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

Establishing a research agenda for the study and assessment of opioid withdrawal

The opioid crisis is an international public health concern. Treatments for opioid use disorder centre largely on the management of opioid withdrawal, an aversive collection of signs and symptoms that contribute to opioid use disorder. Whereas in the past 50 years more than 90 medications have been developed for depression, only five medications have been developed for opioid use disorder during this period. We posit that underinvestment has occurred in part due to an underdeveloped understanding of opioid withdrawal syndrome. This Personal View summarises substantial gaps in our understanding of opioid withdrawal that are likely to continue to limit major advancements in its treatment. There is no firm consensus in the field as to how withdrawal should be precisely defined; 10-550 symptoms of withdrawal can be measured on 18 scales. The imprecise understanding of withdrawal is likely to result in overestimating or underestimating the severity of an individual's withdrawal syndrome or potential therapeutic effects of different candidate medications. The severity of the opioid crisis is not remitting, and an international research agenda for the study and assessment of opioid withdrawal is necessary to support transformational changes in withdrawal management and treatment of opioid use disorder. Nine actionable targets are delineated here: develop a consensus definition of opioid withdrawal; understand withdrawal symptomatology after exposure to different opioids (particularly fentanyl); understand precipitated opioid withdrawal; understand how co-exposure of other drugs (eg, xylazine and stimulants) influences withdrawal expression; examine individual variation in withdrawal phenotypes; precisely characterise the protracted withdrawal syndrome; identify biomarkers of opioid withdrawal severity; identify predictors of opioid withdrawal severity; and understand which symptoms are most closely associated with treatment attrition or relapse. The US Food and Drug Administration recently established a formal indication for opioid withdrawal that has invigorated interest in drug development for opioid withdrawal management. Action is now needed to support these interests and help industry identify new classes of medications so that real change can be achieved for people with opioid use disorder.

Clinical and electrophysiological correlates of hopelessness in the context of suicide risk✰

Hopelessness is a key risk factor for suicide. This analysis explored whether hopelessness indicates a recent suicide crisis state and is linked with magnetoencephalography (MEG) oscillatory power and effective connectivity differences. Change in hopelessness ratings and effective connectivity post-ketamine were also evaluated in a subsample of high-risk individuals to evaluate correlates of dynamic changes over time. Participants (66F;44 M;1 transgender) included individuals with suicide crisis in the last two weeks (High Risk (HR), n = 14), those with past suicide attempt but no recent suicide ideation (SI) (Low Risk (LR), n = 37), clinical controls (CC, n = 33), and healthy volunteers at minimal risk (MinR, n = 27). MEG oscillatory power and clinical hopelessness ratings (via the Beck Hopelessness Scale (BHS)) were evaluated across groups. Dynamic casual modeling (DCM) evaluated connectivity within and between the anterior insula (AI) and anterior cingulate cortex (ACC). A subsample of HR individuals who received ketamine (n = 10) were evaluated at Day 1 post-infusion. The HR group reported the highest levels of hopelessness, even when adjusting for SI. MEG results linked hopelessness with reduced activity across frequency bands in salience network regions, with no group or group-by-interaction effects. Using DCM, the HR group had reduced intrinsic drive from granular Layer IV stellate cells to superficial pyramidal cells in the ACC and AI. In the pilot HR study, reduced hopelessness was linked with increased drive for this same connection post-ketamine. Hopelessness is a possible proxy for suicide risk. Electrophysiological targets for hopelessness include widespread reductions in salience network activity, particularly in the ACC and AI.

Impact of Toxoplasma gondii and Human Microbiome on Suicidal Behavior: A Systematic Review

BACKGROUND

Suicide remains a persistent global health challenge, resisting widespread prevention efforts. According to previous findings, toxoplasmosis is particularly associated with altered decision making, which could lead to risk-taking behavior, thereby increasing the likelihood for suicidal behavior (SB). In addition, discussion about the role of microbiome in psychiatric disorders has emerged lately, which also makes it relevant to investigate its role in the context of SB. Therefore, two systematic reviews are integrated in this paper, and the existing knowledge is comprehensively summarized regarding the association between microbial pathogens and SB.

METHODS

We conducted a systematic search with keywords including SB and Toxoplasma gondii (Suicid* AND Toxoplasm*) and microbiome (Suicid* AND Microbiome AND Microbiota) throughout PubMed and Scopus to retrieve related studies up to 9 November 2023, identifying 24 eligible records. The subjects of the included studies had to have fulfilled the criteria of an SB disorder as defined by DSM-5, and death cases needed to have been defined as suicide.

