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Molecular Architecture of the Helicobacter pylori Cag Type IV Secretion System.
Hu B, Khara P, Song L, Lin AS, Frick-Cheng AE, Harvey ML, Cover TL, Christie PJ
(2019) MBio 10:
MeSH Terms: Antigens, Bacterial, Bacterial Proteins, Cryoelectron Microscopy, Genomic Islands, Helicobacter pylori, Humans, Type IV Secretion Systems
Show Abstract · Added July 14, 2019
colonizes about half of humans worldwide, and its presence in the gastric mucosa is associated with an increased risk of gastric adenocarcinoma, gastric lymphoma, and peptic ulcer disease. strains carrying the pathogenicity island (PAI) are associated with increased risk of disease progression. The PAI encodes the Cag type IV secretion system (Cag), which delivers the CagA oncoprotein and other effector molecules into human gastric epithelial cells. We visualized structures of native and mutant Cag machines on the cell envelope by cryoelectron tomography. Individual cells contain multiple Cag nanomachines, each composed of a wheel-shaped outer membrane complex (OMC) with 14-fold symmetry and an inner membrane complex (IMC) with 6-fold symmetry. CagX, CagY, and CagM are required for assembly of the OMC, whereas strains lacking Cag3 and CagT produce outer membrane complexes lacking peripheral components. The IMC, which has never been visualized in detail, is configured as six tiers in cross-section view and three concentric rings surrounding a central channel in end-on view. The IMC contains three T4SS ATPases: (i) VirB4-like CagE, arranged as a hexamer of dimers at the channel entrance; (ii) a hexamer of VirB11-like Cagα, docked at the base of the CagE hexamer; and (iii) VirD4-like Cagβ and other unspecified Cag subunits, associated with the stacked CagE/Cagα complex and forming the outermost rings. The Cag and recently solved Dot/Icm system comprise new structural prototypes for the T4SS superfamily. Bacterial type IV secretion systems (T4SSs) have been phylogenetically grouped into two subfamilies. The T4ASSs, represented by the VirB/VirD4, include "minimized" machines assembled from 12 VirB- and VirD4-like subunits and compositionally larger systems such as the Cag T4BSSs encompass systems closely related in subunit composition to the Dot/Icm Here, we present structures of native and mutant Cag machines determined by cryoelectron tomography. We identify distinct outer and inner membrane complexes and, for the first time, visualize structural contributions of all three "signature" ATPases of T4SSs at the cytoplasmic entrance of the translocation channel. Despite their evolutionary divergence, the Cag aligns structurally much more closely to the Dot/Icm than an available VirB/VirD4 subcomplex. Our findings highlight the diversity of T4SSs and suggest a structural classification scheme in which T4SSs are grouped as minimized VirB/VirD4-like or larger Cag-like and Dot/Icm-like systems.
Copyright © 2019 Hu et al.
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Multi-tissue transcriptome analyses identify genetic mechanisms underlying neuropsychiatric traits.
Gamazon ER, Zwinderman AH, Cox NJ, Denys D, Derks EM
(2019) Nat Genet 51: 933-940
MeSH Terms: Algorithms, Computational Biology, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mental Disorders, Organ Specificity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Transcriptome
Show Abstract · Added July 17, 2019
The genetic architecture of psychiatric disorders is characterized by a large number of small-effect variants located primarily in non-coding regions, suggesting that the underlying causal effects may influence disease risk by modulating gene expression. We provide comprehensive analyses using transcriptome data from an unprecedented collection of tissues to gain pathophysiological insights into the role of the brain, neuroendocrine factors (adrenal gland) and gastrointestinal systems (colon) in psychiatric disorders. In each tissue, we perform PrediXcan analysis and identify trait-associated genes for schizophrenia (n associations = 499; n unique genes = 275), bipolar disorder (n associations = 17; n unique genes = 13), attention deficit hyperactivity disorder (n associations = 19; n unique genes = 12) and broad depression (n associations = 41; n unique genes = 31). Importantly, both PrediXcan and summary-data-based Mendelian randomization/heterogeneity in dependent instruments analyses suggest potentially causal genes in non-brain tissues, showing the utility of these tissues for mapping psychiatric disease genetic predisposition. Our analyses further highlight the importance of joint tissue approaches as 76% of the genes were detected only in difficult-to-acquire tissues.
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Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer.
