Towards genomic-Newborn Screening: Technical feasibility of Exome Sequencing starting from dried blood spots.

Each year thousands of babies are born with rare genetic disorders not identified by current NBS panels, due to programs which are not yet optimal. Next-generation sequencing technologies have the potential to overcome many NBS drawbacks and provide large amounts of molecular data, broadening the number of diseases investigated. Here, we design and set up an NGS-based approach to evaluate the feasibility of NGS from dried blood spot starting from 34 DBSs. After assessing gDNA yield and integrity, libraries were performed using three target enrichment approaches, sequenced on NS500 platform, and analyzed on commercial platform. Specifically, we focus on virtual gene panels related to highly actionable neonatal/pediatric disorders. WES show that amount and quality of DBS-extracted gDNA are suitable for high-throughput sequencing. We obtain 500-1500 ng for each specimen, 1.7-1.8 260/280 wavelength, and DIN of 7 resulting DNA integrity, on par with traditional venous blood collection. A high read depth with 94.3% coverage uniformity is achieved for all samples. Data results on mean coverage are comparable among the different workflows tested and demonstrate that DBS from newborn collected at birth is a suitable material for the developing of gNBS programs.

Foreign body ingestion in children: Definition of a nomogram to predict surgical or endoscopic intervention.

BACKGROUND AND AIMS: Foreign body ingestion (FBI) in children requires early identification to prevent adverse outcomes and may necessitate endoscopic or surgical intervention. This study aims to develop a nomogram that identifies children who require urgent surgical or endoscopic intervention by using the patient's medical history and clinical parameters collected at admission. METHODS: This study is a retrospective review (01/2015-12/2020) of a multicenter case series of children admitted for FBI. Data from 5864 records from 24 hospitals in Italy were analyzed. Logistic regression models were used to establish the probability of requiring surgical or endoscopic intervention based on patient history and clinical characteristics. The nomogram representing the results from the multivariable model was reported to examine the propensity for surgery/endoscopy. RESULTS: The study identified a significant association between intervention and various factors, including type of foreign body (blunt: reference category, disk battery (odds ratio OR:4.89), food bolus (OR:1.88), magnets (OR:2.61), sharp-pointed (OR:1.65), unknown (OR:1.02)), pre-existing diseases or conditions (OR 3.42), drooling (OR 10.91), dysphagia (OR 5.58), vomiting (OR 3.30), retrosternal pain (OR 5.59), abdominal pain (OR 1.58), hematemesis (OR 2.82), food refusal/poor feeding (OR 2.99), and unexplained crying (OR 2.01). The multivariable regression model showed good calibration and discrimination ability, with an area under the ROC curve of 0.77. CONCLUSIONS: This study developed the first nomogram to predict the probability of the need for surgical or endoscopic intervention in children with FBI, based on the information collected at admission. The nomogram will aid clinicians in identifying children who require early intervention to prevent adverse outcomes.

Environmental and Lifestyle Cancer Risk Factors: Shaping Extracellular Vesicle OncomiRs and Paving the Path to Cancer Development.

Intercellular communication has been transformed by the discovery of extracellular vesicles (EVs) and their cargo, including microRNAs (miRNAs), which play crucial roles in intercellular signaling. These EVs were previously disregarded as cellular debris but are now recognized as vital mediators of biological information transfer between cells. Furthermore, they respond not only to internal stimuli but also to environmental and lifestyle factors. Identifying EV-borne oncomiRs, a subset of miRNAs implicated in cancer development, could revolutionize our understanding of how environmental and lifestyle exposures contribute to oncogenesis. To investigate this, we studied the plasma levels of EV-borne oncomiRs in a population of 673 women and 238 men with a body mass index > 25 kg/m2 (SPHERE population). The top fifty oncomiRs associated with the three most common cancers in women (breast, colorectal, and lung carcinomas) and men (lung, prostate, and colorectal carcinomas) were selected from the OncomiR database. Only oncomiRs expressed in more than 20% of the population were considered for statistical analysis. Using a Multivariate Adaptive Regression Splines (MARS) model, we explored the interactions between environmental/lifestyle exposures and EV oncomiRs to develop optimized predictor combinations for each EV oncomiR. This innovative approach allowed us to better understand miRNA regulation in response to multiple environmental and lifestyle influences. By uncovering non-linear relationships among variables, we gained valuable insights into the complexity of miRNA regulatory networks. Ultimately, this research paves the way for comprehensive exposome studies in the future.

Variance analysis of dynamic light scattering data.

