Capturing the Spectrum of Interaction Effects in Genetic Association Studies by Simulated Evaporative Cooling Network Analysis

Evidence from human genetic studies of several disorders suggests that interactions between alleles at multiple genes play an important role in influencing phenotypic expression. Analytical methods for identifying Mendelian disease genes are not appropriate when applied to common multigenic diseases, because such methods investigate association with the phenotype only one genetic locus at a time. New strategies are needed that can capture the spectrum of genetic effects, from Mendelian to multifactorial epistasis. Random Forests (RF) and Relief-F are two powerful machine-learning methods that have been studied as filters for genetic case-control data due to their ability to account for the context of alleles at multiple genes when scoring the relevance of individual genetic variants to the phenotype. However, when variants interact strongly, the independence assumption of RF in the tree node-splitting criterion leads to diminished importance scores for relevant variants. Relief-F, on the other hand, was designed to detect strong interactions but is sensitive to large backgrounds of variants that are irrelevant to classification of the phenotype, which is an acute problem in genome-wide association studies. To overcome the weaknesses of these data mining approaches, we develop Evaporative Cooling (EC) feature selection, a flexible machine learning method that can integrate multiple importance scores while removing irrelevant genetic variants. To characterize detailed interactions, we construct a genetic-association interaction network (GAIN), whose edges quantify the synergy between variants with respect to the phenotype. We use simulation analysis to show that EC is able to identify a wide range of interaction effects in genetic association data. We apply the EC filter to a smallpox vaccine cohort study of single nucleotide polymorphisms (SNPs) and infer a GAIN for a collection of SNPs associated with adverse events. Our results suggest an important role for hubs in SNP disease susceptibility networks. The software is available at http://sites.google.com/site/McKinneyLab/software

Structural Diversity of Ultralong CDRH3s in Seven Bovine Antibody Heavy Chains

Antigen recognition by mammalian antibodies represents the most diverse setting for protein-protein interactions, because antibody variable regions contain exceptionally diverse variable gene repertoires of DNA sequences containing combinatorial, non-templated junctional mutational diversity. Some animals use additional strategies to achieve structural complexity in the antibody combining site, and one of the most interesting of these is the formation of ultralong heavy chain complementarity determining region 3 loops in cattle. Repertoire sequencing studies of bovine antibody heavy chain variable sequences revealed that bovine antibodies can contain heavy chain complementarity determining region 3 (CDRH3) loops with 60 or more amino acids, with complex structures stabilized by multiple disulfide bonds. It is clear that bovine antibodies can achieve long, peculiarly structured CDR3s, but the range of diversity and complexity of those structures is poorly understood. We determined the atomic resolution structure of seven ultralong bovine CDRH3 loops. The studies, combined with five previous structures, reveal a large diversity of cysteine pairing variations, and highly diverse globular domains

A polarized atomic hydrogen beam

We describe the design and operating characteristics of a simple polarized atomic hydrogen beam particularly suitable for applications to crossed beams experiments. In addition to experimental measurements, we present the results of detailed computer models, using Monte-Carlo ray tracing techniques, optical analogs, and phase-space methods, that not only provide us with a confirmation of our measurement, but also allow us to characterize the density, polarization, and atomic fraction of the beam at all points along its path. As a subsidiary result, we also present measurements of the relative and absolute efficiencies of the V/G Supavac mass analyzer for masses 1 and 2

Personalised Ambient Monitoring (PAM) for People with Bipolar Disorder

This paper presents the architecture and preliminary trial results of a monitoring system for patients with bipolar disorder containing environmental and wearable sensors

Closed loop identification of systems within cascade connected control strategies

A brief review of the background to the Phase-Locked Loop (PLL) method of non-parametric system identification is presented. This introduces the idea of performing the non-parametric identification for any point on the frequency response curve of a process. The PLL identification method is then extended to perform the non-parametric identification of the component parts of a cascade connected control system. An advantage of the method is that the non-parametric identification is performed with the cascade control system connected in closed loop. An example demonstrating the identification method is given

Quantitative analysis of the ACL and PCL using T1rho and T2 relaxation time mapping: an exploratory, cross-sectional comparison between OA and healthy control knees.

