scholarly journals Analysis of Glucocorticoid-Related Genes Reveal CCHCR1 as a New Candidate Gene for Type 2 Diabetes

2020 ◽  
Vol 4 (11) ◽  
Author(s):  
Laura N Brenner ◽  
Josep M Mercader ◽  
Catherine C Robertson ◽  
Joanne Cole ◽  
Ling Chen ◽  
...  

Abstract Glucocorticoids have multiple therapeutic benefits and are used both for immunosuppression and treatment purposes. Notwithstanding their benefits, glucocorticoid use often leads to hyperglycemia. Owing to the pathophysiologic overlap in glucocorticoid-induced hyperglycemia (GIH) and type 2 diabetes (T2D), we hypothesized that genetic variation in glucocorticoid pathways contributes to T2D risk. To determine the genetic contribution of glucocorticoid action on T2D risk, we conducted multiple genetic studies. First, we performed gene-set enrichment analyses on 3 collated glucocorticoid-related gene sets using publicly available genome-wide association and whole-exome data and demonstrated that genetic variants in glucocorticoid-related genes are associated with T2D and related glycemic traits. To identify which genes are driving this association, we performed gene burden tests using whole-exome sequence data. We identified 20 genes within the glucocorticoid-related gene sets that are nominally enriched for T2D-associated protein-coding variants. The most significant association was found in coding variants in coiled-coil α-helical rod protein 1 (CCHCR1) in the HLA region (P = .001). Further analyses revealed that noncoding variants near CCHCR1 are also associated with T2D at genome-wide significance (P = 7.70 × 10–14), independent of type 1 diabetes HLA risk. Finally, gene expression and colocalization analyses demonstrate that variants associated with increased T2D risk are also associated with decreased expression of CCHCR1 in multiple tissues, implicating this gene as a potential effector transcript at this locus. Our discovery of a genetic link between glucocorticoids and T2D findings support the hypothesis that T2D and GIH may have shared underlying mechanisms.

2014 ◽  
Vol 94 (3) ◽  
pp. 479
Author(s):  
Kirk E. Lohmueller ◽  
Thomas Sparsø ◽  
Qibin Li ◽  
Ehm Andersson ◽  
Thorfinn Korneliussen ◽  
...  

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Jason Flannick ◽  
Christian Fuchsberger ◽  
Anubha Mahajan ◽  
Tanya M. Teslovich ◽  
Vineeta Agarwala ◽  
...  

Abstract To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1–5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.


2013 ◽  
Vol 93 (6) ◽  
pp. 1072-1086 ◽  
Author(s):  
Kirk E. Lohmueller ◽  
Thomas Sparsø ◽  
Qibin Li ◽  
Ehm Andersson ◽  
Thorfinn Korneliussen ◽  
...  

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1703-P ◽  
Author(s):  
SHYLAJA SRINIVASAN ◽  
JENNIFER TODD ◽  
LING CHEN ◽  
JASMIN DIVERS ◽  
SAM GIDDING ◽  
...  

2019 ◽  
Vol 74 (17) ◽  
pp. 2162-2174 ◽  
Author(s):  
Yanjun Guo ◽  
Wonil Chung ◽  
Zhaozhong Zhu ◽  
Zhilei Shan ◽  
Jun Li ◽  
...  

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