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ABSTRACT: At the individual cow level, suboptimum fertility, mastitis, negative energy balance, and ketosis are major issues in dairy farming. These problems are widespread on dairy farms and have an important economic impact. The objectives of this study were (1) to assess the potential of milk mid-infrared (MIR) spectra to predict key biomarkers of energy deficit (citrate, isocitrate, glucose-6 phosphate [glucose-6P], free glucose), ketosis (β-hydroxybutyrate [BHB] and acetone), mastitis (N-acetyl-β-d-glucosaminidase activity [NAGase] and lactate dehydrogenase), and fertility (progesterone); (2) to test alternative methodologies to partial least squares (PLS) regression to better account for the specific asymmetric distribution of the biomarkers; and (3) to create robust models by merging large datasets from 5 international or national projects. Benefiting from this international collaboration, the dataset comprised a total of 9,143 milk samples from 3,758 cows located in 589 herds across 10 countries and represented 7 breeds. The samples were analyzed by reference chemistry for biomarker contents, whereas the MIR analyses were performed on 30 instruments from different models and brands, with spectra harmonized into a common format. Four quantitative methodologies were evaluated to address the strongly skewed distribution of some biomarkers. Partial least squares regression was used as the reference basis, and compared with a random modification of distribution associated with PLS (random-downsampling-PLS), an optimized modification of distribution associated with PLS (KennardStone-downsampling-PLS), and support vector machine (SVM). When the ability of MIR to predict biomarkers was too low for quantification, different qualitative methodologies were tested to discriminate low versus high values of biomarkers. For each biomarker, 20% of the herds were randomly removed within all countries to be used as the validation dataset. The remaining 80% of herds were used as the calibration dataset. In calibration, the 3 alternative methodologies outperform the PLS performances for the majority of biomarkers. However, in the external herd validation, PLS provided the best results for isocitrate, glucose-6P, free glucose, and lactate dehydrogenase (coefficient of determination in external herd validation [R2v] = 0.48, 0.58, 0.28, and 0.24, respectively). For other molecules, PLS-random-downsampling and PLS-KennardStone-downsampling outperformed PLS in the majority of cases, but the best results were provided by SVM for citrate, BHB, acetone, NAGase, and progesterone (R2v = 0.94, 0.58, 0.76, 0.68, and 0.15, respectively). Hence, PLS and SVM based on the entire dataset provided the best results for normal and skewed distributions, respectively. Complementary to the quantitative methods, the qualitative discriminant models enabled the discrimination of high and low values for BHB, acetone, and NAGase with a global accuracy around 90%, and glucose-6P with an accuracy of 83%. In conclusion, MIR spectra of milk can enable quantitative screening of citrate as a biomarker of energy deficit and discrimination of low and high values of BHB, acetone, and NAGase, as biomarkers of ketosis and mastitis. Finally, progesterone could not be predicted with sufficient accuracy from milk MIR spectra to be further considered. Consequently, MIR spectrometry can bring valuable information regarding the occurrence of energy deficit, ketosis, and mastitis in dairy cows, which in turn have major influences on their fertility and survival.

