We have previously proposed, and provide proof for, an approach to help identify blood biomarkers for mood state. Such biomarkers can serve as a basis for objective clinical laboratory tests. We are interested in carrying out similar studies to identify blood biomarkers for psychosis and to address the important scientific and clinical issue of specificity vs. overlap between the biomarkers for these disorders. There are to date no clinical laboratory blood tests for psychosis Given the complex nature of psychotic disorders, the current reliance on patient self-report of symptoms and the clinician's impression on interview of patient is a rate limiting step in deliverig the best possible care with existing treatment modalities, as well as in developing new and improved treatment approaches, including new medications. We propose to identify biomarkers using Convergent Functional Genomics (CFG), an approach developed by us over the last decade, which is based on comprehensive integration of gene expression and genetic data, from human and animal model studies. We have provided proof of principle for this approach helping to identify blood biomarkers for mood disorders (Le- Niculescu et al. 2009)1 and more recently for psychosis (Kurian et al. 2011)2. In that latter work, we have identified a series of high probability blood candidate biomarker genes for psychosis that deserve future scrutiny. A predictive score developed based on a panel of seven top candidate biomarkers for hallucinations (a key symptom for psychosis), shows good sensitivity and moderate specificity, in independent patient cohorts. Our preliminary studies suggest that blood biomarkers may offer an unexpectedly informative window into brain functioning and psychosis state. This exciting preliminary work needs to be carefully extended and replicated in a larger independent cohort, as well as compared to normal controls to derive additional normative data, which is what we propose to do in this project. Moreover, there was overlap between our lists of candidate genes and biomarkers for mood disorders and for psychosis, suggesting that we need to better understand the overlap between bipolar disorder and schizophrenia, and, as a field, explore and refine our integration of nosology with biology. Potential Impact on Veterans Health Care: The development of clinical laboratory blood tests for psychosis will lead to more targeted treatments for veterans affected by psychiatric disorders involving psychotic symptoms, such as schizophrenia and schizoaffective disorder, as well as severe forms of bipolar disorder, depression and PTSD, with improved efficacy and decreased side-effects. This will have an impact on patient health, well-being, safety, quality of life, and independent functioning, as well as decrease hospitalizations and overall health-care costs. Moreover, biomarker profiling may help with assessing response to treatment, risk of relapse, and early intervention efforts to prevent the full-blown development of illness in susceptible individuals.
Objective molecular correlates (biomarkers) of illness and response to treatment would make a significant difference in our ability to diagnose and treat patients with psychiatric disorders, eliminating subjectivity and reliance on patient's self-report of symptoms. Blood gene expression studies have emerged as a particularly interesting area of research in the search for peripheral biomarkers. We propose to conduct such studies in human subjects with schizophrenia, as a way of accelerating the discovery of biomarkers for psychosis symptoms. Moreover, we propose to study how much of an overlap there is between mood disorders and psychosis, at a biomarker level.
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|Niculescu, A B (2016) A brief proposal for improving clinical trials. Mol Psychiatry 21:736-7|
|Rangaraju, S; Levey, D F; Nho, K et al. (2016) Mood, stress and longevity: convergence on ANK3. Mol Psychiatry 21:1037-49|
|Niculescu, A B; Levey, D F; Phalen, P L et al. (2015) Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach. Mol Psychiatry 20:1266-85|
|Niculescu, A B; Levey, D; Le-Niculescu, H et al. (2015) Psychiatric blood biomarkers: avoiding jumping to premature negative or positive conclusions. Mol Psychiatry 20:286-8|
|Levey, D F; Le-Niculescu, H; Frank, J et al. (2014) Genetic risk prediction and neurobiological understanding of alcoholism. Transl Psychiatry 4:e391|
|Le-Niculescu, H; Levey, D F; Ayalew, M et al. (2013) Discovery and validation of blood biomarkers for suicidality. Mol Psychiatry 18:1249-64|
|Niculescu, A B (2013) Convergent functional genomics of stem cell-derived cells. Transl Psychiatry 3:e305|
|Ayalew, M; Le-Niculescu, H; Levey, D F et al. (2012) Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. Mol Psychiatry 17:887-905|
|Le-Niculescu, H; Balaraman, Y; Patel, S D et al. (2011) Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms. Transl Psychiatry 1:e9|