RESUMO
PURPOSE: Auto-antibodies (auto-abs) to type I interferons (IFNs) have been identified in patients with life-threatening coronavirus disease 2019 (COVID-19), suggesting that the presence of auto-abs may be a risk factor for disease severity. We therefore investigated the mechanism underlying COVID-19 exacerbation induced by auto-abs to type I IFNs. METHODS: We evaluated plasma from 123 patients with COVID-19 to measure auto-abs to type I IFNs. We performed single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells from the patients with auto-abs and conducted epitope mapping of the auto-abs. RESULTS: Three of 19 severe and 4 of 42 critical COVID-19 patients had neutralizing auto-abs to type I IFNs. Patients with auto-abs to type I IFNs showed no characteristic clinical features. scRNA-seq from 38 patients with COVID-19 revealed that IFN signaling in conventional dendritic cells and canonical monocytes was attenuated, and SARS-CoV-2-specific BCR repertoires were decreased in patients with auto-abs. Furthermore, auto-abs to IFN-α2 from COVID-19 patients with auto-abs recognized characteristic epitopes of IFN-α2, which binds to the receptor. CONCLUSION: Auto-abs to type I IFN found in COVID-19 patients inhibited IFN signaling in dendritic cells and monocytes by blocking the binding of type I IFN to its receptor. The failure to properly induce production of an antibody to SARS-CoV-2 may be a causative factor of COVID-19 severity.
Assuntos
Autoanticorpos , COVID-19 , Interferon Tipo I , Células Mieloides , Feminino , Humanos , Masculino , Autoanticorpos/imunologia , Autoanticorpos/sangue , COVID-19/imunologia , Células Dendríticas/imunologia , Interferon Tipo I/imunologia , Interferon Tipo I/metabolismo , Células Mieloides/imunologia , SARS-CoV-2/imunologia , Índice de Gravidade de Doença , Transdução de Sinais/imunologiaRESUMO
Increased fluid overload (FO) is associated with poor outcomes in critically ill patients, especially in acute kidney injury (AKI). However, the exact timing from when FO influences outcomes remains unclear. We retrospectively screened intensive care unit (ICU) admitted patients with AKI between January 2011 and December 2015. Logistic or linear regression analyses were performed to determine when hourly %FO was significant on 90-day in-hospital mortality (primary outcome) or ventilator-free days (VFDs). In total, 1120 patients were enrolled in this study. Univariate analysis showed that a higher %FO was significantly associated with higher mortality from the first hour of ICU admission (odds ratio 1.34, 95% confidence interval 1.15-1.56, P < 0.001), whereas multivariate analysis adjusted with age, sex, APACHE II score, and sepsis etiology showed the association was significant from the 27th hour. Both univariate and multivariate analyses showed that a higher %FO was significantly associated with shorter VFDs from the 1st hour. The significant associations were retained during all following observation periods after they showed significance. In patients with AKI, a higher %FO was associated with higher mortality and shorter VFDs from the early phase after ICU admission. FO should be administered with a physiological target or goal in place from the initial phase of critical illness.
Assuntos
Injúria Renal Aguda , Desequilíbrio Hidroeletrolítico , Humanos , Estado Terminal , Estudos Retrospectivos , Desequilíbrio Hidroeletrolítico/complicações , Cuidados Críticos , Injúria Renal Aguda/etiologia , Unidades de Terapia IntensivaRESUMO
Predicting out-of-hospital cardiac arrest (OHCA) events might improve outcomes of OHCA patients. We hypothesized that machine learning algorithms using meteorological information would predict OHCA incidences. We used the Japanese population-based repository database of OHCA and weather information. The Tokyo data (2005-2012) was used as the training cohort and datasets of the top six populated prefectures (2013-2015) as the test. Eight various algorithms were evaluated to predict the high-incidence OHCA days, defined as the daily events exceeding 75% tile of our dataset, using meteorological and chronological values: temperature, humidity, air pressure, months, days, national holidays, the day before the holidays, the day after the holidays, and New Year's holidays. Additionally, we evaluated the contribution of each feature by Shapley Additive exPlanations (SHAP) values. The training cohort included 96,597 OHCA patients. The eXtreme Gradient Boosting (XGBoost) had the highest area under the receiver operating curve (AUROC) of 0.906 (95% confidence interval; 0.868-0.944). In the test cohorts, the XGBoost algorithms also had high AUROC (0.862-0.923). The SHAP values indicated that the "mean temperature on the previous day" impacted the most on the model. Algorithms using machine learning with meteorological and chronological information could predict OHCA events accurately.
