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Fetal anomalies, characterized by structural or functional abnormalities occurring during intrauterine life, pose a significant medical challenge, with a notable prevalence, affecting approximately 2–3% of live births and 20% of spontaneous miscarriages. This study aims to identify the genetic cause of ultrasound anomalies through clinical exome sequencing (CES) analysis. The focus is on utilizing CES analysis in a trio setting, involving the fetuses and both parents. To achieve this objective, prenatal trio clinical exome sequencing was conducted in 51 fetuseses exhibiting ultrasound anomalies with previously negative results from chromosomal microarray (CMA) analysis. The study revealed pathogenic variants in 24% of the analyzed cases (12 out of 51). It is worth noting that the findings include de novo variants in 50% of cases and the transmission of causative variants from asymptomatic parents in 50% of cases. Trio clinical exome sequencing stands out as a crucial tool in advancing prenatal diagnostics, surpassing the effectiveness of relying solely on chromosomal microarray analysis. This underscores its potential to become a routine diagnostic standard in prenatal care, particularly for cases involving ultrasound anomalies.

Ciliopathies are rare congenital disorders caused by defects in the structure or function of cilia, which can lead to a wide range of clinical manifestations. Among them, a subset known as skeletal ciliopathies exhibits significant phenotypic overlap and primarily affects skeletal development. This group includes several syndromes with overlapping but distinct clinical features, such as short-rib polydactyly syndrome (SRPS), Jeune asphyxiating thoracic dystrophy (JATD), Mainzer–Saldino syndrome (MZSDS), and cranioectodermal dysplasia (CED), also called Sensenbrenner syndrome. The most characterized features of skeletal ciliopathies are short stature, rhizomelic limb shortening, and thoracic narrowing to varying extents, with JATD presenting the most severe form. Here, we report a fetus with an extension of skeletal ciliopathy phenotype and compound heterozygous variants in the IFT140 gene. The affected fetus had multiple malformations, including increased nuchal transparency (NT), shortened and thick long bones, hypoplastic tibia and fibula, absence of bladder, flat nose, and frontal bossing. Our findings expand the mutation spectrum of IFT140, and the clinical spectrum associated with skeletal ciliopathies, highly relevant in diagnosis prenatal settings.

Abstract Objective Non invasive prenatal testing (NIPT) using cell-free fetal DNA (cffDNA) has been widely accepted in recent years to detect common fetal autosomal chromosome aneuploidies and sex chromosome aneuploidies (SCAs). In this study, the clinical performance of our fetal DNA testing was investigated by analyzing the sex chromosome aneuploidy aberrations among 9985 pregnancies. The study was a retrospective analysis of collected NIPT data from the Ion S5 next-generation sequencing (NGS) platform obtained from Altamedica Medical Centre of Rome. Results NIPT analysis of 9985 pregnancies revealed 31 cases with abnormal SCA results (0.31%). Among the 31 positive NIPT cases, 22 women agreed to undergo fetal karyotyping, whereas 9 refused further analyses. Of the 22 women verified by karyotyping analysis, 77.3% (17/22) were confirmed to be true positive SCAs, whereas 22.7% (5/22) were false positive. Among the true positive cases, 53.0% (9/17) were positive for monosomy X, 17.6% (3/17) were positive for 47, XXX aneuploidy, 23.5% (4/17) were positive for 47, XXY aneuploidy, and 5.9% (1/17) were positive for 47, XYY aneuploidy. In conclusion, the present results confirm that NIPT is a potential method for SCA screening, although this technology needs to be further investigated to improve the test performance.

Abstract The need for timely establishment of a complete diagnostic protocol of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is demanded worldwide. We selected 15 positive novel coronavirus disease 19 (COVID-19) patients with mild or no symptom. Initially, fecal samples were negative in the 67% (10/15) of the cases, while 33% (5/10) of the cases were positive. After serial virus RNA testing, 73% (11/15) of the cases resulted positive to fecal specimens. In particular, 15 days after the first positive respiratory specimens test, 6 fecal specimens became positive for SARS-CoV-2 RNA, while 13 respiratory test returned negative result. In conclusion, qRT-PCR assays of fecal specimens, is an important step to control infection, suggesting that samples remained positive for SARS-CoV-2 RNA longer time then respiratory tract samples. Our results enhance the recent knowledge on this emerging infectious disease and offer suggestions for a more complete diagnostic strategy.

Advanced ovarian cancer is one of the most lethal gynecological tumor, mainly due to late diagnoses and acquired drug resistance. MicroRNAs (miRNAs) are small-non coding RNA acting as tumor suppressor/oncogenes differentially expressed in normal and epithelial ovarian cancer and has been recognized as a new class of tumor early detection biomarkers as they are released in blood fluids since tumor initiation process. Here, we evaluated by droplet digital PCR (ddPCR) circulating miRNAs in serum samples from healthy (N = 105) and untreated ovarian cancer patients (stages I to IV) (N = 72), grouped into a discovery/training and clinical validation set with the goal to identify the best classifier allowing the discrimination between earlier ovarian tumors from health controls women. The selection of 45 candidate miRNAs to be evaluated in the discovery set was based on miRNAs represented in ovarian cancer explorative commercial panels. We found six miRNAs showing increased levels in the blood of early or late-stage ovarian cancer groups compared to healthy controls. The serum levels of miR-320b and miR-141-3p were considered independent markers of malignancy in a multivariate logistic regression analysis. These markers were used to train diagnostic classifiers comprising miRNAs (miR-320b and miR-141-3p) and miRNAs combined with well-established ovarian cancer protein markers (miR-320b, miR-141-3p, CA-125 and HE4). The miRNA-based classifier was able to accurately discriminate early-stage ovarian cancer patients from health-controls in an independent sample set (Sensitivity = 80.0%, Specificity = 70.3%, AUC = 0.789). In addition, the integration of the serum proteins in the model markedly improved the performance (Sensitivity = 88.9%, Specificity = 100%, AUC = 1.000). A cross-study validation was carried out using four data series obtained from Gene Expression Omnibus (GEO), corroborating the performance of the miRNA-based classifier (AUCs ranging from 0.637 to 0.979). The clinical utility of the miRNA model should be validated in a prospective cohort in order to investigate their feasibility as an ovarian cancer early detection tool.