X B Mo1,2,3, Y H Zhang2,3, S F Lei4,5,6. 1. Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. 2. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. 3. Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. 4. Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. leisf@suda.edu.cn. 5. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. leisf@suda.edu.cn. 6. Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. leisf@suda.edu.cn.
Abstract
This study investigated the effect of the N6-methyladenosine (m6A)-associated SNPs on bone mineral density (BMD) and found plenty of m6A-SNPs that were associated with BMD. This study increases our understanding on the regulation patterns of SNP and may provide new clues for further detection of functional mechanism underlying the associations between SNPs and osteoporosis. INTRODUCTION: m6A plays critical roles in many fundamental biological processes and a variety of diseases. The m6A-associated SNPs may be potential functional variants for BMD. The aim of this study was to investigate the effect of the genome-wide m6A-SNPs on BMD. METHODS: We examined the association of m6A-SNPs with femoral neck (FN) and lumbar spine (LS) BMD in 32,961 individuals and quantitative heel ultrasounds (eBMD) in 142,487 individuals. Furthermore, we performed expression quantitative trait locus (eQTL) analyses for the m6A-SNPs using whole genome data of about 10.5 million SNPs and 21,323 mRNAs from 43 Chinese individuals, as well as public available data. Differential expression analyses were also performed to support the identified genes. RESULTS: We found 138, 125, and 993 m6A-SNPs which were associated with FN-BMD, LS-BMD, and eBMD (P < 0.05), respectively. The associations of rs11614913 (P = 8.92 × 10-10) in MIR196A2 and rs1110720 (P = 2.05 × 10-10) in ESPL1 with LS-BMD reached the genome-wide significance level. In addition, a total of 24 m6A-SNPs were significantly associated with eBMD (P < 5.0 × 10-8). Further eQTL analyses showed that 47 of these BMD-associated m6A-SNPs were associated with expressions of the 46 corresponding local genes. Moreover, the expressions of 26 of these genes were associated with BMD. CONCLUSION: The present study represents the first effort of investigating the associations and the mechanisms underlying the link between m6A-SNPs and BMD. The results suggested that m6A-SNP may play important roles in the pathology of osteoporosis.
This study investigated the effect of the N6-methyladenosine (m6A)-associated SNPs on bone mineral density (BMD) and found plenty of m6A-SNPs that were associated with BMD. This study increases our understanding on the regulation patterns of SNP and may provide new clues for further detection of functional mechanism underlying the associations between SNPs and osteoporosis. INTRODUCTION:m6A plays critical roles in many fundamental biological processes and a variety of diseases. The m6A-associated SNPs may be potential functional variants for BMD. The aim of this study was to investigate the effect of the genome-wide m6A-SNPs on BMD. METHODS: We examined the association of m6A-SNPs with femoral neck (FN) and lumbar spine (LS) BMD in 32,961 individuals and quantitative heel ultrasounds (eBMD) in 142,487 individuals. Furthermore, we performed expression quantitative trait locus (eQTL) analyses for the m6A-SNPs using whole genome data of about 10.5 million SNPs and 21,323 mRNAs from 43 Chinese individuals, as well as public available data. Differential expression analyses were also performed to support the identified genes. RESULTS: We found 138, 125, and 993 m6A-SNPs which were associated with FN-BMD, LS-BMD, and eBMD (P < 0.05), respectively. The associations of rs11614913 (P = 8.92 × 10-10) in MIR196A2 and rs1110720 (P = 2.05 × 10-10) in ESPL1 with LS-BMD reached the genome-wide significance level. In addition, a total of 24 m6A-SNPs were significantly associated with eBMD (P < 5.0 × 10-8). Further eQTL analyses showed that 47 of these BMD-associated m6A-SNPs were associated with expressions of the 46 corresponding local genes. Moreover, the expressions of 26 of these genes were associated with BMD. CONCLUSION: The present study represents the first effort of investigating the associations and the mechanisms underlying the link between m6A-SNPs and BMD. The results suggested that m6A-SNP may play important roles in the pathology of osteoporosis.
Entities:
Keywords:
Bone mineral density; Gene expression; Genome-wide association study; RNA methylation; m6A
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