A genome-wide study of Hardy–Weinberg equilibrium with next generation sequence data

Statistical tests for Hardy–Weinberg equilibrium have been an important tool for detecting genotyping errors in the past, and remain important in the quality control of next generation sequence data. In this paper, we analyze complete chromosomes of the 1000 genomes project by using exact test procedures for autosomal and X-chromosomal variants. We find that the rate of disequilibrium largely exceeds what might be expected by chance alone for all chromosomes. Observed disequilibrium is, in about 60% of the cases, due to heterozygote excess. We suggest that most excess disequilibrium can be explained by sequencing problems, and hypothesize mechanisms that can explain exceptional heterozygosities. We report higher rates of disequilibrium for the MHC region on chromosome 6, regions flanking centromeres and p-arms of acrocentric chromosomes. We also detected long-range haplotypes and areas with incidental high disequilibrium. We report disequilibrium to be related to read depth, with variants having extreme read depths being more likely to be out of equilibrium. Disequilibrium rates were found to be 11 times higher in segmental duplications and simple tandem repeat regions. The variants with significant disequilibrium are seen to be concentrated in these areas. For next generation sequence data, Hardy–Weinberg disequilibrium seems to be a major indicator for copy number variation.Peer ReviewedPostprint (published version

Functional strength training versus movement performance therapy for upper limb motor recovery early after stroke: a RCT

BACKGROUND: Not all stroke survivors respond to the same form of physical therapy in the same way early after stroke. The response is variable and a detailed understanding of the interaction between specific physical therapies and neural structure and function is needed. OBJECTIVES: To determine if upper limb recovery is enhanced more by functional strength training (FST) than by movement performance therapy (MPT), to identify the differences in the neural correlates of response to (1) FST and (2) MPT and to determine whether or not pretreatment neural characteristics can predict recovery in response to (1) FST and (2) MPT. DESIGN: Randomised, controlled, observer-blind, multicentre trial with embedded explanatory investigations. An independent facility used computer-generated randomisation for participants’ group allocation. SETTING: In-patient rehabilitation, participants’ homes, university movement analysis facilities and NHS or university neuroimaging departments in the UK. PARTICIPANTS: People who were between 2 and 60 days after stroke in the territory of the anterior cerebral circulation, with some voluntary muscle contraction in the more affected upper limb but not full function. INTERVENTIONS: Routine rehabilitation [conventional physical therapy (CPT)] plus either MPT or FST in equal doses during a 6-week intervention phase. FST was progressive resistive exercise provided during training of functional tasks. MPT was therapist ‘hands-on’ sensory input and guidance for production of smooth and accurate movement. MAIN OUTCOMES: Action Research Arm Test (ARAT) score for clinical efficacy. Neural measures were made of corticocortical [fractional anisotropy (FA) from corpus callosum midline], corticospinal connectivity (asymmetry of corticospinal tracts FA) and resting motor threshold of paretic biceps brachii (pBB) and extensor carpi radialis muscles (derived from transcranial magnetic stimulation). ANALYSIS: Change in ARAT scores were analysed using analysis of covariance models adjusted for baseline variables and randomisation strata. Correlation coefficients were calculated between change in neural measures and change in ARAT score per group and for the whole sample. An interaction term was calculated for each baseline neural measure and ARAT score change from baseline to outcome. RESULTS: A total of 288 participants were randomised [mean age 72.2 (standard deviation 12.5) years; mean ARAT score of 25.5 (18.2); n = 283]. For the 240 participants with ARAT measurements at baseline and outcome, the mean change scores were FST + CPT = 9.70 (11.72) and MPT + CPT = 7.90 (9.18). The group difference did not reach statistical significance (least squares mean difference 1.35, 95% confidence interval –1.20 to 3.90; p = 0.298). Correlations between ARAT change scores and baseline neural values ranged from –0.147 (p = 0.385) for whole-sample corticospinal connectivity (n = 37) to 0.199 (p = 0.320) for MPT + CPT resting motor threshold pBB (n = 27). No statistically significant interaction effects were found between baseline neural variables and change in ARAT score. There were no differences between groups in adverse events. LIMITATIONS: The number of participants in the embedded explanatory investigation was lower than expected. CONCLUSIONS: The small difference in upper limb improvement in response to FST and MPT did not reach statistical significance. Baseline neural measures neither correlated with upper limb recovery nor predicted therapy response. FUTURE WORK: Needs to continue investigation of the variability of response to specific physical therapies in people early after stroke. TRIAL REGISTRATION: Current Controlled Trials ISRCTN19090862 and National Research Ethics Service reference number 11/EE/0524. FUNDING: This project was funded by the Efficacy and Mechanism Evaluation programme, a Medical Research Council and National Institute for Health Research partnership

Generation and quality control of lipidomics data for the alzheimers disease neuroimaging initiative cohort.

Alzheimers disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/

High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines.

