Eventhestrongestofindividualriskfactorsarepoorpredictorsofsuicideattempts.Manyriskfactorsrelyon subjectiveorself-reportedmeasuresandunderreportingcontributestopoorpredictionaccuracy.Inthemidst oftheongoingVeteransuicidecrisis,weclearlyneednew,objectivepredictorsofriskthatcanbeimplemented acrosstheVAsystem.Previousfindingsindicatethatbehavioralandneuroimagingcorrelatesofdecision- makingandcognitivecontrolarepromising,objectivemarkersofsuicidalrisk.Thoughintriguing,thesefindings arefromresearchconductedprimarilyindepressedcivilians.Itisunknownifthesepotentialmarkersofsuicide riskwillgeneralizetoatransdiagnosticsampleofVeterans.TheprimaryresearchobjectiveofthisCDA-2isto evaluatewhetherstructuralneuroimaging,andfunctionalneuroimagingduringdecision-makingandcognitive controltaskscanbeusedtoidentifybrain-behaviorcorrelatesofsuicidalthoughtsandbehaviorsinVeterans. Suicidalthoughtsandbehaviorsareassociatedwithshort-sighted,maladaptive,decision-makingthatis accompaniedbydifferencesinstriatal-prefrontalrewardcircuitry.However,studiesthathavecompared decision-makingtaskperformancebetweenindividualswhohavemademoreorganized,lethalattemptsat self-harmvs.thosemakinglessseriousattemptshaveidentifieddifferencesintheirbehaviorthatmaysupply morenuancedinformationaboutsuicidalseverity.Interestingly,thedecision-makingofseriousattemptersis actuallylessimpulsive.Infact,decisionmakinginseriousattemptersislessimpulsiveevenrelativetohealthy controls.Thisimpliesthatagreatercapacityforcognitivecontrolmayfacilitate,ratherthanprotectagainst, harminsuicidalindividuals.Thesepotentialobjectivemarkersofsuicidalthoughtsandbehaviorsandsuicidal riskseverityarepromisinganddemandfurtherevaluation.Theproposedbehavioralandneuroimaging methodologies(diffusionimaging,morphometryanalyses,univariateandfunctionalconnectivityneuroimaging) includedinthisproposalhavebeensuccessfullyappliedbythecandidate,acognitiveneuroscientist,in previouspublishedwork.Thecandidate?sexploratoryresearchobjectiveistoapplymachinelearning algorithmstoablendeddatasetofparticipants?electronichealthdataandneurocognitivemarkersina preliminarypredictivemodelingproject.Thisexploratoryobjectivewillprovidefoundationaldataforfuture Merit-fundedworkfocusedonthedevelopmentofclinicallyimplementablesuicideriskpredictiontools.Though theproposedneurocognitiveresearchhasthepotentialtoimprovetheeffectivenessofsuicidescreeningand treatment,thecandidateacknowledgesthatalltoooften,insightsfromneurosciencefailtoimproveclinical carebecausefewneuroscientistshavetheclinicalperspectiveneededtotranslatemechanisticknowledgeinto clinicalinnovations.TheprotectedtimefundedbythisCDAawardwillallowthecandidatetoparticipatein activitiesimpartingauniquecombinationofskillsandperspectivesthatwillallowthecandidatetobridgebasic andclinicalscienceintheserviceofreducingVeteransuicide.TheCDAtrainingplanbuildscompetenciesin threeareas:1)methodologiesandpracticalskillsforsuicideresearch,2)psychiatricassessmentandclinical perspective,and3)traininginbioinformaticsandmachinelearningmethodologies.Thecandidateiswell- establishedwithintheVAsystemholdingaHealthScienceSpecialistpositionsince2015.Thecandidate?s mentorshipteamiscomprisedprimarilyofVAclinician-scientistsactivelyworkingwithsuicidalorhigh-risk populationsandarewell-qualifiedtomentorthecandidatetowardthecareergoalofbecomingaleaderin translationalVeteransuicideresearch.

Public Health Relevance

RecentVeteransarenowmorelikelytodiebysuicidethancombat.TheproposedCDA-2researchwill generatenovelbiologicalandbehavioralmakersofsuiciderisk,andwillconductapreliminarydemonstration oftheiruseinpredictivemodelsofsuicidalthoughtsandbehaviors.Methodsusedtodefineriskfactorsare implementedinatransdiagnosticVeteransample.Importantly,definingriskfactorsindependentofpsychiatric populationwillincreasegeneralizabilityofstudyfindingstoawiderVeteranpopulation.Thesenovelsuicide riskfactorswillidentifyhigh-riskVeteransthatmaynothavebeenidentifiedbytraditionalsuicideassessment methods.ThismeansthatmoreVeteransatriskforsuicidewillreceivelife-savinginterventions,thus,this researchisconsistentwiththeVA?smissiontocombatVeteransuicide.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Veterans Administration (IK2)
Project #
5IK2CX001824-02
Application #
9842276
Study Section
Special Emphasis Panel (ZRD1)
Project Start
2019-01-01
Project End
2023-12-31
Budget Start
2020-01-01
Budget End
2020-12-31
Support Year
2
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Providence VA Medical Center
Department
Type
DUNS #
182465745
City
Providence
State
RI
Country
United States
Zip Code