Second schizophrenia subtype identified
Researchers from the University of Pennsylvania School of Medicine have identified two distinct neuroanatomical subtypes of schizophrenia after analysing the brain scans of more than 300 patients from three continents. By examining the scans, the researchers found that one-third of the study participants had brains that looked similar to healthy brains.
The first type of schizophrenia showed lower widespread volumes of grey matter compared with healthy controls, while the second type had volumes similar to normal brains. The findings are published in the journal Brain.
“Numerous other studies have shown that people with schizophrenia have significantly smaller volumes of brain tissue than healthy controls. However, for at least a third of patients we looked at, this was not the case at all — their brains were almost completely normal,” said principal investigator Professor Christos Davatzikos, from the Perelman School of Medicine at the University of Pennsylvania.
“In the future, we’re not going to be saying, ‘This patient has schizophrenia’. We’re going to be saying, ‘This patient has this subtype’ or ‘this abnormal pattern’, rather than having a wide umbrella under which everyone is categorised.”
Schizophrenia is a poorly understood mental disorder that typically presents with hallucinations, delusions and other cognitive issues, although symptoms and responses to treatment vary widely. Up until now, attempts to study the disease — by comparing healthy and diseased brains — have neglected to account for this heterogeneity.
To better characterise the distinct brain differences within the schizophrenia patient population, brain scans were analysed using a machine-learning method called HYDRA (Heterogeneity Through Discriminative Analysis), which helps to identify ‘true disease subtypes’ by limiting the influence of confounding variables.
“This method enabled us to subcategorise patients and find how they differed from the controls, while allowing us, at the same time, to dissect this heterogeneity and tease out multiple pathologies, rather than trying to find a dominant pattern,” Davatzikos said.
The research team observed that out of 115 patients with schizophrenia, nearly 40% did not have the typical pattern of reduced grey matter volume that has been historically linked to the disorder. In fact, their brains showed increases of brain volume in the middle of the brain, in an area called the striatum, which plays a role in voluntary movement. When controlling for differences in medication, age and other demographics, the researchers could not find any clear explanation for the variation.
“The subtype 2 patients are very interesting because they have similar demographic and clinical measures with subtype 1, and the only differences were their brain structures,” said Ganesh Chand, a lead author and postdoctoral researcher in the radiology department at Penn.
There are a variety of antipsychotic medications available to manage the symptoms of schizophrenia, but how they affect a particular patient is often a shot in the dark, according to study co-senior author Associate Professor Daniel Wolf.
“The treatments for schizophrenia work really well in a minority of people, pretty well in most people, and hardly at all in a minority of people. We mostly can’t predict that outcome, so it becomes a matter of trial and error,” Wolf said.
“Now that we are starting to understand the biology behind this disorder, then we will hopefully one day have more informed, personalised approaches to treatment.”
As to why an entire subset of patients with schizophrenia have brains that resemble healthy people, Davatzikos is not willing to speculate.
“This is where we are puzzled right now,” Davatzikos said.
“We don’t know. What we do know is that studies that are putting all schizophrenia patients in one group, when seeking associations with response to treatment or clinical measures, might not be using the best approach.”
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