In this final article in our three-part series about proteomics, we will discuss how proteomic tests can change the future of cardiovascular disease (CVD), including diagnosis, prevention and treatment.
- Read the first article for an overview of proteins and proteomics.
- Read the second article for an overview of diagnostic proteomic tests and research.
In summary, proteins in the body tell us about a patient’s current health status and their outlook for future health events. When we study a person’s proteins via a proteomic diagnostic or prognostic test, we can use the real-time findings to provide the patient with advanced precision healthcare. This is especially important when it comes to cardiovascular risk, disease and severe events since CVD is the leading cause of death in the United States and worldwide.
CVD includes a family of diseases that affect the heart and blood vessels. The primary origin of CVD is most often atherosclerotic in nature, in which fatty plaque deposits line arteries and obstruct blood circulation. There are an estimated 17.9 million CVD-based deaths globally each year. In the United States, more than 800,000 people die from CVD each year – that’s one in every three deaths – and about 160,000 of them occur in people under age 65.
Having CVD can also lead to other chronic health conditions, including but not limited to dementia, Alzheimer's, diabetes, poor COVID-19 outcomes and more. Notably, CVD is the leading cause of death and disability among people with Type 2 diabetes. 65% of people with diabetes will die from heart disease or stroke – that’s two times more likely than someone who doesn’t have Type 2 diabetes.
CVD remains the number one cause of death in the United States, yet current mechanisms to screen patients, risk-stratify and personalize treatment decisions are ineffective. Classic risk factors associated with CVD include conditions like hypertension, hyperlipidemia, diabetes and smoking, yet many individuals with CVD do not present with any of the classic risk factors. There are, therefore, limitations to using risk factors alone as prognostic tools for CVD.
SomaLogic’s SomaSignal® tests bring life-changing protein-based health information to the point of care. SomaLogic’s cardiovascular risk portfolio contains multiple tests for distinct populations available for clinical use under a laboratory-developed test designation (LDT). These tests can accurately predict the 4-year likelihood of myocardial infarction, heart failure, stroke or death based on the levels of 27 plasma proteins. They identify patients more likely to experience major acute cardiovascular events, enabling physicians to implement precision medical treatments that result in improved quality of care and fewer life-threatening events.
Let’s look at how the state of CVD care can be improved when providers are armed with insights from SomaLogic's cardiovascular risk model:
Current state of CVD care | Future state of CVD care |
---|---|
Sub-optimal use of cardioprotective (CP) medications |
Targeted and precise use of CP medications |
Poor medication adherence to existing therapies |
Improved adherence through identified urgency |
Inefficient, low throughput and high cost of existing diagnostics, post-symptom development |
Efficient and high throughput for early detection |
Limited biomarker information for the physician and patient discussions |
Holistic and patient-centric biomarker, diagnostic risk |
Tests rely on age, sex and race, which result in poor risk stratification and can often under-represent risk in communities of color |
By using individual biology and machine learning, SomaSignal tests eliminate race, sex and ethnicity bias1 |
Poor sensitivity to physiological change |
Highly sensitive to patient behavioral modifications and medication upgrade |
The cardiovascular risk model was described in a study published earlier this year in the journal Science Translational Medicine. This was one of the largest proteomics studies ever conducted. It featured 22,849 participants, nine clinical studies, 5,000 proteins and 32,130 archived plasma samples. SomaLogic’s model outperformed existing clinical models based on traditional risk factors such as cholesterol, blood pressure, diabetes and smoking. The model:
- Had roughly 2x the accuracy of existing risk scores
- Predicted cardiovascular events with 90% accuracy
- Was sensitive to the effects of lifestyle changes and various classes of drugs
Detecting CVD risk is important, but this model is impactful on an even deeper level since having CVD is commonly linked to having or developing other conditions, such as Type 2 diabetes or dementia. The SomaLogic cardiovascular risk model can identify and manage CV risk in populations with chronic conditions where CV risk is known to have an impact on survival.
Physicians can and should expand their toolbox as modern medicine, including prognostic tests like these proteomic tests come to fruition. Providers can learn more or sign up to become a SomaSignal test provider at somalogic.com/providers/.
SomaSignal tests are developed and their performance characteristics determined by SomaLogic, Inc. They have neither been cleared or approved by the US Food and Drug Administration. SomaLogic operates a Clinical Laboratory Improvement Amendments (CLIA) certified, and College of American Pathologists (CAP) accredited laboratory.
(c)2022 SomaLogic Operating Co., Inc.; SomaLogic, SomaSignal and associated logo are trademarks of SomaLogic Operating Co., Inc.
References
1. Williams SA, et al. A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk. Sci Transl Med. 2022 Apr 6;14(639):eabj9625.