Clinical and Molecular Genetic Analysis of Children with Severe Short Stature due to Isolated Growth Hormone Deficiency: Insights from a South Indian Cohort and Predictors of Growth Response.

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Dhivya Shanmugam, Subbiah Sridhar, Kathirvel M, Sreenivasan Palaniappan, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7689542/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Pituitary → Version 1 posted 11 You are reading this latest preprint version Abstract Purpose: Isolated growth hormone deficiency (IGHD) is one among the treatable causes of short stature. We aimed to describe the clinical, biochemical, and molecular characteristics of IGHD as well as to identify clinical predictors of mutation positivity and first-year height response to recombinant human growth hormone (rhGH). Methods: Sixty-three children with IGHD who had received minimum of one year of rhGH therapy were included. Detailed auxology, growth hormone provocative testing, pituitary MRI were performed and genetic analysis was done by using whole-exome sequencing. The mutation positivity was correlated with auxological and biochemical diagnosis of IGHD. The first-year height response was assessed as ΔHeight SDS and predictors of response were analysed using regression models. Results: The mean age at presentation was 9 years; 57% were born to consanguineous parents. Severe auxological impairment (mean height SDS − 4.29, and mean genetic height deficit − 2.42 SDS) was observed. Genetic variants were identified in 49% of the study cohort, predominantly in GHRHR (39.7%), with p.Glu72Ter being the most frequent, whereas G H1 variants were less prevalent (4.8%). Genetic-variant positive children had a younger age at onset, more severe growth failure, and a better response to rhGH treatment. Regression analysis revealed genetic-variant positive status as an independent predictor of favourable first-year growth response (ΔHeight-SDS:1.24 ± 0.50). Conclusion The South Indian IGHD cohort exhibits a distinct genetic profile, with GHRHR p.Glu72Ter being the most frequent variant, consistent with a founder effect. Severe short stature, low peak stimulated growth hormone levels, and superior first-year growth response indirectly predicted mutation positivity. Isolated growth hormone deficiency Short Stature GHRHR GH1 Combined pituitary hormone deficiency Recombinant human growth hormone (rhGH) Figures Figure 1 Figure 2 Figure 3 Introduction Growth hormone deficiency (GHD) is an important treatable cause of short stature [ 1 ]. GHD can manifest either as isolated growth hormone deficiency (IGHD) or as part of combined pituitary hormone deficiency (CPHD), with IGHD being more prevalent [ 2 ]. Mutations in the GH1 and GHRHR genes have been recognized as important genetic causes of IGHD [ 3 , 4 ]. Molecular genetic analysis plays a key role in identifying the underlying etiology and guides clinical management, long-term follow-up, and genetic counselling of affected families [ 4 ]. Recombinant human growth hormone (rhGH) remains the cornerstone of IGHD treatment and has been shown to significantly improve auxological parameters [ 5 , 6 ]. In this study, we aimed to evaluate the clinical and molecular genetic characteristics of IGHD from South India, and to analyse the clinical, biochemical, and mutation positivity predictors in relation to rhGH therapy. Materials and Methods This study was conducted in the short stature clinic of the Department of Endocrinology at a multi-speciality tertiary care hospital in South India, between 2020 and 2025. It used a combined retrospective and prospective design, involving severe short stature children and adolescents of isolated growth hormone deficiency (IGHD) and on treatment with recombinant human growth hormone (rhGH) for a minimum of one year. Children with combined pituitary hormone deficiency (CPHD), Turner syndrome, Noonan syndrome, and other syndromic short stature, skeletal dysplasia-related short stature, and chronic systemic illness were excluded (Fig. 1 : study algorithm). Ethical approval was obtained from the Institutional Ethics Committee of Madurai Medical College and Government Rajaji Hospital (Ref No. 3374/IEC/2024-02/22 dated 15.04.2024). Written informed consent was obtained from parents and assent from participants, wherever applicable. Participant confidentiality was strictly maintained throughout the study. Severe short stature was defined as height more than three standard deviations (SD) below the mean for age and sex or less than the 3rd percentile, as per the combined WHO 2006 and IAP 2015 growth chart [ 7 ]. GHD was diagnosed by growth hormone provocative tests, performed after an overnight fasting with euthyroid and eucortisolemic status. Either clonidine or glucagon was used as a provocative agent, and peak GH levels were assessed at 60 and 90minutes following clonidine and at 120 and 180minutes following glucagon. A Peak GH level < 7ng/ml was considered diagnostic of growth hormone deficiency [ 5 ]. All hormonal evaluations, including FT4, TSH, cortisol, LH, FSH, Testosterone, Estradiol, prolactin, IGF-1(age and sex-matched), and GH were performed at fasting and, using electrochemiluminescent immunoassay (ECLIA), Roche Cobas e411 analyzer. Whole exome sequencing (WES) was performed using three mL of peripheral blood. Genetic analysis primarily focused on the GH1 and GHRHR genes, which are commonly implicated in IGHD. Both coding and non-coding variants were annotated using databases such as ClinVar, OMIM, HGMD, LOVD, and DECIPHER (population CNV). Common variants were filtered based on allele frequencies from public databases, including 1000Genomes (Phase 3), gnomAD (v3.1 & 2.1.1), dbSNP (GCF_000001405.38), 1000 Japanese Genome, TOPMed (Freeze_8), Genome Asia, and our internal Indian population database (MedVarDb v3.0). Non-synonymous variants' effect is calculated using multiple algorithms such as PolyPhen-2, SIFT, MutationTaster2, and LRT. Clinically significant variants are used for interpretation and reporting. The classification of the variants is done based on the American College of Medical Genetics [ 8 ]. Parental testing was done in selected index cases to assess heterozygosity and segregation patterns. Pedigree charts were drawn to illustrate familial inheritance. All biochemically confirmed children and adolescents with severe short stature were treated with daily recombinant human growth hormone therapy (rhGH) at a dose of 0.16–0.24 mg/kg/week [ 5 , 6 ]. The dose was adjusted based on body weight, height velocity, and age- and sex-matched IGF-1 levels. Patients were followed up at 3–6 months intervals for assessment of auxological parameters, pubertal status, development of other pituitary hormone deficiencies, and for monitoring of adverse effects [ 5 , 6 , 9 ]. Bone age was assessed every 6 months to one year by the Greulich and Pyle atlas [ 10 ]. rhGH therapy was provided free of cost to children from below poverty line (BPL) families through the Chief Minister’s Comprehensive Health Insurance Scheme (CMCHIS) and/or the National Health Mission (NHM) rare disease fund of the Government of Tamil Nadu. Statistical analysis: Data were computed in SPSS v27.0 (IBM Corp.). Continuous variables were assessed for normality (Shapiro–Wilk) and summarized as mean ± SD or median (IQR); categorical variables as n (%). Group comparisons (genetic-variant-positive variant-negative) used Student’s t-test or Mann–Whitney U for continuous outcomes and Chi-square or Fisher’s exact for categorical variables. Unadjusted linear regressions were fitted for clinical predictors of first-year growth response. For mutation-status discrimination, ROC analyses were performed in R v4.3.0 using pROC (DeLong AUC with 95% CI). Youden-optimized cutoffs are reported with sensitivity and specificity. The forest plot of regression coefficients and the ROC operating-point figure were generated in R using ggplot2. All tests were two-tailed, with α = 0.05. Results Clinical and Auxological characteristics: Sixty-three children with isolated growth hormone deficiency (IGHD), who had received a minimum of one year of recombinant human growth hormone therapy (rhGH), were included in the study. Baseline clinical and auxological parameters were summarized in Table 1 . The mean age at presentation was 8.9 ± 2.95 years, with a near-equal gender distribution. Parental consanguinity was present in 57% with a mean birth weight SDS of – 0.88 ± 2.09, indicating that most children were born appropriate for gestational age. Table 1 Baseline clinical characteristics and auxological parameters of the cohort Clinical and Auxological parameters Mean ± SD (n = 63) Mean Age at presentation (years) 8.92 ± 2.95 Male: Female 35: 28 (56%: 44%) Birth Weight SDS -0.88 ± 2.09 Height SDS at presentation -4.29 ± 1.09 MPH SDS -1.87 ± 0.67 Height SDS - MPH SDS -2.42 ± 1.12 BMI SDS -3.35 ± 2.80 BA/CA ratio 0.58 ± 0.16 Peak GH (ng/mL) a 1.1 (0.56–3) IGF1 (ng/mL) a 28.8 (15.5–80.4) First-year Height gain (cm) 9.75 ± 2.77 First-year ▲ Height SDS (mean ± SD) 0.87 ± 0.58 SDS = Standard Deviation Score; MPH = Mid-Parental Height; Height SDS - MPH SDS = difference between Height SDS and MPH SDS; BA/CA = Bone Age to Chronological Age ratio (bone age delay); IGF1 = Insulin-like Growth Factor 1. First-year ▲ Height SDS = difference between 1 st year height SDS and baseline height SDS All continuous values are presented as mean ± SD or median (Q3-Q1); categorical values as n (%). a - median (Q1-Q3) The mean height SDS in the study cohort was − 4.29 ± 1.09, suggestive of severe short stature. On average, height SDS was significantly below the mid-parental height (Height SDS minus MPH SDS: 2.42 ± 1.12 SDS), indicating a marked deviation from predicted growth. Bone age was significantly delayed, with a mean BA/CA ratio of 0.58 ± 0.16. Biochemical and Pituitary Imaging: Biochemical evaluation showed low peak GH levels (median 1.1ng/mL; range 0.56–3 ng/mL) following a clonidine stimulation test and very low median IGF-1 