Browsing by Author "Levey, D. F."

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    Discovery and validation of blood biomarkers for suicidality
    (Springer Nature, 2013) Le-Niculescu, H.; Levey, D. F.; Ayalew, M.; Palmer, L.; Gavrin, L. M.; Jain, N.; Winiger, E.; Bhosrekar, S.; Shankar, G.; Radel, M.; Bellanger, E.; Duckworth, H.; Olesek, K.; Vergo, J.; Schweitzer, R.; Yard, M.; Ballew, A.; Shekhar, A.; Sandusky, G. E.; Schork, N. J.; Kurian, S. M.; Salomon, D. R.; Niculescu, A. B., III; Psychiatry, School of Medicine
    Suicides are a leading cause of death in psychiatric patients, and in society at large. Developing more quantitative and objective ways (biomarkers) for predicting and tracking suicidal states would have immediate practical applications and positive societal implications. We undertook such an endeavor. First, building on our previous blood biomarker work in mood disorders and psychosis, we decided to identify blood gene expression biomarkers for suicidality, looking at differential expression of genes in the blood of subjects with a major mood disorder (bipolar disorder), a high-risk population prone to suicidality. We compared no suicidal ideation (SI) states and high SI states using a powerful intrasubject design, as well as an intersubject case-case design, to generate a list of differentially expressed genes. Second, we used a comprehensive Convergent Functional Genomics (CFG) approach to identify and prioritize from the list of differentially expressed gene biomarkers of relevance to suicidality. CFG integrates multiple independent lines of evidence-genetic and functional genomic data-as a Bayesian strategy for identifying and prioritizing findings, reducing the false-positives and false-negatives inherent in each individual approach. Third, we examined whether expression levels of the blood biomarkers identified by us in the live bipolar subject cohort are actually altered in the blood in an age-matched cohort of suicide completers collected from the coroner's office, and report that 13 out of the 41 top CFG scoring biomarkers (32%) show step-wise significant change from no SI to high SI states, and then to the suicide completers group. Six out of them (15%) remained significant after strict Bonferroni correction for multiple comparisons. Fourth, we show that the blood levels of SAT1 (spermidine/spermine N1-acetyltransferase 1), the top biomarker identified by us, at the time of testing for this study, differentiated future as well as past hospitalizations with suicidality, in a live cohort of bipolar disorder subjects, and exhibited a similar but weaker pattern in a live cohort of psychosis (schizophrenia/schizoaffective disorder) subjects. Three other (phosphatase and tensin homolog (PTEN), myristoylated alanine-rich protein kinase C substrate (MARCKS), and mitogen-activated protein kinase kinase kinase 3 (MAP3K3)) of the six biomarkers that survived Bonferroni correction showed similar but weaker effects. Taken together, the prospective and retrospective hospitalization data suggests SAT1, PTEN, MARCKS and MAP3K3 might be not only state biomarkers but trait biomarkers as well. Fifth, we show how a multi-dimensional approach using SAT1 blood expression levels and two simple visual-analog scales for anxiety and mood enhances predictions of future hospitalizations for suicidality in the bipolar cohort (receiver-operating characteristic curve with area under the curve of 0.813). Of note, this simple approach does not directly ask about SI, which some individuals may deny or choose not to share with clinicians. Lastly, we conducted bioinformatic analyses to identify biological pathways, mechanisms and medication targets. Overall, suicidality may be underlined, at least in part, by biological mechanisms related to stress, inflammation and apoptosis.
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    Genetic risk prediction and neurobiological understanding of alcoholism
    (Springer Nature, 2014-05-20) Levey, D. F.; Le-Niculescu, H.; Frank, J.; Ayalew, M.; Jain, N.; Kirlin, B.; Learman, R.; Winiger, E.; Rodd, Z.; Shekhar, A.; Schork, N.; Kiefe, F.; Wodarz, N.; Müller-Myhsok, B.; Dahmen, N.; GESGA Consortium; Nöthen, M.; Sherva, R.; Farrer, L.; Smith, A. H.; Kranzler, H. R.; Rietschel, M.; Gelernter, J.; Niculescu, A. B.; Psychiatry, School of Medicine
    We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) was used to generate a genetic risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse cohort (P=0.023). So did eight other genes from the panel of 11 genes taken individually, albeit to a lesser extent and/or less broadly across cohorts. SNCA, GRM3 and MBP survived strict Bonferroni correction for multiple comparisons. Taken together, these results suggest that our stress-reactive DBP animal model helped to validate and prioritize from the CFG-discovered genes some of the key behaviorally relevant genes for alcoholism. These genes fall into a series of biological pathways involved in signal transduction, transmission of nerve impulse (including myelination) and cocaine addiction. Overall, our work provides leads towards a better understanding of illness, diagnostics and therapeutics, including treatment with omega-3 fatty acids. We also examined the overlap between the top candidate genes for alcoholism from this work and the top candidate genes for bipolar disorder, schizophrenia, anxiety from previous CFG analyses conducted by us, as well as cross-tested genetic risk predictions. This revealed the significant genetic overlap with other major psychiatric disorder domains, providing a basis for comorbidity and dual diagnosis, and placing alcohol use in the broader context of modulating the mental landscape.