BACKGROUND: Quantitative magnetic resonance imaging (MRI) methods such as T1rho and T2 mapping are sensitive to changes in tissue composition, however their use in cruciate ligament assessment has been limited to studies of asymptomatic populations or patients with posterior cruciate ligament tears only. The aim of this preliminary study was to compare T1rho and T2 relaxation times of the anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) between subjects with mild-to-moderate knee osteoarthritis (OA) and healthy controls. METHODS: A single knee of 15 patients with mild-to-moderate knee OA (Kellgren-Lawrence grades 2-3) and of 6 age-matched controls was imaged using a 3.0 T MRI. Three-dimensional (3D) fat-saturated spoiled gradient recalled-echo images were acquired for morphological assessment and T1ρ- and T2-prepared pseudo-steady-state 3D fast spin echo images for compositional assessment of the cruciate ligaments. Manual segmentation of whole ACL and PCL, as well as proximal / middle / distal thirds of both ligaments was carried out by two readers using ITK-SNAP and mean relaxation times were recorded. Variation between thirds of the ligament were assessed using repeated measures ANOVAs and differences in these variations between groups using a Kruskal-Wallis test. Inter- and intra-rater reliability were assessed using intraclass correlation coefficients (ICCs). RESULTS: In OA knees, both T1rho and T2 values were significantly higher in the distal ACL when compared to the rest of the ligament with the greatest differences in T1rho (e.g. distal mean = 54.5 ms, proximal = 47.0 ms, p < 0.001). The variation of T2 values within the PCL was lower in OA knees (OA: distal vs middle vs proximal mean = 28.5 ms vs 29.1 ms vs 28.7 ms, p = 0.748; Control: distal vs middle vs proximal mean = 26.4 ms vs 32.7 ms vs 33.3 ms, p = 0.009). ICCs were excellent for the majority of variables. CONCLUSION: T1rho and T2 mapping of the cruciate ligaments is feasible and reliable. Changes within ligaments associated with OA may not be homogeneous. This study is an important step forward in developing a non-invasive, radiological biomarker to assess the ligaments in diseased human populations in-vivo.Declarations Ethics approval and consent to participate This study was approved by the East of England Cambridge Central Research Ethics Committee and written informed consent was given by all subjects included in the study. All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication Not Applicable Availability of data and materials The datasets generated and analysed during the current study are not publicly available due to unattained permission from participants and research ethics committee but could be made available from JWM (email: [email protected]). Competing interests JWM, DAK and JDK acknowledge funding support from GlaxoSmithKline for their studentships and fellowships, respectively. JWM is an employee of AstraZeneca. CDSR, VAC and SMM have no competing interests to declare. Acknowledgements The Addenbrooke's Hospital Magnetic Resonance Imaging and Spectroscopy (MRIS) staff are thanked for their help with arranging and conducting the study MRI examinations. We also acknowledge the support of the Addenbrooke's Charitable Trust and the National Institute for Health Research Cambridge Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Funding The study was funded by an Experimental Medicine Initiative PhD studentship from the University of Cambridge [grant number RG81329] and by GlaxoSmithKline [grant number RG87552]. Authors' contributions Writing of original draft manuscript: CDSR. Study design and coordination: CDSR, JWM, JDK and SMM. Data acquisition: JWM and JDK. Data curation, analysis and interpretation: CDSR, JWM, VAC, JDK, DAK and SMM. Statistical analysis: CDSR and JWM. Review and editing of manuscript: JWM, VAC, JDK, DAK and SMM. All authors read and approved the final manuscript

Distinct conformations, aggregation and cellular internalization of different tau strains

The inter-cellular propagation of tau aggregates in several neurodegenerative diseases involves, in part, recurring cycles of extracellular tau uptake, initiation of endogenous tau aggregation, and extracellular release of at least part of this protein complex. However, human brain tau extracts from diverse tauopathies exhibit variant or “strain” specificity in inducing inter-cellular propagation in both cell and animal models. It is unclear if these distinctive properties are affected by disease-specific differences in aggregated tau conformation and structure. We have used a combined structural and cell biological approach to study if two frontotemporal dementia (FTD)-associated pathologic mutations, V337M and N279K, affect the aggregation, conformation and cellular internalization of the tau four-repeat domain (K18) fragment. In both heparin-induced and native-state aggregation experiments, each FTD variant formed soluble and fibrillar aggregates with remarkable morphological and immunological distinctions from the wild type (WT) aggregates. Exogenously-applied oligomers of the FTD tau-K18 variants (V337M and N279K) were significantly more efficiently taken up by SH-SY5Y neuroblastoma cells than WT tau-K18, suggesting mutation-induced changes in cellular internalization. However, shared internalization mechanisms were observed: endocytosed oligomers were distributed in the cytoplasm and nucleus of SH-SY5Y cells and the neurites and soma of human induced pluripotent stem cell-derived neurons where they co-localized with endogenous tau and the nuclear protein nucleolin. Altogether, evidence of conformational and aggregation differences between WT and disease-mutated tau K18 is demonstrated, which may explain their distinct cellular internalization potencies. These findings may account for critical aspects of the molecular pathogenesis of tauopathies involving WT and mutated tau

