A Multiethnic Genome-Wide Analysis of 44,039 Individuals Identifies 41 New Loci Associated with Central Corneal Thickness
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Murine MPDZ-Linked Hydrocephalus Is Caused by Hyperpermeability of the Choroid Plexus
Thomas Jefferson University Jefferson Digital Commons Cardeza Foundation for Hematologic Research Sidney Kimmel Medical College 1-1-2019 Murine MPDZ-linked hydrocephalus is caused by hyperpermeability of the choroid plexus. Junning Yang Thomas Jefferson University Claire Simonneau Thomas Jefferson University Robert Kilker Thomas Jefferson University Laura Oakley ThomasFollow this Jeff anderson additional University works at: https://jdc.jefferson.edu/cardeza_foundation Part of the Medical Pathology Commons Matthew D. Byrne ThomasLet us Jeff knowerson Univ howersity access to this document benefits ouy Recommended Citation See next page for additional authors Yang, Junning; Simonneau, Claire; Kilker, Robert; Oakley, Laura; Byrne, Matthew D.; Nichtova, Zuzana; Stefanescu, Ioana; Pardeep-Kumar, Fnu; Tripathi, Sushil; Londin, Eric; Saugier-Veber, Pascale; Willard, Belinda; Thakur, Mathew; Pickup, Stephen; Ishikawa, Hiroshi; Schroten, Horst; Smeyne, Richard; and Horowitz, Arie, "Murine MPDZ-linked hydrocephalus is caused by hyperpermeability of the choroid plexus." (2019). Cardeza Foundation for Hematologic Research. Paper 49. https://jdc.jefferson.edu/cardeza_foundation/49 This Article is brought to you for free and open access by the Jefferson Digital Commons. The Jefferson Digital Commons is a service of Thomas Jefferson University's Center for Teaching and Learning (CTL). The Commons is a showcase for Jefferson books and journals, peer-reviewed scholarly publications, unique historical collections from the University archives, and teaching tools. The Jefferson Digital Commons allows researchers and interested readers anywhere in the world to learn about and keep up to date with Jefferson scholarship. This article has been accepted for inclusion in Cardeza Foundation for Hematologic Research by an authorized administrator of the Jefferson Digital Commons. For more information, please contact: [email protected]. -
The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
(Dominance) Effects of Genetic Variants Associated with Refractive Error And
Molecular Genetics and Genomics https://doi.org/10.1007/s00438-020-01666-w ORIGINAL ARTICLE Non‑additive (dominance) efects of genetic variants associated with refractive error and myopia Alfred Pozarickij1 · Cathy Williams2 · Jeremy A. Guggenheim1 · and the UK Biobank Eye and Vision Consortium Received: 26 November 2019 / Accepted: 16 March 2020 © The Author(s) 2020 Abstract Genome-wide association studies (GWAS) have revealed that the genetic contribution to certain complex diseases is well- described by Fisher’s infnitesimal model in which a vast number of polymorphisms each confer a small efect. Under Fisher’s model, variants have additive efects both across loci and within loci. However, the latter assumption is at odds with the com- mon observation of dominant or recessive rare alleles responsible for monogenic disorders. Here, we searched for evidence of non-additive (dominant or recessive) efects for GWAS variants known to confer susceptibility to the highly heritable quantitative trait, refractive error. Of 146 GWAS variants examined in a discovery sample of 228,423 individuals whose refractive error phenotype was inferred from their age-of-onset of spectacle wear, only 8 had even nominal evidence (p < 0.05) of non-additive efects. In a replication sample of 73,577 individuals who underwent direct assessment of refractive error, 1 of these 8 variants had robust independent evidence of non-additive efects (rs7829127 within ZMAT4, p = 4.76E−05) while a further 2 had suggestive evidence (rs35337422 in RD3L, p = 7.21E−03 and rs12193446 in LAMA2, p = 2.57E−02). Account- ing for non-additive efects had minimal impact on the accuracy of a polygenic risk score for refractive error (R2 = 6.04% vs. -
Structural Insights Into Ubiquitin Recognition and Ufd1 Interaction of Npl4
ARTICLE https://doi.org/10.1038/s41467-019-13697-y OPEN Structural insights into ubiquitin recognition and Ufd1 interaction of Npl4 Yusuke Sato1,2,3,5,7, Hikaru Tsuchiya4,7, Atsushi Yamagata1,2,3,6, Kei Okatsu1,2, Keiji Tanaka4, Yasushi Saeki 4* & Shuya Fukai 1,2,3* Npl4 is likely to be the most upstream factor recognizing Lys48-linked polyubiquitylated substrates in the proteasomal degradation pathway in yeast. Along with Ufd1, Npl4 forms a 1234567890():,; heterodimer (UN), and functions as a cofactor for the Cdc48 ATPase. Here, we report the crystal structures of yeast Npl4 in complex with Lys48-linked diubiquitin and with the Npl4- binding motif of Ufd1. The distal and proximal ubiquitin moieties of Lys48-linked diubiquitin primarily interact with the C-terminal helix and N-terminal loop of the Npl4 C-terminal domain (CTD), respectively. Mutational analysis suggests that the CTD contributes to linkage selectivity and initial binding of ubiquitin chains. Ufd1 occupies a hydrophobic groove of the Mpr1/Pad1 N-terminal (MPN) domain of Npl4, which corresponds to the catalytic groove of the MPN domain of JAB1/MPN/Mov34 metalloenzyme (JAMM)-family deubiquitylating enzyme. This study provides important structural insights into the polyubiquitin chain recognition by the Cdc48–UN complex and its assembly. 1 Institute for Quantitative Biosciences, The University of Tokyo, Tokyo 113-0032, Japan. 2 Synchrotron Radiation Research Organization, The University of Tokyo, Tokyo 113-0032, Japan. 3 Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan. 4 Laboratory of Protein Metabolism, Tokyo Metropolitan Institute of Medical Science, Tokyo 156-8506, Japan. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Genetic Variant in 3' Untranslated Region of the Mouse Pycard Gene
