Simulation and Estimation of Gene Number in a Biological Pathway
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A CRISPR-Cas9–Engineered Mouse Model for GPI-Anchor Deficiency Mirrors Human Phenotypes and Exhibits Hippocampal Synaptic Dysfunctions
A CRISPR-Cas9–engineered mouse model for GPI-anchor deficiency mirrors human phenotypes and exhibits hippocampal synaptic dysfunctions Miguel Rodríguez de los Santosa,b,c,d, Marion Rivalane,f, Friederike S. Davidd,g, Alexander Stumpfh, Julika Pitschi,j, Despina Tsortouktzidisi, Laura Moreno Velasquezh, Anne Voigth, Karl Schillingk, Daniele Matteil, Melissa Longe,f, Guido Vogta,c, Alexej Knausd, Björn Fischer-Zirnsaka,c, Lars Wittlerm, Bernd Timmermannn, Peter N. Robinsono,p, Denise Horna, Stefan Mundlosa,c, Uwe Kornaka,c,q, Albert J. Beckeri, Dietmar Schmitzh, York Wintere,f, and Peter M. Krawitzd,1 aInstitute for Medical Genetics and Human Genetics, Charité–Universitätsmedizin Berlin, 13353 Berlin, Germany; bBerlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; cResearch Group Development and Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; dInstitute for Genomic Statistics and Bioinformatics, University of Bonn, 53127 Bonn, Germany; eAnimal Outcome Core Facility of the NeuroCure Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; fInstitute of Cognitive Neurobiology, Humboldt University, 10117 Berlin, Germany; gInstitute of Human Genetics, Faculty of Medicine, University Hospital Bonn, 53127 Bonn, Germany; hNeuroscience Research Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; iSection for Translational Epilepsy Research, Department of Neuropathology, University Hospital Bonn, 53127 Bonn, Germany; jDepartment of Epileptology, -
NICU Gene List Generator.Xlsx
Neonatal Crisis Sequencing Panel Gene List Genes: A2ML1 - B3GLCT A2ML1 ADAMTS9 ALG1 ARHGEF15 AAAS ADAMTSL2 ALG11 ARHGEF9 AARS1 ADAR ALG12 ARID1A AARS2 ADARB1 ALG13 ARID1B ABAT ADCY6 ALG14 ARID2 ABCA12 ADD3 ALG2 ARL13B ABCA3 ADGRG1 ALG3 ARL6 ABCA4 ADGRV1 ALG6 ARMC9 ABCB11 ADK ALG8 ARPC1B ABCB4 ADNP ALG9 ARSA ABCC6 ADPRS ALK ARSL ABCC8 ADSL ALMS1 ARX ABCC9 AEBP1 ALOX12B ASAH1 ABCD1 AFF3 ALOXE3 ASCC1 ABCD3 AFF4 ALPK3 ASH1L ABCD4 AFG3L2 ALPL ASL ABHD5 AGA ALS2 ASNS ACAD8 AGK ALX3 ASPA ACAD9 AGL ALX4 ASPM ACADM AGPS AMELX ASS1 ACADS AGRN AMER1 ASXL1 ACADSB AGT AMH ASXL3 ACADVL AGTPBP1 AMHR2 ATAD1 ACAN AGTR1 AMN ATL1 ACAT1 AGXT AMPD2 ATM ACE AHCY AMT ATP1A1 ACO2 AHDC1 ANK1 ATP1A2 ACOX1 AHI1 ANK2 ATP1A3 ACP5 AIFM1 ANKH ATP2A1 ACSF3 AIMP1 ANKLE2 ATP5F1A ACTA1 AIMP2 ANKRD11 ATP5F1D ACTA2 AIRE ANKRD26 ATP5F1E ACTB AKAP9 ANTXR2 ATP6V0A2 ACTC1 AKR1D1 AP1S2 ATP6V1B1 ACTG1 AKT2 AP2S1 ATP7A ACTG2 AKT3 AP3B1 ATP8A2 ACTL6B ALAS2 AP3B2 ATP8B1 ACTN1 ALB AP4B1 ATPAF2 ACTN2 ALDH18A1 AP4M1 ATR ACTN4 ALDH1A3 AP4S1 ATRX ACVR1 ALDH3A2 APC AUH ACVRL1 ALDH4A1 APTX AVPR2 ACY1 ALDH5A1 AR B3GALNT2 ADA ALDH6A1 ARFGEF2 B3GALT6 ADAMTS13 ALDH7A1 ARG1 B3GAT3 ADAMTS2 ALDOB ARHGAP31 B3GLCT Updated: 03/15/2021; v.3.6 1 Neonatal Crisis Sequencing Panel Gene List Genes: B4GALT1 - COL11A2 B4GALT1 C1QBP CD3G CHKB B4GALT7 C3 CD40LG CHMP1A B4GAT1 CA2 CD59 CHRNA1 B9D1 CA5A CD70 CHRNB1 B9D2 CACNA1A CD96 CHRND BAAT CACNA1C CDAN1 CHRNE BBIP1 CACNA1D CDC42 CHRNG BBS1 CACNA1E CDH1 CHST14 BBS10 CACNA1F CDH2 CHST3 BBS12 CACNA1G CDK10 CHUK BBS2 CACNA2D2 CDK13 CILK1 BBS4 CACNB2 CDK5RAP2 -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
A Novel Resveratrol Analog: Its Cell Cycle Inhibitory, Pro-Apoptotic and Anti-Inflammatory Activities on Human Tumor Cells
