Suicide risk modification by statin prescriptions in US Veterans with common inflammation-mediated clinical conditions- a controlled, quasi-randomized epidemiological approach
Project Number1I01CX002259-01A2
Former Number1I01CX002259-01A1
Contact PI/Project LeaderPOSTOLACHE, TEODOR T
Awardee OrganizationBALTIMORE VA MEDICAL CENTER
Description
Abstract Text
In addition to their metabolic and cardiovascular protective effects, statins reproducibly engage multiple
pathophysiological factors implicated in suicidal behavior - neuroinflammation, increased oxidative
stress, excitotoxicity, and endothelial dysfunction. Add-on statins have been also reported to improve
therapeutic control in physical and mental health. The Veterans’ persistent higher rates of suicide have
remained unabated challenges and, and thus, demanding new ways of understanding and engaging in
preventative efforts. The long-term objective of our group is to uncovering new modifiable targets, novel
and repurposed treatments in suicide prevention, and identifying individuals at risk who are likely to most
benefit from specific interventions. Macro-epidemiological approaches using electronic medical records
in suicide research are irreplaceable for their capability to account for multiple interactive risk factors,
moderators and confounders, and potential for immediate impact. The primary aims of the proposed
research project are to: 1) Estimate potentiating interactions between traumatic brain injury (TBI), a very
common condition in US Veterans, and inflammation-mediated medical conditions (IMCs: allergies,
infection, and autoimmune conditions), in predicting suicide in US Veterans. Our preliminary data
support hypothesizing synergistic interactions. 2) Estimate the suicide protective effect of sustained vs.
unsustained statin treatment 3) Identify demographic and clinical Veteran characteristics and
pharmacological statin features (dose, lipophilia, potency, duration) conducive to stronger attenuating
effects of statins on suicidal behavior. We will test these hypotheses on a Veterans Health Administration
(VHA) retrospective cohort (individuals with clinical encounters in VA Medical Centers nationwide
beginning in 2004 and followed for 13 years) including 5,446,318 Veterans with 28,749 suicides. The
Cox proportional hazard model will be applied to evaluate the interactions between TBI immune
mediated conditions , with Relative Excess Risk due to Interaction (RERI), the Attributable Proportion
(AP) due to interaction, and the Synergy Index (SI) to test synergism on an additive scale (Aim 1). A Cox
proportional hazard model will also be applied to testing risk attenuation with statins, with propensity
scoring for time-independent confounding and marginal structural Cox proportional hazards (Aim 2).
Finally, we will identify the demographic, clinical (diagnostic codes, medications, laboratory markers of
inflammation (e.g., white blood count) and pharmacological characteristic of Veterans expected to benefit
the most from sustained statin treatment using an aggregate machine learning approach (the
SuperLearner integrative methodology). Considering the high prevalence of TBI history and its ongoing
sequelae,( “a silent epidemic”) , especially in the VA, and confirming their synergistic interaction with
IMCs may contribute to developing suicide risk-attenuating interventions specifically for those
subpopulations. The PI’s preliminary data nested in Danish registers, our team’s piloting confirming
preliminarily a reduction in rates of psychiatric hospitalization (considered a proxy measure of suicide
risk) with statins in US Veterans diagnosed with schizophrenia or bipolar disorder and treated with
psychotropic medication (Appendix 4C), and our successful evaluation of potential heterogenous effects
of an alternative modifiable suicide risk using the specific machine learning algorithms proposed in this
project (Appendix 4B) support our hypotheses, integration, and purpose, and overall, project completion
capability. Using tailored repurposed medications, such as statins, targeting specifically molecular,
cellular and histological mechanisms directly implicated in suicidal behavior, to individuals at risk who
are identified by machine learning to potentially derive the greatest benefit from treatment , may provide
a much-needed breakthrough in suicide risk management and prevention.
Public Health Relevance Statement
New approaches to suicide prevention are much needed in US Veterans, given their persistent increased
suicide risk relative to demographically matched general population. Increasing evidence links suicide with
persistent inflammation, oxidative stress and endothelial dysfunction. These physio-pathological processes are
ameliorated by statins , independent of their known metabolic and cardiovascular benefits. Add on statins have
been reported to be beneficial in mental illness (depression, schizophrenia, cognitive disorders) and for
common immune-mediated conditions (IMCs) - infections, allergies, and autoimmune disease – and traumatic
brain injury (TBI) . These upregulate inflammation, and have been predictively associated with suicidal
behavior. Our three aims are to examine: 1) if IMCs and TBI interact synergistically in elevating suicide risk, 2)
if persistent statin treatment reduces the hazard of suicide and 3) what are the characteristics of the Veterans
who would benefit the most from statin add-on treatment to ameliorate their suicide risk.
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