Ask a GC: Genetic Counseling for Polygenic Risk Assessments (PRAs), Chapter 1

Series Introduction: Let’s be real - as a clinician, you have a lot of information to keep up with. Whether in primary care or a specialty field, the basic knowledge maintenance, continuing education requirements, and overwhelming barrage of new or updated innovations, companies, tests, methodologies, guidelines, etc. that clinicians have to keep up with can leave many feeling like there is barely any time to actually take care of patients. 

This can be especially true in regards to the ever-evolving field of Genomics. When our team at GenomicMD needs guidance wading through the chaos, we lean on our expert Genetic Counselors (GCs)-professionals with Master's degrees in Human Genetics & Genetic Counseling, which make them uniquely qualified to serve as translators for the alphabet soup that is genetic testing. This knowledge and experience has been so invaluable to the GMD team that it felt wrong to keep it all to ourselves, so 'Ask a GC' was created to 'share the wealth' with the clinicians (and patients) we serve. The next time you need a general update when it comes to Genomics (and particularly polygenic testing) let our GC team help guide you through the chaos and get to the heart of what you need to know, so you can get back out there where you want to be-with your patients!

Please note: Though GenomicMD's Ask a GC series is written under the guidance of genetics professionals and may refer to recent medical recommendations, it is not intended to be used as personalized medical advice. Patients seeking medical evaluation and clinicians seeking assistance with the development of healthcare plans should seek referral to an appropriate specialty provider.

Chapter 1 - An Introduction to Polygenic Risk Scores

Hello, and welcome to the latest edition of Ask a GC! This series, and more specifically, our next few clinically-focused posts, will likely be most helpful for genetic counselors and other clinicians looking to hone their polygenic testing knowledge. However, please feel free to read on if you’re interested in learning more about Polygenic Risk Scores (PRS), 
no matter your experience, background, or goals! 

PRS play an important role in personalized risk assessments and population health screening. However, there is a scarcity of published guidelines on how to implement them in a clinical setting. While this series is not intended to serve as a fully comprehensive or official guide, we hope that it will help get you up to speed on what's happening in the field of polygenic testing. Starting here in Chapter 1, we’ll review some definitions, differentiate PRS from other types of tests, review how they’re created, and discuss clinical applications. Let’s get started!

What are PRS and how are they different from other genetic tests?

In case you are not yet aware (or are a little rusty on PRS versus other, more historically well-known types of genetic testing), let’s look first here at how PRS are different from other genetic assessments/testing: 

Most people and clinicians will be familiar with Mendelian/monogenic genetic testing. These tests analyze very specific consecutive sequences of nucleotides within a given gene (or within a subset of genes that are all associated with a given disease/condition). There are thousands and thousands of such genes, in which one lone sequence error (referred to as a “mutation” or “pathogenic variant”) impacts the gene’s function with sufficient magnitude to result in significant risk for a given disease. Think of the following examples: 

• BRCA1/2 gene mutations and high breast/ovarian cancer risk
• CFTR gene mutations and cystic fibrosis (when a child inherits two mutations-one from each parent)
• PSEN1/2 gene mutations and early-onset Alzheimer’s disease (before age 60-65)

Alternatively, polygenic risk assessments (PRAs) analyze for the presence of many (dozens to millions) small genetic variants called single nucleotide polymorphisms, or SNPs, spread throughout the genome. Each SNP alone usually has minimal or virtually no impact on a person’s health. However, when combined together these SNPs can collectively result in significant risk for certain complex, multifactorial diseases such as: 

• Type 1 and 2 Diabetes (T1D/T2D)
• Coronary Artery Disease (CAD) and other cardiovascular disorders
• Multiple types of cancer
• Alzheimer’s Disease (specifically, more typical or ‘later’ onset types that occur after age 60-65)

The results of the PRA are consolidated into a score for each disease assessed-these are your polygenic risk scores (PRS). For each disease, the score is usually presented as a single value that represents that person’s relative risk for developing the disease–that is, the likelihood the person will develop the disease compared with (or relative to) the average individual. Some methodologies will compare these results to a more specific subset of people, like those of a particular ancestry or background. 