levels (28.8 ng/mL), suggestive of severe growth hormone deficiency. In pituitary MRI, the most common finding was anterior pituitary hypoplasia (n = 46, 73%), followed by pituitary stalk interruption syndrome (PSIS) (n = 8, 13%). Nine children (14%) had normal pituitary morphology. First-year growth response to rhGH: The rhGH therapy was initiated at a mean age of 8.9 ± 3.0 years. After one year, the mean height gain noted was 9.8 ± 2.8 cm, with a corresponding mean height SDS gain of 0.87 ± 0.58. Most children showed a satisfactory initial growth response to rhGH. Molecular genetic analysis: Whole-exome sequencing identified pathogenic or likely pathogenic variants in 31 children (49%). The most frequent variant noted in the present study cohort was GHRHR (n = 25, 39.7%), followed by GH1 (n = 3, 4.8%). Two children carried ROBO1 mutations (3.2%), and a single child harbored a GLI2 mutation (1.6%). Comparison between genetic variant-positive vs genetic variant-negative IGHD: Significant differences were noted across auxological and biochemical parameters between the genetic variant-positive and genetic variant-negative groups and are summarized in Table 2 . Mutation-positive children presented at a younger age, had a higher prevalence of parental consanguinity, more severe short stature, greater deviation from mid-parental height, and more delayed bone age. Table 2. Comparison of auxological and biochemical parameters between genetic variant positive and genetic variant negative IGHD cohorts Variables Genetic variant positive (n = 31) Genetic variant negative (n = 32) p value Chronological Age (yrs) 7.84 ± 2.64 9.97 ± 2.89 0.003* Consanguinity n (%) (positive) 22.0 (71.0%) 14.0 (43.8%) 0.029* Height SDS -5.01 ± 1.02 -3.59 ± 0.60 0.001* MPH SDS a -1.78 ± 0.59 -1.97 ± 0.73 0.381 Height SDS - MPH SDS -3.05 ± 0.87 -1.81 ± 0.99 0.001* BA/CA ratio 0.51 ± 0.15 0.65 ± 0.15 0.001* Peak GH Levels (ng/ml) a 0.55 (0.1 – 0.7) 3 (1.9 – 4.5) 0.001* First-year Δ Height SDS 1.24 ± 0.50 0.50 ± 0.40 0.001* First-year height gain (cm) 11.72 ± 1.97 7.85 ± 2.01 0.001* Student t test; a- Mann whitney U test; * (p<0.05); n (%)-chisquare test; BA/CA = Bone Age to Chronological Age ratio. IGF1 = Insulin-like Growth Factor 1. All continuous values are presented as mean ± SD except peak GH levels as median (Q1-Q3); In addition, they also had markedly lower baseline IGF-1 and peak stimulated GH levels. Despite this, their first-year height gain was more than double that of the mutation-negative group. Clinical predictors of mutation-positivity based on ROC analysis: ROC analysis (Fig. 2 ) identified a peak GH ≤ 1.11 ng/mL as the most accurate predictor of mutation-positive status (AUC 0.988), with 100% sensitivity and specificity. Height SDS ≤ -4.32 (AUC 0.890) and Height SDS minus MPH SDS ≤ − 1.22 (AUC 0.913) were also strong predictors. A BA/CA ratio of ≤ 0.45 had moderate predictive value (AUC 0.765). Although IGF-1 levels were significantly lower in the genetic variant-positive group, it was difficult to define a fixed ROC cut-off due to variability in the reference range with age, gender, and pubertal stage. Predictors of first-year growth response: In unadjusted linear regression analysis (Fig. 3 ), several clinical and biochemical parameters predicted the first-year growth outcomes. Baseline height SDS was inversely associated with growth response (B₁ = − 0.378, p < 0.001), indicating that children with more severe short stature at presentation achieved greater height gain. Larger deviation from mid-parental height SDS (Height SDS − MPH SDS) also predicted better response (B₁ = − 0.335, p < 0.001); for every 1-SDS height deficit from mid-parental height, the first-year height SDS increased by 0.335. Lower peak stimulated GH levels (B₁ = − 0.146 per 1 ng/mL, p < 0.001) and younger age at initiation of rhGH therapy (B₁ = − 0.080 per year, p < 0.001) were associated with greater height gains. Mutation-positive status was associated with a 0.736 SDS greater first-year gain compared with mutation-negative peers (p < 0.001). In contrast, mid-parental height SDS (B₁ = − 0.065, p = 0.560) and bone age/chronological age ratio (B₁ = 0.020, p = 0.896) were not significant predictors of response. rhGH therapy response in relation to genetic-variants: The identified genetic variants showed variable response to rhGH therapy (Table 3 ). The most frequent variant, GHRHR p.Glu72Ter (E72X) (n = 17, 27.0%), was associated with a mean first-year height velocity of 11.87 cm and height SDS gain of 1.30 ± 0.40, indicating a better response. The GHRHR p.Gly71Cys variant (n = 4, 6.3%) showed a comparable growth outcome (12.31 ± 1.16 cm; ΔHeight SDS 1.32 ± 0.35). Rare GHRHR missense variants (p.Arg161Trp, p.Gly298Arg; n = 1 each) also showed favourable responses, with height SDS gains of 1.28 and 1.60, respectively. Among the observed GHRHR mutations, structural variants such as partial exon 5–13 deletion and a homozygous 8.13 kb deletion on chromosome 7 (each seen in a single case) were associated with excellent growth outcomes (ΔHeight SDS 2.23 and 1.69, respectively). Table 3. Summary of identified genetic variants and first‑year growth response Gene Protein Change Classification n (%) First-year height velocity (cm) First‑year ΔHeight SDS GHRHR n=25 (39.7%) p.Glu72Ter Pathogenic 17 (27.0) 11.87 ± 1.71 1.30 ± 0.40 p.Gly71Cys Likely pathogenic 4 (6.3) 12.31 ± 1.16 1.32 ± 0.35 Partial Exon 5–13 deletion Likely pathogenic 1 (1.6) 16.00 2.23 homozygous deletion of 8.13KB on chr7 (30969965_30979244?) Likely pathogenic 1 (1.6) 14.00 1.69 p.Arg161Trp Likely pathogenic 1 (1.6) 11.50 1.28 p.Gly298Arg Uncertain significance 1 (1.6) 14.00 1.60 GH1 n=3 (4.8%) p.Gln66Ter Likely pathogenic 1 (1.6) 10.00 1.13 GH gene deletion a Pathogenic 2 (3.2) 9.75 ± 1.06 0.57 ± 1.05 ROBO1 n=2 (3.2%) p.Lys625Arg Uncertain significance 1 (1.6) 9.50 0.83 p.Thr314Ser Uncertain significance 1 (1.6) 8.00 0.44 GLI2 n=1 (1.6) p.Arg231Gln Uncertain significance 1 (1.6) 9.75 0.75 First‑year height velocity = absolute height gain in cm over the first year of GH therapy; ΔHeight SDS = change in height SDS over the same period. Continuous values are mean ± SD; a -Two distinct GH1 gene‐deletion (∼1.467 kb and ∼1.470 kb), both classified as pathogenic or likely pathogenic. In contrast to GHRHR , the variants in the GH1 gene showed variable outcomes. The heterozygous p.Gln66Ter variant (n = 1;1.6%) showed a favourable response (ΔHeight SDS;1.13), whereas homozygous GH1 deletions (n = 2, 3.2%, representing two distinct ∼1.467 kb and ∼1.470 kb deletions) were associated with modest outcomes (ΔHeight 0.57 ± 0.5). Variants of uncertain significance in GLI2 (p.Arg231Gln, n = 1) and ROBO1 (p.Lys625Arg and p.Thr314Ser, n = 2) were associated with lower responses compared with GHRHR , with height velocities ranging from 8.00 to 9.75 cm and ΔHeight SDS between 0.44 and 0.83. Discussion Growth hormone deficiency (GHD) is one among the treatable causes of short stature, with an estimated global incidence of 1 in 4000 to 1 in 10,000 live births [ 4 , 9 ]. Genetic factors play a significant role in the etiology of IGHD, with identifiable mutations accounting for approximately 30% of cases globally [ 11 ]. The most commonly implicated genes are GH1 and GHRHR [ 11 , 12 ]. To the best of our knowledge, the present study is the first from South India and the fifth largest from the Indian subcontinent among the IGHD cohort to describe the molecular genetic profile [ 12 – 15 ]. All the children in the present cohort had severe short stature, highlighting the severity of IGHD at presentation. Gender distribution was nearly equal, and mean age at presentation was nine years, similar to previously reported Indian cohorts [ 13 , 14 ], suggesting that delay in recognition and referral is not uncommon in India. Parental consanguinity was observed in 57% of the present cohort, higher than reported in other Indian cohorts (25.3%) [ 14 , 15 ]. This likely reflects regional sociocultural marriage practices and may contribute to the higher prevalence of autosomal-recessive subtypes of IGHD [ 16 ] observed in the present cohort. The auxological findings showed severe growth failure, with a mean baseline height SDS below − 4 and an average deficit of more than 2 SDS from mid-parental height. This wider height deficit from the expected genetic height potential was more pronounced than in other reported Indian cohorts, emphasizing the severity of disease burden at presentation [ 13 , 14 , 15 ]. Bone age was also markedly delayed relative to chronological age, indicating substantial residual growth potential and supporting its role as an important clinical predictor of favourable response to growth-promoting agents [ 6 ]. All the children in the study cohort showed severe GH deficiency, with very low stimulated peak GH levels and low IGF-1 levels. Although low IGF-1 supports the diagnosis of GHD, its interpretation is limited by wide variability with age, sex, and pubertal status, making absolute thresholds less reliable for use across a broad paediatric population [ 17 ]. MRI revealed anterior pituitary hypoplasia as the most common abnormality, a feature consistent with severe IGHD. PSIS was also observed in a subset of patients (13%), indicating that structural anomalies may also underlie isolated forms of GHD [ 18 ] Several genetic subtypes of IGHD have been described in the literature [ 19 ]. Type IA (homozygous GH1 gene deletions) and IB ( GHRHR mutation, occasionally GH1 ) are autosomal recessive forms, whereas Type II follows an autosomal dominant inheritance pattern and is typically caused by splice-site or missense mutations in the GH1 . Type III, which is X-linked, involves the BTK gene (Bruton’s Tyrosine Kinase) [ 4 , 16 , 19 ]. Recently, GHRHR mutations have been referred to as Type IV IGHD by a few authors [ 20 ], and have been increasingly reported from South Asia and Brazil [ 15 , 21 , 22 ] In the present study, molecular genetic analysis identified a higher mutation positivity rate (49%), exceeding the commonly reported global