Ferreira MA, Gamazon ER, Al-Ejeh F, Aittomäki K, Andrulis IL, Anton-Culver H, Arason A, Arndt V, Aronson KJ, Arun BK, Asseryanis E, Azzollini J, Balmaña J, Barnes DR, Barrowdale D, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Białkowska K, Blomqvist C, Bogdanova NV, Bojesen SE, Bolla MK, Borg A, Brauch H, Brenner H, Broeks A, Burwinkel B, Caldés T, Caligo MA, Campa D, Campbell I, Canzian F, Carter J, Carter BD, Castelao JE, Chang-Claude J, Chanock SJ, Christiansen H, Chung WK, Claes KBM, Clarke CL, EMBRACE Collaborators, GC-HBOC Study Collaborators, GEMO Study Collaborators, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, de la Hoya M, Dennis J, Devilee P, Diez O, Dörk T, Dunning AM, Dwek M, Eccles DM, Ejlertsen B, Ellberg C, Engel C, Eriksson M, Fasching PA, Fletcher O, Flyger H, Friedman E, Frost D, Gabrielson M, Gago-Dominguez M, Ganz PA, Gapstur SM, Garber J, García-Closas M, García-Sáenz JA, Gaudet MM, Giles GG, Glendon G, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Greene MH, Gronwald J, Guénel P, Haiman CA, Hall P, Hamann U, He W, Heyworth J, Hogervorst FBL, Hollestelle A, Hoover RN, Hopper JL, Hulick PJ, Humphreys K, Imyanitov EN, ABCTB Investigators, HEBON Investigators, BCFR Investigators, Isaacs C, Jakimovska M, Jakubowska A, James PA, Janavicius R, Jankowitz RC, John EM, Johnson N, Joseph V, Karlan BY, Khusnutdinova E, Kiiski JI, Ko YD, Jones ME, Konstantopoulou I, Kristensen VN, Laitman Y, Lambrechts D, Lazaro C, Leslie G, Lester J, Lesueur F, Lindström S, Long J, Loud JT, Lubiński J, Makalic E, Mannermaa A, Manoochehri M, Margolin S, Maurer T, Mavroudis D, McGuffog L, Meindl A, Menon U, Michailidou K, Miller A, Montagna M, Moreno F, Moserle L, Mulligan AM, Nathanson KL, Neuhausen SL, Nevanlinna H, Nevelsteen I, Nielsen FC, Nikitina-Zake L, Nussbaum RL, Offit K, Olah E, Olopade OI, Olsson H, Osorio A, Papp J, Park-Simon TW, Parsons MT, Pedersen IS, Peixoto A, Peterlongo P, Pharoah PDP, Plaseska-Karanfilska D, Poppe B, Presneau N, Radice P, Rantala J, Rennert G, Risch HA, Saloustros E, Sanden K, Sawyer EJ, Schmidt MK, Schmutzler RK, Sharma P, Shu XO, Simard J, Singer CF, Soucy P, Southey MC, Spinelli JJ, Spurdle AB, Stone J, Swerdlow AJ, Tapper WJ, Taylor JA, Teixeira MR, Terry MB, Teulé A, Thomassen M, Thöne K, Thull DL, Tischkowitz M, Toland AE, Torres D, Truong T, Tung N, Vachon CM, van Asperen CJ, van den Ouweland AMW, van Rensburg EJ, Vega A, Viel A, Wang Q, Wappenschmidt B, Weitzel JN, Wendt C, Winqvist R, Yang XR, Yannoukakos D, Ziogas A, Kraft P, Antoniou AC, Zheng W, Easton DF, Milne RL, Beesley J, Chenevix-Trench G
(2019) Nat Commun 10: 1741
MeSH Terms: Breast Neoplasms, Female, Gene Expression Profiling, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Quantitative Trait Loci
Show Abstract · Added July 17, 2019
Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
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Intrinsic functional architecture of the non-human primate spinal cord derived from fMRI and electrophysiology.