A cross-reactive antibody protects against Ross River virus musculoskeletal disease despite rapid neutralization escape in mice

Arthritogenic alphaviruses cause debilitating musculoskeletal disease and historically have circulated in distinct regions. With the global spread of chikungunya virus (CHIKV), there now is more geographic overlap, which could result in heterologous immunity affecting natural infection or vaccination. Here, we evaluated the capacity of a cross-reactive anti-CHIKV monoclonal antibody (CHK-265) to protect against disease caused by the distantly related alphavirus, Ross River virus (RRV). Although CHK-265 only moderately neutralizes RRV infection in cell culture, it limited clinical disease in mice independently of Fc effector function activity. Despite this protective phenotype, RRV escaped from CHK-265 neutralization in vivo, with resistant variants retaining pathogenic potential. Near the inoculation site, CHK-265 reduced viral burden in a type I interferon signaling-dependent manner and limited immune cell infiltration into musculoskeletal tissue. In a parallel set of experiments, purified human CHIKV immune IgG also weakly neutralized RRV, yet when transferred to mice, resulted in improved clinical outcome during RRV infection despite the emergence of resistant viruses. Overall, this study suggests that weakly cross-neutralizing antibodies can protect against heterologous alphavirus disease, even if neutralization escape occurs, through an early viral control program that tempers inflammation

The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.

Automated semantic segmentation of multiple knee joint tissues is desirable to allow faster and more reliable analysis of large datasets and to enable further downstream processing e.g. automated diagnosis. In this work, we evaluate the use of conditional Generative Adversarial Networks (cGANs) as a robust and potentially improved method for semantic segmentation compared to other extensively used convolutional neural network, such as the U-Net. As cGANs have not yet been widely explored for semantic medical image segmentation, we analysed the effect of training with different objective functions and discriminator receptive field sizes on the segmentation performance of the cGAN. Additionally, we evaluated the possibility of using transfer learning to improve the segmentation accuracy. The networks were trained on i) the SKI10 dataset which comes from the MICCAI grand challenge "Segmentation of Knee Images 2010″, ii) the OAI ZIB dataset containing femoral and tibial bone and cartilage segmentations of the Osteoarthritis Initiative cohort and iii) a small locally acquired dataset (Advanced MRI of Osteoarthritis (AMROA) study) consisting of 3D fat-saturated spoiled gradient recalled-echo knee MRIs with manual segmentations of the femoral, tibial and patellar bone and cartilage, as well as the cruciate ligaments and selected peri-articular muscles. The Sørensen-Dice Similarity Coefficient (DSC), volumetric overlap error (VOE) and average surface distance (ASD) were calculated for segmentation performance evaluation. DSC ≥ 0.95 were achieved for all segmented bone structures, DSC ≥ 0.83 for cartilage and muscle tissues and DSC of ≈0.66 were achieved for cruciate ligament segmentations with both cGAN and U-Net on the in-house AMROA dataset. Reducing the receptive field size of the cGAN discriminator network improved the networks segmentation performance and resulted in segmentation accuracies equivalent to those of the U-Net. Pretraining not only increased segmentation accuracy of a few knee joint tissues of the fine-tuned dataset, but also increased the network's capacity to preserve segmentation capabilities for the pretrained dataset. cGAN machine learning can generate automated semantic maps of multiple tissues within the knee joint which could increase the accuracy and efficiency for evaluating joint health.European Union's Horizon 2020 Framework Programme [grant number 761214] Addenbrooke’s Charitable Trust (ACT) National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre University of Cambridge Cambridge University Hospitals NHS Foundation Trust GSK VARSITY: PHD STUDENTSHIP Funder reference: 300003198