rates (20–40%) [ 4 , 23 ] and consistent with a western Indian cohort (45.5%) [ 15 ]. This relatively high yield is likely due to the severe nature of IGHD (severe short stature and low stimulated peak GH levels), the high rate of parental consanguinity (57%), and the exclusion of syndromic as well as CPHD children. The majority of variants clustered in GHRHR (39.7%), with recurrent nonsense and structural mutations; notably, the p.Glu72Ter (E72X) variant was the most prevalent (27%). The recurrence of the E72X variant across South Asian populations, as reported in multiple studies [ 12 , 15 , 21 ], raises the possibility of a founder mutation. Founder mutations are pathogenic alleles that arise from a single ancestor and become enriched in a population through genetic drift and consanguinity. In addition to South Asia, where the p.Glu72Ter GHRHR variant has been identified as a founder mutation [ 15 , 20 , 21 ], a similar phenomenon has also been described in Northeastern Brazil, where the c.57 + 1G > A splice-site mutation represents a distinct founder mutation [ 16 , 22 ]. Although our findings strongly suggest a shared ancestral allele, confirmation will require formal haplotype analysis. Other GHRHR variants in our series, including p.Gly71Cys, p.Arg161Trp, p.Gly298Arg, and structural deletions, also presented with a classical IGHD phenotype. In contrast to the higher prevalence of GHRHR mutations in South Asia and Brazil (supplement 1), studies from Europe and North America have consistently reported GH1 mutations as the most frequent cause of IGHD, particularly large gene deletions in Type IA and splice-site mutations in Type II [ 11 , 23 ]. Similar to other reported South Asian studies [ 12 – 15 ], we also observed a reversal of the global pattern, with GH1 variants being less frequent (4.8%). The identified GH1 variants in this cohort were a heterozygous nonsense variant (p.Gln66Ter) and homozygous gene deletions detected using WES-based copy number variations (CNV) algorithms. In addition to these classical IGHD genes, we also identified variants of uncertain significance (VUS) in GLI2 and ROBO1 [4.8%], both of which are implicated in pituitary development and have been previously reported in the PSIS genetics [ 24 , 25 ]. MRI pituitary of three children with these VUS showed PSIS morphology, suggesting an overlapping phenotype rather than classic IGHD [ 25 ]. These children require close follow-up for evolving additional pituitary hormone deficiencies. Despite rare GHRHR variants such as p.Gly298Arg classified as VUS under ACMG criteria, their consistent correlation with severe biochemical GHD and excellent growth response suggests likely pathogenicity. Future segregation and functional studies may enable the reclassification of all these VUS and contribute to the global genetics database. The ROC analysis demonstrates that children with very low stimulated peak GH levels and marked genetic height deficits were most likely to harbour mutations. In particular, peak GH ≤ 1.11 ng/mL was perfectly discriminative, supporting its utility as a practical clinical marker of genetic IGHD as well as favourable treatment response. A large genetic height deficit also strongly predicted mutation positivity, whereas the BA/CA ratio offered only modest discrimination. The above-reported clinical and biochemical parameters may help predict mutation positivity without doing genetic analysis in children with severe short stature in resource-limited settings. However, larger validation studies are needed to substantiate this finding. Growth hormone therapy is FDA-approved for several etiologies of short stature, including certain syndromes [ 26 ]. However, growth outcomes in IGHD are heterogeneous, with both auxological and genetic factors influencing the response [ 27 , 28 ]. To the best of our knowledge, this is the largest South Indian IGHD cohort with detailed genetic characterization and first-year treatment-response analysis using multivariable regression. The first-year response to rhGH therapy in the present cohort was favourable, with a mean first-year ΔHeight SDS of 0.87 ± 0.58, comparable to other Indian and international series [ 28 – 30 ] Using univariate and multivariate regression analysis, the present study identified several independent predictors of favourable first-year ΔHeight SDS. Lower baseline height SDS, greater deviation from mid-parental height, lower peak stimulated GH levels, delayed bone age and younger age at initiation of rhGH therapy were all associated with greater gains, mirroring the classical determinants reported in the KIGS multinational registry (Ranke 1999), the ANSWER registry (Lee 2011), subsequent KIGS model validations (Maghnie 2022) [ 6 , 27 , 29 ], and Indian cohorts (Bajpai 2006; Khadilkar 2017; Gahlot 2019) [ 30 – 32 ] Notably, genetic-variant positive status emerged as a novel independent predictor, conferring an additional 0.7 SDS height gain in the first year compared with variant-negative peers. This additional phenotype-genotype correlation, compared with previous descriptive Indian studies [ 33 ], provided multivariable confirmation of the prognostic value of the genetic etiology. The major strength of this study is its comprehensive design. We integrated detailed auxology, including pedigree analysis, biochemistry, and pituitary imaging, with molecular testing and systematic first-year growth-response assessment using multivariable regression. This approach allowed clear genotype-phenotype correlations and the definition of ROC cut-offs for predicting mutation positivity. Since the cohort is drawn from a South-Indian population with high consanguinity, these findings are directly relevant for settings where recessive forms of IGHD are common. This study has a few limitations. Segregation analysis was not performed in all families, which limits confirmation of inheritance patterns and re-classification of some variants of uncertain significance. The sample was from a single tertiary care centre, so referral bias cannot be excluded, and the findings may not fully represent the entire region. The follow-up period was limited to the first year of growth hormone therapy; hence, long-term outcomes remain to be evaluated. To conclude, this South-Indian cohort demonstrates that genetic IGHD represents a distinct subgroup characterized by an earlier onset, more severe auxological and biochemical phenotypes, and a favorable response to rhGH therapy. Genetic diagnosis has implications not only for confirming etiology but also for prognostication, long-term management, and family counselling [ 33 ]. In consanguineous populations, the identification of founder GHRHR mutations opens up opportunities for targeted genetic testing and reproductive counselling [ 15 , 22 ]. Declarations Acknowledgements: National Health Mission, Department of Health and Family Welfare, Government of Tamil Nadu and Chief Minister’s Comprehensive Health Insurance Scheme (CMCHIS) for providing growth hormone free of cost. Author contributions: D.S. was involved in the collection of data and preparation of the manuscript for submission. S.S. was involved in the concept, design, and final approval of the manuscript. K.M. was involved in the interpretation of genetic data and reviewed the manuscript. P.S. was involved in clinical evaluation, management, and data collection. K.N. was involved in the revision of the manuscript. R.C. was involved in the statistical analysis and interpretation of statistical results. J.S. was involved in supervising the workup. Funding: None. Data availability: The datasets generated and analyzed during the current study are not publicly available due to ethical restrictions, but are available from the corresponding author on reasonable request. Disclosure summary: There are no relevant financial or non-financial interests to disclose . Competing interests: The authors declare that they have no competing interests. Consent to participate: Written informed consent was obtained from the parents/ guardians of all children included in this study. Ethical approval : The study was performed in line with the principles of the Declaration of Helsinki, and has been approved by the Institutional Ethics Committee of Madurai Medical College and Government Rajaji Hospital (Ref No. 3374/IEC/2024-02/22 dated 15.04.2024). Supporting grants or fellowships: None References Vyas V, Kumar A, Jain V et al (2017) Growth Hormone Deficiency in Children: From Suspecting to Diagnosing. Indian Pediatr 54(11):955–960 Alatzoglou KS, Dattani MT (2010) Genetic causes and treatment of isolated growth hormone deficiency-an update. Nat Rev Endocrinol 6(10):562–576 Argente J, Tatton-Brown K, Lehwalder D, Pfäffle R (2019) Genetics of Growth Disorders-Which Patients Require Genetic Testing? Front Endocrinol (Lausanne) 10:602 Mullis PE (2010) Genetics of isolated growth hormone deficiency. 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Supplementary Files Supplement1.docx Cite Share Download PDF Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Pituitary → Version 1 posted Editorial decision: Revision requested 20 Oct, 2025 Reviews received at journal 19 Oct, 2025 Reviews received at journal 16 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviews received at journal 05 Oct, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers agreed at journal 28 Sep, 2025 Reviewers invited by journal 28 Sep, 2025 Editor assigned by journal 24 Sep, 2025 Submission checks completed at journal 24 Sep, 2025 First submitted to journal 23 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":137171,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy algorithm\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7689542/v1/19aa27632becc73f1461a835.png"},{"id":93249009,"identity":"1ea6d369-bc50-457d-a0b1-d56e9cddd18c","added_by":"auto","created_at":"2025-10-10 15:36:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":233750,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver Operator Characteristic Curve;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eROC analysis of clinical predictors of mutation positivity.