methods for assessing and mitigating suicidality in male and female subjects respectively, featuring the use of specific panels of blood biomarkers and administration of treatment based on biomarker expression differences.
Method for assessing and mitigating suicidality in male subjects using specific biomarker panels
The method involves determining expression levels of at least a first panel of increased expression blood biomarkers (such as SLC4A4, CADM1, DTNA, SAT1, IL6, among others) or a second panel of decreased expression blood biomarkers (such as SKA2, CLIP4, KIF2C, KLHDC3, and others) from a sample of a male subject, identifying suicidality based on increased or decreased expression relative to references, and administering a drug to treat suicidality in the identified subject.
Method for assessing and mitigating suicidality in female subjects using specific biomarker panels
The method involves determining expression levels of at least a first panel of increased expression blood biomarkers (such as EPB41L5, HTRA1, DPCD, GTF3C3, PER1, among others) or a second panel of decreased expression blood biomarkers (such as PIK3C3, ALDH3A2, ACTR3, BCL2, MOB3B, CSNK1A1, and others) from a sample of a female subject, identifying suicidality based on increased or decreased expression relative to references, and administering a drug to treat suicidality in the identified subject.
Use of biomarker panel scores compared to references for identifying suicidality
The claims specify that identifying suicidality further comprises comparing a biomarker panel score of the subject to a biomarker panel score of a reference to determine risk.
Treatment administration using specified drugs
The claims include administering drugs selected from dissociants, mood stabilizers, antipsychotics, antidepressants, omega-3 fatty acids, and specific drugs such as ketamine, lithium, clozapine, chlorpromazine, selegiline, fluoxetine, trimipramine, docosahexaenoic acid, and others to subjects identified with suicidality based on biomarker expression.
Subject diagnosis including psychiatric disorders
The claims specify that the subject may have a psychiatric diagnosis including bipolar disorder, major depressive disorder, schizophrenia, schizoaffective disorder, anxiety disorders, and post-traumatic stress disorder.
The independent claims capture methods of determining suicidality risk in male and female subjects by measuring expression levels of gender-specific panels of blood biomarkers, identifying suicidality based on these levels compared to references, and administering appropriate treatments. The claims also include comparison of biomarker panel scores to references and use of a variety of pharmaceutical and nutraceutical agents for mitigation, covering subjects with various psychiatric disorders.
Stated Advantages
Provides objective, reliable prediction and tracking of suicidality without directly asking subjects about suicidal thoughts, overcoming limitations of self-reporting.
Enables early identification of individuals at risk for suicide and future hospitalization due to suicidality, allowing timely intervention.
Combines genomic biomarker data with quantitative clinical assessments (via apps and questionnaires) to improve predictive accuracy versus individual methods alone.
Offers a standardized, systematic approach integrating biological and psycho-social risk factors.
Facilitates monitoring of treatment response and potentially guides personalized treatment selection based on biomarker profiles.
Documented Applications
Screening and prediction of suicidality including suicidal ideation, suicidal acts, future hospitalizations for suicidality, and suicide completion.
Use in clinical settings for early identification of suicide risk in subjects with psychiatric disorders such as bipolar disorder, major depressive disorder, schizophrenia, schizoaffective disorder, and post-traumatic stress disorder.
Use of quantitative questionnaires and mobile applications (SASS, CFI-S) for assessing affective state and socio-demographic/psychological suicide risk factors for risk assessment.
Combination of blood biomarker testing and clinical information apps as a universal predictor (UP-Suicide) of suicidality.
Mitigation and prevention of suicidality by administering treatments including drugs and lifestyle modifications based on biomarker expression levels.
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