Immune biomarkers to predict SARS-CoV-2 vaccine effectiveness in patients with hematological malignancies

AbstractThere is evidence of reduced SARS-CoV-2 vaccine effectiveness in patients with hematological malignancies. We hypothesized that tumor and treatment-related immunosuppression can be depicted in peripheral blood, and that immune profiling prior to vaccination can help predict immunogenicity. We performed a comprehensive immunological characterization of 83 hematological patients before vaccination and measured IgM, IgG, and IgA antibody response to four viral antigens at day +7 after second-dose COVID-19 vaccination using multidimensional and computational flow cytometry. Health care practitioners of similar age were the control group (n = 102). Forty-four out of 59 immune cell types were significantly altered in patients; those with monoclonal gammopathies showed greater immunosuppression than patients with B-cell disorders and Hodgkin lymphoma. Immune dysregulation emerged before treatment, peaked while on-therapy, and did not return to normalcy after stopping treatment. We identified an immunotype that was significantly associated with poor antibody response and uncovered that the frequency of neutrophils, classical monocytes, CD4, and CD8 effector memory CD127low T cells, as well as naive CD21+ and IgM+D+ memory B cells, were independently associated with immunogenicity. Thus, we provide novel immune biomarkers to predict COVID-19 vaccine effectiveness in hematological patients, which are complementary to treatment-related factors and may help tailoring possible vaccine boosters.

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Simulated bacterial infection disrupts the circadian fluctuation of immune cells in wrinkle-lipped bats (Chaerephon plicatus)

PeerJ ◽

10.7717/peerj.3570 ◽

2017 ◽

Vol 5 ◽

pp. e3570 ◽

Cited By ~ 11

Author(s):

Philipp Weise ◽

Gábor A. Czirják ◽

Oliver Lindecke ◽

Sara Bumrungsri ◽

Christian C. Voigt

Keyword(s):

Bacterial Infection ◽

Immune Cells ◽

Immune Cell ◽

Experimental Treatment ◽

Cell Types ◽

Diurnal Fluctuation ◽

Control Group ◽

Carrier Liquid ◽

Cell Counts ◽

Body Mass Changes

BackgroundLeukocyte concentrations follow a circadian pattern in mammals, with elevated values at times of potential contact with pathogens and parasites. We hypothesized that this pattern is disturbed after an immune challenge.MethodsIn Thailand, we captured wrinkle-lipped bats (Chaerephon plicatus), when they returned to their colony at dawn. We challenged half of the animals (experimental group) with bacterial lipopolysaccharides and treated the others only with the carrier liquid (control group). We then compared body mass changes and differences in circulating immune cell counts at 8 h post-treatment.ResultsIn experimental animals, we observed an increase in total leukocyte and neutrophil numbers of 17% and 95%, respectively. In control animals, concentrations of leukocytes decreased by 44% and those of neutrophils remained constant. Experimental treatment had no effect on lymphocytes, yet changes in eosinophil numbers were explained by sex. Eosinophils decreased by 66% in females and by 62% in males. Basophils and monocytes were rarest among all observed cell types and analysis was either impossible because of low numbers or yielded no significant effects, respectively.DiscussionOur findings show that a simulated bacterial infection triggered a neutrophil-associated immune response in wrinkle-lipped bats, indicating a disruption of the diurnal fluctuation of immune cells. Our study suggests that bats exhibit circadian rhythms in immune cell counts. The magnitude of these fluctuations may vary across species according to specific-specific infection risks associated with colony sizes or specific roosting habits.

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Immunological Biomarkers of Fatal COVID-19: A Study of 868 Patients

Frontiers in Immunology ◽

10.3389/fimmu.2021.659018 ◽

2021 ◽

Vol 12 ◽

Author(s):

Esperanza Martín-Sánchez ◽

Juan José Garcés ◽

Catarina Maia ◽

Susana Inogés ◽

Ascensión López-Díaz de Cerio ◽

...

Keyword(s):

