Haemochromatosis in children: A national retrospective cohort promoted by the A.I.E.O.P. (Associazione Italiana Emato-Oncologia Pediatrica) study group.

Haemochromatosis (HC) encompasses a range of genetic disorders. HFE-HC is by far the most common in adults, while non-HFE types are rare due to mutations of HJV, HAMP, TFR2 and gain-of-function mutations of SLC40A1. HC is often unknown to paediatricians as it is usually asymptomatic in childhood. We report clinical and biochemical data from 24 paediatric cases of HC (10 cases of HFE-, 5 TFR2-, 9 HJV-HC), with a median follow-up of 9.6 years. Unlike in the adult population, non-HFE-HC constitutes 58% (14/24) of the population in our series. Transferrin saturation was significantly higher in TFR2- and HJV-HC compared to HFE-HC, and serum ferritin and LIC were higher in HJV-HC compared to TFR2- and HFE-HC. Most HFE-HC subjects had relatively low ferritin and LIC at the time of diagnosis, so therapy could be postponed for most of them after the age of 18. Our results confirm that HJV-HC is a severe form already in childhood, emphasizing the importance of early diagnosis and treatment to avoid the development of organ damage and reduce morbidity and mortality. Although phlebotomies were tolerated by most patients, oral iron chelators could be a valid option in early-onset HC.

Machine learning streamlines the morphometric characterization and multi-class segmentation of nuclei in different follicular thyroid lesions: everything in a NUTSHELL.

The diagnostic assessment of thyroid nodules is hampered by the persistence of uncertainty in borderline cases, and further complicated by the inclusion of non-invasive follicular tumor with papillary-like nuclear features (NIFTP) as a less aggressive alternative to papillary thyroid carcinoma (PTC). In this setting, computational methods might facilitate the diagnostic process by unmasking key nuclear characteristics of NIFTPs. The main aims of this work were to (1) identify morphometric features of NIFTP and PTC that are interpretable for the human eye, and (2) develop a deep learning model for multi-class segmentation as a support tool to reduce diagnostic variability. Our findings confirmed that nuclei in NIFTP and PTC share multiple characteristics, setting them apart from hyperplastic nodules (HP). The morphometric analysis identified 15 features that can be translated into nuclear alterations readily understandable by pathologists, such as a remarkable inter-nuclear homogeneity for HP in contrast to a major complexity in the chromatin texture of NIFTP, and to the peculiar pattern of nuclear texture variability of PTC. A few NIFTP cases with available NGS data were also analyzed to initially explore the impact of RAS-related mutations on nuclear morphometry. Finally, a pixel-based deep learning model was trained and tested on whole slide images (WSIs) of NIFTP, PTC, and HP cases. The model, named NUTSHELL (NUclei from Thyroid tumors Segmentation to Highlight Encapsulated Low-malignant Lesions), successfully detected and classified the majority of nuclei in all WSIs' tiles, showing comparable results with already well-established pathology nuclear scores. NUTSHELL provides an immediate overview of NIFTP areas and can be used to detect microfoci of PTC within extensive glandular samples or identify lymph node metastases. NUTSHELL can be run inside WSInfer with an easy rendering in QuPath, thus facilitating the democratization of digital pathology.

A DNA damage response-like phenotype defines a third of colon cancers at onset.

