Your Biomarkers Small & Large
When it comes to evaluating a person's health, doctors use a wide variety of tests and measurements called biomarkers. These can range from simple readings such as blood pressure to sophisticated genetic analyses. In between are dozens of tests performed on blood, urine, and other samples that can diagnose disease, measure damage, and collect information about the function of every organ in the body, from lungs and liver to bones and bowels. Biomarkers can provide a snapshot of a person's health, but their real power is seen when they track the course of change over time. By enabling individuals to follow the components of their health, biomarkers can chart the direction of wellness and provide benchmarks for personal health goals.
What are biomarkers?
Biomarkers are measures that indicate the presence or absence of disease or factors that can increase or decrease your risk of disease. You are most likely familiar with elevated blood cholesterol as a risk factor for heart disease. In the case of disease like Alzheimer's, biomarkers being studied include physical changes in the brain, such as shrinkage in specific brain regions, and certain protein levels in blood and cerebrospinal fluid. These changes, which are measured by imaging, blood, and lumbar puncture tests, may detect who is at risk for Alzheimer's disease. Biomarkers are also being studied to see how they may be used to measure disease progression or the effect of interventions.
Why are biomarkers important?
Biomarkers include the measurements of a physical exam, but most biomarkers are measurements taken at the cellular and molecular levels in an attempt to detect the presence of a wide range of substances and provide information about the function of every organ and system in the body, from lungs to liver and bones to bowels.
Our blood and other bodily fluids tell us stories about our bodies. The substances carried in these fluids reflect the lives and deaths of cells, which in turn mirror the function or failure of organs. We've known that, at least in principle, since antiquity. But measuring the levels of glucose in the blood or urine, for example, is not the same as measuring a person's pulse or the rate of respiration. While you can directly observe how fast or slow someone is breathing, you can't directly observe the cellular processes of nutrient metabolism. Instead, you can only measure the presence of a substance (in this example, glucose) that indirectly reflects how fast or slow this process is proceeding.
This might not seem like a significant difference, but in some cases it is. The goal of medical technology is to look as close as possible at the actual physiological processes of the body. Biomarkers are often only an approximation of what is happening in the body. Imagine being an archaeologist excavating an ancient campsite and finding piles of clam shells and the bones of rabbits. It would be reasonable to surmise from this evidence that the people who lived at the campsite relied on shellfish and rabbits as important components of their diet. But that's not the same as actually watching those people eat.
The same is true for many biomarkers. That doesn't mean biomarkers are not accurate; many are extremely sensitive and specific measurements. But it reminds us that the goal of medical science is to actually see cells function or fail directly; in many cases, biomarkers are (at least for now) an approximation of what is taking place, the next best thing to being there.
What does "normal" and "abnormal" really mean?
High-tech scans of the body can spot abnormalities the size of a pencil tip. That can be a good thing; we can all see the value of spotting problems when they are tiny. But such micro-detection does not always work in a patient's favor. It does, though, illustrate the problem of defining what is "normal" and what is not.
Finding out that you have an "abnormality" even though you still feel perfectly fine is not always helpful, because the fact is that we all have abnormalities that won't cause us problems. As Dr. Michael Stein of Brown University points out, when every organ, bone, and muscle is scanned, more than three-quarters of those without symptoms are discovered to have abnormalities. Among patients without any current knee pain or even a history of knee injury, for example, 40% have meniscal damage detected by MRI scans. Among adults without back pain, over 50% have bulging lumbar discs. Gallstones show up in 10% of adults with no symptoms, and 7% of adults under age 50 have had a stroke without knowing it.
The problem of determining what's normal also goes for blood tests. Normal and abnormal are statistical inventions. Test results of healthy people are basically compared to the results for people who have a particular disease or condition. If you imagine a standard bell curve, think of the ends as disease states and the middle as normal. And while age and gender are taken into account in these statistical calculations, they are still averages based on populations.
Normal is also often a moving target. Take blood glucose levels, for example. In 1965, the World Health Organization proposed the first definition of diabetes based solely on laboratory testing in 1965. But by 1979, explains Stein, the lab test this definition was based on was outdated. A new standard, a single fasting blood test (a glucose level higher than 140), was now "diabetes." In 1997, this glucose threshold was lowered to anything higher than 126, which in one stroke increased the number of diabetics in the country.
Around the same time, says Stein, new terms such as "pre-diabetes," were introduced, identifying persons whose glucose control was not quite "normal," but not quite diabetic. In 2003, this "pre-diabetes" cut-off number was lowered as well, further increasing the number of Americans worried about and monitored for sugar-related abnormalities. The development of new tests, such as hemoglobin A1C, further expanded the number of people considered to either have or be at risk for the disease. Human physiology hasn't changed in the past 50 years, but the definition of diabetes certainly has.
The power of repetition
Biomarkers can be used as snapshots to freeze a single moment in physiological time, but their real power is seen when they are used as a movie to capture the course of change over time.The critical question for patients, explains Dr. Michael Stein, of Brown University, is this: is it more useful to have your current glucose (let's say it's 98) compared to the statistical "normal" of 67-99, or would it be more clinically helpful to compare your current glucose to your glucose readings from the past 4 years (let's say it has trended upward from 68 to 78 to 88). If in year 5 it goes to 108, you "suddenly" become diabetic according to the average normal, even though it was clear you were on an unhealthy trajectory for years. Biosystems rarely fail suddenly, explains Stein; chronic deterioration is more typical. The potential of "personalized medicine" is to reveal the underlying trends, which will make it easier for individuals to understand their health and what they might do to improve it.
Source: TheVisualMD