Volume 36 Issue 5
May  2023
Turn off MathJax
Article Contents

WANG Bi Yan, SONG Man Shu, ZHANG Jie, MENG Xiao Ni, XING Wei Jia, WANG You Xin. A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke[J]. Biomedical and Environmental Sciences, 2023, 36(5): 389-396. doi: 10.3967/bes2023.048
Citation: WANG Bi Yan, SONG Man Shu, ZHANG Jie, MENG Xiao Ni, XING Wei Jia, WANG You Xin. A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke[J]. Biomedical and Environmental Sciences, 2023, 36(5): 389-396. doi: 10.3967/bes2023.048

A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke

doi: 10.3967/bes2023.048
Funds:  The study was supported by grants from the National Natural Science Foundation of China [No.81673247, 81872682, and 81903401]
More Information
  • Author Bio:

    WANG Bi Yan, female, born in 1997, MS, majoring in molecular epidemiology

    SONG Man Shu, female, born in 1975, PhD, majoring in molecular epidemiology and glycomic biomarkers

  • Corresponding author: WANG You Xin, PhD, Professor, Tel/Fax: 86-10-83911779; E-mail: wangy@ccmu.edu.cn; XING Wei Jia, PhD, Professor, E-mail: xingweijia@hotmail.com
  • WANG You Xin and XING Wei Jia conceptualized the study. WANG Bi Yan, SONG Man Shu, ZHANG Jie, and MENG Xiao Ni conducted the experiments on IgG N-glycome analysis, analyzed the data and drafted the manuscript. BW and WX recruited the participants and collected the demographic and clinical information. WANG You Xin, SONG Man Shu, and XING Wei Jia critically revised the manuscript.
  • The study was approved by the Ethics Committee of Capital Medical University, China, and abided by the principles of the Declaration of Helsinki. All voluntary participants provided written informed consent before taking part in this study.
  • &These authors contributed equally to this work.
  • Received Date: 2022-11-28
  • Accepted Date: 2023-01-09
  •   Objective  This study prospectively investigates the association between immunoglobulin G (IgG) N-glycan traits and ischemic stroke (IS) risk.  Methods  A nested case-control study was conducted in the China suboptimal health cohort study, which recruited 4,313 individuals in 2013–2014. Cases were identified as patients diagnosed with IS, and controls were 1:1 matched by age and sex with cases. IgG N-glycans in baseline plasma samples were analyzed.  Results  A total of 99 IS cases and 99 controls were included, and 24 directly measured glycan peaks (GPs) were separated from IgG N-glycans. In directly measured GPs, GP4, GP9, GP21, GP22, GP23, and GP24 were associated with the risk of IS in men after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia. Derived glycan traits representing decreased galactosylation and sialylation were associated with IS in men (FBG2S2/(FBG2 + FBG2S1 + FBG2S2): odds ratio (OR) = 0.92, 95% confidence interval (CI): 0.87–0.97; G1n: OR = 0.74, 95% CI: 0.63–0.87; G0n: OR = 1.12, 95% CI: 1.03–1.22). However, these associations were not found among women.  Conclusion  This study validated that altered IgG N-glycan traits were associated with incident IS in men, suggesting that sex discrepancies might exist in these associations.
  • WANG You Xin and XING Wei Jia conceptualized the study. WANG Bi Yan, SONG Man Shu, ZHANG Jie, and MENG Xiao Ni conducted the experiments on IgG N-glycome analysis, analyzed the data and drafted the manuscript. BW and WX recruited the participants and collected the demographic and clinical information. WANG You Xin, SONG Man Shu, and XING Wei Jia critically revised the manuscript.
    The study was approved by the Ethics Committee of Capital Medical University, China, and abided by the principles of the Declaration of Helsinki. All voluntary participants provided written informed consent before taking part in this study.
    &These authors contributed equally to this work.
  • 加载中
  • [1] GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet, 2020; 396, 1204−22. doi:  10.1016/S0140-6736(20)30925-9
    [2] Hankey GJ. Stroke. Lancet, 2017; 389, 641−54. doi:  10.1016/S0140-6736(16)30962-X
    [3] Wang YJ, Li ZX, Gu HQ, et al. China Stroke Statistics: an update on the 2019 report from the National Center for Healthcare Quality Management in Neurological Diseases, China National Clinical Research Center for Neurological Diseases, the Chinese Stroke Association, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention and Institute for Global Neuroscience and Stroke Collaborations. Stroke Vasc Neurol, 2022; 7, 415−50. doi:  10.1136/svn-2021-001374
    [4] Cuenca-López MD, Brea D, Segura T, et al. [Inflammation as a therapeutic agent in cerebral infarction: cellular inflammatory response and inflammatory mediators]. Rev Neurol, 2010; 50, 349−59.
    [5] Rudd PM, Wormald MR, Dwek RA. Glycosylation and the immune system. J Protein Chem, 1998; 17, 519.
    [6] Kronimus Y, Dodel R, Galuska SP, et al. IgG Fc N-glycosylation: alterations in neurologic diseases and potential therapeutic target? J Autoimmun, 2019; 96, 14-23.
    [7] Anthony RM, Wermeling F, Ravetch JV. Novel roles for the IgG Fc glycan. Ann N Y Acad Sci, 2012; 1253, 170−80. doi:  10.1111/j.1749-6632.2011.06305.x
    [8] Russell A, Adua E, Ugrina I, et al. Unravelling immunoglobulin G Fc N-glycosylation: a dynamic marker potentiating predictive, preventive and personalised medicine. Int J Mol Sci, 2018; 19, 390. doi:  10.3390/ijms19020390
    [9] Varki A. Biological roles of glycans. Glycobiology, 2017; 27, 3−49. doi:  10.1093/glycob/cww086
    [10] Krištić J, Zaytseva OO, Ram R, et al. Profiling and genetic control of the murine immunoglobulin G glycome. Nat Chem Biol, 2018; 14, 516−24. doi:  10.1038/s41589-018-0034-3
    [11] Zaytseva OO, Seeling M, Krištić J, et al. Fc-linked IgG N-glycosylation in FcγR knock-out mice. Front Cell Dev Biol, 2020; 8, 67. doi:  10.3389/fcell.2020.00067
    [12] Klarić L, Tsepilov YA, Stanton CM, et al. Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases. Sci Adv, 2020; 6, eaax0301. doi:  10.1126/sciadv.aax0301
    [13] Knezević A, Polašek O, Gornik O, et al. Variability, heritability and environmental determinants of human plasma N-glycome. J Proteome Res, 2009; 8, 694−701. doi:  10.1021/pr800737u
    [14] Novokmet M, Lukić E, Vučković F, et al. Changes in IgG and total plasma protein glycomes in acute systemic inflammation. Sci Rep, 2014; 4, 4347. doi:  10.1038/srep04347
    [15] Liu D, Zhao ZY, Wang AX, et al. Ischemic stroke is associated with the pro-inflammatory potential of N-glycosylated immunoglobulin G. J Neuroinflammation, 2018; 15, 123. doi:  10.1186/s12974-018-1161-1
    [16] Liu D, Li Q, Dong J, et al. The association between normal BMI with central adiposity and proinflammatory potential immunoglobulin G N-glycosylation. Diabetes Metab Syndr Obes, 2019; 12, 2373−85. doi:  10.2147/DMSO.S216318
    [17] Greto VL, Cvetko A, Štambuk T, et al. Extensive weight loss reduces glycan age by altering IgG N-glycosylation. Int J Obes (Lond), 2021; 45, 1521−31. doi:  10.1038/s41366-021-00816-3
    [18] Gao Q, Dolikun M, Štambuk J, et al. Immunoglobulin G N-glycans as potential postgenomic biomarkers for hypertension in the Kazakh population. OMICS, 2017; 21, 380−9. doi:  10.1089/omi.2017.0044
    [19] Wang YX, Klarić L, Yu XW, et al. The association between glycosylation of immunoglobulin g and hypertension: a multiple ethnic cross-sectional study. Medicine (Baltimore), 2016; 95, e3379. doi:  10.1097/MD.0000000000003379
    [20] Lemmers RFH, Vilaj M, Urda D, et al. IgG glycan patterns are associated with type 2 diabetes in independent European populations. Biochim Biophys Acta Gen Subj, 2017; 1861, 2240−9. doi:  10.1016/j.bbagen.2017.06.020
    [21] Liu D, Chu X, Wang H, et al. The changes of immunoglobulin G N-glycosylation in blood lipids and dyslipidaemia. J Transl Med, 2018; 16, 235. doi:  10.1186/s12967-018-1616-2
    [22] Cvetko A, Kifer D, Gornik O, et al. Glycosylation alterations in multiple sclerosis show increased proinflammatory potential. Biomedicines, 2020; 8, 410. doi:  10.3390/biomedicines8100410
    [23] Ząbczyńska M, Link-Lenczowski P, Novokmet M, et al. Altered N-glycan profile of IgG-depleted serum proteins in Hashimoto's thyroiditis. Biochim Biophys Acta Gen Subj, 2020; 1864, 129464. doi:  10.1016/j.bbagen.2019.129464
    [24] Sun Y, Wang YX, Zhang J, et al. Comparison of gender specific structure profiles of immunoglobulin G N-glycans. Chin J Epidemiol, 2016; 37, 1409−12. (In Chinese
    [25] Krištić J, Vučković F, Menni C, et al. Glycans are a novel biomarker of chronological and biological ages. J Gerontol A Biol Sci Med Sci, 2014; 69, 779−89. doi:  10.1093/gerona/glt190
    [26] Ercan A, Kohrt WM, Cui J, et al. Estrogens regulate glycosylation of IgG in women and men. JCI Insight, 2017; 2, e89703.
    [27] Wang YX, Ge SQ, Yan YX, et al. China suboptimal health cohort study: rationale, design and baseline characteristics. J Transl Med, 2016; 14, 291. doi:  10.1186/s12967-016-1046-y
    [28] World Health Organization. Recommendations on stroke prevention, diagnosis, and therapy. Report of the WHO Task Force on Stroke and other Cerebrovascular Disorders. Stroke, 1989; 20, 1407−31. doi:  10.1161/01.STR.20.10.1407
    [29] Haslam DW, James WPT. Obesity. Lancet, 2005; 366, 1197−1209. doi:  10.1016/S0140-6736(05)67483-1
    [30] Yu CZ, Wang J, Li YR, et al. Exposure to the Chinese famine in early life and hypertension prevalence risk in adults. J Hypertens, 2017; 35, 63−8. doi:  10.1097/HJH.0000000000001122
    [31] Wang S, Xu L, Jonas JB, et al. Prevalence and associated factors of dyslipidemia in the adult Chinese population. PLoS One, 2011; 6, e17326. doi:  10.1371/journal.pone.0017326
    [32] John M Cruickshank. Follow-up of intensive glucose control in type 2 diabetes. N Engl J Med, 2009; 360, 417−8.
    [33] Liu D, Xu XZ, Li YJ, et al. Immunoglobulin G N-glycan analysis by ultra-performance liquid chromatography. J Vis Exp,doi:  10.3791/60104.
    [34] Meng XN, Song MS, Vilaj M, et al. Glycosylation of IgG Associates with hypertension and type 2 diabetes mellitus comorbidity in the Chinese Muslim ethnic minorities and the Han Chinese. J Pers Med, 2021; 11, 614. doi:  10.3390/jpm11070614
    [35] Trbojević-Akmačić I, Vilaj M, Lauc G. High-throughput analysis of immunoglobulin G glycosylation. Expert Rev Proteomics, 2016; 13, 523−34. doi:  10.1080/14789450.2016.1174584
    [36] Pučić-Baković M. High-throughput analysis of the IgG N-Glycome by UPLC-FLR. In: Lauc G, Wuhrer M. High-Throughput Glycomics and Glycoproteomics. Humana Press. 2017, 21-29.
    [37] Pučić M, Knežević A, Vidič J, et al. High throughput isolation and glycosylation analysis of IgG-variability and heritability of the IgG glycome in three isolated human populations. Mol Cell Proteomics, 2011; 10, M111.010090. doi:  10.1074/mcp.M111.010090
    [38] Wu GY, Wan X, Xu BH. A new estimation of protein-level false discovery rate. BMC Genomics, 2018; 19, 567. doi:  10.1186/s12864-018-4923-3
    [39] Peng CY, Manz BD, Keck J. Modeling categorical variables by logistic regression. Am J Health Behav, 2001; 25, 278−84. doi:  10.5993/AJHB.25.3.15
    [40] Witten DM, Tibshirani R. Covariance-regularized regression and classification for high dimensional problems. J Roy Stat Soc Series B Stat Methodol, 2009; 71, 615−36. doi:  10.1111/j.1467-9868.2009.00699.x
    [41] Ding N, Nie H, Sun XM, et al. Human serum N-glycan profiles are age and sex dependent. Age Ageing, 2011; 40, 568−75. doi:  10.1093/ageing/afr084
    [42] Wittenbecher C, Štambuk T, Kuxhaus O, et al. Plasma N-Glycans as emerging biomarkers of cardiometabolic risk: a prospective investigation in the EPIC-potsdam cohort study. Diabetes Care, 2020; 43, 661−8. doi:  10.2337/dc19-1507
    [43] Štambuk T, Klasić M, Zoldoš V, et al. N-glycans as functional effectors of genetic and epigenetic disease risk. Mol Aspects Med, 2021; 79, 100891. doi:  10.1016/j.mam.2020.100891
    [44] Vilar-Bergua A, Riba-Llena I, Vanhooren V, et al. N-glycome profile levels relate to silent brain infarcts in a cohort of hypertensives. J Am Heart Assoc, 2015; 4, e002669. doi:  10.1161/JAHA.115.002669
    [45] Menni C, Gudelj I, Macdonald-Dunlop E, et al. Glycosylation profile of immunoglobulin G is cross-sectionally associated with cardiovascular disease risk score and subclinical atherosclerosis in two independent cohorts. Circ Res, 2018; 122, 1555−64. doi:  10.1161/CIRCRESAHA.117.312174
    [46] Kaneko Y, Nimmerjahn F, Ravetch JV. Anti-inflammatory activity of immunoglobulin G resulting from Fc sialylation. Science, 2006; 313, 670−3. doi:  10.1126/science.1129594
    [47] Nikolac Perkovic M, Pucic Bakovic M, Kristic J, et al. The association between galactosylation of immunoglobulin G and body mass index. Prog Neuropsychopharmacol Biol Psychiatry, 2014; 48, 20−5. doi:  10.1016/j.pnpbp.2013.08.014
    [48] Russell AC, Kepka A, Trbojević-Akmačić I, et al. Increased central adiposity is associated with pro-inflammatory immunoglobulin G N-glycans. Immunobiology, 2019; 224, 110−5. doi:  10.1016/j.imbio.2018.10.002
    [49] Matsumoto A, Shikata K, Takeuchi F, et al. Autoantibody activity of IgG rheumatoid factor increases with decreasing levels of galactosylation and sialylation. J Biochem, 2000; 128, 621−8. doi:  10.1093/oxfordjournals.jbchem.a022794
    [50] Ackerman ME, Crispin M, Yu XJ, et al. Natural variation in Fc glycosylation of HIV-specific antibodies impacts antiviral activity. J Clin Invest, 2013; 123, 2183−92. doi:  10.1172/JCI65708
    [51] Vidarsson G, Dekkers G, Rispens T. IgG subclasses and allotypes: from structure to effector functions. Front Immunol, 2014; 5, 520.
  • 22360+Supplementary Materials.pdf
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(3)  / Tables(9)

