The Genetic Landscape of Children Born Small for Gestational Age with Persistent Short Stature

Introduction: Among children born small for gestational age, 10–15% fail to catch up and remain short (SGA-SS). The underlying mechanisms are mostly unknown. We aimed to decipher genetic aetiologies of SGA-SS within a large single-centre cohort. Methods: Out of 820 patients treated with growth hormone (GH), 256 were classified as SGA-SS (birth length and/or birth weight <−2 SD for gestational age and life-minimum height <−2.5 SD). Those with the DNA triplet available (child and both parents) were included in the study (176/256). Targeted testing (karyotype/FISH/MLPA/specific Sanger sequencing) was performed if a specific genetic disorder was clinically suggestive. All remaining patients underwent MS-MLPA to identify Silver-Russell syndrome, and those with unknown genetic aetiology were subsequently examined using whole-exome sequencing or targeted panel of 398 growth-related genes. Genetic variants were classified using ACMG guidelines. Results: The genetic aetiology was elucidated in 74/176 (42%) children. Of these, 12/74 (16%) had pathogenic or likely pathogenic (P/LP) gene variants affecting pituitary development (LHX4, OTX2, PROKR2, PTCH1, POU1F1), the GH-IGF-1 or IGF-2 axis (GHSR, IGFALS, IGF1R, STAT3, HMGA2), 2/74 (3%) the thyroid axis (TRHR, THRA), 17/74 (23%) the cartilaginous matrix (ACAN, various collagens, FLNB, MATN3), and 7/74 (9%) the paracrine chondrocyte regulation (FGFR3, FGFR2, NPR2). In 12/74 (16%), we revealed P/LP affecting fundamental intracellular/intranuclear processes (CDC42, KMT2D, LMNA, NSD1, PTPN11, SRCAP, SON, SOS1, SOX9, TLK2). SHOX deficiency was found in 7/74 (9%), Silver-Russell syndrome in 12/74 (16%) (11p15, UPD7), and miscellaneous chromosomal aberrations in 5/74 (7%) children. Conclusions: The high diagnostic yield sheds a new light on the genetic landscape of SGA-SS, with a central role for the growth plate with substantial contributions from the GH-IGF-1 and thyroid axes and intracellular regulation and signalling.

© 2023 The Author(s). Published by S. Karger AG, Basel

Introduction

Approximately 5% of children are born small for gestational age (SGA) – with a birth weight and/or length below −2 SD compared to normative values for their gestational age [1]. The aetiology of SGA is heterogeneous (environmental, maternal, placental, and endogenous factors, including defined gene variants [2]). Up to 90% of SGA children develop catch-up growth during the first 2 years of life, while the remaining fail to catch up and are referred to as ‘small for gestational age – short stature’ (SGA-SS). These children are known to remain small throughout childhood and reach a substantially reduced adult body height [[3], [4]]. They are therefore indicated for treatment with growth hormone (GH) [[1], [5], [6]]. Nevertheless, the response to GH administration is variable among individual SGA-SS children, which may reflect the heterogeneous aetiology of their growth failure [[7], [8]].

In SGA-SS, several genetic mechanisms should be taken into consideration: imprinting disorders and abnormal methylation patterns such as Silver-Russell syndrome (SRS), Temple syndrome, IMAGe syndrome, and others [[9]–[11]]. In addition, a long list of single gene conditions has been associated with the regulation of human growth and thus impact on final height, albeit not necessarily associated with prenatal growth restriction [[12], [13]]. Some of these genes regulate the structural development of the cerebral midline and pituitary and functional components of the GH-IGF-1 axis (hormones, their receptors, and post-receptor signalisation). Moreover, new genes have been discovered which code for important growth plate paracrine factors, proteins of cartilage extracellular matrix, components of intracellular regulating cascades, and proteins involved in fundamental intranuclear processes [2].

The elucidation of the genetic background of SGA-SS was initiated no more than 2 decades ago [2]. In some cases, a child might present with typical features, leading to targeted genetic testing. A typical example is the genetic diagnosis of SRS in individuals fulfilling the Netchine-Harbison clinical criteria [9]. However, most SGA-SS children present with no apparent syndromic features; therefore, genetic diagnosis is challenging.

New possibilities of genetic testing such as next-generation sequencing (NGS) allowed new advancements in discovering the genetic aetiology of short stature within the past decade [14]. Knowledge of the genetic basis of growth disorders in these children not only helps in better understanding the pathophysiology of growth but may have important consequences for their treatment and follow-up as well. The aim of this study was to decipher genetic aetiologies among a large single-centre cohort of SGA-SS children treated with GH and to stratify them according to molecular mechanisms leading to combined pre- and postnatal growth failure.

