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9 results on '"Duclos, Grant"'

1. Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways

Author

Xu, Ke, Shi, Xingyi, Husted, Christopher, Hong, Rui, Wang, Yichen, Ning, Boting, Sullivan, Travis B., Rieger-Christ, Kimberly M., Duan, Fenghai, Marques, Helga, Gower, Adam C., Xiao, Xiaohui, Liu, Hanqiao, Liu, Gang, Duclos, Grant, Platt, Michael, Spira, Avrum E., Mazzilli, Sarah A., Billatos, Ehab, Lenburg, Marc E., Campbell, Joshua D., and Beane, Jennifer E.

Published
2022
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2. Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Author

Muus, Christoph, Luecken, Malte D., Eraslan, Gökcen, Sikkema, Lisa, Waghray, Avinash, Heimberg, Graham, Kobayashi, Yoshihiko, Vaishnav, Eeshit Dhaval, Subramanian, Ayshwarya, Smillie, Christopher, Jagadeesh, Karthik A., Duong, Elizabeth Thu, Fiskin, Evgenij, Torlai Triglia, Elena, Ansari, Meshal, Cai, Peiwen, Lin, Brian, Buchanan, Justin, Chen, Sijia, Shu, Jian, Haber, Adam L., Chung, Hattie, Montoro, Daniel T., Adams, Taylor, Aliee, Hananeh, Allon, Samuel J., Andrusivova, Zaneta, Angelidis, Ilias, Ashenberg, Orr, Bassler, Kevin, Bécavin, Christophe, Benhar, Inbal, Bergenstråhle, Joseph, Bergenstråhle, Ludvig, Bolt, Liam, Braun, Emelie, Bui, Linh T., Callori, Steven, Chaffin, Mark, Chichelnitskiy, Evgeny, Chiou, Joshua, Conlon, Thomas M., Cuoco, Michael S., Cuomo, Anna S. E., Deprez, Marie, Duclos, Grant, Fine, Denise, Fischer, David S., Ghazanfar, Shila, Gillich, Astrid, Giotti, Bruno, Gould, Joshua, Guo, Minzhe, Gutierrez, Austin J., Habermann, Arun C., Harvey, Tyler, He, Peng, Hou, Xiaomeng, Hu, Lijuan, Hu, Yan, Jaiswal, Alok, Ji, Lu, Jiang, Peiyong, Kapellos, Theodoros S., Kuo, Christin S., Larsson, Ludvig, Leney-Greene, Michael A., Lim, Kyungtae, Litviňuková, Monika, Ludwig, Leif S., Lukassen, Soeren, Luo, Wendy, Maatz, Henrike, Madissoon, Elo, Mamanova, Lira, Manakongtreecheep, Kasidet, Leroy, Sylvie, Mayr, Christoph H., Mbano, Ian M., McAdams, Alexi M., Nabhan, Ahmad N., Nyquist, Sarah K., Penland, Lolita, Poirion, Olivier B., Poli, Sergio, Qi, CanCan, Queen, Rachel, Reichart, Daniel, Rosas, Ivan, Schupp, Jonas C., Shea, Conor V., Shi, Xingyi, Sinha, Rahul, Sit, Rene V., Slowikowski, Kamil, Slyper, Michal, Smith, Neal P., Sountoulidis, Alex, Strunz, Maximilian, Sullivan, Travis B., Sun, Dawei, Talavera-López, Carlos, Tan, Peng, Tantivit, Jessica, Travaglini, Kyle J., Tucker, Nathan R., Vernon, Katherine A., Wadsworth, Marc H., Waldman, Julia, Wang, Xiuting, Xu, Ke, Yan, Wenjun, Zhao, William, and Ziegler, Carly G. K.

Published
2021
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3. Molecular subtyping reveals immune alterations associated with progression of bronchial premalignant lesions

Author

Beane, Jennifer E., Mazzilli, Sarah A., Campbell, Joshua D., Duclos, Grant, Krysan, Kostyantyn, Moy, Christopher, Perdomo, Catalina, Schaffer, Michael, Liu, Gang, Zhang, Sherry, Liu, Hanqiao, Vick, Jessica, Dhillon, Samjot S., Platero, Suso J., Dubinett, Steven M., Stevenson, Christopher, Reid, Mary E., Lenburg, Marc E., and Spira, Avrum E.

