A new tool for linking genes, behavior and the brain is here and could dramatically change the field of neuroscience. Scientists have created a tool to detect which genes and their non-coding counterparts are associated with psychiatric and other brain disorders, something that is notoriously hard to pin down in patients.
Led by UNC School of Medicine neuroscientist Hyejung Won, PhD, she and fellow researchers have created ‘H-MAGMA’, a computational tool that improves current technology used to link non-coding genetic variants to genes associated with diseases through genome-wide association studies.
H-MAGMA is publicly available, widely applicable and available to the genetic and neuroscience research community for helping expand research.
Won and colleagues used H-MAGMA to study the genetic underpinnings of nine brain disorders, and identified new genes associated with each disorder.
The research, published in Nature Neuroscience, revealed that genes associated with psychiatric disorders are typically expressed early in life, highlighting the likelihood that the early period of life is critical in the development of psychiatric illnesses. The researchers also discovered that neurodegenerative disorder-associated genes are expressed later in life, and were able to link disorder-associated genes to specific brain cell types.
“By using H-MAGMA, we were able to link non-coding variants to their target genes, a challenge that had previously limited scientists’ ability to derive biologically meaningful hypotheses from genome-wide association studies of brain disorders,” said study senior author Hyejung Won. “Additionally, we uncovered important biology underlying the genetics of brain disorders, and we think these molecular mechanisms could serve as potential targets for treatment.”
Genome-wide association studies (GWAS) is a technique that allows researchers to compare genetic sequences of individuals with a particular trait—such as a disorder— to control subjects. Researchers do this by analyzing the genetic sequences of thousands of people. GWAS has revolutionized our understanding of the genetic architecture related to many health conditions, including brain-related disorders.
“To date, we know of hundreds of genomic regions associated with a person’s risk of developing a disorder,” Won said. “However, understanding how those genetic variants impact health remained a challenge because the majority of the variants are located in regions of the genome that do not make proteins. They are called non-coding genetic variants. Thus, their specific roles have not been clearly defined.”
Prior research suggested that while non-coding variants might not directly encode proteins, they can interact with and regulate gene expression.
“Given the importance of non-coding variants, and that they make up a large proportion of GWAS findings, we sought to link them to the genes they interact with, using a map of chromatin interaction in the human brain,” Won said. Chromatin is the tightly packed structure of DNA and proteins inside cells, folded in the nucleus in a way to maintain normal human health.
Won and colleagues used this map to identify genes and biological principles underlying the nine different brain disorders, including psychiatric conditions such as schizophrenia, autism, depression, and bipolar disorder; and neurodegenerative disorders such as Alzheimer’s, Parkinson’s, amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS).
Using the computational tool H-MAGMA, Won and colleagues could then link non-coding variants to their interacting genes (previously implicated in GWAS findings).
Another important question Won was able to answer with H-MAGMA was which cells were directly involved in brain disorders, clarifying the cellular etiology. This is critical information, as the brain is a complex organ with many different cell types that respond differently to treatments. In an attempt to differentiate critical cell types involved in each brain disorder, the researchers found that genes associated with psychiatric disorders are highly expressed in glutamatergic neurons, and genes associated with neurodegenerative disorders are highly expressed in glia. This information further demonstrates how the two cellular clusters diverge from each other.
“We classified biological processes central to the disorders,” Won continued on, listing another discovery the technology assisted in. “From this analysis, we found that the generation of new brain cells, transcriptional regulation, and immune response as being essential to many brain disorders.”
Won and colleagues also generated a list of shared genes across psychiatric disorders to describe common biological principles that link psychiatric disorders.
“Amongst the shared genes, we once again identified the brain’s early developmental process as being critical and upper layer neurons as being the fundamental cell-types involved,” Won said “We unveiled the molecular mechanism that underscores how one gene can affect two or more psychiatric diseases.”
Hopefully, this new system of studying gene interactions will lead to a more complete understanding of brain behavior, allowing for treatments of brain diseases and disorders to be more precise and powerful.
Brain disorders such as schizophrenia and Alzheimer’s disease are among the most burdensome disorders worldwide because there are few treatment options, largely due to our limited understanding of the genetics and neurobiological mechanisms involved in disease development and causation.
