Worldwide, one person dies every 40 seconds by suicide, a potentially preventable tragedy. A limiting step in our ability to intervene is the lack of objective, reliable predictors. We have previously provided proof of principle for the use of blood gene expression biomarkers to predict future hospitalizations due to suicidality, in male bipolar disorder participants. We now generalize the discovery, prioritization, validation, and testing of such markers across major psychiatric disorders (bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) in male participants, to understand commonalities and differences. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation and high suicidal ideation states (n=37 participants out of a cohort of 217 psychiatric participants followed longitudinally). We then used a convergent functional genomics (CFG) approach with existing prior evidence in the field to prioritize the candidate biomarkers identified in the discovery step. Next, we validated the top biomarkers from the prioritization step for relevance to suicidal behavior, in a demographically matched cohort of suicide completers from the coroner's office (n=26). The biomarkers for suicidal ideation only are enriched for genes involved in neuronal connectivity and schizophrenia, the biomarkers also validated for suicidal behavior are enriched for genes involved in neuronal activity and mood. The 76 biomarkers that survived Bonferroni correction after validation for suicidal behavior map to biological pathways involved in immune and inflammatory response, mTOR signaling and growth factor regulation. mTOR signaling is necessary for the effects of the rapid-acting antidepressant agent ketamine, providing a novel biological rationale for its possible use in treating acute suicidality. Similarly, MAOB, a target of antidepressant inhibitors, was one of the increased biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would show broad-spectrum predictive ability across psychiatric diagnoses. Indeed, the UP-Suicide was able to predict suicidal ideation across psychiatric diagnoses with an AUC of 92%. For bipolar disorder, it predicted suicidal ideation with an AUC of 98%, and future hospitalizations with an AUC of 94%. Of note, both types of tests we developed (blood biomarkers and clinical information apps) do not require asking the individual assessed if they have thoughts of suicide, as individuals who are truly suicidal often do not share that information with clinicians. We propose that the widespread use of such risk prediction tests as part of routine or targeted healthcare assessments will lead to early disease interception followed by preventive lifestyle modifications and proactive treatment.

/pdf/understanding-and-predicting-suicidality-using-a-combined-4qqx6ek5n8.pdf

Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach

Rationale
Abnormalities in Toll-like receptor (TLR) expression in depression have been inferred in part from observed increases in TLR4 levels in peripheral blood mononuclear cells (PBMCs) and postmortem brains of depressed and suicidal patients. Our previous study found differences in the TLR expression in PBMCs between healthy controls and patients with major depressive disorder. Normalization of increased TLR4 in PBMCs by cognitive behavior psychotherapy has been reported. However, the effects of antidepressants remain unknown.

/pdf/antidepressants-normalize-elevated-toll-like-receptor-tm1h29fy1m.pdf

Antidepressants normalize elevated Toll-like receptor profile in major depressive disorder

Asthma is a highly prevalent chronic condition worldwide, and is particularly common in younger people compared to other chronic conditions. Asthma can result in a number of symptoms that are detrimental to the quality of life of sufferers. The aim of the present systematic literature review was to analyse the existing literature on the relationship between asthma and fatal and nonfatal suicidal behaviours. Articles were retrieved from Scopus, PubMed, ProQuest and Web of Knowledge. We searched for the terms (suicid* OR self-harm) AND (asthma* OR "bronchial hyperreactivity") published in English-language peer-reviewed journals between 1990 and December 2014. Original research papers providing empirical evidence about the potential link between asthma and suicidal behaviours were included. The initial search identified 746 articles. Specific limiting criteria reduced the number of articles to the 19 articles that were finally included in the systematic review. The review found a potential link between asthma and suicide mortality, ideation and attempts across the age groups. Limitations of the review include the restriction to English-language papers published within the chosen time period, the limited number of papers involving suicide mortality, and the fact that the majority of papers originated from the USA.

https://erj.ersjournals.com/content/erj/46/1/96.full.pdf

The relationship between asthma and suicidal behaviours: a systematic literature review.

Definition of mutations in polyautoimmunity.

Death by suicide is a significant cause of mortality among youth. However, there is limited information on the demographic and clinical factors associated with youth suicide deaths. The objective of this study was to link large statewide databases to describe demographic, clinical, and cause of death characteristics among youth who died by suicide. We examined 1,218 decedents under age 26 who died by suicie between 2000 and 2014. Eighteen died before age 12, 53 died between ages 12 and 14, 292 died between ages 15 and 18, and 855 died between ages 19 and 25. Most were male (83%), and firearm was most common cause of death; 28% previously attempted suicide, 31% had a mental health diagnosis, and 17% were prescribed psychotropic medication. Younger children died by hanging/smothering (89% of all 7- to 11-year olds), and overdose/poisoning increased progressively with age. Adolescents had a higher proportion of females than young adults (23% vs. 14%, p = .002). Combining data from the medical examiner and large hospital systems allows examination of youth suicide from a developmental perspective. Differences between age groups included gender, method, diagnosed mental illness, and diagnosis of attention deficit hyperactivity disorder. These data point to missed opportunities for effective interventions for specific developmental stages.

Youth Suicide Deaths: Investigation of Clinical Predictors in a Statewide Sample.

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12,000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to result in asthma. Our top associated genes included those related to neurodevelopment or neural signaling (brain-derived neurotrophic factor (BDNF), neutral sphingomyelinase 2 (SMPD2), homeobox b2 (HOXB2), neural cell adhesion molecule (NCAM2), heterogeneous nuclear ribonucleoprotein A0 (HNRNPA0)), inflammation (free fatty acid receptor 2 (FFAR2)) and inflammation with additional evidence of neuronal involvement (oxidized low density lipoprotein receptor 1 (OLR1), toll-like receptor 3 (TLR3)). Of particular interest, BDNF has been previously implicated in both psychiatric disorders and asthma. Our results demonstrate the utility of combining pedigree and co-occurring phenotypes to identify rare variants associated with suicide risk in conjunction with specific co-occurring conditions.

/pdf/identifying-rare-variants-for-genetic-risk-through-a-109d1uh09o.pdf

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma

A DIGITAL TELLURIUM ATLAS FOR SPECTRAL CALIBRATION, 19000 - 24000 cm−1

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

J Cardon

Author Tools

Chat about Author

Papers

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma

A DIGITAL TELLURIUM ATLAS FOR SPECTRAL CALIBRATION, 19000 - 24000 cm−1