Beckmann ND, Comella PH, Cheng E, Lepow L, Beckmann AG, Tyler SR, Mouskas K, Simons NW, Hoffman GE, Francoeur NJ, Del Valle DM, Kang G, Do A, Moya E, Wilkins L, Le Berichel J, Chang C, Marvin R, Calorossi S, Lansky A, Walker L, Yi N, Yu A, Chung J, Hartnett M, Eaton M, Hatem S, Jamal H, Akyatan A, Tabachnikova A, Liharska LE, Cotter L, Fennessy B, Vaid A, Barturen G, Shah H, Wang YC, Sridhar SH, Soto J, Bose S, Madrid K, Ellis E, Merzier E, Vlachos K, Fishman N, Tin M, Smith M, Xie H, Patel M, Nie K, Argueta K, Harris J, Karekar N, Batchelor C, Lacunza J, Yishak M, Tuballes K, Scott I, Kumar A, Jaladanki S, Agashe C, Thompson R, Clark E, Losic B, Peters L; Mount Sinai COVID-19 Biobank Team, Roussos P, Zhu J, Wang W, Kasarskis A, Glicksberg BS, Nadkarni G, Bogunovic D, Elaiho C, Gangadharan S, Ofori-Amanfo G, Alesso-Carra K, Onel K, Wilson KM, Argmann C, Bunyavanich S, Alarcón-Riquelme ME, Marron TU, Rahman A, Kim-Schulze S, Gnjatic S, Gelb BD, Merad M, Sebra R, Schadt EE, Charney AW. (2021) Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children. Nat Commun 12(1):4854. [article]
Mount Sinai researchers have found an important clue to a rare but serious aftereffect of COVID-19 in children, known as multisystem inflammatory syndrome in children or MIS-C.
The researchers reported that RNA sequencing of blood samples from the Mount Sinai COVID-19 Biobank led to the discovery that specific infection-fighting cells of the immune system are downregulated in children with MIS-C, and that this is associated with a sustained inflammatory response, a hallmark of infection with SARS-CoV-2, the virus that causes COVID-19. The study was published in Nature Communications on August 11.
MIS-C is characterized by fever, pain, and inflammation of multiple organs including the heart, lungs, kidneys, skin, eyes, or gastrointestinal tract. More than 2,600 cases of MIS-C have been reported in the United States since the COVID-19 pandemic began. While an autoimmune condition has been suggested as an underlying cause, specific genes, pathways, and cell types remain unknown. Through Mount Sinai’s extensive gene-expression study, the researchers have taken a significant step in providing the field with new exploratory pathways involving complex networks and subnetworks of genes they constructed from pediatric cases of MIS-C and COVID-19 from the Mount Sinai COVID-19 Biobank.
One of the more significant of these gene networks implicated the suppression of two types of immune cells: natural killer (NK) cells and CD8+ T cells. Previous research has shown that when CD8+ T cells are persistently exposed to pathogens, they enter a state of “exhaustion,” resulting in a loss of their effectiveness and ability to proliferate. The researchers in the new study specifically pointed to the CD8+ T cells being in this exhausted state, thus potentially weakening the inflammatory immune response. An increase in NK cells is also associated with exhausted CD8+ T cells.
Workflow of the analyses
A RNA-seq was generated on whole blood samples from MIS-C cases, pediatric COVID-19 cases, and healthy controls. B Deconvolution estimated the relative cell-type proportions in each transcriptome, which were compared between cases and controls to identify the immune cell types involved in the pathogenesis of MIS-C. C Expression of each gene in the transcriptome was tested for association with disease, resulting in a MIS-C signature that was queried to resolve the dysregulated molecular pathways. D Co-expression network construction organized genes into coherent units called modules. E and F Modules loaded with genes of the MIS-C signature were empirically identified (E), validated using DE signatures from a large Kawasaki disease (KD) gene-expression dataset (F), and functionally annotated to pathway, cell type, and other disease signatures (F). G The module with the strongest enrichment for MIS-C that also enriched for KD signatures was further annotated to pinpoint cell subtypes, and key regulators of the processes captured by this module were identified in a regulatory network built from whole blood gene expression in an independent cohort. This figure was created with BioRender.com.