Hundreds of genetically characterized cell lines are available for the discovery of genotype-specific cancer vulnerabilities. However, screening large numbers of compounds against large numbers of cell lines is currently impractical, and such experiments are often difficult to control. Here we report a method called PRISM that allows pooled screening of mixtures of cancer cell lines by labeling each cell line with 24-nucleotide barcodes. PRISM revealed the expected patterns of cell killing seen in conventional (unpooled) assays. In a screen of 102 cell lines across 8,400 compounds, PRISM led to the identification of BRD-7880 as a potent and highly specific inhibitor of aurora kinases B and C. Cell line pools also efficiently formed tumors as xenografts, and PRISM recapitulated the expected pattern of erlotinib sensitivity in vivo

TLR-4 ligation of dendritic cells is sufficient to drive pathogenic T cell function in experimental autoimmune encephalomyelitis

<p>Abstract</p> <p>Background</p> <p>Experimental autoimmune encephalomyelitis (EAE) depends on the initial activation of CD4⁺ T cells responsive to myelin autoantigens. The key antigen presenting cell (APC) population that drives the activation of naïve T cells most efficiently is the dendritic cell (DC). As such, we should be able to trigger EAE by transfer of DC that can present the relevant autoantigen(s). Despite some sporadic reports, however, models of DC-driven EAE have not been widely adopted. We sought to test the feasibility of this approach and whether activation of the DC by toll-like receptor (TLR)-4 ligation was a sufficient stimulus to drive EAE.</p> <p>Findings</p> <p>Host mice were seeded with myelin basic protein (MBP)-reactive CD4+ T cells and then were injected with DC that could present the relevant MBP peptide which had been exposed to lipopolysaccharide as a TLR-4 agonist. We found that this approach induced robust clinical signs of EAE.</p> <p>Conclusions</p> <p>DC are sufficient as APC to effectively drive the differentiation of naïve myelin-responsive T cells into autoaggressive effector T cells. TLR-4-stimulation can activate the DC sufficiently to deliver the signals required to drive the pathogenic function of the T cell. These models will allow the dissection of the molecular requirements of the initial DC-T cell interaction in the lymphoid organs that ultimately leads to autoimmune pathology in the central nervous system.</p

Dicer Is Required for Maintaining Adult Pancreas

Dicer1, an essential component of RNA interference and the microRNA pathway, has many important roles in the morphogenesis of developing tissues. Dicer1 null mice have been reported to die at E7.5; therefore it is impossible to study its function in adult tissues. We previously reported that Dicer1-hypomorphic mice, whose Dicer1 expression was reduced to 20% in all tissues, were unexpectedly viable. Here we analyzed these mice to ascertain whether the down-regulation of Dicer1 expression has any influence on adult tissues. Interestingly, all tissues of adult (8–10 week old) Dicer1-hypomorphic mice were histologically normal except for the pancreas, whose development was normal at the fetal and neonatal stages; however, morphologic abnormalities in Dicer1-hypomorphic mice were detected after 4 weeks of age. This suggested that Dicer1 is important for maintaining the adult pancreas

Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease

<p>Abstract</p> <p>Background</p> <p>Natural Language Processing (NLP) systems can be used for specific Information Extraction (IE) tasks such as extracting phenotypic data from the electronic medical record (EMR). These data are useful for translational research and are often found only in free text clinical notes. A key required step for IE is the manual annotation of clinical corpora and the creation of a reference standard for (1) training and validation tasks and (2) to focus and clarify NLP system requirements. These tasks are time consuming, expensive, and require considerable effort on the part of human reviewers.</p> <p>Methods</p> <p>Using a set of clinical documents from the VA EMR for a particular use case of interest we identify specific challenges and present several opportunities for annotation tasks. We demonstrate specific methods using an open source annotation tool, a customized annotation schema, and a corpus of clinical documents for patients known to have a diagnosis of Inflammatory Bowel Disease (IBD). We report clinician annotator agreement at the document, concept, and concept attribute level. We estimate concept yield in terms of annotated concepts within specific note sections and document types.</p> <p>Results</p> <p>Annotator agreement at the document level for documents that contained concepts of interest for IBD using estimated Kappa statistic (95% CI) was very high at 0.87 (0.82, 0.93). At the concept level, F-measure ranged from 0.61 to 0.83. However, agreement varied greatly at the specific concept attribute level. For this particular use case (IBD), clinical documents producing the highest concept yield per document included GI clinic notes and primary care notes. Within the various types of notes, the highest concept yield was in sections representing patient assessment and history of presenting illness. Ancillary service documents and family history and plan note sections produced the lowest concept yield.</p> <p>Conclusion</p> <p>Challenges include defining and building appropriate annotation schemas, adequately training clinician annotators, and determining the appropriate level of information to be annotated. Opportunities include narrowing the focus of information extraction to use case specific note types and sections, especially in cases where NLP systems will be used to extract information from large repositories of electronic clinical note documents.</p