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Article: TREC/KREC Levels and T and B Lymphocyte Subpopulations in COVID-19 Patients at Different Stages of the Disease

Savchenko, Andrei A. / Tikhonova, Elena / Kudryavtsev, Igor / Kudlay, Dmitry / Korsunsky, Ilya / Beleniuk, Vasily / Borisov, Alexandr

Viruses. 2022 Mar. 21, v. 14, no. 3

2022

Abstract: Background: T and B cell-mediated immunity can be assessed using T cell receptor excision circle (TREC) and Kappa-deleting recombination excision circle (KREC) analysis, respectively, and successful implementation of this method requires evaluation of ... ...

Abstract	Background: T and B cell-mediated immunity can be assessed using T cell receptor excision circle (TREC) and Kappa-deleting recombination excision circle (KREC) analysis, respectively, and successful implementation of this method requires evaluation of the correlation between the TREC frequencies and T cell subsets as well as KREC levels and B lymphocyte subsets. The aim of the present study was to evaluate the correlation between the TREC/KREC concentrations and T/B lymphocyte subsets at different stages of COVID-19. Methods: We examined 33 patients in the acute stage of COVID-19 (including 8 patients with poor outcomes) and 33 COVID-19 survivors. TREC/KREC concentrations were measured using quantitative real-time PCR. T/B lymphocyte subsets were determined using flow cytometry. Results: Blood TREC and KREC levels were found to be significantly lower in the acute stage of COVID-19 compared to control values. Moreover, a zero blood TREC level was a predictor of a poor disease outcome. Reductions in CD3⁺CD4⁺CD45RO⁻CD62L⁻ and CD3⁺CD8⁺CD45RO⁻CD62L⁻ T cell counts (as well as in the main fractions of B1 and B2 B cells) indicated a favorable outcome in COVID-19 patients in the acute stage of the disease. Decreased CD3⁺CD4⁺CD45RO⁻CD62L⁺ and CD3⁺CD8⁺CD45RO⁻CD62L⁺ T cell frequencies and increased CD3⁺CD8⁺CD45RO⁻CD62L⁻ cell counts were found to indicate a poor outcome in patients with acute COVID-19. These patients were also found to have increased B1 cell counts while demonstrating no changes in B2 cell counts. The levels of effector T cell subsets an naïve B cells were normal in COVID-19 survivors. The most pronounced correlations between TREC/KREC levels and T/B cell subsets counts were observed in COVID-19 survivors: there were positive correlations with naïve T and B lymphocytes and negative correlations with central and effector memory T cell subsets. Conclusions: The assessment of correlations between TREC and T cell subsets as well as KREC levels and B cell subset counts in patients with acute COVID-19 and COVID-19 survivors has shown that blood concentrations of TREC and KREC are sensitive indicators of the stage of antigen-independent differentiation of adaptive immunity cells. The results of the TREC and KREC analysis correlated with the stages of COVID-19 and differed depending on the outcome of COVID-19.
Keywords	B-lymphocytes ; COVID-19 infection ; T-lymphocytes ; cell-mediated immunity ; circular DNA ; excision ; flow cytometry ; quantitative polymerase chain reaction
Language	English
Dates of publication	2022-0321
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2516098-9
ISSN	1999-4915
ISSN	1999-4915
DOI	10.3390/v14030646
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: TREC/KREC Levels and T and B Lymphocyte Subpopulations in COVID-19 Patients at Different Stages of the Disease.

Savchenko, Andrei A / Tikhonova, Elena / Kudryavtsev, Igor / Kudlay, Dmitry / Korsunsky, Ilya / Beleniuk, Vasily / Borisov, Alexandr

