Serotonin transporter gene polymorphism as a predictor of short-term risk of suicide reattempts

Genetic analysis of suicide: a sample study in Tuscany (Central Italy)

Many studies have examined the genetic contribution to suicide. However, data on suicide in the Italian population are scarce. We therefore aimed to address this gap by investigating a cohort of 111 Italians for whom a verdict of suicide had been declared in court in Florence, Italy between 2007 and 2017. This cohort included 86 men and 25 women. DNA samples were obtained from tissues or blood, and 22 genes from multiple neurobiological pathways previously shown to be associated with the pathogenesis of suicide were analysed. Next-generation sequencing was used to compare these gene sequences with those from a large, normal population. In this study, we identified 19 gene variants that were present at significantly lower frequencies in our Italian cohort than in the general population. In addition, four missense mutations were identified in four different genes: Monoamine Oxidase A (MAOA), 5-Hydroxytryptamine Receptor 2 A (HTR2A), Sodium Voltage-Gated Channel Alpha Subunit 8 (SCN8A), and Nitric Oxide Synthase 3 (NOS3). Our study identified several potential genetic links with suicide in a cohort of Italians and supports a relationship between specific genetic variants and suicidal behaviour in this population.

Suicide Biomarkers to Predict Risk, Classify Diagnostic Subtypes, and Identify Novel Therapeutic Targets: 5 Years of Promising Research

BACKGROUND

Suicide is a global health crisis. However, no objective biomarkers of suicide risk currently exist, and self-reported data can be unreliable, which limits prediction, diagnostic, and treatment efforts. Reliable biomarkers that can differentiate between diagnostic subgroups, predict worsening symptoms, or suggest novel therapeutic targets would be extremely valuable for patients, researchers, and clinicians.

METHODS

MEDLINE was searched for reports published between 2016 and 2021 using search terms (suicid*) AND (biomarker*) OR (indicat*). Reports that compared biomarkers between suicidal ideation, suicide attempt, death from suicide, or any suicide subgroup against other neuropsychiatric disorders were included. Studies exclusively comparing suicidal behavior or death from suicide with healthy controls were not included to ensure that biomarkers were specific to suicide and not other psychopathology.

RESULTS

This review summarizes the last 5 years of research into suicide-associated biomarkers and provides a comprehensive guide for promising and novel biomarkers that encompass varying presentations of suicidal ideation, suicide attempt, and death by suicide. The serotonergic system, inflammation, hypothalamic-pituitary-adrenal axis, lipids, and endocannabinoids emerged as the most promising diagnostic, predictive, and therapeutic indicators.

CONCLUSIONS

The utility of diagnostic and predictive biomarkers is evident, particularly for suicide prevention. While larger-scale studies and further in-depth research are required, the last 5 years of research has uncovered essential biomarkers that could ultimately improve predictive strategies, aid diagnostics, and help develop future therapeutic targets.

Peripheral BDNF levels in psychiatric patients with and without a history of suicide attempt: A systematic review and meta-analysis

OBJECTIVE

Psychiatric patients are at increased risk of attempting suicide. Several potential biomarkers of suicide risk have been proposed with inconsistent findings. The present paper aimed to evaluate differences in peripheral BDNF levels between psychiatric patients with and without a history of suicide attempts.

METHODS

We conducted a systematic review and meta-analysis following the PRISMA guidelines. Relevant papers published up to January 5, 2021 were identified searching the electronic databases Web of Knowledge^SM and PsycINFO. A random-effect meta-analysis was conducted using Stata 16.

RESULTS

Thirteen studies met inclusion criteria. Overall, no significant differences in BDNF levels between the two groups were found (13 studies, n = 1340, Hedge's g = -0.21, 95% CI -0.44 to 0.02). Heterogeneity was substantial (I² = 72.91%). Subgroup analyses revealed that BDNF levels were significantly reduced in plasma with medium effect size (5 studies, n = 363, Hedge's g = -0.44, 95% CI -0.86 to -0.02), but not in serum (8 studies, n = 977, Hedge's g = -0.09, 95% CI -0.33 to 0.15). No significant differences were found according to the type of diagnosis (major depressive disorder vs. other diagnoses) or the period of suicide attempt (lifetime vs. recent).

