Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose
Aims/hypothesis An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed t...
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Published in | Diabetologia Vol. 64; no. 7; pp. 1613 - 1625 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.07.2021
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 0012-186X 1432-0428 1432-0428 |
DOI | 10.1007/s00125-021-05449-9 |
Cover
Abstract | Aims/hypothesis
An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses.
Methods
We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data.
Results
Our meta-analysis identified 18 significant (
p
< 5 × 10
−8
) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the
G6PC2
gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in
G6PC2
as the instrument.
Conclusions/interpretation
Our analysis results suggest that rs2232326 and rs2232328 in
G6PC2
may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in
G6PC2
and CpGs near
G6PC2
may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near
G6PC2
, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose.
Graphical abstract |
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AbstractList | An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses.
We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data.
Our meta-analysis identified 18 significant (p < 5 × 10
) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument.
Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose. Aims/hypothesisAn elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses.MethodsWe first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data.ResultsOur meta-analysis identified 18 significant (p < 5 × 10−8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument.Conclusions/interpretationOur analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose. Aims/hypothesis An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses. Methods We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data. Results Our meta-analysis identified 18 significant ( p < 5 × 10 −8 ) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument. Conclusions/interpretation Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2 , an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose. Graphical abstract An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses.AIMS/HYPOTHESISAn elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses.We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data.METHODSWe first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data.Our meta-analysis identified 18 significant (p < 5 × 10-8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument.RESULTSOur meta-analysis identified 18 significant (p < 5 × 10-8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument.Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose.CONCLUSIONS/INTERPRETATIONOur analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose. |
Author | Lee, I-Te Chuang, Lee-Ming Hwu, Chii-Min Hsiung, Chao A. Quertermous, Thomas Chung, Ren-Hua Hung, Yi-Jen Chang, I-Shou Chiu, Yen-Feng Rotter, Jerome I. Chen, Yii-Der I. Wang, Wen-Chang |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33842983$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.2337/dcS13-2009 10.2337/db13-1100 10.1371/journal.pone.0152314 10.1093/hmg/ddw346 10.1038/ng.520 10.1038/s41467-019-12228-z 10.1038/nature08625 10.1007/s10654-017-0255-x 10.1038/sdata.2017.179 10.1038/nature15393 10.1002/gepi.21896 10.1016/j.ajhg.2018.09.007 10.1038/ng.939 10.1086/519795 10.1186/s13059-016-0926-z 10.1371/journal.pgen.1007275 10.1093/ije/dyr233 10.2337/db14-0563 10.1186/s13059-016-1066-1 10.1093/hmg/ddx293 10.1007/s11892-013-0422-8 10.1186/s13742-015-0047-8 10.2337/dc10-2263 10.1371/journal.pgen.1004876 10.2337/db12-1067 10.1038/ng.608 10.1007/s00125-006-0564-1 10.1016/j.gdata.2016.05.012 10.1038/ng.548 10.1038/ng.2274 10.1038/ng.277 10.1038/s41467-018-04951-w 10.1038/nature20784 10.1093/nar/gkw1133 10.2337/diabetes.48.3.531 10.1093/nar/gkq603 10.1038/s41467-019-10487-4 10.1038/nmeth0410-248 10.1002/sim.3034 10.1038/ng.290 10.1038/ncomms6897 10.1038/ng.2385 10.1007/s10654-015-0011-z 10.1016/j.ajhg.2018.03.012 10.1080/15592294.2016.1178418 10.1291/hypres.25.529 10.1038/s41467-020-19366-9 10.1186/s12864-017-3975-0 10.1186/s13073-017-0414-4 10.1038/nature18642 10.1093/bioinformatics/btw018 10.1186/1471-2164-14-293 10.2337/db09-1568 10.1007/s00125-017-4497-7 10.1038/s41588-018-0047-6 10.1007/s40142-019-00176-5 10.1371/journal.pgen.1004735 10.1016/j.ajhg.2017.09.003 10.2217/14622416.9.2.235 10.1038/s41588-018-0241-6 10.1186/s12862-017-0897-z 10.1371/journal.pgen.1002793 10.18637/jss.v023.i04 10.1093/bioinformatics/bty713 10.1038/ejhg.2011.184 10.1093/ije/dyw331 10.1016/j.bbagen.2012.12.013 10.1038/ng.2213 10.3389/fgene.2014.00370 10.1038/ng.572 10.1093/hmg/ddv232 |
