Dataset Information

Rare genetic variants involved in multisystem inflammatory syndrome in children: a multicenter Brazilian cohort study.

ABSTRACT:

Introduction

Despite the existing data on the Multisystem Inflammatory Syndrome in Children (MIS-C), the factors that determine these patients evolution remain elusive. Answers may lie, at least in part, in genetics. It is currently under investigation that MIS-C patients may have an underlying innate error of immunity (IEI), whether of monogenic, digenic, or even oligogenic origin.

Methods

To further investigate this hypothesis, 30 patients with MIS-C were submitted to whole exome sequencing.

Results

Analyses of genes associated with MIS-C, MIS-A, severe covid-19, and Kawasaki disease identified twenty-nine patients with rare potentially damaging variants (50 variants were identified in 38 different genes), including those previously described in IFNA21 and IFIH1 genes, new variants in genes previously described in MIS-C patients (KMT2D, CFB, and PRF1), and variants in genes newly associated to MIS-C such as APOL1, TNFRSF13B, and G6PD. In addition, gene ontology enrichment pointed to the involvement of thirteen major pathways, including complement system, hematopoiesis, immune system development, and type II interferon signaling, that were not yet reported in MIS-C.

Discussion

These data strongly indicate that different gene families may favor MIS- C development. Larger cohort studies with healthy controls and other omics approaches, such as proteomics and RNAseq, will be precious to better understanding the disease dynamics.

SUBMITTER: Reis BCSD

PROVIDER: S-EPMC10426286 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Rare genetic variants involved in multisystem inflammatory syndrome in children: a multicenter Brazilian cohort study.

Reis Bárbara Carvalho Santos Dos BCSD Soares Faccion Roberta R de Carvalho Flavia Amendola Anisio FAA Moore Daniella Campelo Batalha Cox DCBC Zuma Maria Celia Chaves MCC Plaça Desirée Rodrigues DR Salerno Filgueiras Igor I Leandro Mathias Fonseca Dennyson D Cabral-Marques Otavio O Bonomo Adriana Cesar AC Savino Wilson W Freitas Flávia Cristina de Paula FCP Faoro Helisson H Passetti Fabio F Robaina Jaqueline Rodrigues JR de Oliveira Felipe Rezende Caino FRC Novaes Bellinat Ana Paula AP Zeitel Raquel de Seixas RS Salú Margarida Dos Santos MDS de Oliveira Mariana Barros Genuíno MBG Rodrigues-Santos Gustavo G Prata-Barbosa Arnaldo A de Vasconcelos Zilton Farias Meira ZFM

Frontiers in cellular and infection microbiology 20230731

<h4>Introduction</h4>Despite the existing data on the Multisystem Inflammatory Syndrome in Children (MIS-C), the factors that determine these patients evolution remain elusive. Answers may lie, at least in part, in genetics. It is currently under investigation that MIS-C patients may have an underlying innate error of immunity (IEI), whether of monogenic, digenic, or even oligogenic origin.<h4>Methods</h4>To further investigate this hypothesis, 30 patients with MIS-C were submitted to whole exom ...[more]

PMID: 37588055

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Project description:Background: Most children and adolescents infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop a mild coronavirus disease 2019 (COVID-19) that usually does not require medical intervention. However, a small proportion of pediatric patients develop a severe clinical condition, Multisystem Inflammatory Syndrome in Children (MIS-C). The involvement of epigenetics in the control of the immune response and viral activity prompted us to carry out an epigenomic study to uncover target loci regulated by DNA methylation that could be altered upon the appearance of MIS-C. Methods: Peripheral blood samples were recruited from 43 confirmed MIS-C patients with a median age of 7.7 years, most of whom were of West-Eurasian origin. Four or more organ systems were involved in the majority of patients. 69 non-COVID-19 pediatric samples and 15 COVID-19 pediatric samples without MIS-C were used as controls. The cases in the two groups were mixed and divided into discovery (MIS-C = 29 and non-MIS-C = 56) and validation (MIS-C = 14 and non-MIS-C = 28) cohorts, and balanced for age, gender and ethnic background. We interrogated 850,000 CpG sites of the human genome for DNA methylation variants. Findings: The DNA methylation content of 33 CpG loci was linked with the presence of MIS-C. Of these sites, 18 (54.5%) were located in described genes. The top candidate gene was the immune T-cell mediator ZEB2; and others highly ranked candidates included the regulator of natural killer cell functional competence SH2D1B; VWA8, which contains a domain of the Von Willebrand factor A involved in the pediatric hemostasis disease; and human leukocyte antigen complex member HLA-DRB1; in addition to pro-inflammatory genes such as CUL2 and AIM2. The identified loci were used to construct a DNA methylation profile (EPIMISC) that was associated with MIS-C in both cohorts. The EPIMISC signature was also overrepresented in Kawasaki disease patients, a childhood pathology with also a possible viral trigger, that shares many of the clinical features of MIS-C. Interpretation: We have characterized DNA methylation loci that are associated with the onset of MIS-C. The identified genes are likely contributors to the characteristic exaggerated host inflammatory response observed in these patients. The described epigenetic signature could also provide new targets for more specific therapies for the disorder.