A NOVEL RESVERATROL ANALOG : ITS CELL CYCLE INHIBITORY, PRO-APOPTOTIC AND ANTI-INFLAMMATORY ACTIVITIES ON HUMAN TUMOR CELLS A dissertation submitted to Kent State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy by Boren Lin May 2006 Dissertation written by Boren Lin B.S., Tunghai University, 1996 M.S., Kent State University, 2003 Ph. D., Kent State University, 2006 Approved by Dr. Chun-che Tsai , Chair, Doctoral Dissertation Committee Dr. Bryan R. G. Williams , Co-chair, Doctoral Dissertation Committee Dr. Johnnie W. Baker , Members, Doctoral Dissertation Committee Dr. James L. Blank , Dr. Bansidhar Datta , Dr. Gail C. Fraizer , Accepted by Dr. Robert V. Dorman , Director, School of Biomedical Sciences Dr. John R. Stalvey , Dean, College of Arts and Sciences ii TABLE OF CONTENTS LIST OF FIGURES……………………………………………………………….………v LIST OF TABLES……………………………………………………………………….vii ACKNOWLEDGEMENTS….………………………………………………………….viii I INTRODUCTION….………………………………………………….1 Background and Significance……………………………………………………..1 Specific Aims………………………………………………………………………12 II MATERIALS AND METHODS.…………………………………………….16 Cell Culture and Compounds…….……………….…………………………….….16 MTT Cell Viability Assay………………………………………………………….16 Trypan Blue Exclusive Assay……………………………………………………...18 Flow Cytometry for Cell Cycle Analysis……………..……………....……………19 DNA Fragmentation Assay……………………………………………...…………23 Caspase-3 Activity Assay………………………………...……….….…….………24 Annexin V-FITC Staining Assay…………………………………..…...….………28 NF-kappa B p65 Activity Assay……………………………………..………….…29 -
Innate Immune Activity Is Detected Prior to Seroconversion in Children with HLA-Conferred Type 1 Diabetes Susceptibility
2402 Diabetes Volume 63, July 2014 Henna Kallionpää,1,2,3 Laura L. Elo,1,4 Essi Laajala,1,3,5,6 Juha Mykkänen,1,3,7,8 Isis Ricaño-Ponce,9 Matti Vaarma,10 Teemu D. Laajala,1 Heikki Hyöty,11,12 Jorma Ilonen,13,14 Riitta Veijola,15 Tuula Simell,3,7 Cisca Wijmenga,9 Mikael Knip,3,16,17,18 Harri Lähdesmäki,1,3,5 Olli Simell,3,7,8 and Riitta Lahesmaa1,3 Innate Immune Activity Is Detected Prior to Seroconversion in Children With HLA-Conferred Type 1 Diabetes Susceptibility Diabetes 2014;63:2402–2414 | DOI: 10.2337/db13-1775 The insult leading to autoantibody development in chil- signatures. Genes and pathways related to innate immu- dren who will progress to develop type 1 diabetes (T1D) nity functions, such as the type 1 interferon (IFN) re- has remained elusive. To investigate the genes and sponse, were active, and IFN response factors were molecular pathways in the pathogenesis of this disease, identified as central mediators of the IFN-related tran- we performed genome-wide transcriptomics analysis on scriptional changes. Importantly, this signature was a unique series of prospective whole-blood RNA samples detected already before the T1D-associated autoanti- from at-risk children collected in the Finnish Type 1 bodies were detected. Together, these data provide Diabetes Prediction and Prevention study. We studied a unique resource for new hypotheses explaining T1D 28 autoantibody-positive children, out of which 22 pro- biology. gressed to clinical disease. Collectively, the samples PATHOPHYSIOLOGY covered the time span from before the development of autoantibodies (seroconversion) through the diagnosis of By the time of clinical diagnosis of type 1 diabetes (T1D), diabetes. -
High Mutation Frequency of the PIGA Gene in T Cells Results In
