One of your kidneys’ major functions is keeping your blood in tip-top shape. In doing so, the kidneys help regulate acid-base balance, electrolyte concentrations, extracellular fluid volume, and blood pressure.
The kidneys maintain these features of whole-body homeostasis through filtration, reabsorption, secretion, and excretion. The consequence of these processes is the production of urine.
Urine is this end-product of metabolism. The contents of which are complex and dynamic. Thus, the concentrations of these urinary metabolites are always changing. But they don’t change randomly. They shift according to your body’s metabolic activity. This, in turn, is driven largely by your diet.
Your diet is your body’s source of fuel and nutrients. After you eat, your body begins to digest your meal and metabolize its components for energy and performing various biochemical processes.
Your body then regulates these nutrients it needs by filtering your blood in the kidneys and excreting the leftovers. For example, dietary protein is composed of 20 different kinds of amino acids, each containing nitrogen. The body metabolizes these amino acids during digestion producing nitrogen-containing ammonia as a waste product. Ammonia is toxic, and must be converted to another molecule before excretion. The end-result of this conversion (a process known as the urea cycle) is a metabolite called urea.
If you start eating more protein, your body metabolizes more amino acids and produces more urea. If you eat less, you produce less.
By measuring how much urea is present in your urine, we can determine how much protein you’ve been eating (Maroni, et al.).
All of your dietary nutrients, not just protein, are used and metabolized in different ways and for different purposes. Nearly each of these processes produces different urinary metabolites that we measure to give you a snapshot of your dietary intake.
We then quantify the amount of these metabolites with our proprietary biosensors. Each sensor contains multiple testing sites that detect different metabolites.
We have engineered these testing sites so that each metabolite interacts with one, and only one, testing site.
The test results are wirelessly transmitted to your phone, and we crunch the numbers for you instantly!
Let’s compare the accuracy to other techniques for measuring nutrient intake. First, some background.
A correlation coefficient is a number between 0 (zero correlation) and 1 (perfect correlation) used to describe how different parameters relate to each other.
In our case, we are interested in how well a measurement of protein intake correlates to true protein intake.
Popular dietary assessment methods used in epidemiological research are the 24-hour recall method and the Food Frequency Questionnaire (FFQ). A pooled analysis showed that the correlation coefficients of the FFQ for protein and protein density (% of total calories derived from protein) were 0.29 and 0.41, respectively, while the 24-hour recall method were 0.40, and 0.36, respectively (Freedman, et al.).
Weighed food records that combine detailed food logs and scales for weighing food portions consumed improves the correlation further, with average correlation coefficients around 0.7 - 0.8 (Bingham, et al.).
But testing actual, biological fluids beats them all.
A single urine test has a correlation coefficient of approximately 0.84 (Maroni, et al.).
But it gets better.
Eight days worth of urine tests improves the correlation coefficient to 0.95, while a month (28 days worth of testing) improves it further to 0.99.
Yes! Good eye!
Does it matter?
Actually, no! Here’s why.
We normalize all of our measurements. We do this by measuring another urinary metabolite called creatinine. Creatinine is a metabolic breakdown product of muscle tissue. Creatinine is excreted by the body at a relatively constant rate, depending largely on your body composition, height, weight, gender, and age.
Therefore, each measurement we take is a ratio of the metabolite that is correlated to dietary intake and creatinine.
For those of you who are really interested in understanding this more, here’s some math to show what’s going on:
Say we measured 6 mmol of urea and 3 mmol of creatinine. The urea-to-creatinine ratio is 6-to-3. When we divide 6 by 3, the result is 2.
Now, say we dilute the water three times over. Now, we only measure 2 mmol of urea and 1 mmol of creatinine. The urea-to-creatinine ratio is 2-to-1. When we divide, the ratio of 2/1 is still equal to 2.
This process is a tried-and-true method for many urinalysis tests, like urea for protein tracking (Kihara, et al.; Umesawa, et al.; Ndzengue, et al.). And in the clinical world, measuring urinary albumin-to-creatinine ratios is how doctors determine whether you have a condition known as chronic kidney disease.
We extend this same technique to all of the metabolites we test so that we can provide an accurate measurement no matter the dilution.
It can, depending on how you perform a test.
Our biosensors are engineered so that each testing spot only interacts with its specific metabolite of interest.
For example, we mentioned earlier that we quantify urea. The test for urea only interacts biochemically with urea, and nothing else. Therefore, no matter what else is in solution, the test just simply won’t give a response to other molecules.
Nevertheless, we only recommend performing a test after urination only. This can ensure nothing gets in the way and blocks (or traps) solution near the testing site and skews the results.
There is still one way, however, the tests results will become skewed. If the previous user forgot to flush. The test will not differentiate between your urine and what might have been left behind. So for accurate results, start from a clean bowl.
The focus of our first generation biosensors were on accuracy and reliability and are currently designed for one-time-use.
However, we are actively researching two areas to reduce sensor-disposal waste. The first is the development of biodegradable sensors that can easily be flushed and will dissolve safely over time.
The second area of research focuses on multi-use sensors that can be used more than once before disposal and reducing waste in the process.