Ventriculoperitoneal shunt management in children undergoing liver transplantation.

There is a lack of data to guide neurosurgeons on the management of ventriculoperitoneal shunts (VPS) in patients undergoing abdominal transplant operations. We present the cases of two pediatric patients with VPS undergoing liver transplantation who were successfully managed with externalization of the VPS at time of transplantation, with subsequent re-internalization once cleared by the transplant surgery team. We present this as an effective management strategy in patients undergoing liver transplantation.

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants. METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members. RESULTS: AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously implicated in AD pathology; rs141402160 (NOTCH3) and rs140914494 (NOTCH3) were previously reported; rs200290640 (PIDD1) and rs199752248 (PIDD1) were present in more than one cousin pair; rs61729902 (SNAP91), rs140129800 (COX6A2, AC026471), and rs191804178 (MUC16) were not present in a longevity cohort; and rs148294193 (PELI3) and rs147599881 (FCHO1) approached significance from analysis of AD-related phenotypes. Three variants were validated via evidence of co-segregation to additional relatives (PELI3, ABCA7, and SNAP91). DISCUSSION: These analyses support ABCA7 and TTR as AD risk genes, expand on previously reported NOTCH3 variant identification, and prioritize seven additional candidate variants.

Transcriptional response to VZV infection is modulated by RNA polymerase III in lung epithelial cell lines.

Ancestral RNA polymerase III (Pol III) is a multi-subunit polymerase responsible for transcription of short non-coding RNA, such as double-stranded short interspersed nuclear elements (SINEs). Although SINE ncRNAs are generally transcriptionally repressed, they can be induced in response to viral infections and can stimulate immune signaling pathways. Indeed, mutations in RNA Pol III have been associated with poor antiviral interferon response following infection with varicella zoster virus (VZV). In this study, we probed the role of Pol III transcripts in the detection and initial immune response to VZV by characterizing the transcriptional response following VZV infection of wild type A549 lung epithelial cells as well as A549 cells lacking specific RNA sensors MAVS and TLR3, or interferon-stimulated genes RNase L and PKR in presence or absence of functional RNA Pol III. Multiple components of the antiviral sensing and interferon signaling pathways were involved in restricting VZV replication in lung epithelial cells thus suggesting an innate defense system with built-in redundancy. In addition, RNA Pol III silencing altered the antiviral transcriptional program indicating that it plays an essential role in the sensing of VZV infection.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores.

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Failure to detect synergy between variants in transferrin and hemochromatosis and Alzheimer's disease in large cohort.

Alzheimer's disease (AD) is the most common cause of dementia and, despite decades of effort, there is no effective treatment. In the last decade, many association studies have identified genetic markers that are associated with AD status. Two of these studies suggest that an epistatic interaction between variants rs1049296 in the transferrin (TF) gene and rs1800562 in the homeostatic iron regulator (HFE) gene, commonly known as hemochromatosis, is in genetic association with AD. TF and HFE are involved in the transport and regulation of iron in the brain, and disrupting these processes exacerbates AD pathology through increased neurodegeneration and oxidative stress. However, by using a significantly larger data set from the Alzheimer's Disease Genetics Consortium, we fail to detect an association between TF rs1049296 or HFE rs1800562 with AD risk (TF rs1049296 p = 0.38 and HFE rs1800562 p = 0.40). In addition, logistic regression with an interaction term and a synergy factor analysis both failed to detect epistasis between TF rs1049296 and HFE rs1800562 (SF = 0.94; p = 0.48) in AD cases. Each of these analyses had sufficient statistical power (power > 0.99), suggesting that previously reported associations may be the result of more complex epistatic interactions, genetic heterogeneity, or false-positive associations because of limited sample sizes.