Patients

The study cohort was selected from 820 children treated with GH in our centre between May 2008 and December 2018 using a stepwise selection process as displayed in Figure 1. Other causes of growth failure were considered and appropriately evaluated before starting GH therapy. Extremely preterm children (gestational age <28 weeks) were excluded due to missing relevant normative values for their size at birth. After exclusion of children treated with GH for other causes (chronic kidney disease, acquired GH deficiency (GHD), Turner syndrome, Prader-Willi syndrome, and primary GHD born either appropriate for gestational age or SGA but with life-minimum height >−2.5 SD), 256 children with SGA-SS (birth weight or length <−2 SD and body height <−2.5 SD after 3 years of life) remained for further evaluation. Out of them, 176/256 (69%) families agreed to genetic testing; therefore, the child and both of his/her parents were enrolled in the study (Fig. 1). The clinical assessment of all children included measurements of weight (using an electronic scale) and height (mean of three measurements using a calibrated stadiometre to the nearest 1 mm). These results were converted to the SDS using age- and sex-specific normative values [15]. The height of the parents was either obtained during the patients’ visit using the same method or referred from their medical records. Birth parameters were obtained from medical records.

Fig. 1.

Flowchart of the study. GH, growth hormone; CKD, chronic kidney disease; GHD, growth hormone deficit; IGHD, idiopathic growth hormone deficit; AGA, appropriate for gestational age; MS-MLPA, methylation-specific multiplex ligation-dependent probe amplification; WES, whole-exome sequencing; SRS, Silver-Russell syndrome; VUS, variant of uncertain significance; LB, likely benign; B, benign; LP, likely pathogenic; P, pathogenic.

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The cohort included 93 males and 83 females. The median birth term was 39 weeks (interquartile range [IQR] 37; 40), median birth weight was 2,485 g (IQR 2,108; 2,788), and median birth length was 45 cm (IQR 43; 47). The median age at initiation of GH therapy was 4.95 years (IQR 3.13; 7.18), and the median life-minimum height SDS was −3.04 (IQR −3.49; −2.72).

All SGA-SS children underwent long-term GH treatment with a dosage of 35 μg/kg/day as suggested in the consensus from Clayton et al. [5]. If the child was also found to have GHD, the dose was in the range of 25–35 μg/kg/day in accordance with summary of product characteristics, and in the case of SHOX deficiency, 50 μg/kg/day as recommended in previous studies [16].

MethodsGenetic TestingGenetic Testing Prior to the Study

All children with a clinical suspicion of a specific genetic disorder underwent genetic examination with an appropriate method (karyotype, FISH, MLPA, targeted Sanger sequencing) prior to the study. The remaining children were examined for SRS. After its’ exclusion, patients were examined by NGS methods.

Examination of SRS

Methylation-specific multiplex ligation-dependent Probe amplification (MS-MLPA) was done in all patients. MS-MLPA (probe mixes ME030 and ME032 examining regions of 11p15, 7q32, 7p12, and 14q32, respectively) and subsequent data analyses by software Coffalyser were performed according to the manufacturer’s instructions (MRC Holland, Amsterdam, The Netherlands).

Targeted NGS

Genomic DNA was extracted from peripheral blood using QIAmp DNA Blood Mini (Qiagen, Hilden, Germany) or from saliva (collected into Oragene OG-500) according to the manufacturer’s instructions (DNA Genotek, Ontario, Canada). DNA of patients without a verified genetic cause of their growth failure was analysed using a custom-targeted NGS panel of 398 genes with a known or potential association with growth [17] using SureSelect Custom Kit (Agilent Technologies, Santa Clara, CA, USA), and the indexed products were sequenced by synthesis on an Illumina MiSeq platform (San Diego, CA, USA) with ×100 average coverage. Altogether 6 DNA samples from probands underwent the whole-exome sequencing using SureSelect Human All Exon v6+UTR Kit (Agilent Technologies). The indexed products were sequenced by synthesis on an Illumina MiSeq or NextSeq platform (San Diego, CA, USA) with ×100 average coverage. Obtained sequences were annotated and mapped to reference genome followed by variant calling as described previously [17]. Detected variants were filtered using software Variant Annotation and Filter Tool [18] with filter settings described previously [17].