Viruses

2022 Volume 14, Issue 3

Abstract	Background: T and B cell-mediated immunity can be assessed using T cell receptor excision circle (TREC) and Kappa-deleting recombination excision circle (KREC) analysis, respectively, and successful implementation of this method requires evaluation of the correlation between the TREC frequencies and T cell subsets as well as KREC levels and B lymphocyte subsets. The aim of the present study was to evaluate the correlation between the TREC/KREC concentrations and T/B lymphocyte subsets at different stages of COVID-19. Methods: We examined 33 patients in the acute stage of COVID-19 (including 8 patients with poor outcomes) and 33 COVID-19 survivors. TREC/KREC concentrations were measured using quantitative real-time PCR. T/B lymphocyte subsets were determined using flow cytometry. Results: Blood TREC and KREC levels were found to be significantly lower in the acute stage of COVID-19 compared to control values. Moreover, a zero blood TREC level was a predictor of a poor disease outcome. Reductions in CD3 Conclusions: The assessment of correlations between TREC and T cell subsets as well as KREC levels and B cell subset counts in patients with acute COVID-19 and COVID-19 survivors has shown that blood concentrations of TREC and KREC are sensitive indicators of the stage of antigen-independent differentiation of adaptive immunity cells. The results of the TREC and KREC analysis correlated with the stages of COVID-19 and differed depending on the outcome of COVID-19.
MeSH term(s)	B-Lymphocyte Subsets ; B-Lymphocytes ; COVID-19 ; DNA ; Humans ; Receptors, Antigen, T-Cell
Chemical Substances	Receptors, Antigen, T-Cell ; DNA (9007-49-2)
Language	English
Publishing date	2022-03-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v14030646
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Maximizing statistical power to detect differentially abundant cell states with scPOST.

Millard, Nghia / Korsunsky, Ilya / Weinand, Kathryn / Fonseka, Chamith Y / Nathan, Aparna / Kang, Joyce B / Raychaudhuri, Soumya

Cell reports methods

2021 Volume 1, Issue 8

Abstract: To estimate a study design's power to detect differential abundance, we require a framework that simulates many multi-sample single-cell datasets. However, current simulation methods are challenging for large-scale power analyses because they are ... ...

Abstract	To estimate a study design's power to detect differential abundance, we require a framework that simulates many multi-sample single-cell datasets. However, current simulation methods are challenging for large-scale power analyses because they are computationally resource intensive and do not support easy simulation of multi-sample datasets. Current methods also lack modeling of important inter-sample variation, such as the variation in the frequency of cell states between samples that is observed in single-cell data. Thus, we developed single-cell POwer Simulation Tool (scPOST) to address these limitations and help investigators quickly simulate multi-sample single-cell datasets. Users may explore a range of effect sizes and study design choices (such as increasing the number of samples or cells per sample) to determine their effect on power, and thus choose the optimal study design for their planned experiments.
MeSH term(s)	Research Design ; Computer Simulation
Language	English
Publishing date	2021-11-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2667-2375
ISSN (online)	2667-2375
DOI	10.1016/j.crmeth.2021.100120
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation.

Zhang, Fan / Mears, Joseph R / Shakib, Lorien / Beynor, Jessica I / Shanaj, Sara / Korsunsky, Ilya / Nathan, Aparna / Donlin, Laura T / Raychaudhuri, Soumya

Genome medicine

2021 Volume 13, Issue 1, Page(s) 64

Abstract: Background: Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate ... ...

Abstract	Background: Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Methods: To identify cellular phenotypes that may be shared across tissues affected by disparate inflammatory diseases, we developed a meta-analysis and integration pipeline that models and removes the effects of technology, tissue of origin, and donor that confound cell-type identification. Using this approach, we integrated > 300,000 single-cell transcriptomic profiles from COVID-19-affected lungs and tissues from healthy subjects and patients with five inflammatory diseases: rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and interstitial lung disease. We tested the association of shared immune states with severe/inflamed status compared to healthy control using mixed-effects modeling. To define environmental factors within these tissues that shape shared macrophage phenotypes, we stimulated human blood-derived macrophages with defined combinations of inflammatory factors, emphasizing in particular antiviral interferons IFN-beta (IFN-β) and IFN-gamma (IFN-γ), and pro-inflammatory cytokines such as TNF. Results: We built an immune cell reference consisting of > 300,000 single-cell profiles from 125 healthy or disease-affected donors from COVID-19 and five inflammatory diseases. We observed a CXCL10+ CCL2+ inflammatory macrophage state that is shared and strikingly abundant in severe COVID-19 bronchoalveolar lavage samples, inflamed RA synovium, inflamed CD ileum, and UC colon. These cells exhibited a distinct arrangement of pro-inflammatory and interferon response genes, including elevated levels of CXCL10, CXCL9, CCL2, CCL3, GBP1, STAT1, and IL1B. Further, we found this macrophage phenotype is induced upon co-stimulation by IFN-γ and TNF-α. Conclusions: Our integrative analysis identified immune cell states shared across inflamed tissues affected by inflammatory diseases and COVID-19. Our study supports a key role for IFN-γ together with TNF-α in driving an abundant inflammatory macrophage phenotype in severe COVID-19-affected lungs, as well as inflamed RA synovium, CD ileum, and UC colon, which may be targeted by existing immunomodulatory therapies.
MeSH term(s)	Arthritis, Rheumatoid/genetics ; Arthritis, Rheumatoid/immunology ; Bronchoalveolar Lavage Fluid/cytology ; Bronchoalveolar Lavage Fluid/immunology ; COVID-19/genetics ; COVID-19/immunology ; Colitis, Ulcerative/genetics ; Colitis, Ulcerative/immunology ; Colon/immunology ; Crohn Disease/genetics ; Crohn Disease/immunology ; Cytokines/immunology ; Humans ; Inflammation/genetics ; Inflammation/immunology ; Lung/immunology ; Lung Diseases, Interstitial/genetics ; Lung Diseases, Interstitial/immunology ; Lupus Erythematosus, Systemic/genetics ; Lupus Erythematosus, Systemic/immunology ; Macrophages/immunology ; Phenotype ; RNA-Seq ; SARS-CoV-2
Chemical Substances	Cytokines
Language	English
Publishing date	2021-04-20
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-021-00881-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Efficient and precise single-cell reference atlas mapping with Symphony.

