summary: By investigating four preexisting publicly available neuropsychiatric datasets, researchers identify a network of brain regions that underlie psychiatric disorders including depression, anxiety, bipolar disorder and schizophrenia.
Source: Brigham and Women’s Hospital
Psychiatric illnesses, such as schizophrenia and depression, affect approximately one in five adults in the United States, and nearly half of patients diagnosed with a mental illness meet criteria for a second.
With so much overlap, researchers are beginning to suspect that there may be a single neurobiological explanation for a variety of psychiatric illnesses.
A new study by investigators from Brigham and Women’s Hospital, a founding member of General Brigham and General Healthcare System, looked at four pre-existing publicly available neuropsychiatric datasets and identified a network of brain regions underlying psychiatric illnesses.
Their results have been published in The nature of human behavior.
said corresponding author Joseph J. Taylor, MD, medical director of transcranial magnetic stimulation at Brigham’s Center for Brain Circuit Therapies and an associate psychiatrist in Brigham’s Department of Psychiatry.
Neurology asks: Where is the lesion? And psychiatry asks: “What are the symptoms?” We now have tools to explore the “where” question of psychiatric disorders. In this study, we examined whether psychiatric disorders share a common brain network. “
The researchers began by analyzing a set of structural brain data from more than 15,000 healthy controls as well as patients diagnosed with schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, or anxiety. They found a reduction in gray matter in the anterior cingulate and insula, two brain regions commonly associated with psychiatric illness.
However, only a third of the studies showed a decrease in gray matter in these brain regions. In addition, neurodegenerative diseases also showed decreased gray matter in these same regions.
To address these shortcomings, the team used the human neural network (the wiring diagram of the human brain) to test whether gray matter changes in psychiatric illnesses more effectively in a shared brain network than in shared brain regions.
Researchers explored a diagnostic network in which up to 85 percent of studies showed gray matter decline. This network was specific for gray matter decline in psychiatric versus neurodegenerative disorders.
They then performed the same analyzes excluding data from one psychiatric diagnosis at a time. The diagnostic network across diagnoses remained robust, suggesting that no single psychiatric illness was disproportionately responsible for the network they identified.
In post hoc analyzes of a dataset including brain imaging of 194 veterans with and without penetrating head injuries as well as their psychiatric diagnoses, the researchers superimposed lesions on the transient diagnosis network and found that damage from lesions in the network was associated with a higher likelihood of developing multiple psychiatric illnesses. . diseases.
They also used seasoned data to derive a diagnostic network based on brain lesions associated with psychiatric illnesses. They found that this lesion-based psychiatric network was very similar to the atrophy-based psychiatric network even though it was derived from an entirely different dataset.
Finally, the team used data from neurosurgical resections of patients with severe, untreatable psychiatric illnesses. Ablation targets correspond to the diagnostic grid.
Most surprising, Taylor said, is that their findings challenge the idea that gray matter decreases in the anterior cingulate and that the insula are causally linked to psychiatric illness.
“We found that the lesions in those areas were correlated less Mental illness, and nothing more, Taylor said, atrophy in that cingulate and insula may be a consequence or compensation for, rather than a cause of, a mental illness.
Instead, their analyzes point to the posterior parietal cortex as the brain network node most likely to be causally linked to mental illness.
By identifying a significant, sensitive, and specific diagnostic network for psychiatric illness, the team opened up a number of potential new directions for follow-up studies, including analyzing existing fMRI datasets to see whether patterns of neural activation follow the same circuit and investigating circuit-based differences in psychiatric disorders. Taylor also plans to use transcranial magnetic stimulation (TMS) to modify the network, specifically using the posterior parietal region as a target.
“Mental disorders are brain disorders, and now we’re just beginning to have the tools to study and modify its underlying circuitry,” Taylor said. “There may be more common factors across these disorders than we originally thought.”
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“Diagnostic network for psychiatric diseases resulting from atrophies and lesionsBy Joseph Taylor et al. The nature of human behavior
Diagnostic network for psychiatric diseases resulting from atrophies and lesions
Psychiatric disorders share neurobiology and occur frequently. This neurobiological and clinical overlap highlights opportunities for treatment across diagnosis.
In this study, we used focal and lesion network maps to test a common brain network across psychiatric disorders. In our meta-analysis of 193 studies, atrophy coordinates across six psychiatric disorders mapped to a common brain network defined by positive connectivity to the anterior cingulate and insula, and negative connectivity to the posterior and lateral parietal cortex.
This network was robust to leave validation across individual diagnoses and specific for dystrophic coordinates of psychiatric disorders versus neurodegenerative disorders (72 studies). In 194 patients with penetrating head trauma, damage to this network was associated with the number of post-injury psychiatric diagnoses. The goals of psychiatric neuroablation (four goals) are also in line with the network.
This converged brain network of psychiatric diseases may partly explain high rates of comorbid psychopathy and could shed light on neuromodulation targets for patients with more than one psychiatric disorder.