RESULTS

Most studies reported significant association between toxoplasmosis and SB, suggesting a higher likelihood of SB in the infected population. Regarding the microbiome, only very few studies investigated an association between SB and alterations in the microbiome. Based on six included studies, there were some indications of a link between changes in the microbiome and SB.

CONCLUSION

The cognitive aspects of decision making in T. gondii-infected individuals with SB should be further investigated to unravel the underlying mechanisms. Further sufficiently powered studies are needed to establish a link between SB and alterations in the microbiome.

EEG wakefulness regulation in transdiagnostic patients after a recent suicide attempt

OBJECTIVE

Decades of research have not yet produced statistically reliable predictors of preparatory behavior eventually leading to suicide attempts or deaths by suicide. As the nature of suicidal behavior is complex, it is best investigated in a transdiagnostic approach, while assessing objective markers, as proposed by the Research Domain Criteria (Cuthbert, 2013).

METHODS

A 15-min resting-state EEG was recorded in 45 healthy controls, and 49 transdiagnostic in-patients with a recent (<6 months) suicide attempt. Brain arousal regulation in eyes-closed condition was assessed with the Vigilance Algorithm Leipzig (VIGALL) (Sander et al., 2015).

RESULTS

A significant incline of median vigilance and vigilance slope was observed in patients within the first 3-min of the EEG recording. Additionally, a significant positive correlation of self-reported suicidal ideation with the vigilance slope over 15-min recording time, as well as a significant negative correlation with EEG vigilance stage A1 during the first 3-min was found.

CONCLUSIONS

Transdiagnostic patients with a recent suicide attempt show a distinct vigilance regulation pattern. Further studies including a control group consisting of patients without life-time suicide attempts are needed to increase the clinical utility of the findings.

SIGNIFICANCE

These findings might serve as potential objective markers of suicidal behavior.

Peripheral Markers of Suicidal Behavior: Current Findings and Clinical Implications

Biomarkers of suicidal behavior (SB), particularly peripheral biomarkers, may aid in the development of preventive and intervention strategies. The peripheral biomarkers of SB should be easily accessible, cost-effective, and minimally invasive. To identify peripheral biomarkers of SB, we summarized the current knowledge related to SB biomarkers with a focus on suicidal outcomes (suicidal ideation [SI], suicide risk [SR], suicide attempt [SA], and suicide death [SD]), measured site (center or periphery), and study design (cross-sectional or longitudinal). We also evaluated the central findings to validate the findings of peripheral biomarkers of SB. We found reduced peripheral interleukin (IL)-2 levels in individuals with a recent SA, higher cerebrospinal fluid (CSF) IL-6 levels in patients with a current SR and future SD, higher CSF tumor necrosis factor-α levels for current and future SRs, higher high-sensitivity C-reactive protein levels and lower peripheral total cholesterol levels for recent SAs, lower peripheral 5-HT levels for present SR, and a lower folate level for future SR and SA within 1 year. Previous studies have shown inconsistent associations of low peripheral leptin levels with SR and recent SA; therefore, further study is required. Given the multiple determinants of SB and weak associations with single biological markers, combinations of potential biological markers rather than single markers may improve the screening, diagnosis, and prediction of SB.

EEG source functional connectivity in patients after a recent suicide attempt

OBJECTIVE

Electroencephalogram (EEG) based frequency measures within the alpha frequency range (AFR), including functional connectivity, show potential in assessing the underlying pathophysiology of depression and suicide-related outcomes. We investigated the association between AFR connectivity, suicidal thoughts and behaviors, and depression in a transdiagnostic sample of patients after a recent suicide attempt (SA).

METHODS

Lagged source-based measures of linear and nonlinear whole-brain connectivity within the standard AFR ([sAFR], 8-12 Hz) and the individually referenced AFR (iAFR) were applied to 70 15-minute resting-state EEGs from patients after a SA and 70 age- and gender-matched healthy controls (HC). Hypotheses were tested using network-based statistics and multiple regression models.

RESULTS

Results showed no significant differences between patients after a SA and HC in any of the assessed connectivity modalities. However, a subgroup analysis revealed significantly increased nonlinear connectivity within the sAFR for patients after a SA with a depressive disorder or episode ([DD], n = 53) compared to matched HC. Furthermore, a multiple regression model, including significant main effects for group and global nonlinear connectivity within the sAFR outperformed all other models in explaining variance in depressive symptom severity.

CONCLUSIONS

Our study further supports the importance of the AFR in pathomechanisms of suicidality and depression. The iAFR does not seem to improve validity of phase-based connectivity.

SIGNIFICANCE

Our results implicate distinct neurophysiological patterns in suicidal subgroups. Exploring the potential of these patterns for treatment stratification might advance targeted interventions for suicidal thoughts and behaviors.