Assuntos
Parada Cardíaca Extra-Hospitalar , Humanos , Parada Cardíaca Extra-Hospitalar/epidemiologia , Parada Cardíaca Extra-Hospitalar/etiologia , Incidência , Aprendizado de Máquina , Tempo (Meteorologia) , AlgoritmosRESUMO
While the development of prehospital diagnosis scales has been reported in various regions, we have also developed a scale to predict stroke type using machine learning. In the present study, we aimed to assess for the first time a scale that predicts the need for surgical intervention across stroke types, including subarachnoid haemorrhage and intracerebral haemorrhage. A multicentre retrospective study was conducted within a secondary medical care area. Twenty-three items, including vitals and neurological symptoms, were analysed in adult patients suspected of having a stroke by paramedics. The primary outcome was a binary classification model for predicting surgical intervention based on eXtreme Gradient Boosting (XGBoost). Of the 1143 patients enrolled, 765 (70%) were used as the training cohort, and 378 (30%) were used as the test cohort. The XGBoost model predicted stroke requiring surgical intervention with high accuracy in the test cohort, with an area under the receiver operating characteristic curve of 0.802 (sensitivity 0.748, specificity 0.853). We found that simple survey items, such as the level of consciousness, vital signs, sudden headache, and speech abnormalities were the most significant variables for accurate prediction. This algorithm can be useful for prehospital stroke management, which is crucial for better patient outcomes.
Assuntos
Serviços Médicos de Emergência , Acidente Vascular Cerebral , Humanos , Estudos Retrospectivos , Acidente Vascular Cerebral/diagnóstico , Acidente Vascular Cerebral/cirurgia , Hemorragia Cerebral , Aprendizado de MáquinaRESUMO
Rapid and precise prehospital recognition of acute coronary syndrome (ACS) is key to improving clinical outcomes. The aim of this study was to investigate a predictive power for predicting ACS using the machine learning-based prehospital algorithm. We conducted a multicenter observational prospective study that included 10 participating facilities in an urban area of Japan. The data from consecutive adult patients, identified by emergency medical service personnel with suspected ACS, were analyzed. In this study, we used nested cross-validation to evaluate the predictive performance of the model. The primary outcomes were binary classification models for ACS prediction based on the nine machine learning algorithms. The voting classifier model for ACS using 43 features had the highest area under the receiver operating curve (AUC) (0.861 [95% CI 0.775-0.832]) in the test score. After validating the accuracy of the model using the external cohort, we repeated the analysis with a limited number of selected features. The performance of the algorithms using 17 features remained high AUC (voting classifier, 0.864 [95% CI 0.830-0.898], support vector machine (radial basis function), 0.864 [95% CI 0.829-0.887]) in the test score. We found that the machine learning-based prehospital algorithms showed a high predictive power for predicting ACS.