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Keywords | DNA methylation Han Chinese GWAS Multi-omics analysis Fasting glucose Mendelian randomisation |
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PublicationDate | 20210700 2021-07-00 20210701 |
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PublicationPlace | Berlin/Heidelberg |
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PublicationSubtitle | Clinical, Translational and Experimental Diabetes and Metabolism |
PublicationTitle | Diabetologia |
PublicationTitleAbbrev | Diabetologia |
PublicationTitleAlternate | Diabetologia |
PublicationYear | 2021 |
Publisher | Springer Berlin Heidelberg Springer Nature B.V |
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References | Nagy, Boutin, Marten (CR7) 2017; 9 Wessel, Chu, Willems (CR69) 2015; 6 Bouatia-Naji, Bonnefond, Cavalcanti-Proenca (CR3) 2009; 41 Dupuis, Langenberg, Prokopenko (CR4) 2010; 42 Olsson, Volkov, Bacos (CR11) 2014; 10 Adzhubei, Schmidt, Peshkin (CR71) 2010; 7 Kulkarni, Kos, Neary (CR19) 2015; 24 Yang, Benyamin, McEvoy (CR52) 2010; 42 Manning, Hivert, Scott (CR6) 2012; 44 Juvinao-Quintero, Hivert, Sharp, Relton, Elliott (CR23) 2019; 7 CR34 Xue, Wu, Zhu (CR12) 2018; 9 Marcolongo, Fulceri, Gamberucci, Czegle, Banhegyi, Benedetti (CR61) 2013; 1830 Wu, Hsiao, Ho (CR27) 2002; 25 Al-Daghri, Pontremoli, Cagliani (CR72) 2017; 17 Chen, Erdos, Jackson (CR2) 2008; 118 Auton, Brooks (CR36) 2015; 526 Benner, Spencer, Havulinna, Salomaa, Ripatti, Pirinen (CR55) 2016; 32 Pidsley, Zotenko, Peters (CR38) 2016; 17 Pound, Oeser, O’Brien (CR64) 2013; 62 Fan, Lin, Lee (CR25) 2008; 9 Gaunt, Shihab, Hemani (CR59) 2016; 17 Dayeh, Tuomi, Almgren (CR74) 2016; 11 Henningsen, Hamann (CR53) 2007; 23 Hsu, Chang, Wu (CR26) 2017; 46 Takeuchi, Yokota, Yamamoto (CR46) 2012; 20 Hidalgo, Irvin, Sha (CR17) 2014; 63 Kanai, Akiyama, Takahashi (CR16) 2018; 50 Purcell, Neale, Todd-Brown (CR30) 2007; 81 Huan, Joehanes, Song (CR60) 2019; 10 Brambilla, La Valle, Falbo (CR1) 2011; 34 Verma, de Andrade, Tromp (CR37) 2014; 5 Gorrie-Stone, Smart, Saffari (CR39) 2019; 35 McCartney, Walker, Morris, McIntosh, Porteous, Evans (CR42) 2016; 9 Mahajan, Sim, Ng (CR68) 2015; 11 Kang, Sul, Service (CR43) 2010; 42 Chung, Chiu, Hung (CR32) 2017; 18 Fuchsberger, Flannick, Teslovich (CR44) 2016; 536 Scott, Lagou, Welch (CR5) 2012; 44 Lyssenko, Laakso (CR9) 2013; 36 Hwang, Sim, Wu (CR14) 2015; 64 Wheeler, Marenne, Barroso (CR67) 2017; 26 Kim, Go, Hu (CR13) 2011; 43 Yang, Ferreira, Morris (CR48) 2012; 44 Burgess, Thompson (CR73) 2017; 32 Lawlor, Harbord, Sterne, Timpson, Davey Smith (CR57) 2008; 27 Chang, Chow, Tellier, Vattikuti, Purcell, Lee (CR33) 2015; 4 Liu, Tozzi, Waterworth (CR47) 2010; 42 Chen, Yang, Chiang (CR28) 2016; 25 Staples, Maxwell, Gosalia (CR31) 2018; 102 Pidsley, Wong, Volta, Lunnon, Mill, Schalkwyk (CR40) 2013; 14 Mahajan, Taliun, Thurner (CR45) 2018; 50 Richardson, Zheng, Davey Smith (CR22) 2017; 101 Spracklen, Shi, Vadlamudi (CR15) 2018; 14 Arden, Zahn, Steegers (CR62) 1999; 48 Kriebel, Herder, Rathmann (CR18) 2016; 11 Hannon, Gorrie-Stone, Smart (CR41) 2018; 103 Kong, Steinthorsdottir, Masson (CR10) 2009; 462 MacArthur, Bowler, Cerezo (CR49) 2017; 45 Relton, Davey Smith (CR21) 2012; 41 Burgess, Scott, Timpson, Davey Smith, Thompson (CR56) 2015; 30 Flannick, Fuchsberger, Mahajan (CR70) 2017; 4 Conomos, Miller, Thornton (CR35) 2015; 39 Liu, Carnero-Montoro, van Dongen (CR24) 2019; 10 Walaszczyk, Luijten, Spijkerman (CR20) 2018; 61 Wahl, Drong, Lehne (CR54) 2017; 541 CR66 Voight, Kang, Ding (CR29) 2012; 8 O’Brien (CR65) 2013; 13 Lagou, Magi, Hottenga (CR50) 2021; 12 Wang, Martin, Oeser (CR63) 2007; 50 Ingelsson, Langenberg, Hivert (CR8) 2010; 59 Prokopenko, Langenberg, Florez (CR51) 2009; 41 Wang, Li, Hakonarson (CR58) 2010; 38 V Lagou (5449_CR50) 2021; 12 CC Chang (5449_CR33) 2015; 4 TJ Gorrie-Stone (5449_CR39) 2019; 35 R Pidsley (5449_CR40) 2013; 14 T Dayeh (5449_CR74) 2016; 11 CT Fan (5449_CR25) 2008; 9 S Purcell (5449_CR30) 2007; 81 BF Voight (5449_CR29) 2012; 8 CL Relton (5449_CR21) 2012; 41 J Wessel (5449_CR69) 2015; 6 J Flannick (5449_CR70) 2017; 4 CH Chen (5449_CR28) 2016; 25 IA Adzhubei (5449_CR71) 2010; 7 E Wheeler (5449_CR67) 2017; 26 E Walaszczyk (5449_CR20) 2018; 61 J Staples (5449_CR31) 2018; 102 JZ Liu (5449_CR47) 2010; 42 A Henningsen (5449_CR53) 2007; 23 5449_CR66 A Mahajan (5449_CR45) 2018; 50 E Hannon (5449_CR41) 2018; 103 C Fuchsberger (5449_CR44) 2016; 536 SD Arden (5449_CR62) 1999; 48 DL McCartney (5449_CR42) 2016; 9 RA Scott (5449_CR5) 2012; 44 RH Chung (5449_CR32) 2017; 18 N Bouatia-Naji (5449_CR3) 2009; 41 KD Wu (5449_CR27) 2002; 25 P Marcolongo (5449_CR61) 2013; 1830 AH Olsson (5449_CR11) 2014; 10 DL Juvinao-Quintero (5449_CR23) 2019; 7 TR Gaunt (5449_CR59) 2016; 17 E Ingelsson (5449_CR8) 2010; 59 JY Hwang (5449_CR14) 2015; 64 5449_CR34 J Yang (5449_CR52) 2010; 42 NM Al-Daghri (5449_CR72) 2017; 17 HM Kang (5449_CR43) 2010; 42 A Mahajan (5449_CR68) 2015; 11 DA Lawlor (5449_CR57) 2008; 27 RM O’Brien (5449_CR65) 2013; 13 C Benner (5449_CR55) 2016; 32 S Burgess (5449_CR73) 2017; 32 R Nagy (5449_CR7) 2017; 9 S Wahl (5449_CR54) 2017; 541 V Lyssenko (5449_CR9) 2013; 36 A Xue (5449_CR12) 2018; 9 J Kriebel (5449_CR18) 2016; 11 MP Conomos (5449_CR35) 2015; 39 TG Richardson (5449_CR22) 2017; 101 P Brambilla (5449_CR1) 2011; 34 CN Spracklen (5449_CR15) 2018; 14 SS Verma (5449_CR37) 2014; 5 J Liu (5449_CR24) 2019; 10 AK Manning (5449_CR6) 2012; 44 I Prokopenko (5449_CR51) 2009; 41 K Wang (5449_CR58) 2010; 38 CC Hsu (5449_CR26) 2017; 46 J Dupuis (5449_CR4) 2010; 42 J Yang (5449_CR48) 2012; 44 J MacArthur (5449_CR49) 2017; 45 B Hidalgo (5449_CR17) 2014; 63 YJ Kim (5449_CR13) 2011; 43 T Huan (5449_CR60) 2019; 10 WM Chen (5449_CR2) 2008; 118 H Kulkarni (5449_CR19) 2015; 24 Y Wang (5449_CR63) 2007; 50 R Pidsley (5449_CR38) 2016; 17 LD Pound (5449_CR64) 2013; 62 A Auton (5449_CR36) 2015; 526 A Kong (5449_CR10) 2009; 462 S Burgess (5449_CR56) 2015; 30 F Takeuchi (5449_CR46) 2012; 20 M Kanai (5449_CR16) 2018; 50 |
References_xml | – volume: 36 start-page: S120 issue: Suppl 2 year: 2013 end-page: S126 ident: CR9 article-title: Genetic screening for the risk of type 2 diabetes: worthless or valuable? publication-title: Diabetes Care doi: 10.2337/dcS13-2009 – volume: 63 start-page: 801 year: 2014 end-page: 807 ident: CR17 article-title: Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the Genetics of Lipid Lowering Drugs and Diet Network study publication-title: Diabetes doi: 10.2337/db13-1100 – volume: 11 start-page: e0152314 year: 2016 ident: CR18 article-title: Association between DNA Methylation in Whole Blood and Measures of Glucose Metabolism: KORA F4 Study publication-title: PLoS One doi: 10.1371/journal.pone.0152314 – volume: 25 start-page: 5321 year: 2016 end-page: 5331 ident: CR28 article-title: Population structure of Han Chinese in the modern Taiwanese population based on 10,000 participants in the Taiwan Biobank project publication-title: Hum Mol Genet doi: 10.1093/hmg/ddw346 – volume: 42 start-page: 105 year: 2010 end-page: 116 ident: CR4 article-title: New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk publication-title: Nat Genet doi: 10.1038/ng.520 – volume: 10 start-page: 4267 year: 2019 ident: CR60 article-title: Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease publication-title: Nat Commun doi: 10.1038/s41467-019-12228-z – volume: 462 start-page: 868 year: 2009 end-page: 874 ident: CR10 article-title: Parental origin of sequence variants associated with complex diseases publication-title: Nature doi: 10.1038/nature08625 – volume: 32 start-page: 377 year: 2017 end-page: 389 ident: CR73 article-title: Interpreting findings from Mendelian randomization using the MR-Egger method publication-title: Eur J Epidemiol doi: 10.1007/s10654-017-0255-x – volume: 4 start-page: 170179 year: 2017 ident: CR70 article-title: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls publication-title: Sci Data doi: 10.1038/sdata.2017.179 – volume: 526 start-page: 68 year: 2015 end-page: 74 ident: CR36 article-title: A global reference for human genetic variation publication-title: Nature doi: 10.1038/nature15393 – volume: 39 start-page: 276 year: 2015 end-page: 293 ident: CR35 article-title: Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness publication-title: Genet Epidemiol doi: 10.1002/gepi.21896 – volume: 103 start-page: 654 year: 2018 end-page: 665 ident: CR41 article-title: Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2018.09.007 – volume: 43 start-page: 990 year: 2011 end-page: 995 ident: CR13 article-title: Large-scale genome-wide association studies in East Asians identify new genetic loci influencing metabolic traits publication-title: Nat Genet doi: 10.1038/ng.939 – volume: 81 start-page: 559 year: 2007 end-page: 575 ident: CR30 article-title: PLINK: a tool set for whole-genome association and population-based linkage analyses publication-title: Am J Hum Genet doi: 10.1086/519795 – volume: 17 start-page: 61 year: 2016 ident: CR59 article-title: Systematic identification of genetic influences on methylation across the human life course publication-title: Genome Biol doi: 10.1186/s13059-016-0926-z – volume: 14 start-page: e1007275 year: 2018 ident: CR15 article-title: Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey publication-title: PLoS Genet doi: 10.1371/journal.pgen.1007275 – volume: 41 start-page: 161 year: 2012 end-page: 176 ident: CR21 article-title: Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease publication-title: Int J Epidemiol doi: 10.1093/ije/dyr233 – volume: 64 start-page: 291 year: 2015 end-page: 298 ident: CR14 article-title: Genome-wide association meta-analysis identifies novel variants associated with fasting plasma glucose in East Asians publication-title: Diabetes doi: 10.2337/db14-0563 – volume: 17 start-page: 208 year: 2016 ident: CR38 article-title: Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling publication-title: Genome Biol doi: 10.1186/s13059-016-1066-1 – volume: 26 start-page: R172 year: 2017 end-page: R184 ident: CR67 article-title: Genetic aetiology of glycaemic traits: approaches and insights publication-title: Hum Mol Genet doi: 10.1093/hmg/ddx293 – volume: 13 start-page: 768 year: 2013 end-page: 777 ident: CR65 article-title: Moving on from GWAS: functional studies on the G6PC2 gene implicated in the regulation of fasting blood glucose publication-title: Curr Diab Rep doi: 10.1007/s11892-013-0422-8 – volume: 4 start-page: 7 year: 2015 ident: CR33 article-title: Second-generation PLINK: rising to the challenge of larger and richer datasets publication-title: Gigascience doi: 10.1186/s13742-015-0047-8 – volume: 34 start-page: 1372 year: 2011 end-page: 1374 ident: CR1 article-title: Normal fasting plasma glucose and risk of type 2 diabetes publication-title: Diabetes Care doi: 10.2337/dc10-2263 – volume: 11 start-page: e1004876 year: 2015 ident: CR68 article-title: Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus publication-title: PLoS Genet doi: 10.1371/journal.pgen.1004876 – volume: 62 start-page: 1547 year: 2013 end-page: 1556 ident: CR64 article-title: G6PC2: a negative regulator of basal glucose-stimulated insulin secretion publication-title: Diabetes doi: 10.2337/db12-1067 – volume: 42 start-page: 565 year: 2010 end-page: 569 ident: CR52 article-title: Common SNPs explain a large proportion of the heritability for human height publication-title: Nat Genet doi: 10.1038/ng.608 – volume: 50 start-page: 774 year: 2007 end-page: 778 ident: CR63 article-title: Deletion of the gene encoding the islet-specific glucose-6-phosphatase catalytic subunit-related protein autoantigen results in a mild metabolic phenotype publication-title: Diabetologia doi: 10.1007/s00125-006-0564-1 – volume: 9 start-page: 22 year: 2016 end-page: 24 ident: CR42 article-title: Identification of polymorphic and off-target probe binding sites on the Illumina Infinium MethylationEPIC BeadChip publication-title: Genom Data doi: 10.1016/j.gdata.2016.05.012 – volume: 42 start-page: 348 year: 2010 end-page: 354 ident: CR43 article-title: Variance component model to account for sample structure in genome-wide association studies publication-title: Nat Genet doi: 10.1038/ng.548 – volume: 44 start-page: 659 year: 2012 end-page: 669 ident: CR6 article-title: A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance publication-title: Nat Genet doi: 10.1038/ng.2274 – volume: 41 start-page: 89 year: 2009 end-page: 94 ident: CR3 article-title: A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk publication-title: Nat Genet doi: 10.1038/ng.277 – volume: 9 start-page: 2941 year: 2018 ident: CR12 article-title: Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes publication-title: Nat Commun doi: 10.1038/s41467-018-04951-w – volume: 541 start-page: 81 year: 2017 end-page: 86 ident: CR54 article-title: Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity publication-title: Nature doi: 10.1038/nature20784 – volume: 45 start-page: D896 year: 2017 end-page: D901 ident: CR49 article-title: The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog) publication-title: Nucleic Acids Res doi: 10.1093/nar/gkw1133 – volume: 48 start-page: 531 year: 1999 end-page: 542 ident: CR62 article-title: Molecular cloning of a pancreatic islet-specific glucose-6-phosphatase catalytic subunit-related protein publication-title: Diabetes doi: 10.2337/diabetes.48.3.531 – volume: 38 start-page: e164 year: 2010 ident: CR58 article-title: ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data publication-title: Nucleic Acids Res doi: 10.1093/nar/gkq603 – ident: CR66 – volume: 10 start-page: 2581 year: 2019 ident: CR24 article-title: An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis publication-title: Nat Commun doi: 10.1038/s41467-019-10487-4 – volume: 7 start-page: 248 year: 2010 end-page: 249 ident: CR71 article-title: A method and server for predicting damaging missense mutations publication-title: Nat Methods doi: 10.1038/nmeth0410-248 – volume: 27 start-page: 1133 year: 2008 end-page: 1163 ident: CR57 article-title: Mendelian randomization: using genes as instruments for making causal inferences in epidemiology publication-title: Stat Med doi: 10.1002/sim.3034 – volume: 41 start-page: 77 year: 2009 end-page: 81 ident: CR51 article-title: Variants in MTNR1B influence fasting glucose levels publication-title: Nat Genet doi: 10.1038/ng.290 – volume: 6 start-page: 5897 year: 2015 ident: CR69 article-title: Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility publication-title: Nat Commun doi: 10.1038/ncomms6897 – volume: 44 start-page: 991 year: 2012 end-page: 1005 ident: CR5 article-title: Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways publication-title: Nat Genet doi: 10.1038/ng.2385 – volume: 30 start-page: 543 year: 2015 end-page: 552 ident: CR56 article-title: Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors publication-title: Eur J Epidemiol doi: 10.1007/s10654-015-0011-z – volume: 102 start-page: 874 year: 2018 end-page: 889 ident: CR31 article-title: Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2018.03.012 – volume: 11 start-page: 482 year: 2016 end-page: 488 ident: CR74 article-title: DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk publication-title: Epigenetics doi: 10.1080/15592294.2016.1178418 – volume: 25 start-page: 529 year: 2002 end-page: 536 ident: CR27 article-title: Clustering and heritability of insulin resistance in Chinese and Japanese hypertensive families: a Stanford-Asian Pacific Program in Hypertension and Insulin Resistance sibling study publication-title: Hypertens Res doi: 10.1291/hypres.25.529 – volume: 12 start-page: 24 year: 2021 ident: CR50 article-title: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability publication-title: Nat Commun doi: 10.1038/s41467-020-19366-9 – volume: 18 start-page: 591 year: 2017 ident: CR32 article-title: Genome-wide copy number variation analysis identified deletions in SFMBT1 associated with fasting plasma glucose in a Han Chinese population publication-title: BMC Genomics doi: 10.1186/s12864-017-3975-0 – volume: 9 start-page: 23 year: 2017 ident: CR7 article-title: Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants publication-title: Genome Med doi: 10.1186/s13073-017-0414-4 – volume: 536 start-page: 41 year: 2016 end-page: 47 ident: CR44 article-title: The genetic architecture of type 2 diabetes publication-title: Nature doi: 10.1038/nature18642 – volume: 32 start-page: 1493 year: 2016 end-page: 1501 ident: CR55 article-title: FINEMAP: efficient variable selection using summary data from genome-wide association studies publication-title: Bioinformatics doi: 10.1093/bioinformatics/btw018 – volume: 14 start-page: 293 year: 2013 ident: CR40 article-title: A data-driven approach to preprocessing Illumina 450K methylation array data publication-title: BMC Genomics doi: 10.1186/1471-2164-14-293 – volume: 59 start-page: 1266 year: 2010 end-page: 1275 ident: CR8 article-title: Detailed physiologic characterization reveals diverse mechanisms for novel genetic Loci regulating glucose and insulin metabolism in humans publication-title: Diabetes doi: 10.2337/db09-1568 – volume: 61 start-page: 354 year: 2018 end-page: 368 ident: CR20 article-title: DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels: a systematic review and replication in a case-control sample of the Lifelines study publication-title: Diabetologia doi: 10.1007/s00125-017-4497-7 – volume: 50 start-page: 390 year: 2018 end-page: 