ABSTRACT: Among the dairy sector's current concerns, the assessment of global animal health status is a complex challenge. Its multidimensionality means that global monitoring tools are rarely considered. Instead, specific disease detection is often studied separately and, due to financial and ethical issues, uses small-scale data sets focusing on few biomarkers. Several studies have already been conducted using milk Fourier transform mid-infrared (FT-MIR) spectroscopy to detect mastitis and lameness or to quantify health-related biomarkers in milk or blood. Those studies are relevant but they focus mainly on one biomarker or disease. To solve this issue and the small-scale data set, in this study, we proposed a holistic approach using big data obtained from milk recording, including milk yield, somatic cell count, and 27 FT-MIR–based predictors related to milk composition and animal health status. Using 740,454 records collected from 114,536 first-parity Holstein cows in southern Belgium, we performed repeated unsupervised learning algorithms based on Ward's agglomerative hierarchical clustering method to find potential interesting patterns. A divide-and-conquer approach was used to overcome the limitation of computational resources in clustering a relatively large data set. Five groups of records were identified. Differences observed in the fourth group suggested a relationship to metabolic disorders. The fifth group seemed to be related to mastitis. In a second step, we performed a partial least squares discriminant analysis (PLS-DA) to predict the probability of belonging to those specific groups for the entire data set. The obtained global accuracy was 0.77 and the balanced accuracy (i.e., the mean between sensitivity and specificity) of discriminating the fourth and fifth groups was 0.88 and 0.96, respectively. Then, a validation of the interpretation of those groups was performed using 204 milk and blood reference records. The predicted probability associated with the metabolic disorders issue had significant correlations of 0.54 with blood β-hydroxybutyrate, 0.44 with blood nonesterified fatty acids, −0.32 with blood glucose, −0.23 with milk glucose-6-phosphate, and 0.38 with milk isocitrate. In contrast, the predicted probability of belonging to the mastitis group had correlations of 0.69 with milk lactate dehydrogenase, 0.46 with milk N-acetyl-β-d-glucosaminidase, −0.18 with milk free glucose, and 0.16 with milk glucose-6-phosphate. Consequently, these results suggest that the obtained quantitative traits indirectly reflect some of the main health disorders in dairy farming and could be used to monitor dairy cows on a large scale. By using unsupervised learning on large-scale milk recording data and then validating the pattern using reference laboratory measures, we propose a new approach to quickly assess dairy cow health status.

Stress in dairy herds can occur from multiple sources. When stress becomes chronic because of a long duration and inability of animals to adapt, it is likely to deeply affect the emotional state, health, immunity, fertility and milk production of cows. While assessing chronic stress in herds would be beneficial, no real consensus has emerged from the literature regarding the indicators of interest. The goal of this study was to compare and evaluate potential biomarkers for chronic stress after inducing stress over a 4-week period through severe overstocking, restricted access to feed and isolated unusual events. A total of 30 cows were involved in the experiment and two similar groups were constituted. Over a 4-week period, the 15 cows of the stress group were housed in overstocked conditions, with 4.6 m2 per cow, including resting and feeding areas. In this area, only seven individual places at the feeding area were available for the 15 cows to generate competition for feed access. Twice during the trial and over a period of 2 h, an additional stress was induced by moving cows to an unfamiliar barn and diffusion of stressing noises (dog barking). Meanwhile, the 15 cows of the control group stayed in the original barn, with more than 10 m2 per cow and more individual places at the feeding area than cow number. On a weekly basis, several variables considered as potential biomarkers for chronic stress were recorded. Collected data were analysed using single trait linear repeated mixed models. No differences were observed regarding milk yield, BW of cows or body condition score but the milk loss was more pronounced in the stress group. The activity was more heterogeneous and the rumination of cows was lower in the stress group. The heart rate was lower in the stress group and showed more heterogeneity at the end of the stress period. No differences were observed regarding salivary cortisol, blood glucose, β-endorphin, thyroxine and leucocyte profile. A higher level of hair cortisol and blood fructosamine were observed in the stress group at the end of the stress period. Regarding the practical use of the highlighted biomarkers, milk loss may be an effective and easy way to detect general problems, including stress. The blood fructosamine and the hair cortisol concentrations are promising indicators to assess chronic stress in commercial farms.