Article Metrics

Article views(476) PDF downloads(64) Cited by()

Proportional views
Related

A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke

doi: 10.3967/bes2023.048
Funds:  The study was supported by grants from the National Natural Science Foundation of China [No.81673247, 81872682, and 81903401]
  • Author Bio:

  • Corresponding author: WANG You Xin, PhD, Professor, Tel/Fax: 86-10-83911779; E-mail: wangy@ccmu.edu.cn XING Wei Jia, PhD, Professor, E-mail: xingweijia@hotmail.com
  • WANG You Xin and XING Wei Jia conceptualized the study. WANG Bi Yan, SONG Man Shu, ZHANG Jie, and MENG Xiao Ni conducted the experiments on IgG N-glycome analysis, analyzed the data and drafted the manuscript. BW and WX recruited the participants and collected the demographic and clinical information. WANG You Xin, SONG Man Shu, and XING Wei Jia critically revised the manuscript.
  • The study was approved by the Ethics Committee of Capital Medical University, China, and abided by the principles of the Declaration of Helsinki. All voluntary participants provided written informed consent before taking part in this study.
  • &These authors contributed equally to this work.

Abstract:   Objective  This study prospectively investigates the association between immunoglobulin G (IgG) N-glycan traits and ischemic stroke (IS) risk.  Methods  A nested case-control study was conducted in the China suboptimal health cohort study, which recruited 4,313 individuals in 2013–2014. Cases were identified as patients diagnosed with IS, and controls were 1:1 matched by age and sex with cases. IgG N-glycans in baseline plasma samples were analyzed.  Results  A total of 99 IS cases and 99 controls were included, and 24 directly measured glycan peaks (GPs) were separated from IgG N-glycans. In directly measured GPs, GP4, GP9, GP21, GP22, GP23, and GP24 were associated with the risk of IS in men after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia. Derived glycan traits representing decreased galactosylation and sialylation were associated with IS in men (FBG2S2/(FBG2 + FBG2S1 + FBG2S2): odds ratio (OR) = 0.92, 95% confidence interval (CI): 0.87–0.97; G1n: OR = 0.74, 95% CI: 0.63–0.87; G0n: OR = 1.12, 95% CI: 1.03–1.22). However, these associations were not found among women.  Conclusion  This study validated that altered IgG N-glycan traits were associated with incident IS in men, suggesting that sex discrepancies might exist in these associations.