Dr. Beckmann adds that one of those regulators, TBX21, is a promising therapeutic target because it serves as a master coordinator of the transition of CD8+ T cells from effective to exhausted.
Mount Sinai’s work on MIS-C represents the first gene-expression study from the hospital’s COVID-19 Biobank. Created through the work of a volunteer team of more than 100 nurses, doctors, and researchers, the repository serves as the backbone of Mount Sinai’s rapidly expanding COVID-19 research. The team has collected blood samples from several hundred COVID-19 patients (including “longitudinal” or multiple samples from the same person) admitted to Mount Sinai hospitals which, in turn, have generated a diverse set of molecular data yielding invaluable insights into better understanding and new therapeutic approaches to the disease.
Source – Mount Sinai
Beckmann ND, Comella PH, Cheng E, Lepow L, Beckmann AG, Tyler SR, Mouskas K, Simons NW, Hoffman GE, Francoeur NJ, Del Valle DM, Kang G, Do A, Moya E, Wilkins L, Le Berichel J, Chang C, Marvin R, Calorossi S, Lansky A, Walker L, Yi N, Yu A, Chung J, Hartnett M, Eaton M, Hatem S, Jamal H, Akyatan A, Tabachnikova A, Liharska LE, Cotter L, Fennessy B, Vaid A, Barturen G, Shah H, Wang YC, Sridhar SH, Soto J, Bose S, Madrid K, Ellis E, Merzier E, Vlachos K, Fishman N, Tin M, Smith M, Xie H, Patel M, Nie K, Argueta K, Harris J, Karekar N, Batchelor C, Lacunza J, Yishak M, Tuballes K, Scott I, Kumar A, Jaladanki S, Agashe C, Thompson R, Clark E, Losic B, Peters L; Mount Sinai COVID-19 Biobank Team, Roussos P, Zhu J, Wang W, Kasarskis A, Glicksberg BS, Nadkarni G, Bogunovic D, Elaiho C, Gangadharan S, Ofori-Amanfo G, Alesso-Carra K, Onel K, Wilson KM, Argmann C, Bunyavanich S, Alarcón-Riquelme ME, Marron TU, Rahman A, Kim-Schulze S, Gnjatic S, Gelb BD, Merad M, Sebra R, Schadt EE, Charney AW. (2021) Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children. Nat Commun 12(1):4854. [article]
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Mount Sinai researchers have found an important clue to a rare but serious aftereffect of COVID-19 in children, known as multisystem inflammatory syndrome in children or MIS-C.
The researchers reported that RNA sequencing of blood samples from the Mount Sinai COVID-19 Biobank led to the discovery that specific infection-fighting cells of the immune system are downregulated in children with MIS-C, and that this is associated with a sustained inflammatory response, a hallmark of infection with SARS-CoV-2, the virus that causes COVID-19. The study was published in Nature Communications on August 11.
MIS-C is characterized by fever, pain, and inflammation of multiple organs including the heart, lungs, kidneys, skin, eyes, or gastrointestinal tract. More than 2,600 cases of MIS-C have been reported in the United States since the COVID-19 pandemic began. While an autoimmune condition has been suggested as an underlying cause, specific genes, pathways, and cell types remain unknown. Through Mount Sinai’s extensive gene-expression study, the researchers have taken a significant step in providing the field with new exploratory pathways involving complex networks and subnetworks of genes they constructed from pediatric cases of MIS-C and COVID-19 from the Mount Sinai COVID-19 Biobank.
One of the more significant of these gene networks implicated the suppression of two types of immune cells: natural killer (NK) cells and CD8+ T cells. Previous research has shown that when CD8+ T cells are persistently exposed to pathogens, they enter a state of “exhaustion,” resulting in a loss of their effectiveness and ability to proliferate. The researchers in the new study specifically pointed to the CD8+ T cells being in this exhausted state, thus potentially weakening the inflammatory immune response. An increase in NK cells is also associated with exhausted CD8+ T cells.
