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Blood-Based PTSD Diagnostic Being Developed by Indiana University Team


NEW YORK (GenomeWeb) – The Indiana University School of Medicine is leading a team of researchers developing a gene expression test to detect post-traumatic stress disorder.

The new testing platform could lead to earlier intervention and prevent PTSD occurrences in more patients, according to Alexander Niculescu, one of the test's leading developers, who is a psychiatry professor at IU School of Medicine and a psychiatrist at the Indianapolis VA Medical Center.

A blood test that measures gene expression biomarkers associated with stress disorders such as PTSD could offer a viable method of diagnosis and complement existing clinical validation methods, Niculescu said in an interview.

In a study published recent in in Molecular Psychiatry, he and his colleagues describe their work tracking more than 250 military veterans at the Richard L. Roudebush VA Medical Center in Indianapolis, and identifying, analyzing, and validating 285 gene expression biomarkers associated with PTSD that they intend to use as a basis for a blood test that doctors will be able to begin using in the medium term.

Getting the test ready for a commercial launch will depend on a number of variables coming together — including achieving broader validation in larger studies — but the test could be available within about two years on an early-access basis to physicians interested in sending samples for commercial testing to a CLIA-certified laboratory, Niculescu said.

He has founded an undisclosed startup company that is working to commercialize the test. After offering early access laboratory developed testing to physicians and then pushing its broader adoption as an LDT, he anticipates pursuing US Food and Drug Administration clearance and seeking approvals for reimbursements from public and private payors. In planning out a commercial pathway his company will follow the blueprint of other companies that have been successful in getting reimbursement approvals for their tests, Niculescu said.

For diagnosing PTSD, which is currently largely based on the observation and assessment of symptoms, a biomarker-based test could represent a new frontier.

Joseph Rayman, a neuroscientist at Columbia University’s Zuckerman Institute, said in an interview that "as scientists continue to unravel the biological basis of PTSD, it will be possible to develop reliable clinical tests based on analysis of genes and gene expression, which should facilitate diagnosis, improve estimation of risk, and enable more personalized medical treatment."

Rayman is the first author or a study published last week in Cell Reports that points to TIA1 as a new target in the fight against PTSD.

A single gene may account for only a small proportion of overall risk, Rayman noted. Therefore, clinical tests based on the analysis of genes and gene expression will need to evaluate many genes or biomarkers simultaneously, Rayman said, adding that the "work by Niculescu and colleagues is an admirable step in the right direction."

Diagnosing PTSD requires considering factors in addition to genes. The condition is caused by a complex interaction between many genes and environmental factors, and an accurate interpretation of such tests will depend on additional variables such as gender, early life stress, and access to social support, among other variables, Rayman said.

However, lack of objective testing and the existence of a stigma associated with PTSD has been a hindrance to people getting properly diagnosed and treated, Niculescu said, adding that the belief that PTSD is a weakness to be concealed more than a condition that is determined by biology has been a contributing factor.

His team's current platform uses whole blood from a tube and quantitatively measures RNA expression using microarrays, but for clinical applications, it could incorporate gene expression testing by qPCR or RNA sequencing.

Initially, the test is likely to be completed in a laboratory but "technology is evolving so fast that RNA levels could be measured in clinics in the not-too-distant future," Niculescu said.

Gene expression study

The researchers began their work about 10 years ago by conducting whole-genome gene expression testing. Over the course of multiple visits to the VA center in Indianapolis, the researchers analyzed the blood of the study participants for detectable changes in gene expression and compared the results when the patients were experiencing low stress and high stress as a basis for the discovery of biomarkers.

The researchers used a four-step process of biomarker discovery, prioritization, validation, and then testing in an independent cohort and, in the end, narrowed the study's focus down to 285 individual biomarkers. The gene expression markers were predictive of high-stress and whether patients would be admitted to a hospital for psychiatric treatments related to stress.

Targeting patients who had severe psychiatric symptoms and high scores on a PTSD scale, they found that FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1 to be the genetic biomarkers with the best overall fit for association with stress.

Across all subjects tested, NUB1 was the top risk biomarker after validation and the best predictor for high stress state. APOL3 was the best predictor for first-year future hospitalizations with stress.

FKBP5, a gene involved in stress response that served as a positive control for the study, was one of the top biomarkers to make it through validation, Niculescu said. As an additional control, the group also compared their biomarker findings with telomere length, an established biomarker of psychological stress.

They found new predictive biomarkers, such as NUB1, APOL3, MAD1L1, and NKTR, that were comparable or better predictors of stress than better known telomere length and FKBP5.

More than half of the top predictive biomarkers of stress to emerge from the study had prior evidence of an association with suicide, and most were associated with other psychiatric disorders.

Niculescu noted that some of the biomarkers are targets for existing drugs and have potential utility in patient stratification and pharmacogenomics approaches to treatment.

Using the biomarker signatures that they discovered, the IU group searched in databases that combined specific molecular signatures with associated drugs and natural compounds. That yielded leads for possible new drug candidates and natural compounds, such as calcium folinate and betulin.

"We think of this as a one-two punch where you first assess and diagnose people with a quantitative test and then pair them with the correct treatment," Niculescu said.