Project description:IntroductionMultisystem inflammatory syndrome in children associated with coronavirus disease 2019 (MIS-C), a novel hyperinflammatory condition secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, is associated with severe outcomes such as coronary artery aneurysm and death.MethodsThis multicenter, retrospective, observational cohort study including eight centers in Mexico, aimed to describe the clinical characteristics and outcomes of patients with MIS-C. Patient data were evaluated using latent class analysis (LCA) to categorize patients into three phenotypes: toxic shock syndrome-like (TSSL)-MIS-C, Kawasaki disease-like (KDL)-MIS-C, and nonspecific MIS-C (NS-MIS-C). Risk factors for adverse outcomes were estimated using multilevel mixed-effects logistic regression.ResultsThe study included 239 patients with MIS-C, including 61 (26%), 70 (29%), and 108 (45%) patients in the TSSL-MIS-C, KDL-MIS-C, and NS-MIS-C groups, respectively. Fifty-four percent of the patients were admitted to the intensive care unit, and 42%, 78%, and 41% received intravenous immunoglobulin, systemic glucocorticoids, and anticoagulants, respectively. Coronary artery dilatation and aneurysms were found in 5.7% and 13.2% of the patients in whom coronary artery diameter was measured, respectively. Any cause in-hospital mortality was 5.4%. Hospitalization after ten days of symptoms was associated with coronary artery abnormalities (odds ratio [OR] 1.6, 95% confidence interval [CI] 1.2-2.0). Age ≥10 years (OR: 5.6, 95% CI: 1.4-2.04), severe underlying condition (OR: 9.3, 95% CI: 2.8-31.0), platelet count <150,000 /mm3 (OR: 4.2, 95% CI: 1.2-14.7), international normalized ratio >1.2 (OR: 3.8, 95% CI: 1.05-13.9), and serum ferritin concentration >1,500 mg/dl at admission (OR: 52, 95% CI: 5.9-463) were risk factors for death.DiscussionMortality in patients with MIS-C was higher than reported in other series, probably because of a high rate of cases with serious underlying diseases.

Project description:BackgroundMultisystem inflammatory syndrome in children (MIS-C) is a severe disease with an unpredictable course and a substantial risk of cardiogenic shock. Our objectives were to (a) compare MIS-C phenotypes across the COVID-19 pandemic, (b) identify features associated with intensive care need and treatment with biologic agents.MethodsYouth aged 0-18 years, fulfilling the World Health Organization case definition of MIS-C, and admitted to the Alberta Children's Hospital during the first four waves of the COVID-19 pandemic (May 2020-December 2021) were included in this cohort study. Demographic, clinical, biochemical, imaging, and treatment data were captured.ResultsFifty-seven MIS-C patients (median age 6 years, range 0-17) were included. Thirty patients (53%) required intensive care. Patients in the third or fourth wave (indicated as phase 2 of the pandemic) presented with higher peak ferritin (µg/l, median (IQR) = 1134 (409-1806) vs. 370 (249-629), P = 0.001), NT-proBNP (ng/l, median (IQR) = 12,217 (3013-27,161) vs. 3213 (1216-8483), P = 0.02) and D-dimer (mg/l, median (IQR) = 4.81 (2.24-5.37) vs. 2.01 (1.27-3.34), P = 0.004) levels, and higher prevalence of liver enzyme abnormalities (n(%) = 17 (68) vs. 11 (34), P = 0.02), hypoalbuminemia (n(%) = 24 (100) vs. 25 (81), P = 0.03) and thrombocytopenia (n(%) 18 (72) vs. 11 (34), P = 0.007) compared to patients in the first two waves (phase 1). These patients had a higher need of non-invasive/mechanical ventilation (n(%) 4 (16) vs. 0 (0), P = 0.03). Unsupervised clustering analyses classified 47% of the patients in the correct wave and 74% in the correct phase of the pandemic. NT-proBNP was the only significant contributor to the need for intensive care in all applied multivariate regression models. Treatment with biologic agents was significantly associated with peak CRP (mg/l (median, IQR = 240.9 (132.9-319.4) vs. 155.8 (101.0-200.7), P = 0.02) and ferritin levels (µg/l, median (IQR) = 1380 (509-1753) vs. 473 (280-296)).ConclusionsMIS-C patients in a later stage of the pandemic displayed a more severe phenotype, reflecting the impact of distinct SARS-CoV-2 variants. NT-proBNP emerged as the most crucial feature associated with intensive care need, underscoring the importance of monitoring.

Dataset Information

Rare genetic variants involved in multisystem inflammatory syndrome in children: a multicenter Brazilian cohort study.

Introduction

Methods

Results

Discussion

Publications

Rare genetic variants involved in multisystem inflammatory syndrome in children: a multicenter Brazilian cohort study.

Similar Datasets

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