Published
2019
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4. A Dynamic Bronchial Airway Gene Expression Signature of Chronic Obstructive Pulmonary Disease and Lung Function Impairment

Author

Steiling, Katrina, van den Berge, Maarten, Hijazi, Kahkeshan, Florido, Roberta, Campbell, Joshua, Liu, Gang, Xiao, Ji, Zhang, Xiaohui, Duclos, Grant, Drizik, Eduard, Si, Huiqing, Perdomo, Catalina, Dumont, Charles, Coxson, Harvey O., Alekseyev, Yuriy O., Sin, Don, Pare, Peter, Hogg, James C., McWilliams, Annette, Hiemstra, Pieter S., Sterk, Peter J., Timens, Wim, Chang, Jeffrey T., Sebastiani, Paola, OʼConnor, George T., Bild, Andrea H., Postma, Dirkje S., Lam, Stephen, Spira, Avrum, and Lenburg, Marc E.

Published
2013
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5. Associations of autoantibodies, autoimmune risk alleles, and clinical diagnoses from the electronic medical records in rheumatoid arthritis cases and non–rheumatoid arthritis controls

Author

Liao, Katherine P., Kurreeman, Fina, Li, Gang, Duclos, Grant, Murphy, Shawn, Guzman, Raul, Cai, Tianxi, Gupta, Namrata, Gainer, Vivian, Schur, Peter, Cui, Jing, Denny, Joshua C., Szolovits, Peter, Churchill, Susanne, Kohane, Isaac, Karlson, Elizabeth W., and Plenge, Robert M.

Published
2013
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6. Characterizing smoking-induced transcriptional heterogeneity in the human bronchial epithelium at single-cell resolution.

Author

Duclos, Grant E., Teixeira, Vitor H., Autissier, Patrick, Gesthalter, Yaron B., Reinders-Luinge, Marjan A., Terrano, Robert, Dumas, Yves M., Gang Liu, Mazzilli, Sarah A., Brandsma, Corry-Anke, van den Berge, Maarten, Janes, Sam M., Timens, Wim, Lenburg, Marc E., Spira, Avrum, Campbell, Joshua D., and Beane, Jennifer

Subjects
*HABIT breaking, *EPITHELIUM, *METHYL vinyl ketone
Abstract

The article informs about characterizing smoking-induced transcriptional heterogeneity in the human bronchial epithelium at single-cell resolution. Topics discussed include human bronchial epithelium is composed of distinct cell types that cooperate to defend against environmental insults; characterization of a set of toxin metabolism genes; and cellular alterations may prime the human bronchial epithelium for disease.

Published
2019
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7. Autoantibodies, autoimmune risk alleles and clinical associations in rheumatoid arthritis cases and non-RA controls in the electronic medical records

Author

Liao, Katherine P., Kurreeman, Fina, Li, Gang, Duclos, Grant, Murphy, Shawn N., Guzman, Raul, Cai, Tianxi, Gupta, Namrata, Gainer, Vivian, Schur, Peter, Cui, Jing, Denny, Joshua C., Szolovits, Peter, Churchill, Susanne, Kohane, Isaac, Karlson, Elizabeth W., Plenge, Robert M., Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, and Szolovits, Peter