In some cases, the risks inferred by these collective SNPs are on par with (and sometimes even greater than) the risks associated with Mendelian diseases or monogenic variants. For example, a woman with a single mutation in a gene called CHEK2 has between a 20-40% lifetime risk for developing breast cancer (compared to the average woman’s risk of 12%). But a woman could have normal CHEK2 gene testing (i.e. no mutations identified), and have no mutations identified in any other single genes associated with high breast cancer risk (e.g. BRCA1/2), and yet her polygenic assessment could reveal the presence of numerous SNPs that collectively increase her breast cancer risk to or even above that 20% risk. 

It’s important to note that there are other types of genetic testing that don’t neatly fit into either of the above two categories of Mendelian/monogenic and PRA. One example you may have heard of is pharmacogenomic testing, often referred to as PGx. This type of testing analyzes how a person’s genetic code affects their metabolism of (or response to) certain medications.

How are PRS Developed?

PRS are developed using genome-wide association studies (GWAS). These are large population-based studies that scan the genomes of hundreds to thousands of people, looking for patterns and other signs of disease associations. For the purpose of PRAs, GWAS are used to identify SNPs that have a common population prevalence of >1% (we’ll discuss this in more detail in a future post) and are also associated with complex multifactorial diseases. These SNPs are then given a numerical weight and added together into a cumulative score that represents an individual’s polygenic risk score for that given disease. 

The inspiring thing about GWAS is that additional studies continue to be run, and with each sequential large-scale GWAS, PRS have the potential to continually improve in terms of their accuracy, applicability, what they can screen for, etc. There's a wealth of information to cover when it comes to PRS development, so if you’re unsatisfied with the length of this section because you find methodology talk especially fascinating, don’t worry–we will have an in depth discussion of the history of GWAS use in PRS creation in a future chapter of this series!

Clinical Applications

Now that we are up to speed with the definitions of PRS, how they are created, and how they differ from other types of genetic testing, you may be thinking: “Okay, so why should these tests be implemented into my practice?” (Great question!) Let’s start by reviewing the current general standards of risk assessment and from there discuss how PRS can bolster those methods.

More traditional medicine methods tend to approach patients based on where they fall according to standard risk factor criteria. Using type 2 diabetes as an example, we’ll first address the most basic risk factors¹:

• Age: all else being equal, patients over the age of 45 are known to have higher risk for type 2 diabetes than patients under the age of 45
• Sex: (does not appear to significantly influence risk for this disease)
• Ethnic background: patients of African American, Hispanic or Latino, American Indian, and Alaskan descent all have higher risk than those of European descent

Health risks can be further stratified when considering the following additional risk factor categories:

• Family history: a person with a first-degree relative with type 2 diabetes has higher risk for the disease than a person without a family history
• Lifestyle/behavioral factors: a person who is physically inactive/overweight has higher risk than those people who are active and have a healthy weight
• Standard lab test results: fasting blood sugar levels, hemoglobin A1C levels, and perhaps other screening labs will provide additional information for the healthcare provider to consider regarding the patient’s potential for disease

Now, let’s consider adding an additional tool to the risk assessment toolbox-polygenic risk scores. That additional step of specifying a patient’s disease risk based on their personal genomic profile is a cornerstone of personalized medicine–that is, healthcare plans and methods that are customized to each individual patient. By utilizing a personalized PRS in addition to the more traditional risk assessment methods, the following benefits may be achieved:

