1
|
Kaushik A, Chang I, Han X, He Z, Komlosi ZI, Ji X, Cao S, Akdis CA, Boyd S, Pulendran B, Maecker HT, Davis MM, Chinthrajah RS, DeKruyff RH, Nadeau KC. Single cell multi-omic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients. Front Immunol 2024; 15:1374828. [PMID: 39026668 PMCID: PMC11255397 DOI: 10.3389/fimmu.2024.1374828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 06/07/2024] [Indexed: 07/20/2024] Open
Abstract
Introduction Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. Methods To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omics approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. Results We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Discussion Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.
Collapse
Affiliation(s)
- Abhinav Kaushik
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Iris Chang
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Xiaorui Han
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Ziyuan He
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Zsolt I. Komlosi
- Department of Genetics, Cell- and Immunobiology, Semmelweis University, Budapest, Hungary
- Swiss Institute of Allergy and Asthma (SIAF), University of Zurich, Davos, Switzerland
| | - Xuhuai Ji
- Human Immune Monitoring Center, Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA, United States
| | - Shu Cao
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Cezmi A. Akdis
- Swiss Institute of Allergy and Asthma (SIAF), University of Zurich, Davos, Switzerland
- Christine Kühne-Center for Allergy Research and Education, Davos, Switzerland
| | - Scott Boyd
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
- Department of Pathology, Stanford University, Stanford, CA, United States
| | - Bali Pulendran
- Department of Pathology, Stanford University, Stanford, CA, United States
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, United States
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, United States
| | - Holden T. Maecker
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, United States
| | - Mark M. Davis
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, United States
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, United States
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, United States
| | - R. Sharon Chinthrajah
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Rosemarie H. DeKruyff
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Kari C. Nadeau
- Sean N. Parker Center for Allergy and Asthma Research, Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| |
Collapse
|
2
|
Kang JY, Cho H, Gil M, Lee H, Park S, Kim KE. The novel prognostic marker SPOCK2 regulates tumour progression in melanoma. Exp Dermatol 2024; 33:e15092. [PMID: 38888196 DOI: 10.1111/exd.15092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/12/2024] [Accepted: 04/19/2024] [Indexed: 06/20/2024]
Abstract
Secreted protein acidic and cysteine rich/osteonectin, cwcv and kazal-like domain proteoglycan 2 (SPOCK2) is a protein that regulates cell differentiation and growth. Recent studies have reported that SPOCK2 plays important roles in the progression of various human cancers; however, the role of SPOCK2 in melanoma remains unknown. Therefore, this study investigated the roles of SPOCK2 and the related mechanisms in melanoma progression. To evaluate the clinical significance of SPOCK2 expression in patients with melanoma, we analysed the association between SPOCK2 expression and its prognostic value for patients with melanoma using systematic multiomic analysis. Subsequently, to investigate the roles of Spock2 in melanoma progression in vitro and in vivo, we knocked down Spock2 in the B16F10 melanoma cell line. High SPOCK2 levels were positively associated with good prognosis and long survival rate of patients with melanoma. Spock2 knockdown promoted melanoma cell proliferation by inducing the cell cycle and inhibiting apoptosis. Moreover, Spock2 downregulation significantly increased cell migration and invasion by upregulating MMP2 and MT1-MMP. The increased cell proliferation and migration were inhibited by MAPK inhibitor, and ERK phosphorylation was considerably enhanced in Spock2 knockdown cells. Therefore, Spock2 could function as a tumour suppressor gene to regulate melanoma progression by regulating the MAPK/ERK signalling pathway. Additionally, Spock2 knockdown cell injection induced considerable tumour growth and lung metastasis in C57BL6 mice compared to that in the control group. Our findings suggest that SPOCK2 plays crucial roles in malignant progression of melanoma and functions as a novel therapeutic target of melanoma.
