summary: The study suggests that there is an overlap between genetic architecture and co-morbid mental health diagnosis. Researchers have found that 70% of the genetic signals associated with schizophrenia are also associated with bipolar disorder. Anorexia and OCD have a strong and common genetic structure.
source: University of Colorado
More than half of people with a single mental disorder will be diagnosed in the second or third life. About a third have four or more.
This can make treatment difficult and leave patients feeling unlucky and frustrated.
But a comprehensive new analysis of 11 major psychiatric disorders offers new insight into why comorbidities are the norm, rather than the exception, when it comes to mental illness.
The study was published this week in the journal nature genetics, found that although no genes or set of genes underlie risk for all of them, subgroups of disorders – including bipolar disorder and schizophrenia; Anorexia nervosa and obsessive-compulsive disorder. And depression and severe anxiety – they share a common genetic structure.
“Our findings confirm that higher comorbidity across some disorders partly reflects overlapping pathways of genetic risk,” said lead author Andrew Grotzinger, assistant professor in the Department of Psychology and Neuroscience.
He said the finding could eventually open the door to treatments that treat multiple psychiatric disorders simultaneously and help reshape the method for diagnosis.
“If you had a cold, you wouldn’t want to be diagnosed with cough disorder, sneezing disorder, and joint pain disorder,” Grotzinger said.
“This study is a stepping stone towards creating a diagnostic guide that better maps what is actually going on biologically.”
How did the study work?
For the study, Grotzinger and colleagues at the University of Texas at Austin, Vrije Universiteit Amsterdam and other collaborating institutions analyzed publicly available genomic-wide association (GWAS) data from hundreds of thousands of people who submitted genetic material to large-scale data sets, such as the UK Biobank. Psychogenomics Consortium.
They studied genes associated with 11 disorders, including: schizophrenia, bipolar disorder, major depressive disorder, anxiety disorder, anorexia nervosa, obsessive-compulsive disorder, Tourette’s syndrome, post-traumatic stress disorder, alcohol use, and attention deficit hyperactivity disorder. and autism.
In addition, they looked at data collected via wearable motion trackers, and survey data documenting physical and behavioral traits.
They then applied new statistical genetics methods to identify common patterns across disorders.
They found that 70% of the genetic signals associated with schizophrenia were also linked to bipolar disorder. This finding was surprising, given current diagnostic guidelines, doctors would usually not diagnose an individual with both.
They also found that anorexia nervosa and obsessive-compulsive disorder have a strong and shared genetic structure, and that people with a genetic predisposition to having a smaller body type or a lower body mass index (BMI) also tend to have a genetic predisposition to these disorders.
Not surprisingly, given that the two diagnoses often combined, the study found significant genetic overlap between anxiety disorder and major depressive disorder.
Analyzing the accelerometer data, the researchers found that disorders that tend to cluster together also tend to share genes that influence how and when we move during the day.
For example, those with internalized disorders, such as anxiety and depression, tend to have a genetic makeup associated with reduced mobility throughout the day.
Compulsive disorders (obsessive-compulsive disorder, anorexia) tend to be linked to genes associated with higher movement throughout the day, and psychotic disorders (schizophrenia and bipolar disorder) tend to be genetically linked to excessive movement in the early morning hours.
“When you think about it, it makes sense,” Grotzinger said, noting that depressed individuals often appear as fatigued or low on energy, while those with compulsive disorders may have difficulty sitting still.
Overall, the study identified 152 genetic variants that are common across multiple disorders, including those already known to affect certain types of brain cells.
For example, it appears that genetic variants affecting excitatory and GABAergic neurons in the brain—which are involved in critical signaling pathways in the brain—strongly underlie shared genetic signaling across schizophrenia and bipolar disorder.
While much more needs to be done to determine exactly what specific genes do, Grotzinger sees the research as a first step toward developing treatments that can tackle multiple disorders with a single treatment.
“Today it is likely that many drugs will be prescribed to people in order to treat multiple diagnoses and in some cases these drugs can have side effects,” he said.
“By identifying what is being shared across these issues, we hope to devise ways to target them in a different way that does not require four separate pills or four separate psychotherapy interventions.”
In the meantime, simply understanding the genes behind their disorders may provide relief for some.
“It’s important for people to know that they not only have a terrible roll of the dice in life – that they do not have many different problems, but rather one set of risk factors that affect them all.”
About this genetics and mental health news
author: press office
source: University of Colorado
Contact: Press Office – University of Colorado
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“Genetic engineering of 11 major psychiatric disorders at the levels of bio-behavioral, functional genomic and molecular genetic analysis” by Andrew D. Grotzinger et al. nature genetics
Genetic architecture of 11 major psychiatric disorders at the bio-behavioral, functional genomic, and molecular levels of genetic analysis.
We interrogate the common genetic architecture of 11 major psychiatric disorders at the levels of behavioral, functional and molecular genetic analysis.
We identify four broad factors (neurodevelopmental, compulsive, psychotic and introspective) that underlie genetic associations between disorders and test whether these factors adequately explain their genetic associations with vital behavioral traits.
We present stratified genomic structural equation modeling, which we use to identify groups of genes that disproportionately contribute to genetic risk sharing. This includes protein-severing intolerant variant genes expressed in excitatory and GABAergic brain cells enriched for gene interference across disorders with psychotic features.
Multivariate correlation analyzes discover 152 (20) independent loci that act on individual factors and identify nine sites that act heterogeneously across perturbations within a factor.
Despite moderate to high genetic associations across all 11 disorders, we find little benefit to one dimension of genetic risk across psychiatric disorders either at the level of vital behavioral correlates or at the level of individual variants.