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.26.437184; this version posted March 26, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 2 3 Title: 4 Genetic Variant in 3’ Untranslated Region of the Mouse Pycard Gene Regulates Inflammasome 5 Activity 6 Running Title: 7 3’UTR SNP in Pycard regulates inflammasome activity 8 Authors: 9 Brian Ritchey1*, Qimin Hai1*, Juying Han1, John Barnard2, Jonathan D. Smith1,3 10 1Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, 11 Cleveland, OH 44195 12 2Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 13 44195 14 3Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western 15 Reserve University, Cleveland, OH 44195 16 *, These authors contributed equally to this study. 17 Address correspondence to Jonathan D. Smith: email [email protected]; ORCID ID 0000-0002-0415-386X; 18 mailing address: Cleveland Clinic, Box NC-10, 9500 Euclid Avenue, Cleveland, OH 44195, USA. 19 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.26.437184; this version posted March 26, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 20 Abstract 21 Quantitative trait locus mapping for interleukin-1 release after inflammasome priming and activation 22 was performed on bone marrow-derived macrophages (BMDM) from an AKRxDBA/2 strain intercross. -
High Throughput Computational Mouse Genetic Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.01.278465; this version posted January 22, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. High Throughput Computational Mouse Genetic Analysis Ahmed Arslan1+, Yuan Guan1+, Zhuoqing Fang1, Xinyu Chen1, Robin Donaldson2&, Wan Zhu, Madeline Ford1, Manhong Wu, Ming Zheng1, David L. Dill2* and Gary Peltz1* 1Department of Anesthesia, Stanford University School of Medicine, Stanford, CA; and 2Department of Computer Science, Stanford University, Stanford, CA +These authors contributed equally to this paper & Current Address: Ecree Durham, NC 27701 *Address correspondence to: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.09.01.278465; this version posted January 22, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Background: Genetic factors affecting multiple biomedical traits in mice have been identified when GWAS data that measured responses in panels of inbred mouse strains was analyzed using haplotype-based computational genetic mapping (HBCGM). Although this method was previously used to analyze one dataset at a time; but now, a vast amount of mouse phenotypic data is now publicly available, which could lead to many more genetic discoveries. Results: HBCGM and a whole genome SNP map covering 53 inbred strains was used to analyze 8462 publicly available datasets of biomedical responses (1.52M individual datapoints) measured in panels of inbred mouse strains. As proof of concept, causative genetic factors affecting susceptibility for eye, metabolic and infectious diseases were identified when structured automated methods were used to analyze the output. -
QUANTITATIVE TRAIT LOCUS ANALYSIS: in Several Variants (I.E., Alleles)
TECHNOLOGIES FROM THE FIELD QUANTITATIVE TRAIT LOCUS ANALYSIS: in several variants (i.e., alleles). QTL analysis allows one MULTIPLE CROSS AND HETEROGENEOUS to map, with some precision, the genomic position of STOCK MAPPING these alleles. For many researchers in the alcohol field, the break Robert Hitzemann, Ph.D.; John K. Belknap, Ph.D.; through with respect to the genetic determination of alcohol- and Shannon K. McWeeney, Ph.D. related behaviors occurred when Plomin and colleagues (1991) made the seminal observation that a specific panel of RI mice (i.e., the BXD panel) could be used to identify KEY WORDS: Genetic theory of alcohol and other drug use; genetic the physical location of (i.e., to map) QTLs for behavioral factors; environmental factors; behavioral phenotype; behavioral phenotypes. Because the phenotypes of the different strains trait; quantitative trait gene (QTG); inbred animal strains; in this panel had been determined for many alcohol- recombinant inbred (RI) mouse strains; quantitative traits; related traits, researchers could readily apply the strategy quantitative trait locus (QTL) mapping; multiple cross mapping of RI–QTL mapping (Gora-Maslak et al. 1991). Although (MCM); heterogeneous stock (HS) mapping; microsatellite investigators recognized early on that this panel was not mapping; animal models extensive enough to answer all questions, the emerging data illustrated the rich genetic complexity of alcohol- related phenotypes (Belknap 1992; Plomin and McClearn ntil well into the 1990s, both preclinical and clinical 1993). research focused on finding “the” gene for human The next advance came with the development of diseases, including alcoholism. This focus was rein U microsatellite maps (Dietrich et al. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Anti-PLEKHA1 / TAPP1 Antibody (ARG42988)