Evaluation of Genetic Findings

Confirmation of all variants of interest in the patient and segregation analyses in available family members were performed by direct Sanger sequencing [19]. Subsequently, variants were scored according to the American College of Medical Genetics and Genomics (ACMG) standards and guidelines [20] implemented in the VarSome software [21] as pathogenic (P), likely pathogenic (LP), benign (B), likely benign (LB), or as variants of uncertain significance (VUS). Consideration of co-segregation in the pathogenicity classification of variants (criterion PP1 in the ACMG guidelines) was applied based on recommendations by Jarvik and Browning [22].

Ethics Statement

This study protocol was reviewed and approved by the Institutional Ethics Committees of the 2nd Faculty of Medicine, Charles University in Prague, and University Hospital Motol, Czech Republic (date of approval: June 30, 2017; not numbered). Written informed consent was obtained from the parents/legal guardians of the patients for publication of the details of their medical cases and any accompanying images.

Results

In total, the genetic diagnosis was elucidated in 74/176 (42%) children (Fig. 1). We confirmed pathogenic or likely pathogenic (P/LP) gene variants affecting pituitary development or GH secretion (LHX4, OTX2, PROKR2, PTCH1, POU1F, GHSR) and/or the GH-IGF-1 axis and IGF-2 axis (IGFALS, IGF1R, STAT3, HMGA2) in 12/74 (16%) patients. Two out of 74 children (3%) had P/LP gene variants affecting the thyroid axis (TRHR, THRA). P/LP gene variants affecting the growth plate were revealed in 31/74 (42%). Of these, 17/74 children had P/LP variants in genes responsible for components of the cartilaginous matrix (ACAN [in four], COL1A1, COL1A2, COL2A1, COL9A1, COL9A2, COL11A1, FLNB, MATN3), 7/74 had impaired paracrine regulation of chondrocytes (FGFR3, FGFR2, NPR2), and 7/74 had SHOX gene defects. In 12/74 children (16%), we revealed P/LP variants in genes involved in fundamental intracellular and intranuclear processes (CDC42, KMT2D, LMNA, NSD1, PTPN11, SRCAP, SON, SOS1, SOX9, TLK2). SRS was diagnosed in 12/74 (16%) (11p15, UPD7), and miscellaneous chromosomal aberrations were identified in 5/74 (7%) children.

Overall, in our cohort, 40 out of 74 patients (54%) had positive genetic findings and no dysmorphic features. Part of these results were published in our previous reports on children from families with vertical transmission of short stature (“familiar short stature”) [17] and/or in a paper summarising the effect of GH therapy in children with pathogenic NPR2 variants [23] and non-syndromic collagenopathies [24]. The principal clinical and growth data are summarised in Table 1. All the genetic findings are presented in Table 2. The single-gene conditions (and SRS) and their significance at three levels of growth regulation are displayed in Figure 2a–c.

Table 1.

Clinical findings in children born small for gestational age with persistent short stature (SGA-SS) with elucidated genetic diagnosis

