A recent publication focused on biomarkers of future suicidal behaviors identifies several genes expressed in high-risk states among four samples. We discuss the implications of this study as well as the current state of research regarding biomarkers of suicidal behavior

Baca-García, Enrique

Blasco-Fontecilla, Hilario

Giner Jiménez, Lucas

Lopez Castroman, Jorge

Oquendo, María

English

PubMed

idUS. Depósito de Investigación Universidad de Sevilla

INVITED COMMENTARYPredicting Suicidal Behavior: Are We Reallythat Far Along? Comment on “Discovery and Validationof Blood Biomarkers for Suicidality”Hilario Blasco-Fontecilla & Jorge Lopez-Castroman &Lucas Giner & Enrique Baca-Garcia & Maria A. OquendoPublished online: 20 November 2013# Springer Science+Business Media New York 2013Abstract A recent publication focused on biomarkers offuture suicidal behaviors identifies several genes expressedin high-risk states among four samples. We discuss the impli-cations of this study as well as the current state of researchregarding biomarkers of suicidal behavior.Keywords Suicidal behavior . Prediction . BiomarkersMr. Marks , by mandate of the District of ColumbiaPrecrime Division , I ’m placing you under arrest forthe future murder of Sarah Marks and Donald Dubinthat was to take place today, April 22 at 0800 hours andfour minutes .“Minority Report”, Steven Spielberg (2002)Predicting future behavior is a long-standing goal and amatter of particular interest for behavioral scientists. Theprediction of suicidal behavior, from minimally harmful tolethal suicide attempts, is particularly challenging because, thusfar, it depends on the subjective reports of the individual at risk.However, the elevated expression of certain RNA biomarkersmight help to predict future suicidal behavior according to arecent paper published in Molecular Psychiatry by Le-Niculescu and colleagues [1]. Their findings aim to take uscloser to an objective measure of suicide risk. The relevance ofsuch studies is sustained by other reports showing that suicidalsubjects often do not disclose their suicidal thoughts [2, 3], withmyriad underlying reasons –i.e., hospitalization, fear of stigma,thwarted plans– for hiding this information [1].The low base rate of attempted and completed suicide [4],and the relatively poor performance of models based on arestricted number of variables [5] are major difficulties in theprediction of suicidal behavior. To date, clinical factors (notablydepression and alcoholism), previous suicide attempts, and lifeevents are among the best predictive factors for suicidal behav-ior [6–8]. Some biological factors have also been closely asso-ciated with suicide risk, particularly reduced concentrations ofthe serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA)in cerebrospinal fluid (CSF) and abnormal results in the dexa-methasone suppression test (DST) [9]. Given that biomarkersshould be simple to obtain, non-invasive, and inexpensive,recent research has focused on other putative biomarkers ofsuicidal behavior such as reduced cholesterol, omega 3 fattyacids [10], or brain-derived neurotrophic factor (BDNF) inserum or plasma [11].An essential issue is that biomarker studies must use notonly excellent biological approaches but robust phenotypes.Indeed, given that for complex behaviors such as suicidalbehavior, it is anticipated that only biomarkers of small effectsizes will be in play, identification is likely to only be attainedwhen reliable, valid clinical characterization is used. This is ahigh bar and one of the reasons why identification of bio-markers, thus far, has been disappointing.H. Blasco-FontecillaVillalba Mental Health Center, Department of Psychiatry,IDIPHIM-Puerta de Hierro University Hospital, CIBERSAM,Madrid, SpainJ. Lopez-Castroman : E. Baca-GarciaDepartment of Psychiatry, IIS-Jimenez Diaz Foundation,Universidad Autonoma de Madrid. CIBERSAM, Madrid, SpainJ. Lopez-CastromanCHRU Montpellier and INSERM unit 1061, Montpellier, FranceL. GinerDepartment of Psychiatry, University of Seville, Seville, SpainE. Baca-Garcia :M. A. Oquendo (*)Department of Psychiatry, New York State Psychiatric Institute,Columbia University, 1051 Riverside Drive, Unit 42, New York,NY 10032, USAe-mail: mao4@columbia.eduCurr Psychiatry Rep (2013) 15:424DOI 10.1007/s11920-013-0424-xLe-Niculescu and colleagues explored blood gene expres-sion biomarkers for suicidality in four small male cohorts: i)one discovery cohort of live bipolar subjects (n=9); ii) oneage-matched cohort of suicides from the coroner’s office (n=9); and iii) two prospective follow-up cohorts with subjectsaffected by bipolar disorder (n=42) and psychosis (n=46) [1].Suicidal behavior in the live