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作者

Hou H Xu X Sun F Zhang X Dong H Wang L Ge S An K Sun Q Li Y Cao W Song M Hu S Xing W Wang W

作者单位

Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. School of Medical and Health Sciences, Edith Cowan University, Perth, Australia. Search for more papers by this author Clinical Laboratory, Lianyungang Municipal Oriental Hospital, Lianyungang, China. Search for more papers by this author School of Public Health, Taishan Medical University, Taian, China. * These authors contributed equally to this work. Search for more papers by this author and Address correspondence to: Youxin Wang, PhD, Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Youanmen Xitoutiao, Beijing 100069, China E-mail Address: wangy@ccmu.edu.cn Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. Search for more papers by this author Department of Bioinformatics, School of Medical Informatics, Xuzhou Medical University, Xuzhou, China. Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, School of Pharmacy, Xuzhou Medical University, Xuzhou, China. Search for more papers by this author Beijing Neurosurgical Institute, Capital Medical University, Beijing, China. Search for more papers by this author School of Public Health, Taishan Medical University, Taian, China. Search for more papers by this author School of Public Health, Taishan Medical University, Taian, China. Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. School of Medical and Health Sciences, Edith Cowan University, Perth, Australia. Search for more papers by this author Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China. Search for more papers by this author Taishan Hospital of Shandong Province, Taian, China. Search for more papers by this author Taishan Hospital of Shandong Province, Taian, China. * These authors contributed equally to this work. Search for more papers by this author com School of Public Health, Taishan Medical University, Taian, China. Search for more papers by this author Dong Li, PhD, School of Public Health, Taishan Medical University, 619 Changcheng Road, Taian 271000, China E-mail Address: tsmcdongli@16

刊名

Omics: A Journal Of Integrative Biology

年份

2019

卷号

Vol.23 No.12

页码

660-667

ISSN

1557-8100

关键词

glycan biomarkers glycan diagnostics glycosylation hyperuricemia personalized medicine public health

摘要

The increasing prevalence of hyperuricemia has been recognized as an emerging public health concern in both developed and developing countries. Hyperuricemia is a metabolic condition characterized by an elevated serum uric acid, and associated with renal damage, diabetes, autoimmune disorders, and cardiovascular diseases. Although human genetic variation has been recognized as a factor, posttranslational cellular processes and glycan biomarkers have not been studied extensively for susceptibilit...更多

The increasing prevalence of hyperuricemia has been recognized as an emerging public health concern in both developed and developing countries. Hyperuricemia is a metabolic condition characterized by an elevated serum uric acid, and associated with renal damage, diabetes, autoimmune disorders, and cardiovascular diseases. Although human genetic variation has been recognized as a factor, posttranslational cellular processes and glycan biomarkers have not been studied extensively for susceptibility to hyperuricemia. We evaluated whether immunoglobulin G N-glycans play a role in hyperuricemia in the general population. This cross-sectional study enrolled 635 participants , ages ≥18 years, from a community-based population in Beijing, China. The IgG N-glycan composition of serum was analyzed by an ultraperformance liquid chromatography method. The prevalence of hyperuricemia observed in this sample was 5.98% . Serum uric acid level was positively correlated with glycan peaks 1, GP2, GP4, GP6, GP10, and GP11, whereas it was negatively correlated with GP12, GP13, GP14, GP15, GP18, and GP20. The combination of GP9, GP10, body mass index, and gender distinguished individuals with hyperuricemia from subjects without hyperuricemia, with an area under the curve value of 0.849 . These findings collectively suggest a possible link between hyperuricemia and IgG N-glycans, which might be potentially mediated through inflammation-related mechanisms. Additional research on glycan biomarkers in independent and community-based population samples might allow the development of glycan diagnostics for hyperuricemia and gout in the future.收起

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