The role of genetic testing in suspected fulminant myocarditis: A case report.

ACM is a rare hereditary heart disease characterized by a progressive fibro-fatty replacement of the myocardium that can affect either the right or the left ventricle or both. It is mainly caused by variants in the desmosome genes with autosomal dominant transmission and incomplete penetrance. The disease shows a wide spectrum of clinical manifestations, including ventricular arrhythmias, HF and myocarditis. The latter is considered a 'hot phase' in the natural history of the disease and must therefore be distinguished from the isolated AM, which is frequently due to viral infections. Our case report is an example of how an AM, as the first manifestation of the disease, helped to reach a diagnosis of ACM through the genetic analysis. In fact, the multi-parametric investigation, which also included CMR and EMB, revealed controversial aspects that led us to perform the genetic test. The latter revealed a heterozygous pathogenic variant in the PKP2 that was considered definitive proof of ACM.

Whole-Exome and Transcriptome Sequencing Expands the Genotype of Majewski Osteodysplastic Primordial Dwarfism Type II.

Microcephalic Osteodysplastic Primordial Dwarfism type II (MOPDII) represents the most common form of primordial dwarfism. MOPD clinical features include severe prenatal and postnatal growth retardation, postnatal severe microcephaly, hypotonia, and an increased risk for cerebrovascular disease and insulin resistance. Autosomal recessive biallelic loss-of-function genomic variants in the centrosomal pericentrin (PCNT) gene on chromosome 21q22 cause MOPDII. Over the past decade, exome sequencing (ES) and massive RNA sequencing have been effectively employed for both the discovery of novel disease genes and to expand the genotypes of well-known diseases. In this paper we report the results both the RNA sequencing and ES of three patients affected by MOPDII with the aim of exploring whether differentially expressed genes and previously uncharacterized gene variants, in addition to PCNT pathogenic variants, could be associated with the complex phenotype of this disease. We discovered a downregulation of key factors involved in growth, such as IGF1R, IGF2R, and RAF1, in all three investigated patients. Moreover, ES identified a shortlist of genes associated with deleterious, rare variants in MOPDII patients. Our results suggest that Next Generation Sequencing (NGS) technologies can be successfully applied for the molecular characterization of the complex genotypic background of MOPDII.

A Novel Nonsense Pathogenic TTN Variant Identified in a Patient with Severe Dilated Cardiomyopathy.

Both genetic and environmental factors contribute to the development of dilated cardiomyopathy. Among the genes involved, TTN mutations, including truncated variants, explain 25% of DCM cases. We performed genetic counseling and analysis on a 57-year-old woman diagnosed with severe DCM and presenting relevant acquired risk factors for DCM (hypertension, diabetes, smoking habit, and/or previous alcohol and cocaine abuse) and with a family history of both DCM and sudden cardiac death. The left ventricular systolic function, as assessed by standard echocardiography, was 20%. The genetic analysis performed using TruSight Cardio panel, including 174 genes related to cardiac genetic diseases, revealed a novel nonsense TTN variant (TTN:c.103591A > T, p.Lys34531*), falling within the M-band region of the titin protein. This region is known for its important role in maintaining the structure of the sarcomere and in promoting sarcomerogenesis. The identified variant was classified as likely pathogenic based on ACMG criteria. The current results support the need of genetic analysis in the presence of a family history, even when relevant acquired risk factors for DCM may have contributed to the severity of the disease.

De novo 3q13.13q21.2 interstitial deletion and paternal 12p13.3 microdeletion in a fetus with dysplasia of the corpus callosum and ventriculomegaly: A case report.

Chromosome 3q syndrome is a well-known genetic condition caused by interstitial deletion in the long arm of chromosome 3. The phenotype of this syndrome is variable and the great variability in the extent of these deletions leads to a wide spectrum of clinical manifestations. Terminal 12p deletion represents one of the rarest subtelomeric imbalances; patients with distal monosomy 12p present different phenotypes ranging from muscular hypotonia to autism spectrum disorders. The present study reported a prenatal diagnosis of a male fetus presenting ultrasound evidence of corpus callosum dysplasia and ventriculomegaly showing a 3q13q21.2 deletion and a 12p13.33 microdeletion paternally inherited. Among several features previously attributed to the terminal deletion of 3q, corpus callosum dysplasia and ventriculomegaly have rarely been reported together. As the 12p13.33 microdeletion in the father was associated only with muscular hypotonia and joint laxity, the involvement of terminal 12p deletions in the clinical features of the fetus was not possible to verify during the prenatal period. The present case report may provide a reference for prenatal diagnosis and genetic counseling in patients who present 3q13q21.2 deletions and 12p13.33 microdeletion.

A New SMAD4 Splice Site Variant in a Three-Generation Italian Family with Juvenile Polyposis Syndrome.