400 ident: CR16 article-title: Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases publication-title: Nat Genet doi: 10.1038/s41588-018-0047-6 – volume: 7 start-page: 191 year: 2019 end-page: 207 ident: CR23 article-title: DNA Methylation and Type 2 Diabetes: the Use of Mendelian Randomization to Assess Causality publication-title: Curr Genet Med Rep doi: 10.1007/s40142-019-00176-5 – volume: 10 start-page: e1004735 year: 2014 ident: CR11 article-title: Genome-wide associations between genetic and epigenetic variation influence mRNA expression and insulin secretion in human pancreatic islets publication-title: PLoS Genet doi: 10.1371/journal.pgen.1004735 – volume: 101 start-page: 590 year: 2017 end-page: 602 ident: CR22 article-title: Mendelian Randomization Analysis Identifies CpG Sites as Putative Mediators for Genetic Influences on Cardiovascular Disease Risk publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2017.09.003 – volume: 9 start-page: 235 year: 2008 end-page: 246 ident: CR25 article-title: Taiwan Biobank: a project aiming to aid Taiwan’s transition into a biomedical island publication-title: Pharmacogenomics doi: 10.2217/14622416.9.2.235 – volume: 50 start-page: 1505 year: 2018 end-page: 1513 ident: CR45 article-title: Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps publication-title: Nat Genet doi: 10.1038/s41588-018-0241-6 – volume: 17 start-page: 43 year: 2017 ident: CR72 article-title: Susceptibility to type 2 diabetes may be modulated by haplotypes in G6PC2, a target of positive selection publication-title: BMC Evol Biol doi: 10.1186/s12862-017-0897-z – volume: 8 start-page: e1002793 year: 2012 ident: CR29 article-title: The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits publication-title: PLoS Genet doi: 10.1371/journal.pgen.1002793 – volume: 23 start-page: 1 year: 2007 end-page: 40 ident: CR53 article-title: systemfit: A package for estimating systems of simultaneous equations in R publication-title: J Stat Softw doi: 10.18637/jss.v023.i04 – volume: 35 start-page: 981 year: 2019 end-page: 986 ident: CR39 article-title: Bigmelon: tools for analysing large DNA methylation datasets publication-title: Bioinformatics doi: 10.1093/bioinformatics/bty713 – volume: 20 start-page: 333 year: 2012 end-page: 340 ident: CR46 article-title: Genome-wide association study of coronary artery disease in the Japanese publication-title: Eur J Hum Genet doi: 10.1038/ejhg.2011.184 – volume: 46 start-page: 1106 year: 2017 end-page: 1106j ident: CR26 article-title: Cohort Profile: The Healthy Aging Longitudinal Study in Taiwan (HALST) publication-title: Int J Epidemiol doi: 10.1093/ije/dyw331 – ident: CR34 – volume: 1830 start-page: 2608 year: 2013 end-page: 2618 ident: CR61 article-title: Multiple roles of glucose-6-phosphatases in pathophysiology: state of the art and future trends publication-title: Biochim Biophys Acta doi: 10.1016/j.bbagen.2012.12.013 – volume: 44 start-page: 369 year: 2012 end-page: 375 ident: CR48 article-title: Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits publication-title: Nat Genet doi: 10.1038/ng.2213 – volume: 118 start-page: 2620 year: 2008 end-page: 2628 ident: CR2 article-title: Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels publication-title: J Clin Invest – volume: 5 start-page: 370 year: 2014 ident: CR37 article-title: Imputation and quality control steps for combining multiple genome-wide datasets publication-title: Front Genet doi: 10.3389/fgene.2014.00370 – volume: 42 start-page: 436 year: 2010 end-page: 440 ident: CR47 article-title: Meta-analysis and imputation refines the association of 15q25 with smoking quantity publication-title: Nat Genet doi: 10.1038/ng.572 – volume: 24 start-page: 5330 year: 2015 end-page: 5344 ident: CR19 article-title: Novel epigenetic determinants of type 2 diabetes in Mexican-American families publication-title: Hum Mol Genet doi: 10.1093/hmg/ddv232 – volume: 536 start-page: 41 year: 2016 ident: 5449_CR44 publication-title: Nature doi: 10.1038/nature18642 – volume: 42 start-page: 565 year: 2010 ident: 5449_CR52 publication-title: Nat Genet doi: 10.1038/ng.608 – volume: 8 start-page: e1002793 year: 2012 ident: 5449_CR29 publication-title: PLoS Genet doi: 10.1371/journal.pgen.1002793 – volume: 4 start-page: 7 year: 2015 ident: 5449_CR33 publication-title: Gigascience doi: 10.1186/s13742-015-0047-8 – volume: 9 start-page: 23 year: 2017 ident: 5449_CR7 publication-title: Genome Med doi: 10.1186/s13073-017-0414-4 – volume: 9 start-page: 2941 year: 2018 ident: 5449_CR12 publication-title: Nat Commun doi: 10.1038/s41467-018-04951-w – volume: 42 start-page: 105 year: 2010 ident: 5449_CR4 publication-title: Nat Genet doi: 10.1038/ng.520 – ident: 5449_CR34 – volume: 27 start-page: 1133 year: 2008 ident: 5449_CR57 publication-title: Stat Med doi: 10.1002/sim.3034 – volume: 6 start-page: 5897 year: 2015 ident: 5449_CR69 publication-title: Nat Commun doi: 10.1038/ncomms6897 – volume: 25 start-page: 529 year: 2002 ident: 5449_CR27 publication-title: Hypertens Res doi: 10.1291/hypres.25.529 – volume: 1830 start-page: 2608 year: 2013 ident: 5449_CR61 publication-title: Biochim Biophys Acta doi: 10.1016/j.bbagen.2012.12.013 – volume: 14 start-page: e1007275 year: 2018 ident: 5449_CR15 publication-title: PLoS Genet doi: 10.1371/journal.pgen.1007275 – volume: 4 start-page: 170179 year: 2017 ident: 5449_CR70 publication-title: Sci Data doi: 10.1038/sdata.2017.179 – volume: 36 start-page: S120 issue: Suppl 2 year: 2013 ident: 5449_CR9 publication-title: Diabetes Care doi: 10.2337/dcS13-2009 – volume: 9 start-page: 22 year: 2016 ident: 5449_CR42 publication-title: Genom Data doi: 10.1016/j.gdata.2016.05.012 – volume: 42 start-page: 348 year: 2010 ident: 5449_CR43 publication-title: Nat Genet doi: 10.1038/ng.548 – volume: 62 start-page: 1547 year: 2013 ident: 5449_CR64 publication-title: Diabetes doi: 10.2337/db12-1067 – volume: 44 start-page: 991 year: 2012 ident: 5449_CR5 publication-title: Nat Genet doi: 10.1038/ng.2385 – volume: 17 start-page: 208 year: 2016 ident: 5449_CR38 publication-title: Genome Biol doi: 10.1186/s13059-016-1066-1 – volume: 10 start-page: 4267 year: 2019 ident: 5449_CR60 publication-title: Nat Commun doi: 10.1038/s41467-019-12228-z – volume: 17 start-page: 43 year: 2017 ident: 5449_CR72 publication-title: BMC Evol Biol doi: 10.1186/s12862-017-0897-z – volume: 41 start-page: 89 year: 2009 ident: 5449_CR3 publication-title: Nat Genet doi: 10.1038/ng.277 – volume: 44 start-page: 659 year: 2012 ident: 5449_CR6 publication-title: Nat Genet doi: 10.1038/ng.2274 – volume: 11 start-page: e1004876 year: 2015 ident: 5449_CR68 publication-title: PLoS Genet doi: 10.1371/journal.pgen.1004876 – volume: 541 start-page: 81 year: 2017 ident: 5449_CR54 publication-title: Nature doi: 10.1038/nature20784 – volume: 462 start-page: 868 year: 2009 ident: 5449_CR10 publication-title: Nature doi: 10.1038/nature08625 – volume: 41 start-page: 77 year: 2009 ident: 5449_CR51 publication-title: Nat Genet doi: 10.1038/ng.290 – volume: 44 start-page: 369 year: 2012 ident: 5449_CR48 publication-title: Nat Genet doi: 10.1038/ng.2213 – volume: 10 start-page: 2581 year: 2019 ident: 5449_CR24 publication-title: Nat Commun doi: 10.1038/s41467-019-10487-4 – volume: 18 start-page: 591 year: 2017 ident: 5449_CR32 publication-title: BMC Genomics doi: 10.1186/s12864-017-3975-0 – volume: 30 start-page: 543 year: 2015 ident: 5449_CR56 publication-title: Eur J Epidemiol doi: 10.1007/s10654-015-0011-z – volume: 23 start-page: 1 year: 2007 ident: 5449_CR53 publication-title: J Stat Softw doi: 10.18637/jss.v023.i04 – volume: 14 start-page: 293 year: 2013 ident: 5449_CR40 publication-title: BMC Genomics doi: 10.1186/1471-2164-14-293 – volume: 17 start-page: 61 year: 2016 ident: 5449_CR59 publication-title: Genome Biol doi: 10.1186/s13059-016-0926-z – volume: 38 start-page: e164 year: 2010 ident: 5449_CR58 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkq603 – volume: 43 start-page: 990 year: 2011 ident: 5449_CR13 publication-title: Nat Genet doi: 10.1038/ng.939 – volume: 12 start-page: 24 year: 2021 ident: 5449_CR50 publication-title: Nat Commun doi: 10.1038/s41467-020-19366-9 – volume: 526 start-page: 68 year: 2015 ident: 5449_CR36 publication-title: Nature doi: 10.1038/nature15393 – volume: 10 start-page: e1004735 year: 2014 ident: 5449_CR11 publication-title: PLoS Genet doi: 10.1371/journal.pgen.1004735 – volume: 20 start-page: 333 year: 2012 ident: 5449_CR46 publication-title: Eur J Hum Genet doi: 10.1038/ejhg.2011.184 – volume: 13 start-page: 768 year: 2013 ident: 5449_CR65 publication-title: Curr Diab Rep doi: 10.1007/s11892-013-0422-8 – volume: 11 start-page: e0152314 year: 2016 ident: 5449_CR18 publication-title: PLoS One doi: 10.1371/journal.pone.0152314 – volume: 7 start-page: 191 year: 2019 ident: 5449_CR23 publication-title: Curr Genet Med Rep doi: 10.1007/s40142-019-00176-5 – volume: 46 start-page: 1106 year: 2017 ident: 5449_CR26 