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7689542/v1/cde689779bdc957694d91651.png"},{"id":93249013,"identity":"eebd6f72-57d1-4e8e-a2f1-d5693b58ff35","added_by":"auto","created_at":"2025-10-10 15:36:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182175,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot of unadjusted (B) linear regression coefficients predicting first‑year Δ height SDS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlack circles denote point estimates (B); horizontal gray lines denote 95% confidence intervals. The vertical dashed line at 0 indicates no effect. Predictors are ordered by effect magnitude\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7689542/v1/cde640115bb672c5a7c356b1.png"},{"id":99172425,"identity":"a426e4e9-e667-4632-af6b-5f831a0dca9e","added_by":"auto","created_at":"2025-12-29 16:09:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1742962,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7689542/v1/2f36c8d5-5ef6-4768-958d-922804a31af9.pdf"},{"id":93251798,"identity":"11530be8-158a-4f25-ae4d-1b27c4f2b45a","added_by":"auto","created_at":"2025-10-10 15:52:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19372,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7689542/v1/abc5e0f592a3f257826e5d3a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical and Molecular Genetic Analysis of Children with Severe Short Stature due to Isolated Growth Hormone Deficiency: Insights from a South Indian Cohort and Predictors of Growth Response.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGrowth hormone deficiency (GHD) is an important treatable cause of short stature [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. GHD can manifest either as isolated growth hormone deficiency (IGHD) or as part of combined pituitary hormone deficiency (CPHD), with IGHD being more prevalent [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Mutations in the \u003cem\u003eGH1\u003c/em\u003e and \u003cem\u003eGHRHR\u003c/em\u003e genes have been recognized as important genetic causes of IGHD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Molecular genetic analysis plays a key role in identifying the underlying etiology and guides clinical management, long-term follow-up, and genetic counselling of affected families [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecombinant human growth hormone (rhGH) remains the cornerstone of IGHD treatment and has been shown to significantly improve auxological parameters [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In this study, we aimed to evaluate the clinical and molecular genetic characteristics of IGHD from South India, and to analyse the clinical, biochemical, and mutation positivity predictors in relation to rhGH therapy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e This study was conducted in the short stature clinic of the Department of Endocrinology at a multi-speciality tertiary care hospital in South India, between 2020 and 2025. It used a combined retrospective and prospective design, involving severe short stature children and adolescents of isolated growth hormone deficiency (IGHD) and on treatment with recombinant human growth hormone (rhGH) for a minimum of one year. Children with combined pituitary hormone deficiency (CPHD), Turner syndrome, Noonan syndrome, and other syndromic short stature, skeletal dysplasia-related short stature, and chronic systemic illness were excluded (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: study algorithm). Ethical approval was obtained from the Institutional Ethics Committee of Madurai Medical College and Government Rajaji Hospital (Ref No. 3374/IEC/2024-02/22 dated 15.04.2024). Written informed consent was obtained from parents and assent from participants, wherever applicable. Participant confidentiality was strictly maintained throughout the study.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSevere short stature was defined as height more than three standard deviations (SD) below the mean for age and sex or less than the 3rd percentile, as per the combined WHO 2006 and IAP 2015 growth chart [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. GHD was diagnosed by growth hormone provocative tests, performed after an overnight fasting with euthyroid and eucortisolemic status. Either clonidine or glucagon was used as a provocative agent, and peak GH levels were assessed at 60 and 90minutes following clonidine and at 120 and 180minutes following glucagon. A Peak GH level\u0026thinsp;\u0026lt;\u0026thinsp;7ng/ml was considered diagnostic of growth hormone deficiency [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. All hormonal evaluations, including FT4, TSH, cortisol, LH, FSH, Testosterone, Estradiol, prolactin, IGF-1(age and sex-matched), and GH were performed at fasting and, using electrochemiluminescent immunoassay (ECLIA), Roche Cobas e411 analyzer.\u003c/p\u003e\u003cp\u003eWhole exome sequencing (WES) was performed using three mL of peripheral blood. Genetic analysis primarily focused on the \u003cem\u003eGH1\u003c/em\u003e and \u003cem\u003eGHRHR\u003c/em\u003e genes, which are commonly implicated in IGHD. Both coding and non-coding variants were annotated using databases such as ClinVar, OMIM, HGMD, LOVD, and DECIPHER (population CNV). Common variants were filtered based on allele frequencies from public databases, including 1000Genomes (Phase 3), gnomAD (v3.1 \u0026amp; 2.1.1), dbSNP (GCF_000001405.38), 1000 Japanese Genome, TOPMed (Freeze_8), Genome Asia, and our internal Indian population database (MedVarDb v3.0). Non-synonymous variants' effect is calculated using multiple algorithms such as PolyPhen-2, SIFT, MutationTaster2, and LRT. Clinically significant variants are used for interpretation and reporting. The classification of the variants is done based on the American College of Medical Genetics [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Parental testing was done in selected index cases to assess heterozygosity and segregation patterns. Pedigree charts were drawn to illustrate familial inheritance.\u003c/p\u003e\u003cp\u003eAll biochemically confirmed children and adolescents with severe short stature were treated with daily recombinant human growth hormone therapy (rhGH) at a dose of 0.16\u0026ndash;0.24 mg/kg/week [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The dose was adjusted based on body weight, height velocity, and age- and sex-matched IGF-1 levels. Patients were followed up at 3\u0026ndash;6 months intervals for assessment of auxological parameters, pubertal status, development of other pituitary hormone deficiencies, and for monitoring of adverse effects [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Bone age was assessed every 6 months to one year by the Greulich and Pyle atlas [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. rhGH therapy was provided free of cost to children from below poverty line (BPL) families through the Chief Minister\u0026rsquo;s Comprehensive Health Insurance Scheme (CMCHIS) and/or the National Health Mission (NHM) rare disease fund of the Government of Tamil Nadu.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis:\u003c/h2\u003e\u003cp\u003eData were computed in SPSS v27.0 (IBM Corp.). Continuous variables were assessed for normality (Shapiro\u0026ndash;Wilk) and summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (IQR); categorical variables as n (%). Group comparisons (genetic-variant-positive variant-negative) used Student\u0026rsquo;s t-test or Mann\u0026ndash;Whitney U for continuous outcomes and Chi-square or Fisher\u0026rsquo;s exact for categorical variables.\u003c/p\u003e\u003cp\u003eUnadjusted linear regressions were fitted for clinical predictors of first-year growth response. For mutation-status discrimination, ROC analyses were performed in R v4.3.0 using pROC (DeLong AUC with 95% CI). Youden-optimized cutoffs are reported with sensitivity and specificity. The forest plot of regression coefficients and the ROC operating-point figure were generated in R using ggplot2. All tests were two-tailed, with α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eClinical and Auxological characteristics:\u003c/h2\u003e\n \u003cp\u003eSixty-three children with isolated growth hormone deficiency (IGHD), who had received a minimum of one year of recombinant human growth hormone therapy (rhGH), were included in the study. Baseline clinical and auxological parameters were summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age at presentation was 8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95 years, with a near-equal gender distribution. Parental consanguinity was present in 57% with a mean birth weight SDS of \u0026ndash; 0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09, indicating that most children were born appropriate for gestational age.\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline clinical characteristics and auxological parameters of the cohort\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClinical and Auxological parameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Age at presentation (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale: Female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35: 28 (56%: 44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth Weight SDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight SDS at presentation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPH SDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight SDS - MPH SDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI SDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBA/CA ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak GH (ng/mL)\u003c/strong\u003e \u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1 (0.56\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIGF1 (ng/mL)\u003c/strong\u003e \u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.8 (15.5\u0026ndash;80.