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"Alexandre, David"
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EIF2AK4 mutations cause pulmonary veno-occlusive disease, a recessive form of pulmonary hypertension
Florent Soubrier and colleagues identify biallelic mutations in
EIF2AK4
as a major cause of pulmonary veno-occlusive disease, a rare form of pulmonary hypertension.
EIF2AK4
encodes a serine-threonine kinase, and the disease-causing mutations are predicted to result in loss of protein function.
Pulmonary veno-occlusive disease (PVOD) is a rare and devastating cause of pulmonary hypertension that is characterized histologically by widespread fibrous intimal proliferation of septal veins and preseptal venules and is frequently associated with pulmonary capillary dilatation and proliferation
1
,
2
. PVOD is categorized into a separate pulmonary arterial hypertension–related group in the current classification of pulmonary hypertension
3
. PVOD presents either sporadically or as familial cases with a seemingly recessive mode of transmission
4
. Using whole-exome sequencing, we detected recessive mutations in
EIF2AK4
(also called
GCN2
) that cosegregated with PVOD in all 13 families studied. We also found biallelic
EIF2AK4
mutations in 5 of 20 histologically confirmed sporadic cases of PVOD. All mutations, either in a homozygous or compound-heterozygous state, disrupted the function of the gene. These findings point to
EIF2AK4
as the major gene that is linked to PVOD development and contribute toward an understanding of the complex genetic architecture of pulmonary hypertension.
Journal Article
Who owns this sentence? : a history of copyrights and wrongs
An exploration into how copyright has become a tool of unprecedented power and wealth for the few, widening the gap between the richest and poorest in society.
Book
A Novel Channelopathy in Pulmonary Arterial Hypertension
In a family with pulmonary arterial hypertension, whole-exome sequencing led to identification of a mutation in the potassium-channel gene
KCNK3
. Additional mutations resulting in loss of function of the channel were found in other families and in patients with idiopathic disease.
Pulmonary arterial hypertension is a rare disease that is characterized by increased pulmonary-artery pressure in the absence of common causes of pulmonary hypertension, such as chronic heart, lung, or thromboembolic disease.
1
Before the advent of novel therapies, patients with idiopathic or familial pulmonary arterial hypertension had an estimated median survival of 2.8 years, with 1-year, 3-year, and 5-year survival rates of 68%, 48%, and 34%, respectively.
2
However, despite progress in treatment, pulmonary arterial hypertension remains a progressive, fatal disease. The clinical presentation can be nonspecific, and patients often receive a diagnosis late in their clinical course.
The cause of pulmonary . . .
Journal Article
The ribosome, (slow) beating heart of cancer (stem) cell
The ribosome has long been considered as a consistent molecular factory, with a rather passive role in the translation process. Recent findings have shifted this obsolete view, revealing a remarkably complex and multifaceted machinery whose role is to orchestrate spatiotemporal control of gene expression. Ribosome specialization discovery has raised the interesting possibility of the existence of its malignant counterpart, an 'oncogenic' ribosome, which may promote tumor progression. Here we weigh the arguments supporting the existence of an 'oncogenic' ribosome and evaluate its role in cancer evolution. In particular, we provide an analysis and perspective on how the ribosome may play a critical role in the acquisition and maintenance of cancer stem cell phenotype.
Journal Article
Impaired balance between neutrophil extracellular trap formation and degradation by DNases in COVID-19 disease
Background
Thrombo-inflammation and neutrophil extracellular traps (NETs) are exacerbated in severe cases of COVID-19, potentially contributing to disease exacerbation. However, the mechanisms underpinning this dysregulation remain elusive. We hypothesised that lower DNase activity may be associated with higher NETosis and clinical worsening in patients with COVID-19.
Methods
Biological samples were obtained from hospitalized patients (15 severe, 37 critical at sampling) and 93 non-severe ambulatory cases. Our aims were to compare NET biomarkers, functional DNase levels, and explore mechanisms driving any imbalance concerning disease severity.
Results
Functional DNase levels were diminished in the most severe patients, paralleling an imbalance between NET markers and DNase activity. DNase1 antigen levels were higher in ambulatory cases but lower in severe patients. DNase1L3 antigen levels remained consistent across subgroups, not rising alongside NET markers.
DNASE1
polymorphisms correlated with reduced DNase1 antigen levels. Moreover, a quantitative deficiency in plasmacytoid dendritic cells (pDCs), which primarily express
DNase1L3
, was observed in critical patients. Analysis of public single-cell RNAseq data revealed reduced
DNase1L3
expression in pDCs from severe COVID-19 patient.
Conclusion
Severe and critical COVID-19 cases exhibited an imbalance between NET and DNase functional activity and quantity. Early identification of NETosis imbalance could guide targeted therapies against thrombo-inflammation in COVID-19-related sepsis, such as DNase administration, to avert clinical deterioration.
Trial registration
: COVERAGE trial (NCT04356495) and COLCOV19-BX study (NCT04332016).
Graphical Abstract
Journal Article
Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data
Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.
Journal Article