publication-title: Int J Epidemiol doi: 10.1093/ije/dyw331 – volume: 7 start-page: 248 year: 2010 ident: 5449_CR71 publication-title: Nat Methods doi: 10.1038/nmeth0410-248 – volume: 64 start-page: 291 year: 2015 ident: 5449_CR14 publication-title: Diabetes doi: 10.2337/db14-0563 – volume: 118 start-page: 2620 year: 2008 ident: 5449_CR2 publication-title: J Clin Invest – volume: 50 start-page: 774 year: 2007 ident: 5449_CR63 publication-title: Diabetologia doi: 10.1007/s00125-006-0564-1 – volume: 101 start-page: 590 year: 2017 ident: 5449_CR22 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2017.09.003 – volume: 59 start-page: 1266 year: 2010 ident: 5449_CR8 publication-title: Diabetes doi: 10.2337/db09-1568 – volume: 61 start-page: 354 year: 2018 ident: 5449_CR20 publication-title: Diabetologia doi: 10.1007/s00125-017-4497-7 – volume: 41 start-page: 161 year: 2012 ident: 5449_CR21 publication-title: Int J Epidemiol doi: 10.1093/ije/dyr233 – volume: 26 start-page: R172 year: 2017 ident: 5449_CR67 publication-title: Hum Mol Genet doi: 10.1093/hmg/ddx293 – volume: 34 start-page: 1372 year: 2011 ident: 5449_CR1 publication-title: Diabetes Care doi: 10.2337/dc10-2263 – volume: 103 start-page: 654 year: 2018 ident: 5449_CR41 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2018.09.007 – volume: 48 start-page: 531 year: 1999 ident: 5449_CR62 publication-title: Diabetes doi: 10.2337/diabetes.48.3.531 – volume: 42 start-page: 436 year: 2010 ident: 5449_CR47 publication-title: Nat Genet doi: 10.1038/ng.572 – volume: 63 start-page: 801 year: 2014 ident: 5449_CR17 publication-title: Diabetes doi: 10.2337/db13-1100 – volume: 32 start-page: 1493 year: 2016 ident: 5449_CR55 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btw018 – volume: 50 start-page: 390 year: 2018 ident: 5449_CR16 publication-title: Nat Genet doi: 10.1038/s41588-018-0047-6 – volume: 39 start-page: 276 year: 2015 ident: 5449_CR35 publication-title: Genet Epidemiol doi: 10.1002/gepi.21896 – volume: 5 start-page: 370 year: 2014 ident: 5449_CR37 publication-title: Front Genet doi: 10.3389/fgene.2014.00370 – volume: 9 start-page: 235 year: 2008 ident: 5449_CR25 publication-title: Pharmacogenomics doi: 10.2217/14622416.9.2.235 – volume: 25 start-page: 5321 year: 2016 ident: 5449_CR28 publication-title: Hum Mol Genet doi: 10.1093/hmg/ddw346 – volume: 45 start-page: D896 year: 2017 ident: 5449_CR49 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkw1133 – volume: 11 start-page: 482 year: 2016 ident: 5449_CR74 publication-title: Epigenetics doi: 10.1080/15592294.2016.1178418 – volume: 81 start-page: 559 year: 2007 ident: 5449_CR30 publication-title: Am J Hum Genet doi: 10.1086/519795 – volume: 35 start-page: 981 year: 2019 ident: 5449_CR39 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bty713 – ident: 5449_CR66 – volume: 32 start-page: 377 year: 2017 ident: 5449_CR73 publication-title: Eur J Epidemiol doi: 10.1007/s10654-017-0255-x – volume: 102 start-page: 874 year: 2018 ident: 5449_CR31 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2018.03.012 – volume: 50 start-page: 1505 year: 2018 ident: 5449_CR45 publication-title: Nat Genet doi: 10.1038/s41588-018-0241-6 – volume: 24 start-page: 5330 year: 2015 ident: 5449_CR19 publication-title: Hum Mol Genet doi: 10.1093/hmg/ddv232 |
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An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS)... An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified... Aims/hypothesisAn elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have... |
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SubjectTerms | Aging Biobanks Blood Glucose - genetics Cohort Studies CpG islands CpG Islands - genetics Deoxyribonucleic acid Diabetes Diabetes mellitus (non-insulin dependent) DNA DNA Methylation Fasting Fasting - blood Genetic diversity Genome-Wide Association Study Genomes Genomics - methods Glucose Glucose-6-Phosphatase - genetics Human Physiology Humans Insulin Insulin resistance Insulin secretion Internal Medicine Laboratory testing Longitudinal Studies Medicine Medicine & Public Health Mendelian Randomization Analysis Metabolic Diseases Polymorphism, Single Nucleotide Quantitative trait loci Quantitative Trait Loci - genetics Single-nucleotide polymorphism Taiwan - epidemiology |
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Title | Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose |
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