Biomarkers: What Makes One Great?
With great potential to guide our health decisions, what qualities separate poor biomarkers from great ones?
So you want to design the perfect biomarker, or perhaps you’re curious whether a hot new biomarker from a top journal or biotech startup will truly be useful and stand the test of time.
This article aims to provide a framework for assessing the effectiveness of biomarkers in health, disease, or any biological metric. For technical definitions, I recommend the NIH’s BEST Resource. Here, a biomarker refers to any characteristic that serves as an indicator of a biological function, state of health, or metric reflecting a health-related process. Biomarkers can originate from blood tests (like serum glucose levels), imaging characteristics (from a brain MRI or PET scan), digital footprints (such as personal Google search histories that suggest anxiety), genetic variants (like the BRCA1 cancer risk gene), or virtually any measurable parameter.
The ultimate goal of a biomarker is to guide healthcare management, measure response to treatment, or provide an index of future risk.
An ideal biomarker maximizes benefits, clarifies how individuals and healthcare teams should proceed, is easy to measure and track, and responds to specific interventions.
In this article, we’ll first discuss the importance of context, then outline essential criteria for evaluating biomarkers, and finally touch on specific indications.
The Importance of Context
Before delving into the specifics of biomarkers, it’s crucial to clearly define the problem you’re trying to solve—a concept that applies equally to academic research and launching a startup. For biomarkers, this means determining what issue your biomarker aims to address. Will it guide treatment for Alzheimer’s disease? Will it identify the optimal diet to enhance sleep quality? A biomarker labeled as a “key health indicator” without specific context is nearly useless because it doesn’t provide actionable knowledge to the individual.
Key questions to consider include:
If I get this biomarker tested, will it inform how I should change my behavior?
Will it present me with decisions that could alter the course of my health?
If the biomarker correlates with disease risk, does an effective solution or intervention exist?
The bottom line is that context is essential when introducing a biomarker. A good example is VO2 max, which measures the maximal rate of oxygen consumption during exercise and is the gold standard for cardiorespiratory fitness. This biomarker is particularly useful for someone about to begin a new exercise program or an Olympic athlete preparing for a conditioning regimen. VO2 max is beneficial for the right person with the right resources (e.g., a coach or trainer), at the right time (before starting a fitness intervention), and with a specific goal in mind (tracking progress during a conditioning program).
Essential Criteria for Evaluating Biomarkers
Several qualitative and quantitative metrics can help define the purpose and utility of a biomarker. Here are some general features that are useful to consider:
Predictive Value: Does the biomarker predict a particular health or disease state? For example, HbA1c—the amount of glycosylated hemoglobin in your blood—is highly predictive of future microvascular damage caused by elevated blood sugar levels. It can predict conditions like diabetic neuropathy, retinopathy, and kidney disease, making it an excellent predictive biomarker.
Feasibility: Is the biomarker easy to measure? Can it be tested at home or does it require specialized equipment? Biomarkers with at-home test kits, such as the HbA1c tests now available through retailers like Walmart thanks to companies like Simple HealthKit, are highly feasible. On the other end of the spectrum, a PET/CT scan requires injection of a radioisotope and specialized imaging equipment, making it less feasible for widespread use.
Responsiveness to Intervention: Does the biomarker respond predictably to interventions? VO2 max is an interesting case; it generally increases with rigorous aerobic training. However, significantly improving VO2 max can be challenging without regular measurement and professional guidance, making it less responsive for the average person.
Actionability: Does the biomarker provide a clear course of action? Heart rate variability (HRV) is associated with recovery states but lacks specific guidelines for action based on its readings. While an individual might adopt general healthy behaviors to improve HRV, the lack of specific action steps makes it less actionable compared to other biomarkers.
Minimal Invasiveness: How invasive is the biomarker to measure? HRV scores high in this category because it can be obtained non-invasively through a wearable wrist monitor. HbA1c requires a small blood sample, which is moderately invasive. Measuring VO2 max is more involved, requiring strenuous exercise with monitoring equipment, and thus is less minimally invasive.
Explainability: Can we understand and explain how the biomarker is linked to health outcomes? HbA1c is well-understood; it reflects blood sugar control over the past 90-120 days based on the lifespan of red blood cells and the glycation process. This explainability enhances its credibility and utility. In contrast, biomarkers like procalcitonin are useful in guiding treatment for bacterial infections but lack a clear understanding of why they are effective.
These criteria are more subjective and qualitative but are intended to help individuals assess how a biomarker may be useful on a personal level. Traditional metrics like sensitivity, specificity, positive predictive value, and negative predictive value are important but are generally used at the population level.
Specific Indications for Biomarkers
Biomarkers can be developed for various purposes, and it’s important to understand their specific indications. According to the NIH BEST resource, these include:
Diagnosis: Identifying the presence of a disease or condition.
Disease/Risk Prediction: Assessing the likelihood of developing a disease in the future.
Safety: Monitoring adverse effects or toxicity.
Monitoring: Tracking the progression of a disease or the effectiveness of treatment.
Treatment Response: Evaluating how well a treatment is working.
Prognosis: Predicting the likely course or outcome of a disease.
For a biomarker to be widely adopted in clinical practice, it must meet certain criteria and be supported by robust evidence within these indications.
Conclusion
As you encounter new biomarkers, consider these essential criteria to evaluate their potential effectiveness. Understanding the predictive value and explainability of a biomarker can significantly impact its utility and credibility.
What is the best biomarker you’ve come across?