Demystifying Schizophrenia and Related Psychotic Disorders

A veteran clinician-researcher seeks to advance knowledge of schizophrenia and related disorders.

Schizophrenia and related psychotic disorders have a lifetime prevalence of approximately 3.5% and account for a major health care burden in the United States. The disorders are also associated with reduced life expectancy – about 15 years shorter than the general population and a 5% to 10% risk of death by suicide.

While antipsychotic medications are effective for the management of psychotic symptoms (e.g., hallucinations, delusions), these drugs essentially all have the same function and targets: blocking dopamine and serotonin receptors. Recent developments in genetics, neuroimaging, and preclinical research have begun to untangle the mechanisms underlying schizophrenia and related psychotic disorders.

“The medications used to treat schizophrenia were discovered serendipitously and not based on objective brain characteristics matching the underlying mechanisms of disease,” says Elena Ivleva, M.D., Ph.D., an Associate Professor in the UT Southwestern Department of Psychiatry’s Division of Translational Neuroscience Research in Schizophrenia and a member of the Peter O’Donnell Jr. Brain Institute.

Dr. Ivleva is a dedicated physician-scientist in the field of neurobiological psychosis research. She focuses on understanding the neurobiological mechanisms of schizophrenia and developing human in vivo biomarkers for psychotic disorders, primarily using cognition and multimodal brain imaging approaches.

Seeking an Explanation

According to Dr. Ivleva, schizophrenia syndrome is a clinically and neurobiologically complex and heterogeneous illness, as reflected in the large number of independent risk genes for the condition and extensive variability in clinical presentation, outcomes, and neurobiological features.

Importantly, this notion suggests schizophrenia syndrome may in fact represent a combination of unique diseases with overlapping clinical presentations.

“In recent years, several studies have investigated this heterogeneity using a range of approaches,” Dr. Ivleva says. “MRI studies in schizophrenia have typically utilized case-control designs to identify group-level brain alterations in patient cohorts.”

The findings of these studies have led to the identification of regional gray matter alterations, such as decreased volume, cortical thickness, or surface area in many regions of the brain – but most prominent in frontal and temporal lobes – as well as widely distributed white matter alterations. While these group-level findings are of interest, Dr. Ivleva explains, the severity and specific features of neuroanatomical alterations vary widely among individual patients.

“It still remains unclear whether neuroanatomic variability is driven by varying degrees of illness severity or by qualitatively distinct schizophrenia subtypes,” she says.

The Search for Biomarkers

Dr. Ivleva is working within the five-site Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) team, led by Carol A. Tamminga, M.D., Chair of the UT Southwestern Department of Psychiatry and Director of the Psychosis Research Program. The team is looking at multiple biomarkers of brain function to delineate illness groups and predict psychosis responses. The B-SNIP consortium is studying the genetic, neurophysiological, imaging, and cognitive markers of severe mental illnesses. UT Southwestern is the consortium’s lead site; others are in Boston, Chicago, Hartford, and Athens.

To better grasp the complexity of the neuroanatomic milieu surrounding psychosis, Dr. Ivleva is employing the B-SNIP biomarker strategies, harnessing the power of MRI along with the clinical biomarkers to identify neurobiologically distinct subtypes within schizophrenia and related disorders. These strategies have the potential to move diagnostic and therapeutic practice away from a reliance on symptom and behavioral features, Dr. Ivleva notes.

“Whether quantitative imaging biomarkers can identify discrete subgroups of patients, thereby fostering personalized medicine approaches for patients, remains unclear,” she says.

Dr. Ivleva adds that neuroimaging is well-positioned for biomarker development in schizophrenic psychosis, explaining that it could capture phenotypic variations in molecular and cellular disease targets, or in the brain circuits themselves.

“These mechanistically based biomarkers collected in B-SNIP may represent a direct measure of the pathophysiological underpinnings of the disease process,” Dr. Ivleva says. “We are using biomarkers to explore novel treatment targets, aid in prediction of response, determine optimal treatment regimens, and provide a rationale for personalized medicine approaches.”

Subtyping a Complex Illness

Historically, many different clustering algorithms were used to classify patients with schizophrenic psychosis into subgroups based on similarities in symptoms or imaging features. However, no consensus was reached as to the definition of a “cluster.”

A novel density peak-based clustering (DPC) algorithm has recently been proposed by a group of researchers, which, when compared with conventional clustering algorithms, may be able to better detect nonspherical clusters and to automatically find the correct number of clusters, without initialization and multiple iterations.

In a recent study published in Schizophrenia Bulletin, Dr. Ivleva and colleagues examined cortical (surface area, cortical thickness) and subcortical (volume) morphology in a cohort of acutely ill patients with never-treated first-episode schizophrenia and clinically stable chronic patients with midcourse schizophrenia. The researchers matched each of these cohorts with a healthy control group.

