Pathogenic variants damage cell compositions and single cell transcription in cardiomyopathies

 

Pathogenic variants in genes that cause dilated (DCM) and arrhythmogenic cardiomyopathies (ACM) convey high risks for the development of heart failure (HF) through unknown mechanisms. Using single nucleus RNA sequencing (snRNAseq), we characterized the transcriptome of 880,000 nuclei from 18 control and 61 failing, non-ischemic human hearts with pathogenic variants in DCM and ACM genes or idiopathic disease. We performed genotype-stratified analyses of the ventricular cell lineages and transcriptional states. The resultant DCM and ACM ventricular cell atlas demonstrated distinct right and left ventricular responses, highlighting genotype-associated pathways, intercellular interactions, and differential gene expression at single cell resolution. Together these data illuminate both shared and distinct cellular and molecular architectures of human HF and suggest novel candidate therapeutic targets.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): Chan Zuckerberg FoundationLeducq Foundation

The single-cell eQTLGen consortium

In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.

Probable reinfection with Legionella pneumophila - A case report

In Germany community-acquired Legionnaires' disease is usually caused by the species Legionella pneumophila. Recurrent cases of Legionnaires' disease are rarely reported and are due either to a second infection (reinfection) or a relapse of a previous case. We report a case of recurrent Legionnaires' disease in an 86-year-old female patient infected with Legionella pneumophila serogroup 1, monoclonal antibody-subtype Knoxville, sequence type unknown. Between the two disease incidents the patient had completely recovered. Legionella pneumophila was detected with the monoclonal antibody-subtype Knoxville, sequence type 182, in the drinking water of the patient's apartment. Exposure to contaminated drinking water was interrupted after the first incident exposure through the application of point-of-use water filters. The filters were later removed due to low water pressure, and the second illness occurred thereafter. It is unclear if immunological predisposition has contributed to this case of probable reinfection of Legionnaires' disease. Clinical, microbiological and epidemiological information combined suggest this is a case of reinfection of Legionnaires' disease. In cases of recurrent Legionnaires' disease complete collection of patient and water samples is necessary to differentiate relapse from reinfection cases, to implicate the source of infection and to gain more evidence for the role of immunological predisposition.

MetaMap: an atlas of metatranscriptomic reads in human disease-related RNA-seq data

Background

With the advent of the age of big data in bioinformatics, large volumes of data and high-performance computing power enable researchers to perform re-analyses of publicly available datasets at an unprecedented scale. Ever more studies imply the microbiome in both normal human physiology and a wide range of diseases. RNA sequencing technology (RNA-seq) is commonly used to infer global eukaryotic gene expression patterns under defined conditions, including human disease-related contexts; however, its generic nature also enables the detection of microbial and viral transcripts.

Findings

We developed a bioinformatic pipeline to screen existing human RNA-seq datasets for the presence of microbial and viral reads by re-inspecting the non-human-mapping read fraction. We validated this approach by recapitulating outcomes from six independent, controlled infection experiments of cell line models and compared them with an alternative metatranscriptomic mapping strategy. We then applied the pipeline to close to 150 terabytes of publicly available raw RNA-seq data from  more than 17,000 samples from more than 400 studies relevant to human disease using state-of-the-art high-performance computing systems. The resulting data from this large-scale re-analysis are made available in the presented MetaMap resource.

Conclusions

Our results demonstrate that common human RNA-seq data, including those archived in public repositories, might contain valuable information to correlate microbial and viral detection patterns with diverse diseases. The presented MetaMap database thus provides a rich resource for hypothesis generation toward the role of the microbiome in human disease. Additionally, codes to process new datasets and perform statistical analyses are made available.

Establishing the relative accuracy of three new definitions of the adult respiratory distress syndrome

OBJECTIVES

Over the last few years, new definitions of the adult respiratory distress syndrome (ARDS) have been introduced that potentially identify patients earlier in their course of acute lung injury. However, these definitions have never been compared with any of the older and potentially stricter definitions of ARDS to determine if similar patients are eventually identified. We compared new definitions of ARDS--as represented by the Lung Injury Score, a modified Lung Injury Score, and the American-European Consensus Conference definition--against a stricter definition of ARDS to determine their accuracy.

DESIGN

Prospective.

SETTING

Intensive care unit (ICU) patients in a tertiary, university-affiliated city hospital.

PATIENTS

ICU patients with clearly defined at-risk diagnoses for ARDS (group 1, n = 111) and general medical ICU patients without clearly defined at-risk diagnoses for ARDS (group 2, n = 125).

MEASUREMENTS AND MAIN RESULTS

Measurements of hypoxemia, static respiratory system compliance, positive end-expiratory pressure, radiographic changes, and general demographic information were collected. The sensitivity, specificity, positive-predictive value, negative-predictive value, and accuracy of all three new definitions were determined. Accuracy was defined as the true-positive plus the true-negative results divided by the total number of patients. When compared with a stricter definition of ARDS, all three definitions maintained a high degree of accuracy in those patients with a clearly defined at-risk diagnosis (group 1): Lung Injury Score 90.0% (95% confidence interval 84-96); modified Lung Injury Score 97.3% (95% confidence interval 94-100), and the American-European Consensus Conference definition 97.3% (95% confidence interval 94-100). For these at-risk patients, the accuracy of the modified Lung Injury Score and the American-European Consensus Conference definition was significantly better than the Lung Injury Score when compared with the strict definition (p = .027 for both comparisons). Although all three definitions maintained an accuracy of > 90% for general medical ICU patients (group 2), the low frequency of ARDS in these patients (3.4%) produced a low positive-predictive value for all three definitions.

CONCLUSIONS

We conclude that the Lung Injury Score, the modified Lung Injury Score, and the American-European Consensus Conference definition identify similar patients, provided that these methods are applied to patients with clearly defined at-risk diagnoses for ARDS.

Quantitative sensitivity of ultrasound in detecting free intraperitoneal fluid

The minimum volume of intraperitoneal fluid that is detectable in Morison's pouch with ultrasound in the trauma setting is not well defined. To evaluate this question, we used diagnostic peritoneal lavage (DPL) as a model for intraperitoneal hemorrhage and undertook a blinded prospective study of the sensitivity of ultrasound in detecting intraperitoneal fluid. Participants included attending physicians and residents in emergency medicine, radiology, and surgery. During the infusion of the DPL fluid, participants continuously scanned Morison's pouch until they detected fluid. All participants were blinded to the rate of infusion and the volume infused. One hundred patients were entered into the study. The mean volume of fluid detected was 619 mL. Only 10% of participants detected fluid volumes less than 400 mL and the overall sensitivity at one liter was 97%. We conclude that reliable detection of intraperitoneal fluid in Morison's pouch requires a greater volume than has been previously described.