October 13, 2022

    Biomarkers for Human Performance: What Are They and How Are They Utilized?

    “Biomarker” is a term that is beginning to be used more frequently in human health and performance domains, but what does it actually mean? If you look for a simple dictionary definition, you’ll probably find something like, “biomarkers assess unique physical and behavioral human characteristics through measurement and analysis.” While this definition is accurate, it doesn’t quite provide the detail necessary to understand the utility of biomarkers.

    Simply put, a biomarker can quantify unique traits or characteristics of an individual. Biomarkers can be extremely simple to measure (e.g. height, weight, BMI) or much more complex (e.g. salivary and blood markers). Additionally, biomarkers can assess characteristics that frequently change like heart rate variability (HRV), or traits that are more stable like genetics. At this point, you may still be struggling to understand what biomarkers can best be utilized to address human performance, so let’s go into some more explicit examples.

    Common Biomarkers for Performance Optimization

    As we mentioned BMI above, we will start by discussing biomarkers that quantify body composition. BMI is one of the most common biomarkers utilized by health professionals as it is extremely practical to collect: simply measure an individual’s height and weight and perform a simple calculation. The interpretation of BMI in general populations is also relatively simple as being one of the most researched biomarker guidelines is readily available. In some populations, such as athletes, BMI is often criticized because these guidelines don’t match our intuition. More advanced technologies like DEXA, BIA, and 3D-scanning can generate relevant biomarkers like body fat percentage and lean body mass (LBM). The relationship between BMI and these more precise measures of body composition is indeed less consistent in athletic populations, often due to the specificity of sporting demands. An ‘average’ BMI may be optimal for the general population, but in some sports or positions, more mass or weight can contribute to improved performance. As such a higher BMI may be optimal for these individuals. Importantly, this does not necessarily make BMI a poor metric; it may just require more population-specific norms and guidelines for interpretation.

    Conditioning, endurance, and aerobic fitness are different terms often utilized to represent overall physical capacities related to efficient energy utilization. While these qualities are often assessed with the ever-dreaded conditioning test, resting heart rate (RHR) can also be utilized as a simple biomarker to represent aerobic fitness capabilities. More specific biomarkers such as VO2Max and Lactate Threshold (LT) also exist but are rarely assessed outside of lab settings. Thanks to consumer-available wearable technology, heart rate data is collected more frequently than ever! Different ranges of RHR can represent different levels of aerobic fitness with consistent and frequent collection allowing practitioners to assess improvement or deterioration of aerobic capacity. While aerobic capacity or fitness is a relatively stable trait over the short term, heart rate derived metrics can also be utilized to identify acute anomalies. If a person’s RHR on a given day is 20 or 30 bpm higher than compared to their typical RHR, this biomarker now provides relevant information about the individual’s stress, recovery, or readiness. It’s not likely that aerobic capacity deteriorated overnight, yet stress from an upcoming test or lack of sleep from a late night may be the true culprit. There are various other biomarkers that can be extracted from heart rate data. For example, heart rate variability, or HRV is most frequently used to monitor recovery and readiness more directly.

    Other characteristics of performance that biomarkers can assess and quantify are movement qualities or capabilities. Strength qualities, for example, are often directly assessed with 1RM testing, yet biomarkers such as max isometric force and max vertical jump height can be collected more frequently and practically. An individual’s max jump height is simply the measurable result of their force production relative to their body weight, or in other words, an important movement quality called relative strength. Practitioners may be less familiar with movement-related biomarkers as the accurate measurement of movement has been quite difficult until recent years. Now that hardware such as cameras, accelerometers, and force sensors are no longer cost-prohibitive, more movement data is being measured and analyzed than ever before! Reactive Strength Index or RSI is another relatively simple group of biomarker measures that provides a ratio of jump height to jump time. With a higher ratio considered ‘better’ (jump higher in less time), this aptly named metric represents a person’s reactive strength. Balance testing data can be utilized to generate biomarkers that assess limb asymmetry and balance variability, providing useful information for practitioners treating a range of injuries from ankle sprains to concussions.

    Key Considerations for Utilizing Biomarkers

    While this article discusses a wide variety of biomarkers, many considerations should be made prior to simply selecting metrics that sound interesting and buying the technology or tools to collect them. The approach for collecting and utilizing biomarker data must be optimized based on goals and feasibility. For example, some organizations will likely have fewer resources and different goals than others. Questions may include: What information do you need to make better decisions? How do you ensure good consistency in biomarker data collection (e.g. compliance)? How does technology integrate into your overall training system?

    Future articles will discuss in more detail optimal approaches to integrating biomarkers into training environments, but we will leave you with three key considerations for optimizing the utility of biomarkers in sport and athletic optimization:

    1. Can it be feasibly (and accurately) collected consistently?
    2. Does it provide actionable information?
    3. Will your stakeholders (practitioners, individuals) actually care?

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