Fight the Fire: Association of Cytokine Genomic Markers and Suicidal Behavior May Pave the Way for Future Therapies

The fight against suicide is highly challenging as it may be one of the most complex and, at the same time, most threatening among all psychiatric phenomena. In spite of its huge impact, and despite advances in neurobiology research, understanding and predicting suicide remains a major challenge for both researchers and clinicians. To be able to identify those patients who are likely to engage in suicidal behaviors and identify suicide risk in a reliable and timely manner, we need more specific, novel biological and genetic markers/indicators to develop better screening and diagnostic methods, and in the next step to utilize these molecules as intervention targets. One such potential novel approach is offered by our increasing understanding of the involvement of neuroinflammation based on multiple observations of increased proinflammatory states underlying various psychiatric disorders, including suicidal behavior. The present paper overviews our existing understanding of the association between suicide and inflammation, including peripheral and central biomarkers, genetic and genomic markers, and our current knowledge of intervention in suicide risk using treatments influencing inflammation; also overviewing the next steps to be taken and obstacles to be overcome before we can utilize cytokines in the treatment of suicidal behavior.

Unlocking the Secrets: Exploring the Biochemical Correlates of Suicidal Thoughts and Behaviors in Adults with Autism Spectrum Conditions

Involving 1 million people a year, suicide represents one of the major topics of psychiatric research. Despite the focus in recent years on neurobiological underpinnings, understanding and predicting suicide remains a challenge. Many sociodemographical risk factors and prognostic markers have been proposed but they have poor predictive accuracy. Biomarkers can provide essential information acting as predictive indicators, providing proof of treatment response and proposing potential targets while offering more assurance than psychological measures. In this framework, the aim of this study is to open the way in this field and evaluate the correlation between blood levels of serotonin, brain derived neurotrophic factor, tryptophan and its metabolites, IL-6 and homocysteine levels and suicidality. Blood samples were taken from 24 adults with autism, their first-degree relatives, and 24 controls. Biochemical parameters were measured with enzyme-linked immunosorbent assays. Suicidality was measured through selected items of the MOODS-SR. Here we confirm the link between suicidality and autism and provide more evidence regarding the association of suicidality with increased homocysteine (0.278) and IL-6 (0.487) levels and decreased tryptophan (-0.132) and kynurenic acid (-0.253) ones. Our results suggest a possible transnosographic association between these biochemical parameters and increased suicide risk.

Resting State EEG Correlates of Suicide Ideation and Suicide Attempt

Suicide is a global phenomenon that impacts individuals, families, and communities from all income groups and all regions worldwide. While it can be prevented if personalized interventions are implemented, more objective and reliable diagnostic methods are needed to complement interview-based risk assessments. In this context, electroencephalography (EEG) might play a key role. We systematically reviewed EEG resting state studies of adults with suicide ideation (SI) or with a history of suicide attempts (SAs). After searching for relevant studies using the PubMed and Web of Science databases, we applied the PRISMA method to exclude duplicates and studies that did not match our inclusion criteria. The selection process yielded seven studies, which suggest that imbalances in frontal and left temporal brain regions might reflect abnormal activation and correlate with psychological distress. Furthermore, asymmetrical activation in frontal and posterior cortical regions was detected in high-risk depressed persons, although the pattern in the frontal region was inverted in non-depressed persons. The literature reviewed suggests that SI and SA may be driven by separate neural circuits and that high-risk persons can be found within non-depressed populations. More research is needed to develop intelligent algorithms for the automated detection of high-risk EEG anomalies in the general population.

Peripheral blood cytokines as potential diagnostic biomarkers of suicidal ideation in patients with first-episode drug-naïve major depressive disorder

Objective

Major Depressive Disorder (MDD) is a leading cause of disability, with a high risk of suicidal ideation (SI). Few studies have evaluated the potential of multiple cytokines as biomarkers for SI in patients with MDD. In the present study, we examined the serum levels of multiple cytokines in patients with first-episode drug-naïve MDD, with the aim to discover and identify serum cytokines-based biomarkers for identification of SI in MDD.

Methods

A total of 55 patients with first-episode drug-naïve MDD were enrolled and divided into two groups: 26 MDD patients without SI and 29 MDD patients with SI. Beck Scale for Suicide Ideation was used to estimate SI. A total of 37 cytokines were measured using Multiplex Luminex Assays. The levels of serum cytokines between MDD patients without SI and MDD patients with SI were compared and diagnostic values of different cytokines were evaluated using the receiver operating characteristic (ROC) curve method for discriminating MDD patients with SI from MDD patients without SI. The relationship between the group and the abnormal cytokines were investigated in multiple linear regression models, with adjustments for age, gender, BMI, smoking, and Hamilton Depression Rating Scale-24 (HAMD-24) scores.