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst-year Height gain (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst-year ▲ Height SDS (mean\u003c/strong\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eSDS = Standard Deviation Score; MPH = Mid-Parental Height;\u003c/p\u003e\n \u003cp\u003eHeight SDS - MPH SDS = difference between Height SDS and MPH SDS;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eBA/CA = Bone Age to Chronological Age ratio (bone age delay);\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIGF1 = Insulin-like Growth Factor 1.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFirst-year ▲ Height SDS = difference between 1\u003csup\u003est\u003c/sup\u003e year height SDS and baseline height SDS\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAll continuous values are presented as mean \u0026plusmn; SD or median (Q3-Q1); categorical values as n (%).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e- median\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Q1-Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe mean height SDS in the study cohort was \u0026minus;\u0026thinsp;4.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09, suggestive of severe short stature. On average, height SDS was significantly below the mid-parental height (Height SDS minus MPH SDS: 2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 SDS), indicating a marked deviation from predicted growth. Bone age was significantly delayed, with a mean BA/CA ratio of 0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eBiochemical and Pituitary Imaging:\u003c/h3\u003e\n\u003cp\u003eBiochemical evaluation showed low peak GH levels (median 1.1ng/mL; range 0.56\u0026ndash;3 ng/mL) following a clonidine stimulation test and very low median IGF-1 levels (28.8 ng/mL), suggestive of severe growth hormone deficiency. In pituitary MRI, the most common finding was anterior pituitary hypoplasia (n\u0026thinsp;=\u0026thinsp;46, 73%), followed by pituitary stalk interruption syndrome (PSIS) (n\u0026thinsp;=\u0026thinsp;8, 13%). Nine children (14%) had normal pituitary morphology.\u003c/p\u003e\n\u003ch3\u003eFirst-year growth response to rhGH:\u003c/h3\u003e\n\u003cp\u003eThe rhGH therapy was initiated at a mean age of 8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0 years. After one year, the mean height gain noted was 9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 cm, with a corresponding mean height SDS gain of 0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58. Most children showed a satisfactory initial growth response to rhGH.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eMolecular genetic analysis:\u003c/h2\u003e\n \u003cp\u003eWhole-exome sequencing identified pathogenic or likely pathogenic variants in 31 children (49%). The most frequent variant noted in the present study cohort was \u003cem\u003eGHRHR\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;25, 39.7%), followed by \u003cem\u003eGH1\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;3, 4.8%). Two children carried \u003cem\u003eROBO1\u003c/em\u003e mutations (3.2%), and a single child harbored a \u003cem\u003eGLI2\u003c/em\u003e mutation (1.6%).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eComparison between genetic variant-positive vs genetic variant-negative IGHD:\u003c/h3\u003e\n\u003cp\u003eSignificant differences were noted across auxological and biochemical parameters between the genetic variant-positive and genetic variant-negative groups and are summarized in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Mutation-positive children presented at a younger age, had a higher prevalence of parental consanguinity, more severe short stature, greater deviation from mid-parental height, and more delayed bone age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Comparison of auxological and biochemical parameters between genetic variant positive and genetic variant negative IGHD cohorts\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"670\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenetic variant positive\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenetic variant negative\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 32)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronological Age (yrs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e7.84 \u0026plusmn; 2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e9.97 \u0026plusmn; 2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsanguinity n (%) (positive)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e22.0 (71.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e14.0 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.029*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight SDS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-5.01 \u0026plusmn; 1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e-3.59 \u0026plusmn; 0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMPH SDS\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-1.78 \u0026plusmn; 0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e-1.97 \u0026plusmn; 0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight SDS - MPH SDS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-3.05 \u0026plusmn; 0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e-1.81 \u0026plusmn; 0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBA/CA ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.51 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.65 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak GH Levels (ng/ml) \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.55 (0.1 \u0026ndash; 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e3 (1.9 \u0026ndash; 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst-year \u0026Delta; Height SDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.24 \u0026plusmn; 0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.50 \u0026plusmn; 0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst-year height gain (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e11.72 \u0026plusmn; 1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e7.85 \u0026plusmn; 2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eStudent t test;\u003cstrong\u003e\u003csup\u003e\u0026nbsp;a-\u003c/sup\u003e\u003c/strong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eMann whitney U test;\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e(p\u0026lt;0.05); n (%)-chisquare test;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBA/CA = Bone Age to Chronological Age ratio. IGF1 = Insulin-like Growth Factor 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll continuous values are presented as mean \u0026plusmn; SD except peak GH levels as median (Q1-Q3);\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, they also had markedly lower baseline IGF-1 and peak stimulated GH levels. Despite this, their first-year height gain was more than double that of the mutation-negative group.\u003c/p\u003e\n\u003ch3\u003eClinical predictors of mutation-positivity based on ROC analysis:\u003c/h3\u003e\n\u003cp\u003eROC analysis (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) identified a peak GH\u0026thinsp;\u0026le;\u0026thinsp;1.11 ng/mL as the most accurate predictor of mutation-positive status (AUC 0.988), with 100% sensitivity and specificity. Height SDS \u0026le; -4.32 (AUC 0.890) and Height SDS minus MPH SDS \u0026le; \u0026minus;\u0026thinsp;1.22 (AUC 0.913) were also strong predictors. A BA/CA ratio of \u0026le;\u0026thinsp;0.45 had moderate predictive value (AUC 0.765). Although IGF-1 levels were significantly lower in the genetic variant-positive group, it was difficult to define a fixed ROC cut-off due to variability in the reference range with age, gender, and pubertal stage.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003ePredictors of first-year growth response:\u003c/h2\u003e\n \u003cp\u003eIn unadjusted linear regression analysis (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), several clinical and biochemical parameters predicted the first-year growth outcomes. Baseline height SDS was inversely associated with growth response (B₁ = \u0026minus;\u0026thinsp;0.378, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that children with more severe short stature at presentation achieved greater height gain. Larger deviation from mid-parental height SDS (Height SDS\u0026thinsp;\u0026minus;\u0026thinsp;MPH SDS) also predicted better response (B₁ = \u0026minus;\u0026thinsp;0.335, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); for every 1-SDS height deficit from mid-parental height, the first-year height SDS increased by 0.335.\u003c/p\u003e\n \u003cp\u003eLower peak stimulated GH levels (B₁ = \u0026minus;\u0026thinsp;0.146 per 1 ng/mL, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and younger age at initiation of rhGH therapy (B₁ = \u0026minus;\u0026thinsp;0.080 per year, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were associated with greater height gains. Mutation-positive status was associated with a 0.736 SDS greater first-year gain compared with mutation-negative peers (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, mid-parental height SDS (B₁ = \u0026minus;\u0026thinsp;0.065, p\u0026thinsp;=\u0026thinsp;0.560) and bone age/chronological age ratio (B₁ = 0.020, p\u0026thinsp;=\u0026thinsp;0.896) were not significant predictors of response.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003erhGH therapy response in relation to genetic-variants:\u003c/h2\u003e\n \u003cp\u003eThe identified genetic variants showed variable response to rhGH therapy (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The most frequent variant, \u003cem\u003eGHRHR\u003c/em\u003e p.Glu72Ter (E72X) (n\u0026thinsp;=\u0026thinsp;17, 27.0%), was associated with a mean first-year height velocity of 11.87 cm and height SDS gain of 1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40, indicating a better response. The \u003cem\u003eGHRHR\u003c/em\u003e p.Gly71Cys variant (n\u0026thinsp;=\u0026thinsp;4, 6.3%) showed a comparable growth outcome (12.