We propose a novel method alternative to the classical Dynamic Light Scattering (DLS) technique for performing particle sizing on diluted dispersions of nanosized particles. Differently from DLS, which works by determining the correlation function of the intensity scattered by the sample, our method does not require the use of a correlator because it exploits the behavior of the variance (VAR) of the scattered signal as a function of the sampling time Δt. By using a wide range of sampling times Δtmin ≪ τc ≪ Δtmax, it is possible to recover the correlation time τc of the scattered field and, in turn (by using the Stokes-Einstein relation), the hydrodynamic diameter of the particles. The new method is endowed with an analytical expression for the error bars associated with to the VAR data. Extensive computer simulations carried out on monodisperse and narrow polydisperse samples show that VAR and DLS techniques provide fairly similar performances. The same results were obtained on calibrated polystyrene spheres and fluorescent perovskite nanoparticles tested with different setups and detection schemes.

Individual risk prediction of high grade prostate cancer based on the combination between total prostate-specific antigen (PSA) and free to total PSA ratio.

OBJECTIVES: Clinical practice guidelines endorse the stratification of prostate cancer (PCa) risk according to individual total prostate-specific antigen (tPSA) values and age to enhance the individual risk-benefit ratio. We defined two nomograms to predict the individual risk of high and low grade PCa by combining the assay of tPSA and %free/tPSA (%f/tPSA) in patients with a pre-biopsy tPSA between 2 and 10 µg/L. METHODS: The study cohort consisted of 662 patients that had fPSA, tPSA, and a biopsy performed (41.3% with a final diagnosis of PCa). Logistic regression including age, tPSA and %f/tPSA was used to model the probability of having high or low grade cancer by defining 3 outcome levels: no PCa, low grade (International Society of Urological Pathology grade, ISUP<3) and high grade PCa (ISUP≥3). RESULTS: The nomogram identifying patients with: (a) high vs. those with low grade PCa and without the disease showed a good discriminating capability (∼80%), but the calibration showed a risk of underestimation for predictive probabilities >30% (a considerable critical threshold of risk), (b) ISUP<3 vs. those without the disease showed a discriminating capability of 63% and overestimates predictive probabilities >50%. In ISUP 5 a possible loss of PSA immunoreactivity has been observed. CONCLUSIONS: The estimated risk of high or low grade PCa by the nomograms may be of aid in the decision-making process, in particular in the case of critical comorbidities and when the digital rectal examinations are inconclusive. The improved characterization of the risk of ISUP≥3 might enhance the use for magnetic resonance imaging in this setting.

Beyond Traditional Morphological Characterization of Lung Neuroendocrine Neoplasms: In Silico Study of Next-Generation Sequencing Mutations Analysis across the Four World Health Organization Defined Groups.

Lung neuroendocrine neoplasms (LNENs) represent a rare and heterogeneous population of lung tumors. LNENs incidence rate has increased dramatically over the past 30 years. The current World Health Organization LNENs classification (WHO 2015), distinguished four LNENs prognostic categories, according to their morphology, necrosis amount and mitotic count: typical carcinoid (TC), atypical-carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC) and small cell lung cancer (SCLC). At present, due to their rarity and biological heterogeneity there is still no consensus on the best therapeutic approach. Next-generation-sequencing analysis showed that WHO 2015 LNENs classes, could be characterized also by specific molecular alterations: frequently mutated genes involving chromatin remodeling and generally characterized by low mutational burden (MB) are frequently detected in both TC and AC; otherwise, TP53 and RB1 tumor suppressor genes alterations and high MB are usually detected in LCNEC and SCLC. We provide an overview concerning gene mutations in each WHO 2015 LNENs class in order to report the current LNENs mutational status as potential tool to better understand their clinical outcome and to drive medical treatment.

Statistical analysis of dynamic light scattering data: revisiting and beyond the Schätzel formulas.

We revisited the classical Schätzel formulas (K. Schätzel, Quantum Optics2, 2871990) of the variance and covariance matrix associated to the normalized auto-correlation function in a Dynamic Light Scattering experiment when the sample is characterized by a single exponential decay function. Although thoroughly discussed by Schätzel who also outlined a correcting procedure, such formulas do not include explicitly the effects of triangular averaging that arise when the sampling time Δt is comparable or larger than the correlation time τc. If these effects are not taken into account, such formulas might be highly inaccurate. In this work we have solved this problem and worked out two exact analytical expressions that generalize the Schätzel formulas for any value of the ratio Δt/τc. By the use of extensive computer simulations we tested the correctness of the new formulas and showed that the variance formula can be exploited also in the case of fairly broad bell-shaped polydisperse samples (polydispersities up to ∼ 50 - 100%) and in connection with single exponential decay cross-correlation functions, provided that the average count rate is computed as the geometrical mean of the average count rates of the two channels. Finally, when tested on calibrated polystyrene particles, the new variance formula is able to reproduce quite accurately the error bars obtained by averaging the experimental data.