Abstract
Aim To identify novel candidate genes and gene sets for diabetes. Methods We performed an integrative analysis of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) data for diabetes. Summary data was driven from a large-scale GWAS of diabetes, totally involving 58,070 individuals. eQTLs dataset included 923,021 cis-eQTL for 14,329 genes and 4,732 trans-eQTL for 2,612 genes. Integrative analysis of GWAS and eQTLs data was conducted by summary data-based Mendelian randomization (SMR). To identify the gene sets associated with diabetes, the SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA). A total of 13,311 annotated gene sets were analyzed in this study. Results SMR analysis identified 6 genes significantly associated with fasting glucose, such as C11ORF10 (p value = 6.04 × 10−8), MRPL33 (p value = 1.24 × 10−7), and FADS1 (p value = 2.39 × 10−7). Gene set analysis identified HUANG_FOXA2_TARGETS_UP (false discovery rate = 0.047) associated with fasting glucose. Conclusion Our study provides novel clues for clarifying the genetic mechanism of diabetes. This study also illustrated the good performance of SMR approach and extended it to gene set association analysis for complex diseases.
Highlights
Diabetes is a group of metabolic diseases, mainly characterized by raised blood glucose over a prolonged period
After strict Bonferroni correction, summary data-based Mendelian randomization (SMR) identified 6 genes significantly associated with fasting glucose (Table 1), including C11ORF10 (p value = 6.04 × 10−8), MRPL33 (p value = 1.24 × 10−7), FADS1 (p value = 2.39 × 10−7), ACP2 (p value = 1.74 × 10−6), NR1H3 (p value = 1.78 × 10−6), and SNX17 (p value = 2.19 × 10−6)
We identified multiple genes and gene sets associated with fasting glucose or fasting insulin
Summary
Diabetes is a group of metabolic diseases, mainly characterized by raised blood glucose over a prolonged period. Diabetes will lead to serious secondary disorders, such as heart disease, stroke, chronic kidney failure, and foot ulcers. The prevalence of diabetes continues to increase, caused by aging, obesity, smoking, and other unhealthy lifestyle factors [1]. Genetic factors contribute greatly to the development of diabetes. Extensive genetic studies have been conducted and identified a group of susceptibility genes for diabetes, such as PTEN [2], SREBF1 [3], JAZF1 [4], BCL2 [5], and FAM19A2 [5]. The genetic risk of diabetes explained by the identified loci was limited, suggesting the existence of undiscovered susceptibility loci for diabetes. The missing heritability can partly be attributed to the regulatory genetic variants, which are mostly locating outside genes and ignored by traditional genetic studies
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