Noninvasive prenatal screening for cystic fibrosis using circulating trophoblasts: Detection of the 50 most common disease-causing variants.

OBJECTIVES: Cystic fibrosis (CF) is one of the most common severe autosomal recessive disorders. Prenatal or preconception CF screening is offered in some countries. A maternal blood sample in early pregnancy can provide circulating trophoblasts and offers a DNA source for genetic analysis of both the mother and the fetus. This study aimed to develop a cell-based noninvasive prenatal test (NIPT) to screen for the 50 most common CF variants. METHODS: Blood samples were collected from 30 pregnancies undergoing invasive diagnostics and circulating trophoblasts were harvested in 27. Cystic fibrosis testing was conducted using two different methods: by fragment length analysis and by our newly developed NGS-based CF analysis. RESULTS: In all 27 cases, cell-based NIPT provided a result using both methods in agreement with the invasive test result. CONCLUSION: This study shows that cell-based NIPT for CF screening provides a reliable result without the need for partner- and proband samples.

Neuropeptide Y and religious commitment in healthy young women.

OBJECTIVE: The present study explores the relationship between neuroactive hormones and religious commitment. We hypothesised that religious commitment is mediated by neuropeptide Y and oxytocin. These neurohormones have a well-established role in general well-being, anxiety regulation, stress-resilience, social affiliation and spirituality. METHODS: Sixty healthy women (median age 21) participated in the study and completed the Religious Commitment Inventory and other psychometric surveys. Blood was sampled from each participant and serum levels of neuropeptide Y were measured using radioimmunoassay. Oxytocin, stress and sex hormones were measured using enzyme-linked immunosorbent assay. Correlations were tested using non-parametric statistical methods. RESULTS: We found a positive correlation between serum neuropeptide Y levels and religious commitment, but not between oxytocin and religious commitment. CONCLUSIONS: The present study provides preliminary evidence that neuropeptide Y is a biological correlate of religious commitment.

Predicting psychogenic non-epileptic seizures from serum levels of neuropeptide Y and adrenocorticotropic hormone.

OBJECTIVE: Patients with psychogenic non-epileptic seizures (PNES) may present with convulsive events that are not accompanied by epileptiform brain activity. Video-electroencephalography (EEG) monitoring is the gold standard for diagnosis, yet not all patients experience convulsive episodes during video-EEG sessions. Hence, we aimed to construct a predictive model in order to detect PNES from serum hormone levels, detached from an evaluation of patients' convulsive episodes. METHODS: Fifteen female patients with PNES and 60 healthy female controls participated in the study, providing blood samples for hormone analysis. A binomial logistic regression model and the leave-one-out cross-validation were employed. RESULTS: We found that levels of neuropeptide Y and adrenocorticotropic hormone were the optimal combination of predictors, with over 90% accuracy (area under the curve=0.980). CONCLUSIONS: The ability to diagnose PNES irrespective of convulsive events would represent an important step considering its feasibility and affordability in daily clinical practice.

Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery.

DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples. It is suitable for any genome with a known reference. We present a full rewrite of the original pipeline showing a significant reduction of storage requirements by using the CRAM format and runtime by increasing intra-sample parallelization. Both are leading to a 70% cost reduction in commercial clouds enabling users to do large-scale and cross-platform data analysis while keeping costs and CO2 emissions low. The code is available at https://nf-co.re/sarek.