High Mutation Frequency of the PIGA Gene in T Cells Results in Reconstitution of GPI A nchor−/CD52− T Cells That Can Give Early Immune Protection after This information is current as Alemtuzumab-Based T Cell−Depleted of October 1, 2021. Allogeneic Stem Cell Transplantation Floris C. Loeff, J. H. Frederik Falkenburg, Lois Hageman, Wesley Huisman, Sabrina A. J. Veld, H. M. Esther van Egmond, Marian van de Meent, Peter A. von dem Borne, Hendrik Veelken, Constantijn J. M. Halkes and Inge Jedema Downloaded from J Immunol published online 2 February 2018 http://www.jimmunol.org/content/early/2018/02/02/jimmun ol.1701018 http://www.jimmunol.org/ Supplementary http://www.jimmunol.org/content/suppl/2018/02/02/jimmunol.170101 Material 8.DCSupplemental Why The JI? Submit online. by guest on October 1, 2021 • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2018 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published February 2, 2018, doi:10.4049/jimmunol.1701018 The Journal of Immunology High Mutation Frequency of the PIGA Gene in T Cells Results in Reconstitution of GPI Anchor2/CD522 T Cells That Can Give Early Immune Protection after Alemtuzumab- Based T Cell–Depleted Allogeneic Stem Cell Transplantation Floris C. -
Comparing Spatial Expression Dynamics of Bovine
Comparing spatial expression dynamics of bovine blastocyst under three different procedures : in-vivo, in-vitro derived, Title and somatic cell nuclear transfer embryos Nagatomo, Hiroaki; Akizawa, Hiroki; Sada, Ayari; Kishi, Yasunori; Yamanaka, Ken-ichi; Takuma, Tetsuya; Sasaki, Author(s) Keisuke; Yamauchi, Nobuhiko; Yanagawa, Yojiro; Nagano, Masashi; Kono, Tomohiro; Takahashi, Masashi; Kawahara, Manabu Citation Japanese Journal of Veterinary Research, 63(4), 159-171 Issue Date 2015-11 DOI 10.14943/jjvr.63.4.159 Doc URL http://hdl.handle.net/2115/60304 Type bulletin (article) Additional Information There are other files related to this item in HUSCAP. Check the above URL. File Information JJVR63-4 p.159-171 Suppl. Table 3.pdf (Supplemental Table 3) Instructions for use Hokkaido University Collection of Scholarly and Academic Papers : HUSCAP Supplemental table 3. Genes that were differentially expressed in the ICM relative to the TE in in SCNT blastocyst (SCNT list). Gene Symbol Probe Set ID Regulation Fold change ([ICM] / [TE]) Gene Title EEF1A1 AFFX-Bt-ef1a-3_at UP 1.2092365 eukaryotic translation elongation factor 1 alpha 1 IGFBP3 Bt.422.1.S2_at UP 2.5323892 insulin-like growth factor binding protein 3 IGFBP3 Bt.422.1.S1_at UP 3.7850845 insulin-like growth factor binding protein 3 SULT1A1 Bt.3537.1.S1_at UP 2.7092714 sulfotransferase family, cytosolic, 1A, phenol-preferring, member 1 SPP1 Bt.2632.1.S1_at UP 5.6928325 secreted phosphoprotein 1 SCARB1 Bt.4520.1.S1_at UP 3.106944 scavenger receptor class B, member 1 TSPO Bt.3988.1.S1_at -
Complement and Inflammasome Overactivation Mediates Paroxysmal Nocturnal Hemoglobinuria with Autoinflammation
Complement and inflammasome overactivation mediates paroxysmal nocturnal hemoglobinuria with autoinflammation Britta Höchsmann, … , Peter M. Krawitz, Taroh Kinoshita J Clin Invest. 2019. https://doi.org/10.1172/JCI123501. Research Article Hematology Inflammation Graphical abstract Find the latest version: https://jci.me/123501/pdf The Journal of Clinical Investigation RESEARCH ARTICLE Complement and inflammasome overactivation mediates paroxysmal nocturnal hemoglobinuria with autoinflammation Britta Höchsmann,1,2 Yoshiko Murakami,3,4 Makiko Osato,3,5 Alexej Knaus,6 Michi Kawamoto,7 Norimitsu Inoue,8 Tetsuya Hirata,3 Shogo Murata,3,9 Markus Anliker,1 Thomas Eggermann,10 Marten Jäger,11 Ricarda Floettmann,11 Alexander Höllein,12 Sho Murase,7 Yasutaka Ueda,5 Jun-ichi Nishimura,5 Yuzuru Kanakura,5 Nobuo Kohara,7 Hubert Schrezenmeier,1 Peter M. Krawitz,6 and Taroh Kinoshita3,4 1Institute of Transfusion Medicine, University of Ulm, Ulm, Germany. 2Institute of Clinical Transfusion Medicine and Immunogenetics, German Red Cross Blood Transfusion Service and University Hospital Ulm, Ulm, Germany. 3Research Institute for Microbial Diseases and 4WPI Immunology Frontier Research Center, Osaka University, Osaka, Japan. 5Department of Hematology and Oncology, Graduate School of Medicine, Osaka University, Osaka, Japan. 6Institute for Genomic Statistics and Bioinformatics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany. 7Department of Neurology, Kobe City Medical Center General Hospital, Kobe, Japan. 8Department of Tumor Immunology, Osaka -