WANG You Xin and XING Wei Jia conceptualized the study. WANG Bi Yan, SONG Man Shu, ZHANG Jie, and MENG Xiao Ni conducted the experiments on IgG N-glycome analysis, analyzed the data and drafted the manuscript. BW and WX recruited the participants and collected the demographic and clinical information. WANG You Xin, SONG Man Shu, and XING Wei Jia critically revised the manuscript.
The study was approved by the Ethics Committee of Capital Medical University, China, and abided by the principles of the Declaration of Helsinki. All voluntary participants provided written informed consent before taking part in this study.
&These authors contributed equally to this work.
WANG Bi Yan, SONG Man Shu, ZHANG Jie, MENG Xiao Ni, XING Wei Jia, WANG You Xin. A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke[J]. Biomedical and Environmental Sciences, 2023, 36(5): 389-396. doi: 10.3967/bes2023.048
Citation: WANG Bi Yan, SONG Man Shu, ZHANG Jie, MENG Xiao Ni, XING Wei Jia, WANG You Xin. A Nested Case-Control Study to Explore the Association between Immunoglobulin G N-glycans and Ischemic Stroke[J]. Biomedical and Environmental Sciences, 2023, 36(5): 389-396. doi: 10.3967/bes2023.048
    • According to the Global Burden of Diseases 2019 study, stroke has been a leading cause of disability-adjusted life-years (DALYs) lost among the elderly worldwide [1]. Approximately 80% of strokes are ischemic strokes (IS), constituting a major burden on the public health system [2]. In the past 30 years, the crude mortality rate of stroke in China has been rising rapidly, and the age-standardized incidence rate of IS increased by 34.7% [3]. IS is a multifactorial and complex syndrome triggered by a cerebral embolism resulting from the interaction of environmental and genetic factors [4].

      N-glycosylation is a ubiquitous and complexly regulated posttranslational protein modification, with N-glycans covalently linked to asparagine residues in target proteins [5, 6]. N-glycosylation participates in many key biological processes, ranging from protein folding, molecular trafficking and clearance, and cell adhesion to immune regulation [7-9]. Immunoglobulin G (IgG) is one of the most suitable candidates for glycomic research due to its unique structure with conserved N-glycosylation in the Fc domain of IgG [10]. Alterations of N-glycosylation in the Fc domain can affect the structure and function of IgG, which may regulate inflammation and trigger several inflammatory diseases [6, 11, 12]. In addition, N-glycosylation is remarkably stable in healthy individuals and can be modified under specific pathophysiological conditions [13, 14].

      Several studies have reported that IgG N-glycan profiles are associated with IS [15] and its risk factors, such as obesity [16, 17], hypertension [18, 19], type 2 diabetes [20], dyslipidemia [21], and inflammation-related diseases [14, 22, 23]. We recently reported proinflammatory alterations in IgG N-glycan profiles, including decreased sialylation and galactosylation, and increased levels of bisecting N-acetylglucosamine (GlcNAc) are linked to IS. They might be involved in the molecular mechanism of inflammation. However, most previous studies on N-glycans were case-control studies, and thus, the observed altered IgG N-glycosylation may be a consequence rather than a cause of IS. There is no prospective study linking IgG N-glycan profiles to IS.

      In this study, we hypothesized that IgG N-glycan profiles are prospectively associated with IS and may serve as potential candidate biomarkers for incident IS. We examined the associations of IgG N-glycan profiles and IS using a nested case-control study in a prospective cohort. Previous studies have suggested sex-specific differences in IgG N-glycan traits [24, 25], and sex hormones can modulate human IgG N-glycosylation [26]. Given the sex-specific differences in IgG N-glycosylation, we analyzed its stratification in men and women.

    • We conducted a nested case-control study in the China suboptimal health cohort study (COACS), an ongoing longitudinal study starting in 2013 [27]. A detailed description of the COACS cohort has been published elsewhere [27]. In total, 4,313 participants from Tangshan city in northern China completed baseline questionnaires and physical examinations and provided peripheral venous blood samples. IS is a sudden onset focal neurological deficit caused by damage to an area in the central nervous system resulting from decreased or completely blocked blood flow. IS was diagnosed according to the International Classification of Disease (ICD-10) based on clinical symptoms, physical examinations, and evidence from brain X-ray computed tomography (CT) or magnetic resonance imaging (MRI) [28]. By the end of December 13, 2018, we identified 99 new incident IS cases in follow-up investigations. Controls were randomly selected from participants who were free of IS before or at the index date using risk-set sampling and were matched by age and sex with cases. Thus, the present study included 99 incident IS cases and 99 controls.

      All voluntary participants provided written informed consent before participating in this study. The study was approved by the Ethics Committee of Capital Medical University, China, and abided by the principles of the Declaration of Helsinki.

    • After overnight fasting, venipuncture collected blood samples (5 mL) in the morning. Then, whole blood was centrifuged at 3,000 rpm for 10 min, and plasma was separated to detect IgG N-glycan profiles. Blood samples were stored at 4 °C and processed within 8 h. The separated plasma samples were stored at –80 °C until laboratory measurements.

      During the baseline survey, trained interviewers collected information about the demographics (age, sex, ethnicity, and levels of education) and clinical history of all participants. Specialized nurses performed physical examinations to obtain information on height, weight, waist and hip circumference, and blood pressure. Blood lipids [total cholesterol (TC), total triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL)], and glucose [fasting blood glucose (FBG) concentrations] were measured immediately at a certified laboratory. Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared. Obesity was defined as BMI > 28.0 kg/m[29]. Hypertension was defined as mean systolic blood pressure (SBP) ≥ 140 mmHg or mean diastolic blood pressure (DBP) ≥ 90 mmHg [30]. The participants were classified as having dyslipidemia with TC ≥ 6.2 mmol/L, TGs ≥ 2.3 mmol/L, HDL < 1.0 mmol/L, and LDL ≥ 4.1 mmol/L, according to the Guidelines for the Prevention and Treatment of Dyslipidemia of adults in China [31]. The participants were diagnosed with T2D by physicians according to the 1999 WHO Criteria (FBG ≥ 7.0 mmol/L) [32].

    • IgG N-glycan traits were separated into 24 glycan peaks (GP1–GP24) by Ultra-Performance Liquid Chromatography (UPLC, Water, USA) in our laboratory, according to standard operating procedures described in our previous publications [16, 21, 33, 34]. First, 50 μL of plasma was diluted 10× with binding buffer (1× phosphate-buffered saline, pH  =  7.4) and applied to washed and equilibrated 96-well protein G plates (Water, USA), followed by the immediate washing of protein G plates. Then, 0.1 mol/L formic acid (Sigma Aldrich, USA) and 1 mol/L ammonium bicarbonate (BBI Life Science, China) were used to elute and neutralize IgG, respectively. Samples of IgG were denatured with sodium dodecyl sulfate (SDS, Sigma Aldrich, USA) at 65 °C for 10 minutes. IgG N-glycans were then released with N-glycosidase F (Roche, Germany) and incubated overnight at 37 °C. Next, IgG N-glycans were labeled with mixtures of 2-aminobenzamide (Sigma Aldrich, USA), dimethylsulfoxide (Sigma Aldrich, USA), glacial acetic acid (Merck, Germany), and 2-picoline borane (Sigma Aldrich, USA) to make them visible by UPLC. Finally, 24 GPs were separated from IgG N-glycans by hydrophilic interaction chromatography-UPLC on a Waters BEH Glycan chromatography column. The glycan structures corresponding to each glycan peak are described in Supplementary Table S1 (available in www.besjournal.com) [35, 36]. Each batch (96-well plates) included standard samples and blanks for quality control.

      Glycan peakStructures of
      glycan peak
      Graphic peak
      composition
      Glycan peakStructures of
      glycan peak
      Graphic peak
      composition
      GP1FA1GP13A2BG2
      GP2A2GP14FA2G2
      GP3A2BGP15FA2BG2
      GP4FA2GP16FA2G1S1
      GP5M5GP17A2G2S1
      GP6FA2BGP18FA2G2S1
      GP7A2G1GP19FA2BG2S1
      GP8FA2[6]G1GP20FA2FG2S1
      GP9FA2[3]G1GP21A2G2S2
      GP10FA2[6]BG1GP22A2BG2S2
      GP11FA2[3]BG1GP23FA2G2S2
      GP12A2G2GP24FA2BG2S2
        Note. UPLC, ultra-performance liquid chromatography; IgG, immunoglobulin G; GP, glycan peaks; F, represents a fucose attached to core N-acetylglucosamine; M, represents mannoses attached to core N-acetylglucosamine; A, represents N-acetylglucosamine attached to core triple mannose; B, represents bisected N-acetylglucosamine linked to core triple mannose; G, represents galactose; [3]G1 and [6]G1 represent galactose attached to α1–3 and α1–6 mannose respectively; S represents N-acetylneuraminic acid attached to galactose; blue square represents N-acetylglucosamine; red triangle represents fucose; green circle represents mannose; yellow circle represents galactose; purple square represents N-acetylneuraminic acid.

      Table S1.  Description of structures for UPLC results of IgG glycan peaks

      All chromatograms were divided similarly into 24 peaks, and the number of glycans in each peak was expressed as a percentage of the total integrated area. In addition, 54 derived glycan traits (DGs) were calculated from 24 directly measured glycan peaks to describe the relative abundances of galactosylation, sialylation, GlcNAc, and core fucosylation [37]. Detailed information on the derived glycan traits is presented in Supplementary Table S2 (available in www.besjournal.com). Normalization of UPLC data was performed as described previously [35].

