Pathogenic Copy Number and Sequence Variants in Children Born SGA With Short Stature Without Imprinting Disorders

Role of genetic investigation in the diagnosis of short stature in a cohort of Italian children

BACKGROUND

Short stature (SS) is defined as height more than 2 standard deviations below the mean for age and sex. Hypothyroidism, celiac disease, growth hormone deficiency, hormonal abnormalities, and genetic conditions are among its causes. A wide range of conditions often due to largely unknown genetic variants can elude conventional diagnostic workup.

AIM

We used next-generation sequencing (NGS) to better understand the etiology of SS in a cohort of Italian children.

PATIENTS AND METHODS

The study sample was 125 children with SS of unknown origin referred to our Institute between 2015 and 2021. All had undergone complete auxological and hormonal investigations to exclude common causes of SS. Genetic analysis was performed using a NGS panel of 104 genes. Clinical data were reviewed to clarify the pathogenicity of the variants detected.

RESULTS

In this cohort, 43 potentially causing variants were identified in 38 children. A syndromic genetic condition was diagnosed in 7: Noonan syndrome in 3, Leri-Weill syndrome in 3, and hypochondroplasia in 1. Moreover, 8 benign variants and other 37 like benign variants were found. In 88 children, 179 variants of uncertain significance (VUS) were identified. No variant was found in 16 children.

CONCLUSION

Genetic analysis is a useful tool in the diagnostic workup of patients with SS, in adapting management and treatment, and in identifying syndromes with mild atypical clinical features. The role of VUS should not be underestimated, particularly when multiple VUS with possible mutual worsening effects are present in the same child.

Comprehensive assessment of the genetic characteristics of small for gestational age newborns in NICU: from diagnosis of genetic disorders to prediction of prognosis

BACKGROUND

In China, ~1,072,100 small for gestational age (SGA) births occur annually. These SGA newborns are a high-risk population of developmental delay. Our study aimed to evaluate the genetic profile of SGA newborns in the newborn intensive care unit (NICU) and establish a prognosis prediction model by combining clinical and genetic factors.

METHODS

A cohort of 723 SGA and 1317 appropriate for gestational age (AGA) newborns were recruited between June 2018 and June 2020. Clinical exome sequencing was performed for each newborn. The gene-based rare-variant collapsing analyses and the gene burden test were applied to identify the risk genes for SGA and SGA with poor prognosis. The Gradient Boosting Machine framework was used to generate two models to predict the prognosis of SGA. The performance of two models were validated with an independent cohort of 115 SGA newborns without genetic diagnosis from July 2020 to April 2022. All newborns in this study were recruited through the China Neonatal Genomes Project (CNGP) and were hospitalized in NICU, Children's Hospital of Fudan University, Shanghai, China.

RESULTS

Among the 723 SGA newborns, 88(12.2%) received genetic diagnosis, including 42(47.7%) with monogenic diseases and 46(52.3%) with chromosomal abnormalities. SGA with genetic diagnosis showed higher rates in severe SGA(54.5% vs. 41.9%, P=0.0025) than SGA without genetic diagnosis. SGA with chromosomal abnormalities showed higher incidences of physical and neurodevelopmental delay compared to those with monogenic diseases (45.7% vs. 19.0%, P=0.012). We filtered out 3 genes (ITGB4, TXNRD2, RRM2B) as potential causative genes for SGA and 1 gene (ADIPOQ) as potential causative gene for SGA with poor prognosis. The model integrating clinical and genetic factors demonstrated a higher area under the receiver operating characteristic curve (AUC) over the model based solely on clinical factors in both the SGA-model generation dataset (AUC=0.9[95% confidence interval 0.84-0.96] vs. AUC=0.74 [0.64-0.84]; P=0.00196) and the independent SGA-validation dataset (AUC=0.76 [0.6-0.93] vs. AUC=0.53[0.29-0.76]; P=0.0117).

CONCLUSION

SGA newborns in NICU presented with roughly equal proportions of monogenic and chromosomal abnormalities. Chromosomal disorders were associated with poorer prognosis. The rare-variant collapsing analyses studies have the ability to identify potential causative factors associated with growth and development. The SGA prognosis prediction model integrating genetic and clinical factors outperformed that relying solely on clinical factors. The application of genetic sequencing in hospitalized SGA newborns may improve early genetic diagnosis and prognosis prediction.

Molecular Diagnostic Yield of Exome Sequencing and Chromosomal Microarray in Short Stature: A Systematic Review and Meta-Analysis

Importance

Currently, the diagnostic yield of exome sequencing (ES) and chromosomal microarray analysis (CMA) for short stature cohorts is uncertain. Despite previous studies reporting the widespread use of ES and CMA, a definitive diagnostic yield has not been established.

Objective

To investigate the diagnostic yield of ES and CMA in short stature.

Data Sources

A systematic literature search was conducted using relevant keywords in 3 databases (PubMed, Embase, and Web of Science) in February 2023.

Study Selection

Eligible studies for meta-analysis were those that had at least 10 participants with short stature who were diagnosed using either ES or CMA and the number of diagnosed patients was reported. Of 5222 identified studies, 20 were eventually included in the study.

Data Extraction and Synthesis

Two independent investigators extracted relevant information from each study, which was then synthesized using proportional meta-analysis to obtain the overall diagnostic yield of ES and CMA.

