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发现影响糖尿病相关血清生物标志物的编码基因变异及其对2型糖尿病风险的影响。

Discovery of coding genetic variants influencing diabetes-related serum biomarkers and their impact on risk of type 2 diabetes.

作者信息

Ahluwalia Tarunveer Singh, Allin Kristine Højgaard, Sandholt Camilla Helene, Sparsø Thomas Hempel, Jørgensen Marit Eika, Rowe Michael, Christensen Cramer, Brandslund Ivan, Lauritzen Torsten, Linneberg Allan, Husemoen Lise Lotte, Jørgensen Torben, Hansen Torben, Grarup Niels, Pedersen Oluf

机构信息

Novo Nordisk Foundation Center for Basic Metabolic Research (T.S.A., K.H.A., C.H.S., T.H.A., T.H., N.G., O.P.), Section of Metabolic Genetics, Faculty of Health and Medical Sciences, Department of Clinical Medicine (A.L.), Faculty of Health and Medical Sciences, and Institute of Public Health (T.J.), University of Copenhagen, 2100 Copenhagen, Denmark; Copenhagen Prospective Studies on Asthma in Childhood (T.S.A.), Faculty of Health and Medical Sciences, University of Copenhagen, 2820 Copenhagen, Denmark; The Danish Paediatric Asthma Center (T.S.A.), Gentofte Hospital, The Capital Region, 2820 Copenhagen, Denmark; Steno Diabetes Center (E.J.), 2820 Gentofte, Denmark; Tethys Bioscience Inc (M.R.), Emeryville, California 94608; Departments of Internal Medicine and Endocrinology (C.C.) and Clinical Biochemistry (I.B.), Vejle Hospital, 7100 Vejle, Denmark; Institute of Regional Health Research (I.B.), and Faculty of Health Sciences (T.H.), University of Southern Denmark, 5230 Odense, Denmark; Department of General Practice (T.L.), Aarhus University, 8000 C Aarhus, Denmark; Research Centre for Prevention and Health (A.L., L.L.H., T.J.), The Capital Region of Denmark, Copenhagen, Denmark; Department of Clinical Experimental Research (A.L.), Glostrup University Hospital, 2600 Glostrup, Denmark; and Faculty of Medicine (T.J.), University of Aalborg, 9220 Aalborg, Denmark.

出版信息

J Clin Endocrinol Metab. 2015 Apr;100(4):E664-71. doi: 10.1210/jc.2014-3677. Epub 2015 Jan 19.

DOI:10.1210/jc.2014-3677
PMID:25599387
Abstract

CONTEXT

Type 2 diabetes (T2D) prevalence is spiraling globally, and knowledge of its pathophysiological signatures is crucial for a better understanding and treatment of the disease.

OBJECTIVE

We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin.

DESIGN AND PARTICIPANTS

A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single-nucleotide polymorphisms and were tested for association with each biomarker. Identified loci were tested for association with T2D through a large-scale meta-analysis involving up to 17 024 T2D cases and up to 64 186 controls.

RESULTS

We discovered 11 associations between single-nucleotide polymorphisms and five distinct biomarkers at a study-wide P < 3.4 × 10(-7). Nine associations were novel: IL18: BIRC6, RAD17, MARVELD2; ferritin: F5; IGF binding protein 1: SERPING1, KLKB, GCKR, CELSR2, and heat shock 70-kDa protein 1B: CFH. Three of the identified loci (CELSR2, HNF1A, and GCKR) were significantly associated with T2D, of which the association with the CELSR2 locus has not been shown previously.

CONCLUSION

The identified loci influence processes related to insulin signaling, cell communication, immune function, apoptosis, DNA repair, and oxidative stress, all of which could provide a rationale for novel diabetes therapeutic strategies.

摘要

背景

2型糖尿病(T2D)在全球的患病率呈螺旋式上升,了解其病理生理特征对于更好地理解和治疗该疾病至关重要。

目的

我们旨在发现影响与T2D相关的九种生物标志物空腹血清水平的潜在编码基因变异:脂联素、C反应蛋白、铁蛋白、热休克70 kDa蛋白1B、胰岛素样生长因子结合蛋白1和胰岛素样生长因子结合蛋白2、白细胞介素-18、白细胞介素-2受体α和瘦素。

设计与参与者

对6215名丹麦成年人的人群样本进行了16340个编码单核苷酸多态性的基因分型,并检测了与每种生物标志物的关联。通过一项大规模荟萃分析,对多达17024例T2D病例和多达64186例对照进行了鉴定位点与T2D关联的检测。

结果

我们在全研究范围内P<3.4×10⁻⁷时发现了单核苷酸多态性与五种不同生物标志物之间的11种关联。九种关联是新发现的:白细胞介素-18:BIRC6、RAD17、MARVELD2;铁蛋白:F5;胰岛素样生长因子结合蛋白1:SERPING1、KLKB、GCKR、CELSR2;以及热休克70 kDa蛋白1B:CFH。鉴定出的三个位点(CELSR2、HNF1A和GCKR)与T2D显著相关,其中与CELSR2位点的关联此前未被报道。

结论

鉴定出的位点影响与胰岛素信号传导、细胞通讯、免疫功能、细胞凋亡、DNA修复和氧化应激相关的过程,所有这些都可为新型糖尿病治疗策略提供理论依据。

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