Publications by authors named "Keith Smith"

218 Publications

The COVIDome Explorer Researcher Portal.

medRxiv 2021 Mar 8. Epub 2021 Mar 8.

COVID-19 pathology involves dysregulation of diverse molecular, cellular, and physiological processes. In order to expedite integrated and collaborative COVID-19 research, we completed multi-omics analysis of hospitalized COVID-19 patients including matched analysis of the whole blood transcriptome, plasma proteomics with two complementary platforms, cytokine profiling, plasma and red blood cell metabolomics, deep immune cell phenotyping by mass cytometry, and clinical data annotation. We refer to this multidimensional dataset as the COVIDome. We then created the COVIDome Explorer, an online researcher portal where the data can be analyzed and visualized in real time. We illustrate here the use of the COVIDome dataset through a multi-omics analysis of biosignatures associated with C-reactive protein (CRP), an established marker of poor prognosis in COVID-19, revealing associations between CRP levels and damage-associated molecular patterns, depletion of protective serpins, and mitochondrial metabolism dysregulation. We expect that the COVIDome Explorer will rapidly accelerate data sharing, hypothesis testing, and discoveries worldwide.
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http://dx.doi.org/10.1101/2021.03.04.21252945DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987038PMC
March 2021

Seroconversion stages COVID19 into distinct pathophysiological states.

Elife 2021 03 16;10. Epub 2021 Mar 16.

Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, United States.

COVID19 is a heterogeneous medical condition involving diverse underlying pathophysiological processes including hyperinflammation, endothelial damage, thrombotic microangiopathy, and end-organ damage. Limited knowledge about the molecular mechanisms driving these processes and lack of staging biomarkers hamper the ability to stratify patients for targeted therapeutics. We report here the results of a cross-sectional multi-omics analysis of hospitalized COVID19 patients revealing that seroconversion status associates with distinct underlying pathophysiological states. Low antibody titers associate with hyperactive T cells and NK cells, high levels of IFN alpha, gamma and lambda ligands, markers of systemic complement activation, and depletion of lymphocytes, neutrophils, and platelets. Upon seroconversion, all of these processes are attenuated, observing instead increases in B cell subsets, emergency hematopoiesis, increased D-dimer, and hypoalbuminemia. We propose that seroconversion status could potentially be used as a biosignature to stratify patients for therapeutic intervention and to inform analysis of clinical trial results in heterogenous patient populations.
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http://dx.doi.org/10.7554/eLife.65508DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963480PMC
March 2021

Benchmarking network-based gene prioritization methods for cerebral small vessel disease.

Brief Bioinform 2021 Feb 26. Epub 2021 Feb 26.

Health Data Research UK, London, United Kingdom.

Network-based gene prioritization algorithms are designed to prioritize disease-associated genes based on known ones using biological networks of protein interactions, gene-disease associations (GDAs) and other relationships between biological entities. Various algorithms have been developed based on different mechanisms, but it is not obvious which algorithm is optimal for a specific disease. To address this issue, we benchmarked multiple algorithms for their application in cerebral small vessel disease (cSVD). We curated protein-gene interactions (PGIs) and GDAs from databases and assembled PGI networks and disease-gene heterogeneous networks. A screening of algorithms resulted in seven representative algorithms to be benchmarked. Performance of algorithms was assessed using both leave-one-out cross-validation (LOOCV) and external validation with MEGASTROKE genome-wide association study (GWAS). We found that random walk with restart on the heterogeneous network (RWRH) showed best LOOCV performance, with median LOOCV rediscovery rank of 185.5 (out of 19 463 genes). The GenePanda algorithm had most GWAS-confirmable genes in top 200 predictions, while RWRH had best ranks for small vessel stroke-associated genes confirmed in GWAS. In conclusion, RWRH has overall better performance for application in cSVD despite its susceptibility to bias caused by degree centrality. Choice of algorithms should be determined before applying to specific disease. Current pure network-based gene prioritization algorithms are unlikely to find novel disease-associated genes that are not associated with known ones. The tools for implementing and benchmarking algorithms have been made available and can be generalized for other diseases.
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http://dx.doi.org/10.1093/bib/bbab006DOI Listing
February 2021

Explaining the emergence of complex networks through log-normal fitness in a Euclidean node similarity space.

Sci Rep 2021 Jan 21;11(1):1976. Epub 2021 Jan 21.

Usher Institute, University of Edinburgh, Edinburgh, UK.

