Evolutionary strategy reveals impression of missense variants in autism | Spectrum
Leveraging cross-species data on the evolution of proteins can help understand subtle genetic variants in people with autism and identify hundreds of new genes that may contribute to the condition, according to a new analysis.
The work focuses on “missense” variants that alter a single amino acid in a protein and often have mild effects. Although researchers have identified thousands of variants of missense in people with autism, filtering out those that contribute to the condition has been a challenge.
“The effects of a mutation that converts one amino acid to another in a protein is difficult to interpret,” says Olivier Lichtarge, professor of molecular and human genetics at Baylor College of Medicine in Houston who led the latest research. It could change the way the protein folds, breaks down, is transported, or interacts with other molecules, and predicting that outcome is complex, he says.
To identify variants of missense associated with autism, Lichtarge and his colleagues used an approach known as “evolutionary action,” which involves comparing the amino acid sequences of a protein across different species to determine the likely effect of missense. Derive variant.
Using this strategy, the team identified missense variants in 398 genes that could contribute to autism. Some are well-known genes associated with autism, such as RELN, PTEN, and SYNGAP1, but others have not been previously associated with the condition.
The approach “does seem to identify important mutations associated with autism,” says Ivan Iossifov, an adjunct professor at the Cold Spring Harbor Laboratory in New York who was not involved in the work. Although researchers have developed many methods to assess the effects of missense variants, detection of autism patients is still a major problem in the area, he says, and “this seems like a good approach”.
Evolutionary experiment:
Lichtarge and his colleagues looked for non-inherited or de novo missense variants in 2,384 people with autism and 1,792 of their unaffected siblings. The data comes from the Simons Simplex Collection, a collection of genetic and trait information from families with an autistic child. (The dataset is funded by the Simons Foundation, Spectrum’s parent organization.)
The autistic participants have 1,418 de novo missense variants that affect 1,269 genes and their siblings have 976 missense variants that affect 911 genes, the researchers reported in Science Translational Medicine in May.
The team calculated the evolutionary action score of each variant on a scale from 0 to 100; the higher the score, the more likely it is that a variant will damage the corresponding protein in the gene. The score takes into account two factors: the sensitivity of a particular point in the amino acid sequence of a protein to variants and the severity of the disorder caused by an amino acid change.
To measure sensitivity, the team used existing databases to compare amino acid sequences in proteins from different species for the protein associated with each mutated gene. They then measured the evolutionary distance associated with a change at a particular position in the sequence. If a change was associated with a great evolutionary distance, it was assumed that variants at this point likely change the function of the corresponding protein.
To assess the severity of a disorder caused by an amino acid change, the team measured how often a particular amino acid in any protein was swapped for another across species. A change that was seldom seen during evolution suggested that the new amino acid had different properties than the one it replaced and that the change was potentially harmful.
Although people with autism have more de novo missense variants than their siblings, the distribution of scores in the two groups wasn’t significantly different, and researchers say they couldn’t without their knowledge of genes associated with autism they would have been able to identify which of the affected genes contribute to the disease.
So the team grouped variants based on 368 biological pathways – focused on the variants in the 1,792 autistic people who have siblings – and examined the distribution of evolutionary action values. Only 23 signaling pathways were geared towards highly effective variants, many of which are associated with neural development, neural signal transmission, and the development of neural projections called axons.
Highly potent signaling pathways include 398 genes, many of which appear in the SFARI gene bank of genes associated with autism. (SFARI Gene is funded by the Simons Foundation.) Of these 398 genes, 28 were not categorized as “high trust” in 2017, but were listed as such in 2020.
These results suggest that the evolutionary action approach could help identify candidate genes for future research, the researchers say.
Severity:
In another analysis, the team divided people with autism into three groups based on their intelligence quotient (IQ). For each person they counted the evolutionary action value of the variants within the 398 genes.
People with the lowest IQ have the highest impact variants in the prioritized genes, supporting a link between the variants and autism, the researchers say. Cumulative values of rare, inherited missense variants also track the IQ, as another test shows.
Previous studies have found no statistically significant association between rare, inherited missense variants and the severity of autism traits, says Yufeng Shen, an adjunct professor of systems biology and biomedical informatics at Columbia University who was not involved in the research. So the evolutionary approach can be useful in uncovering the role these variants play in the disease, he says.
One limitation of the study is that the researchers did not systematically compare the evolutionary action approach to other methods that are commonly used to identify harmful missense variants, Shen says. “Without a comparison with other methods, it is very difficult to assess the contribution this method makes to autism research.”
The researchers also warn that IQ is only a measure of the severity of autism characteristics, and that a person’s impact score doesn’t necessarily predict their IQ.
The results are only the “tip of the iceberg,” says Lichtarge. Eventually, as researchers analyze more data, they can use evolutionary action assessments to find out how a person’s variants affect their genetic traits in more individualized ways.
Quote this article: https://doi.org/10.53053/VESX6574