Assuntos
Síndrome Coronariana Aguda , Serviços Médicos de Emergência , Adulto , Algoritmos , Humanos , Aprendizado de Máquina , Estudos ProspectivosRESUMO
The mortality of coronavirus disease 2019 (COVID-19) is strongly correlated with pulmonary vascular pathology accompanied by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-triggered immune dysregulation and aberrant activation of platelets. We combined histological analyses using field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy analyses of the lungs from autopsy samples and single-cell RNA sequencing of peripheral blood mononuclear cells to investigate the pathogenesis of vasculitis and immunothrombosis in COVID-19. We found that SARS-CoV-2 accumulated in the pulmonary vessels, causing exudative vasculitis accompanied by the emergence of thrombospondin-1-expressing noncanonical monocytes and the formation of myosin light chain 9 (Myl9)-containing microthrombi in the lung of COVID-19 patients with fatal disease. The amount of plasma Myl9 in COVID-19 was correlated with the clinical severity, and measuring plasma Myl9 together with other markers allowed us to predict the severity of the disease more accurately. This study provides detailed insight into the pathogenesis of vasculitis and immunothrombosis, which may lead to optimal medical treatment for COVID-19.
Assuntos
COVID-19 , Pulmão , Cadeias Leves de Miosina , SARS-CoV-2 , Índice de Gravidade de Doença , Tromboinflamação , Vasculite , COVID-19/sangue , COVID-19/complicações , COVID-19/patologia , Humanos , Leucócitos Mononucleares , Pulmão/irrigação sanguínea , Pulmão/metabolismo , Pulmão/patologia , Pulmão/virologia , Cadeias Leves de Miosina/sangue , RNA-Seq , SARS-CoV-2/isolamento & purificação , Análise de Célula Única , Espectrometria por Raios X , Tromboinflamação/patologia , Tromboinflamação/virologia , Vasculite/patologia , Vasculite/virologiaRESUMO
Machine learning can predict outcomes and determine variables contributing to precise prediction, and can thus classify patients with different risk factors of outcomes. This study aimed to investigate the predictive accuracy for mortality and length of stay in intensive care unit (ICU) patients using machine learning, and to identify the variables contributing to the precise prediction or classification of patients. Patients (n = 12,747) admitted to the ICU at Chiba University Hospital were randomly assigned to the training and test cohorts. After learning using the variables on admission in the training cohort, the area under the curve (AUC) was analyzed in the test cohort to evaluate the predictive accuracy of the supervised machine learning classifiers, including random forest (RF) for outcomes (primary outcome, mortality; secondary outcome, length of ICU stay). The rank of the variables that contributed to the machine learning prediction was confirmed, and cluster analysis of the patients with risk factors of mortality was performed to identify the important variables associated with patient outcomes. Machine learning using RF revealed a high predictive value for mortality, with an AUC of 0.945 (95% confidence interval [CI] 0.922-0.977). In addition, RF showed high predictive value for short and long ICU stays, with AUCs of 0.881 (95% CI 0.876-0.908) and 0.889 (95% CI 0.849-0.936), respectively. Lactate dehydrogenase (LDH) was identified as a variable contributing to the precise prediction in machine learning for both mortality and length of ICU stay. LDH was also identified as a contributing variable to classify patients into sub-populations based on different risk factors of mortality. The machine learning algorithm could predict mortality and length of stay in ICU patients with high accuracy. LDH was identified as a contributing variable in mortality and length of ICU stay prediction and could be used to classify patients based on mortality risk.
Assuntos
Algoritmos , Unidades de Terapia Intensiva , Aprendizado de Máquina , Mortalidade , Área Sob a Curva , Humanos , Tempo de Internação , Estudos RetrospectivosRESUMO
Soon after the emergence and global spread of the SARS-CoV-2 Omicron lineage BA.1, another Omicron lineage, BA.2, began outcompeting BA.1. The results of statistical analysis showed that the effective reproduction number of BA.2 is 1.4-fold higher than that of BA.1. Neutralization experiments revealed that immunity induced by COVID vaccines widely administered to human populations is not effective against BA.2, similar to BA.1, and that the antigenicity of BA.2 is notably different from that of BA.1. Cell culture experiments showed that the BA.2 spike confers higher replication efficacy in human nasal epithelial cells and is more efficient in mediating syncytia formation than the BA.1 spike. Furthermore, infection experiments using hamsters indicated that the BA.2 spike-bearing virus is more pathogenic than the BA.1 spike-bearing virus. Altogether, the results of our multiscale investigations suggest that the risk of BA.2 to global health is potentially higher than that of BA.1.