Networks of disparate phenomena-be it the global ecology, human social institutions, within the human brain, or in micro-scale protein interactions-exhibit broadly consistent architectural features. To explain this, we propose a new theory where link probability is modelled by a log-normal node fitness (surface) factor and a latent Euclidean space-embedded node similarity (depth) factor. Building on recurring trends in the literature, the theory asserts that links arise due to individualistic as well as dyadic information and that important dyadic information making up the so-called depth factor is obscured by this essentially non-dyadic information making up the surface factor. Modelling based on this theory considerably outperforms popular power-law fitness and hyperbolic geometry explanations across 110 networks. Importantly, the degree distributions of the model resemble power-laws at small densities and log-normal distributions at larger densities, posing a reconciliatory solution to the long-standing debate on the nature and existence of scale-free networks. Validating this theory, a surface factor inversion approach on an economic world city network and an fMRI connectome results in considerably more geometrically aligned nearest neighbour networks, as is hypothesised to be the case for the depth factor. This establishes new foundations from which to understand, analyse, deconstruct and interpret network phenomena.
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http://dx.doi.org/10.1038/s41598-021-81547-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820353PMC
January 2021

Seroconversion stages COVID19 into distinct pathophysiological states.

medRxiv 2020 Dec 7. Epub 2020 Dec 7.

Linda Crnic Institute for Down Syndrome; University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

COVID19 is a heterogeneous medical condition involving a suite of underlying pathophysiological processes including hyperinflammation, endothelial damage, thrombotic microangiopathy, and end-organ damage. Limited knowledge about the molecular mechanisms driving these processes and lack of staging biomarkers hamper the ability to stratify patients for targeted therapeutics. We report here the results of a cross-sectional multi-omics analysis of hospitalized COVID19 patients revealing that seroconversion status associates with distinct underlying pathophysiological states. Seronegative COVID19 patients harbor hyperactive T cells and NK cells, high levels of IFN alpha, gamma and lambda ligands, markers of systemic complement activation, neutropenia, lymphopenia and thrombocytopenia. In seropositive patients, all of these processes are attenuated, observing instead increases in B cell subsets, emergency hematopoiesis, increased markers of platelet activation, and hypoalbuminemia. We propose that seroconversion status could potentially be used as a biosignature to stratify patients for therapeutic intervention and to inform analysis of clinical trial results in heterogenous patient populations.
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http://dx.doi.org/10.1101/2020.12.05.20244442DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7743101PMC
December 2020

Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.

Lupus 2021 Feb 13;30(2):285-298. Epub 2020 Dec 13.

Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.

Objective: This work investigates network organisation of brain structural connectivity in systemic lupus erythematosus (SLE) relative to healthy controls and its putative association with lesion distribution and disease indicators.

Methods: White matter hyperintensity (WMH) segmentation and connectomics were performed in 47 patients with SLE and 47 healthy age-matched controls from structural and diffusion MRI data. Network nodes were divided into hierarchical tiers based on numbers of connections. Results were compared between patients and controls to assess for differences in brain network organisation. Voxel-based analyses of the spatial distribution of WMH in relation to network measures and SLE disease indicators were conducted.

Results: Despite inter-individual differences in brain network organization observed across the study sample, the connectome networks of SLE patients had larger proportion of connections in the peripheral nodes. SLE patients had statistically larger numbers of links in their networks with generally larger fractional anisotropy weights (i.e. a measure of white matter integrity) and less tendency to aggregate than those of healthy controls. The voxels exhibiting connectomic differences were coincident with WMH clusters, particularly the left hemisphere's intersection between the anterior limb of the internal and external capsules. Moreover, these voxels also associated more strongly with disease indicators.

Conclusion: Our results indicate network differences reflective of compensatory reorganization of the neural circuits, reflecting adaptive or extended neuroplasticity in SLE.
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http://dx.doi.org/10.1177/0961203320979045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854491PMC
February 2021

Hierarchical Complexity of the Macro-Scale Neonatal Brain.

Cereb Cortex 2021 Mar;31(4):2071-2084

MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.

The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.
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http://dx.doi.org/10.1093/cercor/bhaa345DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945030PMC
March 2021

JAK1 Inhibition Blocks Lethal Immune Hypersensitivity in a Mouse Model of Down Syndrome.

Cell Rep 2020 11;33(7):108407

Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Section of Developmental Biology, Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA. Electronic address:

Individuals with Down syndrome (DS; trisomy 21) display hyperactivation of interferon (IFN) signaling and chronic inflammation, which could potentially be explained by the extra copy of four IFN receptor (IFNR) genes encoded on chromosome 21. However, the clinical effects of IFN hyperactivity in DS remain undefined. Here, we report that a commonly used mouse model of DS overexpresses IFNR genes and shows hypersensitivity to IFN ligands in diverse immune cell types. When treated repeatedly with a TLR3 agonist to induce chronic inflammation, these animals overexpress key IFN-stimulated genes, induce cytokine production, exhibit liver pathology, and undergo rapid weight loss. Importantly, the lethal immune hypersensitivity and cytokine production and the ensuing pathology are ameliorated by JAK1 inhibition. These results indicate that individuals with DS may experience harmful hyperinflammation upon IFN-inducing immune stimuli, as observed during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, pointing to JAK1 inhibition as a strategy to restore immune homeostasis in DS.
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http://dx.doi.org/10.1016/j.celrep.2020.108407DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7727402PMC
November 2020

Sampling the Early Solar System.

