Jee-Young Moon1, Tin L Louie2, Deepti Jain2, Tamar Sofer2,3, Claudia Schurmann4, Jennifer E Below5, Chao-Qiang Lai6, M Larissa Aviles-Santa7, Gregory A Talavera8, Caren E Smith6, Lauren E Petty5, Erwin P Bottinger9, Yii-Der Ida Chen10, Kent D Taylor10, Martha L Daviglus11, Jianwen Cai12, Tao Wang1, Katherine L Tucker13, José M Ordovás6,14, Craig L Hanis5, Ruth J F Loos4, Neil Schneiderman15, Jerome I Rotter10, Robert C Kaplan1,16, Qibin Qi17. 1. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY. 2. Department of Biostatistics, University of Washington, Seattle, WA. 3. Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA. 4. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. 5. Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX. 6. Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA. 7. National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD. 8. Graduate School of Public Health, San Diego State University, San Diego, CA. 9. Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. 10. Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA. 11. Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL. 12. Department of Biostatistics and Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, NC. 13. Department of Biomedical and Nutritional Sciences, University of Massachusetts Lowell, Lowell, MA. 14. IMDEA Food Institute, Campus de Excelencia Internacional Universidad Autónoma de Madrid-Consejo Superior de Investigaciones Científicas, Madrid, Spain. 15. Department of Psychology, University of Miami, Miami, FL. 16. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA. 17. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY qibin.qi@einstein.yu.edu.
Abstract
OBJECTIVE: We aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries. RESEARCH DESIGN AND METHODS: We conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies. RESULTS: Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28). CONCLUSIONS: This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.
OBJECTIVE: We aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries. RESEARCH DESIGN AND METHODS: We conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies. RESULTS: Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28). CONCLUSIONS: This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.
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