Collapse
Affiliation(s)
- Ji Young Kang
- Department of Health Industry, Sookmyung Women's University, Seoul, Korea
| | - Hyeijin Cho
- Department of Health Industry, Sookmyung Women's University, Seoul, Korea
| | - Minchan Gil
- Department of Health Industry, Sookmyung Women's University, Seoul, Korea
| | - Haeryung Lee
- Department of Biological Sciences, Sookmyung Women's University, Seoul, Korea
| | - Soochul Park
- Department of Biological Sciences, Sookmyung Women's University, Seoul, Korea
| | - Kyung Eun Kim
- Department of Health Industry, Sookmyung Women's University, Seoul, Korea
| |
Collapse
|
3
|
Husain M. Influenza Virus Host Restriction Factors: The ISGs and Non-ISGs. Pathogens 2024; 13:127. [PMID: 38392865 PMCID: PMC10893265 DOI: 10.3390/pathogens13020127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/18/2024] [Accepted: 01/26/2024] [Indexed: 02/25/2024] Open
Abstract
Influenza virus has been one of the most prevalent and researched viruses globally. Consequently, there is ample information available about influenza virus lifecycle and pathogenesis. However, there is plenty yet to be known about the determinants of influenza virus pathogenesis and disease severity. Influenza virus exploits host factors to promote each step of its lifecycle. In turn, the host deploys antiviral or restriction factors that inhibit or restrict the influenza virus lifecycle at each of those steps. Two broad categories of host restriction factors can exist in virus-infected cells: (1) encoded by the interferon-stimulated genes (ISGs) and (2) encoded by the constitutively expressed genes that are not stimulated by interferons (non-ISGs). There are hundreds of ISGs known, and many, e.g., Mx, IFITMs, and TRIMs, have been characterized to restrict influenza virus infection at different stages of its lifecycle by (1) blocking viral entry or progeny release, (2) sequestering or degrading viral components and interfering with viral synthesis and assembly, or (3) bolstering host innate defenses. Also, many non-ISGs, e.g., cyclophilins, ncRNAs, and HDACs, have been identified and characterized to restrict influenza virus infection at different lifecycle stages by similar mechanisms. This review provides an overview of those ISGs and non-ISGs and how the influenza virus escapes the restriction imposed by them and aims to improve our understanding of the host restriction mechanisms of the influenza virus.
Collapse
Affiliation(s)
- Matloob Husain
- Department of Microbiology and Immunology, University of Otago, P.O. Box 56, Dunedin 9054, New Zealand
| |
Collapse
|
4
|
Giriyappagoudar M, Vastrad B, Horakeri R, Vastrad C. Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis. Biomedicines 2023; 11:3109. [PMID: 38137330 PMCID: PMC10740779 DOI: 10.3390/biomedicines11123109] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 12/24/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.
Collapse
Affiliation(s)
- Muttanagouda Giriyappagoudar
- Department of Radiation Oncology, Karnataka Institute of Medical Sciences (KIMS), Hubballi 580022, Karnataka, India;
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry, K.L.E. Socitey’s College of Pharmacy, Gadag 582101, Karnataka, India;
| | - Rajeshwari Horakeri
- Department of Computer Science, Govt First Grade College, Hubballi 580032, Karnataka, India;
| | - Chanabasayya Vastrad
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India
| |
Collapse
|
5
|
Xue J, Ma T, Zhang X. TRA2: The dominant power of alternative splicing in tumors. Heliyon 2023; 9:e15516. [PMID: 37151663 PMCID: PMC10161706 DOI: 10.1016/j.heliyon.2023.e15516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/30/2023] [Accepted: 04/12/2023] [Indexed: 05/09/2023] Open
Abstract
The dysregulation of alternative splicing (AS) is frequently found in cancer and considered as key markers for cancer progression and therapy. Transformer 2 (TRA2), a nuclear RNA binding protein, consists of transformer 2 alpha homolog (TRA2A) and transformer 2 beta homolog (TRA2B), and plays a role in the regulation of pre-mRNA splicing. Growing evidence has been provided that TRA2A and TRA2B are dysregulated in several types of tumors, and participate in the regulation of proliferation, migration, invasion, and chemotherapy resistance in cancer cells through alteration of AS of cancer-related genes. In this review, we highlight the role of TRA2 in tumorigenesis and metastasis, and discuss potential molecular mechanisms how TRA2 influences tumorigenesis and metastasis via controlling AS of pre-mRNA. We propose that TRA2Ais a novel biomarker and therapeutic target for cancer progression and therapy.
