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Article ; Online: A no-Wnt situation for alveolar macrophage self-renewal.

Suber, Tomeka / Camiolo, Matthew J / Ray, Anuradha

2021 Volume 54, Issue 6, Page(s) 1099–1101

Abstract: Alveolar macrophages (AMs) are central to defense against respiratory pathogens. Impediments in restoring AMs after infection increase the risk for superinfection, which is associated with significant morbidity and mortality worldwide. In this issue of ... ...

Abstract	Alveolar macrophages (AMs) are central to defense against respiratory pathogens. Impediments in restoring AMs after infection increase the risk for superinfection, which is associated with significant morbidity and mortality worldwide. In this issue of Immunity, Zhu et al. report a Wnt-β-catenin-HIF-1α axis in AMs that promotes an inflammatory phenotype while restricting proliferation and self-renewal.
MeSH term(s)	Macrophages, Alveolar ; Phenotype
Language	English
Publishing date	2021-06-07
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	1217235-2
ISSN	1097-4180 ; 1074-7613
ISSN (online)	1097-4180
ISSN	1074-7613
DOI	10.1016/j.immuni.2021.05.013
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Article ; Online: Using ICLite for deconvolution of bulk transcriptional data from mixed cell populations.

Camiolo, Matthew J / Wenzel, Sally E / Ray, Anuradha

STAR protocols

2021 Volume 2, Issue 4, Page(s) 100847

Abstract: ... on the use and execution of this protocol, please refer to Camiolo et al. (2021). ...

Abstract	Bulk expression data from heterogeneous cell populations pose a challenge for investigators, as differences in cell numbers and transcriptional programs may complicate analysis. To improve the performance of bulk RNA sequencing on mixed populations, we created Immune Cell Linkage through Exploratory Matrices (ICLite). The ICLite package for R constructs modules of correlated genes and identifies their relationship to specific lineages in mixed cell populations. This protocol details formatting, optimization of run parameters, and interpretation of results following implementation of ICLite. For complete details on the use and execution of this protocol, please refer to Camiolo et al. (2021).
MeSH term(s)	Base Sequence ; Gene Expression Profiling/methods ; Sequence Analysis, RNA/methods
Language	English
Publishing date	2021-09-27
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2666-1667
ISSN (online)	2666-1667
DOI	10.1016/j.xpro.2021.100847
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Article ; Online: Using ICLite for deconvolution of bulk transcriptional data from mixed cell populations

Matthew J. Camiolo / Sally E. Wenzel / Anuradha Ray

STAR Protocols, Vol 2, Iss 4, Pp 100847- (2021)

2021

Abstract: ... on the use and execution of this protocol, please refer to Camiolo et al. (2021). ...

Abstract	Summary: Bulk expression data from heterogeneous cell populations pose a challenge for investigators, as differences in cell numbers and transcriptional programs may complicate analysis. To improve the performance of bulk RNA sequencing on mixed populations, we created Immune Cell Linkage through Exploratory Matrices (ICLite). The ICLite package for R constructs modules of correlated genes and identifies their relationship to specific lineages in mixed cell populations. This protocol details formatting, optimization of run parameters, and interpretation of results following implementation of ICLite.For complete details on the use and execution of this protocol, please refer to Camiolo et al. (2021).
Keywords	Bioinformatics ; Sequence analysis ; Immunology ; Gene Expression ; Systems biology ; Science (General) ; Q1-390
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Immune responses and exacerbations in severe asthma.

Camiolo, Matthew J / Kale, Sagar L / Oriss, Timothy B / Gauthier, Marc / Ray, Anuradha

Current opinion in immunology

2021 Volume 72, Page(s) 34–42

Abstract: Asthma as a clinical entity manifests with a broad spectrum of disease severity. Unlike milder asthma, severe disease is poorly controlled by inhaled corticosteroids, the current standard of care. Transcriptomic data, along with patient characteristics ... ...

