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Genome wide identification of new genes and pathways in patients with both autoimmune thyroiditis and type 1 diabetes

Overview of attention for article published in Journal of Autoimmunity, April 2015
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Title
Genome wide identification of new genes and pathways in patients with both autoimmune thyroiditis and type 1 diabetes
Published in
Journal of Autoimmunity, April 2015
DOI 10.1016/j.jaut.2015.03.006
Pubmed ID
Authors

Yaron Tomer, Lawrence M. Dolan, George Kahaly, Jasmin Divers, Ralph B. D'Agostino, Giuseppina Imperatore, Dana Dabelea, Santica Marcovina, Mary Helen Black, Catherine Pihoker, Alia Hasham, Sara Salehi Hammerstad, David A. Greenberg, Vaneet Lotay, Weijia Zhang, Maria Cristina Monti, Nina Matheis, SEARCH for Diabetes in Youth Study

Abstract

Autoimmune thyroid diseases (AITD) and Type 1 diabetes (T1D) frequently occur in the same individual pointing to a strong shared genetic susceptibility. Indeed, the co-occurrence of T1D and AITD in the same individual is classified as a variant of the autoimmune polyglandular syndrome type 3 (designated APS3v). Our aim was to identify new genes and mechanisms causing the co-occurrence of T1D + AITD (APS3v) in the same individual using a genome-wide approach. For our discovery set we analyzed 346 Caucasian APS3v patients and 727 gender and ethnicity matched healthy controls. Genotyping was performed using the Illumina Human660W-Quad.v1. The replication set included 185 APS3v patients and 340 controls. Association analyses were performed using the PLINK program, and pathway analyses were performed using the MAGENTA software. We identified multiple signals within the HLA region and conditioning studies suggested that a few of them contributed independently to the strong association of the HLA locus with APS3v. Outside the HLA region, variants in GPR103, a gene not suggested by previous studies of APS3v, T1D, or AITD, showed genome-wide significance (p < 5 × 10(-8)). In addition, a locus on 1p13 containing the PTPN22 gene showed genome-wide significant associations. Pathway analysis demonstrated that cell cycle, B-cell development, CD40, and CTLA-4 signaling were the major pathways contributing to the pathogenesis of APS3v. These findings suggest that complex mechanisms involving T-cell and B-cell pathways are involved in the strong genetic association between AITD and T1D.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 19%
Student > Ph. D. Student 9 16%
Researcher 7 12%
Other 5 9%
Student > Postgraduate 4 7%
Other 10 17%
Unknown 12 21%
Readers by discipline Count As %
Medicine and Dentistry 19 33%
Agricultural and Biological Sciences 12 21%
Biochemistry, Genetics and Molecular Biology 9 16%
Immunology and Microbiology 2 3%
Unspecified 1 2%
Other 2 3%
Unknown 13 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 January 2021.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from Journal of Autoimmunity
#1,310
of 1,650 outputs
Outputs of similar age
#169,659
of 279,950 outputs
Outputs of similar age from Journal of Autoimmunity
#13
of 18 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,650 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 279,950 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.