Validating genetic markers of response to recombinant human growth hormone in children with growth hormone deficiency and Turner syndrome: the PREDICT validation study

Abstract

Objective: Single-nucleotide polymorphisms (SNPs) associated with the response to recombinant human growth hormone (r-hGH) have previously been identified in growth hormone deficiency (GHD) and Turner syndrome (TS) children in the PREDICT long-term follow-up (LTFU) study (Nbib699855). Here, we describe the PREDICT validation (VAL) study (Nbib1419249), which aimed to confirm these genetic associations.

Design and methods: Children with GHD (n = 293) or TS (n = 132) were recruited retrospectively from 29 sites in nine countries. All children had completed 1 year of r-hGH therapy. 48 SNPs previously identified as associated with first year growth response to r-hGH were genotyped. Regression analysis was used to assess the association between genotype and growth response using clinical/auxological variables as covariates. Further analysis was undertaken using random forest classification.

Results: The children were younger, and the growth response was higher in VAL study. Direct genotype analysis did not replicate what was found in the LTFU study. However, using exploratory regression models with covariates, a consistent relationship with growth response in both VAL and LTFU was shown for four genes - SOS1 and INPPL1 in GHD and ESR1 and PTPN1 in TS. The random forest analysis demonstrated that only clinical covariates were important in the prediction of growth response in mild GHD (>4 to <10 μg/L on GH stimulation test), however, in severe GHD (≤4 μg/L) several SNPs contributed (in IGF2, GRB10, FOS, IGFBP3 and GHRHR).

Conclusions: The PREDICT validation study supports, in an independent cohort, the association of four of 48 genetic markers with growth response to r-hGH treatment in both pre-pubertal GHD and TS children after controlling for clinical/auxological covariates. However, the contribution of these SNPs in a prediction model of first-year response is not sufficient for routine clinical use.

Figure 1

Comparison of demographics and growth end points between the PREDICT LTFU study and the VAL study. (A) Age distribution in GHD and TS children. (B) Growth response end point distribution after 1 year of treatment with r-hGH in GHD and TS children. Growth response end points used were, change in height (cm), change in height (SDS) and height velocity SDS.

Figure 2

Replicated genetic associations in GHD. (A) Regression of mid-parental height and growth response (change in height (cm)) in the three genotypes of rs2276048 in both the Y1 of the PREDICT LTFU and the VAL studies (numbers of patients in brackets). (B) Box and whisker plots (median ± interquartile range) of growth response (change in height SDS) by genotype of rs2888586 in both the Y1 of the PREDICT LTFU and the VAL studies (numbers of patients (genotype colour)).

Figure 3

Replicated genetic associations in TS using regression modelling. (A) Regression of distance to target height and growth response (change in height SDS) in the three genotypes of rs2038526 in both the Y1 of the PREDICT LTFU and the VAL studies (numbers of patients in brackets). (B) Box and whisker plots (median ± interquartile range) of growth response (height velocity SDS) by genotype of rs2347867 in both the Y1 of the PREDICT LTFU and the VAL studies (numbers of patients (genotype colour)).

Figure 4

Receiver-operator curve analysis of the random forest modelling of growth response to r-hGH after 1 year of treatment using basal clinical measurements. The receiver-operator curve and associated area under the curve (AUC) are shown for all growth response end points (change in height (cm), change in height SDS and height velocity SDS). A Z-score was used to compare the AUC data with the 50% level (dotted line) and used to generate a P value.

Figure 5

Random forest modelling of growth response to r-hGH after 1 year of treatment in GHD children categorised by GHD severity (severe ≤4 µg/L, mild >4 and <10 µg/L GH peak). Prediction of growth response by random forest analysis in GHD severity-stratified sub-populations. Variable importance scores used to rank variables were derived using the R package random forest. P. Height = mid-parental height SDS, Dist Target = distance to target height SDS.