Science 2020 11;370(6517):672-673

Deputy Editor, Science Advances.

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http://dx.doi.org/10.1126/science.abf2271DOI Listing
November 2020

Subdural Hemorrhage in Asymptomatic Neonates: Neurodevelopmental Outcomes and MRI Findings at 2 Years.

Radiology 2021 01 27;298(1):173-179. Epub 2020 Oct 27.

From the Department of Radiology, Division of Neuroradiology (C.Z., J.K.S.); and Department of Psychiatry (E.A.C., Z.Y., J.H.G.), University of North Carolina School of Medicine, 2006 Old Clinic Building, CB# 7510, Chapel Hill, NC 27599-7510; and Division of Pediatric Imaging, Department of Diagnostic Imaging, Hasbro Children's Hospital, Rhode Island Medical Imaging, Warren Alpert Medical School of Brown University, Providence, RI (C.S.).

Background Subdural hemorrhage (SDH) is thought to have a benign course in asymptomatic neonates. However, effects on neurodevelopmental outcomes have not been established. Purpose To evaluate neurodevelopmental outcomes, gray matter volumes, and MRI findings in asymptomatic neonates with SDH compared with control neonates. Materials and Methods This retrospective analysis was conducted between 2003 and 2016 and was based on data from the University of North Carolina Early Brain Development Study. Neurodevelopmental outcomes were evaluated at 2 years of age by using the Mullen Scales of Early Learning (MSEL). All infants were imaged with 3.0-T MRI machines and were evaluated for SDH at baseline (neonates) and at ages 1 and 2 years. Volumetric MRI for brain segmentation was performed at ages 1 and 2 years. A secondary analysis was performed in neonates matched 1:1 with control neonates. Differences in categorical variables were measured by using the Fisher exact test, and the test was used for continuous variables. Results A total of 311 neonates (mean gestational age ± standard deviation, 39.3 weeks ± 1.5), including 57 with SDH (mean gestational age, 39.5 weeks ± 1.2), were evaluated. The subgroup included 55 neonates with SDH (mean gestational age, 39.6 weeks ± 1.2) and 55 matched control neonates (mean gestational age, 39.7 weeks ± 1.2). Fifty-five of 57 neonates with SDH (97%; 95% CI: 92, 100) were delivered vaginally compared with 157 of 254 control neonates (62%, 95% CI: 56, 68; < .001). Otherwise, there were no differences in perinatal, maternal, or obstetric parameters. There were no differences in composite MSEL scores (115 ± 15 and 109 ± 16 at 2 years, respectively; = .05) or gray matter volumes between the neonatal SDH group and control neonates (730 cm ± 85 and 742 cm ± 76 at 2 years, respectively; = .70). There was no evidence of rebleeding at follow-up MRI. Conclusion Neurodevelopmental scores and gray matter volumes at age 2 years did not differ between asymptomatic neonates with subdural hemorrhage and control neonates. © RSNA, 2020
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http://dx.doi.org/10.1148/radiol.2020201857DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842194PMC
January 2021

Pipeline comparisons of convolutional neural networks for structural connectomes: predicting sex across 3,152 participants.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:1692-1695

With several initiatives well underway towards amassing large and high-quality population-based neuroimaging datasets, deep learning is set to push the boundaries of what is possible in classification and prediction in neuroimaging studies. This includes those that derive increasingly popular structural connectomes, which map out the connections (and their relative strengths) between brain regions. Here, we test different Convolutional Neural Network (CNN) models in a benchmark sex prediction task in a large sample of N=3,152 structural connectomes acquired from the UK Biobank, and compare results across different connectome processing choices. The best results (76.5% test accuracy) were achieved using Fractional Anisotropy (FA) weighted connectomes, without sparsification, and with a simple weight normalisation through division by the maximum FA value. We also confirm that for structural connectomes, a Graph CNN approach, the recently proposed BrainNetCNN, outperforms an image-based CNN.
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http://dx.doi.org/10.1109/EMBC44109.2020.9175596DOI Listing
July 2020

Synthetic Antibody Mimics Based on Cancer-Targeting Immunostimulatory Peptides.

Chembiochem 2020 Sep 22. Epub 2020 Sep 22.