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16 cm; \u0026Delta;Height SDS 1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35). Rare \u003cem\u003eGHRHR\u003c/em\u003e missense variants (p.Arg161Trp, p.Gly298Arg; n\u0026thinsp;=\u0026thinsp;1 each) also showed favourable responses, with height SDS gains of 1.28 and 1.60, respectively. Among the observed \u003cem\u003eGHRHR\u003c/em\u003e mutations, structural variants such as partial exon 5\u0026ndash;13 deletion and a homozygous 8.13 kb deletion on chromosome 7 (each seen in a single case) were associated with excellent growth outcomes (\u0026Delta;Height SDS 2.23 and 1.69, respectively).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. Summary of identified genetic variants and first‑year growth response\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"726\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClassification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst-year height velocity (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst‑year \u0026Delta;Height SDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGHRHR\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=25\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(39.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Glu72Ter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePathogenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.87 \u0026plusmn; 1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.30 \u0026plusmn; 0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Gly71Cys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLikely pathogenic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.31 \u0026plusmn; 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.32 \u0026plusmn; 0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePartial Exon 5\u0026ndash;13 deletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLikely pathogenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ehomozygous deletion of 8.13KB on chr7 (30969965_30979244?)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLikely pathogenic\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Arg161Trp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLikely pathogenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Gly298Arg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUncertain significance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGH1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(4.8%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Gln66Ter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLikely pathogenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGH gene deletion\u003cstrong\u003e\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePathogenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.75 \u0026plusmn; 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.57 \u0026plusmn; 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eROBO1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(3.2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Lys625Arg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUncertain significance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep.Thr314Ser\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUncertain significance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGLI2\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.6)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ep.Arg231Gln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eUncertain significance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eFirst‑year height velocity = absolute height gain in cm over the first year of GH therapy; \u0026Delta;Height SDS = change in height SDS over the same period. Continuous values are mean \u0026plusmn; SD;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e-Two distinct GH1 gene‐deletion (\u0026sim;1.467 kb and \u0026sim;1.470 kb), both classified as pathogenic or likely pathogenic.\u003c/p\u003e\n \u003cp\u003eIn contrast to \u003cem\u003eGHRHR\u003c/em\u003e, the variants in the GH1 gene showed variable outcomes. The heterozygous p.Gln66Ter variant (n\u0026thinsp;=\u0026thinsp;1;1.6%) showed a favourable response (\u0026Delta;Height SDS;1.13), whereas homozygous \u003cem\u003eGH1\u003c/em\u003e deletions (n\u0026thinsp;=\u0026thinsp;2, 3.2%, representing two distinct \u0026sim;1.467 kb and \u0026sim;1.470 kb deletions) were associated with modest outcomes (\u0026Delta;Height 0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5). Variants of uncertain significance in \u003cem\u003eGLI2\u003c/em\u003e (p.Arg231Gln, n\u0026thinsp;=\u0026thinsp;1) and \u003cem\u003eROBO1\u003c/em\u003e (p.Lys625Arg and p.Thr314Ser, n\u0026thinsp;=\u0026thinsp;2) were associated with lower responses compared with \u003cem\u003eGHRHR\u003c/em\u003e, with height velocities ranging from 8.00 to 9.75 cm and \u0026Delta;Height SDS between 0.44 and 0.83.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGrowth hormone deficiency (GHD) is one among the treatable causes of short stature, with an estimated global incidence of 1 in 4000 to 1 in 10,000 live births [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Genetic factors play a significant role in the etiology of IGHD, with identifiable mutations accounting for approximately 30% of cases globally [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The most commonly implicated genes are \u003cem\u003eGH1\u003c/em\u003e and \u003cem\u003eGHRHR\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. To the best of our knowledge, the present study is the first from South India and the fifth largest from the Indian subcontinent among the IGHD cohort to describe the molecular genetic profile [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAll the children in the present cohort had severe short stature, highlighting the severity of IGHD at presentation. Gender distribution was nearly equal, and mean age at presentation was nine years, similar to previously reported Indian cohorts [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], suggesting that delay in recognition and referral is not uncommon in India. Parental consanguinity was observed in 57% of the present cohort, higher than reported in other Indian cohorts (25.3%) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This likely reflects regional sociocultural marriage practices and may contribute to the higher prevalence of autosomal-recessive subtypes of IGHD [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] observed in the present cohort.\u003c/p\u003e\u003cp\u003eThe auxological findings showed severe growth failure, with a mean baseline height SDS below \u0026minus;\u0026thinsp;4 and an average deficit of more than 2 SDS from mid-parental height. This wider height deficit from the expected genetic height potential was more pronounced than in other reported Indian cohorts, emphasizing the severity of disease burden at presentation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Bone age was also markedly delayed relative to chronological age, indicating substantial residual growth potential and supporting its role as an important clinical predictor of favourable response to growth-promoting agents [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAll the children in the study cohort showed severe GH deficiency, with very low stimulated peak GH levels and low IGF-1 levels. Although low IGF-1 supports the diagnosis of GHD, its interpretation is limited by wide variability with age, sex, and pubertal status, making absolute thresholds less reliable for use across a broad paediatric population [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. MRI revealed anterior pituitary hypoplasia as the most common abnormality, a feature consistent with severe IGHD. PSIS was also observed in a subset of patients (13%), indicating that structural anomalies may also underlie isolated forms of GHD [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eSeveral genetic subtypes of IGHD have been described in the literature [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Type IA (homozygous \u003cem\u003eGH1\u003c/em\u003e gene deletions) and IB (\u003cem\u003eGHRHR\u003c/em\u003e mutation, occasionally \u003cem\u003eGH1\u003c/em\u003e) are autosomal recessive forms, whereas Type II follows an autosomal dominant inheritance pattern and is typically caused by splice-site or missense mutations in the \u003cem\u003eGH1\u003c/em\u003e. Type III, which is X-linked, involves the \u003cem\u003eBTK\u003c/em\u003e gene (Bruton\u0026rsquo;s Tyrosine Kinase) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Recently, \u003cem\u003eGHRHR\u003c/em\u003e mutations have been referred to as Type IV IGHD by a few authors [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and have been increasingly reported from South Asia and Brazil [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eIn the present study, molecular genetic analysis identified a higher mutation positivity rate (49%), exceeding the commonly reported global rates (20\u0026ndash;40%) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and consistent with a western Indian cohort (45.5%) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This relatively high yield is likely due to the severe nature of IGHD (severe short stature and low stimulated peak GH levels), the high rate of parental consanguinity (57%), and the exclusion of syndromic as well as CPHD children. The majority of variants clustered in \u003cem\u003eGHRHR\u003c/em\u003e (39.7%), with recurrent nonsense and structural mutations; notably, the p.Glu72Ter (E72X) variant was the most prevalent (27%). The recurrence of the E72X variant across South Asian populations, as reported in multiple studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], raises the possibility of a founder mutation. Founder mutations are pathogenic alleles that arise from a single ancestor and become enriched in a population through genetic drift and consanguinity. In addition to South Asia, where the p.Glu72Ter \u003cem\u003eGHRHR\u003c/em\u003e variant has been identified as a founder mutation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], a similar phenomenon has also been described in Northeastern Brazil, where the c.57\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A splice-site mutation represents a distinct founder mutation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although our findings strongly suggest a shared ancestral allele, confirmation will require formal haplotype analysis. Other \u003cem\u003eGHRHR\u003c/em\u003e variants in our series, including p.Gly71Cys, p.Arg161Trp, p.Gly298Arg, and structural deletions, also presented with a classical IGHD phenotype.