Collapse
Affiliation(s)
- Jiancheng Xue
- Medical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Key Laboratory of Research and Application of Animal Model for Environmental and Metabolic Diseases, Shenyang, China
| | - Tie Ma
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, China
- Corresponding author.
| | - Xiaowen Zhang
- Medical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Key Laboratory of Research and Application of Animal Model for Environmental and Metabolic Diseases, Shenyang, China
- Corresponding author. Medical Research Center, Shengjing Hospital of China Medical University, #36 Sanhao Street, Heping District, Shenyang, 110004, China.
| |
Collapse
|
6
|
Wen D, Zhou L, Zheng Z, Surapaneni A, Ballantyne CM, Hoogeveen RC, Shlipak MG, Waikar SS, Vasan RS, Kimmel PL, Dubin RF, Deo R, Feldman HI, Ganz P, Coresh J, Grams ME, Rhee EP. Testican-2 Is Associated with Reduced Risk of Incident ESKD. J Am Soc Nephrol 2023; 34:122-131. [PMID: 36288905 PMCID: PMC10101586 DOI: 10.1681/asn.2022020216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 08/23/2022] [Accepted: 11/14/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Testican-2 was recently identified as a podocyte-derived protein that is released into circulation by the kidneys and is positively correlated with eGFR and eGFR slope. However, whether higher testican-2 levels are associated with lower risk of ESKD is unknown. METHODS Aptamer-based proteomics assessed blood testican-2 levels among participants in the African American Study of Kidney Disease and Hypertension (AASK, n =703), the Chronic Renal Insufficiency Cohort (CRIC) study ( n =3196), and the Atherosclerosis Risk in Communities (ARIC) study ( n =4378). We compared baseline characteristics by testican-2 tertile and used Cox proportional hazards models to study the association of testican-2 with incident ESKD. RESULTS Higher testican-2 levels were associated with higher measured GFR (mGFR) in AASK, higher eGFR in the CRIC and ARIC studies, and lower albuminuria in all cohorts. Baseline testican-2 levels were significantly associated with incident ESKD in Cox proportional hazards models adjusted for age, sex, and race (model 1) and model 1+mGFR or eGFR+comorbidities (model 2). In model 3 (model 2+proteinuria), the associations between testican-2 (per SD increase) and incident ESKD were AASK (hazard ratio [HR]=0.84 [0.72 to 0.98], P =0.023), CRIC (HR=0.95 [0.89 to 1.02], P =0.14), ARIC (HR=0.54 [0.36 to 0.83], P =0.0044), and meta-analysis (HR=0.92 [0.86 to 0.98], P =0.0073). CONCLUSIONS Across three cohorts spanning >8000 individuals, testican-2 is associated with kidney health and prognosis, with higher levels associated with reduced risk of ESKD.