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    Mood, stress and longevity: convergence on ANK3
    (Springer Nature, 2016) Rangaraju, S.; Levey, D. F.; Nho, K.; Jain, N.; Andrews, K. D.; Le-Niculescu, H.; Salomon, D. R.; Saykin, A. J.; Petrascheck, M.; Niculescu, A. B.; Psychiatry, School of Medicine
    Antidepressants have been shown to improve longevity in C. elegans. It is plausible that orthologs of genes involved in mood regulation and stress response are involved in such an effect. We sought to understand the underlying biology. First, we analyzed the transcriptome from worms treated with the antidepressant mianserin, previously identified in a large-scale unbiased drug screen as promoting increased lifespan in worms. We identified the most robust treatment-related changes in gene expression, and identified the corresponding human orthologs. Our analysis uncovered a series of genes and biological pathways that may be at the interface between antidepressant effects and longevity, notably pathways involved in drug metabolism/degradation (nicotine and melatonin). Second, we examined which of these genes overlap with genes which may be involved in depressive symptoms in an aging non-psychiatric human population (n=3577), discovered using a genome-wide association study (GWAS) approach in a design with extremes of distribution of phenotype. Third, we used a convergent functional genomics (CFG) approach to prioritize these genes for relevance to mood disorders and stress. The top gene identified was ANK3. To validate our findings, we conducted genetic and gene-expression studies, in C. elegans and in humans. We studied C. elegans inactivating mutants for ANK3/unc-44, and show that they survive longer than wild-type, particularly in older worms, independently of mianserin treatment. We also show that some ANK3/unc-44 expression is necessary for the effects of mianserin on prolonging lifespan and survival in the face of oxidative stress, particularly in younger worms. Wild-type ANK3/unc-44 increases in expression with age in C. elegans, and is maintained at lower youthful levels by mianserin treatment. These lower levels may be optimal in terms of longevity, offering a favorable balance between sufficient oxidative stress resistance in younger worms and survival effects in older worms. Thus, ANK3/unc-44 may represent an example of antagonistic pleiotropy, in which low-expression level in young animals are beneficial, but the age-associated increase becomes detrimental. Inactivating mutations in ANK3/unc-44 reverse this effect and cause detrimental effects in young animals (sensitivity to oxidative stress) and beneficial effect in old animals (increased survival). In humans, we studied if the most significant single nucleotide polymorphism (SNP) for depressive symptoms in ANK3 from our GWAS has a relationship to lifespan, and show a trend towards longer lifespan in individuals with the risk allele for depressive symptoms in men (odds ratio (OR) 1.41, P=0.031) but not in women (OR 1.08, P=0.33). We also examined whether ANK3, by itself or in a panel with other top CFG-prioritized genes, acts as a blood gene-expression biomarker for biological age, in two independent cohorts, one of live psychiatric patients (n=737), and one of suicide completers from the coroner's office (n=45). We show significantly lower levels of ANK3 expression in chronologically younger individuals than in middle age individuals, with a diminution of that effect in suicide completers, who presumably have been exposed to more severe and acute negative mood and stress. Of note, ANK3 was previously reported to be overexpressed in fibroblasts from patients with Hutchinson-Gilford progeria syndrome, a form of accelerated aging. Taken together, these studies uncover ANK3 and other genes in our dataset as biological links between mood, stress and longevity/aging, that may be biomarkers as well as targets for preventive or therapeutic interventions. Drug repurposing bioinformatics analyses identified the relatively innocuous omega-3 fatty acid DHA (docosahexaenoic acid), piracetam, quercetin, vitamin D and resveratrol as potential longevity promoting compounds, along with a series of existing drugs, such as estrogen-like compounds, antidiabetics and sirolimus/rapamycin. Intriguingly, some of our top candidate genes for mood and stress-modulated longevity were changed in expression in opposite direction in previous studies in the Alzheimer disease. Additionally, a whole series of others were changed in expression in opposite direction in our previous studies on suicide, suggesting the possibility of a "life switch" actively controlled by mood and stress.