High Risk ◽

B Cell ◽

Large Scale ◽

Immune Cell ◽

Severe Disease ◽

Fatal Outcome ◽

Cell Types ◽

Risk Of Death ◽

Immune Biomarkers ◽

Healthy Donors

Information on the immunopathobiology of coronavirus disease 2019 (COVID-19) is rapidly increasing; however, there remains a need to identify immune features predictive of fatal outcome. This large-scale study characterized immune responses to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection using multidimensional flow cytometry, with the aim of identifying high-risk immune biomarkers. Holistic and unbiased analyses of 17 immune cell-types were conducted on 1,075 peripheral blood samples obtained from 868 COVID-19 patients and on samples from 24 patients presenting with non-SARS-CoV-2 infections and 36 healthy donors. Immune profiles of COVID-19 patients were significantly different from those of age-matched healthy donors but generally similar to those of patients with non-SARS-CoV-2 infections. Unsupervised clustering analysis revealed three immunotypes during SARS-CoV-2 infection; immunotype 1 (14% of patients) was characterized by significantly lower percentages of all immune cell-types except neutrophils and circulating plasma cells, and was significantly associated with severe disease. Reduced B-cell percentage was most strongly associated with risk of death. On multivariate analysis incorporating age and comorbidities, B-cell and non-classical monocyte percentages were independent prognostic factors for survival in training (n=513) and validation (n=355) cohorts. Therefore, reduced percentages of B-cells and non-classical monocytes are high-risk immune biomarkers for risk-stratification of COVID-19 patients.

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Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data with ImmClassifier

10.1101/2020.03.23.002758 ◽

2020 ◽

Author(s):

Xuan Liu ◽

Sara J.C. Gosline ◽

Lance T. Pflieger ◽

Pierre Wallet ◽

Archana Iyer ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Cell Types ◽

Effector Memory ◽

Immune Cell Population ◽

Fine Grained ◽

Knowledge Based ◽

Comparable Performance

AbstractSingle-cell RNA sequencing is an emerging strategy for characterizing the immune cell population in diverse environments including blood, tumor or healthy tissues. While this has traditionally been done with flow or mass cytometry targeting protein expression, scRNA-Seq has several established and potential advantages in that it can profile immune cells and non-immune cells (e.g. cancer cells) in the same sample, identify cell types that lack precise markers for flow cytometry, or identify a potentially larger number of immune cell types and activation states than is achievable in a single flow assay. However, scRNA-Seq is currently limited due to the need to identify the types of each immune cell from its transcriptional profile, which is not only time-consuming but also requires a significant knowledge of immunology. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells vs macrophages), making fine distinctions has turned out to be a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that ImmClassifier outperforms other tools (+20% recall, +14% precision) in distinguishing fine-grained cell types (e.g. CD8+ effector memory T cells) with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.

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Exploring inflammatory signatures in arthritic joint biopsies with Spatial Transcriptomics

Scientific Reports ◽

10.1038/s41598-019-55441-y ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 7

Author(s):

Konstantin Carlberg ◽

Marina Korotkova ◽

Ludvig Larsson ◽

Anca I. Catrina ◽

Patrik L. Ståhl ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Immune Cell ◽

Memory T Cells ◽

Inflammatory Diseases ◽

Adaptive Immune Response ◽

Cell Types ◽

Effector Memory ◽

Cellular Mechanisms ◽

Chronic Inflammatory Diseases

AbstractLately it has become possible to analyze transcriptomic profiles in tissue sections with retained cellular context. We aimed to explore synovial biopsies from rheumatoid arthritis (RA) and spondyloarthritis (SpA) patients, using Spatial Transcriptomics (ST) as a proof of principle approach for unbiased mRNA studies at the site of inflammation in these chronic inflammatory diseases. Synovial tissue biopsies from affected joints were studied with ST. The transcriptome data was subjected to differential gene expression analysis (DEA), pathway analysis, immune cell type identification using Xcell analysis and validation with immunohistochemistry (IHC). The ST technology allows selective analyses on areas of interest, thus we analyzed morphologically distinct areas of mononuclear cell infiltrates. The top differentially expressed genes revealed an adaptive immune response profile and T-B cell interactions in RA, while in SpA, the profiles implicate functions associated with tissue repair. With spatially resolved gene expression data, overlaid on high-resolution histological images, we digitally portrayed pre-selected cell types in silico. The RA displayed an overrepresentation of central memory T cells, while in SpA effector memory T cells were most prominent. Consequently, ST allows for deeper understanding of cellular mechanisms and diversity in tissues from chronic inflammatory diseases.

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Immune biomarkers link air pollution exposure to blood pressure in adolescents

Environmental Health ◽

10.1186/s12940-020-00662-2 ◽

2020 ◽

Vol 19 (1) ◽

Author(s):

Mary Prunicki ◽

Nicholas Cauwenberghs ◽

Jennifer Arthur Ataam ◽

Hesam Movassagh ◽

Juyong Brian Kim ◽

...