Collapse
Affiliation(s)
- Donghai Wen
- Nephrology Division, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Linda Zhou
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Zihe Zheng
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Aditya Surapaneni
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Christie M. Ballantyne
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Ron C. Hoogeveen
- Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Michael G. Shlipak
- Kidney Health Research Collaborative, Department of Medicine, San Francisco Veterans Affairs Health Care System
- University of California, San Francisco, California
| | - Sushrut S. Waikar
- Section of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts
| | - Ramachandran S. Vasan
- Sections of Preventive Medicine and Epidemiology and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Paul L. Kimmel
- Division of Kidney Urologic and Hematologic Diseases, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland
| | - Ruth F. Dubin
- Division of Nephrology, San Francisco VA Medical Center, University of California, San Francisco, California
| | - Rajat Deo
- Division of Cardiology, Electrophysiology Section, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Harold I. Feldman
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Peter Ganz
- Cardiovascular Division, Zuckerberg San Francisco General Hospital, University of California, San Francisco, California
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Morgan E. Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Eugene P. Rhee
- Nephrology Division, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| |
Collapse
|
7
|
Kaiser KA, Loffredo LF, Santos-Alexis KDL, Ringham OR, Arpaia N. Regulation of the alveolar regenerative niche by amphiregulin-producing regulatory T cells. J Exp Med 2022; 220:213767. [PMID: 36534084 PMCID: PMC9767680 DOI: 10.1084/jem.20221462] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/26/2022] [Accepted: 11/16/2022] [Indexed: 12/23/2022] Open
Abstract
Following respiratory viral infection, regeneration of the epithelial barrier is required to preserve lung function and prevent secondary infections. Lung regulatory T (Treg) cells are critical for maintaining blood oxygenation following influenza virus infection through production of the EGFR ligand amphiregulin (Areg); however, how Treg cells engage with progenitors within the alveolar niche is unknown. Here, we describe local interactions between Treg cells and an Areg-responsive population of Col14a1+EGFR+ lung mesenchymal cells that mediate type II alveolar epithelial (AT2) cell-mediated regeneration following influenza virus infection. We propose a mechanism whereby Treg cells are deployed to sites of damage and provide pro-survival cues that support mesenchymal programming of the alveolar niche. In the absence of fibroblast EGFR signaling, we observe impaired AT2 proliferation and disrupted lung remodeling following viral clearance, uncovering a crucial immune/mesenchymal/epithelial network that guides alveolar regeneration.
Collapse
Affiliation(s)
- Katherine A. Kaiser
- Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Lucas F. Loffredo
- Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Olivia R. Ringham
- Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Nicholas Arpaia
- Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, USA,Correspondence to Nicholas Arpaia:
| |
Collapse
|
8
|
Forst CV, Martin-Sancho L, Tripathi S, Wang G, Dos Anjos Borges LG, Wang M, Geber A, Lashua L, Ding T, Zhou X, Carter CE, Metreveli G, Rodriguez-Frandsen A, Urbanowski MD, White KM, Stein DA, Moulton H, Chanda SK, Pache L, Shaw ML, Ross TM, Ghedin E, García-Sastre A, Zhang B. Common and species-specific molecular signatures, networks, and regulators of influenza virus infection in mice, ferrets, and humans. SCIENCE ADVANCES 2022; 8:eabm5859. [PMID: 36197970 PMCID: PMC9534503 DOI: 10.1126/sciadv.abm5859] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 08/11/2022] [Indexed: 05/04/2023]
Abstract
Molecular responses to influenza A virus (IAV) infections vary between mammalian species. To identify conserved and species-specific molecular responses, we perform a comparative study of transcriptomic data derived from blood cells, primary epithelial cells, and lung tissues collected from IAV-infected humans, ferrets, and mice. The molecular responses in the human host have unique functions such as antigen processing that are not observed in mice or ferrets. Highly conserved gene coexpression modules across the three species are enriched for IAV infection-induced pathways including cell cycle and interferon (IFN) signaling. TDRD7 is predicted as an IFN-inducible host factor that is up-regulated upon IAV infection in the three species. TDRD7 is required for antiviral IFN response, potentially modulating IFN signaling via the JAK/STAT/IRF9 pathway. Identification of the common and species-specific molecular signatures, networks, and regulators of IAV infection provides insights into host-defense mechanisms and will facilitate the development of novel therapeutic interventions against IAV infection.