Workflow of the analyses
A RNA-seq was generated on whole blood samples from MIS-C cases, pediatric COVID-19 cases, and healthy controls. B Deconvolution estimated the relative cell-type proportions in each transcriptome, which were compared between cases and controls to identify the immune cell types involved in the pathogenesis of MIS-C. C Expression of each gene in the transcriptome was tested for association with disease, resulting in a MIS-C signature that was queried to resolve the dysregulated molecular pathways. D Co-expression network construction organized genes into coherent units called modules. E and F Modules loaded with genes of the MIS-C signature were empirically identified (E), validated using DE signatures from a large Kawasaki disease (KD) gene-expression dataset (F), and functionally annotated to pathway, cell type, and other disease signatures (F). G The module with the strongest enrichment for MIS-C that also enriched for KD signatures was further annotated to pinpoint cell subtypes, and key regulators of the processes captured by this module were identified in a regulatory network built from whole blood gene expression in an independent cohort. This figure was created with BioRender.com.
Dr. Beckmann adds that one of those regulators, TBX21, is a promising therapeutic target because it serves as a master coordinator of the transition of CD8+ T cells from effective to exhausted.
Mount Sinai’s work on MIS-C represents the first gene-expression study from the hospital’s COVID-19 Biobank. Created through the work of a volunteer team of more than 100 nurses, doctors, and researchers, the repository serves as the backbone of Mount Sinai’s rapidly expanding COVID-19 research. The team has collected blood samples from several hundred COVID-19 patients (including “longitudinal” or multiple samples from the same person) admitted to Mount Sinai hospitals which, in turn, have generated a diverse set of molecular data yielding invaluable insights into better understanding and new therapeutic approaches to the disease.
Source – Mount Sinai
Beckmann ND, Comella PH, Cheng E, Lepow L, Beckmann AG, Tyler SR, Mouskas K, Simons NW, Hoffman GE, Francoeur NJ, Del Valle DM, Kang G, Do A, Moya E, Wilkins L, Le Berichel J, Chang C, Marvin R, Calorossi S, Lansky A, Walker L, Yi N, Yu A, Chung J, Hartnett M, Eaton M, Hatem S, Jamal H, Akyatan A, Tabachnikova A, Liharska LE, Cotter L, Fennessy B, Vaid A, Barturen G, Shah H, Wang YC, Sridhar SH, Soto J, Bose S, Madrid K, Ellis E, Merzier E, Vlachos K, Fishman N, Tin M, Smith M, Xie H, Patel M, Nie K, Argueta K, Harris J, Karekar N, Batchelor C, Lacunza J, Yishak M, Tuballes K, Scott I, Kumar A, Jaladanki S, Agashe C, Thompson R, Clark E, Losic B, Peters L; Mount Sinai COVID-19 Biobank Team, Roussos P, Zhu J, Wang W, Kasarskis A, Glicksberg BS, Nadkarni G, Bogunovic D, Elaiho C, Gangadharan S, Ofori-Amanfo G, Alesso-Carra K, Onel K, Wilson KM, Argmann C, Bunyavanich S, Alarcón-Riquelme ME, Marron TU, Rahman A, Kim-Schulze S, Gnjatic S, Gelb BD, Merad M, Sebra R, Schadt EE, Charney AW. (2021) Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children. Nat Commun 12(1):4854. [article]
Related Posts
Benchmarking RNA sequencing for more accurate alternative splicing analysis
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Small RNA sequencing reveals regulatory roles for sdRNAs in acute myeloid leukemia
POND-seq enables non-destructive RNA sequencing in living cells
Worm’s radical transformation shows metamorphosis can change the functions of cells
New method allows scientists to follow gene activity over time in the same cells
Single-cell and single-embryo RNA sequencing
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Deep learning improves microRNA target prediction from sequence
Atlas of the brain’s striatum could guide researchers to new drug treatments
scLS – a computationally efficient differentially expressed gene detection algorithm
Spatial mapping of RNA turnover kinetics in the mouse brain
Immune cells offer insights on billion-dollar virus
SPIDER improves spatial transcriptomics data using single-cell RNA sequencing
Ultrafast and reference-free sequence discovery in single-cell data
ARCADIA combines RNA sequencing and spatial proteomics to reveal how tissue location shapes cell behavior
An end-to-end computational framework for “Record-seq” transcriptional recording data
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
ExoShorkie – predicting RNA-seq coverage of exogenous genomes in yeast by transfer learning
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
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