Kang, Joyce B / Nathan, Aparna / Weinand, Kathryn / Zhang, Fan / Millard, Nghia / Rumker, Laurie / Moody, D Branch / Korsunsky, Ilya / Raychaudhuri, Soumya

Nature communications

2021 Volume 12, Issue 1, Page(s) 5890

Abstract: Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a ... ...

Abstract	Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony ( https://github.com/immunogenomics/symphony ), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.
MeSH term(s)	Algorithms ; Computational Biology ; Genome ; Humans ; Single-Cell Analysis ; Software
Language	English
Publishing date	2021-10-07
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-021-25957-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics.

Reshef, Yakir A / Rumker, Laurie / Kang, Joyce B / Nathan, Aparna / Korsunsky, Ilya / Asgari, Samira / Murray, Megan B / Moody, D Branch / Raychaudhuri, Soumya

Nature biotechnology

2021 Volume 40, Issue 3, Page(s) 355–363

Abstract: As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes, such as clinical phenotypes. Current statistical approaches typically map cells to clusters ... ...

Abstract	As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes, such as clinical phenotypes. Current statistical approaches typically map cells to clusters and then assess differences in cluster abundance. Here we present co-varying neighborhood analysis (CNA), an unbiased method to identify associated cell populations with greater flexibility than cluster-based approaches. CNA characterizes dominant axes of variation across samples by identifying groups of small regions in transcriptional space-termed neighborhoods-that co-vary in abundance across samples, suggesting shared function or regulation. CNA performs statistical testing for associations between any sample-level attribute and the abundances of these co-varying neighborhood groups. Simulations show that CNA enables more sensitive and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, identifies monocyte populations expanded in sepsis and identifies a novel T cell population associated with progression to active tuberculosis.
MeSH term(s)	Cluster Analysis ; Phenotype ; T-Lymphocytes ; Transcriptome/genetics
Language	English
Publishing date	2021-10-21
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1311932-1
ISSN	1546-1696 ; 1087-0156
ISSN (online)	1546-1696
ISSN	1087-0156
DOI	10.1038/s41587-021-01066-4
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Zs.A 2167: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article: Adipocytes regulate fibroblast function, and their loss contributes to fibroblast dysfunction in inflammatory diseases.

Faust, Heather J / Cheng, Tan-Yun / Korsunsky, Ilya / Watts, Gerald F M / Gal-Oz, Shani T / Trim, William / Kongthong, Kurt / Jonsson, Anna Helena / Simmons, Daimon P / Zhang, Fan / Padera, Robert / Chubinskaya, Susan / Wei, Kevin / Raychaudhuri, Soumya / Lynch, Lydia / Moody, D Branch / Brenner, Michael B

bioRxiv : the preprint server for biology

2023

Abstract: Fibroblasts play critical roles in tissue homeostasis, but in pathologic states can drive fibrosis, inflammation, and tissue destruction. In the joint synovium, fibroblasts provide homeostatic maintenance and lubrication. Little is known about what ... ...

Abstract	Fibroblasts play critical roles in tissue homeostasis, but in pathologic states can drive fibrosis, inflammation, and tissue destruction. In the joint synovium, fibroblasts provide homeostatic maintenance and lubrication. Little is known about what regulates the homeostatic functions of fibroblasts in healthy conditions. We performed RNA sequencing of healthy human synovial tissue and identified a fibroblast gene expression program characterized by enhanced fatty acid metabolism and lipid transport. We found that fat-conditioned media reproduces key aspects of the lipid-related gene signature in cultured fibroblasts. Fractionation and mass spectrometry identified cortisol in driving the healthy fibroblast phenotype, confirmed using glucocorticoid receptor gene (
Language	English
Publishing date	2023-05-18
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.05.16.540975
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history.