Abstract	Asthma as a clinical entity manifests with a broad spectrum of disease severity. Unlike milder asthma, severe disease is poorly controlled by inhaled corticosteroids, the current standard of care. Transcriptomic data, along with patient characteristics and response to biologics show that though Type 2 (T2) immune response remains an integral feature of asthma, additional molecular and immunologic factors may play important roles in pathogenesis. Mechanisms of T2 development, cellular sources of T2 cytokines and their relationship to additional immune pathways concurrently activated may distinguish several different subphenotypes, and perhaps endotypes of asthma, with differential response to non-specific and targeted anti-inflammatory therapies. Recent data have also associated non-T2 cytokines derived from T cells, particularly IFN-γ, and epithelial mediators with severe asthma. These topics and their relationships to acute asthma exacerbations are discussed in this review.
MeSH term(s)	Allergens/immunology ; Animals ; Asthma/diagnosis ; Asthma/immunology ; Asthma/metabolism ; Cytokines/metabolism ; Disease Progression ; Disease Susceptibility/immunology ; Eosinophils/immunology ; Eosinophils/metabolism ; Host-Pathogen Interactions/genetics ; Host-Pathogen Interactions/immunology ; Humans ; Immunity ; Immunization ; Neutrophils/immunology ; Neutrophils/metabolism ; Organ Specificity/immunology ; Severity of Illness Index ; T-Lymphocyte Subsets/immunology ; T-Lymphocyte Subsets/metabolism
Chemical Substances	Allergens ; Cytokines
Language	English
Publishing date	2021-03-24
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1035767-1
ISSN	1879-0372 ; 0952-7915
ISSN (online)	1879-0372
ISSN	0952-7915
DOI	10.1016/j.coi.2021.03.004
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Article ; Online: Are We Meeting the Promise of Endotypes and Precision Medicine in Asthma?

Ray, Anuradha / Camiolo, Matthew / Fitzpatrick, Anne / Gauthier, Marc / Wenzel, Sally E

Physiological reviews

2020 Volume 100, Issue 3, Page(s) 983–1017

Abstract: While the ... ...

Abstract	While the term
MeSH term(s)	Anti-Asthmatic Agents/therapeutic use ; Asthma/drug therapy ; Asthma/pathology ; Biomarkers ; Genetic Predisposition to Disease ; Humans ; Precision Medicine
Chemical Substances	Anti-Asthmatic Agents ; Biomarkers
Language	English
Publishing date	2020-01-09
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Review
ZDB-ID	209902-0
ISSN	1522-1210 ; 0031-9333
ISSN (online)	1522-1210
ISSN	0031-9333
DOI	10.1152/physrev.00023.2019
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Article ; Online: Expression of SARS-CoV-2 receptor ACE2 and coincident host response signature varies by asthma inflammatory phenotype.

Camiolo, Matthew / Gauthier, Marc / Kaminski, Naftali / Ray, Anuradha / Wenzel, Sally E

The Journal of allergy and clinical immunology

2020 Volume 146, Issue 2, Page(s) 315–324.e7

Abstract: Background: More than 300 million people carry a diagnosis of asthma, with data to suggest that they are at a higher risk for infection or adverse outcomes from severe acute respiratory syndrome coronavirus 2. Asthma is remarkably heterogeneous, and it ... ...