Department of Biological Sciences and Chemistry and Biochemistry, Seton Hall University, 400 South Orange Avenue, South Orange, NJ 07079, USA.

De novo cancer-targeting immunostimulatory peptides have been designed and developed as synthetic antibody mimics. A series of bifunctional peptides incorporating NKp30-binding and NK-cell-activating domains were synthesized as linear dimers and then extended into branching trimeric peptides by the incorporation of GRP78-targeting and tumor-cell-binding sequences. A selected trimeric peptide from this small set of peptides displayed binding capabilities on GRP78 HepG2 and A549 target cells. Cell binding diminished in the presence of an anti-GRP78 peptide blocker, thus suggesting GRP78-binding dependence. Similarly, the selected trimeric peptide was also found to exhibit NK cell binding in an NKp30-dependent manner, which translated into NK cell activation as indicated by cytokine secretion. In co-culture, fluorescence microscopy revealed that the target GFP-expressing A549 cells were visibly associated with the effector NK cells when pre-activated with lead trimeric peptide. Accordingly, A549 cells were found to be compromised, as evidenced by the loss of GFP signal and notable detection of early-/late-stage apoptosis. Investigation of the immunological markers related to toxicity revealed detectable secretion of pro-inflammatory cytokines and chemokines, including IFN-γ, TNF-α, and IL-8. Furthermore, administration of peptide-activated NK cells into A549-tumor-bearing mice resulted in a consistent decrease in tumor growth when compared to the untreated control group. Taken together, the identification of a lead trimeric peptide capable of targeting and activating NK cells' immunotoxicity directly towards GRP78 /B7H6 tumors provides a novel proof-of-concept for the development of cancer-targeting immunostimulatory peptide ligands that mimic antibody-targeting and -activating functions related to cancer immunotherapy applications.
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http://dx.doi.org/10.1002/cbic.202000407DOI Listing
September 2020

Disentangled-Multimodal Adversarial Autoencoder: Application to Infant Age Prediction With Incomplete Multimodal Neuroimages.

IEEE Trans Med Imaging 2020 12 30;39(12):4137-4149. Epub 2020 Nov 30.

Effective fusion of structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) data has the potential to boost the accuracy of infant age prediction thanks to the complementary information provided by different imaging modalities. However, functional connectivity measured by fMRI during infancy is largely immature and noisy compared to the morphological features from sMRI, thus making the sMRI and fMRI fusion for infant brain analysis extremely challenging. With the conventional multimodal fusion strategies, adding fMRI data for age prediction has a high risk of introducing more noises than useful features, which would lead to reduced accuracy than that merely using sMRI data. To address this issue, we develop a novel model termed as disentangled-multimodal adversarial autoencoder (DMM-AAE) for infant age prediction based on multimodal brain MRI. Specifically, we disentangle the latent variables of autoencoder into common and specific codes to represent the shared and complementary information among modalities, respectively. Then, cross-reconstruction requirement and common-specific distance ratio loss are designed as regularizations to ensure the effectiveness and thoroughness of the disentanglement. By arranging relatively independent autoencoders to separate the modalities and employing disentanglement under cross-reconstruction requirement to integrate them, our DMM-AAE method effectively restrains the possible interference cross modalities, while realizing effective information fusion. Taking advantage of the latent variable disentanglement, a new strategy is further proposed and embedded into DMM-AAE to address the issue of incompleteness of the multimodal neuroimages, which can also be used as an independent algorithm for missing modality imputation. By taking six types of cortical morphometric features from sMRI and brain functional connectivity from fMRI as predictors, the superiority of the proposed DMM-AAE is validated on infant age (35 to 848 days after birth) prediction using incomplete multimodal neuroimages. The mean absolute error of the prediction based on DMM-AAE reaches 37.6 days, outperforming state-of-the-art methods. Generally, our proposed DMM-AAE can serve as a promising model for prediction with multimodal data.
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http://dx.doi.org/10.1109/TMI.2020.3013825DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773223PMC
December 2020

Radiation safety education and diagnostic imaging in pediatric patients with surgically treated hydrocephalus: the patient and family perspective.

Childs Nerv Syst 2021 Feb 24;37(2):491-497. Epub 2020 Jul 24.

Department of Neurosurgery, University of North Carolina, Chapel Hill, NC, USA.

Purpose: Surgically treated hydrocephalus patients are frequently imaged with head computed tomography (CT), and risk/benefit communication with families is inconsistent and unknown. We aimed to educate patients and caregivers about radiation safety in CT and explore their communication preferences.

Methods: We conducted a pediatric CT radiation safety and diagnostic imaging educational workshop for patients and caregivers at a national conference on hydrocephalus to characterize current practice and desired communication about CT imaging. Our workshop consisted of an interactive educational intervention with pre-/post-session surveys followed by feedback from participants.

