| 1 | Mol. Psychiatry 2015 Nov 20: 1266-85 |
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| PMID | 26283638 |
| Title | Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach. |
| Abstract | Worldwide, one person dies every 40 seconds by suicide, a potentially preventable tragedy. A limiting step in our ability to intervene is the lack of objective, reliable predictors. We have previously provided proof of principle for the use of blood gene expression biomarkers to predict future hospitalizations due to suicidality, in male bipolar disorder participants. We now generalize the discovery, prioritization, validation, and testing of such markers across major psychiatric disorders (bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) in male participants, to understand commonalities and differences. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation and high suicidal ideation states (n=37 participants out of a cohort of 217 psychiatric participants followed longitudinally). We then used a convergent functional genomics (CFG) approach with existing prior evidence in the field to prioritize the candidate biomarkers identified in the discovery step. Next, we validated the top biomarkers from the prioritization step for relevance to suicidal behavior, in a demographically matched cohort of suicide completers from the coroner's office (n=26). The biomarkers for suicidal ideation only are enriched for genes involved in neuronal connectivity and schizophrenia, the biomarkers also validated for suicidal behavior are enriched for genes involved in neuronal activity and mood. The 76 biomarkers that survived Bonferroni correction after validation for suicidal behavior map to biological pathways involved in immune and inflammatory response, mTOR signaling and growth factor regulation. mTOR signaling is necessary for the effects of the rapid-acting antidepressant agent ketamine, providing a novel biological rationale for its possible use in treating acute suicidality. Similarly, MAOB, a target of antidepressant inhibitors, was one of the increased biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would show broad-spectrum predictive ability across psychiatric diagnoses. Indeed, the UP-Suicide was able to predict suicidal ideation across psychiatric diagnoses with an AUC of 92%. For bipolar disorder, it predicted suicidal ideation with an AUC of 98%, and future hospitalizations with an AUC of 94%. Of note, both types of tests we developed (blood biomarkers and clinical information apps) do not require asking the individual assessed if they have thoughts of suicide, as individuals who are truly suicidal often do not share that information with clinicians. We propose that the widespread use of such risk prediction tests as part of routine or targeted healthcare assessments will lead to early disease interception followed by preventive lifestyle modifications and proactive treatment. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 2 | Int. J. Neuropsychopharmacol. 2016 Feb -1: -1 |
| PMID | 26902949 |
| Title | The Expression of the Suicide-Associated Gene SKA2 Is Decreased in the Prefrontal Cortex of Suicide Victims but Not of Nonsuicidal Patients. |
| Abstract | Recent study of genome-wide DNA methylation profiling in the postmortem brain of suicidal and nonsuicidal subjects found that gene expression of spindle and kinetochore associated complex subunit 2 (SKA2) is decreased in the postmortem brain of suicide victims compared with nonsuicidal, nonpsychiatric control subjects. To determine if decreased SKA2 is specific to suicide and independent of diagnosis, we determined gene and protein expression of SKA2 in the prefrontal cortex obtained from suicide victims (n= 52), nonsuicidal psychiatric subjects (n= 27), and normal controls (n= 24). We determined gene expression by quantitative PCR technique and protein expression by Western blot. The postmortem brain samples were obtained from the Maryland Psychiatric Research Center. We found that protein and gene expression of SKA2 was significantly reduced in the prefrontal cortex of suicide victims compared with normal control subjects and nonsuicidal patients. We also found that SKA2 protein and gene expression in depressed suicide victims, schizophrenic suicide victims, and suicide victims with substance abuse and/or conduct disorders was significantly decreased compared with normal control subjects and also with nonsuicidal depressed or schizophrenic subjects. This study shows that decreased gene and protein expression of SKA2 observed in the prefrontal cortex of suicide victims is specific to suicide, which was not observed in the brain of nonsuicidal patients. It also indicates reduced SKA2 expression in suicide is independent of psychiatric diagnosis, since it is observed in all diagnostic groups studied. Therefore, SKA2 may be a potential biomarker for suicide. |
| SCZ Keywords | schizophrenia, schizophrenic |
| 3 | Int. J. Neuropsychopharmacol. 2016 Feb -1: -1 |
| PMID | 26902949 |
| Title | The Expression of the Suicide-Associated Gene SKA2 Is Decreased in the Prefrontal Cortex of Suicide Victims but Not of Nonsuicidal Patients. |
| Abstract | Recent study of genome-wide DNA methylation profiling in the postmortem brain of suicidal and nonsuicidal subjects found that gene expression of spindle and kinetochore associated complex subunit 2 (SKA2) is decreased in the postmortem brain of suicide victims compared with nonsuicidal, nonpsychiatric control subjects. To determine if decreased SKA2 is specific to suicide and independent of diagnosis, we determined gene and protein expression of SKA2 in the prefrontal cortex obtained from suicide victims (n= 52), nonsuicidal psychiatric subjects (n= 27), and normal controls (n= 24). We determined gene expression by quantitative PCR technique and protein expression by Western blot. The postmortem brain samples were obtained from the Maryland Psychiatric Research Center. We found that protein and gene expression of SKA2 was significantly reduced in the prefrontal cortex of suicide victims compared with normal control subjects and nonsuicidal patients. We also found that SKA2 protein and gene expression in depressed suicide victims, schizophrenic suicide victims, and suicide victims with substance abuse and/or conduct disorders was significantly decreased compared with normal control subjects and also with nonsuicidal depressed or schizophrenic subjects. This study shows that decreased gene and protein expression of SKA2 observed in the prefrontal cortex of suicide victims is specific to suicide, which was not observed in the brain of nonsuicidal patients. It also indicates reduced SKA2 expression in suicide is independent of psychiatric diagnosis, since it is observed in all diagnostic groups studied. Therefore, SKA2 may be a potential biomarker for suicide. |
| SCZ Keywords | schizophrenia, schizophrenic |