Assuntos
COVID-19 , SARS-CoV-2 , Glicoproteína da Espícula de Coronavírus , Animais , COVID-19/virologia , Cricetinae , Células Epiteliais , Humanos , SARS-CoV-2/genética , SARS-CoV-2/patogenicidade , Glicoproteína da Espícula de Coronavírus/genéticaRESUMO
BACKGROUND: Acute mesenteric ischemia (AMI) is challenging to diagnose in the early phase. We tested the hypothesis that blood levels of cell-free DNA would increase early after AMI. In addition, proteome analysis was conducted as an exploratory analysis to identify other potential diagnostic biomarkers. METHODS: Mesenteric ischemia, abdominal sepsis, and sham model were compared in Sprague-Dawley rats. The abdominal sepsis model was induced by cecum puncture and mesenteric ischemia model by ligation of the superior mesenteric artery. Blood levels of cell-free DNA were measured 2 h and 6 h after wound closure. Shotgun proteome analysis was performed using plasma samples obtained at the 2 h timepoint; quantitative analysis was conducted for proteins detected exclusively in the AMI models. RESULTS: Blood cell-free DNA levels at 2 h after wound closure were significantly higher in the AMI model than in the sham and the abdominal sepsis models (P < 0.05). Cell-free DNA was positively correlated with the pathologic ischemia severity score (correlation coefficient 0.793-0.834, P < 0.001). Derivative proteome analysis in blood at 2-h time point revealed higher intensity of paraoxonase-1 in the AMI models than in the abdominal sepsis models; the significantly high blood paraoxonase-1 levels in the AMI models were confirmed in a separate quantitative analysis (P = 0.015). CONCLUSIONS: Cell-free DNA was demonstrated to be a promising biomarker for the early diagnosis of mesenteric ischemia in a rat model of AMI. Paraoxonase-1 may also play a role in the differential diagnosis of mesenteric ischemia from abdominal sepsis. The current results warrant further investigation in human studies.
Assuntos
Ácidos Nucleicos Livres , Isquemia Mesentérica , Doença Aguda , Animais , Isquemia/diagnóstico , Artéria Mesentérica Superior , Ratos , Ratos Sprague-DawleyRESUMO
High precision is optimal in prehospital diagnostic algorithms for strokes and large vessel occlusions. We hypothesized that prehospital diagnostic algorithms for strokes and their subcategories using machine learning could have high predictive value. Consecutive adult patients with suspected stroke as per emergency medical service personnel were enrolled in a prospective multicenter observational study in 12 hospitals in Japan. Five diagnostic algorithms using machine learning, including logistic regression, random forest, support vector machine, and eXtreme Gradient Boosting, were evaluated for stroke and subcategories including acute ischemic stroke with/without large vessel occlusions, intracranial hemorrhage, and subarachnoid hemorrhage. Of the 1446 patients in the analysis, 1156 (80%) were randomly included in the training (derivation) cohort and cohorts, and 290 (20%) were included in the test (validation) cohort. In the diagnostic algorithms for strokes using eXtreme Gradient Boosting had the highest diagnostic value (test data, area under the receiver operating curve 0.980). In the diagnostic algorithms for the subcategories using eXtreme Gradient Boosting had a high predictive value (test data, area under the receiver operating curve, acute ischemic stroke with/without large vessel occlusions 0.898/0.882, intracranial hemorrhage 0.866, subarachnoid hemorrhage 0.926). Prehospital diagnostic algorithms using machine learning had high predictive value for strokes and their subcategories.
