Could Methylation States Inform Predictive Risk Scores?

Could Methylation States Inform Predictive Risk Scores?

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Initially published November 7, 2022, | Updated February 14, 2023

In honor of Valentine’s Day, we’re showing some love to a previous post we made back in November. We’ve added some additional context around how our friends at Sampled can help store, manage, analyze, research, and transport samples.

The Goals of Precision Medicine

Anybody who’s anybody is trying to identify biomarkers these days. The cool kids in town are seemingly all about methylation data when it comes to identifying biomarkers and diagnostics. And who can blame them? This epigenetic info holds a ton of potential for making accurate predictions.

We partner with R&D teams looking to extract meaningful insights from biological data with a fundamental goal to be able to predict clinical phenotypes using patient data, from electronic health records for example.

Here’s what’s exciting: genetic data from, say, a polygenic risk score (PRS) can be used synergistically with electronic health record (EHR) data to be more predictive*. Meaning the more genomic elements you have integrated into a predictive model, the better its predictive power.

*A PRS is a metric of disease risk for a clinical phenotype based on the combination of multiple genetic markers

What are Methylation Risk Scores?

How does this transition into a methylation risk score? Well, in a recent study from npj Genomic Medicine, researchers calculated an epigenetic parallel to the polygenic risk score and called it a methylation risk score or MRS. They did this for more than 800 samples. These methylation risk scores consisted of a combination of the methylation states across the genome.

Genomic methylation is one of the key mechanisms that influence gene expression. In simpler terms, methylation is one way that genes are turned on or off. The authors at UCLA combined the methylation risk score with existing computational tools to predict clinical outcomes based on electronic health record data and polygenic risk scores. Including the MRS as a medical feature improved the imputation of lab tests by a whopping 37% using state-of-the-art computational methods for electronic health record data analysis. Not a bad result when you consider the convenience factor and ease of tissue acquisition – the tissue source is whole blood and was done on the EPIC Illumina Array.

It’s true that validation of array-based data is prudent and recommended. And some of you may remember our previous blog on this topic when we announced PacBio’s recent announcement that their new Revio platform will allow for direct measurement of methylation states on its sequencing runs. That puts things into context for older array technologies!  But overall, the big picture still remains that with more readily available methylation data, this type of risk score could become a very useful diagnostic tool.

How biobanking provides control, consistency, and efficiency

As more and more companies send tissue samples to have the DNA/RNA extracted for sequencing, people are realizing the importance of storing samples right next to the sequencing facility. For this reason, biobanking is becoming incredibly popular.

Sampled is a company that offers custom biobanking services, which are becoming increasingly important in the field of bioinformatics. As research becomes more advanced, the need for storing, managing, analyzing, researching, and transporting samples becomes more pressing. Sampled’s team of experts deals with data types of many different forms and works with leading sequencing platforms. This allows them to provide the best service possible and help our clients stay at the cutting edge of research. If you have a sample, Sampled SMART Labs can help Store it, Manage it, Analyze it, Research it, and Transport it. Visit to learn more.

Outsourcing Bioinformatics Analytics: How We Can Help

Once you have your sample and data, we can help you realize your biological data’s full value to answer your research questions with speed and certainty. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey.

As experts across data types from cutting-edge sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing, and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.

Dan Ryder, MPH, PhD

Dan is the founder and CEO of Bridge Informatics, a professional services firm helping pharmaceutical companies translate genomic data into medicine. Unlike any other data analytics firm, Bridge forges sustainable communication change between their client’s biological and computational scientists. Dan is particularly passionate about improving communication between people of different scientific backgrounds, enabling bioinformaticians and software engineers to collectively succeed.
Prior to forming Bridge Informatics, Dan served in a variety of roles helping pharmaceutical clients solve early-phase drug discovery and development challenges.
Dan received both a Ph.D. in Biochemistry and Molecular Biology and an MPH in Disease Control from the University of Texas Health Science Center at Houston (UTHealth Houston). He completed his postdoctoral studies in Molecular Pathways of Energy Metabolism at the University of Florida College of Medicine. Dan received his undergraduate degree in Microbiology from the University of Texas at Austin.

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