• Allowing patients access to the individualized assessment and care they need to reach their own personal highest health potentials.
• Encouraging those patients who are not receptive or adherent to suggested healthy practices to make better lifestyle choices. 
  • For example, a patient may believe they don’t need to exercise or eat healthy because they have no family history of heart disease, normal blood pressure, and normal screening labs. However, their polygenic score may suggest they are at increased risk for heart disease, and this may encourage them to make healthier lifestyle choices.
  • On larger scales, having patients follow healthier lifestyle practices in turn reduces overall burden on the healthcare system.
• Providing clinicians with additional assessment points to consider when determining the best course of action for a patient. This can be especially helpful in patients with less clear-cut histories and risk profiles. 
  • For example, in a previous role of mine as a GC working with breast surgical oncologists, it was not uncommon to see patients with a strong family history of breast cancer but with no causative gene mutations found in the affected relatives. It has historically been challenging explaining to these patients that despite the lack of an identifiable genetic cause, they are likely still at increased risk for cancer due to unknown genetic and/or environmental and/or behavioral risk factors. The use of PRA can, in some instances, explain at least some of that previously unknown genetic risk, helping us as clinicians to provide more concrete feedback to patients. 

Discussion 

The PRA is slowly but surely becoming a more prevalent method of accurately and successfully identifying a person’s individual risks for certain common diseases. Its use is becoming more widespread in various clinical areas (including the fields of oncology, psychiatry, cardiology, metabolic medicine, and more), and studies have shown that it is capable of improving healthcare outcomes both in individuals and in the healthcare system as a whole (stay tuned for more specifics on this in upcoming blog posts). 

While becoming familiar with a new type of risk analysis may take some time and a little practice, it will be worth it. Personalized genomic medicine is becoming more and more common across our ever-evolving healthcare landscape. Whether you actively pursue ordering PRAs or not, chances are high that you’ll see these sorts of reports trickle into your practice sooner or later. Familiarizing yourself with their methodology and clinical utilization now will ensure that you’re ahead of the game when that day comes! 

Our next post in this series will cover the history on how PRAs have progressed through the years, so stick around for our next edition of Ask a GC if you’re interested in learning more about the backstory of this fascinating technology!

Disclaimer 

This blog post is provided by GenomicMD’s certified genetic counselors to serve as a helpful resource and tool for genetic counselors and other clinicians. GenomicMD’s blog posts do not (and are not intended to) dictate an exclusive course of management, nor guarantee a particular outcome and are not intended to replace discussion with a qualified specialist.

Blog Glossary

Genome-Wide Association Studies (GWAS) - large, population-based studies that scan the genomes of hundreds to thousands of people looking for patterns and other signs of disease associations in the form of SNPs.

Mendelian/monogenic genetic testing - tests that analyze for mutations/variants in consecutive sequences of nucleotides within a gene, and in that gene a mutation impacts the gene’s function with sufficient magnitude to result in significant risk for disease.

Personalized medicine – healthcare plans/methods that are customized to each individual patient.

Pharmacogenomic testing - analyzes how a person’s genetic code affects their metabolism of certain medications.

Polygenic Risk Assessment (PRA) - the analysis for the presence of many genetic variants (SNPs) across the genome which, combined together, impact a person’s risk for developing certain common conditions or traits. The results of a PRA are presented as a single or group of PRS (typically one per disease).

Polygenic Risk Score (PRS) - a single value that represents a person’s relative risk for developing a condition compared to the risk for that condition in an average individual within the population. Note that, depending on the context, PRS can also mean polygenic risk scores (plural).

Relative Risk - the likelihood the person will develop a given disease compared with (or relative to) an average individual in the population. Some testing methodologies will compare results to a more specific subset of people, like those of a particular ancestry or background.

Single-Nucleotide Polymorphism (SNP) - The most common type of genetic variation among people. This type of genetic variation takes place at a single nucleotide placement in our DNA.

Traditional medicine - the method of caring for patients using similar standards no matter the age/sex/race/etc. of the patient (with obvious exceptions, like pediatric vs. adult, and sex-specific screens/treatments).

References

1. Centers for Disease Control and Prevention (CDC): Diabetes Risk Factors. Retrieved 28 September 2023 from https://www.cdc.gov/diabetes/basics/risk-factors.html