Assuntos
Serviços Médicos de Emergência/métodos , Aprendizado de Máquina , Acidente Vascular Cerebral/diagnóstico , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos ProspectivosRESUMO
Current research regarding the association between body mass index (BMI) and altered clinical outcomes of sepsis in Asian populations is insufficient. We investigated the association between BMI and clinical outcomes using two Japanese cohorts of severe sepsis (derivation cohort, Chiba University Hospital, n = 614; validation cohort, multicenter cohort, n = 1561). Participants were categorized into the underweight (BMI < 18.5) and non-underweight (BMI ≥ 18.5) groups. The primary outcome was 28-day mortality. Univariate analysis of the derivation cohort indicated increased 28-day mortality trend in the underweight group compared to the non-underweight group (underweight 24.4% [20/82 cases] vs. non-underweight 16.0% [85/532 cases]; p = 0.060). In the primary analysis, multivariate analysis adjusted for baseline imbalance revealed that patients in the underweight group had a significantly increased 28-day mortality compared to those in the non-underweight group (p = 0.031, adjusted odds ratio [OR] 1.91, 95% confidence interval [CI] 1.06-3.46). In a repeated analysis using a multicenter validation cohort (underweight n = 343, non-underweight n = 1218), patients in the underweight group had a significantly increased 28-day mortality compared to those in the non-underweight group (p = 0.045, OR 1.40, 95% CI 1.00-1.97). In conclusion, patients with a BMI < 18.5 had a significantly increased 28-day mortality compared to those with a BMI ≥ 18.5 in Japanese cohorts with severe sepsis.
Assuntos
Índice de Massa Corporal , Sepse/mortalidade , Idoso , Estudos de Coortes , Feminino , Humanos , Interleucina-6/análise , Japão , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Razão de Chances , Sepse/patologia , Taxa de Sobrevida , Fatores de TempoRESUMO
OBJECTIVES: Obese patients have lower sepsis mortality termed the "obesity paradox." We hypothesized that lipopolysaccharide, known to be carried within lipoproteins such as very low density lipoprotein, could be sequestered in adipose tissue during sepsis; potentially contributing a survival benefit. DESIGN: Retrospective analysis. SETTING: University research laboratory. SUBJECTS AND PATIENTS: Vldlr knockout mice to decrease very low density lipoprotein receptors, Pcsk9 knockout mice to increase very low density lipoprotein receptor, and Ldlr knockout mice to decrease low density lipoprotein receptors. Differentiated 3T3-L1 adipocytes. Caucasian septic shock patients. INTERVENTIONS: We measured lipopolysaccharide uptake into adipose tissue 6 hours after injection of fluorescent lipopolysaccharide into mice. Lipopolysaccharide uptake and very low density lipoprotein receptor protein expression were measured in adipocytes. To determine relevance to humans, we genotyped the VLDLR rs7852409 G/C single-nucleotide polymorphism in 519 patients and examined the association of 28-day survival with genotype. MEASUREMENTS AND MAIN RESULTS: Lipopolysaccharide injected into mice was found in adipose tissue within 6 hours and was dependent on very low density lipoprotein receptor but not low density lipoprotein receptors. In an adipocyte cell line decreased very low density lipoprotein receptor expression resulted in decreased lipopolysaccharide uptake. In septic shock patients, the minor C allele of VLDLR rs7852409 was associated with increased survival (p = 0.010). Previously published data indicate that the C allele is a gain-of-function variant of VLDLR which may increase sequestration of very low density lipoprotein (and lipopolysaccharide within very low density lipoprotein) into adipose tissue. When body mass index less than 25 this survival effect was accentuated and when body mass index greater than or equal to 25 this effect was diminished suggesting that the effect of variation in very low density lipoprotein receptor function is overwhelmed when copious adipose tissue is present. CONCLUSIONS: Lipopolysaccharide may be sequestered in adipose tissue via the very low density lipoprotein receptor and this sequestration may contribute to improved sepsis survival.
