Insights Into Mechanism-Based Biomarkers for Psychosis Prediction from Kim Do, PhD

Data on prevalence of first-episode psychosis resulting in subsequent schizophrenia diagnosis is mixed, and variation of symptoms can make it difficult to gauge whether a patient experiencing psychosis will have further episodes or develop a disorder later on. As psychiatry continues research into biological markers for identifying and diagnosing psychiatric disorders, Kim Do, PhD, has contributed to biomarker research to predict psychosis based on specific mechanisms in the brain. At this year’s American Psychiatric Association annual meeting, Do sat down with Psychiatric Times to share more about her conference presentation on biomarker research.

Psychiatric Times: Could you share the clinical highlights of your presentation on biomarkers for psychosis prediction here at APA?

Kim Do, PhD: My talk is about mechanism-based biomarkers at the early stage of psychosis and why they are important for psychiatry. There are many challenges, but especially in psychosis because there are a heterogeneity of symptoms. We know that many positive symptoms (which are hallucination, delirium, etc), they are currently able to be well-controlled by antipsychotics. But there are symptoms such as cognition and negative symptoms which are really not as well treated. Also, there is heterogeneity and dimension overlap, which at the early phase can overlap and they evolve during the development of the disease, and maybe some years later on we see dementia, schizophrenia, mania. The high heterogeneity of treatment outcome and trajectory is also important to note.

So, there are unmet needs. As I said, we do have treatments for cognitive deficits, but also we need a precise, stage-specific mechanism-based biomarker in order to stratify this heterogeneity and move towards precision medicine. We should be going away from one size fits all to giving the right treatment at the right time to the right patient. To deal with all that, we have a new approach. This is a translational approach in 2 ways: coming from patient, seeing the deficit or the impairment, and going to preclinical models to understand the mechanism. So that is what we are proposing is a biomarker for early detection, monitoring of the disease, and having better, stage-specific treatment.¹

One highlight is a biomarker linked to the redox hub. So this is a model on which we have been working for about 2 decades and we are working on validating that in both preclinical and clinical approach, there is convergence of genetic risk with environmental risk and oxidative stress.² And this is a vicious cycle and feed forward interaction with other mechanisms such as NMDA receptor hypofunction, neuroinflammation, mitochondria dysfunction, and, this contributes to impairment of what we call the micro neurocircuit. This is tapping into what we call parvalbumin interneurons and the excitatory inhibitory imbalance. And on the other side is macrocircuit, linking different region of the brain, tapping into oligodendrocytes and myelination, and that would be of basis of cognitive deficit and gamma synchronization.

Working on this hypothesis, we have found that for mitochondria dysfunction, which we found in animal model, the parvalbumin interneuron is critical for gamma oscillation, and this is critical for cognitive function. But these are impaired in schizophrenia. Specifically, we have demonstrated that in early psychosis patients, meaning patients in the early stage for 3 years after the onset of the first episode symptoms, we have been able to identify thanks to the mechanism-based biomarker.

PT: Why are blood biomarkers specifically useful for psychosis prediction—how does that blood analysis work?

The exosomal biomarker of microRNA, which is master regulator of oxidative stress, they are impaired and altered, letting us stratify subgroups of patients with psychosis risk. About 50% of the early psychosis patients in our study cohort at Lausanne had alteration of this biomarker of the parvalbumin interneuron, where mitochondria in these parvalbumin interneurons are impaired; these patients with high risk of mitochondria dysfunction had worse cognitive function, worse functional outcome, and worse symptomatology. So we have been able to classify distinct subgroups with very high accuracy, meaning we can identify at the individual level. If you have this mechanism-based biomarker altered, you have high risk of mitochondrial function, and that is the target we are looking at. For treatment indications, at least in preclinical model, we found a mitochondria-targeted antioxidant, which is called MitoQ. This is an antioxidant which can cross the blood-brain barrier and have around 10 times more effect than something like ubiquinone. We are now doing translation work to test MitoQ in early psychosis patients as well.

For the prediction aspect of our work you have to first go to early phase, and now prediction is dealing with what we call the prodromal phase. This is where, individuals are not yet patients, not all of them at least—they have subthreshold symptoms. The threshold is defined by DSM criteria, where they have, for example, psychosis, but not with full severity and the necessary period of time, so they are subthreshold. The challenge is that only 15 to 30% of what we call clinical high risk, because they have got some clinical symptomatology, will convert to psychosis, right? And that is the next challenge, to predict who will convert or not convert. Thanks to this exosomal biomarker of the redox hub, the oxidative stress hub, we have some idea into prediction.

But why are we focused on the exosomal? Because that is extracellular vesicle which is released by many organs, among them the brain, that can release in the blood. But we can tag them and with this we are also measuring the microRNA, which are master regulators of this pathway, with neuroinflammation and MDA receptor hypofunction. With these exosomal microRNA, we can predict with an outstanding index, who will transition to psychosis.

PT: Why is the field in need of more accurate and biomarker-based test for psychosis prediction?

We do have the potential clinical benefit with this biomarker, where we can predict accurately for more individuals who may convert to psychosis, compared to the standard what we have now of only using the clinical symptoms. What is unique in what I presented at APA, and is not yet published, is that we had an external validation cohort. So this development of the prediction model has been done in a multicenter cohort. It was a multi-country cohort of around 300 patients at clinical high risk. And among them, we saw during the follow up that 18% had converted to psychosis.

Dr Do is a professor of translational psychiatry at Lausanne University.

References

1. Do KQ. From Brain to Blood: Mechanism-Based Biomarkers for Psychosis Prediction and Personalized Early Intervention: Presidential International Lecture. Conference Proceedings of the American Psychiatric Association. May 2026;16-20. San Francisco, CA.

2. Steullet P, Cabungcal JH, Monin A, et al. Redox dysregulation, neuroinflammation, and NMDA receptor hypofunction: a "central hub" in schizophrenia pathophysiology? Schizophr Res. 2016;176(1):41-51.