\u003c/p\u003e\u003cp\u003eIn contrast to the higher prevalence of \u003cem\u003eGHRHR\u003c/em\u003e mutations in South Asia and Brazil (supplement 1), studies from Europe and North America have consistently reported \u003cem\u003eGH1\u003c/em\u003e mutations as the most frequent cause of IGHD, particularly large gene deletions in Type IA and splice-site mutations in Type II [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Similar to other reported South Asian studies [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], we also observed a reversal of the global pattern, with \u003cem\u003eGH1\u003c/em\u003e variants being less frequent (4.8%). The identified \u003cem\u003eGH1\u003c/em\u003e variants in this cohort were a heterozygous nonsense variant (p.Gln66Ter) and homozygous gene deletions detected using WES-based copy number variations (CNV) algorithms.\u003c/p\u003e\u003cp\u003eIn addition to these classical IGHD genes, we also identified variants of uncertain significance (VUS) in \u003cem\u003eGLI2\u003c/em\u003e and \u003cem\u003eROBO1\u003c/em\u003e [4.8%], both of which are implicated in pituitary development and have been previously reported in the PSIS genetics [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. MRI pituitary of three children with these VUS showed PSIS morphology, suggesting an overlapping phenotype rather than classic IGHD [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These children require close follow-up for evolving additional pituitary hormone deficiencies. Despite rare \u003cem\u003eGHRHR\u003c/em\u003e variants such as p.Gly298Arg classified as VUS under ACMG criteria, their consistent correlation with severe biochemical GHD and excellent growth response suggests likely pathogenicity. Future segregation and functional studies may enable the reclassification of all these VUS and contribute to the global genetics database.\u003c/p\u003e\u003cp\u003eThe ROC analysis demonstrates that children with very low stimulated peak GH levels and marked genetic height deficits were most likely to harbour mutations. In particular, peak GH\u0026thinsp;\u0026le;\u0026thinsp;1.11 ng/mL was perfectly discriminative, supporting its utility as a practical clinical marker of genetic IGHD as well as favourable treatment response. A large genetic height deficit also strongly predicted mutation positivity, whereas the BA/CA ratio offered only modest discrimination. The above-reported clinical and biochemical parameters may help predict mutation positivity without doing genetic analysis in children with severe short stature in resource-limited settings. However, larger validation studies are needed to substantiate this finding.\u003c/p\u003e\u003cp\u003eGrowth hormone therapy is FDA-approved for several etiologies of short stature, including certain syndromes [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, growth outcomes in IGHD are heterogeneous, with both auxological and genetic factors influencing the response [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. To the best of our knowledge, this is the largest South Indian IGHD cohort with detailed genetic characterization and first-year treatment-response analysis using multivariable regression. The first-year response to rhGH therapy in the present cohort was favourable, with a mean first-year ΔHeight SDS of 0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58, comparable to other Indian and international series [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eUsing univariate and multivariate regression analysis, the present study identified several independent predictors of favourable first-year ΔHeight SDS. Lower baseline height SDS, greater deviation from mid-parental height, lower peak stimulated GH levels, delayed bone age and younger age at initiation of rhGH therapy were all associated with greater gains, mirroring the classical determinants reported in the KIGS multinational registry (Ranke 1999), the ANSWER registry (Lee 2011), subsequent KIGS model validations (Maghnie 2022) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and Indian cohorts (Bajpai 2006; Khadilkar 2017; Gahlot 2019) [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eNotably, genetic-variant positive status emerged as a novel independent predictor, conferring an additional 0.7 SDS height gain in the first year compared with variant-negative peers. This additional phenotype-genotype correlation, compared with previous descriptive Indian studies [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], provided multivariable confirmation of the prognostic value of the genetic etiology.\u003c/p\u003e\u003cp\u003eThe major strength of this study is its comprehensive design. We integrated detailed auxology, including pedigree analysis, biochemistry, and pituitary imaging, with molecular testing and systematic first-year growth-response assessment using multivariable regression. This approach allowed clear genotype-phenotype correlations and the definition of ROC cut-offs for predicting mutation positivity. Since the cohort is drawn from a South-Indian population with high consanguinity, these findings are directly relevant for settings where recessive forms of IGHD are common.\u003c/p\u003e\u003cp\u003eThis study has a few limitations. Segregation analysis was not performed in all families, which limits confirmation of inheritance patterns and re-classification of some variants of uncertain significance. The sample was from a single tertiary care centre, so referral bias cannot be excluded, and the findings may not fully represent the entire region. The follow-up period was limited to the first year of growth hormone therapy; hence, long-term outcomes remain to be evaluated.\u003c/p\u003e\u003cp\u003eTo conclude, this South-Indian cohort demonstrates that genetic IGHD represents a distinct subgroup characterized by an earlier onset, more severe auxological and biochemical phenotypes, and a favorable response to rhGH therapy. Genetic diagnosis has implications not only for confirming etiology but also for prognostication, long-term management, and family counselling [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In consanguineous populations, the identification of founder \u003cem\u003eGHRHR\u003c/em\u003e mutations opens up opportunities for targeted genetic testing and reproductive counselling [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNational Health Mission, Department of Health and Family Welfare, Government of Tamil Nadu and Chief Minister\u0026rsquo;s Comprehensive Health Insurance Scheme (CMCHIS) for providing growth hormone free of cost.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eD.S. was involved in the collection of data and preparation of the manuscript for submission. S.S. was involved in the concept, design, and final approval of the manuscript. K.M. was involved in the interpretation of genetic data and reviewed the manuscript. P.S. was involved in clinical evaluation, management, and data collection. K.N. was involved in the revision of the manuscript. R.C. was involved in the statistical analysis and interpretation of statistical results. J.S. was involved in supervising the workup.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e None.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe datasets generated and analyzed during the current study are not publicly available due to ethical restrictions, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure summary:\u0026nbsp;\u003c/strong\u003eThere are no relevant financial or non-financial interests to disclose\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eWritten informed consent was obtained from the parents/ guardians of all children included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e: The study was performed in line with the principles of the Declaration of Helsinki, and has been approved by the Institutional Ethics Committee of Madurai Medical College and Government Rajaji Hospital (Ref No. 3374/IEC/2024-02/22 dated 15.04.2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupporting grants or fellowships:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVyas V, Kumar A, Jain V et al (2017) Growth Hormone Deficiency in Children: From Suspecting to Diagnosing. 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Horm Res Paediatr 92(1):1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaghnie M, Ranke MB, Geffner ME, Vlachopapadopoulou E, Ib\u0026aacute;\u0026ntilde;ez L, Carlsson M et al (2022) Safety and Efficacy of Pediatric Growth Hormone Therapy: Results From the Full KIGS Cohort. J Clin Endocrinol Metab 107(12):3287\u0026ndash;3301\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhadikar V, Khadilkar AV, Lohiya NN, Karguppikar MB (2020) Extended growth charts for Indian children. 