Assuntos
Tecido Adiposo/metabolismo , Lipopolissacarídeos/metabolismo , Receptores de LDL/metabolismo , Sepse/metabolismo , Adipócitos/metabolismo , Adulto , Idoso , Animais , Células Cultivadas , Feminino , Humanos , Masculino , Camundongos , Pessoa de Meia-Idade , Estudos RetrospectivosRESUMO
The blood lactate level is used to guide the management of trauma patients with circulatory disturbance. We hypothesized that blood lactate levels at the scene (Lac scene) could improve the prediction for immediate interventions for hemorrhage. We prospectively measured blood lactate levels and assessed retrospectively in 435 trauma patients both at the scene and on arrival at the emergency room (ER) of a level I trauma center. Primary outcome was immediate intervention for hemorrhage defined as surgical/radiological intervention and/or blood transfusion within 24 h. Physiological variables plus Lac scene significantly increased the predictive value for immediate intervention (area under the curve [AUC] 0.882, 95% confidence interval [CI] 0.839-0.925) compared to that using physiological variables only (AUC 0.837, 95% CI 0.787-0.887, P = 0.0073), replicated in the validation cohort (n = 85). There was no significant improvement in predicting value of physiological variables plus Lac scene for massive transfusion compared to physiological variables (AUC 0.903 vs 0.895, P = 0.32). The increased blood lactate level per minute from scene to ER was associated with increased probability for immediate intervention (P < 0.0001). Both adding Lac scene to physiological variables and the temporal elevation of blood lactate levels from scene to ER could improve the prediction of the immediate intervention.
Assuntos
Hemorragia/sangue , Hemorragia/diagnóstico , Ácido Láctico/sangue , Ferimentos e Lesões/sangue , Ferimentos e Lesões/diagnóstico , Adulto , Área Sob a Curva , Transfusão de Sangue/métodos , Serviços Médicos de Emergência/métodos , Serviço Hospitalar de Emergência , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Estudos Prospectivos , Curva ROC , Centros de Traumatologia , Adulto JovemRESUMO
Previous studies have shown lipopolysaccharide from Gram-negative bacteria is cleared from the circulation via LDL receptors on hepatocytes, which are downregulated by PCSK9. Whether clearance of Gram positive bacterial lipoteichoic acid (LTA) shows similar dependence on PCSK9, and whether this is clinically relevant in Gram positive human sepsis, is unknown. We examined survival data from three cohorts of patients who had Gram positive septic shock (n = 170, n = 130, and n = 59) and found that patients who carried a PCSK9 loss-of-function (LOF) allele had significantly higher 28-day survival (73.8%) than those with no LOF alleles (52.8%) (p = 0.000038). Plasma clearance of LTA was also found to be increased in PCSK9 knockout mice compared to wildtype control mice (p = 0.002). In addition, hepatocytes pre-treated with recombinant wildtype PCSK9 showed a dose-dependent decrease in uptake of fluorescently-labeled LTA (p < 0.01). In comparison to wildtype PCSK9, hepatocytes pre-treated with 3 different LOF variants of recombinant PCSK9 showed an increase in LTA uptake. This study shows the clearance of LTA follows a similar route as lipopolysaccharide, which is dependent on hepatic LDL receptors. This has important implications in health as strategies aimed at inhibiting PCSK9 function may be an effective treatment option for both Gram-positive and negative sepsis.