subjects was identified using thesuicide-related item of the Hamilton Depression Rating Scale(HDRS). Suicide was determined by the coroner. Hospitaliza-tion for suicidal behavior was determined through chart re-view. Although the higher scores on the HDRS suicide-relateditem confound different suicidal behaviors (a score of 3 canmean “gesture” or pronounced suicidal ideation), the scoreswere used to classify individuals as having no suicidal idea-tion (SI) or high SI. Those with low and high scores werecompared to identify potential biomarkers in the discoverycohort. Putative relevant biomarkers related to suicidalitywere then validated in the cohort of suicides. After correctionfor multiple comparisons, four biomarkers differentiated fu-ture and past hospitalizations with suicidality in the prospec-tive cohorts of individuals with either bipolar disorder orpsychosis. SAT1 (spermidine/spermine N1–acetyltransferase1) was identified as the top biomarker comporting with alter-ations of the polyamine system in brains of suicides describedby Turecki and colleagues [12]. In fact, several genes impli-cated in polyamine biosynthesis seem to be up-regulated inthe brains of suicides. On the other hand, SAT1 and another“top” biomarker (CD24 molecule/small cell lung carcinomacluster 4 antigen) are related with apoptosis, or programmedcell death .Le-Niculescu and colleagues are to be commended for theuse of multi-dimensional approaches in the prediction of suicid-al behavior. The authors sequentially added data about mood,anxiety and psychosis to the expression levels of the bio-markers. They generated a series of receiver-operating charac-teristic (ROC) curves together with the average area under thecurves (AUC) for increasingly complex models (SAT1; SAT1+anxiety; SAT1+anxiety+mood; SAT1+anxiety+mood+psy-chosis) of future hospitalizations due to suicidal behavior. Inthis way, they found that the AUC for future hospitalizationswith suicidality increased progressively from 0.640 (with SAT1alone) to 0.835 (with SAT1, anxiety, mood, and psychosis). Inother words, they enhanced their capability to predict hospital-izations with suicidality by combining genetic and clinicalfactors.Previous models have achieved better results in classifyingsuicide attempters just using the most discriminant itemsfrom four assessment scales and socio-demographic factors(AUC=0.92) [5]. For a biomarker to be clinically useful, itmust have high sensitivity (>90 %) and specificity (>90 %)[13]. They should also show strong predictive value [14].Unfortunately, ROC curves with an AUC<0.75 are not clin-ically useful [15]. However, the combination of biologicalfactors with other variables (clinical, psychological) associat-ed with suicidal behavior may be a good strategy to improvethe predictive capacity of explanatory models.While acknowledging the value of the study by Le-Niculescu and colleagues, a number of limitations should benoted. The most relevant one is the construction of a “predic-tive” model of suicidal behavior from a small sample of ninemale bipolar individuals with/without suicidal ideation, andthe use of human postmortem brain evidence, a completelydifferent suicidal endophenotype, to test the model. Evensuicide attempters, a more proximate population than suicideideators, share only some of the characteristics of suicidecompleters [16]. Before any generalization can be made, theirresults need to be replicated in larger, more clearly character-ized samples. Moreover, the suicidal behavior of live partici-pants was not well-characterized. The concept of ‘suicidality’,widely used by the authors, lacks precision and decreases thevalidity of their findings [17].The study by Le-Niculescu and colleagues [1] exempla-rizes a potential strategy to identify routine blood tests in theprediction and prevention of suicidal impulses. Unfortunately,we are still far from this point. Among other pending tasks insuicidal research, clinicians can refine known endophenotypesfor suicidal behavior, such as impulsive aggression traits orpsychological pain, to facilitate the identification of expressedgenes that are associated with them. Predicting suicidal be-havior can also be enhanced by selecting the most discrimi-nant variables [5], using predictors from different do-mains (clinical, neurobiological and cognitive) [18], andby applying novel methodological instruments such asdata mining [19]. For the time being, we should remem-ber that several strategies, such as assuring aggressivetreatment for depression [20] and continuity of care toprevent relapses [21] may successfully reduce suicide rates,until such time as we reach the goal of predicting futuresuicide events.Compliance with