Demographic History and Genetic Adaptation in the Himalayan
Demographic History and Genetic Adaptation in the Himalayan Region Inferred from Genome-Wide SNP Genotypes of 49 Populations Elena Arciero,†,1 Thirsa Kraaijenbrink,†,2 Asan,†,3 Marc Haber,1 Massimo Mezzavilla,1,4 Qasim Ayub,1,5,6 Wei Wang,3 Zhaxi Pingcuo,7 Huanming Yang,3,8 Jian Wang,3,8 Mark A. Jobling,9 George van Driem,10 Yali Xue,1 Peter de Knijff,*,2 and Chris Tyler-Smith*,1 1The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom Downloaded from https://academic.oup.com/mbe/article-abstract/35/8/1916/4999976 by Leiden University / LUMC user on 22 July 2019 2Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands 3BGI-Shenzhen, Shenzhen, China 4Division of Experimental Genetics, Sidra Medical and Research Center, Doha, Qatar 5Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia Genomics Facility, Selangor Darul Ehsan, Malaysia 6School of Science, Monash University Malaysia, Selangor Darul Ehsan, Malaysia 7The Third People’s Hospital of the TibetAutonomousRegion,Lhasa,China 8James D. Watson Institute of Genome Science, Hangzhou, China 9Department of Genetics & Genome Biology, University of Leicester, Leicester, United Kingdom 10Institute of Linguistics, University of Bern, Bern, Switzerland †These authors contributed equally to this work. *Corresponding authors: E-mails: [email protected]; [email protected]. Associate editor: Rasmus Nielsen Abstract We genotyped 738 individuals belonging to 49 populations from Nepal, Bhutan, North India, or Tibet at over 500,000 SNPs, and analyzed the genotypes in the context of available worldwide population data in order to investigate the demographic history of the region and the genetic adaptations to the harsh environment. -
NGS Catalog: a Database of Next Generation Sequencing Studies in Humans
HUMAN MUTATION Database in Brief 33: E2341-E2355 (2012) Online DATABASE IN BRIEF HUMAN MUTATION OFFICIAL JOURNAL NGS Catalog: A Database of Next Generation Sequencing Studies in Humans www.hgvs.org Junfeng Xia1,†, Qingguo Wang1,†, Peilin Jia1, Bing Wang1, William Pao2,3, and Zhongming Zhao1,3,4,* 1Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA,2Department of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, TN, USA,3Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA,4Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA †These authors contributed equally to this work. *Correspondence to Zhongming Zhao, Ph.D., Department of Biomedical Informatics, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, Nashville, TN, 37203, USA; Phone: +1-615-343-9158; FAX: +1-615-936-8545; E-mail: [email protected]. Contract grant sponsor: This study was partially supported by the Stand Up To Cancer-American Association for Cancer Research Innovative Research Grant (SU2C-AACR-IRG0109) and the VICC Cancer Center Core grant P30CA68485 from National Institutes of Health. Communicated by Johan T. den Dunnen ABSTRACT: Next generation sequencing (NGS) technologies have been rapidly applied in biomedical and biological research since its advent only a few years ago, and they are expected to advance at an unprecedented pace in the following years. To provide the research community with a comprehensive NGS resource, we have developed the database Next Generation Sequencing Catalog (NGS Catalog, http://bioinfo.mc.vanderbilt.edu/NGS/index.html), a continually updated database that collects, curates and manages available human NGS data obtained from published literature. -