      Derived glycan traitsStructures of derived glycan traitsCalculation formula
      FGS / (FG + FGS)Sialylation of fucosylated galactosylated structures without bisecting GlcNAcSUM (GP16 + GP18 + GP23) / SUM (GP16 + GP18 + GP23 + GP8 + GP9 + GP14) × 100
      FBGS / (FBG + FBGS)Sialylation of fucosylated galactosylated structures with bisecting GlcNAcSUM (GP19 + GP24) / SUM (GP19 + GP24 + GP10 + GP11 + GP15) × 100
      FGS / (F + FG + FGS)Sialylation of all fucosylated structures without bisecting GlcNAcSUM (GP16 + GP18 + GP23) / SUM (GP16 + GP18 + GP23 + GP4 + GP8 + GP9 + GP14) × 100
      FBGS / (FB + FBG + FBGS)Sialylation of all fucosylated structures with bisecting GlcNAcSUM (GP19 + GP24) / SUM (GP19 + GP24 + GP6 + GP10 + GP11 + GP15) × 100
      FG1S1 / (FG1 + FG1S1)Monosialylation of fucosylated monogalactosylated structuresGP16 / SUM (GP16 + GP8 + GP9) × 100
      FG2S1 / (FG2 + FG2S1 + FG2S2)Monosialylation of fucosylated digalactosylated structuresGP18 / SUM (GP18 + GP14 + GP23) × 100
      FG2S2 / (FG2 + FG2S1 + FG2S2)Disialylation of fucosylated digalactosylated structuresGP23 / SUM (GP23 + GP14 + GP18) × 100
      FBG2S1 / (FBG2 + FBG2S1 + FBG2S2)Monosialylation of fucosylated digalactosylated structures with bisecting GlcNAcGP19 / SUM (GP19 + GP15 + GP24) × 100
      FBG2S2 / (FBG2 + FBG2S1 + FBG2S2)Disialylation of fucosylated digalactosylated structures with bisecting GlcNAcGP24 / SUM (GP24 + GP15 + GP19) × 100
      FtotalS1 / FtotalS2Ratio of all fucosylated monosialylated and disialylated structuresSUM (GP16 + GP18 + GP19) / SUM (GP23 + GP24)
      FS1 / FS2Ratio of fucosylated (without bisecting GlcNAc) monosialylated and disialylated structuresSUM (GP16 + GP18) / GP23
      FBS1 / FBS2Ratio of fucosylated (with bisecting GlcNAc) monosialylated and disialylated structuresGP19 / GP24
      FBStotal / FStotalRatio of all fucosylated sialylated structures with and without bisecting GlcNAcSUM (GP19 + GP24) / SUM (GP16 + GP18 + GP23)
      FBS1 / FS1Fucosylated monosialylated structures with and without bisecting GlcNAcGP19 / SUM (GP16 + GP18)
      FBS1 / (FS1 + FBS1)Bisecting GlcNAc in all fucosylated monosialylated structuresGP19 / SUM (GP16 + GP18 + GP19)
      FBS2 / FS2Ratio of fucosylated disialylated structures with and without bisecting GlcNAcGP24 / GP23
      FBS2 / (FS2 + FBS2)Bisecting GlcNAc in all fucosylated disialylated structuresGP24 / SUM (GP23 + GP24)
      GP1nGP1 in total neutral glycan fractionGP1 / GPn × 100
      GP2nGP2 in total neutral glycan fractionGP2 / GPn × 100
      GP4nGP4 in total neutral glycan fractionGP4 / GPn × 100
      GP5nGP5 in total neutral glycan fractionGP5 / GPn × 100
      GP6nGP6 in total neutral glycan fractionGP6 / GPn × 100
      GP7nGP7 in total neutral glycan fractionGP7 / GPn × 100
      GP8nGP8 in total neutral glycan fractionGP8 / GPn × 100
      GP9nGP9 in total neutral glycan fractionGP9 / GPn × 100
      GP10nGP10 in total neutral glycan fractionGP10 / GPn × 100
      GP11nGP11 in total neutral glycan fractionGP11 / GPn × 100
      GP12nGP12 in total neutral glycan fractionGP12 / GPn × 100
      GP13nGP13 in total neutral glycan fractionGP13 / GPn × 100
      GP14nGP14 in total neutral glycan fractionGP14 / GPn × 100
      GP15nGP15 in total neutral glycan fractionGP15 / GPn × 100
      G0nG0 in total neutral glycan fractionSUM (GP1n: GP4n + GP6n)
      G1nG1 in total neutral glycan fractionSUM (GP7n: GP11n)
      G2nG2 in total neutral glycan fractionSUM (GP12n: GP15n)
      Fn totalAll fucosylated structures in total neutral glycan fractionSUM (GP1n + GP4n + GP6n + GP8n + GP9n + GP10n + GP11n + GP14n + GP15n)
      FG0n total / G0nFucosylation in agalactosylated structuresSUM (GP1n + GP4n + GP6n) / G0n × 100
      FG1n total / G1nFucosylation in monogalactosylated structuresSUM (GP8n + GP9n + GP10n + GP11n) / G1n × 100
      FG2n total / G2nFucosylation in digalactosylated structuresSUM (GP14n + GP15) / G2n × 100
      FnFucosylation (without bisecting GlcNAc) in total neutral glycan fractionSUM (GP1n + GP4n + GP8n + GP9n + GP14n)
      FG0n / G0nFucosylation (without bisecting GlcNAc) in agalactosylated structuresSUM (GP1n + GP4n) / G0n × 100
      FG1n / G1nFucosylation (without bisecting GlcNAc) in monogalactosylated structuresSUM (GP8n + GP9n) / G1n × 100
      FG2n / G2nFucosylation (without bisecting GlcNAc) in digalactosylated structuresGP14n / G2n × 100
      FBnFucosylation (with bisecting GlcNAc) structures in total neutral glycan fractionSUM (GP6n + GP10n + GP11n + GP15n)
      FBG0n / G0nFucosylation (with bisecting GlcNAc) of agalactosylated structuresGP6n/ G0n × 100
      FBG1n / G1nFucosylation (with bisecting GlcNAc) of monogalactosylated structuresSUM (GP10n + GP11n) / G1n × 100
      FBG2n / G2nFucosylation (with bisecting GlcNAc) of digalactosylated structuresGP15n / G2n × 100
      FBn / FnRatio of fucosylated structures with and without bisecting GlcNAcFBn / Fn × 100
      FBn / Fn totalBisecting GlcNAc in all fucosylated structures in total neutral glycan fractionFBn / Fn total × 100
      Fn / (Bn + FBn)Ratio of fucosylated non–bisecting GlcNAc structures and all structures with bisecting GlcNAcFn / (GP13n + FBn)
      Bn / (Fn + FBn)Ratio of structures with bisecting GlcNAc and all fucosylated structures (with and without bisecting GlcNAc)GP13n / (Fn + FBn) × 1,000
      FBG2n / FG2nRatio of fucosylated digalactosylated structures with and without bisecting GlcNAcGP15n / GP14n
      FBG2n / (FG2n + FBG2n)Bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral glycan fractionGP15n / (GP14n + GP15n) × 100
      FG2n / (BG2n + FBG2n)Fucosylated digalactosylated without bisecting GlcNAc structures in all digalactosylated structuresGP14n / (GP13n + GP15n)
      BG2n / (FG2n + FBG2n)Digalactosylated structures with bisecting GlcNAc in all fucosylated digalactosylated structures (with and without bisecting GlcNAc)GP13n / (GP14n + GP15n) × 1,000
        Note. F, a fucose attached to core N-acetylglucosamine; B, bisected N-acetylglucosamine linked to core triple mannose; G, galactose; S, N-acetylneuraminic acid attached to galactose; n, neutral glycans.

      Table S2.  Description of structures and calculation formula of derived glycan traits

    • Baseline characteristics are presented as the median (25th–75th percentile) for continuous variables, whereas categorical variables are expressed as n (%). The differences in continuous variables among IS and controls were compared by a t-test or Mann-Whitney U test, and categorical variables were tested by a chi-square test or Fisher’s exact test. Multiple logistic regression analyses were performed to identify the associations of 24 directly measured glycan peaks and 54 derived glycan traits with IS after adjusting for confounding factors, such as obesity, age, waist and hip circumference, diabetes, hypertension, and dyslipidemia. For multiple corrections, the false discovery rate (FDR) was controlled using the Benjamini–Hochberg procedure (q) [38]. The potential internal associations among IgG N-glycan traits could induce multicollinearity. Therefore, ridge, stepwise, and the least absolute shrinkage and selection operator (LASSO) based on logistic regression were performed to reduce the dimension of the feature set [39, 40]. Fivefold cross-validation was used to evaluate the performance of the discriminant models. The false discrimination rates were used to compare the methods of dimension reduction. All analyses were performed with R (version 4.0.2, The R Foundation for Statistical Computing, Vienna, Austria) and SPSS Statistics (version 25.0, Chicago, IL, USA).

    • In total, 99 patients with incident IS and 99 matched controls were included in the nested case-control study. The baseline demographic and biochemical characteristics between IS patients and controls stratified by sex are shown in Table 1. Among male IS patients, waistline, BMI, SBP, DBP, TG, LDL, and TC were significantly higher than in the control group. In contrast, SBP and DBP were significantly higher than those in the control group among female IS patients.