In the study, gray matter was selected as the subgrouping feature because it consists of neuronal cell bodies, neuropil, glial cells, and synapses and is well documented to be altered in patients with schizophrenia. In addition, the novel DPC algorithm was used to classify individuals with schizophrenia into subgroups with distinct neuroanatomical features.

“The primary aim of the study was to identify the number and features of discrete subgroups in a sample of first-episode schizophrenia patients,” Dr. Ivleva says.

After analyzing the data, Dr. Ivleva and her colleagues successfully identified three subgroups of patients, defined by distinct patterns of regional cortical and subcortical morphometric features. Interestingly, a similar three-subgroup pattern was identified in the independent dataset of patients from the multisite B-SNIP consortium.

“Similarities of classification patterns across our two patient cohorts indicate the three-group typology is relatively stable over the course of illness,” Dr. Ivleva explains. “These findings provide new clues into distinct subgroups of patients with psychosis based on structural brain features.”

Based on these results, Dr. Ivleva believes that anatomic magnetic resonance subgrouping – along with other cognition, EEG, and eye-tracking biomarkers – may be able to be leveraged to separate neurobiologically distinct subgroups of individuals with psychosis. This represents an important step toward differentiating subtypes of psychotic disorders for understanding and treating the disorder.  

“Clinical and behavioral features have been shown over many years to have limited utility in stratifying schizophrenia patients for the purpose of clinical trials and personalized treatment,” Dr. Ivleva says. “Our results represent an important step toward the stratification of patients on the basis of a potential biomarker, as opposed to behavioral features.”

Taking Steps to Improve Care

In addition to her research efforts, Dr. Ivleva serves as the Director of the Early Psychosis Clinical and Research Program at UT Southwestern.

“Psychosis is a mental condition in which a person misinterprets information or loses touch with reality – it can impact thoughts, feelings, and behaviors, as well as what people believe, hear, or see,” Dr. Ivleva says. “Early psychosis refers to an initial phase of the illness – within the first two to three years – when a person first exhibits psychotic symptoms.”

Dr. Ivleva notes that prompt, comprehensive treatment is the best way to help manage the symptoms of early psychosis and set a person on the best possible long-term life trajectory. Within UT Southwestern Medical Center’s HOPE program, which stands for “Healing Over Psychosis Early,” she and her team provide innovative and comprehensive intervention for early psychosis in a compassionate, collaborative environment.

“We provide interventions including medication, individual psychotherapy, group psychotherapy, family support and education, employment and education services, and individualized case management,” Dr. Ivleva explains. “Our aim is to alleviate symptoms and restore functioning, with an ultimate goal of having patients live productive, fulfilling lives.”

While the mechanisms of psychotic disorders remain poorly understood, there are multiple causes and triggers for psychosis, including certain drugs, psychological trauma, brain injuries, and various medical illnesses. Genetic factors also play a role in development.

According to Dr. Ivleva, society often portrays individuals with psychosis negatively. However, with treatment, many people are able to achieve functional recovery and live personally meaningful lives. She says it is important to view psychosis as an obstacle to overcome rather than as a preset course with poor outcomes.

Powering Future Trials

In addition to exploring schizophrenia subtypes, Dr. Ivleva is also pioneering clinical trials for patients with early psychosis. In collaboration with Dr. Tamminga, she is conducting studies exploring brain-based biomarkers, including MRI, EEG, ocular motor function, and cognitive assessments. They are also exploring genetic and immunological features, as well as developing novel treatment protocols.

“Over the past two decades, we have seen an increased focus on early intervention in psychotic disorders in research and clinical practice,” Dr. Ivleva says. “Early symptom levels appear to be strongly predictive of later illness trajectories.”

Other researchers have proposed the idea of an “early therapeutic window,” she explains, where patients in the early phase of the psychotic illness – due to high levels of brain plasticity – might derive the highest benefit from interventions. As a result, many studies are now investigating the effect of early interventions aiming to reduce the duration of untreated psychosis as well as multidisciplinary, prolonged early interventions combining psychopharmacological, cognitive, and psychosocial interventions.

While specialized early interventions have been found to be more successful in reducing symptom burden and improving outcomes in individuals with psychosis, Dr. Ivleva acknowledges that we still do not possess the definitive key on therapies that can provide long-term symptom reduction and functional recovery. Thus, the development of new therapeutic interventions is needed.

Paving the Way for Advancements

The heart of psychosis research at UT Southwestern is to improve diagnosis of these illnesses and, ultimately, to find new targets for therapies.

Despite theories and accumulating data, even the most seasoned clinicians and researchers do not fully understand the mechanisms of therapeutic action underlying most of the current treatment options.

While it takes many years to accumulate the necessary data to confidently bring new treatment approaches to the clinic, Dr. Ivleva hopes to provide renewed optimism for clinicians, inspired by novel clinical and basic science research efforts.