Results: Our session included 34 participants (100% response rate for surveys) with 28 being parents of individuals with hydrocephalus. A total of 76% (n = 26) participants showed an increase in knowledge after the session (p < 0.01). All participants (N = 34) uniformly desired risk/benefit discussions before CT scans. However, 71% stated that they were not informed of risks/benefits of CT scans by a medical professional. Following the session, the number of participants indicating that informed consent should be obtained before CT scans increased from 30 to 33. Respondents also revealed that 14% of children and young adults had received > 100 CT scans for shunt evaluation with the median being 25 scans (IQR 20).

Conclusions: Caregivers desire and deserve to be empowered through education and social support, and continuously engaged through sharing decisions and co-designing care plans. The neurosurgical community is in an ideal position to collaborate with radiologists, primary care providers, and parents in the development and testing of credible, high-quality online and social media resources.
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http://dx.doi.org/10.1007/s00381-020-04822-0DOI Listing
February 2021

A network-based microfoundation of Granovetter's threshold model for social tipping.

Sci Rep 2020 07 8;10(1):11202. Epub 2020 Jul 8.

FutureLab Earth Resilience in the Anthropocene, Earth System Analysis, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 60 12 03, 14412, Potsdam, Germany.

Social tipping, where minorities trigger larger populations to engage in collective action, has been suggested as one key aspect in addressing contemporary global challenges. Here, we refine Granovetter's widely acknowledged theoretical threshold model of collective behavior as a numerical modelling tool for understanding social tipping processes and resolve issues that so far have hindered such applications. Based on real-world observations and social movement theory, we group the population into certain or potential actors, such that - in contrast to its original formulation - the model predicts non-trivial final shares of acting individuals. Then, we use a network cascade model to explain and analytically derive that previously hypothesized broad threshold distributions emerge if individuals become active via social interaction. Thus, through intuitive parameters and low dimensionality our refined model is adaptable to explain the likelihood of engaging in collective behavior where social-tipping-like processes emerge as saddle-node bifurcations and hysteresis.
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http://dx.doi.org/10.1038/s41598-020-67102-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343878PMC
July 2020

Normalised degree variance.

Appl Netw Sci 2020 22;5(1):32. Epub 2020 Jun 22.

School of Engineering, Institute for Digital Communications, University of Edinburgh, West Mains Rd, Edinburgh, EH9 3FB UK.

Finding graph indices which are unbiased to network size and density is of high importance both within a given field and across fields for enhancing comparability of modern network science studies. The degree variance is an important metric for characterising network degree heterogeneity. Here, we provide an analytically valid normalisation of degree variance to replace previous normalisations which are either invalid or not applicable to all networks. It is shown that this normalisation provides equal values for graphs and their complements; it is maximal in the star graph (and its complement); and its expected value is constant with respect to density for Erdös-Rényi (ER) random graphs of the same size. We strengthen these results with model observations in ER random graphs, random geometric graphs, scale-free networks, random hierarchy networks and resting-state brain networks, showing that the proposed normalisation is generally less affected by both network size and density than previous normalisation attempts. The closed form expression proposed also benefits from high computational efficiency and straightforward mathematical analysis. Analysis of 184 real-world binary networks across different disciplines shows that normalised degree variance is not correlated with average degree and is robust to node and edge subsampling. Comparisons across subdomains of biological networks reveals greater degree heterogeneity among brain connectomes and food webs than in protein interaction networks.
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http://dx.doi.org/10.1007/s41109-020-00273-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319291PMC
June 2020

Mass Cytometry Reveals Global Immune Remodeling with Multi-lineage Hypersensitivity to Type I Interferon in Down Syndrome.

Cell Rep 2019 11;29(7):1893-1908.e4

Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Molecular, Cellular and Developmental Biology, University of Colorado Boulder, Boulder, CO 80302, USA. Electronic address:

People with Down syndrome (DS; trisomy 21) display a different disease spectrum relative to the general population, including lower rates of solid malignancies and higher incidence of neurological and autoimmune conditions. However, the mechanisms driving this unique clinical profile await elucidation. We completed a deep mapping of the immune system in adults with DS using mass cytometry to evaluate 100 immune cell types, which revealed global immune dysregulation consistent with chronic inflammation, including key changes in the myeloid and lymphoid cell compartments. Furthermore, measurement of interferon-inducible phosphorylation events revealed widespread hypersensitivity to interferon-α in DS, with cell-type-specific variations in downstream intracellular signaling. Mechanistically, this could be explained by overexpression of the interferon receptors encoded on chromosome 21, as demonstrated by increased IFNAR1 surface expression in all immune lineages tested. These results point to interferon-driven immune dysregulation as a likely contributor to the developmental and clinical hallmarks of DS.
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http://dx.doi.org/10.1016/j.celrep.2019.10.038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871766PMC
November 2019

Trisomy 21 dysregulates T cell lineages toward an autoimmunity-prone state associated with interferon hyperactivity.