      ParametersMenWomen
      Incident IS (n = 58)Control (n = 58)PIncident IS (n = 41)Control (n = 41)P
      Age (years)59 (47–61)52 (40–62)0.05757 (48–61)59 (54–62)0.108
      Waistline (cm)92.00 (87.00–98.25)88.00 (83.50–92.25)0.00384.00 (80.00–90.00)85.00 (80.00–93.00)0.700
      Hipline (cm)100.00 (96.75–105.00)100.00 (97.00–102.00)0.37799.00 (95.00–103.50)98.00 (96.00–103.00)0.880
      BMI (kg/m2)26.27 (24.51–27.68)25.00 (23.44–26.45)0.02124.61 (23.00–26.49)25.00 (22.83–26.76)0.692
      SBP (mmHg)137.00 (125.00–144.00)123.00 (115.00–130.25)< 0.001133.00 (120.00–147.50)121.00 (111.00–134.00)0.004
      DBP (mmHg)89.00 (83.00–95.25)79.50 (72.75–87.25)< 0.00181.00 (74.50–90.00)74.00 (67.50–82.00)0.007
      FBG (mmHg)5.30 (4.90–5.90)5.20 (4.90–5.81)0.9565.10 (4.90–5.50)5.10 (4.80–5.70)0.662
      TG (mmol/L)1.33 (1.02–1.97)1.14 (0.87–1.55)0.0311.45 (0.95–1.78)1.31 (0.86–1.85)0.813
      LDL (mmol/L)2.58 (2.21–2.99)2.25 (1.81–2.77)0.0232.63 (2.30–3.39)2.65 (2.42–3.11)0.289
      HDL (mmol/L)1.07 (0.93–1.25)1.11 (0.94–1.33)0.3761.31 (1.15–1.43)1.27 (1.17–1.47)0.878
      TC (mmol/L)4.58 (3.99–5.16)4.31 (3.30–4.82)0.0474.89 (4.34–5.78)4.78 (4.33–5.18)0.321
        Note. IS, ischemic stroke; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; TG, total triglycerides; LDL, low-density lipoprotein; HDL, high-density lipoprotein; TC, total cholesterol. Bold type indicates statistical significance.

      Table 1.  Baseline characteristics of study subjects

      When comparing the IgG N-glycome composition, including 24 directly measured GPs between the two groups, we observed significant differences in 7 GPs between IS patients and controls (P < 0.05, q < 0.05) (Supplementary Table S3, available in www.besjournal.com). The representative IgG N-glycan profiles of UPLC results for sex-specific IS patients and controls are shown in Figure 1. In the sex-stratified analysis, the comparisons of GPs and DGs at baseline between the IS and control groups are shown in Supplementary Tables S4S5 (available in www.besjournal.com). Significant differences in 6 GPs and 5 DGs were observed in men after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia (Figure 2, Supplementary Tables S6S7 available in www.besjournal.com). However, the associations of IgG N-glycan profiles and IS were not found among women (P < 0.05, q < 0.05). For the initial GPs, higher GP4 and lower GP9, GP21, GP22, GP23, and GP24 were associated with a higher risk of IS in men (GP4: OR = 1.16, 95% CI: 1.05–1.29; GP9: OR = 0.70, 95% CI: 0.55–0.90; GP21: OR = 0.02, 95% CI: 0.01–0.27; GP22: OR = 0.01, 95% CI: 0.01–0.02; GP23: OR = 0.32, 95% CI: 0.13–0.78; GP24: OR = 0.21, 95% CI: 0.09–0.54) (Figure 2, Supplementary Table S6). Among the derived glycan traits, lower levels of sialylation [FBG2S2/(FBG2 + FBG2S1 + FBG2S2)] and galactosylation (G1n) and higher levels of no galactosylation (G0n) were found in the men IS group [FBG2S2/(FBG2 + FBG2S1 + FBG2S2]: OR = 0.92, 95% CI: 0.87–0.97; G1n: OR = 0.74, 95% CI: 0.63–0.87; G0n: OR = 1.12, 95% CI: 1.03–1.22) (Figure 2, Supplementary Table S7).

      Figure 1.  Ultra-Performance Liquid Chromatography of IS patients and controls in (A) men and (B) women. The profiles of glycan peaks were randomly selected from IS patients and matched controls. The 24 IgG glycan peaks are numbered. The blue line represents IS patients; the black line represents controls. IS, ischemic stroke

      Figure 2.  Odds ratios (OR) and 95% confidence intervals (95% CI) for the associations of IgG N-glycan traits with IS in (A) men and (B) women. Multiple logistic regression analysis was performed after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia. IS, ischemic stroke

      Initial glycansIncident ISControlP*q#
      GP10.09 (0.06–0.16)0.10 (0.06–0.15)0.922890.92289
      GP20.47 (0.32–0.72)0.54 (0.34–0.74)0.296900.41915
      GP30.14 (0.08–0.25)0.14 (0.06–0.24)0.505320.60638
      GP427.91 (24.37–33.50)26.28 (22.06–30.47)0.00538*0.02356#
      GP50.25 (0.18–0.33)0.23 (0.17–0.28)0.293910.41915
      GP65.83 (4.73–6.84)5.27 (4.54–6.39)0.124980.27268
      GP70.23 (0.14–0.39)0.27 (0.16–0.45)0.146700.29340
      GP818.07 (16.66–19.25)18.48 (16.72–20.15)0.353560.47141
      GP98.92 (6.37–9.99)8.51 (7.52–10.29)0.662430.75706
      GP103.86 (3.47–4.71)3.98 (3.39–4.58)0.804090.87719
      GP110.39 (0.27–0.52)0.46 (0.35–0.65)0.01306*0.04478#
      GP120.44 (0.31–0.73)0.56 (0.40–0.83)0.02977*0.07939
      GP130.59 (0.37–0.76)0.60 (0.43–0.83)0.390730.49355
      GP1415.76 (13.06–18.50)13.79 (16.21–18.45)0.209180.35859
      GP151.31 (1.13–1.69)1.36 (1.19–1.65)0.897660.92289
      GP162.51 (2.14–2.99)2.75 (2.40–3.11)0.02277*0.06831
      GP170.62 (0.48–0.76)0.67 (0.53–0.84)0.256410.41026
      GP188.03 (5.87–9.68)8.58 (6.60–10.89)0.075990.18238
      GP191.22 (0.90–1.47)1.44 (1.04–1.73)0.00589*0.02356#
      GP200.07 (0.04–0.10)0.08 (0.05–0.11)0.170330.31446
      GP210.21 (0.12–0.36)0.31 (0.18–0.45)0.00228*0.01368#
      GP220.04 (0.03–0.07)0.08 (0.03–0.14)0.00077*0.00924#
      GP230.59 (0.35–0.98)0.84 (0.53–1.22)0.00195*0.01368#
      GP240.49 (0.32–1.00)0.93 (0.48–1.37)0.00014*0.00336#
        Note. Data were expressed median (25th–75th percentile); IS, ischemic stroke; GP, glycan peaks. *P < 0.05. #q < 0.05: significant after correction for FDR (false discovery rate).

      Table S3.  Initial glycan peaks levels in the whole study population of nested case-control study

      As shown in Supplementary Figure S1 (available in www.besjournal.com), the sex-specific correlation of IgG N-glycan traits indicated possible multicollinearity. GP4, GP9, and GP22 were selected by stepwise regression and ridge regression. In addition, GP4, GP9, GP22, and GP24 were selected by LASSO regression analysis in male participants. The false discrimination rates of the three methods were 0.267, 0.267, and 0.286, respectively (Supplementary Table S8, available in www.besjournal.com). In a confounder-adjusted and combined significant glycan peak logistic regression model, GP4, GP9, and GP22 were still significantly associated with IS in men (Supplementary Table S8).

      Figure S1.  The correlation coefficients of independent IgG N-glycan peaks in (A) men and (B) women. The positive correlations are represented by blue, while negative correlations are represented by red.

      ItemsStepwise regressionRidge regressionLasso regression
      Initial glycan peaks
      GP40.1470.1440.018
      GP9–0.349–0.393–0.047
      GP21
      GP22–18.174–12.879–0.994
      GP23
      GP24–0.172
      False discrimination rates0.2670.2670.286
        Note. GP, glycan peaks; –, the initial glycans were not included in the model.

      Table S8.  Initial glycan peaks after dimension reduction screening and false discrimination rates of 5-fold cross-validation in the three methods

    • In this study, the observational results showed higher levels of GP4 and lower levels of GP9, GP21, GP22, GP23, and GP24 in male patients with IS than in controls, although we did not find such associations in women. This is the first study to investigate the possible prospective link between IgG N-glycan traits and IS. Our findings indicated that decreased sialylation and galactosylation are associated with an increased risk of IS in men, which was also observed in our previous case-control study [15]. Several studies on the general population found that levels of N-glycosylation differed between men and women [24, 25, 41]. It was speculated that galactosylation and sialylation of IgG are influenced and regulated by different sex hormone levels [26]. Furthermore, a previous sex-stratified study indicated that N-glycan biomarkers could improve the prediction ability of type 2 diabetes and cardiovascular disease, with higher predictive efficacy in men [42]. A recent study also showed higher levels of galactosylation in female mice [11], which may explain the sex differences in our study.

      Associations between N-glycan traits and cardiovascular diseases have been observed in previous studies [42, 43]. Consistent with our results, a prospective study indicated that plasma N-glycan traits could improve cardiovascular event (including stroke) prediction with the established clinical risk score [42]. In this study, all glycan biomarkers of cardiovascular events stemmed from immunoglobulins, suggesting a particular role for the glycosylation-dependent immune response in cardiovascular disease etiology. Similarly, a previous cohort study of stroke‐free individuals also found that the N-glycome might be a potentially useful biomarker for silent brain infarcts. Individuals with silent brain infarcts have a 2- to 4-fold higher risk of stroke [44]. Menni et al. investigated the links between IgG N-glycan traits and the 10-year atherosclerotic cardiovascular disease risk score and subclinical atherosclerosis. They found that galactosylation and sialylation of IgG N-glycan traits were inversely associated with the 10-year atherosclerotic cardiovascular disease risk score [45].