Genetic factors play a crucial role in determining human height. Short stature commonly affects multiple family members and therefore, familial short stature (FSS) represents a significant proportion of growth disorders. Traditionally, FSS was considered a benign polygenic condition representing a subcategory of idiopathic short stature (ISS). However, advancements in genetic research have revealed that FSS can also be monogenic, inherited in an autosomal dominant manner and can result from different mechanisms including primary growth plate disorders, growth hormone deficiency/insensitivity or by the disruption of fundamental intracellular pathways. These discoveries have highlighted a broader phenotypic spectrum for monogenic forms of short stature, which may exhibit mild manifestations indistinguishable from ISS. Given the overlapping features and the difficulty in differentiating polygenic from monogenic FSS without genetic testing, some researchers redefine FSS as a descriptive term that encompasses any familial occurrence of short stature, regardless of the underlying cause. This shift emphasizes the complexity of diagnosing and managing short stature within families, reflecting the diverse genetic landscape that influences human growth., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Plachy, Dusatkova, Amaratunga, Neuman, Sumnik, Lebl and Pruhova.)

Previous reports provided recommendations for familial renal glucosuria diagnosis without complex view on differential diagnosis of glucosuria. The aim of this review was to provide an overview of the causes of glucosuria and to create an evidence-based diagnostic approach for children with glucosuria. We searched the current literature with a focus to identify the possible etiology of glucosuria, gaining insight into the pathophysiology of glucosuria. Urinary glucose is completely reabsorbed in the proximal tubule of kidneys. It only appears in the urine if the plasma glucose concentration exceeds the renal threshold for glucose or in the case of insufficient renal glucose reabsorption. The proteins that provide glucose reabsorption are SGLT2 and SGLT1 - sodium-dependent co-transporters that transport glucose from the lumen into epithelial cells - and GLUT2 - a passive transporter providing facilitative glucose transport from epithelial cells to plasma. Renal glucose reabsorption is affected in case of acquired or inherited complex dysfunction of proximal tubule called Fanconi Syndrome or due to pathogenic variants of genes encoding glucose transporters. Prior to diagnosing any of these, diabetes mellitus must be excluded together with other conditions leading to hyperglycemia. In conclusion, glucosuria is always an abnormal finding. The review provides a simple evidence-based diagnostic approach to navigate the differential diagnosis of glucosuria.

Multisystem inflammatory syndrome in children (MIS-C) is a rare condition following SARS-CoV-2 infection associated with intestinal manifestations. Genetic predisposition, including inborn errors of the OAS-RNAseL pathway, has been reported. We sequenced 154 MIS-C patients and utilized a novel statistical framework of gene burden analysis, "burdenMC," which identified an enrichment for rare predicted-deleterious variants in BTNL8 (OR = 4.2, 95% CI: 3.5-5.3, P < 10-6). BTNL8 encodes an intestinal epithelial regulator of Vγ4+γδ T cells implicated in regulating gut homeostasis. Enrichment was exclusive to MIS-C, being absent in patients with COVID-19 or bacterial disease. Using an available functional test for BTNL8, rare variants from a larger cohort of MIS-C patients (n = 835) were tested which identified eight variants in 18 patients (2.2%) with impaired engagement of Vγ4+γδ T cells. Most of these variants were in the B30.2 domain of BTNL8 implicated in sensing epithelial cell status. These findings were associated with altered intestinal permeability, suggesting a possible link between disrupted gut homeostasis and MIS-C-associated enteropathy triggered by SARS-CoV-2., (© 2024 Bellos et al.)

Purpose: Genetic testing in consanguineous families advances the general comprehension of pathophysiological pathways. However, short stature (SS) genetics remain unexplored in a defined consanguineous cohort. This study examines a unique pediatric cohort from Sulaimani, Iraq, aiming to inspire a genetic testing algorithm for similar populations., Methods: Among 280 SS referrals from 2018-2020, 64 children met inclusion criteria (from consanguineous families; height ≤ -2.25 SD), 51 provided informed consent (30 females; 31 syndromic SS) and underwent investigation, primarily via exome sequencing. Prioritized variants were evaluated by the American College of Medical Genetics and Genomics standards. A comparative analysis was conducted by juxtaposing our findings against published gene panels for SS., Results: A genetic cause of SS was elucidated in 31 of 51 (61%) participants. Pathogenic variants were found in genes involved in the GH-IGF-1 axis (GHR and SOX3), thyroid axis (TSHR), growth plate (CTSK, COL1A2, COL10A1, DYM, FN1, LTBP3, MMP13, NPR2, and SHOX), signal transduction (PTPN11), DNA/RNA replication (DNAJC21, GZF1, and LIG4), cytoskeletal structure (CCDC8, FLNA, and PCNT), transmembrane transport (SLC34A3 and SLC7A7), enzyme coding (CYP27B1, GALNS, and GNPTG), and ciliogenesis (CFAP410). Two additional participants had Silver-Russell syndrome and 1 had del22q.11.21. Syndromic SS was predictive in identifying a monogenic condition. Using a gene panel would yield positive results in only 10% to 33% of cases., Conclusion: A tailored testing strategy is essential to increase diagnostic yield in children with SS from consanguineous populations., Competing Interests: Conflict of Interest The authors have no conflicts of interest to declare., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

• For children with growth hormone deficiency, once-weekly somatrogon injections were less of a burden than once-daily somatropin injections. • The safety of weekly somatrogon was similar to that of daily somatropin . • Compared with daily somatropin injections, children with growth hormone deficiency may be less likely to miss weekly somatrogon injections.  ○ This is because weekly somatrogon injections were less of a burden and were less likely to interfere with daily activities compared with daily somatropin injections. The purpose of this plain language summary is to help you to understand the findings from recent research. •  Somatrogon is used to treat the condition under study that is discussed in this summary. Approval varies by country; please check with your local provider for more details. • The results of this study may differ from those of other studies. Health professionals should make treatment decisions based on all available evidence and not on the results of a single study. This original scientific article on which this summary is based was published in the Journal of the Endocrine Society and can be accessed for free at: https://academic.oup.com/jes/article/6/10/bvac117/6695276. The details of the original article are as follows: Aristides K. Maniatis, Mauri Carakushansky, Sonya Galcheva, Gnanagurudasan Prakasam, Larry A. Fox, Adriana Dankovcikova, Jane Loftus, Andrew A. Palladino, Maria de los Angeles Resa, Carrie Turich Taylor, Mehul T. Dattani, Jan Lebl . Treatment burden of weekly somatrogon versus daily somatropin in children with growth hormone deficiency: a randomized study. J Endocr Soc 2022; 6(10): bvac117. DOI: 10.1210/jendso/bvac117., (© The Author(s), 2024.)

Context: Familial tall stature (FTS) is considered to be a benign variant of growth with a presumed polygenic etiology. However, monogenic disorders with possible associated pathological features could also be hidden under the FTS phenotype., Objective: To elucidate the genetic etiology in families with FTS and to describe their phenotype in detail., Methods: Children with FTS (the life-maximum height in both the child and his/her taller parent > 2 SD for age and sex) referred to the Endocrinology center of Motol University Hospital were enrolled into the study. Their DNA was examined cytogenetically and via a next-generation sequencing panel of 786 genes associated with growth. The genetic results were evaluated by the American College of Molecular Genetics and Genomics guidelines. All of the participants underwent standard endocrinological examination followed by specialized anthropometric evaluation., Results: In total, 34 children (19 girls) with FTS were enrolled in the study. Their median height and their taller parent's height were 3.1 SD and 2.5 SD, respectively. The genetic cause of FTS was elucidated in 11/34 (32.4%) children (47,XXX and 47,XYY karyotypes, SHOX duplication, and causative variants in NSD1 [in 2], SUZ12 [in 2], FGFR3, CHD8, GPC3, and PPP2R5D genes). Ten children had absent syndromic signs and 24 had dysmorphic features., Conclusion: Monogenic (and cytogenetic) etiology of FTS can be found among children with FTS. Genetic examination should be considered in all children with FTS regardless of the presence of dysmorphic features., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Because the causes of combined pituitary hormone deficiency (CPHD) are complex, the etiology of congenital CPHD remains unknown in most cases. The aim of the study was to identify the genetic etiology of CPHD in a well-defined single-center cohort. In total, 34 children (12 girls) with congenital CPHD (growth hormone (GH) deficiency and impaired secretion of at least one other pituitary hormone) treated with GH in our center were enrolled in the study. Their median age was 11.2 years, pre-treatment height was -3.2 s.d., and maximal stimulated GH was 1.4 ug/L. Of them, 30 had central adrenal insufficiency, 27 had central hypothyroidism, ten had hypogonadotropic hypogonadism, and three had central diabetes insipidus. Twenty-six children had a midline defect on MRI. Children with clinical suspicion of a specific genetic disorder underwent genetic examination of the gene(s) of interest via Sanger sequencing or array comparative genomic hybridization. Children without a detected causal variant after the first-tier testing or with no suspicion of a specific genetic disorder were subsequently examined using next-generation sequencing growth panel. Variants were evaluated by the American College of Medical Genetics standards. Genetic etiology was confirmed in 7/34 (21%) children. Chromosomal aberrations were found in one child (14q microdeletion involving the OTX2 gene). The remaining 6 children had causative genetic variants in the GLI2, PROP1, POU1F1, TBX3, PMM2, and GNAO1 genes, respectively. We elucidated the cause of CPHD in a fifth of the patients. Moreover, our study supports the PMM2 gene as a candidate gene for CPHD and suggests pathogenic variants in the GNAO1 gene as a potential novel genetic cause of CPHD.

