Summary: Researchers have identified genetic overlaps between different types of psychiatric disorders including ADHD, bipolar disorder, MDD and schizophrenia. They also identified an overlap between anorexia and OCD, as well as between Tourettes and OCD.
Source: Broad Institute.
Psychiatric disorders such as schizophrenia and bipolar disorder often run in families. In a new international collaboration, researchers explored the genetic connections between these and other disorders of the brain at a scale that far eclipses previous work on the subject. The team determined that psychiatric disorders share many genetic variants, while neurological disorders (such as Parkinson’s or Alzheimer’s) appear more distinct.
Published today in Science, the study takes the broadest look yet at how genetic variation relates to brain disorders. The results indicate that psychiatric disorders likely have important similarities at a molecular level, which current diagnostic categories do not reflect.
The study was led by co-senior authors Ben Neale, director of population genetics in the Stanley Center at Broad Institute of MIT and Harvard and a faculty member in the Analytical and Translational Genetics Unit at Massachusetts General Hospital, and Aiden Corvin, professor at Trinity College Dublin, with first author Verneri Anttila, a postdoctoral research fellow in Neale’s lab. The team further includes researchers from more than 600 institutions worldwide.
“This work is starting to re-shape how we think about disorders of the brain,” says Neale. “If we can uncover the genetic influences and patterns of overlap between different disorders, then we might be able to better understand the root causes of these conditions — and potentially identify specific mechanisms appropriate for tailored treatments.”
Exploring these biological connections is challenging. The brain is a tricky organ to study directly, difficult to scan in detail or ethically biopsy. And, because brain disorders often co-occur, it’s hard to untangle when one might be affecting the development of another.
To examine the biological overlap between these disorders, researchers must rely on genetics. For the current study, international consortia pooled their data to examine the genetic patterns across 25 psychiatric and neurological diseases. Because each genetic variant only contributes a tiny percentage of the risk for developing a given disorder, the analyses required huge sample sizes to separate reliable signals from noise.
The researchers measured the amount of genetic overlap across the disorders using genome-wide association studies (GWAS) of 265,218 patients and 784,643 controls. They also examined the relationships between brain disorders and 17 physical or cognitive measures, such as years of education, from 1,191,588 individuals. The dataset ultimately included all GWAS consortia studying common brain disorders that the team could identify with sufficient sample sizes.
“This was an unprecedented effort in sharing data, from hundreds of researchers all around the world, to improve our understanding of the brain,” says Anttila.
The final results indicated widespread genetic overlap across different types of psychiatric disorders, particularly between attention-deficit/hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder, and schizophrenia. The data also indicated strong overlap between anorexia nervosa and obsessive-compulsive disorder (OCD), as well as between OCD and Tourette syndrome.
In contrast, neurological disorders such as Parkinson’s and multiple sclerosis appeared more distinct from one another and from the psychiatric disorders — except for migraine, which was genetically correlated to ADHD, major depressive disorder, and Tourette syndrome.
According to the researchers, the high degree of genetic correlation among the psychiatric disorders suggests that current clinical categories do not accurately reflect the underlying biology. “The tradition of drawing these sharp lines when patients are diagnosed probably doesn’t follow the reality, where mechanisms in the brain might cause overlapping symptoms,” says Neale.
As a hypothetical example, a single mechanism regulating concentration could drive both inattentive behavior in ADHD and diminished executive function in schizophrenia. Further exploration of these genetic connections could help define new clinical phenotypes and inform treatment development and selection for patients.
Additionally, within the cognitive measures, the researchers were surprised to note that genetic factors predisposing individuals to certain psychiatric disorders — namely anorexia, autism, bipolar, and OCD — were significantly correlated with factors associated with higher childhood cognitive measures, including more years of education and college attainment. Neurological disorders, however, particularly Alzheimer’s and stroke, were negatively correlated with those same cognitive measures.
“We were surprised that genetic factors of some neurological diseases, normally associated with the elderly, were negatively linked to genetic factors affecting early cognitive measures. It was also surprising that the genetic factors related to many psychiatric disorders were positively correlated with educational attainment,” says Anttila. “We’ll need more work and even larger sample sizes to understand these connections.”
The consortia have made their GWAS data accessible online, either freely available for download or by application. They plan to examine additional traits and genetic variants to explore these patterns further, aiming to discover the relevant mechanisms and pathways that underlie and potentially link these disorders.
Funding: National Institutes of Health, Orion Farmos Research Foundation, Fannie and John Hertz Foundation funded this study.
Source: Karen Zusi – Broad Institute
Publisher: Organized by NeuroscienceNews.com.
Image Source: NeuroscienceNews.com image is in the public domain.
Original Research: Abstract for “Social genomics of healthy and disordered internet gaming” in Science. Published June 22 2018.
Social genomics of healthy and disordered internet gaming
Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders.
Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities’ assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms.
Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer’s disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations.
The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important “scaffolding” to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders.