An international team, made up of researchers from the University of Granada, Washington University in St. Louis, and the University of South Florida, has linked the symptoms of schizophrenia with the anatomical characteristics of the brain, by employing magnetic resonance imaging (MRI). Their research, published in the academic journal NeuroImage, could herald a significant step forward in the diagnosis and treatment of schizophrenia. In a major breakthrough, scientists have successfully linked the symptoms of the illness with the brain’s anatomical features, using sophisticated brain-imaging techniques.
By analyzing the brain’s anatomy, the scientists have demonstrated the existence of distinctive subgroups among patients diagnosed with schizophrenia, who suffer from different symptoms.
In order to carry out the study, the researchers employed a magnetic resonance imaging (MRI) technique called «diffusion tensor imaging» on 36 healthy subjects and 47 schizophrenic subjects.
The testsconducted on the schizophrenic subjects revealed that they had variousabnormalities in certain parts of their corpus callosum, a bundle of neuralfibers that connects the right and left cerebral hemispheres and is consideredessential for effective interhemispheric communication.
Anomalies in the corpus callosum
When theresearchers detected anomalies in the brain’s entire corpus callosum, theydiscovered that certain characteristic features revealed in the brain scanscoincided with specific schizophrenic symptoms. For instance, patients withspecific features in a particular part of the corpus callosum exhibited strangeand disorganized behaviour.
In othersubjects, the irregularities observed in a different part of this brainstructure were associated with disorganized thought and speech, and negativesymptoms such as a lack of emotion. Other anomalies in the brain’s corpuscallosum were associated with hallucinations.
In 2014,the same research group proved that schizophrenia is not a single illness.Rather, they demonstrated the existence of eight genetically distinctdisorders, each of which has its own set of symptoms. Javier Arnedo and IgorZwir, researchers from the University of Granada’s Department of ComputerTechnology and Artificial Intelligence, discovered that different sets of geneswere strongly linked with different clinical symptoms.
Schizophrenia is not a single illness
As Igor Zwir points out: «The current study provides further evidence that schizophrenia is a heterogeneous group of disorders, as opposed to a single illness, as was previously thought to be case.»
The researchers believe that, in the future, analyzing how specific gene networks are linked to specific brain features and individual symptoms, will be of fundamental importance and will help to ensure that treatments are adapted effectively to each patient’s specific disorder. Currently, treatments for schizophrenia tend to be generic, regardless of the symptoms exhibited by each individual patient.
In order to conduct the analysis of both the gene groups and brain scans, the researchers developed a new, complex analysis of the relationships between different types of data and recommendations concerning new data. The system is similar to that used by companies such as Netflix in order to determine the films they wish to broadcast.
Professor Zwir explains: «To conduct the research, we did not begin by studying individuals who had certain schizophrenic symptoms in order to determine whether they had the corresponding brain anomalies. Instead, we first analyzed the data, and that’s how we discovered these patterns. This type of information, combined with data on the genetics of schizophrenia, will someday be of vital importance in helping doctors treat the disorders in a more precise and effective way.»
Bibliography:
Decomposition of brain diffusion imagingdata uncovers latent schizophrenias with distinct patterns of white matteranisotropy
JavierArnedo, Daniel Mamah, David A. Baranger, Michael P. Harms, Deanna M. Barch,Dragan M. Svrakic, Gabriel A. de Erausquin, C. Robert Cloninger , Igor Zwir
NeuroImage120 (2015) 43-54
http://dx.doi.org/10.1016/j.neuroimage.2015.06.083
Contact:
IgorZwir
Departmentof Computer Technology and Artificial Intelligence
Universityof Granada
Phone:+34 958 240 468
WashingtonUniversity in St. Louis
Phone:+1 314 362 7014
Email:igor@decsai.ugr.es
