In the rapidly advancing field of personalized medicine, the ability to predict a patient’s future health outcomes has shifted from general family history to high-definition genomic mapping. One of the most significant breakthroughs in this area is the Polygenic Risk Score (PRS). Unlike traditional genetic tests that look for a single, high-impact mutation—such as the BRCA1 gene for breast cancer—a PRS analyzes thousands, or even millions, of small genetic variations across an individual’s entire genome. Each of these variations, known as Single Nucleotide Polymorphisms (SNPs), might only have a tiny influence on its own. However, when these small effects are aggregated and weighted, they provide a powerful statistical estimation of an individual’s genetic liability for common, complex diseases like type 2 diabetes, coronary artery disease, and Alzheimer’s.
For healthcare professionals, the emergence of PRS represents a move toward “preventative stratification.” It allows clinicians to identify individuals who may appear healthy by traditional metrics—like blood pressure or BMI—but who carry a high genetic burden that puts them in the top 1% of the population for disease risk. Documenting these complex scores requires extreme precision, as they are often reported as percentiles or relative risk ratios.
The Scientific Engine: How PRS Is Calculated
The calculation of a Polygenic Risk Score is a feat of modern bioinformatics and big data. It begins with Genome-Wide Association Studies (GWAS), which involve scanning the genomes of hundreds of thousands of people to find specific variants that occur more frequently in those with a certain disease. Researchers assign a “weight” to each variant based on the strength of its association with the condition. To calculate an individual’s specific PRS, a computer sums up the weighted effects of all the risk-associated alleles they carry. The resulting number isn’t a diagnosis; rather, it indicates where that person sits on a spectrum compared to the rest of the population. Someone in the 99th percentile has a genetic profile that makes them significantly more susceptible to the disease than the average person.
Clinical Utility: Beyond “DNA Is Destiny”
One of the most important aspects of a Polygenic Risk Score is that it is not a deterministic “fate.” Unlike a monogenic condition where the presence of a gene almost guarantees the disease, a PRS describes a predisposition that can often be mitigated by lifestyle interventions. For instance, a person with a high PRS for heart disease can significantly lower their actual “absolute risk” by maintaining a healthy diet, exercising, and not smoking. In this context, the PRS serves as a motivational tool and a guide for targeted screening. If a patient knows they are at high genetic risk for colon cancer, their doctor might recommend starting colonoscopies at age 40 instead of age 50, effectively using the genetic data to “buy time” and prevent the disease from progressing.
The interpretation of these scores requires a collaborative effort between genetic counselors, primary care physicians, and the administrative staff who manage the flow of information. Because the science of PRS is still evolving, reports are frequently updated as new genomic data becomes available. Maintaining a clean, organized, and accurately transcribed medical history is paramount. Professionals who have invested in an audio typing course are better equipped to handle the rapid-fire dictation typical of genomic consultations. They understand the importance of transcribing not just the numbers, but the qualifying statements made by the clinician—such as the limitations of the score based on the patient’s ethnicity—which are critical for ensuring the patient receives equitable and safe care.
Ethical Challenges and Population Diversity
While the potential of Polygenic Risk Scores is immense, the technology currently faces a significant ethical hurdle: the lack of genomic diversity. Most GWAS data to date has been derived from individuals of European ancestry. Because genetic variations differ across global populations, a PRS developed using European data might not be accurate—and could even be misleading—when applied to individuals of African, Asian, or Hispanic descent. This “ancestry gap” is a major focus of research in 2026, as scientists work to build more inclusive biobanks. Until then, clinicians must be incredibly careful to document the ancestral context of every PRS result to avoid providing inaccurate risk assessments to minority populations.
This necessity for contextual documentation adds another layer of responsibility for medical transcribers. It is not enough to simply record a numerical score; the transcript must capture the doctor’s assessment of the score’s validity for that specific patient.
The Future: Integrating PRS into Routine Care
As we look toward the end of the decade, Polygenic Risk Scores are expected to become as common as cholesterol checks in routine wellness exams. We are moving toward a future of “genomic-first” medicine, where a child might have their PRS calculated at birth to guide a lifetime of personalized health decisions. This shift will generate an unprecedented amount of audio data as doctors discuss these profiles with millions of patients. The infrastructure of healthcare—both technological and human—must be prepared to handle this surge. The demand for specialists who can bridge the gap between spoken clinical insight and a perfectly formatted digital record will only continue to grow.