Results

The levels of CCL26 and VEGF in MDD patients with SI were significantly lower than those in MDD patients without SI (all P < 0.05). On the contrary, the levels of IL-17C, CXCL10, and TNF-β in MDD patients with SI were significantly higher than those in MDD patients without SI (all P < 0.05). Moreover, the results of multiple linear regression revealed that group was a significant independent predictor of serum IL-17C, CCL-26, VEGF, and TNF-β levels (all P < 0.05). In terms of CXC10, group was also likely to be a significant independent predictor (β = 0.257, P = 0.063). Furthermore, the AUC values of IL-17C and TNF-β were 0.728 and 0.732, respectively. Additionally, a combined panel of IL-17C and TNF-β achieved a high accuracy in discriminating MDD patients with SI from MDD patients without SI (AUC = 0.848, sensitivity = 75.9%, specificity = 72.7%).

Conclusions

These results suggested that circulating IL-17C and TNF-β may hold promise in the discovery of biomarkers for identification of SI in MDD.

C-Reactive Protein as a Potential Peripheral Biomarker for High-Lethality Suicide Attempts

The aim of the present study was to identify a cut-off of c-reactive protein (c-RP) potentially predictive of high-lethality suicide attempts (SA) in an inpatient psychiatric sample. After attempting suicide, subjects were admitted to the emergency ward of the IRCCS Ospedale Policlinico San Martino and later to the section of Psychiatry from 1 August 2013 to 31 July 2018. C-reactive protein was measured. The Area Under the Receiver Operating Characteristic (ROC_AUC) was used to assess the discriminative capacity of c-RP for high- vs. low-lethality SA, and a logistic regression was performed to detect the odds ratio, adjusted for age and sex. High-lethality suicide attempters were 133 (30.8%), while low-lethality suicide attempters were 299 (69.2%). The optimal cut-off threshold (and corresponding sensitivity and specificity values) for c-RP was 4.65 mg/L (68/71%). This cut-off corresponds to an AUC of 73.5%. An odds ratio of 4.70 was generated for current high-lethality SA after a logistic regression, adjusted for age and sex. Research on social and biological factors underlying the lethality of SA is crucial for a better understanding of this complex phenomenon. Identifying potential predictors of SA, especially those at high lethality, is essential to implement personalized preventive strategies.

Using Voice Biomarkers to Classify Suicide Risk in Adult Telehealth Callers: Retrospective Observational Study

BACKGROUND

Artificial intelligence has the potential to innovate current practices used to detect the imminent risk of suicide and to address shortcomings in traditional assessment methods.

OBJECTIVE

In this paper, we sought to automatically classify short segments (40 milliseconds) of speech according to low versus imminent risk of suicide in a large number (n=281) of telephone calls made to 2 telehealth counselling services in Australia.

METHODS

A total of 281 help line telephone call recordings sourced from On The Line, Australia (n=266, 94.7%) and 000 Emergency services, Canberra (n=15, 5.3%) were included in this study. Imminent risk of suicide was coded for when callers affirmed intent, plan, and the availability of means; level of risk was assessed by the responding counsellor and reassessed by a team of clinical researchers using the Columbia Suicide Severity Rating Scale (=5/6). Low risk of suicide was coded for in an absence of intent, plan, and means and via Columbia suicide Severity Scale Ratings (=1/2). Preprocessing involved normalization and pre-emphasis of voice signals, while voice biometrics were extracted using the statistical language r. Candidate predictors were identified using Lasso regression. Each voice biomarker was assessed as a predictor of suicide risk using a generalized additive mixed effects model with splines to account for nonlinearity. Finally, a component-wise gradient boosting model was used to classify each call recording based on precoded suicide risk ratings.

RESULTS

A total of 77 imminent-risk calls were compared with 204 low-risk calls. Moreover, 36 voice biomarkers were extracted from each speech frame. Caller sex was a significant moderating factor (β=-.84, 95% CI -0.85, -0.84; t=6.59, P<.001). Candidate biomarkers were reduced to 11 primary markers, with distinct models developed for men and women. Using leave-one-out cross-validation, ensuring that the speech frames of no single caller featured in both training and test data sets simultaneously, an area under the precision or recall curve of 0.985 was achieved (95% CI 0.97, 1.0). The gamboost classification model correctly classified 469,332/470,032 (99.85%) speech frames.

CONCLUSIONS

This study demonstrates an objective, efficient, and economical assessment of imminent suicide risk in an ecologically valid setting with potential applications to real-time assessment and response.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12622000486729; https://www.anzctr.org.au/ACTRN12622000486729.aspx.