Wu TL, Yang PF, Wang F, Shi Z, Mishra A, Wu R, Chen LM, Gore JC
(2019) Nat Commun 10: 1416
MeSH Terms: Action Potentials, Animals, Electrophysiological Phenomena, Haplorhini, Humans, Magnetic Resonance Imaging, Physical Stimulation, Reproducibility of Results, Rest, Spinal Cord, Spinal Cord Dorsal Horn, Touch
Show Abstract · Added July 11, 2019
Resting-state functional MRI (rsfMRI) has recently revealed correlated signals in the spinal cord horns of monkeys and humans. However, the interpretation of these rsfMRI correlations as indicators of functional connectivity in the spinal cord remains unclear. Here, we recorded stimulus-evoked and spontaneous spiking activity and local field potentials (LFPs) from monkey spinal cord in order to validate fMRI measures. We found that both BOLD and electrophysiological signals elicited by tactile stimulation co-localized to the ipsilateral dorsal horn. Temporal profiles of stimulus-evoked BOLD signals covaried with LFP and multiunit spiking in a similar way to those observed in the brain. Functional connectivity of dorsal horns exhibited a U-shaped profile along the dorsal-intermediate-ventral axis. Overall, these results suggest that there is an intrinsic functional architecture within the gray matter of a single spinal segment, and that rsfMRI signals at high field directly reflect this underlying spontaneous neuronal activity.
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Aberrant FGFR signaling mediates resistance to CDK4/6 inhibitors in ER+ breast cancer.
Formisano L, Lu Y, Servetto A, Hanker AB, Jansen VM, Bauer JA, Sudhan DR, Guerrero-Zotano AL, Croessmann S, Guo Y, Ericsson PG, Lee KM, Nixon MJ, Schwarz LJ, Sanders ME, Dugger TC, Cruz MR, Behdad A, Cristofanilli M, Bardia A, O'Shaughnessy J, Nagy RJ, Lanman RB, Solovieff N, He W, Miller M, Su F, Shyr Y, Mayer IA, Balko JM, Arteaga CL
(2019) Nat Commun 10: 1373
MeSH Terms: Aminopyridines, Animals, Antineoplastic Agents, Hormonal, Antineoplastic Combined Chemotherapy Protocols, Breast Neoplasms, Circulating Tumor DNA, Cyclin D1, Cyclin-Dependent Kinase 4, Cyclin-Dependent Kinase 6, Drug Resistance, Neoplasm, Female, Fulvestrant, High-Throughput Nucleotide Sequencing, Humans, MCF-7 Cells, Mice, Mutation, Naphthalenes, Piperazines, Progression-Free Survival, Proportional Hazards Models, Protein Kinase Inhibitors, Purines, Pyrazoles, Pyridines, Quinolines, Quinoxalines, Receptor, Fibroblast Growth Factor, Type 1, Receptor, Fibroblast Growth Factor, Type 2, Receptors, Estrogen, Signal Transduction, Xenograft Model Antitumor Assays
Show Abstract · Added April 2, 2019
Using an ORF kinome screen in MCF-7 cells treated with the CDK4/6 inhibitor ribociclib plus fulvestrant, we identified FGFR1 as a mechanism of drug resistance. FGFR1-amplified/ER+ breast cancer cells and MCF-7 cells transduced with FGFR1 were resistant to fulvestrant ± ribociclib or palbociclib. This resistance was abrogated by treatment with the FGFR tyrosine kinase inhibitor (TKI) lucitanib. Addition of the FGFR TKI erdafitinib to palbociclib/fulvestrant induced complete responses of FGFR1-amplified/ER+ patient-derived-xenografts. Next generation sequencing of circulating tumor DNA (ctDNA) in 34 patients after progression on CDK4/6 inhibitors identified FGFR1/2 amplification or activating mutations in 14/34 (41%) post-progression specimens. Finally, ctDNA from patients enrolled in MONALEESA-2, the registration trial of ribociclib, showed that patients with FGFR1 amplification exhibited a shorter progression-free survival compared to patients with wild type FGFR1. Thus, we propose breast cancers with FGFR pathway alterations should be considered for trials using combinations of ER, CDK4/6 and FGFR antagonists.
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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk.
Huckins LM, Dobbyn A, Ruderfer DM, Hoffman G, Wang W, Pardiñas AF, Rajagopal VM, Als TD, T Nguyen H, Girdhar K, Boocock J, Roussos P, Fromer M, Kramer R, Domenici E, Gamazon ER, Purcell S, CommonMind Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, iPSYCH-GEMS Schizophrenia Working Group, Demontis D, Børglum AD, Walters JTR, O'Donovan MC, Sullivan P, Owen MJ, Devlin B, Sieberts SK, Cox NJ, Im HK, Sklar P, Stahl EA
(2019) Nat Genet 51: 659-674
MeSH Terms: Brain, Case-Control Studies, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk, Schizophrenia, Transcriptome
Show Abstract · Added July 17, 2019
Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.
