8 research outputs found
Functional study of the IFN-γ/IL-12 axis and oxidative burst in P1.
<p>A). Whole-blood IL-12/IFN-γ pathway screening. P1 and P2 had normal responses to IFN-γ and IL-12. B). EMSA detecting GAF DNA-binding activity after IFN-γ stimulation in the EBV-B cells from two healthy controls, P1 and individuals with complete recessive IFN-γR2 deficiency, used as a negative control. Cells were stimulated for 15 minutes with the indicated dose of IFN-γ. C). Oxidative burst. The production of superoxide in the EBV-B cells from healthy controls, P1 and patients with chronic granulomatous disease, used as negative controls, was determined following stimulation with PMA. These experiments were carried out at least twice.</p
Summary of clinical neurological presentations.
<p>Summary of clinical neurological presentations.</p
Immunoprecipitation and immunofluorescence of the AP-4 complex in P1.
<p>A). EBV-B cells and SV40 fibroblasts from P1 and a healthy control were subjected to immunoprecipitation under native conditions with antibodies against AP-4ε or AP-4β, and the immunoprecipitates were then western blotted with antibodies against AP-4ε or AP-4β. Equal amounts of protein were used for immunoprecipitation from patient and control cells. A small amount of AP-4β is coassembled with AP-4ε, and the AP-4ε assembled with AP-4β in P1 appears to be slightly smaller (AP-4ε*) than the AP-4ε in control cells. B). Fibroblasts from P1 and a healthy control were double-labeled for AP-4ε and the AP-4-associated protein tepsin. Note the specific loss of AP-4ε and tepsin from the cells of P1. Bar 20 µm. These experiments were carried out at least three times.</p
Data_Sheet_1_CDG: An Online Server for Detecting Biologically Closest Disease-Causing Genes and its Application to Primary Immunodeficiency.PDF
<p>High-throughput genomic technologies yield about 20,000 variants in the protein-coding exome of each individual. A commonly used approach to select candidate disease-causing variants is to test whether the associated gene has been previously reported to be disease-causing. In the absence of known disease-causing genes, it can be challenging to associate candidate genes with specific genetic diseases. To facilitate the discovery of novel gene-disease associations, we determined the putative biologically closest known genes and their associated diseases for 13,005 human genes not currently reported to be disease-associated. We used these data to construct the closest disease-causing genes (CDG) server, which can be used to infer the closest genes with an associated disease for a user-defined list of genes or diseases. We demonstrate the utility of the CDG server in five immunodeficiency patient exomes across different diseases and modes of inheritance, where CDG dramatically reduced the number of candidate genes to be evaluated. This resource will be a considerable asset for ascertaining the potential relevance of genetic variants found in patient exomes to specific diseases of interest. The CDG database and online server are freely available to non-commercial users at: http://lab.rockefeller.edu/casanova/CDG.</p
Table_1_CDG: An Online Server for Detecting Biologically Closest Disease-Causing Genes and its Application to Primary Immunodeficiency.XLSX
<p>High-throughput genomic technologies yield about 20,000 variants in the protein-coding exome of each individual. A commonly used approach to select candidate disease-causing variants is to test whether the associated gene has been previously reported to be disease-causing. In the absence of known disease-causing genes, it can be challenging to associate candidate genes with specific genetic diseases. To facilitate the discovery of novel gene-disease associations, we determined the putative biologically closest known genes and their associated diseases for 13,005 human genes not currently reported to be disease-associated. We used these data to construct the closest disease-causing genes (CDG) server, which can be used to infer the closest genes with an associated disease for a user-defined list of genes or diseases. We demonstrate the utility of the CDG server in five immunodeficiency patient exomes across different diseases and modes of inheritance, where CDG dramatically reduced the number of candidate genes to be evaluated. This resource will be a considerable asset for ascertaining the potential relevance of genetic variants found in patient exomes to specific diseases of interest. The CDG database and online server are freely available to non-commercial users at: http://lab.rockefeller.edu/casanova/CDG.</p
Summary of whole-exome sequencing results.
a<p>Number of variants not found in dbSNP or 1000 Genomes or HapMap and <0.001% in our database;</p>b<p>Hom: homozygous mutation;</p>c<p>Het, heterozygous mutation;</p>d<p>UTR-5: the five-prime untranslated region;</p>e<p>UTR-3: the three-prime untranslated region;</p>f<p>lincRNA: long non-coding RNA;</p>g<p>miRNA: microRNA.</p
mRNA and protein levels for the subunits of the AP-4 complex.
<p>A). RT-qPCR to assess mRNA levels for the components of the AP-4 complex in EBV-B cells from P1. B). RT-PCR to assess the splicing of <i>AP4E1</i> mRNA. C). Western blot: whole-cell homogenates from EBV-B cells from P1 and a healthy control were subjected to western blotting for clathrin heavy chain (CHC; loading control), AP-4ε, AP-4β or AP-4 μ. The loss of AP-4ε results in a concomitant decrease in the levels of AP-4β and AP-4 μ (specific bands are indicated by an arrow). These experiments were carried out at least twice.</p
COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19
The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p