CONCLUSION

The utility of BDNF as a biomarker of suicide attempts in psychiatric patients appears limited to its plasma concentration. Although caution interpretation is needed, our findings may represent a starting point for the design of rigorous case-control studies exploring the association between neurotrophins and suicidal behaviors.

Comparison of traditional model-based statistical methods with machine learning for the prediction of suicide behaviour

BACKGROUND

Despite considerable research efforts during the last five decades, the prediction of suicidal behaviour (SB) using traditional model-based statistical has been weak. This marks the need to explore new statistical methods.

OBJECTIVE

To compare the performance of Cox regression models versus Random Survival Forest (RSF) to predict SB.

METHODS

Using a data set of more than 300 high-risk suicidal patients from a multicenter prospective cohort study, we compare Cox regression models with RSF to address predictors of time to suicide reattempt. Cross-validation was used to assess model prediction performance, including the area under the receiver operator curve (AUC), precision, Integrated Brier Score (IBS), sensitivity, and specificity.

RESULTS

A variant of the RSF denominated the RSFElimin, in which irrelevant predictor variables were eliminated from the model, presented the best accuracy, sensitivity, AUC and IBS. At the same time, the sensitivity of this method was slightly lower than that obtained with the Cox regression model with all predictor variables (CoxComp).

CONCLUSION

The RSF, a machine learning model, seems more sensitive and precise than the traditional Cox regression model in predicting suicidal behaviour.

Cerebrospinal fluid levels of monoamines among suicide attempters: A systematic review and random-effects meta-analysis

BACKGROUND

It remains unclear whether the dopaminergic and noradrenergic systems may be implied in suicide attempt risk. In addition, although the serotonergic system has been extensively studied, no formal meta-analysis has been performed to examine its association with suicide attempt.

METHODS

Using PRISMA methodology, we performed a systematic literature review and random-effects meta-analyses of the differences in cerebrospinal fluid (CSF) levels of 5-HIAA, HVA and MHPG between suicide attempters and individuals who never attempted suicide.

RESULTS

We identified 30 studies including 937 suicide attempters and 1128 non-attempters; 29 of them measured CSF levels of 5-HIAA, 22 measured CSF levels of HVA and 14 measured CSF levels of MHPG. CSF levels of 5-HIAA and HVA were significantly lower in suicide attempters than in non-attempters [SMD = -0.43 (95% CI: -0.71 to -0.15; p < 0.01) and SMD = -0.45 (95% CI: -0.72 to -0.19; p < 0.01), respectively]. We did not find a significant association between CSF MHPG levels and suicide attempt.

LIMITATIONS

Our analyses relied on a limited number of studies of good quality and most studies included small sample sizes.

CONCLUSION

Both serotonin and dopamine systems may play a role in suicide attempt risk. Our findings suggest that a silo approach to biomarkers should be phased out in favor of the study of multiple systems in parallel and in the same populations to progress in the identification of the biological components independently associated with suicide risk, with the goal of identifying new treatment targets and improving suicide risk prediction.

Suicidal ideation and aggression in childhood, genetic variation and young adult depression

BACKGROUND

Suicidal thoughts and behaviors have been studied in association with a variety of risk factors. The aim of the present study was to determine if levels of child/adolescent aggression and/or variation in candidate genes previously associated with suicidal behaviors in adults would influence the presence of suicidal ideation in childhood/adolescence, and to determine if ideation was associated with young adult depression.

METHODS

A longitudinal study of children, adolescents and young adults who were at high or low risk for alcohol and other substance use disorders by familial background were assessed. The Child Behavior Checklist (CBCL) aggression scale scores with derived subtypes (physical and relational) and genetic variation (ANKK1, DRD2, COMT, SLC6A4, HTR2C) were used as predictors of the presence and onset of suicidal ideation in childhood using survival analysis. Structural equation models (SEM) were fit to determine the relative importance of the predictors controlling for background variables.