Juvenile polyposis syndrome (JPS) is an autosomal dominant disorder characterized by hyperplastic polyps in the upper and lower gastrointestinal (GI) tract with a high risk of developing GI cancers. We have described a three-generation Italian family with all the spectrum of SMAD4 phenotype. A multigene panel test was performed on the genomic DNA of the proband by next-generation sequencing, including genes related to hereditary GI tumor syndromes. Molecular analysis revealed the presence of the c.1140-2A>G substitution in the SMAD4 gene, a novel splice variant that has never been described before. Our family is remarkable in that it illustrates the variable expressivity of the SMAD4 phenotype within the same family. The possibility of phenotype variability should also be considered within family members carrying the same mutation. In JPS, a timely genetic diagnosis allows clinicians to better manage patients and to provide early surveillance and intervention for their asymptomatic mutated relatives in the early decades of life.

Mosaic human preimplantation embryos and their developmental potential in a prospective, non-selection clinical trial.

Chromosome imbalance (aneuploidy) is the major cause of pregnancy loss and congenital disorders in humans. Analyses of small biopsies from human embryos suggest that aneuploidy commonly originates during early divisions, resulting in mosaicism. However, the developmental potential of mosaic embryos remains unclear. We followed the distribution of aneuploid chromosomes across 73 unselected preimplantation embryos and 365 biopsies, sampled from four multifocal trophectoderm (TE) samples and the inner cell mass (ICM). When mosaicism impacted fewer than 50% of cells in one TE biopsy (low-medium mosaicism), only 1% of aneuploidies affected other portions of the embryo. A double-blinded prospective non-selection trial (NCT03673592) showed equivalent live-birth rates and miscarriage rates across 484 euploid, 282 low-grade mosaic, and 131 medium-grade mosaic embryos. No instances of mosaicism or uniparental disomy were detected in the ensuing pregnancies or newborns, and obstetrical and neonatal outcomes were similar between the study groups. Thus, low-medium mosaicism in the trophectoderm mostly arises after TE and ICM differentiation, and such embryos have equivalent developmental potential as fully euploid ones.

Multi-analytical test based on serum miRNAs and proteins quantification for ovarian cancer early detection.

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.

Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils.

In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among the prominent studies essential oils are investigated as antibacterial agents alone or in combination with known drugs. Minor studies involved essential oil inspection as potential anticancer and antiviral natural remedies. In line with the authors previous reports the investigation of an in-house library of extracted essential oils as a potential blocker of HSV-1 infection is reported herein. A subset of essential oils was experimentally tested in an in vitro model of HSV-1 infection and the determined IC50s and CC50s values were used in conjunction with the results obtained by gas-chromatography/mass spectrometry chemical analysis to derive machine learning based classification models trained with the partial least square discriminant analysis algorithm. The internally validated models were thus applied on untested essential oils to assess their effective predictive ability in selecting both active and low toxic samples. Five essential oils were selected among a list of 52 and readily assayed for IC50 and CC50 determination. Interestingly, four out of the five selected samples, compared with the potencies of the training set, returned to be highly active and endowed with low toxicity. In particular, sample CJM1 from Calaminta nepeta was the most potent tested essential oil with the highest selectivity index (IC50 = 0.063 mg/mL, SI > 47.5). In conclusion, it was herein demonstrated how multidisciplinary applications involving machine learning could represent a valuable tool in predicting the bioactivity of complex mixtures and in the near future to enable the design of blended essential oil possibly endowed with higher potency and lower toxicity.

Incidence, Origin, and Predictive Model for the Detection and Clinical Management of Segmental Aneuploidies in Human Embryos.

Despite next-generation sequencing, which now allows for the accurate detection of segmental aneuploidies from in vitro fertilization embryo biopsies, the origin and characteristics of these aneuploidies are still relatively unknown. Using a multifocal biopsy approach (four trophectoderms [TEs] and one inner cell mass [ICM] analyzed per blastocyst; n = 390), we determine the origin of the aneuploidy and the diagnostic predictive value of segmental aneuploidy detection in TE biopsies toward the ICM's chromosomal constitution. Contrary to the prevalent meiotic origin of whole-chromosome aneuploidies, we show that sub-chromosomal abnormalities in human blastocysts arise from mitotic errors in around 70% of cases. As a consequence, the positive-predictive value toward ICM configuration was significantly lower for segmental as compared to whole-chromosome aneuploidies (70.8% versus 97.18%, respectively). In order to enhance the clinical utility of reporting segmental findings in clinical TE biopsies, we have developed and clinically verified a risk stratification model based on a second TE biopsy confirmation and segmental length; this model can significantly improve the prediction of aneuploidy risk in the ICM in over 86% of clinical cases enrolled. In conclusion, we provide evidence of the predominant mitotic origin of segmental aneuploidies in preimplantation embryos and develop a risk stratification model that can help post-test genetic counseling and that facilitates the decision-making process on clinical utilization of these embryos.