Assuntos
Infecções por Bactérias Gram-Positivas/metabolismo , Lipopolissacarídeos/metabolismo , Pró-Proteína Convertase 9/metabolismo , Choque Séptico/metabolismo , Ácidos Teicoicos/metabolismo , Animais , Feminino , Citometria de Fluxo , Infecções por Bactérias Gram-Positivas/microbiologia , Hepatócitos/metabolismo , Humanos , Masculino , Camundongos Knockout , Pessoa de Meia-Idade , Pró-Proteína Convertase 9/sangue , Choque Séptico/microbiologia , Choque Séptico/mortalidade , Análise de SobrevidaRESUMO
Genetic variants are associated with altered clinical outcome of patients with sepsis and cardiovascular diseases. Common gene signaling pathways may be involved in the pathophysiology of these diseases. A better understanding of genetic commonality among these diseases may enable the discovery of important genes, signaling pathways, and therapeutic targets for these diseases. We investigated the common genetic factors by a systematic search of the literature. Twenty-four genes (ADRB2, CD14, FGB, FV, HMOX1, IL1B, IL1RN, IL6, IL10, IL17A, IRAK1, MASP2, MBL, MIR608, MIF, NOD2, PCSK9, PPARG, PROC, SERPINE1, SOD2, SVEP1, TF, TIRAP, TLR1) were extracted as reported genetic variations associated with altered outcome of both sepsis and cardiovascular diseases. Of these genes, the adverse allele (or combinations) was same in nine (ADRB2, FV, HMOX1, IL6, MBL, MIF, NOD2, PCSK9, SERPINE1), and the effect appears to be in the same direction in both sepsis and cardiovascular disease. Shared gene signaling pathways suggest that these are true biological results and could point to overlapping drug targets in sepsis and cardiovascular disease.
Assuntos
Doenças Cardiovasculares , Cuidados Críticos , Sepse , Transdução de Sinais , Doenças Cardiovasculares/tratamento farmacológico , Doenças Cardiovasculares/genética , Cuidados Críticos/métodos , Cuidados Críticos/tendências , Descoberta de Drogas , Predisposição Genética para Doença , Humanos , Terapia de Alvo Molecular/tendências , Polimorfismo de Nucleotídeo Único , Sepse/tratamento farmacológico , Sepse/genética , Transdução de Sinais/efeitos dos fármacos , Transdução de Sinais/genéticaRESUMO
High-density cholesterol (HDL-C) levels are influenced by genetic variation in several genes. Low levels of HDL-C have been associated with increased risk of acute kidney injury (AKI). We investigated whether genetic polymorphisms in ten genes known to regulate HDL-C levels are associated with both HDL-C levels and AKI development during sepsis. Two cohorts were retrospectively analyzed: Derivation Cohort (202 patients with sepsis enrolled at the Emergency Department from 2011 to 2014 in Vancouver, Canada); Validation Cohort (604 septic shock patients enrolled into the Vasopressin in Septic Shock Trial (VASST)). Associations between HDL-related genetic polymorphisms and both HDL-C levels, and risk for clinically significant sepsis-associated AKI (AKI KDIGO stages 2 and 3) were evaluated. In the Derivation Cohort, one genetic variant in the Cholesteryl Ester Transfer Protein (CETP) gene, rs1800777 (allele A), was strongly associated with lower HDL-C levels (17.4 mg/dL vs. 32.9 mg/dL, P = 0.002), greater CETP mass (3.43 µg/mL vs. 1.32 µg/mL, P = 0.034), and increased risk of clinically significant sepsis-associated AKI (OR: 8.28, p = 0.013). Moreover, the same allele was a predictor of sepsis-associated AKI in the Validation Cohort (OR: 2.38, p = 0.020). Our findings suggest that CETP modulates HDL-C levels in sepsis. CETP genotype may identify patients at high-risk of sepsis-associated AKI.
Assuntos
Injúria Renal Aguda/complicações , Alelos , Proteínas de Transferência de Ésteres de Colesterol/genética , HDL-Colesterol/sangue , Polimorfismo de Nucleotídeo Único , Sepse/sangue , Sepse/genética , Adulto , Idoso , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Sepse/complicaçõesRESUMO
The toxicity caused by different organisms in septic shock is substantially complex and characterized by an intricate pathogenicity that involves several systems and pathways. Immune cells' pattern recognition receptors initiate the host response to pathogens after the recognition of pathogen-associated molecular patterns. In essence, the subsequent activation of downstream pathways may progress to infection resolution or to a dysregulated host response that represents the hallmark of organ injury in septic shock. Likewise, the management of organism toxicity in septic shock is complicated and comprises a multiplicity of suitable targets. In this review, the classic immune responses to pathogens are discussed as well as other factors that are relevant in the pathogenicity of septic shock, including sepsis-induced immune suppression, inflammasome activation, intestinal permeability, and the role of lipids and proprotein convertase subtilisin/kexin type 9. Current therapies aiming to eliminate the organisms causing septic shock, recent and ongoing trials in septic shock treatment, and potential new therapeutic strategies are also explored.