Collapse
Affiliation(s)
- Christian V. Forst
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
| | - Laura Martin-Sancho
- Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Shashank Tripathi
- Centre for Infectious Disease Research, Department of Microbiology and Cell Biology, Indian Institute of Science, Bengaluru 560012, India
| | - Guojun Wang
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, People’s Republic of China
| | | | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Adam Geber
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Lauren Lashua
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Tao Ding
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Xianxiao Zhou
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Chalise E. Carter
- Department of Infectious Diseases, Center for Vaccines and Immunology, University of Georgia, Athens, GA 30602, USA
| | - Giorgi Metreveli
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
| | - Ariel Rodriguez-Frandsen
- Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Matthew D. Urbanowski
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
| | - Kris M. White
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
| | - David A. Stein
- Department of Biomedical Sciences, College of Veterinary Medicine, Oregon State University, Corvallis, OR 97331, USA
| | - Hong Moulton
- Department of Biomedical Sciences, College of Veterinary Medicine, Oregon State University, Corvallis, OR 97331, USA
| | - Sumit K. Chanda
- Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Lars Pache
- Infectious and Inflammatory Disease Center, Sanford Burnham Prebys Medical Discovery Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Megan L. Shaw
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
| | - Ted M. Ross
- Department of Infectious Diseases, Center for Vaccines and Immunology, University of Georgia, Athens, GA 30602, USA
| | - Elodie Ghedin
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
- Systems Genomics Section, Laboratory of Parasitic Diseases, NIAID, NIH, Bethesda, MD 20892, USA
| | - Adolfo García-Sastre
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
- Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
- The Tisch Cancer Center, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| |
Collapse
|
9
|
Mikhaylova AV, McHugh CP, Polfus LM, Raffield LM, Boorgula MP, Blackwell TW, Brody JA, Broome J, Chami N, Chen MH, Conomos MP, Cox C, Curran JE, Daya M, Ekunwe L, Glahn DC, Heard-Costa N, Highland HM, Hobbs BD, Ilboudo Y, Jain D, Lange LA, Miller-Fleming TW, Min N, Moon JY, Preuss MH, Rosen J, Ryan K, Smith AV, Sun Q, Surendran P, de Vries PS, Walter K, Wang Z, Wheeler M, Yanek LR, Zhong X, Abecasis GR, Almasy L, Barnes KC, Beaty TH, Becker LC, Blangero J, Boerwinkle E, Butterworth AS, Chavan S, Cho MH, Choquet H, Correa A, Cox N, DeMeo DL, Faraday N, Fornage M, Gerszten RE, Hou L, Johnson AD, Jorgenson E, Kaplan R, Kooperberg C, Kundu K, Laurie CA, Lettre G, Lewis JP, Li B, Li Y, Lloyd-Jones DM, Loos RJF, Manichaikul A, Meyers DA, Mitchell BD, Morrison AC, Ngo D, Nickerson DA, Nongmaithem S, North KE, O'Connell JR, Ortega VE, Pankratz N, Perry JA, Psaty BM, Rich SS, Soranzo N, Rotter JI, Silverman EK, Smith NL, Tang H, Tracy RP, Thornton TA, Vasan RS, Zein J, Mathias RA, Reiner AP, Auer PL. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program. Am J Hum Genet 2021; 108:1836-1851. [PMID: 34582791 PMCID: PMC8546043 DOI: 10.1016/j.ajhg.2021.08.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 08/11/2021] [Indexed: 12/15/2022] Open
Abstract
Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.
Collapse
MESH Headings
- Asthma/epidemiology
- Asthma/genetics
- Asthma/metabolism
- Asthma/pathology
- Biomarkers/metabolism
- Dermatitis, Atopic/epidemiology
- Dermatitis, Atopic/genetics
- Dermatitis, Atopic/metabolism
- Dermatitis, Atopic/pathology
- Genetic Predisposition to Disease
- Genome, Human
- Genome-Wide Association Study
- Humans
- Leukocytes/pathology
- National Heart, Lung, and Blood Institute (U.S.)