Proc Natl Acad Sci U S A 2019 11 7;116(48):24231-24241. Epub 2019 Nov 7.

Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, CO 80045;

Trisomy 21 (T21) causes Down syndrome (DS), a condition characterized by high prevalence of autoimmune disorders. However, the molecular and cellular mechanisms driving this phenotype remain unclear. Building upon our previous finding that T cells from people with DS show increased expression of interferon (IFN)-stimulated genes, we have completed a comprehensive characterization of the peripheral T cell compartment in adults with DS with and without autoimmune conditions. CD8+ T cells from adults with DS are depleted of naïve subsets and enriched for differentiated subsets, express higher levels of markers of activation and senescence (e.g., IFN-γ, Granzyme B, PD-1, KLRG1), and overproduce cytokines tied to autoimmunity (e.g., TNF-α). Conventional CD4+ T cells display increased differentiation, polarization toward the Th1 and Th1/17 states, and overproduction of the autoimmunity-related cytokines IL-17A and IL-22. Plasma cytokine analysis confirms elevation of multiple autoimmunity-related cytokines (e.g., TNF-α, IL17A-D, IL-22) in people with DS, independent of diagnosis of autoimmunity. Although Tregs are more abundant in DS, functional assays show that CD8+ and CD4+ effector T cells with T21 are resistant to Treg-mediated suppression, regardless of Treg karyotype. Transcriptome analysis of white blood cells and T cells reveals strong signatures of T cell differentiation and activation that correlate positively with IFN hyperactivity. Finally, mass cytometry analysis of 8 IFN-inducible phosphoepitopes demonstrates that T cell subsets with T21 show elevated levels of basal IFN signaling and hypersensitivity to IFN-α stimulation. Therefore, these results point to T cell dysregulation associated with IFN hyperactivity as a contributor to autoimmunity in DS.
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http://dx.doi.org/10.1073/pnas.1908129116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883781PMC
November 2019

Trisomy 21 activates the kynurenine pathway via increased dosage of interferon receptors.

Nat Commun 2019 10 18;10(1):4766. Epub 2019 Oct 18.

Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.

Trisomy 21 (T21) causes Down syndrome (DS), affecting immune and neurological function by ill-defined mechanisms. Here we report a large metabolomics study of plasma and cerebrospinal fluid, showing in independent cohorts that people with DS produce elevated levels of kynurenine and quinolinic acid, two tryptophan catabolites with potent immunosuppressive and neurotoxic properties, respectively. Immune cells of people with DS overexpress IDO1, the rate-limiting enzyme in the kynurenine pathway (KP) and a known interferon (IFN)-stimulated gene. Furthermore, the levels of IFN-inducible cytokines positively correlate with KP dysregulation. Using metabolic tracing assays, we show that overexpression of IFN receptors encoded on chromosome 21 contribute to enhanced IFN stimulation, thereby causing IDO1 overexpression and kynurenine overproduction in cells with T21. Finally, a mouse model of DS carrying triplication of IFN receptors exhibits KP dysregulation. Together, our results reveal a mechanism by which T21 could drive immunosuppression and neurotoxicity in DS.
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http://dx.doi.org/10.1038/s41467-019-12739-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800452PMC
October 2019

Shooting for the Moon.

Authors:
Keith T Smith

Science 2019 Jul;365(6450):232-233

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http://dx.doi.org/10.1126/science.aay6006DOI Listing
July 2019

Radiology Resident Journal Club: Enhancements Add Educational Value.

Acad Radiol 2020 04 5;27(4):591-595. Epub 2019 Jul 5.

Department of Radiology, University of North Carolina School of Medicine, 321 South Columbia Street, Chapel Hill, NC 27514. Electronic address:

Rationale And Objectives: Resident journal clubs are essential to develop skills to critically appraise existing literature. However, most reports of journal clubs focus on logistics of the activity and less on established roles of those involved. Our objective is to report on an innovative journal club from the perspective of key participants.

Materials And Methods: Journal club schedule, assignments, evaluations, and analysis are proffered from our institution. The journal club goals were formulated as: (1) improving resident understanding of research (biostatistical and epidemiologic) methods and statistical concepts, (2) teaching critical appraisal skills, and (3) promoting the use of evidence-based medicine. Each session's format is interactive, consisting of a 10 minute lecture with radiology examples of a research or statistical concept, followed by a journal club style discussion. Crucial to the success of this curriculum has been input and engagement of multiple parties: radiology residents, epidemiologist directors, and subspecialist clinician educator faculty members.