Abstract

Objective: The significance of non–rheumatoid arthritis (RA) autoantibodies in patients with RA is unclear. The aim of this study was to assess associations of autoantibodies with autoimmune risk alleles and with clinical diagnoses from the electronic medical records (EMRs) among RA cases and non-RA controls. Methods: Data on 1,290 RA cases and 1,236 non-RA controls of European genetic ancestry were obtained from the EMRs of 2 large academic centers. The levels of anti–citrullinated protein antibodies (ACPAs), antinuclear antibodies (ANAs), anti–tissue transglutaminase antibodies (AGTAs), and anti–thyroid peroxidase (anti-TPO) antibodies were measured. All subjects were genotyped for autoimmune risk alleles, and the association between number of autoimmune risk alleles present and number of types of autoantibodies present was studied. A phenome-wide association study (PheWAS) was conducted to study potential associations between autoantibodies and clinical diagnoses among RA cases and non-RA controls. Results: The mean ages were 60.7 years in RA cases and 64.6 years in non-RA controls. The proportion of female subjects was 79% in each group. The prevalence of ACPAs and ANAs was higher in RA cases compared to controls (each P < 0.0001); there were no differences in the prevalence of anti-TPO antibodies and AGTAs. Carriage of higher numbers of autoimmune risk alleles was associated with increasing numbers of autoantibody types in RA cases (P = 2.1 × 10[superscript −5]) and non-RA controls (P = 5.0 × 10[superscript −3]). From the PheWAS, the presence of ANAs was significantly associated with a diagnosis of Sjögren's/sicca syndrome in RA cases. Conclusion: The increased frequency of autoantibodies in RA cases and non-RA controls was associated with the number of autoimmune risk alleles carried by an individual. PheWAS of EMR data, with linkage to laboratory data obtained from blood samples, provide a novel method to test for the clinical significance of biomarkers in disease., National Institutes of Health (U.S.) (Grant U54-LM-008748)

Published
2012

8. Human Genetics in Rheumatoid Arthritis Guides a High-Throughput Drug Screen of the CD40 Signaling Pathway

Author

Li, Gang, Diogo, Dorothée, Wu, Di, Spoonamore, Jim, Dancik, Vlado, Franke, Lude, Kurreeman, Fina, Rossin, Elizabeth J., Duclos, Grant, Hartland, Cathy, Zhou, Xuezhong, Li, Kejie, Liu, Jun, De Jager, Philip L., Siminovitch, Katherine A., Zhernakova, Alexandra, Raychaudhuri, Soumya, Bowes, John, Eyre, Steve, and Padyukov, Leonid

Subjects
GENETICS of rheumatoid arthritis, HUMAN genetics, ARTHRITIS, GENETICS of autoimmune diseases, PHENOTYPES, GENETICS
Abstract

Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4×10−9). Second, we demonstrate that subjects homozygous for the RA risk allele have ∼33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10−9), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA–approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA. [ABSTRACT FROM AUTHOR]

Published
2013
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9. Smoking Modulates Different Secretory Subpopulations Expressing SARS-CoV-2 Entry Genes in the Nasal and Bronchial Airways.

Author

Xu K, Shi X, Husted C, Hong R, Wang Y, Ning B, Sullivan T, Rieger-Christ K, Duan F, Marques H, Gower A, Xiao X, Liu H, Liu G, Duclos G, Platt M, Spira A, Mazzilli S, Billatos E, Lenburg M, Campbell J, and Beane J

Abstract

Background : SARS-CoV-2 infection and disease severity are influenced by viral entry (VE) gene expression patterns in airway epithelium. The similarities and differences of VE gene expression (ACE2, TMPRSS2, and CTSL) across nasal and bronchial compartments has not been fully characterized using matched samples from large cohorts. Results : Gene expression data from 793 nasal and 1,673 bronchial brushes obtained from individuals participating in lung cancer screening or diagnostic workup revealed that smoking was the only clinical factor significantly and reproducibly associated with VE gene expression. ACE2 and TMPRSS2 expression were higher in smokers in the bronchus but not in the nose. scRNA-seq of nasal brushings indicated that ACE2 co-expressed genes were highly expressed in club and C15orf48 + secretory cells while TMPRSS2 co-expressed genes were highly expressed in keratinizing epithelial cells. In contrast, these ACE2 and TMPRSS2 modules were highly expressed in goblet cells in scRNA-seq from bronchial brushings. Cell-type deconvolution of the RNA-seq confirmed that smoking increased the abundance of several secretory cell populations in the bronchus, but only goblet cells in the nose. Conclusions : The association of ACE2 and TMPRSS2 with smoking in the bronchus is due to their high expression in goblet cells which increase in abundance in current smoker airways. In contrast, in the nose these genes are not predominantly expressed in cell populations modulated by smoking. Smoking-induced VE gene expression changes in the nose likely has minimal impact on SARS-CoV-2 infection, but in the bronchus, smoking may lead to higher viral loads and more severe disease.

Published
2021
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