Colon adenocarcinoma (COAD) has a limited range of diversified, personalized therapeutic opportunities, besides DNA hypermutating cases; thus, both new targets or broadening existing strategies for personalized intervention are of interest. Routinely processed material from 246 untreated COADs with clinical follow-up was probed for evidence of DNA damage response (DDR), that is, the gathering of DDR-associated molecules at discrete nuclear spots, by multiplex immunofluorescence and immunohistochemical staining for DDR complex proteins (γH2AX, pCHK2, and pNBS1). We also tested the cases for type I interferon response, T-lymphocyte infiltration (TILs), and mutation mismatch repair defects (MMRd), known to be associated with defects of DNA repair. FISH analysis for chromosome 20q copy number variations was obtained. A total of 33.7% of COAD display a coordinated DDR on quiescent, non-senescent, non-apoptotic glands, irrespective of TP53 status, chromosome 20q abnormalities, and type I IFN response. Clinicopathological parameters did not differentiate DDR+ cases from the other cases. TILs were equally present in DDR and non-DDR cases. DDR+ MMRd cases were preferentially retaining wild-type MLH1. The outcome after 5FU-based chemotherapy was not different in the two groups. DDR+ COAD represents a subgroup not aligned with known diagnostic, prognostic, or therapeutic categories, with potential new targeted treatment opportunities, exploiting the DNA damage repair pathways.

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology.

INTRODUCTION: Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions. AREAS COVERED: This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions. EXPERT COMMENTARY: Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

Plasma Proteomic Variables Related to COVID-19 Severity: An Untargeted nLC-MS/MS Investigation.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection leads to a wide range of clinical manifestations and determines the need for personalized and precision medicine. To better understand the biological determinants of this heterogeneity, we explored the plasma proteome of 43 COVID-19 patients with different outcomes by an untargeted liquid chromatography-mass spectrometry approach. The comparison between asymptomatic or pauci-symptomatic subjects (MILDs), and hospitalised patients in need of oxygen support therapy (SEVEREs) highlighted 29 proteins emerged as differentially expressed: 12 overexpressed in MILDs and 17 in SEVEREs. Moreover, a supervised analysis based on a decision-tree recognised three proteins (Fetuin-A, Ig lambda-2chain-C-region, Vitronectin) that are able to robustly discriminate between the two classes independently from the infection stage. In silico functional annotation of the 29 deregulated proteins pinpointed several functions possibly related to the severity; no pathway was associated exclusively to MILDs, while several only to SEVEREs, and some associated to both MILDs and SEVEREs; SARS-CoV-2 signalling pathway was significantly enriched by proteins up-expressed in SEVEREs (SAA1/2, CRP, HP, LRG1) and in MILDs (GSN, HRG). In conclusion, our analysis could provide key information for 'proteomically' defining possible upstream mechanisms and mediators triggering or limiting the domino effect of the immune-related response and characterizing severe exacerbations.

Towards the Definition of the Molecular Hallmarks of Idiopathic Membranous Nephropathy in Serum Proteome: A DIA-PASEF Approach.

Idiopathic membranous nephropathy (IMN) is a pathologically defined disorder of the glomerulus, primarily responsible for nephrotic syndromes (NS) in nondiabetic adults. The underlying molecular mechanisms are still not completely clarified. To explore possible molecular and functional signatures, an optimised mass spectrometry (MS) method based on next-generation data-independent acquisition combined with ion-mobility was applied to serum of patients affected by IMN (n = 15) or by other glomerulopathies (PN) (n = 15). The statistical comparison highlighted a panel of 57 de-regulated proteins with a significant increase in lipoprotein-related proteins (APOC1, APOB, APOA1, APOL1 and LCAT) and a substantial quantitative alteration of key serpins (including A4, D1, A7, A6, F2, F1 and 1) possibly associated with IMN or NS and podocyte stress. A critical dysregulation in metabolisms of lipids (e.g., VLDL assembly and clearance) likely to be related to known hyperlipidemia in IMN, along with involvement of non-classical complement pathways and a putative enrolment of ficolin-2 in sustaining the activation of the lectin-mediated complement system have been pinpointed. Moreover, mannose receptor CD206 (MRC1-down in IMN) and biotinidase (BTD-up in IMN) are able alone to accurately distinguish IMN vs. PN. To conclude, our work provides key proteomic insights into the IMN complexity, opening the way to an efficient stratification of MN patients.

Spatially Resolved Molecular Approaches for the Characterisation of Non-Invasive Follicular Tumours with Papillary-like Features (NIFTPs).

Noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) are low-risk thyroid lesions most often characterised by RAS-type mutations. The histological diagnosis may be challenging, and even immunohistochemistry and molecular approaches have not yet provided conclusive solutions. This study characterises a set of NIFTPs by Matrix-Assisted Laser Desorption/Ionisation (MALDI)-Mass Spectrometry Imaging (MSI) to highlight the proteomic signatures capable of overcoming histological challenges. Archived formalin-fixed paraffin-embedded samples from 10 NIFTPs (n = 6 RAS-mutated and n = 4 RAS-wild type) were trypsin-digested and analysed by MALDI-MSI, comparing their profiles to normal tissue and synchronous benign nodules. This allowed the definition of a four-peptide signature able to distinguish RAS-mutant from wild-type cases, the latter showing proteomic similarities to hyperplastic nodules. Moreover, among the differentially expressed signals, Peptidylprolyl Isomerase A (PPIA, 1505.8 m/z), which has already demonstrated a role in the development of cancer, was found overexpressed in NIFTP RAS-mutated nodules compared to wild-type lesions. These results underlined that high-throughput proteomic approaches may add a further level of biological comprehension for NIFTPs. In the future, thanks to the powerful single-cell detail achieved by new instruments, the complementary NGS-MALDI imaging sequence might be the correct methodological approach to confirm that the current NIFTP definition encompasses heterogeneous lesions that must be further characterised.

Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section.

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Dissecting the histological features of lupus nephritis highlights new common patterns of injury in class III/IV.

OBJECTIVE: The International Society of Nephrology/Renal Pathology Society classification is the gold standard for the characterisation of lupus nephritis (LN) on renal biopsy, with therapeutic repercussions. Its recent revision simplified the current class subdivisions, eliminating the S/G forms of class IV, although data on a possible pathogenetic/clinical value of this subdivision are still contradictory. METHODS: 353 renal biopsies from Belimumab International Study in LN were assessed through central pathology review. Univariate logistic models and a decision tree were performed on 314 adequate biopsies to evaluate the impact of histological features on focal/diffuse classes. Removing class I/II (n=6) and 'pure' class V (n=34), principal component analysis (PCA) and heatmap were used to explore similarities among III, IVS and IVG biopsies either incorporating or not the mixed classes (+V, n=274). Finally, a method aimed at partitioning the cases into k clusters based on their similarity (KMeans), was used to study features from the cohort of 'pure' class III/IVS/IVG cases (n=214) to determine alternative subdivisions based on phenotypic data. RESULTS: Segmental endocapillary hypercellularity (EH) was prevalent in class III, global EH, wire loops, hyaline thrombi and double contours were hallmarks of class IVG, with IVS cases showing intermediate characteristics. Heatmap and PCA confirmed the segregation of these features among classes, showing better segregation for focal/diffuse LN as compared with the mixed classes (+V). KMeans revealed the presence of two main clusters, membranoproliferative-like (n=83) or vasculitis-like (n=131). CONCLUSIONS: This study reveals new phenotypic forms of LN surpassing the traditional classes as determined by the current classification. Future validation and confirmation are required to confirm these findings.

FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks.

Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can be tested by means of targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the one hand, detailed mechanistic models can involve hundreds or thousands of molecular species and their intermediate complexes, as well as hundreds or thousands of chemical reactions, a situation generally occurring in rule-based modeling. On the other hand, the computational analysis of a model typically requires the execution of a large number of simulations for its calibration, or to test the effect of perturbations. As a consequence, the computational capabilities of modern Central Processing Units can be easily overtaken, possibly making the modeling of biochemical networks a worthless or ineffective effort. To the aim of overcoming the limitations of the current state-of-the-art simulation approaches, we present in this paper FiCoS, a novel "black-box" deterministic simulator that effectively realizes both a fine-grained and a coarse-grained parallelization on Graphics Processing Units. In particular, FiCoS exploits two different integration methods, namely, the Dormand-Prince and the Radau IIA, to efficiently solve both non-stiff and stiff systems of coupled Ordinary Differential Equations. We tested the performance of FiCoS against different deterministic simulators, by considering models of increasing size and by running analyses with increasing computational demands. FiCoS was able to dramatically speedup the computations up to 855×, showing to be a promising solution for the simulation and analysis of large-scale models of complex biological processes.

Cytomolecular Classification of Thyroid Nodules Using Fine-Needle Washes Aspiration Biopsies.

Fine-needle aspiration biopsies (FNA) represent the gold standard to exclude the malignant nature of thyroid nodules. After cytomorphology, 20-30% of cases are deemed "indeterminate for malignancy" and undergo surgery. However, after thyroidectomy, 70-80% of these nodules are benign. The identification of tools for improving FNA's diagnostic performances is explored by matrix-assisted laser-desorption ionization mass spectrometry imaging (MALDI-MSI). A clinical study was conducted in order to build a classification model for the characterization of thyroid nodules on a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/malignant cells. The model had optimal performances in the internal validation set (n = 70), with 100.0% (95% CI = 83.2-100.0%) sensitivity and 96.0% (95% CI = 86.3-99.5%) specificity. The external validation (n = 170) showed a specificity of 82.9% (95% CI = 74.3-89.5%) and a sensitivity of 43.1% (95% CI = 30.9-56.0%). The performance of the model was hampered in the presence of poor and/or noisy spectra. Consequently, restricting the evaluation to the subset of FNAs with adequate cellularity, sensitivity improved up to 76.5% (95% CI = 58.8-89.3). Results also suggest the putative role of MALDI-MSI in routine clinical triage, with a three levels diagnostic classification that accounts for an indeterminate gray zone of nodules requiring a strict follow-up.

Definition of IgG Subclass-Specific Glycopatterns in Idiopathic Membranous Nephropathy: Aberrant IgG Glycoforms in Blood.

The podocyte injury, and consequent proteinuria, that characterize the pathology of idiopathic membranous nephropathy (IMN) is mediated by an autoimmune reaction against podocyte antigens. In particular, the activation of pathways leading to abundant renal deposits of complement is likely to involve the binding of mannose-binding lectin (MBL) to aberrant glycans on immunoglobulins. To obtain a landscape of circulatory IgG Fc glycosylation characterizing this disease, we conducted a systematic N-glycan profiling study of IgG1, 2, and 4 by mass spectrometry. The cohort included 57 IMN patients, a pathological control group with nephrotic syndrome (PN) (n = 20), and 88 healthy control subjects. The effect of sex and age was assessed in all groups and controlled by rigorous matching. Several IgG Fc glycan traits were found to be associated with IMN. Interestingly, among them, only IgG4-related results were specific for IMN and not for PN. Hypo-galactosylation of IgG4, already shown for IMN, was observed to occur in the absence of core fucose, in line with a probable increase of pro-inflammatory IgG. In addition, elevated levels of fucosylated IgG4, along with low levels of hybrid-type glycans, were detected. Some of these IgG4 alterations are likely to be more pronounced in high PLA2R (phospholipase A2 receptor) patients. IgG Fc glycosylation patterns associated with IMN warrant further studies of their role in disease mechanisms and may eventually enrich the diagnostic spectrum regarding patient stratification.

Ex vivo thyroid fine needle aspirations as an alternative for MALDI-MSI proteomic investigation: intra-patient comparison.

Fine needle aspiration (FNA) is the reference standard for the diagnosis of thyroid nodules. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been successfully used to discriminate the proteomic profiles of benign and malignant thyroid FNAs within the scope of providing support to pathologists for the classification of morphologically borderline cases. However, real FNAs provide a limited amount of material due to sample collection restrictions. Ex vivo FNAs could represent a valuable alternative, increasing sample size and the power of statistical conclusions. In this study, we compared the real and ex vivo MALDI-MSI proteomic profiles, extracted from thyrocyte containing regions of interest, of 13 patients in order to verify their similarity. Statistical analysis demonstrated the mass spectra similarity of the proteomic profiles by performing intra-patient comparison, using statistical similarity systems. In conclusion, these results show that post-surgical FNAs represent a possible alternative source of material for MALDI-MSI proteomic investigations in instances where pre-surgical samples are unavailable or the number of cells is scarce.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction.

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The 'omics' techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

The management of haemoglobin interference for the MALDI-MSI proteomics analysis of thyroid fine needle aspiration biopsies.

MALDI-MSI represents an ideal tool to explore the spatial distribution of proteins directly in situ, integrating molecular and cytomorphological information, enabling the discovery of potential diagnostic markers in thyroid cytopathology. However, red cells present in the fine needle aspiration biopsy (FNAB) specimens caused ion suppression of other proteins during the MALDI-MSI analysis due to large amount of haemoglobin. Aim of this study was to set up a sample preparation workflow able to manage this haemoglobin interference. Three protocols were compared using ex vivo cytological samples collected from fresh thyroid nodules of 9 patients who underwent thyroidectomy: (A) conventional air-dried smears, (B) cytological smears immediately fixed in ethanol, and (C) ThinPrep liquid-based preparation. Protocols C and A were also evaluated using real FNABs. Results show that protocol C markedly decreased the amount of haemoglobin, with respect to protocols A and B. Protein profiles obtained with protocols A and B were characterised by high inter-patient variability, probably related to the abundance of the haemoglobin, whereas similar spectra were observed for protocol C, where haemoglobin contents were lower. Our findings suggest protocol C as the sample preparation method for MALDI-MSI analysis. Graphical abstract.

Update on: proteome analysis in thyroid pathology - part II: overview of technical and clinical enhancement of proteomic investigation of the thyroid lesions.

INTRODUCTION: An accurate diagnostic classification of thyroid lesions remains an important clinical aspect that needs to be addressed in order to avoid 'diagnostic' thyroidectomies. Among the several 'omics' techniques, proteomics is playing a pivotal role in the search for diagnostic markers. In recent years, different approaches have been used, taking advantage of the technical improvements related to mass spectrometry that have occurred. Areas covered: The review provides an update of the recent findings in diagnostic classification, in genetic definition and in the investigation of thyroid lesions based on different proteomics approaches and on different type of specimens: cytological, surgical and biofluid samples. A brief section will discuss how these findings can be integrated with those obtained by metabolomics investigations. Expert commentary: Among the several proteomics approaches able to deepen our knowledge of the molecular alterations of the different thyroid lesions, MALDI-MSI is strongly emerging above all. In fact, MS-imaging has also been demonstrated to be capable of distinguishing thyroid lesions, based on their different molecular signatures, using cytological specimens. The possibility to use the material obtained by the fine needle aspiration makes MALDI-MSI a highly promising technology that could be implemented into the clinical and pathological units.

Endocrine, auxological and metabolic profile in children and adolescents with Down syndrome: from infancy to the first steps into adult life.

Down syndrome (DS) is the most common chromosomal disorder worldwide. Along with intellectual disability, endocrine disorders represent a remarkable share of the morbidities experienced by children, adolescents and young adults with DS. Auxological parameters are plotted on syndrome-specific charts, as growth rates are reduced compared to healthy age- and gender-matched peers. Furthermore, children with DS are at increased risk for thyroid dysfunctions, diabetes mellitus, osteopenia and obesity compared to general population. Additionally, male individuals with DS often show infertility, while women tend to experience menopause at an overall younger age than healthy controls. Given the recent outstanding improvements in the care of severe DS-related comorbidities, infant mortality has dramatically decreased, with a current average life expectancy exceeding 60 years. Accordingly, the awareness of the specificities of DS in this field is pivotal to timely detect endocrine dysfunctions and to undertake a prompt dedicated treatment. Notably, best practices for the screening and monitoring of pediatric endocrine disorders in DS are still controversial. In addition, specific guidelines for the management of metabolic issues along the challenging period of transitioning from pediatric to adult health care are lacking. By performing a review of published literature, we highlighted the issues specifically involving children and adolescent with DS, aiming at providing clinicians with a detailed up-to-date overview of the endocrine, metabolic and auxological disorders in this selected population, with an additional focus on the management of patients in the critical phase of the transitioning from childhood to adult care.