Keyword(s):

Oxidative Stress ◽

Blood Pressure ◽

Air Pollution ◽

Acute Inflammation ◽

Immune Cell ◽

Cell Types ◽

Pollution Levels ◽

Immune Biomarkers ◽

Air Pollution Exposure ◽

Pollution Exposure

Abstract Background Childhood exposure to air pollution contributes to cardiovascular disease in adulthood. Immune and oxidative stress disturbances might mediate the effects of air pollution on the cardiovascular system, but the underlying mechanisms are poorly understood in adolescents. Therefore, we aimed to identify immune biomarkers linking air pollution exposure and blood pressure levels in adolescents. Methods We randomly recruited 100 adolescents (mean age, 16 years) from Fresno, California. Using central-site data, spatial-temporal modeling, and distance weighting exposures to the participant’s home, we estimated average pollutant levels [particulate matter (PM), polyaromatic hydrocarbons (PAH), ozone (O3), carbon monoxide (CO) and nitrogen oxides (NOx)]. We collected blood samples and vital signs on health visits. Using proteomic platforms, we quantitated markers of inflammation, oxidative stress, coagulation, and endothelial function. Immune cellular characterization was performed via mass cytometry (CyTOF). We investigated associations between pollutant levels, cytokines, immune cell types, and blood pressure (BP) using partial least squares (PLS) and linear regression, while adjusting for important confounders. Results Using PLS, biomarkers explaining most of the variance in air pollution exposure included markers of oxidative stress (GDF-15 and myeloperoxidase), acute inflammation (C-reactive protein), hemostasis (ADAMTS, D-dimer) and immune cell types such as monocytes. Most of these biomarkers were independently associated with the air pollution levels in fully adjusted regression models. In CyTOF analyses, monocytes were enriched in participants with the highest versus the lowest PM2.5 exposure. In both PLS and linear regression, diastolic BP was independently associated with PM2.5, NO, NO2, CO and PAH456 pollution levels (P ≤ 0.009). Moreover, monocyte levels were independently related to both air pollution and diastolic BP levels (P ≤ 0.010). In in vitro cell assays, plasma of participants with high PM2.5 exposure induced endothelial dysfunction as evaluated by eNOS and ICAM-1 expression and tube formation. Conclusions For the first time in adolescents, we found that ambient air pollution levels were associated with oxidative stress, acute inflammation, altered hemostasis, endothelial dysfunction, monocyte enrichment and diastolic blood pressure. Our findings provide new insights on pollution-related immunological and cardiovascular disturbances and advocate preventative measures of air pollution exposure.

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Profiles of Immune Cell Infiltration in Carotid Artery Atherosclerosis Based on Gene Expression Data

Frontiers in Immunology ◽

10.3389/fimmu.2021.599512 ◽

2021 ◽

Vol 12 ◽

Author(s):

Long Wang ◽

Beibei Gao ◽

Mingyue Wu ◽

Wei Yuan ◽

Ping Liang ◽

...

Keyword(s):

T Cells ◽

Carotid Artery ◽

Immune Cells ◽

Immune Cell ◽

Cell Types ◽

Th2 Cells ◽

Effector Memory ◽

T Helper ◽

Carotid Artery Atherosclerosis ◽

Helper Type

Since immune infiltration is closely associated with the progression and prognosis of atherosclerosis, we aimed to describe the abundance of 24 immune cell types within atherosclerotic tissues. In the current study, we used the Immune Cell Abundance Identifier (ImmuCellAI), a web-based tool, to estimate the abundance of 24 immune cells based on the microarray profiles of atherosclerotic carotid artery samples to analyze the proportions and the dysregulation of immune cell types within carotid atherosclerosis. We found that atherosclerotic immune cells had a diverse landscape dominated by T cells and myeloid cells and that macrophages and dendritic cells (DCs) showed different abundance in normal and atherosclerotic tissues. Moreover, the expression of macrophages was closely related to the level of the expression of DCs and of exhausted T cells, while the expression of T-helper type 1 (Th1) cells was strongly correlated with the expression of T-helper type 2 (Th2) cells and effector memory cells. Our data confirm a distinct profile of atherosclerosis-infiltrating immune cell subpopulations, which may inspire an immunological direction for research on atherosclerosis.

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Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data

Briefings in Bioinformatics ◽

10.1093/bib/bbab039 ◽

2021 ◽

Author(s):

Xuan Liu ◽

Sara J C Gosline ◽

Lance T Pflieger ◽

Pierre Wallet ◽

Archana Iyer ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Immune Cell ◽

Cell Types ◽

Effector Memory ◽

Fine Grained ◽

Knowledge Based ◽

Learning Classifier ◽

Comparable Performance ◽

Difficult Challenge

Abstract Single-cell RNA sequencing (scRNA-Seq) is an emerging strategy for characterizing immune cell populations. Compared to flow or mass cytometry, scRNA-Seq could potentially identify cell types and activation states that lack precise cell surface markers. However, scRNA-Seq is currently limited due to the need to manually classify each immune cell from its transcriptional profile. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells versus macrophages), making fine distinctions (e.g. CD8+ effector memory T cells) remains a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that its predictions are highly concordant with flow-based markers from CITE-seq and outperforms other tools (+15% recall, +14% precision) in distinguishing fine-grained cell types with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.

