Polygenic scoring system may help to predict ALS risk

The score takes hundreds of different genetic variations into account

Marisa Wexler, MS avatar

by Marisa Wexler, MS |

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A RISK dial is turned toward high.

A new genetic risk score that takes hundreds of different genetic variations into account may help predict who’s most likely to develop amyotrophic lateral sclerosis (ALS).

The score needs to be validated in future studies before being used in the clinic, but could be important to stratify people according to their risk of developing the disease and aid in designing ALS prevention studies.

“This polygenic [multi-gene] scoring system we developed for ALS allows us to better understand the genetic architecture of the disease. This may help to distinguish which populations have greater odds to develop the disease and inform future prevention studies and interventions,” Stephen Goutman, MD, co-author of the study from the University of Michigan, said in a press release.

The study, “Cumulative Genetic Score and C9orf72 Repeat Status Independently Contribute to Amyotrophic Lateral Sclerosis Risk in 2 Case-Control Studies,” was published in Neurology Genetics.

The causes of ALS remain poorly understood. Genetics are thought to play a role and mutations in a few key genes have been shown to cause a minority of cases. Most people with ALS don’t have mutations in any of these genes, even in many cases where the disease runs in families and is presumed to have a strong genetic component, however.

Rather than looking at the effect of mutations in individual genes, the researchers here developed a scoring system that accounts for many different genetic variations cumulatively. “It is increasingly clear that many common [genetic variations] may contribute a small amount of disease risk,” they wrote.

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Assessing ALS risk

The scoring system was derived from an earlier genome-wise association study (GWAS) that included more than 20,000 people with ALS, along with nearly 60,000 people without it. A GWAS is a type of analysis to identify genetic variations that are statistically more common among people with a disease, which implies these variations might affect the risk of developing it.

The system took into account 275 ALS-associated single-nucleotide variations (SNVs), or places where one nucleotide (a building block of DNA) differs from person to person. The score excludes variations in or near the C9ORF72 gene, the most common single-gene cause of ALS.

Many of the 275 SNVs in this score are located in genes important for nerve cells’ health and function, noted the researchers, who calculated risk scores for 219 people with ALS, 7.8% of whom had a family history of the disease. Scores were also calculated for 223 people without ALS or a family history of the disease for comparison.

Using statistical analyses, the researchers evaluated whether the scores were significantly higher among people with ALS and found they were. For every one standard deviation increase in risk score, the likelihood of ALS was increased by about 28%.

Based on the models, the researchers estimated that, if a theoretical treatment were available that could completely eliminate the increased risk associated with these 275 genes, about 4.1% of cases wouldn’t have developed.

“Currently, there is no biomarker or tool that can definitively predict who will develop ALS later in life. Therefore, even if the polygenic score can only explain a small number of individuals at risk, it could be an important screening method for risk reduction,” the researchers wrote.

Findings from the initial analyses were replicated using data from a Spanish group of 548 ALS cases and 2,756 people without the disease. Because not all SNVs were available in this dataset, the analysis focused only on the 132 SNVs with available data. Nonetheless, the results in the Spanish cohort showed the risk of ALS was significantly increased among those with a higher genetic risk score, consistent with the results from the original analysis.

“Although the SNVs included in the polygenic score were adjusted due to the available overlap of SNVs in both data sets, there was consistency in the magnitude of the polygenic score effect, further providing support for our proposed polygenic score. Replication of polygenic scores is critical to ascertain that the methods and population background used to develop the score is generalizable,” wrote the researchers, who emphasized that further research that looked at at more SNVs in larger sample sizes was needed to verify the results and refine the genetic risk score. Diverse populations should be included to make the findings as generalizable as possible, they said.

“There is a lot of room for improvement in ALS prediction so that folks at risk can be identified for prevention and treatment. Future research into additional risk factors, including environmental exposures, will be critical,” said Kelly M. Bakulski, PhD, study co-author and professor of epidemiology at the University of Michigan.