Product datasheet [email protected] ARG42988 Package: 100 μl anti-PLEKHA1 / TAPP1 antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes PLEKHA1 / TAPP1 Tested Reactivity Hu, Ms, Rat Tested Application IP, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name PLEKHA1 / TAPP1 Antigen Species Human Immunogen Synthetic peptide of Human PLEKHA1 / TAPP1. Conjugation Un-conjugated Alternate Names Pleckstrin homology domain-containing family A member 1; TAPP1; Tandem PH domain-containing protein 1; TAPP-1; PH domain-containing family A member 1 Application Instructions Application table Application Dilution IP 1:20 WB 1:1000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Positive Control K562 Calculated Mw 46 kDa Observed Size ~ 46 kDa Properties Form Liquid Purification Affinity purified. Buffer 50 nM Tris-Glycine (pH 7.4), 0.15M NaCl, 0.01% Sodium azide, 40% Glycerol and 0.05% BSA. Preservative 0.01% Sodium azide Stabilizer 40% Glycerol and 0.05% BSA Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/2 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Gene Symbol PLEKHA1 Gene Full Name pleckstrin homology domain containing, family A (phosphoinositide binding specific) member 1 Background This gene encodes a pleckstrin homology domain-containing adapter protein. -
Transcriptome Analysis of Human Diabetic Kidney Disease
ORIGINAL ARTICLE Transcriptome Analysis of Human Diabetic Kidney Disease Karolina I. Woroniecka,1 Ae Seo Deok Park,1 Davoud Mohtat,2 David B. Thomas,3 James M. Pullman,4 and Katalin Susztak1,5 OBJECTIVE—Diabetic kidney disease (DKD) is the single cases, mild and then moderate mesangial expansion can be leading cause of kidney failure in the U.S., for which a cure has observed. In general, diabetic kidney disease (DKD) is not yet been found. The aim of our study was to provide an considered a nonimmune-mediated degenerative disease unbiased catalog of gene-expression changes in human diabetic of the glomerulus; however, it has long been noted that kidney biopsy samples. complement and immunoglobulins sometimes can be de- — tected in diseased glomeruli, although their role and sig- RESEARCH DESIGN AND METHODS Affymetrix expression fi arrays were used to identify differentially regulated transcripts in ni cance is not clear (4). 44 microdissected human kidney samples. The DKD samples were The understanding of DKD has been challenged by multi- significant for their racial diversity and decreased glomerular ple issues. First, the diagnosis of DKD usually is made using filtration rate (~20–30 mL/min). Stringent statistical analysis, using clinical criteria, and kidney biopsy often is not performed. the Benjamini-Hochberg corrected two-tailed t test, was used to According to current clinical practice, the development of identify differentially expressed transcripts in control and diseased albuminuria in patients with diabetes is sufficient to make the glomeruli and tubuli. Two different Web-based algorithms were fi diagnosis of DKD (5). We do not understand the correlation used to de ne differentially regulated pathways. -
Nuclear PTEN Safeguards Pre-Mrna Splicing to Link Golgi Apparatus for Its Tumor Suppressive Role
ARTICLE DOI: 10.1038/s41467-018-04760-1 OPEN Nuclear PTEN safeguards pre-mRNA splicing to link Golgi apparatus for its tumor suppressive role Shao-Ming Shen1, Yan Ji2, Cheng Zhang1, Shuang-Shu Dong2, Shuo Yang1, Zhong Xiong1, Meng-Kai Ge1, Yun Yu1, Li Xia1, Meng Guo1, Jin-Ke Cheng3, Jun-Ling Liu1,3, Jian-Xiu Yu1,3 & Guo-Qiang Chen1 Dysregulation of pre-mRNA alternative splicing (AS) is closely associated with cancers. However, the relationships between the AS and classic oncogenes/tumor suppressors are 1234567890():,; largely unknown. Here we show that the deletion of tumor suppressor PTEN alters pre-mRNA splicing in a phosphatase-independent manner, and identify 262 PTEN-regulated AS events in 293T cells by RNA sequencing, which are associated with significant worse outcome of cancer patients. Based on these findings, we report that nuclear PTEN interacts with the splicing machinery, spliceosome, to regulate its assembly and pre-mRNA splicing. We also identify a new exon 2b in GOLGA2 transcript and the exon exclusion contributes to PTEN knockdown-induced tumorigenesis by promoting dramatic Golgi extension and secretion, and PTEN depletion significantly sensitizes cancer cells to secretion inhibitors brefeldin A and golgicide A. Our results suggest that Golgi secretion inhibitors alone or in combination with PI3K/Akt kinase inhibitors may be therapeutically useful for PTEN-deficient cancers. 1 Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China. 2 Institute of Health Sciences, Shanghai Institutes for Biological Sciences of Chinese Academy of Sciences and SJTU-SM, Shanghai 200025, China.