https://orcid.org/0000-0002-2529-7256
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ABSTRACT
Introduction
Every year about 800,000 complete suicide events occur. The identification of biologic markers to identify subjects at risk would be helpful in targeting specific support treatments.
Area covered
A narrative review defines the meta-analytic level of current evidence about the biologic markers of suicide behavior (SB). The meta-analytic evidence gathered so far indicates that the hypothesis-driven research largely failed to identify the biologic markers of suicide. The most consistent and replicated result was reported for: 1) 5-HTR2A T102C, associated with SB in patients with schizophrenia (OR = 1.73 (1.11–2.69)) and 2) BDNF Val66Met (rs6265), with the Met-Val + Val–Val carriers found to be at risk for suicide in the Caucasian population (OR: 1.96 (1.58–2.43)), while Val–Val vs. Val–Met + Met carriers found to be at risk for suicide in the Asian populations (OR: 1.36 (1.04–1.78)). GWAS-based meta-analyses indicate some positive replicated findings regarding the DRD2, Neuroligin gene, estrogen-related genes, and genes involved in gene expression.
Expert opinion
Most consistent results were obtained when analyzing sub-samples of patients. Some promising results come from the implementation of the polygenic risk score. There is no current consensus about an implementable biomarker for SB.
Article highlights
Suicide behavior is a worldwide concern. About 800,000 individuals commit suicide per year.
The current strategies to prevent suicide are based on: 1) identification of subjects at risk and follow up; 2) psychotherapy and 3) medical treatment.
The current tools to identify individuals at risk are clinical-based.
There is no current biologic marker used to identify subjects at risk for suicide.
Suicide has a genetic basis both in aggregation with other psychiatric disorders and independently from it.
Suicide heritability is estimated to be as large as h2 = 45%.
During the last decades of biologic research on suicide, it is still not possible to identify a reliable, clinical implementable biomarker for Suicide.
Some promising results appear to be related to the use of endophenotypes, polygenic risk score and the analysis of specific sub-clinical samples.
Some of the limits of the current research are the use of a taxonomic approach, limits of GWAS annotation, wear phenotype definition and pleiotropy.
Abbreviations
| RR | = | relative risk |
| OR | = | odds ratio |
| SNP | = | single nucleotide polymorphism |
| GWAS | = | genome wide association study |
| RCT | = | randomized controlled trials |
| SB | = | suicidal behavior |
| TPH1 | = | Tryptophan Hydroxylase |
| 5-HTR1A | = | 5-Hydroxytryptamine Receptor 1A |
| 5-HTR2A | = | 5-Hydroxytryptamine Receptor 2A |
| 5-HTT | = | The gene that codes for the serotonin transporter, the Solute Carrier Family 6 Member 4. |
| DRD2 | = | dopamine receptor 2 |
| DRD4 | = | Dopamine receptor 4 |
| DAT1 | = | Dopamine transporter 1 |
| COMT | = | Catechol-O-Methyltransferase |
| 5-HTR1B | = | 5-Hydroxytryptamine Receptor 1B |
| BDNF | = | Brain Derived Neurotrophic Factor |
| MAO | = | monoamine-oxidase |
| NOS1 | = | Nitric Oxide Synthase 1 |
| FKBP5 | = | FKBP Prolyl Isomerase 5 |
| MDD | = | major depressive disorder |
| BID | = | bipolar disorder |
| SKZ | = | schizophrenia |
| NLGN1 | = | neuroregulin |
| ESR1 | = | Estrogen Receptor 1 |
| EXD3 | = | Exonuclease 3’−5’ Domain Containing 3 |
| TRAF3 | = | TNF Receptor Associated Factor 3 |
| POM121L2 | = | POM121 Transmembrane Nucleoporin Like 2 |
| METTL15/LINC02758 | = | Methyltransferase 15, Mitochondrial 12S RRNA N4-Cytidine |
| PET112/GATB | = | Glutamyl-TRNA Amidotransferase Subunit B |
| DCC | = | DCC Netrin 1 Receptor |
| TRAF3 | = | TNF Receptor Associated Factor 3 |
| TNFR | = | TNF Receptor Superfamily Member 1A |
| Nr3c1 | = | Nuclear Receptor Subfamily 3 Group C Member 1 |
| OXTR | = | Oxytocin Receptor |
| ELAVL4 | = | ELAV Like RNA Binding Protein 4 |
| PSORS1C3 | = | Psoriasis Susceptibility 1 Candidate 3 |
Declaration of Interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Two Peer reviewers on this manuscript have received an honorarium from Expert Review of Proteomics for their review work but have no other relevant financial relationships to disclose.
Author contribution
Antonio Drago, MD, Ph.D (Aalborg University Hospital, Aalborg, Denmark) formulated the idea for the paper, conducted the necessary literature research and wrote the paper. Antonio Drago approves the version of the paper to the published and agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Ethical statements
The present contribution did not involve the use of personal data or personal information. No clinical research or experimentation was conducted on individuals or animals.