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B2 agonist (Salbutamol) modulate skin wound healing processes

International Journal of Research in Pharmaceutical Sciences ◽

10.26452/ijrps.v9i1.1187 ◽

2018 ◽

Vol 9 (1) ◽

pp. 37

Author(s):

Fahim M. Mahmood ◽

Hayder B. Sahib ◽

Khalid W. Qassim

Keyword(s):

Wound Healing ◽

Wound Repair ◽

Cell Types ◽

Skin Wound ◽

Control Group ◽

Related Factors ◽

Skin Wound Healing ◽

Wound Model ◽

Numerous Cell

Wound healing is a complex physiological and dynamic process required the coordination of numerous cell types and biological processes to regenerate damaged tissue and initiate repair which is dependent on a number of inter-related factors. This study was aimed to demonstrate whether the ?2 receptor has role in wound healing and angiogenesis. A murine wild-type (in vivo), excisional skin wound model was done to demonstrate that activation of ?2AR delay wound repair, twenty-four male albino mice were used to investigate the effect of the drug on experimental wound healing grossly, histo-pathologically and immune-histochemically compared with vehicle-only controls. The results showed that the rate of wound healing was significantly slower in salbutamol group than in control group (P

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RELATED FACTORS TO RELAPSE IN DEPRESSED PATIENTS AFTER COGNITIVE BEHAVIOURAL THERAPY DURING ONE YEAR PROSPECTIVE FOLLOW-UP

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2011.5.2 ◽

2011 ◽

pp. 13-19

Author(s):

Nhu Minh Hang Tran ◽

Huu Cat Nguyen ◽

Dang Doanh Nguyen ◽

Van Luong Ngo ◽

Vu Hoang Nguyen ◽

...

Keyword(s):

Cognitive Behavioral Therapy ◽

Relapse Rate ◽

Behavioral Therapy ◽

Cognitive Behavioral ◽

Control Group ◽

Controlled Clinical Trial ◽

Related Factors ◽

Depressed Patients ◽

One Year

Objectives: To determine factors impact on the relapse in depressed patients treated with Cognitive Behavioral Therapy (CBT) during one year follow-up. Materials and Methods: 80 depressed patients divided into two groups, group 1: included 40 patients treated with CBT; group 2: 40 patients on amitriptyline. Non-randomized controlled clinical trial, opened, longiditual and prospective research. Results and Conclusions: relapse rate after CBT during 1 year follow-up is 10% (compared to 25% in control group), related factors to relapse rate in depression after CBT are age and education. Shared predictors between 2 groups are severity and recurrence of depression. Key words: Depression, relapse, Cognitive Behavioral Therapy (CBT)

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Expression and Significance of Th17 Cells and Related Factors in Patients with Autoimmune Hepatitis

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190402160455 ◽

2019 ◽

Vol 22 (4) ◽

pp. 232-237 ◽

Cited By ~ 6

Author(s):

Jihong An

Keyword(s):

Autoimmune Hepatitis ◽

Peripheral Blood ◽

Th17 Cells ◽

Treg Cells ◽

Enzyme Linked Immunosorbent Assay ◽

Control Group ◽

Serum Total Bilirubin ◽

Study Group ◽

Related Factors ◽

Tnf Α

Objective: This study aims to investigate the expression and clinical significance of Th17 cells and related factors in peripheral blood of patients with Autoimmune Hepatitis (AIH). Methods: A retrospective selection of 100 patients with AIH were included as a study group, and 100 healthy volunteers in the outpatient clinic were selected as the control group. The levels of IL- 17, IL-6, IL-21 and TNF-α in peripheral blood of all subjects were detected by enzyme-linked immunosorbent assay and the frequency of Th17 cells and Treg cells was detected by flow cytometry. Results: Results showed that the study group had higher levels of serum total bilirubin (TBil), alkaline phosphatase (ALP), γ -glutamyltranspeptidase (γ-GT), immunoglobulin G (IgG), immunoglobulin M (IgM), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) than the control group, as well as higher levels of IL-17, IL-6, IL-21 and TNF-α in serum. The frequency of Th17 cells in peripheral blood was higher in the study group, while the frequency of Treg cells was lower. Also, serum IL-17, TNF-α levels and Th17 cells frequency were positively correlated with ALT and AST, whereas Treg cells frequency were negatively correlated with ALT and AST levels. Conclusion: Our finding demonstrates that Th17 cell frequency and their related factors IL-17 and TNF-α, are associated with liver damage, which might be used to monitor AIH disease severity.

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