Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 8, 113

Discovery and Replication of a Peripheral Tissue DNA Methylation Biosignature to Augment a Suicide Prediction Model


Discovery and Replication of a Peripheral Tissue DNA Methylation Biosignature to Augment a Suicide Prediction Model

Makena L Clive et al. Clin Epigenetics.


Background: Suicide is the second leading cause of death among adolescents in the USA, and rates are rising. Methods to identify individuals at risk are essential for implementing prevention strategies, and the development of a biomarker can potentially improve prediction of suicidal behaviors. Prediction of our previously reported SKA2 biomarker for suicide and PTSD is substantially improved by questionnaires assessing perceived stress or anxiety and is therefore reliant on psychological assessment. However, such stress-related states may also leave a biosignature that could equally improve suicide prediction. In genome-wide DNA methylation data, we observed significant overlap between waking cortisol-associated and suicide-associated DNA methylation in blood and the brain, respectively.

Results: Using a custom bioinformatic brain to blood discovery algorithm, we derived a DNA methylation biosignature that interacts with SKA2 methylation to improve the prediction of suicidal ideation in our existing suicide prediction model across both blood and saliva data sets. This biosignature was independently validated in the Grady Trauma Project cohort and interacted with HPA axis metrics in the same cohort. The biosignature showed a relationship with immune status by its correlation with myeloid-derived cell proportions in all data sets and with IL-6 measures in a prospective postpartum depression cohort. Three probes showed significant correlations with the biosignature: cg08469255 (DDR1), cg22029879 (ARHGEF10), and cg24437859 (SHP1), of which SHP1 methylation correlated with immune measures.

Conclusions: We conclude that this biosignature interacts with SKA2 methylation to improve suicide prediction and may represent a biological state of immune and HPA axis modulation that mediates suicidal behavior.

Keywords: Biomarker; Childhood trauma; DNA methylation; Epigenetics; HPA axis; Illumina HM450 microarray; SKA2; Suicide.


Fig. 1
Fig. 1
Discovery of interaction biosignature probes and prediction of suicidal ideation using interaction biosignature in multiple cohorts. a Volcano plot in prefrontal cortex neurons (cases, N = 22; controls, N = 23) of the interaction of individual probe methylation with rs7208505 methylation and genotype. b Probes with an interaction P value <0.005 (N = 669) were optimized for prediction of SA in GenRED Offspring blood. Probes with an AUC prediction above 0.825 (N = 72) were used to train a PCA model. c ROC curves of prediction of SI in GenRED Offspring saliva and PPD cohort blood using the first eigenvectors of predicted PCAs. d ROC curves of prediction of SI in the whole GTP cohort and a subset of drug-naïve, non-PTSD individuals (cases = 6; controls = 109)
Fig. 2
Fig. 2
Myeloid-derived cell proportions correlated with the interaction biosignature in all cohorts and were predictive of suicidal behavior. Correlations were observed between the interaction biosignature and the proportion of myeloid-derived cells in a GenRED Offspring blood (P = 2.7 × 10−4), b saliva (P = 0.092), c PPD cohort blood (P = 0.034), and d GTP blood (P = 2.4 × 10−7)
Fig. 3
Fig. 3
Interaction biosignature and methylation at SHP1 (cg24437859) correlated with inflammatory markers and stress measures in the PPD cohort (trimester >1). a Levels of IL-6, an inflammatory marker, correlated with myeloid-derived cell proportion (P = 0.054). b The interaction biosignature correlated with the perceived stress metric (P = 0.019). SHP1 methylation correlated with both c IL-6 levels (P = 0.035) and d myeloid-derived cell proportion (P = 1.4 × 10−8)

Similar articles

See all similar articles

Cited by 5 PubMed Central articles


    1. Suicide Data [online] World Health Organization. 2016.
    1. Web-based Injury Statistics Query and Reporting System (WISQARS) [online] Centers for Disease Control and Prevention: National Center for Injury Prevention and Control. 2016.
    1. Pringle B, Colpe LJ, Heinssen RK, Schoenbaum M, Sherrill JT, Claassen CA, et al. A strategic approach for prioritizing research and action to prevent suicide. Psychiatr Serv. 2013;64(1):71–75. doi: 10.1176/ - DOI - PubMed
    1. Guintivano J, Brown T, Newcomer A, Jones M, Cox O, Maher BS, et al. Identification and replication of a combined epigenetic and genetic biomarker predicting suicide and suicidal behaviors. Am J Psychiatry. 2014;171(12):1287–1296. doi: 10.1176/appi.ajp.2014.14010008. - DOI - PubMed
    1. Niculescu AB, Levey D, Le-Niculescu H, Niculescu E, Kurian SM, Salomon D. Psychiatric blood biomarkers: avoiding jumping to premature negative or positive conclusions. Mol Psychiatry. 2015;20:286–288. doi: 10.1038/mp.2014.180. - DOI - PMC - PubMed

Publication types

MeSH terms