A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Association of Pediatric ASPECTS and NIH Stroke Scale, Hemorrhagic Transformation, and 12-Month Outcome in Children With Acute Ischemic Stroke.

OBJECTIVE We aimed to determine whether a modified pediatric Alberta Stroke Program Early CT Score (modASPECTS) is associated with clinical stroke severity, hemorrhagic transformation, and 12-month functional outcomes in children with acute AIS. METHODS Children (29 days to <18 years) with acute AIS enrolled in two institutional prospective stroke registries at Children's Hospital of Philadelphia and Royal Children's Hospital Melbourne, Australia were retrospectively analyzed to determine whether modASPECTS, in which higher scores are worse, correlated with acute Pediatric NIH Stroke Scale (PedNIHSS) scores (children ≥2 years of age), was associated with hemorrhagic transformation on acute MRI, and correlated with 12-month functional outcome on the Pediatric Stroke Outcome Measure (PSOM). RESULTS 131 children were included; 91 were ≥2 years of age. Median days from stroke to MRI was 1 (interquartile range [IQR] 0-1). Median modASPECTS was 4 (IQR 3-7). ModASPECTS correlated with PedNIHSS (rho=0.40, P=0.0001). ModASPECTS was associated with hemorrhagic transformation (OR 1.13 95% CI 1.02-1.25, P=0.018). Among children with follow-up (N=128, median 12.2 months, IQR 9.5-15.4 months), worse outcomes were associated with higher modASPECTS (common OR 1.14, 95%CI 1.04-1.24, P=0.005). The association between modASPECTS and outcome persisted when we adjusted for age at stroke ictus and the presence of tumor or meningitis as stroke risk factors (common OR 1.14, 95%CI 1.03-1.25, P=0.008). CONCLUSIONS ModASPECTS correlates with PedNIHSS scores, hemorrhagic transformation, and 12-month functional outcome in children with acute AIS. Future pediatric studies should evaluate its usefulness in predicting symptomatic intracranial hemorrhage and outcome after acute revascularization therapies. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that the modified pediatric ASPECTS on MRI is associated with stroke severity (as measured by the baseline pediatric NIH Stroke Scale), hemorrhagic transformation, and 12-month outcome in children with acute supratentorial ischemic stroke

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field