scholarly journals Aging whole blood transcriptome reveals candidate genes for SARS-CoV-2-related vascular and immune alterations

Author(s):  
Luiz Gustavo de Almeida Chuffa ◽  
Paula Paccielli Freire ◽  
Jeferson dos Santos Souza ◽  
Mariana Costa de Mello ◽  
Mário de Oliveira Neto ◽  
...  
2012 ◽  
Vol 31 (1) ◽  
pp. 76 ◽  
Author(s):  
Adel M Zaatar ◽  
Chun Lim ◽  
Chin Bong ◽  
Michelle Mei Lee ◽  
Jian Ooi ◽  
...  

Author(s):  
Abel Plaza-Florido ◽  
Signe Altmäe ◽  
Francisco J. Esteban ◽  
Cristina Cadenas-Sanchez ◽  
Concepción M. Aguilera ◽  
...  

2019 ◽  
Vol 143 (2) ◽  
pp. AB423
Author(s):  
Paul J. Turner ◽  
Nandinee Patel ◽  
Monica Ruiz-Garcia ◽  
Isabel J. Skypala ◽  
Stephen R. Durham ◽  
...  

Vaccine ◽  
2019 ◽  
Vol 37 (13) ◽  
pp. 1743-1755 ◽  
Author(s):  
Peris M. Munyaka ◽  
Arun Kommadath ◽  
Janelle Fouhse ◽  
Jamie Wilkinson ◽  
Natalie Diether ◽  
...  

BMC Genomics ◽  
2017 ◽  
Vol 18 (S8) ◽  
Author(s):  
Guan Wang ◽  
Jérôme Durussel ◽  
Jonathan Shurlock ◽  
Martin Mooses ◽  
Noriyuki Fuku ◽  
...  

PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0139678 ◽  
Author(s):  
Valérie Rodrigues ◽  
Philippe Holzmuller ◽  
Carinne Puech ◽  
Hezron Wesonga ◽  
François Thiaucourt ◽  
...  

2020 ◽  
Author(s):  
Mahashweta Basu ◽  
Kun Wang ◽  
Eytan Ruppin ◽  
Sridhar Hannenhalli

AbstractComplex diseases are systemic, largely mediated via transcriptional dysregulation in multiple tissues. Thus, knowledge of tissue-specific transcriptome in an individual can provide important information about an individual’s health. Unfortunately, with a few exceptions such as blood, skin, and muscle, an individual’s tissue-specific transcriptome is not accessible through non-invasive means. However, due to shared genetics and regulatory programs between tissues, the transcriptome in blood may be predictive of those in other tissues, at least to some extent. Here, based on GTEx data, we address this question in a rigorous, systematic manner, for the first time. We find that an individual’s whole blood gene expression and splicing profile can predict tissue-specific expression levels in a significant manner (beyond demographic variables) for many genes. On average, across 32 tissues, the expression of about 60% of the genes is predictable from blood expression in a significant manner, with a maximum of 81% of the genes for the musculoskeletal tissue. Remarkably, the tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including Hypertension and Type 2 diabetes, substantially surpassing predictors built directly from the blood transcriptome. The code for our pipeline for tissue-specific gene expression prediction – TEEBoT, is provided, enabling others to study its potential translational value in other indications.


Cancers ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 4660
Author(s):  
Sandra van Wilpe ◽  
Victoria Wosika ◽  
Laura Ciarloni ◽  
Sahar Hosseinian Ehrensberger ◽  
Rachel Jeitziner ◽  
...  

Although immune checkpoint inhibitors improve median overall survival in patients with metastatic urothelial cancer (mUC), only a minority of patients benefit from it. Early blood-based response biomarkers may provide a reliable way to assess response weeks before imaging is available, enabling an early switch to other therapies. We conducted an exploratory study aimed at the identification of early markers of response to anti-PD-1 in patients with mUC. Whole blood RNA sequencing and phenotyping of peripheral blood mononuclear cells were performed on samples of 26 patients obtained before and after 2 to 6 weeks of anti-PD-1. Between baseline and on-treatment samples of patients with clinical benefit, 51 differentially expressed genes (DEGs) were identified, of which 37 were upregulated during treatment. Among the upregulated genes was PDCD1, the gene encoding PD-1. STRING network analysis revealed a cluster of five interconnected DEGs which were all involved in DNA replication or cell cycle regulation. We hypothesized that the upregulation of DNA replication/cell cycle genes is a result of T cell proliferation and we were able to detect an increase in Ki-67+ CD8+ T cells in patients with clinical benefit (median increase: 1.65%, range −0.63 to 7.06%, p = 0.012). In patients without clinical benefit, no DEGs were identified and no increase in Ki-67+ CD8+ T cells was observed. In conclusion, whole blood transcriptome profiling identified early changes in DNA replication and cell cycle regulation genes as markers of clinical benefit to anti-PD-1 in patients with urothelial cancer. Although promising, our findings require further validation before implementation in the clinic.


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