      Combined with previous research [15], our findings suggested that faintly aberrant IgG N-glycosylation might play a cascading role in the pathogenesis of IS. N-glycosylation compositions in the Fc segment of IgG can alter effector functions by modulating its affinity for distinct Fc receptors to mediate pro- and anti-inflammatory activities [46]. Abundant evidence has shown potential links between decreased galactosylation and BMI, measures of central adiposity, and hypertension [19, 47, 48], which are risk factors for IS. IgG N-glycosylation with decreased galactosylation mediates proinflammatory activity by recognizing mannose-binding lectin (MBL) and subsequently activating complement [49]. In addition, decreased galactosylation also enhances FcγRIII affinity, thus enhancing antibody-dependent cellular cytotoxicity (ADCC) activity [50]. Moreover, galactose deficiency also affects sialylation, as the addition of terminal sialylation requires galactose as the substrate for sialyltransferases [51].

      A strength of this study was the use of incident cases from a prospective cohort study, which enables keeping the temporal association between IgG N-glycan traits and IS outcome in longitudinal studies. Several limitations should be noted. First, in a prospective setting, the relatively small sample size of the nested case-control study may result in an overfitted model. The results suggested that IgG N-glycan traits were prospectively associated with IS but did not provide a final assessment of predictive accuracy. Further validation of cohort studies in larger independent populations is necessary for our future work. Second, because medication information, such as antihypertensive treatment, was unavailable in the database, the potential for bias arising from medication information could not be assessed. Third, information on menopause time was not collected in the database, and more studies are needed to examine whether the changes in IgG N-glycosylation in women affected by menopausal status can influence the pathogenesis of IS in the future. Finally, this study did not include hemorrhagic stroke because of its low incidence in the cohort by the end of the follow-up. Further external validation of IgG N-glycan biomarkers is needed in large prospective studies.

    • In conclusion, the present study showed that IgG N-glycan traits with decreased galactosylation and sialylation were prospectively associated with incident IS in men, suggesting that sex discrepancy might exist in the association between IgG N-glycans and incident IS. Nevertheless, further research is needed to validate these biomarkers in cohort studies with larger sample sizes and multiethnic populations, which provide novel biomarkers to identify IS patients.

    • The data underlying this article will be shared upon reasonable request to the corresponding author.

    • Initial glycansMenWomen
      Incident ISControlP*q#Incident ISControlP*q#
      GP10.09 (0.06–0.16)0.08 (0.05–0.12)0.532450.614190.10 (0.05–0.15)0.10 (0.07–0.17)0.367580.80236
      GP20.51 (0.32–0.74)0.54 (0.35–0.73)0.812310.829500.47 (0.31–0.69)0.61 (0.34–0.75)0.177110.80236
      GP30.18 (0.09–0.29)0.12 (0.05–0.17)0.02494*0.056790.13 (0.07–0.22)0.22 (0.10–0.29)0.070320.80236
      GP426.64 (24.54–31.37)22.65 (20.42–26.22)0.00001*0.00008#31.87 (23.14–35.61)30.47 (27.15–32.94)0.885390.92388
      GP50.26 (0.18–0.33)0.21 (0.16–0.26)0.085850.137360.25 (0.20–0.30)0.25 (0.20–0.35)0.600910.90137
      GP65.70 (4.91–6.49)5.12 (4.17–6.16)0.288420.381155.96 (4.59–7.07)5.58 (4.76–7.13)0.828980.92388
      GP70.30 (0.15–0.40)0.28 (0.18–0.46)0.301740.381140.22 (0.12–0.33)0.23 (0.15–0.40)0.309600.80236
      GP818.05 (16.40–19.16)17.72 (16.16–19.84)0.829500.8295018.07 (16.94–19.16)18.95 (17.42–20.32)0.095970.80236
      GP98.38 (6.28–9.88)8.71 (7.65–10.37)0.243990.344459.09 (7.41–10.03)8.30 (6.80–10.26)0.590250.90137
      GP103.90 (3.35–4.70)4.02 (3.43–4.58)0.537420.614193.85 (3.50–5.07)3.85 (3.05–4.70)0.337090.80236
      GP110.41 (0.29–0.52)0.49 (0.37–0.72)0.00765*0.02295#0.38 (0.30–0.50)0.43 (0.32–0.55)0.571330.90137
      GP120.51 (0.35–0.76)0.66 (0.48–1.03)0.02393*0.056790.39 (0.25–0.61)0.47 (0.34–0.61)0.301000.80236
      GP130.64 (0.41–0.77)0.63 (0.45–0.92)0.662660.722900.51 (0.35–0.72)0.52 (0.40–0.78)0.401180.80236
      GP1416.06 (14.85–18.51)17.54 (15.13–18.98)0.053300.0948715.04 (11.94–18.36)14.36 (12.59–16.84)0.842040.92388
      GP151.35 (1.03–1.81)1.46 (1.29–1.71)0.241620.344461.28 (1.07–1.58)1.20 (1.01–1.40)0.124040.80236
      GP162.56 (2.16–2.96)2.77 (2.41–3.40)0.02603*0.056792.51 (2.14–3.02)2.68 (2.34–2.97)0.373260.80236
      GP170.68 (0.49–0.80)0.74 (0.60–0.91)0.055340.094870.58 (0.48–0.72)0.60 (0.47–0.69)0.734880.92388
      GP187.90 (6.31–9.68)9.82 (8.01–12.46)0.00218*0.00747#7.77 (5.44–9.93)7.59 (5.97–8.54)0.554850.90136
      GP191.22 (0.88–1.48)1.55 (1.34–1.77)0.00004*0.00019#1.25 (0.94–1.48)1.20 (0.72–1.54)0.400550.80236
      GP200.07 (0.04–0.10)0.10 (0.04–0.12)0.04731*0.094620.07 (0.05–0.10)0.06 (0.05–0.09)0.844810.92388
      GP210.22 (0.12–0.38)0.38 (0.28–0.57)0.00002*0.00012#0.21 (0.11–0.34)0.22 (0.12–0.29)0.874640.92388
      GP220.05 (0.03–0.08)0.12 (0.06–0.20)0.00001*0.00008#0.04 (0.03–0.07)0.05 (0.02–0.09)0.261270.80236
      GP230.56 (0.35–1.09)1.02 (0.68–1.68)0.00008*0.00032#0.59 (0.36–0.90)0.68 (0.38–0.87)0.948230.94823
      GP240.53 (0.35–1.11)1.14 (0.79–1.62)0.00001*0.00008#0.46 (0.31–0.90)0.60 (0.33–0.99)0.666260.92388
        Note. Data were expressed median (25th–75th percentile); IS, ischemic stroke; GP, glycan peaks. *P < 0.05. #q < 0.05: significant after correction for FDR (false discovery rate).