Abstract	Background: More than 300 million people carry a diagnosis of asthma, with data to suggest that they are at a higher risk for infection or adverse outcomes from severe acute respiratory syndrome coronavirus 2. Asthma is remarkably heterogeneous, and it is currently unclear how patient-intrinsic factors may relate to coronavirus disease 2019. Objective: We sought to identify and characterize subsets of patients with asthma at increased risk for severe acute respiratory syndrome coronavirus 2 infection. Methods: Participants from 2 large asthma cohorts were stratified using clinically relevant parameters to identify factors related to angiotensin-converting enzyme-2 (ACE2) expression within bronchial epithelium. ACE-2-correlated gene signatures were used to interrogate publicly available databases to identify upstream signaling events and novel therapeutic targets. Results: Stratifying by type 2 inflammatory biomarkers, we identified subjects who demonstrated low peripheral blood eosinophils accompanied by increased expression of the severe acute respiratory syndrome coronavirus 2 receptor ACE2 in bronchial epithelium. Genes highly correlated with ACE2 overlapped with type 1 and 2 IFN signatures, normally induced by viral infections. T-cell recruitment and activation within bronchoalveolar lavage cells of ACE2-high subjects was reciprocally increased. These patients demonstrated characteristics corresponding to risk factors for severe coronavirus disease 2019, including male sex, history of hypertension, low peripheral blood, and elevated bronchoalveolar lavage lymphocytes. Conclusions: ACE2 expression is linked to upregulation of viral response genes in a subset of type 2-low patients with asthma with characteristics resembling known risk factors for severe coronavirus disease 2019. Therapies targeting the IFN family and T-cell-activating factors may therefore be of benefit in a subset of patients.
MeSH term(s)	Adolescent ; Adult ; Angiotensin-Converting Enzyme 2 ; Asthma/classification ; Asthma/epidemiology ; Asthma/genetics ; Asthma/immunology ; Betacoronavirus/genetics ; Betacoronavirus/immunology ; Biomarkers/metabolism ; Bronchi/immunology ; Bronchi/pathology ; Bronchoalveolar Lavage Fluid/cytology ; Bronchoalveolar Lavage Fluid/immunology ; COVID-19 ; Cohort Studies ; Coronavirus Infections/epidemiology ; Coronavirus Infections/virology ; Eosinophils/immunology ; Eosinophils/pathology ; Female ; Gene Expression Profiling ; Humans ; Interferon Type I/genetics ; Interferon Type I/immunology ; Interferon-gamma/genetics ; Interferon-gamma/immunology ; Male ; Middle Aged ; Pandemics ; Peptidyl-Dipeptidase A/genetics ; Peptidyl-Dipeptidase A/immunology ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/virology ; Protein Interaction Mapping ; Receptors, Virus/genetics ; Receptors, Virus/immunology ; Risk Factors ; SARS-CoV-2 ; Severity of Illness Index ; T-Lymphocytes/classification ; T-Lymphocytes/immunology ; T-Lymphocytes/pathology ; Transcriptome ; United States/epidemiology
Chemical Substances	Biomarkers ; Interferon Type I ; Receptors, Virus ; Interferon-gamma (82115-62-6) ; Peptidyl-Dipeptidase A (EC 3.4.15.1) ; ACE2 protein, human (EC 3.4.17.23) ; Angiotensin-Converting Enzyme 2 (EC 3.4.17.23)
Keywords	covid19
Language	English
Publishing date	2020-06-10
Publishing country	United States
Document type	Journal Article ; Multicenter Study ; Research Support, N.I.H., Extramural
ZDB-ID	121011-7
ISSN	1097-6825 ; 1085-8725 ; 0091-6749
ISSN (online)	1097-6825 ; 1085-8725
ISSN	0091-6749
DOI	10.1016/j.jaci.2020.05.051
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Article ; Online: Machine learning implicates the IL-18 signaling axis in severe asthma.

Camiolo, Matthew J / Zhou, Xiuxia / Wei, Qi / Trejo Bittar, Humberto E / Kaminski, Naftali / Ray, Anuradha / Wenzel, Sally E

JCI insight

2021 Volume 6, Issue 21

Abstract: Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous ... ...

Abstract	Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous studies of the Severe Asthma Research Program (SARP) cohort linked gene expression changes to specific clinical and physiologic characteristics. While invaluable for hypothesis generation, these data include extensive candidate gene lists that complicate target identification and validation. In this analysis, we performed unsupervised clustering of the SARP cohort using bronchial epithelial cell gene expression data, identifying a transcriptional signature for participants suffering exacerbation-prone asthma with impaired lung function. Clinically, participants in this asthma cluster exhibited a mixed inflammatory process and bore transcriptional hallmarks of NF-κB and activator protein 1 (AP-1) activation, despite high corticosteroid exposure. Using supervised machine learning, we found a set of 31 genes that classified patients with high accuracy and could reconstitute clinical and transcriptional hallmarks of our patient clustering in an external cohort. Of these genes, IL18R1 (IL-18 Receptor 1) negatively associated with lung function and was highly expressed in the most severe patient cluster. We validated IL18R1 protein expression in lung tissue and identified downstream NF-κB and AP-1 activity, supporting IL-18 signaling in severe asthma pathogenesis and highlighting this approach for gene and pathway discovery.
MeSH term(s)	Adult ; Asthma/genetics ; Asthma/pathology ; Case-Control Studies ; Female ; Humans ; Interleukin-18/metabolism ; Machine Learning/standards ; Male
Chemical Substances	Interleukin-18
Language	English
Publishing date	2021-11-08
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2379-3708
ISSN (online)	2379-3708
DOI	10.1172/jci.insight.149945
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Expression of SARS-CoV-2 receptor ACE2 and coincident host response signature varies by asthma inflammatory phenotype

Camiolo, Matthew / Gauthier, Marc / Kaminski, Naftali / Ray, Anuradha / Wenzel, Sally E.