RESULTS

CBCL aggression was significantly associated with child/adolescent suicidal ideation. One SNP in the ANKK1 gene (rs1800497), one in the HTR2C gene (rs6318), and two haplotypes, AAAC in the ANKK1-DRD2 complex and the CCC haplotype of the HTR2C gene, were significantly associated with the presence and onset of child/adolescent suicidal ideation. Follow up in young adulthood showed a significant relationship between suicidal ideation in childhood/adolescence and young adult depression.

CONCLUSIONS

Genetic variation and presence of elevated aggression scores from the childhood CBCL are significant predictors of childhood suicidal ideation. Suicidal ideation in childhood and being female are predictors of young adult depression.

5HTTLPR Genetic Variant and Major Depressive Disorder: A Review

Major Depressive Disorder (MDD) is a disease that involves biological, psychological, and social interactions. Studies have shown the importance of genetics contribution to MDD development. The SCL6A4 protein (5HTTLPR) functions transporting serotonin, a neurotransmitter linked to mood and emotion, to the synaptic cleft. Hence, this study seeks, through a literature review, a better comprehension of the 5HTTLPR genetic variant association with MDD. For this purpose, a search was performed on the Virtual Health Library Portal for articles that related 5HTTLPR to MDD. Most of the articles found were conducted in the American continent, with one (1) study implemented in Brazil. 5HTTLPR associations were found regarding changes in the nervous system, pharmacology, and risk factors seen in MDD patients. When verifying the allelic distribution, the S allele had a higher frequency in most of the studies analyzed. Despite not finding a commonality in the different studies, the tremendous genetic variation found demonstrates the MDD complexity. For this reason, further studies in diverse populations should be conducted to assist in the understanding and treatment of the disease.

The effect of sex on suicide risk during and after psychiatric inpatient care in 12 countries-An ecological study

BACKGROUND

Suicide risk in patients is markedly elevated during psychiatric inpatient care, as well as after discharge. However, it is unclear whether, and to what extent, this increased suicide risk varies between sex. Thus, the aim of this study was to analyze sex differences for suicides during and after psychiatric hospitalization in various countries.

METHODS

National suicide mortality rates and inpatient-related suicide rates (three intervals: during psychiatric inpatient treatment, 1 month, and 1 year after discharge) from 12 countries for 2000-2016 were analyzed, and a logistic model was used to quantify the effect of sex.

RESULTS

Persons admitted to or discharged from psychiatric inpatient care exhibited significantly increased rates of suicide compared to those in the general population. Furthermore, increase of suicide risk was significantly higher for females than for males for all investigated time intervals (inpatient suicide odds ratio [OR] 1.85; suicide within 1 month after discharge-OR 1.94; suicide within 1 year after discharge-OR 2.04).

CONCLUSION

Analysis confirmed the time during and after psychiatric inpatient care to be significantly associated with an elevated risk for suicide. Further, a significant sex effect was observed, with females in this population being at a proportionally higher risk for suicide during psychiatric inpatient treatment as well as the year following discharge. Our study implicates that more effective suicide preventive measures during inpatient stay, focusing on female patients, are needed.

Psychological and neurobiological aspects of suicide in adolescents: Current outlooks

Suicidality is one of the leading causes of death among young adults in the United States and represents a significant health problem worldwide. The suicide rate among adolescents in the United States has increased dramatically in the latest years and has been accompanied by considerable changes in youth suicide, especially among young girls. Henceforth, we need a good understanding of the risk factors contributing to suicidal behavior in youth. An explanatory model for suicidal behavior that links clinical and psychological risk factors to the underlying neurobiological, neuropsychological abnormalities related to suicidal behavior might predict to help identify treatment options and have empirical value. Our explanatory model proposes that developmental, biological factors (genetics, proteomics, epigenetics, immunological) and psychological or clinical (childhood adversities) may have causal relevance to the changes associated with suicidal behavior. In this way, our model integrates findings from several perspectives in suicidality and attempts to explain the relationship between various neurobiological, genetic, and clinical observations in suicide research, offering a comprehensive hypothesis to facilitate understanding of this complex outcome. Unraveling the knowledge of the complex interplay of psychological, biological, sociobiological, and clinical risk factors is highly essential, concerning the development of effective prevention strategy plans for suicidal ideation and suicide.