      Table S4.  Sex-specific initial glycan peaks levels in nested case-control study

      Derive glycansMenWomen
      Incident ISControlP*q#Incident ISControlP*q#
      FGS/(FG + FGS)21.58 (17.18–24.75)24.82 (20.35–28.44)0.01024*0.03253#19.92 (16.46–23.58)20.47 (16.83–22.67)0.542490.79174
      FBGS/(FBG + FBGS)22.28 (15.51–32.00)31.46 (23.82–37.07)0.00045*0.00347#22.06 (17.79–29.09)23.24 (16.82–31.50)0.746670.86864
      FGS/(F + FG + FGS)13.84 (10.47–16.80)17.36 (14.10–20.75)0.00103*0.00556#13.09 (9.45–16.37)13.09 (11.09–14.74)0.360870.63734
      FBGS/(FB + FBG + FBGS)13.21 (8.81–19.06)19.22 (14.63–25.69)0.00008*0.00072#12.33 (9.45–17.34)13.58 (8.84–18.63)0.791540.89048
      FG1S1/(FG1 + FG1S1)8.36 (6.87–10.13)9.18 (8.01–11.79)0.02131*0.054797.89 (6.97–9.79)8.92 (7.67–9.99)0.168450.62776
      FG2S1/(FG2 + FG2S1 + FG2S2)31.99 (28.02–36.49)35.12 (31.17–38.62)0.01811*0.0514732.52 (28.71–34.62)32.50 (28.72–35.54)0.974110.98890
      FG2S2/(FG2 + FG2S1 + FG2S2)2.42 (1.46–4.26)3.40 (2.68–5.14)0.00121*0.00594#2.54 (1.70–4.02)3.11 (1.43–3.89)0.856490.92501
      FBG2S1/(FBG2 + FBG2S1 + FBG2S2)36.07 (31.29–41.18)36.53 (33.98–39.56)0.800380.8644139.16 (34.44–45.11)37.95 (32.40–42.82)0.742190.86864
      FBG2S2/(FBG2 + FBG2S1 + FBG2S2)19.40 (11.83–28.99)26.39 (20.92–32.73)0.00002*0.00036#14.76 (10.66–23.97)19.94 (12.67–27.05)0.222640.62776
      FtotalS1/FtotalS29.61 (5.97–14.64)6.57 (5.06–8.69)0.00007*0.00072#10.47 (6.26–14.49)8.74 (6.72–13.80)0.666290.83674
      FS1/FS217.82 (11.06–29.02)12.92 (9.23–17.11)0.00059*0.00354#17.29 (10.68–23.77)15.40 (11.99–25.66)0.951930.98890
      FBS1/FBS21.88 (1.38–3.14)1.41 (1.09–1.71)0.00002*0.00036#2.55 (1.58–3.30)1.96 (1.48–3.32)0.321030.62775
      FBStotal/FStotal0.16 (0.12–0.21)0.19 (0.16–0.23)0.00059*0.00354#0.17 (0.11–0.22)0.16 (0.11–0.22)0.538050.79174
      FBS1/FS10.11 (0.08–0.14)0.12 (0.10–0.16)0.056780.122640.12 (0.09–0.16)0.11 (0.09–0.14)0.206660.62776
      FBS1/FS1 + FBS10.09 (0.07–0.12)0.10 (0.09–0.14)0.063180.130300.11 (0.08–0.14)0.10 (0.08–0.12)0.219820.62776
      FBS2/FS20.89 (0.62–1.28)1.10 (0.84–1.33)0.02100*0.054790.79 (0.65–1.09)1.02 (0.65–1.27)0.538140.79174
      FBS2/(FS2 + FBS2)0.47 (0.38–0.56)0.52 (0.46–0.57)0.04908*0.120470.44 (0.39–0.52)0.50 (0.39–0.56)0.539040.79174
      GP1n0.09 (0.07–0.20)0.11 (0.07–0.16)0.642780.738510.11 (0.06–0.18)0.12 (0.08–0.20)0.632930.81376
      GP2n0.59 (0.38–0.89)0.66 (0.43–0.88)0.500540.600650.54 (0.36–0.77)0.68 (0.40–0.89)0.174900.62776
      GP4n32.55 (29.13–37.07)27.71 (25.51–31.73)0.00003*0.00041#36.88 (27.52–41.70)35.13 (31.34–37.73)0.565690.79915
      GP5n0.31 (0.21–0.39)0.26 (0.19–0.31)0.246230.391070.28 (0.23–0.34)0.29 (0.23–0.39)0.455360.76842
      GP6n6.70 (5.83–7.69)6.12 (5.30–7.39)0.220270.360446.85 (5.56–8.00)6.30 (5.47–8.23)0.606760.79914
      GP7n0.34 (0.18–0.50)0.36 (0.22–0.54)0.155880.280580.25 (0.14–0.36)0.28 (0.17–0.45)0.267760.62776
      GP8n20.93 (19.55–23.35)22.14 (20.06–23.57)0.256760.3961421.02 (18.93–22.51)21.99 (20.31–23.25)0.085560.62776
      GP9n9.88 (7.14–11.46)10.60 (9.55–12.43)0.01181*0.03543#10.54 (8.69–11.55)9.72 (7.85–11.44)0.292900.62776
      GP10n4.63 (3.92–5.50)4.91 (4.29–5.72)0.124100.231084.55 (4.06–5.68)4.44 (3.51–5.45)0.205550.62776
      GP11n0.46 (0.31–0.60)0.61 (0.45–0.82)0.00139*0.00626#0.47 (0.35–0.57)0.49 (0.36–0.62)0.756040.86864
      GP12n0.59 (0.43–0.93)0.80 (0.60–1.25)0.00659*0.02224#0.45 (0.29–0.70)0.53 (0.38–0.74)0.365880.63734
      GP13n0.76 (0.44–0.97)0.79 (0.55–1.10)0.356470.469490.55 (0.40–0.85)0.61 (0.45–0.89)0.332480.62776
      GP14n19.06 (15.87–22.04)22.00 (17.94–24.04)0.00491*0.01768#16.72 (13.35–22.43)16.63 (14.41–19.71)0.963860.98890
      GP15n1.62 (1.21–2.14)1.85 (1.59–2.17)0.052500.122641.53 (1.20–1.94)1.39 (1.15–1.67)0.124820.62776
      G0n39.81 (36.45–44.64)35.43 (32.44–39.42)0.00002*0.00036#43.89 (34.54–49.25)42.01 (39.49–47.09)0.844560.92501
      G1n36.38 (33.12–39.88)39.15 (36.88–40.78)0.00165*0.00685#36.78 (33.66–39.91)36.74 (34.84–38.86)0.988900.98890
      G2n22.03 (18.32–25.91)25.96 (21.39–28.36)0.00180*0.00694#19.87 (15.37–25.34)19.10 (16.49–22.71)0.714650.86864
      Fn total96.92 (96.19–97.85)96.87 (95.94–97.56)0.174360.2942397.50 (96.98–98.14)97.15 (96.61–97.84)0.090550.62776
      FG0n total/G0n98.40 (97.78–98.95)98.31 (98.60–99.50)0.104510.2015698.78 (98.27–99.10)98.50 (97.85–98.88)0.192580.62776
      FG1n total/G1n99.11 (98.62–99.52)99.05 (98.60–99.43)0.317590.4635199.32 (99.07–99.61)99.22 (98.87–99.52)0.203890.62776
      FG2n total/G2n93.52 (92.42–94.99)93.21 (91.72–94.47)0.165770.2887694.06 (93.36–95.44)93.58 (92.48–94.80)0.113830.79174
      Fn82.88 (81.56–85.69)82.93 (80.58–85.59)0.336670.4694983.54 (82.34–85.73)84.32 (81.60–86.26)0.525250.79915
      FG0n/G0n81.58 (79.77–83.54)80.41 (77.86–83.42)0.054660.1226482.35 (80.01–84.19)82.26 (80.13–85.63)0.606760.62776
      FG1n/G1n84.16 (82.80–87.17)84.59 (82.26–86.46)0.282160.4232484.81 (83.71–86.66)85.09 (83.44–88.06)0.198980.79915
      FG2n/G2n85.71 (84.19–87.91)85.70 (83.33–87.08)0.459360.5678885.94 (84.80–88.42)86.82 (84.33–88.19)0.600290.62776
      FBn13.85 (11.86–14.98)13.97 (12.04–15.53)0.521840.6125913.71 (12.31–14.84)13.19 (11.25–15.47)0.133370.62776
      FBG0n/G0n16.78 (14.86–18.41)17.86 (15.07–19.31)0.065150.1303016.61 (14.45–18.75)16.34 (13.13–17.91)0.314300.62776
      FBG1n/G1n14.72 (12.14–16.05)14.33 (12.84–15.86)0.947170.9835914.25 (12.61–15.51)14.34 (11.04–15.63)0.157280.62776
      FBG2n/G2n7.57 (6.34–8.82)7.50 (6.57–8.45)0.697430.784617.58 (6.78–8.59)7.20 (6.17–8.63)0.103610.62776
      FBn/Fn16.74 (13.92–18.25)16.83 (14.02–19.48)0.462720.5678816.43 (14.55–18.11)15.63 (13.09–18.96)0.271780.62776
      FBn/Fn total14.34 (12.22–15.44)14.41 (12.29–16.29)0.462720.5678814.11 (12.70–15.33)13.52 (11.57–15.94)0.271780.62776
      Fn/ (Bn + FBn)5.74 (5.23–6.88)5.63 (4.82–6.76)0.353590.469495.82 (5.33–6.63)6.15 (5.04–7.15)0.327870.62776
      Bn/ (Fn + FBn)7.88 (4.51–9.96)8.08 (5.64–11.28)0.356470.469495.69 (4.04–8.69)6.26 (4.60–9.17)0.337130.62776
      FBG2n/FG2n0.09 (0.07–0.11)0.09 (0.08–0.10)0.976320.992510.09 (0.08–0.10)0.08 (0.07–0.10)0.095980.62776
      FBG2n/(FG2n + FBG2n)8.20 (6.75–9.68)8.18 (7.17–9.23)0.992510.992517.97 (7.34–9.16)7.60 (6.69–9.08)0.095980.62776
      FG2n/(BG2n + FBG2n)7.51 (6.73–9.74)7.77 (6.74–9.29)0.947170.983597.93 (6.96–8.90)8.41 (7.05–9.59)0.259830.62776
      BG2n/(FG2n + FBG2n)35.97 (23.84–48.16)34.19 (23.01–45.88)0.782480.8623233.78 (24.20–42.73)35.75 (27.10–46.79)0.284100.62776
        Note. Data were expressed median (25th–75th percentile); IS ischemic stroke. *represents P < 0.05. #represents q < 0.05: significant after correction for FDR (false discovery rate).