Main Outcomes and Measures

The primary outcome measure was to determine the overall diagnostic yield of ES and CMA. A subgroup meta-analysis was also performed to assess if the diagnostic yield varied depending on whether ES was used as a first-tier or last-resort test. Additionally, a meta-regression was carried out to investigate how the diagnostic yield varied over time.

Results

Twenty studies were included, comprising 1350 patients with short stature who underwent ES and 1070 patients who completed CMA. The overall diagnostic yield of ES among the cohorts and CMA among the cohorts was found to be 27.1% (95% CI, 18.1%-37.2%) and 13.6% (95% CI, 9.2%-18.7%), respectively. No statistically significant difference was observed between the first-tier (27.8%; 95% CI, 15.7%-41.8%) and last-resort groups (25.6%; 95% CI, 13.6%-39.6%) (P = .83) or in the percentage of positively diagnosed patients over time. No statistically significant difference was observed between the first-tier (27.8%; 95% CI, 15.7%-41.8%) and last-resort groups (25.6%; 95% CI, 13.6%-39.6%) (P = .83) or in the percentage of positively diagnosed patients over time.

Conclusion and Relevance

This systematic review and meta-analysis provides high-level evidence supporting the diagnostic efficacy of ES and CMA in patients with short stature. The findings serve as a solid reference for clinicians when making informed decisions about recommending these genetic tests.

Investigation of (Epi)genetic causes in syndromic short children born small for gestational age

Intrauterine onset syndromic short stature constitutes a group of diseases that pose challenges in differential diagnosis due to their rarity and clinical as well as molecular heterogeneity. The aim of this study was to investigate the presence of (epi)genetic causes in children born small for gestational age (SGA) and manifesting clinically undiagnosed syndromic short stature. The study group comprised twenty-nine cases selected from the syndromic SGA cohort. Various analyses were performed, including chromosomal microarray (CMA), methylation-specific-multiple ligation probe amplification for chromosomes 6,14 and 20, and whole exome sequencing (WES). Pathogenic copy number variants (CNVs) on chromosomes 2q13, 22q11.3, Xp22.33, 17q21.31, 19p13.13 and 4p16.31 causing syndromic growth disturbance were detected in six patients. Maternal uniparental disomy 14 was identified in a patient. WES was performed in the remaining 22 patients, revealing pathogenic variants in nine cases; six were monoallelic (ACAN, ARID2, NIPBL, PIK3R1, SMAD4, BRIP1), two were biallelic (BRCA2, RFWD3) and one was hemizygous (HUWE1). Seven of these were novel. Craniofacial dysmorphism, which is an important clue for the diagnosis of syndromes, was very mild in all patients. This study unveiled, for the first time, that ARID2 mutatios can cause syndromic SGA. In conclusion, a high (55.2%) diagnosis rate was achieved through the utilization of CMA, epigenetic and WES analyzes; 15 rare syndromes were defined, who were born with SGA and had atypical and/or mild dysmorphic findings. This study not only drew attention to the association of some rare syndromes with SGA, but also introduced novel genes and CNVs as potential contributors to syndromic SGA.

Exploring the Genetic Causes for Postnatal Growth Failure in Children Born Non-Small for Gestational Age

The most common causes of short stature (SS) in children are familial short stature (FSS) and idiopathic short stature (ISS). Recently, growth plate dysfunction has been recognized as the genetic cause of FSS or ISS. The aim of this study was to investigate monogenic growth failure in patients with ISS and FSS. Targeted exome sequencing was performed in patients categorized as ISS or FSS and the subsequent response to growth hormone (GH) therapy was analyzed. We found 17 genetic causes involving 12 genes (NPR2, IHH, BBS1, COL1A1, COL2A1, TRPS1, MASP1, SPRED1, PTPTN11, ADNP, NADSYN1, and CERT1) and 2 copy number variants. A genetic cause was found in 45.5% and 35.7% of patients with FSS and ISS, respectively. The genetic yield in patients with syndromic and non-syndromic SS was 90% and 23.1%, respectively. In the 11 genetically confirmed patients, a gain in height from -2.6 to -1.3 standard deviations after 2 years of GH treatment was found. The overall diagnostic yield in this study was 41.7%. We identified several genetic causes involving paracrine signaling, the extracellular matrix, and basic intracellular processes. Identification of the causative gene may provide prognostic evidence for the use of GH therapy in non-SGA children.

Approach to the Patient With Short Stature: Genetic Testing

The first step in the evaluation of the short child is to decide whether growth parameters in the context of the history are abnormal or a variant of normal. If growth is considered abnormal, system and hormonal tests are likely to be required, followed by more directed testing, such as skeletal survey and/or genetic screening with karyotype or microarray. In a small percentage of short children in whom a diagnosis has not been reached, this will need to be followed by detailed genetic analysis; currently, exome sequencing using targeted panels relevant to the phenotype is the commonly used test. Clinical scenarios are presented that illustrate how such genetic testing can be used to establish a molecular diagnosis, and how that diagnosis contributes to the management of the short child. New genetic causes for short stature are being recognized on a frequent basis, while the clinical spectrum for known genes is being extended. We recommend that an international repository for short stature conditions is established for new findings to aid dissemination of knowledge, but also to help in the definition of the clinical spectrum both for new and established conditions.