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    Towards precision medicine for anxiety disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs
    (Springer Nature, 2023) Roseberry, K.; Le-Niculescu, H.; Levey, D. F.; Bhagar, R.; Soe, K.; Rogers, J.; Palkowitz, S.; Pina, N.; Anastasiadis, W. A.; Gill, S. S.; Kurian, S. M.; Shekhar, A.; Niculescu, A. B.; Psychiatry, School of Medicine
    Anxiety disorders are increasingly prevalent, affect people's ability to do things, and decrease quality of life. Due to lack of objective tests, they are underdiagnosed and sub-optimally treated, resulting in adverse life events and/or addictions. We endeavored to discover blood biomarkers for anxiety, using a four-step approach. First, we used a longitudinal within-subject design in individuals with psychiatric disorders to discover blood gene expression changes between self-reported low anxiety and high anxiety states. Second, we prioritized the list of candidate biomarkers with a Convergent Functional Genomics approach using other evidence in the field. Third, we validated our top biomarkers from discovery and prioritization in an independent cohort of psychiatric subjects with clinically severe anxiety. Fourth, we tested these candidate biomarkers for clinical utility, i.e. ability to predict anxiety severity state, and future clinical worsening (hospitalizations with anxiety as a contributory cause), in another independent cohort of psychiatric subjects. We showed increased accuracy of individual biomarkers with a personalized approach, by gender and diagnosis, particularly in women. The biomarkers with the best overall evidence were GAD1, NTRK3, ADRA2A, FZD10, GRK4, and SLC6A4. Finally, we identified which of our biomarkers are targets of existing drugs (such as a valproate, omega-3 fatty acids, fluoxetine, lithium, sertraline, benzodiazepines, and ketamine), and thus can be used to match patients to medications and measure response to treatment. We also used our biomarker gene expression signature to identify drugs that could be repurposed for treating anxiety, such as estradiol, pirenperone, loperamide, and disopyramide. Given the detrimental impact of untreated anxiety, the current lack of objective measures to guide treatment, and the addiction potential of existing benzodiazepines-based anxiety medications, there is a urgent need for more precise and personalized approaches like the one we developed.
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    Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs
    (Springer Nature, 2019-04) Niculescu, A. B.; Le-Niculescu, H.; Levey, D. F.; Roseberry, K.; Soe, K. C.; Rogers, J.; Khan, F.; Jones, T.; Judd, S.; McCormick, M.A.; Wessel, A. R.; Williams, A.; Kurian, S. M.; White, F. A.; Psychiatry, School of Medicine
    We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic.
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    Towards precision medicine for stress disorders: diagnostic biomarkers and targeted drugs
    (Springer Nature, 2019-03-12) Le-Niculescu, H.; Roseberry, K.; Levey, D. F.; Rogers, J.; Kosary, K.; Prabha, S.; Jones, T.; Judd, S.; McCormick, M. A.; Wessel, A. R.; Williams, A.; Phalen, P. L.; Mamdani, F.; Sequeira, A.; Kurian, S. M.; Niculescu, A. B.; Department of Psychiatry, School of Medicine
    The biological fingerprint of environmental adversity may be key to understanding health and disease, as it encompasses the damage induced as well as the compensatory reactions of the organism. Metabolic and hormonal changes may be an informative but incomplete window into the underlying biology. We endeavored to identify objective blood gene expression biomarkers for psychological stress, a subjective sensation with biological roots. To quantify the stress perception at a particular moment in time, we used a simple visual analog scale for life stress in psychiatric patients, a high-risk group. Then, using a stepwise discovery, prioritization, validation, and testing in independent cohort design, we were successful in identifying gene expression biomarkers that were predictive of high-stress states and of future psychiatric hospitalizations related to stress, more so when personalized by gender and diagnosis. One of the top biomarkers that survived discovery, prioritization, validation, and testing was FKBP5, a well-known gene involved in stress response, which serves as a de facto reassuring positive control. We also compared our biomarker findings with telomere length (TL), another well-established biological marker of psychological stress and show that newly identified predictive biomarkers such as NUB1, APOL3, MAD1L1, or NKTR are comparable or better state or trait predictors of stress than TL or FKBP5. Over half of the top predictive biomarkers for stress also had prior evidence of involvement in suicide, and the majority of them had evidence in other psychiatric disorders, providing a molecular underpinning for the effects of stress in those disorders. Some of the biomarkers are targets of existing drugs, of potential utility in patient stratification, and pharmacogenomics approaches. Based on our studies and analyses, the biomarkers with the best overall convergent functional evidence (CFE) for involvement in stress were FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1. Moreover, the biomarker gene expression signatures yielded leads for possible new drug candidates and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and betulin. Our work may lead to improved diagnosis and treatment for stress disorders such as PTSD, that result in decreased quality of life and adverse outcomes, including addictions, violence, and suicide.