Research Update

      As noted in the previous blog, we are developing a new test that will allow us to estimate how fast a child is growing at the time of testing based on measuring by-products of the bone growth process in urine and possibly blood.  The by-products, which we refer to as “biomarkers” of bone growth, are fragments of cartilage collagen molecules (type II collagen and type X collagen) released as bones grow in proportion to the rate or velocity of growth.  Since the initial blog, we have expanded the number of samples analyzed, especially from rapidly growing young infants and we have improved the accuracy of the results.  The test is still under development, but our results so far are quite encouraging.

      To date we find that both type II and type X collagen biomarker fragments correlate well with age of normally growing children.  The new results reinforce previous ones showing that when the biomarker values are plotted against age, the graphs mimic well established growth velocity curves for infants and children with very high values in the youngest infants which drop during the first year and level off after the second or third year.  The results are similar for the type II and type X collagen fragment biomarkers, which is not surprising and actually reassuring that we are measuring products of bone growth.  We also detect levels of the type X collagen biomarker in blood (serum) from a limited number of normally growing infants and children and observe a strong correlation with age as with the urine test. 

      As soon as our testing procedures are optimized, we will begin to measure biomarker levels at the same time that we measure actual growth in a small group of children.  The goal will be to correlate biomarker levels with growth velocity determined from measuring growth over 12 months.  In other words, biomarkers will be measured in the same infants and children we actually measure.  The results from these studies should allow us develop an equation that will convert biomarker levels to growth velocity rates and vice versa.

      To simulate how this might work, we turned to a study that reported how fast Dutch children grow at different ages, which allowed us to project hypothetically how fast our study subjects should be growing at the time the urine samples were collected.  There were a number of differences in how the growth measurements were taken, data was handled and ages were represented, but it is allowed us to make crude correlations between growth velocities estimaged from the Dutch study and our biomarker results.  The results showing sizable statistical correlations between velocity and biomarker levels exceeded our expectations.  These results strongly support our contention that biomarkers will provide and quick and easy way to determine growth velocity that can be used to evaluate bone growth and monitor treatment of bone growth disorders.