- Phenotype
- Polymorphism, Single Nucleotide
- Prognosis
- Proteome/analysis
- Proteome/metabolism
- Pulmonary Disease, Chronic Obstructive/epidemiology
- Pulmonary Disease, Chronic Obstructive/genetics
- Pulmonary Disease, Chronic Obstructive/metabolism
- Pulmonary Disease, Chronic Obstructive/pathology
- Quantitative Trait Loci
- United Kingdom/epidemiology
- United States/epidemiology
- Whole Genome Sequencing
Collapse
Affiliation(s)
- Anna V Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Caitlin P McHugh
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Linda M Polfus
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Meher Preethi Boorgula
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Thomas W Blackwell
- TOPMed Informatics Research Center, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98105, USA
| | - Jai Broome
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Nathalie Chami
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Ming-Huei Chen
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA; National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01701, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Corey Cox
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78539, USA
| | - Michelle Daya
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Lynette Ekunwe
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA 02155, USA
| | - Nancy Heard-Costa
- National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01701, USA; Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Yann Ilboudo
- Montréal Heart Institute, Montréal, Québec H1T 1C8, Canada; Faculté de Médecine, Université de Montréal, Montréal, Québec H1T 1C8, Canada
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tyne W Miller-Fleming
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37240, USA
| | - Nancy Min
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Jonathon Rosen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kathleen Ryan
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Albert V Smith
- TOPMed Informatics Research Center, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge CB1 8RN, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB1 8RN, UK; Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Klaudia Walter
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Marsha Wheeler
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Xue Zhong
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37240, USA
| | - Goncalo R Abecasis
- TOPMed Informatics Research Center, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Laura Almasy
- Department of Biomedical and Health Informatics, the Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Kathleen C Barnes
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Terri H Beaty
- School of Public Health, John Hopkins University, Baltimore, MD 21205, USA
| | - Lewis C Becker
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78539, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge CB1 8RN, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB1 8RN, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge CB1 8RN, UK; National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge CB1 8RN, UK
| | - Sameer Chavan
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94601, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Nancy Cox
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37240, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Myriam Fornage
- University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Lifang Hou
- Institute for Public Health and Medicine, Northwestern University, Chicago, IL 60661, USA
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA; National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01701, USA
| | | | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Kousik Kundu
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK; Department of Haematology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
| | - Guillaume Lettre
- Montréal Heart Institute, Montréal, Québec H1T 1C8, Canada; Faculté de Médecine, Université de Montréal, Montréal, Québec H1T 1C8, Canada
| | - Joshua P Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
| | - Yun Li
- Departments of Biostatistics, Genetics, and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Donald M Lloyd-Jones
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60661, USA; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60661, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Deborah A Meyers
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ 85724, USA
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD 21201, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Debby Ngo
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA
| | - Suraj Nongmaithem
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jeffrey R O'Connell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Victor E Ortega
- Department of Internal Medicine, Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - James A Perry
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Bruce M Psaty
- Department of Epidemiology, University of Washington, Seattle, WA 98105, USA; Department of Health Service, University of Washington, Seattle, WA 98105, USA; Department of Medicine, University of Washington, Seattle, WA 98105, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Nicole Soranzo
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge CB1 8RN, UK; Department of Haematology, University of Cambridge, Cambridge CB1 8RN, UK; British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge CB1 8RN, UK
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA 98105, USA; Department of Health Service, University of Washington, Seattle, WA 98105, USA; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA 98105, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine and Department of Biochemistry, University of Vermont Larner College of Medicine, Colchester, VT 05446, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98105, USA; Regeneron Genetics Center, Tarrytown, NY 10591, USA
| | - Ramachandran S Vasan
- National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01701, USA; Departments of Cardiology and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Joe Zein
- Respiratory Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Rasika A Mathias
- Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Alexander P Reiner
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin, Milwaukee, Milwaukee, WI 53205, USA.