Reference Values of Ceruloplasmin across the Adult Age Range in a Large Italian Healthy Population.

BACKGROUND: Ceruloplasmin (Cp) is the most important serum copper transport protein playing a key role in the binding of iron to transferrin. It is a positive acute-phase response protein and the first-level diagnostic marker for Wilson disease and aceruloplasminemia. However, standardization of Cp measurement has not been successful, and assay specific reference levels of Cp are required. METHODS: From May 2019 to July 2022, we enrolled 1706 consecutive healthy Italian blood donors (1285 men and 421 women, 18 to 65 years) to identify the reference intervals of serum Cp through quantile regression and evaluate the relationship of Cp with age, sex, iron, and metabolic status through linear regression. RESULTS: We found that mean serum Cp was influenced by sex and slightly by age. The lower reference Cp value rose slightly with increasing age in both men and women. The upper reference value increased, reaching a plateau of about 25 mg/dL around 25 years in men, while in women it initially increased to around 45 mg/dL in young adults to fall sharply below 30 mg/dL for adults after their fifties. CONCLUSIONS: We showed that the normal reference curves of serum Cp vary according to sex in a large population of healthy adults. While the lower reference values did not appear to be influenced by age and sex, the upper ones differed according to sex and age showing a particularly high variability in women, possibly reflecting different hormonal status.

Pelvic ultrasound and pubertal attainment in girls with sexual precocity: the pivotal role of uterine volume in predicting the timing of menarche.

Introduction: Among girls assessed for pubertal precocity, pelvic ultrasound (pUS) may represent a pivotal tool to predict the time expected to elapse between sonographic assessment and the onset of menarche (TUS-M). Accordingly, the present analysis is meant to define the statistical relationship between sonographic parameters and TUS-M, in order to identify the most reliable predictor of the timing of menarche. Methods: Retrospective, multicenter analysis. Girls assessed for sexual precocity and showing sonographic and clinical findings consistent with pubertal onset upon referral were considered eligible. Patients treated with GnRH analogues were excluded and only those who had subsequently achieved complete and spontaneous pubertal attainment and for whom the exact date of menarche was available were included. Overall, we enrolled 184 girls from five tertiary care Italian Centers. Results: The time elapsed (months) between baseline endocrine assessment and spontaneous achievement of menarche showed a negative statistically significant correlation (p<0.0001) with LH (r:-0.61), FSH (r:-0.59), estradiol (r:-0.52) and stimulated LH values (r:-0.58). Among pUS parameters, ovarian volume (r:-0.17 left, -0.30 right) and uterine body-to-cervix ratio (r:-0.18) poorly correlated with TUS-M, while uterine diameters (r:-0.61 longitudinal, -0.64 anteroposterior) and volume (r:-0.70) achieved a highly statistical significance (p<0.0001). Uterine volume (UV) showed a negative logarithmic relationship with TUS-M and represented the most reliable predictor of the timing of menarche in uni- and multivariable analyses (p <0.001). ROC analyses identified the UV thresholds that best predict the onset of menarche within 18, 12 and 6 months, respectively: 3.76, 6.02 and 8.80 ml. Conclusion: The logarithm of UV shows the best statistical performance in predicting the timing of menarche in girls assessed for pubertal precocity. Accordingly, we developed a user-friendly online application that provides clinicians with an estimation of the months expected to elapse before menarche, based on the UV recorded upon pUS.