Paper accepted in AJRCCM!

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Mar 142018
 

Our paper with the title “Predicting outcome in idiopathic pulmonary fibrosis using automated CT analysis” was accepted in AJRCCM!

Authors:
Joseph Jacob, Brian J. Bartholmai, Srinivasan Rajagopalan, Coline H.M. van Moorsel, Hendrik W. van Es, Frouke T. van Beek, Marjolijn H.L. Struik, Maria Kokosi, Ryoko Egashira, Anne Laure Brun, Arjun Nair, Simon L.F. Walsh, Gary Cross, Joseph Barnett, Angelo de Lauretis, Eoin P. Judge, Sujal, Desai, Ronald Karwoski, Sebastien Ourselin, Elisabetta Renzoni, Toby M. Maher, Andre Altmann, Athol U. Wells

 

 Posted by at 22:30

Marzia receives Merit Abstract Award for the 2018 OHBM Annual Meeting in Singapore!

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Mar 142018
 

Our abstract “Rare genetic events in sporadic Alzheimer’s disease: a network propagation approach” was selected for an oral presentation at OHBM 2018, Singapore!

On top of that lead author Marzia Scelsi received (again!) a Merit Abstract Award for the 2018 OHBM Annual Meeting. Congrats Marzia!

M. A. Scelsi, J. E. Iglesias, J M Schott, S Ourselin, A Altmann, “Rare genetic events in sporadic Alzheimer’s disease: a network propagation approach

Introduction

The discovery of rare genetic mutations in the APP, PSEN1, and PSEN2 that cause familial Alzheimer’s disease (AD) has had profound implications for our understanding of deisease pathognesis. There is much interest in investigating rare genetic variants that might increase risk for, or influence the phenotype of, sporadic AD. This however remains challenging due to the very large sample sizes required and the costs of performing whole-genome sequencing (WGS) in these cohorts. Early successes have included the discovery that TREM2 influences risk (Guerreiro et al. 2013), a discovery that has intensified interest in inflammation in AD. Studies such as the Alzheimer’s Disease Sequencing Project (Bis et al. 2017) continue to address this challenge. Here, we present a method to investigate the effects of rare variant in moderately sized sporadic AD cohorts, such as ADNI Our approach is based on signal diffusion on a gene-interaction network, inspired by its successful application to cancer subtyping (Hofree et al. 2013). We sought to develop an integrative approach to guide gene-based association testing with the knowledge of tissue-specific interaction networks.

 Posted by at 01:23