Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

Regine Bergholdt; Caroline Brorsson; Albert Palleja; Lukas A Berchtold; Tina Fløyel; Claus Heiner Bang-Berthelsen; Klaus Stensgaard Frederiksen; Lars Juhl Jensen; Joachim Størling; Flemming Pociot

doi:10.2337/db11-1263

Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

Regine Bergholdt, Caroline Brorsson, Albert Palleja, Lukas A Berchtold, Tina Fløyel, Claus Heiner Bang-Berthelsen, Klaus Stensgaard Frederiksen, Lars Juhl Jensen, Joachim Størling, Flemming Pociot

82 Citations (Scopus)

Abstract

Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize and substantiate these networks, we performed expressional profiling in human pancreatic islets exposed to proinflammatory cytokines. Three networks were significantly enriched for cytokine-regulated genes and, thus, likely to play an important role for type 1 diabetes in pancreatic islets. Eight of the regulated genes (CD83, IFNGR1, IL17RD, TRAF3IP2, IL27RA, PLCG2, MYO1B, and CXCR7) in these networks also harbored single nucleotide polymorphisms nominally associated with type 1 diabetes. Finally, the expression and cytokine regulation of these new candidate genes were confirmed in insulin-secreting INS-1 β-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.

Original language	English
Journal	Diabetes
Volume	61
Issue number	4
Pages (from-to)	954-62
Number of pages	9
ISSN	0046-0192
DOIs	https://doi.org/10.2337/db11-1263
Publication status	Published - Apr 2012

Keywords

Diabetes Mellitus, Type 1
Gene Expression Profiling
Gene Expression Regulation
Genome, Human
Humans
Islets of Langerhans
Protein Interaction Maps

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.2337/db11-1263

Cite this

Bergholdt, R., Brorsson, C., Palleja, A., Berchtold, L. A., Fløyel, T., Bang-Berthelsen, C. H., Frederiksen, K. S., Jensen, L. J., Størling, J., & Pociot, F. (2012). Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression. Diabetes, 61(4), 954-62. https://doi.org/10.2337/db11-1263

Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression. / Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert et al.

In: Diabetes, Vol. 61, No. 4, 04.2012, p. 954-62.

Research output: Contribution to journal › Journal article › Research › peer-review

Bergholdt, R, Brorsson, C, Palleja, A, Berchtold, LA, Fløyel, T, Bang-Berthelsen, CH, Frederiksen, KS, Jensen, LJ, Størling, J & Pociot, F 2012, 'Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression', Diabetes, vol. 61, no. 4, pp. 954-62. https://doi.org/10.2337/db11-1263

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abstract = "Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize and substantiate these networks, we performed expressional profiling in human pancreatic islets exposed to proinflammatory cytokines. Three networks were significantly enriched for cytokine-regulated genes and, thus, likely to play an important role for type 1 diabetes in pancreatic islets. Eight of the regulated genes (CD83, IFNGR1, IL17RD, TRAF3IP2, IL27RA, PLCG2, MYO1B, and CXCR7) in these networks also harbored single nucleotide polymorphisms nominally associated with type 1 diabetes. Finally, the expression and cytokine regulation of these new candidate genes were confirmed in insulin-secreting INS-1 β-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.",

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AU - Berchtold, Lukas A

AU - Fløyel, Tina

AU - Bang-Berthelsen, Claus Heiner

AU - Frederiksen, Klaus Stensgaard

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AB - Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize and substantiate these networks, we performed expressional profiling in human pancreatic islets exposed to proinflammatory cytokines. Three networks were significantly enriched for cytokine-regulated genes and, thus, likely to play an important role for type 1 diabetes in pancreatic islets. Eight of the regulated genes (CD83, IFNGR1, IL17RD, TRAF3IP2, IL27RA, PLCG2, MYO1B, and CXCR7) in these networks also harbored single nucleotide polymorphisms nominally associated with type 1 diabetes. Finally, the expression and cytokine regulation of these new candidate genes were confirmed in insulin-secreting INS-1 β-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.

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KW - Gene Expression Regulation

KW - Genome, Human

KW - Humans

KW - Islets of Langerhans

KW - Protein Interaction Maps

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Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

Abstract

Keywords

UN SDGs

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