Journal of Allergy and Clinical Immunology

2020 Volume 146, Issue 2, Page(s) 315–324.e7

Keywords	Immunology ; Immunology and Allergy ; covid19
Language	English
Publisher	Elsevier BV
Publishing country	us
Document type	Article ; Online
ZDB-ID	121011-7
ISSN	1085-8725 ; 1097-6825 ; 0091-6749
ISSN (online)	1085-8725 ; 1097-6825
ISSN	0091-6749
DOI	10.1016/j.jaci.2020.05.051
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Article ; Online: Machine learning implicates the IL-18 signaling axis in severe asthma

Matthew J. Camiolo / Xiuxia Zhou / Qi Wei / Humberto E. Trejo Bittar / Naftali Kaminski / Anuradha Ray / Sally E. Wenzel

JCI Insight, Vol 6, Iss

2021 Volume 21

Abstract	Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous studies of the Severe Asthma Research Program (SARP) cohort linked gene expression changes to specific clinical and physiologic characteristics. While invaluable for hypothesis generation, these data include extensive candidate gene lists that complicate target identification and validation. In this analysis, we performed unsupervised clustering of the SARP cohort using bronchial epithelial cell gene expression data, identifying a transcriptional signature for participants suffering exacerbation-prone asthma with impaired lung function. Clinically, participants in this asthma cluster exhibited a mixed inflammatory process and bore transcriptional hallmarks of NF-κB and activator protein 1 (AP-1) activation, despite high corticosteroid exposure. Using supervised machine learning, we found a set of 31 genes that classified patients with high accuracy and could reconstitute clinical and transcriptional hallmarks of our patient clustering in an external cohort. Of these genes, IL18R1 (IL-18 Receptor 1) negatively associated with lung function and was highly expressed in the most severe patient cluster. We validated IL18R1 protein expression in lung tissue and identified downstream NF-κB and AP-1 activity, supporting IL-18 signaling in severe asthma pathogenesis and highlighting this approach for gene and pathway discovery.
Keywords	Immunology ; Pulmonology ; Medicine ; R
Subject code	610
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	American Society for Clinical investigation
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Expression of SARS-CoV-2 receptor ACE2 and coincident host response signature varies by asthma inflammatory phenotype

Camiolo, Matthew / Gauthier, Marc / Kaminski, Naftali / Ray, Anuradha / Wenzel, Sally E

J Allergy Clin Immunol

Abstract: BACKGROUND: More than 300 million people carry a diagnosis of asthma, with data to suggest that they are at a higher risk for infection or adverse outcomes from severe acute respiratory syndrome coronavirus 2. Asthma is remarkably heterogeneous, and it ... ...

Abstract	BACKGROUND: More than 300 million people carry a diagnosis of asthma, with data to suggest that they are at a higher risk for infection or adverse outcomes from severe acute respiratory syndrome coronavirus 2. Asthma is remarkably heterogeneous, and it is currently unclear how patient-intrinsic factors may relate to coronavirus disease 2019. OBJECTIVE: We sought to identify and characterize subsets of patients with asthma at increased risk for severe acute respiratory syndrome coronavirus 2 infection. METHODS: Participants from 2 large asthma cohorts were stratified using clinically relevant parameters to identify factors related to angiotensin-converting enzyme-2 (ACE2) expression within bronchial epithelium. ACE-2-correlated gene signatures were used to interrogate publicly available databases to identify upstream signaling events and novel therapeutic targets. RESULTS: Stratifying by type 2 inflammatory biomarkers, we identified subjects who demonstrated low peripheral blood eosinophils accompanied by increased expression of the severe acute respiratory syndrome coronavirus 2 receptor ACE2 in bronchial epithelium. Genes highly correlated with ACE2 overlapped with type 1 and 2 IFN signatures, normally induced by viral infections. T-cell recruitment and activation within bronchoalveolar lavage cells of ACE2-high subjects was reciprocally increased. These patients demonstrated characteristics corresponding to risk factors for severe coronavirus disease 2019, including male sex, history of hypertension, low peripheral blood, and elevated bronchoalveolar lavage lymphocytes. CONCLUSIONS: ACE2 expression is linked to upregulation of viral response genes in a subset of type 2-low patients with asthma with characteristics resembling known risk factors for severe coronavirus disease 2019. Therapies targeting the IFN family and T-cell-activating factors may therefore be of benefit in a subset of patients.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #592253
Database	COVID19

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