Profiling the Expression Pattern of GPI Transamidase Complex Subunits in Human Cancer
Modern Pathology (2008) 21, 979–991 & 2008 USCAP, Inc All rights reserved 0893-3952/08 $30.00 www.modernpathology.org Profiling the expression pattern of GPI transamidase complex subunits in human cancer Jatin K Nagpal1,5, Santanu Dasgupta1,5, Sana Jadallah2, Young K Chae1, Edward A Ratovitski3, Antoun Toubaji2, George J Netto2, Toby Eagle1, Aviram Nissan4, David Sidransky1 and Barry Trink1 1Department of Otolaryngology-Head and Neck Surgery, Head and Neck Cancer Research Division, Johns Hopkins University School of Medicine, Baltimore, MD, USA; 2Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; 3Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, MD, USA and 4Department of Surgery, Hadassah University Hospital, Mount Scopus, Jerusalem, Israel The glycosylphosphatidylinositol transamidase complex (GPIT) consists of five subunits: PIG-U, PIG-T, GPAA1, PIG-S and GPI8, and is important in attaching GPI anchors to target proteins. On the basis of our previous reports incriminating PIG-U as an oncogene in bladder cancer and PIG-T and GPAA1 as oncogenes in breast cancer, we evaluated the expression pattern of the GPIT subunits in 19 different human cancers at both mRNA and protein levels. In general, our results demonstrate a more frequent expression of GPIT subunits in cancers than in normal. Among the 19 anatomic sites compared; breast, ovary and uterus showed consistent evidence of overexpression of specific GPIT subunits. There was also overexpression of PIG-U and GPI8 in lymphoma. In addition, non-small cell lung carcinoma showed significant overexpression of the GPIT subunits as compared to small cell lung carcinoma and normal lung tissue. -
Genetics of Plgf Plasma Levels Highlights a Role of Its Receptors And
www.nature.com/scientificreports OPEN Genetics of PlGF plasma levels highlights a role of its receptors and supports the link between angiogenesis and immunity Daniela Ruggiero1,2*, Teresa Nutile1, Stefania Nappo3, Alfonsina Tirozzi2, Celine Bellenguez4, Anne‑Louise Leutenegger5,6 & Marina Ciullo1,2* Placental growth factor (PlGF) is a member of the vascular endothelial growth factor family and is involved in bone marrow‑derived cell activation, endothelial stimulation and pathological angiogenesis. High levels of PlGF have been observed in several pathological conditions especially in cancer, cardiovascular, autoimmune and infammatory diseases. Little is known about the genetics of circulating PlGF levels. Indeed, although the heritability of circulating PlGF levels is around 40%, no studies have assessed the relation between PlGF plasma levels and genetic variants at a genome‑wide level. In the current study, PlGF plasma levels were measured in a population‑based sample of 2085 adult individuals from three isolated populations of South Italy. A GWAS was performed in a discovery cohort (N = 1600), followed by a de novo replication (N = 468) from the same populations. The meta‑ analysis of the discovery and replication samples revealed one signal signifcantly associated with PlGF circulating levels. This signal was mapped to the PlGF co‑receptor coding gene NRP1, indicating its important role in modulating the PlGF plasma levels. Two additional signals, at the PlGF receptor coding gene FLT1 and RAPGEF5 gene, were identifed at a suggestive level. Pathway and TWAS analyses highlighted genes known to be involved in angiogenesis and immune response, supporting the link between these processes and PlGF regulation. Overall, these data improve our understanding of the genetic variation underlying circulating PlGF levels.