Conclusion: A well-thought out and well-run resident journal club offers numerous solutions to radiology residencies. To residency program leadership and to each individual resident annually, resident journal club offers cutting edge medical knowledge, interactive conferences in the formal didactic curriculum, resident training in critical thinking skills and research design, resident training in interpersonal and communication skills, opportunity for residents to be teachers, and expanded resident interprofessional education. It meets Accreditation Council for Graduate Medical Education common program, Residency Review Committee diagnostic radiology program, and American Board of Radiology Milestones requirements.
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http://dx.doi.org/10.1016/j.acra.2019.06.007DOI Listing
April 2020

On neighbourhood degree sequences of complex networks.

Authors:
Keith M Smith

Sci Rep 2019 06 6;9(1):8340. Epub 2019 Jun 6.

Usher Institute of Population Health Science and Informatics, University of Edinburgh, 9 BioQuarter, Little France, Edinburgh, EH16 4UX, UK.

Network topology is a fundamental aspect of network science that allows us to gather insights into the complicated relational architectures of the world we inhabit. We provide a first specific study of neighbourhood degree sequences in complex networks. We consider how to explicitly characterise important physical concepts such as similarity, heterogeneity and organization in these sequences, as well as updating the notion of hierarchical complexity to reflect previously unnoticed organizational principles. We also point out that neighbourhood degree sequences are related to a powerful subtree kernel for unlabeled graph classification. We study these newly defined sequence properties in a comprehensive array of graph models and over 200 real-world networks. We find that these indices are neither highly correlated with each other nor with classical network indices. Importantly, the sequences of a wide variety of real world networks are found to have greater similarity and organisation than is expected for networks of their given degree distributions. Notably, while biological, social and technological networks all showed consistently large neighbourhood similarity and organisation, hierarchical complexity was not a consistent feature of real world networks. Neighbourhood degree sequences are an interesting tool for describing unique and important characteristics of complex networks.
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http://dx.doi.org/10.1038/s41598-019-44907-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554413PMC
June 2019

Hierarchical complexity of the adult human structural connectome.

Neuroimage 2019 05 14;191:205-215. Epub 2019 Feb 14.

Usher Institute for Population Health Science and Informatics, Medical School, University of Edinburgh, Edinburgh, EH16 4UX, UK.

The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology.
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http://dx.doi.org/10.1016/j.neuroimage.2019.02.028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6503942PMC
May 2019

Diving within Saturn's rings.

Authors:
Keith T Smith

Science 2018 Oct;362(6410):44-45

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http://dx.doi.org/10.1126/science.aav4175DOI Listing
October 2018

Maximizing Benefit and Minimizing Risk in Medical Imaging Use: An Educational Primer for Health Care Professions Students.

J Med Educ Curric Dev 2018 Jan-Dec;5:2382120518798812. Epub 2018 Sep 10.

Department of Radiology, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

"I am not young enough to know everything."Oscar Wilde.

Background: There is insufficient knowledge among providers and patients/caregivers of ionizing radiation exposure from medical imaging examinations. This study used a brief, interactive educational intervention targeting the topics of best imaging practices and radiation safety early in health professions students' training. The authors hypothesized that public health, medical, and physician assistant students who receive early education for imaging appropriateness and radiation safety will undergo a change in attitude and have increased awareness and knowledge of these topics.

Materials And Methods: The authors conducted a 1.5-hour interactive educational intervention focusing on medical imaging utilization and radiation safety. Students were presented with a pre/postquestionnaire and data were analyzed using tests and multivariate analysis of variance.

Results: A total of 301 students were enrolled in the study. There was 58% ( < .01) and 85% ( < .01) improvement in attitude and knowledge regarding appropriateness of imaging, respectively. The authors also found an 8% increase ( < .01) in students who thought informed consent should be obtained prior to pediatric computed tomographic imaging. Physical assistant students were more likely than medical students to prefer obtaining informed consent at baseline ( = .03).

Conclusions: A brief educational session provided to health professions students early in their education showed an increased awareness and knowledge of the utility, limitations, and risks associated with medical imaging. Incorporation of a best imagining practice educational session early during medical education may promote more thoughtful imaging decisions for future medical providers.
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http://dx.doi.org/10.1177/2382120518798812DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131289PMC
September 2018

Bi-plane and single plane angiography: a study to compare contrast usage and radiation doses for adult cardiac patients in diagnostic studies.

Br J Radiol 2019 Jan 21;92(1093):20180367. Epub 2018 Sep 21.

3 Queensland University of Technology, George St , Brisbane , Queensland, Australia.

Objective:: This study compares the performance of bi-plane coronary angiography against single plane angiography in terms of the volume of contrast used (ml) and the total dose-area product (DAP) (μGym) to the patient measured directly via flat panel detectors.