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Vagus Nerve Stimulation for the Treatment of Epilepsy.
González HFJ, Yengo-Kahn A, Englot DJ
(2019) Neurosurg Clin N Am 30: 219-230
MeSH Terms: Epilepsy, Humans, Seizures, Treatment Outcome, Vagus Nerve Stimulation
Show Abstract · Added June 22, 2019
Vagus nerve stimulation (VNS) was the first neuromodulation device approved for treatment of epilepsy. In more than 20 years of study, VNS has consistently demonstrated efficacy in treating epilepsy. After 2 years, approximately 50% of patients experience at least 50% reduced seizure frequency. Adverse events with VNS treatment are rare and include surgical adverse events (including infection, vocal cord paresis, and so forth) and stimulation side effects (hoarseness, voice change, and cough). Future developments in VNS, including closed-loop and noninvasive stimulation, may reduce side effects or increase efficacy of VNS.
Copyright © 2018 Elsevier Inc. All rights reserved.
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Characterization of the hemodynamic response function in white matter tracts for event-related fMRI.
Li M, Newton AT, Anderson AW, Ding Z, Gore JC
(2019) Nat Commun 10: 1140
MeSH Terms: Adult, Cerebral Cortex, Cerebrovascular Circulation, Female, Gray Matter, Healthy Volunteers, Hemodynamics, Hemoglobins, Humans, Magnetic Resonance Imaging, Male, Nerve Net, Oxygen, Pattern Recognition, Visual, Stroop Test, White Matter
Show Abstract · Added March 26, 2019
Accurate estimates of the BOLD hemodynamic response function (HRF) are crucial for the interpretation and analysis of event-related functional MRI data. To date, however, there have been no comprehensive measurements of the HRF in white matter (WM) despite increasing evidence that BOLD signals in WM change after a stimulus. We performed an event-related cognitive task (Stroop color-word interference) to measure the HRF in selected human WM pathways. The task was chosen in order to produce robust, distributed centers of activity throughout the cortex. To measure the HRF in WM, fiber tracts were reconstructed between each pair of activated cortical areas. We observed clear task-specific HRFs with reduced magnitudes, delayed onsets and prolonged initial dips in WM tracts compared with activated grey matter, thus calling for significant changes to current standard models for accurately characterizing the HRFs in WM and for modifications of standard methods of analysis of functional imaging data.
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16 MeSH Terms
A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research.
Conway CC, Forbes MK, Forbush KT, Fried EI, Hallquist MN, Kotov R, Mullins-Sweatt SN, Shackman AJ, Skodol AE, South SC, Sunderland M, Waszczuk MA, Zald DH, Afzali MH, Bornovalova MA, Carragher N, Docherty AR, Jonas KG, Krueger RF, Patalay P, Pincus AL, Tackett JL, Reininghaus U, Waldman ID, Wright AGC, Zimmermann J, Bach B, Bagby RM, Chmielewski M, Cicero DC, Clark LA, Dalgleish T, DeYoung CG, Hopwood CJ, Ivanova MY, Latzman RD, Patrick CJ, Ruggero CJ, Samuel DB, Watson D, Eaton NR
(2019) Perspect Psychol Sci 14: 419-436
MeSH Terms: Heuristics, Humans, Mental Disorders, Models, Theoretical, Research Design, Terminology as Topic
Show Abstract · Added April 15, 2019
For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.
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6 MeSH Terms
Gastroesophageal Reflux Induces Protein Adducts in the Esophagus.
Caspa Gokulan R, Adcock JM, Zagol-Ikapitte I, Mernaugh R, Williams P, Washington KM, Boutaud O, Oates JA, Dikalov SI, Zaika AI
(2019) Cell Mol Gastroenterol Hepatol 7: 480-482.e7
MeSH Terms: Acetylcysteine, Animals, Benzylamines, Bile Acids and Salts, Cell Line, Cyclic N-Oxides, Esophagus, Gastroesophageal Reflux, Humans, Lipids, Mice, Spin Labels, Tumor Suppressor Protein p53
Added March 26, 2019
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13 MeSH Terms