A novel high-throughput method for accurate, rapid, and economical measurement of multiple Type 1 diabetes autoantibodies

2000 ◽  
Vol 244 (1-2) ◽  
pp. 91-103 ◽  
Author(s):  
W Woo ◽  
J.M LaGasse ◽  
Z Zhou ◽  
R Patel ◽  
J.P Palmer ◽  
...  
2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Sharad Purohit ◽  
Ashok Sharma ◽  
Jin-Xiong She

Complex interactions between a series of environmental factors and genes result in progression to clinical type 1 diabetes in genetically susceptible individuals. Despite several decades of research in the area, these interactions remain poorly understood. Several studies have yielded associations of certain foods, infections, and immunizations with the onset and progression of diabetes autoimmunity, but most findings are still inconclusive. Environmental triggers are difficult to identify mainly due to (i) large number and complex nature of environmental exposures, including bacteria, viruses, dietary factors, and environmental pollutants, (ii) reliance on low throughput technology, (iii) less efforts in quantifying host response, (iv) long silent period between the exposure and clinical onset of T1D which may lead to loss of the exposure fingerprints, and (v) limited sample sets. Recent development in multiplex technologies has enabled systematic evaluation of different classes of molecules or macroparticles in a high throughput manner. However, the use of multiplex assays in type 1 diabetes research is limited to cytokine assays. In this review, we will discuss the potential use of multiplex high throughput technologies in identification of environmental triggers and host response in type 1 diabetes.


2010 ◽  
Vol 135 ◽  
pp. S19
Author(s):  
Brian Hondowicz ◽  
Katharine Schwedhelm ◽  
Arnold Kas ◽  
Michael Tasch ◽  
Nirasha Ramchurren ◽  
...  

2013 ◽  
Vol 13 (5) ◽  
pp. 608-615 ◽  
Author(s):  
Janet M. Wenzlau ◽  
John C. Hutton

Diabetes Care ◽  
2008 ◽  
Vol 32 (1) ◽  
pp. 123-125 ◽  
Author(s):  
R. Bonfanti ◽  
C. Colombo ◽  
V. Nocerino ◽  
O. Massa ◽  
V. Lampasona ◽  
...  

2021 ◽  
Author(s):  
Paola Benaglio ◽  
Han Zhu ◽  
Mei-Lin Okino ◽  
Jian Yan ◽  
Ruth Elgamal ◽  
...  

Beta cells intrinsically contribute to the pathogenesis of type 1 diabetes (T1D), but the genes and molecular processes that mediate beta cell survival in T1D remain largely unknown. We combined high throughput functional genomics and human genetics to identify T1D risk loci regulating genes affecting beta cell survival in response to the proinflammatory cytokines IL-1b, IFNg, and TNFa. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) active in beta cells using ATAC-seq and single nuclear ATAC-seq (snATAC-seq), and linked cytokine-responsive beta cell cCREs to putative target genes using single cell co-accessibility and HiChIP. We performed a genome-wide pooled CRISPR loss-of-function screen in EndoC-betaH1 cells, which identified 867 genes affecting cytokine-induced beta cell loss. Genes that promoted beta cell survival and had up-regulated expression in cytokine exposure were specifically enriched at T1D loci, and these genes were preferentially involved in inhibiting inflammatory response, ubiquitin-mediated proteolysis, mitophagy and autophagy. We identified 2,229 variants in cytokine-responsive beta cell cCREs altering transcription factor (TF) binding using high-throughput SNP-SELEX, and variants altering binding of TF families regulating stress, inflammation and apoptosis were broadly enriched for T1D association. Finally, through integration with genetic fine mapping, we annotated T1D loci regulating beta cell survival in cytokine exposure. At the 16p13 locus, a T1D variant affected TF binding in a cytokine-induced beta cell cCRE that physically interacted with the SOCS1 promoter, and increased SOCS1 activity promoted beta cell survival in cytokine exposure. Together our findings reveal processes and genes acting in beta cells during cytokine exposure that intrinsically modulate risk of T1D.


2007 ◽  
Vol 2 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Zafar Rasheed ◽  
Rizwan Ahmad ◽  
Naila Rasheed ◽  
Trivendra Tripathi ◽  
Rashid Ali

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