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Growth Horm IGF Res 24(5):180\u0026ndash;118\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBidlingmaier M, Friedrich N, Emeny RT, Spranger J, Ole D et al (2014) Reference Intervals for Insulin-like Growth Factor-1 (IGF-I) From Birth to Senescence: Results From a Multicenter Study Using a New Automated Chemiluminescence IGF-I Immunoassay Conforming to Recent International Recommendations, The Journal of Clinical Endocrinology \u0026amp; Metabolism, Volume 99, Issue 5, 1 May Pages 1712\u0026ndash;1721\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSridhar S, Raja BR, Priyanka R, Natarajan S, Soundararajan S, Natarajan V (2023) Clinico-radiological correlation of pituitary stalk interruption syndrome in children with growth hormone deficiency. Pituitary 26(5):622\u0026ndash;628\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmmar THA, Al-Ettribi GMM, Abo Hashish MMA et al (2024) Screening of GHSR, GHRHR, GH1 genes in isolated growth hormone deficiency disease in Egyptian patients. Egypt J Med Hum Genet 25:16\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAhmad S, Ali MZ, Abbasi SW, Abbas S, Ahmed I, Abbas S, Nawaz S, Ziab M, Ahmed I, Fakhro KA, Khan MA, Akil AA (2023) A GHRHR founder mutation causes isolated growth hormone deficiency type IV in a consanguineous Pakistani family. Front Endocrinol (Lausanne) 14:1066182\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSundralingam T, Tennekoon KH, de Silva S, De Silva S, Hewage AS (2017) Pathogenic and likely pathogenic genetic alterations and polymorphisms in growth hormone gene (GH1) and growth hormone releasing hormone receptor gene (GHRHR) in a cohort of isolated growth hormone deficient (IGHD) children in Sri Lanka. Growth Horm IGF Res 36:22\u0026ndash;29\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAguiar-Oliveira MH, Salvatori R (2021) Disruption of the GHRH receptor and its impact on children and adults: The Itabaianinha syndrome. Rev Endocr Metab Disord 22(1):81\u0026ndash;89\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJuanes M, Marino R, Ciaccio M et al (2014) Presence of GH1 and absence of GHRHR gene mutations in a large cohort of Argentinian patients with severe short stature and isolated GH deficiency. Clin Endocrinol (Oxf) 80(4):618\u0026ndash;620\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlum WF, Klammt J, Amselem S, Pf\u0026auml;ffle HM, Legendre M, Sobrier ML et al (2018) Screening a large pediatric cohort with GH deficiency for mutations in genes regulating pituitary development and GH secretion: Frequencies, phenotypes and growth outcomes. EBioMedicine 36:390\u0026ndash;400\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi J, Jung C, Kang E et al (2017) Rare frequency of mutations in pituitary transcription factor genes in combined pituitary hormone or isolated growth hormone deficiencies in Korea. Yonsei Med J 58(3):527\u0026ndash;532\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSridhar S, Nazirudeen R, Ramasamy S, Natarajan V, Thiagarajan K, Karthika LN (2022 Jul-Aug) Clinical Profile and Molecular Genetic Analysis of Prader - Willi Syndrome: A Single Center Experience. Indian J Endocrinol Metab 26(4):384\u0026ndash;388\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRanke MB, Lindberg A, Chatelain P, Wilton P, Cutfield W, Albertsson-Wikland K et al (1999) Derivation and validation of a mathematical model for predicting the response to exogenous recombinant human growth hormone (GH) in prepubertal children with idiopathic GH deficiency. KIGS International Board. Kabi Pharmacia International Growth Study. J Clin Endocrinol Metab 84(4):1174\u0026ndash;1183. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1210/jcem.84.4.5634\u003c/span\u003e\u003cspan address=\"10.1210/jcem.84.4.5634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePolak M, Blair J, Kotnik P, Pournara E, Pedersen BT, Rohrer TR (2017) Early growth hormone treatment start in childhood growth hormone deficiency improves near adult height: analysis from NordiNet\u0026reg; International Outcome Study. Eur J Endocrinol 177(5):421\u0026ndash;429\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee PA, Germak J, Gut R, Khutoryansky N, Ross J (2011) Identification of factors associated with good response to growth hormone therapy in children with short stature: results from the ANSWER Program\u0026reg;. Int J Pediatr Endocrinol 2011(1):6\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBajpai A, Kabra M, Gupta AK, Menon PSN (2006) Growth pattern and skeletal maturation following growth hormone therapy in growth hormone deficiency: Factors influencing outcome. Indian Pediatr 43:593\u0026ndash;599\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGahlot M, Goyal A, Singh AKC, Jyotsna VP, Gupta N, Khadgawat R (2019 Jul-Aug) Long-term Response to Recombinant Human Growth Hormone Therapy in Indian Children with Growth Hormone Deficiency. Indian J Endocrinol Metab 23(4):446\u0026ndash;451\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhadilkar V, Phadke N, Khatod K et al (2017) Molecular genetics of growth hormone deficient children: correlation with auxology and response to first year of growth hormone therapy. J Pediatr Endocrinol Metab 30(6):669\u0026ndash;675\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlatzoglou KS, Dattani MT (2012) Phenotype-genotype correlations in congenital isolated growth hormone deficiency (IGHD). Indian J Pediatr 79(1):99\u0026ndash;106\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pituitary","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pitu","sideBox":"Learn more about [Pituitary]()","snPcode":"11102","submissionUrl":"https://submission.nature.com/new-submission/11102/3","title":"Pituitary","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Isolated growth hormone deficiency, Short Stature, GHRHR, GH1, Combined pituitary hormone deficiency, Recombinant human growth hormone (rhGH)","lastPublishedDoi":"10.21203/rs.3.rs-7689542/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7689542/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose:\u003c/h2\u003e\u003cp\u003eIsolated growth hormone deficiency (IGHD) is one among the treatable causes of short stature. We aimed to describe the clinical, biochemical, and molecular characteristics of IGHD as well as to identify clinical predictors of mutation positivity and first-year height response to recombinant human growth hormone (rhGH).\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eSixty-three children with IGHD who had received minimum of one year of rhGH therapy were included. Detailed auxology, growth hormone provocative testing, pituitary MRI were performed and genetic analysis was done by using whole-exome sequencing. The mutation positivity was correlated with auxological and biochemical diagnosis of IGHD. The first-year height response was assessed as ΔHeight SDS and predictors of response were analysed using regression models.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eThe mean age at presentation was 9 years; 57% were born to consanguineous parents. Severe auxological impairment (mean height SDS \u0026minus;\u0026thinsp;4.29, and mean genetic height deficit \u0026minus;\u0026thinsp;2.42 SDS) was observed. Genetic variants were identified in 49% of the study cohort, predominantly in \u003cem\u003eGHRHR\u003c/em\u003e (39.7%), with p.Glu72Ter being the most frequent, whereas G\u003cem\u003eH1\u003c/em\u003e variants were less prevalent (4.8%). Genetic-variant positive children had a younger age at onset, more severe growth failure, and a better response to rhGH treatment. Regression analysis revealed genetic-variant positive status as an independent predictor of favourable first-year growth response (ΔHeight-SDS:1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe South Indian IGHD cohort exhibits a distinct genetic profile, with \u003cem\u003eGHRHR\u003c/em\u003e p.Glu72Ter being the most frequent variant, consistent with a founder effect. Severe short stature, low peak stimulated growth hormone levels, and superior first-year growth response indirectly predicted mutation positivity.\u003c/p\u003e","manuscriptTitle":"Clinical and Molecular Genetic Analysis of Children with Severe Short Stature due to Isolated Growth Hormone Deficiency: Insights from a South Indian Cohort and Predictors of Growth Response.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 15:36:40","doi":"10.21203/rs.3.rs-7689542/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-20T10:50:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-19T19:11:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T03:57:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70730057589435911847931259744091163511","date":"2025-10-06T18:11:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-05T11:55:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"131305277810680191803071344493585049760","date":"2025-09-29T11:42:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76350990840180661737378741857604297587","date":"2025-09-28T12:48:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-28T08:01:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-24T05:40:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-24T05:39:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pituitary","date":"2025-09-23T04:30:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pituitary","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pitu","sideBox":"Learn more about [Pituitary]()","snPcode":"11102","submissionUrl":"https://submission.nature.com/new-submission/11102/3","title":"Pituitary","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"01ead359-02ce-4221-b1d9-ec9d0023b14f","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:03:46+00:00","versionOfRecord":{"articleIdentity":"rs-7689542","link":"https://doi.org/10.1007/s11102-025-01625-x","journal":{"identity":"pituitary","isVorOnly":false,"title":"Pituitary"},"publishedOn":"2025-12-22 15:57:23","publishedOnDateReadable":"December 22nd, 2025"},"versionCreatedAt":"2025-10-10 15:36:40","video":"","vorDoi":"10.1007/s11102-025-01625-x","vorDoiUrl":"https://doi.org/10.1007/s11102-025-01625-x","workflowStages":[]},"version":"v1","identity":"rs-7689542","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7689542","identity":"rs-7689542","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}