Researchers at the University of Haifa have recently identified genetic changes in the blood that can identify when a patient with Bipolar Disorder (BD) is likely to attempt suicide.
Mental health is an often silent killer, taking more than 700,000 lives each year. Suicide risk in patients with BD is up to 3x that in patients with chronic depression; in people with BD, between 30-60% attempt suicide at least once in their life, and up to 20% tragically die by suicide.
BD is characterized by depressive and manic episodes. This causes mood fluctuations over time with low lows and high highs that, when overlapping, lead to people being extremely depressed and suicidal, without the lack of energy that comes with typical depression, leading to an increased likelihood of suicide attempts.
The new technique has 95% accuracy at detecting suicide risk, a previously unheard accuracy. This development hopes to improve the ability to provide BD patients with support in their time of most need.
By providing psychiatrists with insight into the risk of suicide, the new technique will allow support to be implemented before tragedy strikes.
How was the study carried out?
The study involved RNA sampling on 20 caucasian patients with BD. The RNA was sequenced and analyzed by an algorithm, assessing five distinct classifiers for their ability to predict suicidal and non-suicidal outcomes.
The patients were treated with a variety of medications and divided into two groups: “Suicide”, containing the six patients who died by suicide after sampling, and “Non-Suicide”, containing seven individuals who were monitored for an average of 4 years without any suicide attempts or known family history. The remaining seven patients were used for testing; they had mixed histories and were used to check if the algorithm could classify new data.
The researchers narrowed down the genetic markers to the top-10 genes, selected by the Machine Learning (ML) algorithm.
Findings
The study was focused on developing biomarkers that can be extracted with ease from biological samples to identify the increased risk of suicide attempts in people with BD. They found that various proteins had altered neurons from BD patients; certain proteins were seen to be changed in the group of suicide victims.
These proteins are important for cell growth, immune responses, and cell differentiation, which have important implications for the biological phenomena leading to suicide attempts. They found eight genes that had high accuracy at predicting suicidal and non-suicidal outcomes, and tested the ML algorithm with 50 repetitions to ensure robustness.
The seven patients who did not fall into either group were used to test the ML algorithm’s accuracy at predicting suicide risk. They identified a distinct gene expression signature connected to increased suicide risk by comparing the RNA sequencing of the patients who had died by suicide to that of the patients at low risk.
It found neurophysiological changes in the neurons of patients at high risk, meaning that the researchers can spot, based on physical changes to the genetic makeup of the body, if a BD patient is at high risk of suicide.
What comes next
The study points to a “complex interaction between genetic factors that impact neurological and cardiovascular health”, highlighting this data’s potential to identify biomarkers for assessing risk of suicide.
The study can hopefully be implemented to improve treatment outcomes for BD patients, providing new insights into the genetic markers behind the 30-60% of people with BD who attempt suicide. It should therefore be able to facilitate earlier intervention, which is hoped to reduce the suicide rate in patients with BD.
These Israeli pioneers are opening up new routes for treatment and management of suicidality in people with Bipolar Disorder, which could have massive impacts on mental health care for such a vulnerable group.