Background: Truncating variants in desmoplakin ( DSP tv) are an important cause of arrhythmogenic cardiomyopathy; however the genetic architecture and genotype-specific risk factors are incompletely understood. We evaluated phenotype, risk factors for ventricular arrhythmias, and underlying genetics of DSP tv cardiomyopathy. Methods: Individuals with DSP tv and any cardiac phenotype, and their gene-positive family members were included from multiple international centers. Clinical data and family history information were collected. Event-free survival from ventricular arrhythmia was assessed. Variant location was compared between cases and controls, and literature review of reported DSP tv performed. Results: There were 98 probands and 72 family members (mean age at diagnosis 43±8 years, 59% women) with a DSP tv, of which 146 were considered clinically affected. Ventricular arrhythmia (sudden cardiac arrest, sustained ventricular tachycardia, appropriate implantable cardioverter defibrillator therapy) occurred in 56 (33%) individuals. DSP tv location and proband status were independent risk factors for ventricular arrhythmia. Further, gene region was important with variants in cases (cohort n=98; Clinvar n=167) more likely to occur in the regions resulting in nonsense mediated decay of both major DSP isoforms, compared with n=124 genome aggregation database control variants (148 [83.6%] versus 29 [16.4%]; P <0.0001). Conclusions: In the largest series of individuals with DSP tv, we demonstrate that variant location is a novel risk factor for ventricular arrhythmia, can inform variant interpretation, and provide critical insights to allow for precision-based clinical management.

Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed. NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies. NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.

Background: In prenatal genetic diagnostics, the detection of single-gene defects relies on chorionic villus sampling (CVS) and amniocentesis, which carry a miscarriage risk of 0.2–0.3%. To mitigate this risk, fetal trophoblasts have been isolated from a Papanicolaou smear using Trophoblast Retrieval and Isolation from the Cervix (TRIC). However, this method is labor-intensive and has been shown to be challenging to implement in clinical practice. Here, we describe our experiences in using semi-automated immunomagnetic cell sorting for isolating trophoblasts from clinically obtained Papanicolaou smears during ongoing pregnancies. Methods: Using HLA-G-positive Jeg-3 and HLA-G-negative HeLa cell lines in 10%, 1%, and 0.1% dilutions, we tested and optimized the isolation of HLA-G-positive cells using FACS and semi-automated immunomagnetic cell sorting. We used the latter technique for isolation of HLA-G-positive cells from Papanicolaou smears collected from 26 pregnant women, gestational age between 6 and 20 weeks, who underwent CVS. Results: In four independent dilution series, the mean percentages of Jeg-3 cells went from 7.1% to 53.5%, 0.9% to 32.6%, and 0.4% to 2.6% (7.5, 36, and 6.5-fold enrichment, respectively) using immunomagnetic cell sorting. After sorting of the Papanicolaou smears, HLA-G-positive cells were moderately increased in the positive (14.61 vs. 11.63%) and decreased in the negative fraction (7.87 vs. 11.63%) compared to baseline pre-sorting. However, we could not identify fetal cells using XY-chromosomal FISH in a male sample. Conclusions: Our study supports previous findings that careful sampling of fetal cells from Papanicolaou smears in a clinical context poses significant challenges to cell retrieval.