Competing Interests: The authors declare that they have no conflict of interest.

Given a proper, rational map of balls, D'Angelo and Xiao introduced five natural groups encoding properties of the map. We study these groups using a recently discovered normal form for rational maps of balls. Using this normal form, we also provide several new groups associated to the map., Competing Interests: Conflict of interestThe authors have no Conflict of interest relevant to this paper., (© The Author(s) 2024.)

Aims/hypothesis: Monogenic diabetes is estimated to account for 1-6% of paediatric diabetes cases in primarily non-consanguineous populations, while the incidence and genetic spectrum in consanguineous regions are insufficiently defined. In this single-centre study we aimed to evaluate diabetes subtypes, obtain the consanguinity rate and study the genetic background of individuals with syndromic and neonatal diabetes in a population with a high rate of consanguinity., Methods: Data collection was carried out cross-sectionally in November 2021 at the paediatric diabetic clinic, Dr Jamal Ahmad Rashed Hospital, in Sulaimani, Kurdistan, Iraq. At the time of data collection, 754 individuals with diabetes (381 boys) aged up to 16 years were registered. Relevant participant data was obtained from patient files. Consanguinity status was known in 735 (97.5%) participants. Furthermore, 12 families of children with neonatal diabetes and seven families of children with syndromic diabetes consented to genetic testing by next-generation sequencing. Prioritised variants were evaluated using the American College of Medical Genetics and Genomics guidelines and confirmed by Sanger sequencing., Results: A total of 269 of 735 participants (36.5%) with known consanguinity status were offspring of consanguineous families. An overwhelming majority of participants (714/754, 94.7%) had clinically defined type 1 diabetes (35% of them were born to consanguineous parents), whereas only eight (1.1%) had type 2 diabetes (38% consanguineous). Fourteen (1.9%) had neonatal diabetes (50% consanguineous), seven (0.9%) had syndromic diabetes (100% consanguineous) and 11 (1.5%) had clinically defined MODY (18% consanguineous). We found that consanguinity was significantly associated with syndromic diabetes (p=0.0023) but not with any other diabetes subtype. The genetic cause was elucidated in ten of 12 participants with neonatal diabetes who consented to genetic testing (homozygous variants in GLIS3 [sibling pair], PTF1A and ZNF808 and heterozygous variants in ABCC8 and INS) and four of seven participants with syndromic diabetes (homozygous variants in INSR, SLC29A3 and WFS1 [sibling pair]). In addition, a participant referred as syndromic diabetes was diagnosed with mucolipidosis gamma and probably has type 2 diabetes., Conclusions/interpretation: This unique single-centre study confirms that, even in a highly consanguineous population, clinically defined type 1 diabetes is the prevailing paediatric diabetes subtype. Furthermore, a pathogenic cause of monogenic diabetes was identified in 83% of tested participants with neonatal diabetes and 57% of participants with syndromic diabetes, with most variants being homozygous. Causative genes in our consanguineous participants were markedly different from genes reported from non-consanguineous populations and also from those reported in other consanguineous populations. To correctly diagnose syndromic diabetes in consanguineous populations, it may be necessary to re-evaluate diagnostic criteria and include additional phenotypic features such as short stature and hepatosplenomegaly., (© 2023. The Author(s).)

