| Title |
Multivariate discovery and replication of five novel loci associated with Immunoglobulin G N-glycosylation
|
|---|---|
| Published in |
Nature Communications, September 2017
|
| DOI | 10.1038/s41467-017-00453-3 |
| Pubmed ID | |
| Authors |
Xia Shen, Lucija Klarić, Sodbo Sharapov, Massimo Mangino, Zheng Ning, Di Wu, Irena Trbojević-Akmačić, Maja Pučić-Baković, Igor Rudan, Ozren Polašek, Caroline Hayward, Timothy D. Spector, James F. Wilson, Gordan Lauc, Yurii S. Aulchenko |
| Abstract |
Joint modeling of a number of phenotypes using multivariate methods has often been neglected in genome-wide association studies and if used, replication has not been sought. Modern omics technologies allow characterization of functional phenomena using a large number of related phenotype measures, which can benefit from such joint analysis. Here, we report a multivariate genome-wide association studies of 23 immunoglobulin G (IgG) N-glycosylation phenotypes. In the discovery cohort, our multi-phenotype method uncovers ten genome-wide significant loci, of which five are novel (IGH, ELL2, HLA-B-C, AZI1, FUT6-FUT3). We convincingly replicate all novel loci via multivariate tests. We show that IgG N-glycosylation loci are strongly enriched for genes expressed in the immune system, in particular antibody-producing cells and B lymphocytes. We empirically demonstrate the efficacy of multivariate methods to discover novel, reproducible pleiotropic effects.Multivariate analysis methods can uncover the relationship between phenotypic measures characterised by modern omic techniques. Here the authors conduct a multivariate GWAS on IgG N-glycosylation phenotypes and identify 5 novel loci enriched in immune system genes. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 27% |
| Switzerland | 1 | 9% |
| Sweden | 1 | 9% |
| Croatia | 1 | 9% |
| Singapore | 1 | 9% |
| United States | 1 | 9% |
| China | 1 | 9% |
| Unknown | 2 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 45% |
| Members of the public | 5 | 45% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 95 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 25% |
| Researcher | 11 | 12% |
| Student > Master | 10 | 11% |
| Student > Bachelor | 7 | 7% |
| Student > Doctoral Student | 5 | 5% |
| Other | 15 | 16% |
| Unknown | 23 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 26 | 27% |
| Agricultural and Biological Sciences | 22 | 23% |
| Medicine and Dentistry | 7 | 7% |
| Neuroscience | 4 | 4% |
| Engineering | 3 | 3% |
| Other | 9 | 9% |
| Unknown | 24 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 December 2023.
All research outputs
#2,140,852
of 25,080,471 outputs
Outputs from Nature Communications
#26,727
of 55,165 outputs
Outputs of similar age
#40,050
of 320,977 outputs
Outputs of similar age from Nature Communications
#513
of 981 outputs
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