Patient No.GenderGWBW, gBW (SDS)BL, cmBL (SDS)Father’s height (SDS)Mother’s_height (SDS)Age at start of GH therapy, yearsHeight (SDS) at start of GH therapyHeight (SDS) after 1 year of GH therapyHeight (SDS) after 3 years of GH therapyFinal height (SDS)IGF-1 (SDS) prior to therapyBA-CA, yearsPrimary diagnosis leading to GH treatmentBrain MRIDysmorphic features1F371,860−2.842−3.8−1.3−2.76.3−3.2−2.0−1.6N/A1.09−1.2GHD+SGANormalNo2M422,890−2.150−1.40.4−3.94.1−3.1−2.4−1.9N/A−2.01−0.4GHD+SGANormalNo3M402,840−1.947−2.4−1.7−0.77.7−2.7−2.3−1.6−2.60.11N/AGHD+SGANormalNo4F361,690−3.037−6.40.0−0.53.2−4.2−3.3−3.2N/AN/AN/ASGAN/AYes5F392,210−2.944−3.4−1.50.13.5−2.7−2.0−1.4N/A1.27−1.5SGAN/ANo6M321,260−1.938−3.9−1.6−2.77.0−3−2.2−1.7N/A0.02−0.3SGAN/ANo7F392,480−2.245−2.8−0.7−0.47.4−4.3−4.0−3.4−2.8−1.73N/ASGAN/ANo8M372,060−2.544−2.80.30.62.3−3.8−3.8−2.7N/A−5.37N/AGHD+SGABilateral anophthalmia, agenesis of optic nerves, and chiasmYes9M331,750−1.141−2.7−0.60.41.1−5.0−3.1−1.9N/A−4.40−1.1GHD+SGAN/ANo10F402,350−2.948−1.60.4−1.213.5−3.3−2.3−1.1−1.0−4.78−1.4GHD+SGARathke cleft cystNo11M301,120−1.336−4.00.40.42.8−2.6−1.9−0.7N/A−1.84−1.8GHD+SGANormalNo12M352,200−1.144−2.1−0.03−1.26.3−2.5N/AN/AN/A−2.74−0.8SGAN/ANo13M402,750−2.148−1.9−0.7−0.87.1−3.1−2.6−2.2N/A−1.78−2.3GHD+SGAN/ANo14M402,900−1.847−2.4−2.9−2.011.6−3.7−3.9−2.9−2.6−3.22−3.3SGAN/ANo15F392,850−1.646−2.2−1.7−2.95.7−3.0−2.7−2.5N/A0.741.9SGAN/ANo16M382,670−0.645−2.70.7−1.63.6−2.5−1.5−1.0−0.50.91N/ASGAN/ANo17F402,960−1.346−2.60.7−1.24.4−3.1−2.4−1.9−3.61.190.1SGAN/ANo18M402,920−1.845−3.4−3.6−0.87.4−3.3−2.7−2.1−2.0−3.100.5SGANormalNo19F331,350−2.138−4.3−2.4−2.33.3−2.7−2.6−2.1−1.5−1.510.2SGAN/ANo20M392,450−2.446−2.55−2.3−2.712.6−2.7−2.3−2.7−3.10.73−0.3SGAN/ANo21F402,350−2.946−2.7−1.0−1.55.4−3−2.8−1.9N/A−1.35−0.3GHD+SGANormalYes22M402,520−2.649−1.4−2.00.04.3−2.5−2.0−1.9−2.3−0.64−0.9GHD+SGAN/ANo23F392,270−2.742−4.4−1.5−3.45.7−2.8−2.1−0.8−2.70.49−0.4SGAN/ANo24M392,450−2.545−3.1−2.9−1.312.0−3.4−2.7−2.1−2.2−1.51−1.6SGAN/ANo25F402,500−2.543−4.3−2.2−0.47.0−3.1−2.4−2.1N/A0.93−2.5SGAN/ANo26M392,660−2.047−2.1−3.2−1.56.0−3.7−3.2−2.8N/A−3.16N/ASGACyst of cisterna magnaNo27M402,750−2.148−1.9−1.3−1.59.2−2.7−2.2−1.4N/A0.34−1.4SGAN/ANo28M402,400−2.948−1.9−1.5−1.210.2−2.8−2.0−0.6−1.5−1.26N/AGHD+SGAN/AYes29F403,000−1.345−3.20.8−1.56.4−2.8−2.2−1.5−2.1−0.15−0.2SGANormalNo30M403,200−1.047−2.4−3.20.81.5−2.5−1.8−1.5N/A−0.27N/ASGAN/ANo31M402,650−2.347−2.40.4−2.39.1−2.5−1.6−0.8N/A0.090.1SGAN/ANo32F413,190−1.047−2.4−1.2−1.27.1−2.5−1.60.1N/A−0.90−2.1GHD+SGAPituitary microadenomaNo33F402,600−2.345−3.2−1.1−1.26.0−2.9−2.3−1.4N/A0.32N/ASGANormalNo34F412,880−1.847−2.40.8−2.44.0−2.9−2.9−1.9N/A0.15N/AGHD+SGANormalNo35M392,710−1.946−2.6N/A−1.83.3−2.8−2.4−2.2N/A−2.01−0.4GHD+SGANormalNo36F412,800−2.048−1.8−2.4−2.33.1−3.6−3.0−2.5N/A−6.04N/ASGAN/ANo37F402,630−2.247−2.1−2.0−1.33.4−3.5−2.7−2.5−2.7−1.65−0.3SGAN/ANo38M382,460−244−3.2−1.5−3.74.5−3.5−2.9−2.5N/A−2.48N/AGHD+SGANormalNo39M392,490−2.448−1.6−2.9−1.21.5−2.9−2.9−2.5N/A−2.50−0.8SGANormalYes40M402,460−2.849−1.4−0.50.42.2−2.5−1.1−0.9N/A−0.450.0GHD+SGASmall pituitaryYes41M403,270−0.946−2.9−0.460.431.9−4−3.0−4.8N/A−1.37−0.5GHD+SGASmall pituitaryYes42F392,444−2.344−3.4−1.40.23.9−2.9−2.3−2.5N/A0.88N/ASGAN/AYes43F352,050−1.342−2.90.8−1.52.3

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