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 &lt;-2 SD for gestational age and life-minimum height &lt;-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.)

Background: The thalidomide disaster resulted in tremendous congenital malformations in more than 10,000 children in the late 1950s and early 1960s., Summary: Although numerous putative mechanisms were proposed to explain thalidomide teratogenicity, it was confirmed only recently that thalidomide, rather its derivative 5-hydroxythalidomide (5HT) in a complex with the cereblon protein, interferes with early embryonic transcriptional regulation. 5HT induces selective degradation of SALL4, a principal transcriptional factor of early embryogenesis. Genetic syndromes caused by pathogenic variants of the SALL4 gene phenocopy thalidomide embryopathy with congenital malformations ranging from phocomelia, reduced radial ray, to defects of the heart, kidneys, ear, eye, and possibly cerebral midline and pituitary. SALL4 interacts with TBX5 and a handful of other transcriptional regulators and downregulates the Sonic hedgehog signaling pathway. Cranial midline defects, microcephaly, and short stature due to growth hormone deficiency have been occasionally reported in children carrying SALL4 pathogenic variants associated with generalized stunting of growth rather than just the loss of height attributable to the shortening of leg bones in many children with thalidomide embryopathy., Key Messages: Thus, SALL4 joins the candidate gene list for monogenic syndromic pituitary insufficiency. In this review, we summarize the journey from the thalidomide disaster through the functions of the SALL4 gene to its link to the hormonal regulation of growth., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

Familial short stature (FSS) describes vertically transmitted growth disorders. Traditionally, polygenic inheritance is presumed, but monogenic inheritance seems to occur more frequently than expected. Clinical predictors of monogenic FSS have not been elucidated. The aim of the study was to identify the monogenic etiology and its clinical predictors in FSS children. Of 747 patients treated with growth hormone (GH) in our center, 95 with FSS met the inclusion criteria (pretreatment height ≤-2 SD in child and his/her shorter parent); secondary short stature and Turner/Prader-Willi syndrome were excluded criteria. Genetic etiology was known in 11/95 children before the study, remaining 84 were examined by next-generation sequencing. The results were evaluated by American College of Medical Genetics and Genomics (ACMG) guidelines. Nonparametric tests evaluated differences between monogenic and non-monogenic FSS, an ROC curve estimated quantitative cutoffs for the predictors. Monogenic FSS was confirmed in 36/95 (38%) children. Of these, 29 (81%) carried a causative genetic variant affecting the growth plate, 4 (11%) a variant affecting GH-insulin-like growth factor 1 (IGF1) axis and 3 (8%) a variant in miscellaneous genes. Lower shorter parent's height (P = 0.015) and less delayed bone age (BA) before GH treatment (P = 0.026) predicted monogenic FSS. In children with BA delayed less than 0.4 years and with shorter parent's heights ≤-2.4 SD, monogenic FSS was revealed in 13/16 (81%) cases. To conclude, in FSS children treated with GH, a monogenic etiology is frequent, and gene variants affecting the growth plate are the most common. Shorter parent's height and BA are clinical predictors of monogenic FSS.