Methods:: A total of 5176 adult diagnostic cardiac angiograms from a hospital in Brisbane, Australia were retrospectively studied. Patients with aortograms, iliac or femoral artery imaging, and stenting or graft interventions were excluded. Student's t-tests were used to compare means, and confounding variables were compared using multivariate regression. This quantified the effects of bi-plane system use holding constant other factors (e.g.) body mass index (BMI), age, room, sex, number of digital acquisitions and fluoro time.

Results:: Bi-plane imaging had an average difference in mean contrast use of -15.1 ml [15.5% 95% confidence interval (CI) (-13.2, -17.0) p<0.001], multivariate regression demonstrated a -27.0 ml reduction in contrast use [28% 95% CI (-29.0, -24.83) p<0.0001] when the significant effects of fluoro time, number of digital acquisitions, BMI and sex were held constant. Bi-plane imaging had an average difference in mean DAP of + 887.1 μGym [23% 95% CI (+1110.7, +663.4) p < 0.001], whilst multivariate regression found a +628.3 Gym increase in DAP [16% 95% CI (+467.5, +789.3) p<0.001] when the significant effects of fluoro time, number of digital acquisitions, BMI and sex were held constant.

Conclusion:: These results demonstrate that bi-plane imaging uses less contrast media than single-plane imaging for coronary angiography at the expense of more radiation. Bi-plane imaging may be preferable in patients with renal impairment, however single plane imaging may be preferable in those without renal impairment.

Advances In Knowledge:: This is a large cohort and statistically comprehensive study comparing bi-plane and single plane coronary angiography. Other studies 4, 5, 6, 12 have used Student's t-tests to measure the difference between means, however this provides no causative information on the differences found. This study provides a view of the causative impact of bi-plane usage on DAP and contrast use via multivariate regression modelling.
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http://dx.doi.org/10.1259/bjr.20180367DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435067PMC
January 2019

LCCC 1025: a phase II study of everolimus, trastuzumab, and vinorelbine to treat progressive HER2-positive breast cancer brain metastases.

Breast Cancer Res Treat 2018 Oct 25;171(3):637-648. Epub 2018 Jun 25.

Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 170 Manning Drive, CB #7305, Chapel Hill, NC, 27599-7305, USA.

Purpose: HER2 + breast cancer (BC) is an aggressive subtype with high rates of brain metastases (BCBM). Two-thirds of HER2 + BCBM demonstrate activation of the PI3K/mTOR pathway driving resistance to anti-HER2 therapy. This phase II study evaluated everolimus (E), a brain-permeable mTOR inhibitor, trastuzumab (T), and vinorelbine (V) in patients with HER2 + BCBM.

Patients And Methods: Eligible patients had progressive HER2 + BCBM. The primary endpoint was intracranial response rate (RR); secondary objectives were CNS clinical benefit rate (CBR), extracranial RR, time to progression (TTP), overall survival (OS), and targeted sequencing of tumors from enrolled patients. A two-stage design distinguished intracranial RR of 5% versus 20%.

Results: 32 patients were evaluable for toxicity, 26 for efficacy. Intracranial RR was 4% (1 PR). CNS CBR at 6 mos was 27%; at 3 mos 65%. Median intracranial TTP was 3.9 mos (95% CI 2.2-5). OS was 12.2 mos (95% CI 0.6-20.2). Grade 3-4 toxicities included neutropenia (41%), anemia (16%), and stomatitis (16%). Mutations in TP53 and PIK3CA were common in BCBM. Mutations in the PI3K/mTOR pathway were not associated with response. ERBB2 amplification was higher in BCBM compared to primary BC; ERBB2 amplification in the primary BC trended toward worse OS.

Conclusion: While intracranial RR to ETV was low in HER2 + BCBM patients, one-third achieved CNS CBR; TTP/OS was similar to historical control. No new toxicity signals were observed. Further analysis of the genomic underpinnings of BCBM to identify tractable prognostic and/or predictive biomarkers is warranted.

Clinical Trial: (NCT01305941).
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http://dx.doi.org/10.1007/s10549-018-4852-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779035PMC
October 2018

The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.

Neuroimage 2019 01 22;185:891-905. Epub 2018 Mar 22.

Institute of Child Development, University of Minnesota, USA; Department of Pediatrics, University of Minnesota, USA. Electronic address:

The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain-behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high-resolution structural MRI (T1-and T2-weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0-5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well-established behavioral assessments during this time period will yield an invaluable resource for the scientific community.
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http://dx.doi.org/10.1016/j.neuroimage.2018.03.049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6151176PMC
January 2019