Good News!

We received an independent investigator grant for 5 years under the title “Development of early diagnosis technology for treatment-resistance schizophrenia based on glutamate-dopamine neural circuit using neuromelanin-sensitive MRI and MRS”. This research was supported by the Brain Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning.

Through this study, we plan to develop a crucial technology that reclassifies schizophrenia based on neuroimaging including MRS and Neuromelanin-sensitive-MRI according to dopamine-glutamate pathophysiology and early diagnosis of refractory schizophrenia without treatment response to antipsychotics.

A winter neuroimaging workshop.

We are conducting a neuroimaging workshop with second-year students from Pusan National University School of Medicine. Students learn basic principles of academic writing and systematic-review, Linux operation, and practice a neuroimaging analysis using Freesurfer. Participants parcelled the brains of patients with schizophrenia, compare the thickness of the cerebral cortex to the normal control group, and examine how the defective brain region is related to the actual clinical symptoms. We will also run an elective course that we can actually hypothesize using the given data and complete the paper.


A new clinical trial will begin.

Moschetti et al. Eur J Drug Metab Pharmacokinet 2018

Our clinic has participated in the international clinical trial named “A phase III randomized, double-blind, placebo-controlled parallel group trial to examine the efficacy and safety of BI 425809 once daily over 26 week treatment period in patients with schizophrenia (CONNEX-3)”

The new drug, developed by Boehringer-Ingelheim, is a glutamate-based medication that is expected to revolutionize the limitations of existing treatments for schizophrenia. This compound is a glycine transporter inhibitor that is being developed for the treatment of schizophrenia but was discontinued for Alzheimer’s disease. Glycine transporters GlyT-1 and GlyT-2 located in presynaptic and astrocyte membranes take up glycine into the nerve terminal and adjacent glial cells, thus modulating glycine levels in the synaptic cleft. By blocking these receptors, BI 425809 is proposed to increase glycine levels and its ability to modulate NMDA receptor function.

The drug is aimed to improve the cognition and daily functioning of patients. Patient recruitment is scheduled for April.

Good News!

Our new review paper named “The Role of Estrogen Receptors and Their Signaling across Psychiatric Disorders” has been accepted to the International Journal of Molecular Sciences (IF=4.556).

In this review, we analyzed the emerging literature on estrogen receptors and psychiatric disorders in cellular, preclinical, and clinical studies. Specifically, we discuss the contribution of estrogen receptor and estrogen signaling to cognition and neuroprotection via mediating multiple neural systems, such as dopaminergic, serotonergic, and glutamatergic systems. Then, we assess their disruptions and their potential implications for pathophysiologies in psychiatric disorders. Further, in this review, current treatment strategies involving estrogen and estrogen signaling are evaluated to suggest a future direction in identifying novel treatment strategies in psychiatric disorders.

Good news!

Our new study named “Prediction of psychosis: model development and internal validation of a personalized risk calculator” has been accepted to the Psychological Medicine (IF=5.7).

This study aimed to develop and internally validate a model for predicting the incidence of psychosis in CHR individuals to provide useful assistance in clinical practice. We developed a model that includes social functioning, social cognition, functional decline, verbal memory, and IQ; this model demonstrated fair predictive ability. Using this model, we divided the high-risk groups into three clusters, all of which showed significant differences in the incidence of psychosis. To the best of our knowledge, this is the first study using modern machine learning techniques to model a wide range of variables covering demographic, clinical, and cognitive functions in long-term cohorts spanning more than ten years.