Association of polygenic risk scores with low-density lipoprotein cholesterol levels and control: findings from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)
This study evaluates twenty polygenic risk scores in the diverse Hispanic Community Health Study/Study of Latinos cohort, finding that a score prioritizing functional annotations (PolyFun-pred) best predicts LDL levels and statin treatment response across subgroups, thereby highlighting the need for tailored precision medicine approaches to address genetic heterogeneity and prevent health disparities in Hispanic/Latino populations.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer
Heart disease remains one of the most persistent threats to health, and high levels of a specific type of fat in the blood, known as low-density lipoprotein or LDL, are a primary driver of that risk. For decades, doctors have relied on medications like statins to lower these levels, yet many people struggle to keep their numbers in a safe range, particularly within Hispanic and Latino communities where awareness and treatment rates often lag behind other groups. Scientists have recently begun using a tool called a polygenic risk score, which acts like a genetic report card, to estimate a person's risk based on thousands of tiny variations in their DNA. While these scores have been tested extensively in people of European ancestry, they have rarely been evaluated in the diverse tapestry of Hispanic and Latino populations, who carry a unique mix of genetic backgrounds from Europe, Africa, and the Americas. Understanding whether these genetic tools work for everyone is essential to ensuring that precision medicine does not leave some communities behind.
Researchers from the Hispanic Community Health Study/Study of Latinos set out to test how well twenty different versions of these genetic risk scores performed in a large group of over eleven thousand Hispanic and Latino adults living in the United States. These participants, recruited from four different communities, provided detailed health information and genetic data, allowing the team to see if the scores could accurately predict who would have higher LDL levels and who would struggle to control those levels even while taking medication. The study focused on comparing scores built from different types of genetic data to see which ones could best capture the complexity of this population.
The investigation revealed that no single genetic score worked perfectly for every subgroup, but one specific approach stood out for its ability to handle diversity. A score that prioritized functional parts of the genome and used data primarily from European studies actually performed better than scores built specifically from Hispanic or Latino data for many of the subgroups tested. This finding was surprising because it suggested that for this specific trait, a method refined on European data, when applied carefully, could offer a clearer picture of risk for people with Caribbean, African, or Indigenous American ancestry than methods designed specifically for them. The researchers found that for every step up in this genetic risk score, LDL levels rose by a measurable amount, ranging from three to fourteen milligrams per deciliter, a difference that could significantly impact long-term heart health.
Perhaps more importantly, the study showed that a high genetic risk score did not just predict higher cholesterol levels; it also predicted a harder time getting those levels under control with standard treatment. Among the participants who were already taking statins, those with higher scores were less likely to have their LDL levels reach the target range. This suggests that for individuals with a high genetic burden, standard medication might not be enough on its own, and they may require more aggressive or tailored management strategies. The results indicate that while these genetic tools hold promise for identifying who is at greatest risk, they are not yet a one-size-fits-all solution. The genetic diversity within the Hispanic and Latino community is so vast that a single approach cannot serve everyone equally, and further refinement of these tools is necessary before they can be safely used in clinics to guide treatment decisions for all patients.
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