A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity
IntroductionWe investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.MethodsWe conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD)...
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Frontiers Media S.A.
2024-10-01
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| Series: | Frontiers in Endocrinology |
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| author | John S. House Joseph H. Breeyear Farida S. Akhtari Violet Evans John B. Buse James Hempe Alessandro Doria Josyf C. Mychaleckyi Vivian Fonseca Mengyao Shi Changwei Li Shuqian Liu Tanika N. Kelly Tanika N. Kelly Tanika N. Kelly Daniel Rotroff Daniel Rotroff Daniel Rotroff Alison A. Motsinger-Reif |
| author_facet | John S. House Joseph H. Breeyear Farida S. Akhtari Violet Evans John B. Buse James Hempe Alessandro Doria Josyf C. Mychaleckyi Vivian Fonseca Mengyao Shi Changwei Li Shuqian Liu Tanika N. Kelly Tanika N. Kelly Tanika N. Kelly Daniel Rotroff Daniel Rotroff Daniel Rotroff Alison A. Motsinger-Reif |
| author_sort | John S. House |
| collection | DOAJ |
| description | IntroductionWe investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.MethodsWe conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race.ResultsIn ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) (P = 5.8e−10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin (WHRN) gene formally replicated (meta-P = 2.2e−9). The SNP-based heritability of HGI was 0.39 (P< 1e−10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1.DiscussionMany HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race. |
| format | Article |
| id | doaj-art-40ca2401c4bc4845ae5fe4fd8f5dab9e |
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| issn | 1664-2392 |
| language | English |
| publishDate | 2024-10-01 |
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| series | Frontiers in Endocrinology |
| spelling | doaj-art-40ca2401c4bc4845ae5fe4fd8f5dab9e2025-08-20T02:11:29ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922024-10-011510.3389/fendo.2024.14733291473329A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicityJohn S. House0Joseph H. Breeyear1Farida S. Akhtari2Violet Evans3John B. Buse4James Hempe5Alessandro Doria6Josyf C. Mychaleckyi7Vivian Fonseca8Mengyao Shi9Changwei Li10Shuqian Liu11Tanika N. Kelly12Tanika N. Kelly13Tanika N. Kelly14Daniel Rotroff15Daniel Rotroff16Daniel Rotroff17Alison A. Motsinger-Reif18Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United StatesBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United StatesBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United StatesBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United StatesDivision of Endocrinology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, United StatesDepartment of Pediatrics, Louisiana State University School of Medicine, New Orleans, LA, United StatesSection on Genetics and Epidemiology, Joslin Diabetes Center and Department of Medicine, Harvard Medical School, Boston, MA, United StatesCenter of Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, United StatesSection of Endocrinology, School of Medicine, Tulane University, New Orleans, LA, United StatesDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United StatesDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United StatesBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United StatesDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United StatesDepartment of Health Policy and Management, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United StatesTulane University Translational Science Institute, New Orleans, LA, United States0Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States1Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, OH, United States2Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, United StatesBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United StatesIntroductionWe investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.MethodsWe conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race.ResultsIn ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) (P = 5.8e−10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin (WHRN) gene formally replicated (meta-P = 2.2e−9). The SNP-based heritability of HGI was 0.39 (P< 1e−10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1.DiscussionMany HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race.https://www.frontiersin.org/articles/10.3389/fendo.2024.1473329/fullhemoglobin glycation indexHGIHbA1cACCORDARICGWAS |
| spellingShingle | John S. House Joseph H. Breeyear Farida S. Akhtari Violet Evans John B. Buse James Hempe Alessandro Doria Josyf C. Mychaleckyi Vivian Fonseca Mengyao Shi Changwei Li Shuqian Liu Tanika N. Kelly Tanika N. Kelly Tanika N. Kelly Daniel Rotroff Daniel Rotroff Daniel Rotroff Alison A. Motsinger-Reif A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity Frontiers in Endocrinology hemoglobin glycation index HGI HbA1c ACCORD ARIC GWAS |
| title | A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity |
| title_full | A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity |
| title_fullStr | A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity |
| title_full_unstemmed | A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity |
| title_short | A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity |
| title_sort | genome wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity |
| topic | hemoglobin glycation index HGI HbA1c ACCORD ARIC GWAS |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2024.1473329/full |
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