medwireNews: A candidate gene approach does not identify a panel of genes that can predict the growth response to recombinant human growth hormone (rhGH) better than clinical factors alone, show the findings of the PREDICT validation study.
The validation study included 293 patients with growth hormone deficiency (GHD) and 132 with Turner syndrome. For speed, these patients were retrospectively recruited, but using the same inclusion and exclusion criteria as were used for the 182 patients who were prospectively recruited to the original PREDICT study.
Despite the consistent enrolment criteria, there were significant differences between the prospective and validation cohorts, such as a younger age and higher growth responses in the retrospective cohort, so Peter Clayton (Royal Manchester Children’s Hospital, UK) and co-researchers performed regression analysis to account for the differences.
Just four single nucleotide polymorphisms (SNPs) were associated with response to rhGH over the first year of use in both cohorts. Two, associated with growth response in GHD patients, are located in the SOS1 and INPPL1 genes, which encode proteins that modulate response to GH and insulin/insulin-like growth factor 1, respectively. And SNPs in two other genes – ESR1 and PTNP1 – predicted growth response in Turner syndrome patients. These genes encode, respectively, the oestrogen receptor α and a “protein tyrosine phosphatase central to growth factor signalling”.
A multiple decision-tree analysis replicated some of these findings, but also showed that the ability of genetic mutations to predict growth response was far outweighed by that of auxological variables.
The researchers therefore say that the impact of genes identified through candidate gene analysis “is modest and complicated by interaction with auxological variables that in themselves are related to genetic background.”
The exception was for patients with severe GHD (peak GH ≤4 μg/L), for which the analysis identified several genetic variants – including in IGF2 and IGFBP3 – that were associated with growth response even in the presence of clinical factors, “indicating that in these circumstances the impact of these genes is not co-linear with the auxological variables.”
Overall, the identified genes “could not be used in a predictive test”, the team writes in the European Journal of Endocrinology. But they emphasise that genetic variants can explain around a third of the variance in normal adult height.
“Using current technology, a [genome-wide association study] approach would be preferable and could reveal genes that hitherto have not been implicated in growth mechanisms”, say Clayton and team. “An even better approach may be the use of baseline gene expression profiling, which takes a whole genome approach and captures the combined impact of gene and environment on mRNA levels.”
By Eleanor McDermid
Eur J Endocrinol 2016; Advance online publication
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