Ethics GuidelinesConflict of Interest Hilario Blasco-Fontecilla has received lecture feesfrom Eli Lilly, AB-Biotics, and Shire.Jorge Lopez-Castroman, Lucas Giner, Enrique Baca-Garcia declarethat they have no conflict of interest. Maria A. Oquendo has receivedunrestricted educational grants and/or lecture fees form AstraZeneca,Bristol-Myers Squibb, Eli Lilly, Janssen, Otsuka, Pfizer, Sanofi-Aventis,and Shire. She receives royalties from the commercial use of the C-SSRS,and her family owns stock in Bristol-Myers Squibb.Human and Animal Rights and Informed Consent This article doesnot contain any studies with human or animal subjects performed by anyof the authors.424, Page 2 of 3 Curr Psychiatry Rep (2013) 15:424References1. Le-Niculescu H, Levey DF, Ayalew M, Palmer L, Gavrin LM, JainN, et al. Discovery and validation of blood biomarkers for suicidality.Mol Psychiatry. 2013. doi:10.1038/mp.2013.95.2. Smith EG, KimHM,GanoczyD, Stano C, Pfeiffer PN, ValensteinM.Suicide risk assessment received prior to suicide death by VeteransHealth Administration patients with a history of depression. J ClinPsychiatry. 2013;74:226–32.3. Isometsa ET, Heikkinen ME, Marttunen MJ, Henriksson MM,Aro HM, Lonnqvist JK. The last appointment before suicide:is suicide intent communicated? Am J Psychiatry. 1995;152:919–22.4. Pokorny A. Prediction of suicide in psychiatric patients: report of aprospective study. Arch Gen Psychiatry. 1983;40:249–57.5. Blasco-Fontecilla H, Delgado-Gomez D, Ruiz-Hernandez D, AguadoD, Baca-Garcia E, Lopez-Castroman J. Combining scales to assesssuicide risk. J Psychiatr Res. 2012;46(10):1272–7. doi:10.1016/j.jpsychires.2012.06.013.6. Blasco-Fontecilla H, Delgado-Gomez D, Legido-Gil T, deLeon J, Perez-Rodriguez MM, Baca-Garcia E. Can theHolmes-Rahe Social Readjustment Rating Scale (SRRS) be used asa suicide risk scale? An exploratory study. Arch Suicide Res.2012;16:13–28.7. Baca-Garcia E, Parra CP, Perez-Rodriguez MM, Diaz-Sastre C. ReyesTorres R, Saiz-Ruiz J, de Leon J: Psychosocial stressors may bestrongly associated with suicide attempts. Stress Health. 2007;23:191–8.8. Oquendo MA, Perez-Rodriguez MM, Poh E, Sullivan G, Burke AK,Sublette ME, et al. Life events: a complex role in the timing ofsuicidal behavior among depressed patients. Mol Psychiatry. 2013.doi:10.1038/mp.2013.128.9. Coryell W, Schlesser M. The dexamethasone suppression test andsuicide prediction. Am J Psychiatry. 2001;158:748–53.10. Sublette ME, Hibbeln JR, Galfalvy H, Oquendo MA, MannJJ. Omega-3 polyunsaturated essential fatty acid status as apredictor of future suicide risk. Am J Psychiatry. 2006;163:1100–2.11. Lee BH, Kim YK. Potential peripheral biological predictors of suicidalbehavior in major depressive disorder. Prog NeuropsychopharmacolBiol Psychiatry. 2011;35:842–7.12. Fiori LM, Bureau A, Labbe A, Croteau J, Noel S, Merette C, et al.Global gene expression profiling of the polyamine system in suicidecompleters. Int J Neuropsychopharmacol. 2011;14:595–605.13. Brower V. Biomarkers: Portents of malignancy. Nature. 2011;471(7339):S19–21.14. Jones R. Biomarkers: casting the net wide. Nature. 2010;466(7310):S11–2.15. Fan J, Upadhye S, Worster A. Understanding receiver operatingcharacteristic (ROC) curves. CJEM. 2006;8:19–20.16. Giner L, Blasco-Fontecilla H, Mercedes Perez-Rodriguez M, Garcia-Nieto R, Giner J, Guija JA, et al. Personality disorders and healthproblems distinguish suicide attempters from completers in a directcomparison. J Affect Disord. 2013;151:474–83.17. Meyer RE, Salzman C, Youngstrom EA, Clayton PJ, Goodwin FK,Mann JJ, et al. Suicidality and risk of suicide–definition, drug safetyconcerns, and a necessary target for drug development: a brief report.J Clin Psychiatry. 2010;71:1040–6.18. Gerszten RE, Wang TJ. The search for new cardiovascular bio-markers. Nature. 2008;451(7181):949–52.19. Oquendo MA, Baca-Garcia E, Artes-Rodriguez A, Perez-Cruz F,Galfalvy HC, Blasco-Fontecilla H, et al. Machine learning and datamining: strategies for hypothesis generation. Mol Psychiatry.2012;17:956–9.20. Hampton T. Depression care effort brings dramatic drop in largeHMO population's suicide rate. JAMA. 2010;303:1903–5.21. Troister T, Links PS, Cutcliffe J. Review of predictors of suicide within1 year of discharge from a psychiatric hospital. 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Predicting Suicidal Behavior: Are We Really that Far Along? Comment on “Discovery and Validation of Blood Biomarkers for Suicidality”

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Predicting Suicidal Behavior: Are We Really that Far Along? Comment on “Discovery and Validation of Blood Biomarkers for Suicidality”

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