Maurits, Marc P / Korsunsky, Ilya / Raychaudhuri, Soumya / Murphy, Shawn N / Smoller, Jordan W / Weiss, Scott T / Huizinga, Thomas W J / Reinders, Marcel J T / Karlson, Elizabeth W / van den Akker, Erik B / Knevel, Rachel

Journal of the American Medical Informatics Association : JAMIA

2022 Volume 29, Issue 5, Page(s) 761–769

Abstract: Objective: To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.! ...

Abstract	Objective: To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects. Material and methods: We used 1872 billing codes in EHRs of 102 880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features. Results: We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of ≥0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles. Discussion: Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data. Conclusion: We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.
MeSH term(s)	Child ; Cluster Analysis ; Diabetes Mellitus ; Electronic Health Records ; Humans ; Male ; Phenotype
Language	English
Publishing date	2022-02-10
Publishing country	England
Document type	Journal Article ; Multicenter Study ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1205156-1
ISSN	1527-974X ; 1067-5027
ISSN (online)	1527-974X
ISSN	1067-5027
DOI	10.1093/jamia/ocac008
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Zs.A 4128: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 312: Show issues

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Article: IFN-

Zhang, Fan / Mears, Joseph R / Shakib, Lorien / Beynor, Jessica I / Shanaj, Sara / Korsunsky, Ilya / Nathan, Aparna / Donlin, Laura T / Raychaudhuri, Soumya

bioRxiv : the preprint server for biology

2020

Abstract: Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate ... ...

Abstract	Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Using an integrative strategy, we built a reference by meta-analyzing > 300,000 immune cells from COVID-19 and 5 inflammatory diseases including rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), lupus, and interstitial lung disease. Our cross-disease analysis revealed that an
Keywords	covid19
Language	English
Publishing date	2020-08-05
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.08.05.238360
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Persons with Chronic Spinal Cord Injury Have Decreased Natural Killer Cell and Increased Toll-Like Receptor/Inflammatory Gene Expression.

Herman, Paige / Stein, Adam / Gibbs, Katie / Korsunsky, Ilya / Gregersen, Peter / Bloom, Ona

Journal of neurotrauma

2018 Volume 35, Issue 15, Page(s) 1819–1829

Abstract: Infections are the leading cause of death for individuals with traumatic spinal cord injury (SCI). Along with increased infection rates, inflammation is often also observed in persons with chronic SCI. Together, immunological changes post-SCI are also ... ...

Abstract	Infections are the leading cause of death for individuals with traumatic spinal cord injury (SCI). Along with increased infection rates, inflammation is often also observed in persons with chronic SCI. Together, immunological changes post-SCI are also poised to impede neurological recovery and mediate common medical consequences of SCI, including atherogenesis and neuropathic pain. The molecular mechanisms contributing to increased infection susceptibility and inflammation in persons living with SCI are poorly understood. Here, we used tools of functional genomics to perform a pilot study to compare whole-blood gene expression in individuals with chronic SCI (≥1 year from initial injury; N = 31) and uninjured individuals (N = 26). We identified 1815 differentially expressed genes in all SCI participants and 2226 differentially expressed genes in persons with SCI rostral to thoracic level 5, compared to uninjured participants. This included marked downregulation of natural killer cell genes and upregulation of the proinflammatory Toll-like receptor signaling pathway. These data provide novel mechanistic insights into the causes underlying the symptoms of immune dysfunction in individuals living with SCI.
MeSH term(s)	Adult ; Aged ; Aged, 80 and over ; Female ; Humans ; Inflammation/immunology ; Killer Cells, Natural/immunology ; Male ; Middle Aged ; Pilot Projects ; Prospective Studies ; Spinal Cord Injuries/immunology ; Toll-Like Receptors/biosynthesis ; Toll-Like Receptors/immunology ; Transcriptome ; Young Adult
Chemical Substances	Toll-Like Receptors
Language	English
Publishing date	2018-04-05
Publishing country	United States
Document type	Journal Article ; Observational Study ; Research Support, Non-U.S. Gov't
ZDB-ID	645092-1
ISSN	1557-9042 ; 0897-7151
ISSN (online)	1557-9042
ISSN	0897-7151
DOI	10.1089/neu.2017.5519
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