      Table S5.  Sex-specific derive glycan traits levels in nested case-control study

      Initial glycansIncident IS vs. control (men)Incident IS vs. control (women)
      OR (95% CI)P*q#OR (95% CI)P*q#
      GP12.07 (0.42–10.18)0.372180.509950.60 (0.12–3.04)0.540820.86531
      GP20.53 (0.13–2.11)0.366300.509950.81 (0.16–4.09)0.800730.94287
      GP33.03 (0.84–10.96)0.091490.243970.42 (0.10–1.82)0.247990.73508
      GP41.16 (1.05–1.29)0.00396*0.02356#1.01 (0.91–1.11)0.903590.94287
      GP53.32 (0.52–21.32)0.205370.379140.37 (0.03–4.43)0.428930.74085
      GP61.13 (0.81–1.58)0.468180.591391.24 (0.79–1.92)0.365800.73508
      GP70.37 (0.06–2.20)0.275720.441150.39 (0.06–2.53)0.324650.73508
      GP80.99 (0.82–1.20)0.932090.932090.80 (0.64–1.00)0.051270.71088
      GP90.70 (0.55–0.90)0.00491*0.02356#0.98 (0.78–1.22)0.823050.94287
      GP100.67 (0.42–1.09)0.105350.252841.47 (0.78–2.74)0.230710.73508
      GP110.29 (0.05–1.94)0.204020.379140.54 (0.04–7.82)0.649830.91740
      GP120.26 (0.07–0.95)0.04082*0.122460.73 (0.07–7.56)0.789040.94287
      GP131.43 (0.41–5.01)0.576820.659220.42 (0.06–2.76)0.367540.73508
      GP141.04 (0.89–1.21)0.620480.676890.98 (0.83–1.16)0.832650.94287
      GP150.94 (0.29–2.98)0.911780.932094.06 (0.56–29.63)0.166620.73508
      GP160.58 (0.29–1.18)0.134070.292510.78 (0.30–2.06)0.621330.91740
      GP170.74 (0.29–1.91)0.531500.6378014.54 (0.90–234.80)0.059240.71088
      GP180.94 (0.83–1.08)0.382460.509951.12 (0.90–1.41)0.309690.73508
      GP190.33 (0.13–0.85)0.02092*0.071721.84 (0.61–5.58)0.278670.73508
      GP200.01 (0.01–62.90)0.255260.437591.02 (0.09–10.99)0.990360.99036
      GP210.02 (0.01–0.27)0.00292*0.02357#2.34 (0.43–12.61)0.324500.73508
      GP220.01 (0.01–0.02)0.00403*0.02357#0.50 (0.09–2.83)0.432160.74084
      GP230.32 (0.13–0.78)0.01231*0.04924#1.97 (0.48–8.02)0.344770.73508
      GP240.21 (0.09–0.54)0.00108*0.02357#0.92 (0.31–2.79)0.888690.94287
        Note. IS, ischemic stroke; CI confidence interval; GP, glycan peaks. *P < 0.05. #q < 0.05: significant after correction for FDR (false discovery rate).

      Table S6.  Associations of initial glycan peaks and ischemic stroke in sex-specific analysis (after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia)

      Derive glycansIncident IS vs. control (men)Incident IS vs. control (women)
      OR (95% CI)P*q#OR (95% CI)P*q#
      FGS/(FG + FGS)1.97 (0.90–1.05)0.470350.588211.06 (0.96–1.17)0.252520.66608
      FBGS/(FBG + FBGS)0.97 (0.93–1.01)0.148620.321011.00 (0.95–1.06)0.902610.98529
      FGS/(F + FG + FGS)0.93 (0.84–1.02)0.105780.321011.08 (0.94–1.24)0.292460.66608
      FBGS/(FB + FBG + FBGS)0.94 (0.88–0.99)0.04614*0.207631.01 (0.93–1.09)0.843700.98529
      FG1S1/(FG1 + FG1S1)0.90 (0.76–1.08)0.267530.424780.98 (0.79–1.21)0.852450.98529
      FG2S1/(FG2 + FG2S1 + FG2S2)0.97 (0.91–1.05)0.442770.588211.05 (0.96–1.13)0.290630.66608
      FG2S2/(FG2 + FG2S1 + FG2S2)0.72 (0.55–0.94)0.01443*0.097401.18 (0.85–1.65)0.328290.66608
      FBG2S1/(FBG2 + FBG2S1 + FBG2S2)1.00 (0.93–1.07)0.931780.939991.03 (0.97–1.10)0.357710.66608
      FBG2S2/(FBG2 + FBG2S1 + FBG2S2)0.92 (0.87–0.97)0.00236*0.03186#0.98 (0.92–1.04)0.438830.76441
      FtotalS1/FtotalS21.31 (1.10–1.55)0.00217*0.03186#0.98 (0.92–1.05)0.586890.90459
      FS1/FS21.14 (1.05–1.25)0.00323*0.03488#0.98 (0.94–1.03)0.408070.73452
      FBS1/FBS21.40 (0.95–2.05)0.088640.307801.00 (0.76–1.29)0.967640.98529
      FBStotal/FStotal0.02 (0.00–0.61)0.023540.141242.14 (0.12–37.37)0.603060.90459
      FBS1/FS10.09 (0.00–1.82)0.115990.321016.51 (0.22–189.84)0.276340.66608
      FBS1/FS1 + FBS10.08 (0.00–2.17)0.131190.321017.82 (0.18–338.24)0.284830.66608
      FBS2/FS20.46 (0.17–1.27)0.136100.321010.51 (0.14–1.91)0.316530.66608
      FBS2/(FS2 + FBS2)0.04 (0.00–3.17)0.144560.321010.07 (0.00–13.69)0.327870.66608
      GP1n1.85 (0.36–9.48)0.462400.588210.78 (0.16–3.76)0.752930.98529
      GP2n0.49 (0.15–1.66)0.253500.424780.92 (0.23–3.66)0.901940.98529
      GP4n1.14 (1.04–1.25)0.00579*0.052111.00 (0.93–1.09)0.938990.98529
      GP5n2.86 (0.43–19.18)0.278430.424780.13 (0.00–9.62)0.351890.66608
      GP6n1.04 (0.77–1.41)0.801010.841571.26 (0.84–1.91)0.267590.66608
      GP7n0.40 (0.08–1.96)0.259180.424780.98 (0.09–11.24)0.985290.98529
      GP8n0.93 (0.79–1.08)0.343610.488280.84 (0.69–1.03)0.096740.65695
      GP9n0.65 (0.51–0.84)0.00970*0.074821.01 (0.84–1.22)0.904220.98529
      GP10n0.62 (0.40–0.95)0.028570.146341.48 (0.87–2.51)0.145990.65695
      GP11n0.27 (0.05–1.42)0.133980.321011.14 (0.31–4.15)0.846760.98529
      GP12n0.29 (0.09–0.89)0.02981*0.146342.31 (0.57–9.41)0.244380.66608
      GP13n1.23 (0.43–3.50)0.697770.771300.58 (0.12–2.68)0.480080.81013
      GP14n0.99 (0.88–1.10)0.796500.841570.99 (0.87–1.13)0.908390.98529
      GP15n0.75 (0.30–1.84)0.524580.629493.46 (0.69–17.42)0.132590.65695
      G0n1.12 (1.03–1.22)0.00075*0.02025#1.02 (0.94–1.11)0.619970.90482
      G1n0.74 (0.63–0.87)0.00036*0.01944#0.94 (0.83–1.07)0.352380.66608
      G2n0.97 (0.88–1.07)0.557390.645801.01 (0.90–1.15)0.819870.98529
      Fn total1.18 (0.87–1.61)0.283190.424781.01 (0.63–1.62)0.957280.98529
      FG0n total/G0n1.54 (0.96–2.51)0.082020.307801.04 (0.59–1.80)0.904250.98529
      FG1n total/G1n1.26 (0.79–2.00)0.328940.480070.90 (0.36–2.26)0.825690.98529
      FG2n total/G2n1.16 (0.95–1.41)0.145700.321011.00 (0.78–1.27)0.966090.98529
      Fn1.10 (0.96–1.25)0.171710.356620.86 (0.68–1.08)0.190000.66608
      FG0n/G0n1.11 (0.99–1.24)0.067390.279920.92 (0.77–1.08)0.299390.66608
      FG1n/G1n1.08 (0.94–1.24)0.271070.424780.80 (0.64–1.00)0.049440.65695
      FG2n/G2n1.10 (0.97–1.26)0.142370.321010.91 (0.74–1.11)0.343490.66608
      FBn0.89 (0.75–1.07)0.222850.414961.24 (0.95–1.64)0.118030.65695
      FBG0n/G0n0.89 (0.79–1.02)0.091200.307801.13 (0.93–1.38)0.218650.66608
      FBG1n/G1n0.94 (0.81–1.11)0.479290.588211.27 (1.00–1.60)0.051050.65695
      FBG2n/G2n0.94 (0.68–1.03)0.699890.771301.48 (0.97–2.28)0.072140.65695
      FBn/Fn0.92 (0.82–1.04)0.180690.361381.16 (0.95–1.41)0.136810.65695
      FBn/Fn total0.90 (0.76–1.06)0.193470.373121.23 (0.95–1.60)0.122970.65695
      Fn/ (Bn + FBn)1.20 (0.87–1.65)0.262770.424780.65 (0.39–1.06)0.082520.65695
      Bn/ (Fn + FBn)1.01 (0.92–1.11)0.810410.841570.95 (0.82–1.10)0.505410.82703
      FBG2n/FG2n0.15 (0.00–18.16)0.438120.588210.80 (0.64–1.01)0.057370.65695
      FBG2n/ (FG2n + FBG2n)0.90 (0.68–1.20)0.475650.588211.43 (0.96–2.13)0.077030.65695
      FG2n/ (BG2n + FBG2n)1.05 (0.89–1.23)0.562090.645800.95 (0.75–1.19)0.639630.90894
      BG2n/ (FG2n + FBG2n)1.00 (0.98–1.02)0.939990.939990.99 (0.96–1.02)0.545380.86619
        Note. IS, ischemic stroke; CI, confidence interval. *P < 0.05. #q < 0.05: significant after correction for FDR (false discovery rate).

      Table S7.  Associations of derive glycan traits and ischemic stroke in sex-specific analysis (after adjusting for age, waist and hip circumference, obesity, diabetes, hypertension, and dyslipidemia)

Reference (51)
Supplements:
22360+Supplementary Materials.pdf

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return