Publications by authors named "Deepak S Atri"
Background: Vascular diseases are accompanied by alterations in cellular phenotypes which underlie disease pathogenesis, with single-cell technologies aiding in the discovery of cellular heterogeneity among endothelial cell (EC) and vascular smooth muscle cell (VSMC) populations. In atherosclerotic disease, VSMCs are hypothesized to transition between contractile and synthetic states; however, the specific vascular subpopulations and intermediate cell states responsible for early vascular dysfunction remain unclear.
Methods: We integrated newly generated and published single-nuclear RNA-sequencing (snRNA-seq) datasets to analyze normal (n = 7), aneurysmal (n = 9), and atherosclerotic (n = 2) flash-frozen human ascending thoracic aortas.
The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci.
View Article and Find Full Text PDFBackground Myocardial injury in patients with COVID-19 is associated with increased mortality during index hospitalization; however, the relationship to long-term sequelae of SARS-CoV-2 is unknown. This study assessed the relationship between myocardial injury (high-sensitivity cardiac troponin T level) during index hospitalization for COVID-19 and longer-term outcomes. Methods and Results This is a prospective cohort of patients who were hospitalized at a single center between March and May 2020 with SARS-CoV-2.
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- CRISPR-Cas9 genome editing is a valuable technique for researching gene function, but it faces challenges with vascular cells due to low efficiency using traditional methods.
- The authors propose a new method using nucleofection to directly deliver sgRNA:Cas9 ribonucleoprotein complexes, leading to higher editing efficiency and faster results without needing selection steps.
- This technique not only works well for vascular cells but may also be useful for other hard-to-edit cell types, expanding the possibilities of genome editing research.
Background: Corin is a protease expressed in cardiomyocytes that plays a key role in salt handling and intravascular volume homeostasis via activation of natriuretic peptides. It is unknown if Corin loss-of-function (LOF) is causally associated with risk of coronary artery disease (CAD).
Methods: We analyzed all coding variants in an Italian case-control study of CAD.
Article Synopsis
- This study examines the pathophysiology of COVID-19 by analyzing single-cell and spatial atlases from various organ autopsy samples of individuals who died from the virus.
- Findings revealed significant changes in lung tissue, including impaired tissue regeneration and inflammation, indicating how SARS-CoV-2 affects different cell types.
- The research provides crucial insights into the biological impact of severe COVID-19, aiding in the development of potential new treatments.
Article Synopsis
- The SARS-CoV-2 pandemic has led to over 1 million deaths worldwide, primarily due to severe lung injuries and multiple organ failures, but there is limited understanding of the immune responses involved in COVID-19.
- Researchers collected and analyzed over 420 tissue samples from various organs of 17 COVID-19 victims, utilizing advanced techniques like RNA sequencing to map out cellular changes related to their illness.
- Significant findings include alterations in lung tissue cell types, such as the increase of specific progenitor cells and myofibroblasts, indicating impaired tissue repair and failed regenerative processes in severely damaged lungs.
Pathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of more than 3300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, hepatocyte growth factor, interleukin-8, and granulocyte colony-stimulating factor, which were the strongest predictors of critical illness.
View Article and Find Full Text PDFPathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of over 3,300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, HGF, IL-8, and G-CSF, as the strongest predictors of critical illness.
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