| |
Collapse
|
10
|
Kokelj S, Östling J, Georgi B, Fromell K, Ekdahl KN, Olsson HK, Olin AC. Smoking induces sex-specific changes in the small airway proteome. Respir Res 2021; 22:234. [PMID: 34429114 PMCID: PMC8385797 DOI: 10.1186/s12931-021-01825-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 07/12/2021] [Indexed: 12/31/2022] Open
Abstract
Introduction Cigarette smoke triggers many cellular and signaling responses in the lung and the resulting inflammation plays a central role in smoke-related lung diseases, such as COPD. We explored the effects of smoking on the small airway proteome in samples obtained by collection of exhaled particles with the aim to identify specific proteins dysregulated by smoking. Methods Exhaled particles were obtained from 38 current smokers, 47 former smokers and 22 healthy controls with the PExA method. 120 ng of sample was collected from individual subjects and analyzed with the SOMAscan proteomics platform. General linear model-based statistics were performed. Results Two hundred and three proteins were detected in at least half of 107 total samples. Active smoking exerted a significant impact on the protein composition of respiratory tract lining fluid (RTLF), with 81 proteins altered in current smokers compared to never smokers (p < 0.05, q < 0.124). Among the proteins most clearly discriminating between current and never smokers were sRAGE, FSTL3, SPOCK2 and protein S, all of them being less abundant in current smokers. Analysis stratified for sex unveiled sex differences with more pronounced proteomic alterations due to active smoking in females than males. Proteins whose abundance was altered by active smoking in women were to a larger extent related to the complement system. The small airway protein profile of former smokers appeared to be more similar to that observed in never smokers. Conclusions The study shows that smoking has a strong impact on protein expression in the small airways, and that smoking affects men and women differently, suggesting PExA sampling combined with high sensitivity protein analysis offers a promising platform for early detection of COPD and identification of novel COPD drug targets. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-021-01825-6.
Collapse
Affiliation(s)
- Spela Kokelj
- Occupational and Environmental Medicine, School of Public Health and Community Medicine, Inst. of Medicine, Sahlgrenska Academy, University of Gothenburg, Box 414, 405 30, Gothenburg, Sweden.
| | - Jörgen Östling
- PExA AB, Gothenburg, Sweden.,Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, AstraZeneca, BioPharmaceuticals R&D, Gothenburg, Sweden
| | - Benjamin Georgi
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, AstraZeneca, BioPharmaceuticals R&D, Gothenburg, Sweden
| | - Karin Fromell
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Kristina Nilsson Ekdahl
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.,Linnaeus Centre for Biomaterials Chemistry, Linnaeus University, Kalmar, Sweden
| | - Henric K Olsson
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, AstraZeneca, BioPharmaceuticals R&D, Gothenburg, Sweden
| | - Anna-Carin Olin
- Occupational and Environmental Medicine, School of Public Health and Community Medicine, Inst. of Medicine, Sahlgrenska Academy, University of Gothenburg, Box 414, 405 30, Gothenburg, Sweden
| |
Collapse
|
11
|
Tu Z, He X, Zeng L, Meng D, Zhuang R, Zhao J, Dai W. Exploration of Prognostic Biomarkers for Lung Adenocarcinoma Through Bioinformatics Analysis. Front Genet 2021; 12:647521. [PMID: 33968130 PMCID: PMC8100590 DOI: 10.3389/fgene.2021.647521] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 03/30/2021] [Indexed: 12/30/2022] Open
Abstract
With the development of computer technology, screening cancer biomarkers based on public databases has become a common research method. Here, an eight-gene prognostic model, which could be used to judge the prognosis of patients with lung adenocarcinoma (LUAD), was developed through bioinformatics methods. This study firstly used several gene datasets from GEO database to mine differentially expressed genes (DEGs) in LUAD tissue and healthy tissue via joint analysis. Later, enrichment analysis for the DEGs was performed, and it was found that the DEGs were mainly activated in pathways involved in extracellular matrix, cell adhesion, and leukocyte migration. Afterward, a TCGA cohort was used to perform univariate Cox, least absolute shrinkage and selection operator method, and multivariate Cox regression analyses for the DEGs, and a prognostic model consisting of eight genes (GPX3, TCN1, ASPM, PCP4, CAV2, S100P, COL1A1, and SPOK2) was established. Receiver operation characteristic (ROC) curve was then used to substantiate the diagnostic efficacy of the prognostic model. The survival significance of signature genes was verified through the GEPIA database, and the results exhibited that the risk coefficients of the eight genes were basically congruous with the effects of these genes on the prognosis in the GEPIA database, which suggested that the results were accurate. Finally, combined with clinical characteristics of patients, the diagnostic independence of the prognostic model was further validated through univariate and multivariate regression, and the results indicated that the model had independent prognostic value. The overall finding of the study manifested that the eight-gene prognostic model is closely related to the prognosis of LUAD patients, and can be used as an independent prognostic indicator. Additionally, the prognostic model in this study can help doctors make a better diagnosis in treatment and ultimately benefit LUAD patients.