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Infecções Bacterianas/imunologia , Choque Séptico/imunologia , Junções Íntimas/patologia , Animais , Apoptose , Interações Hospedeiro-Patógeno , Humanos , Tolerância Imunológica , Mucosa Intestinal/microbiologia , Mucosa Intestinal/patologia , Metabolismo dos Lipídeos , Moléculas com Motivos Associados a Patógenos , Pró-Proteína Convertase 9/metabolismo , Receptores de Reconhecimento de Padrão/metabolismo , Choque Séptico/terapia , Transdução de SinaisRESUMO
BACKGROUND: The IL10 family of genes includes crucial immune regulators. We tested the hypothesis that single nucleotide polymorphisms (SNPs) in IL10, IL19, IL20, and IL24 of the IL10 family gene cluster alter the clinical outcome of septic shock. METHODS: Patients with septic shock (n = 1,193) were genotyped for 13 tag SNPs of IL10, IL19, IL20, and IL24. IL20 gene expression was measured in genotyped lymphoblastoid cells in vitro. Cardiac surgical ICU patients (n = 981) were genotyped for IL20 rs2981573 A/G. The primary outcome variable was 28-day mortality. RESULTS: Patients with the G allele of IL20 rs2981573 had a significantly increased hazard of death over the 28-day period compared to patients with the A allele in the septic shock cohort (adjusted hazard ratio 1.27; 95% confidence interval 1.10-1.47; p = 8.0 × 10-4). Patients with the GG genotype had more organ dysfunction (p < 0.05). The GG genotype was associated with increased IL20 gene expression in stimulated lymphoblastoid cells in vitro (p < 0.05). The cardiac surgical ICU patients with the GG genotype had an increased length of ICU stay (p = 0.032). CONCLUSIONS: The GG genotype of IL20 rs2981573 SNP was associated with increased IL20 gene expression and increased adverse outcomes in patients with septic shock and following cardiac surgery.
Assuntos
Predisposição Genética para Doença/genética , Interleucinas/genética , Polimorfismo de Nucleotídeo Único , Choque Séptico/genética , Choque Séptico/mortalidade , Idoso , Linhagem Celular , Estudos de Coortes , Feminino , Expressão Gênica , Estudos de Associação Genética , Genótipo , Humanos , Unidades de Terapia Intensiva , Interleucina-10/genética , Tempo de Internação , Masculino , Pessoa de Meia-Idade , Escores de Disfunção Orgânica , Choque Séptico/cirurgiaRESUMO
Genetic polymorphisms have recently been found to be related to clinical outcome in septic patients. The present study investigated to evaluate the influence of genetic polymorphisms in Japanese septic patients on clinical outcome and whether use of genetic polymorphisms as predictors would enable more accurate prediction of outcome. Effects of 16 genetic polymorphisms related to pro-inflammatory mediators and conventional demographic/clinical parameters (age, sex, past medical history, and APACHE II score) on ICU mortality as well as disease severity during ICU stay were examined in the septic patients (n=123) admitted to the ICU between October 2001 and November 2007 by multivariable logistic regression analysis. ICU mortality was significantly associated with TNF -308GA, IL1ß -31CT/TT, and APACHE II score. Receiver-operating characteristics (ROC) analysis demonstrated that, compared with APACHE II score alone (ROC-AUC=0.68), use of APACHE II score and two genetic parameters (TNF -308 and IL1ß -31) enabled more accurate prediction of ICU mortality (ROC-AUC=0.80). Significant association of two genetic polymorphisms, TNF -308 and IL1ß -31, with ICU mortality was observed in septic patients. In addition, combined use of these genetic parameters with APACHE II score may enable more accurate prediction of outcome in septic patients.