Collapse
Affiliation(s)
- Zhengliang Tu
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiangfeng He
- Department of Thoracic Surgery, Zhuji People's Hospital, Zhuji, China
| | - Liping Zeng
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Di Meng
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Runzhou Zhuang
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiangang Zhao
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wanrong Dai
- Department of Pharmacy, The First Affiliated Hospital, College of Medicine, Hangzhou, China
| |
Collapse
|
12
|
Zhao J, Cheng M, Gai J, Zhang R, Du T, Li Q. SPOCK2 Serves as a Potential Prognostic Marker and Correlates With Immune Infiltration in Lung Adenocarcinoma. Front Genet 2020; 11:588499. [PMID: 33244319 PMCID: PMC7683796 DOI: 10.3389/fgene.2020.588499] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 10/21/2020] [Indexed: 12/31/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is one of the major types of lung cancer. Tumor-infiltrating immune cells (TIICs) are positively associated with overall survival (OS) in LUAD. The SPARC/osteonectin, cwcv and kazal-like domains proteoglycan 2 (SPOCK2) is a complex type of secreted proteoglycan involved in forming a protective barrier against viral infection. The purpose of this study was to investigate the relationship between SPOCK2 and TIICs and the prognostic role of SPOCK2 in LUAD. The GEPIA2, GEO, CPTAC, and HPA databases were analyzed to examine both the mRNA and protein expression of SPOCK2 in LUAD. GEPIA2 and the Kaplan-Meier Plotter (KM Plotter) were used to evaluate the prognostic value of SPOCK2 in LUAD patients. TCGA data were examined for a correlation between SPOCK2 expression and clinical characteristics. Gene enrichment analyses were performed to explore the underlying mechanism of SPOCK2 based on LinkedOmics. RegNetwork was used to predict the regulators of SPOCK2. The correlation between SPOCK2 and TIICs, including immune infiltration level and relative proportion was investigated via TIMER. KM Plotter was also used to evaluate the prognostic role of SPOCK2 expression in LUAD with enriched and decreased TIIC subgroups. We found SPOCK2 was significantly downregulated in LUAD compared with that in non-tumor controls and was correlated with clinical parameters. Moreover, a high SPOCK2 expression level predicted better survival. The SPOCK2-associated regulatory network was constructed. SPOCK2 influenced the TIIC infiltration level and relative proportion in LUAD. Furthermore, a high SPOCK2 expression level was associated with a favorable prognosis in enriched CD4 + T cells and macrophage subgroups in LUAD. In conclusion, a high level of SPOCK2 expression predicted favorable prognosis and was significantly correlated with TIICs in LUAD. Therefore, the expression of SPOCK2 may affect the prognosis of LUAD partly due to TIICs.
Collapse
Affiliation(s)
- Jinming Zhao
- Department of Pathology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Ming Cheng
- Department of Pathology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Junda Gai
- Department of Pathology, College of Basic Medical Sciences, China Medical University, Shenyang, China.,Department of Pathology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Ruochen Zhang
- Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, United States
| | - Tengjiao Du
- Department of Pathology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Qingchang Li
- Department of Pathology, College of Basic Medical Sciences, China Medical University, Shenyang, China.,Department of Pathology, The First Affiliated Hospital of China Medical University, Shenyang, China
| |
Collapse
|