Volume 30 Issue 1
Jan.  2017
Article Contents
Turn off MathJax

Citation:

CDH13 Genetic Polymorphisms, Adiponectin and Ischemic Stroke: a Chinese Family-based Sib-pair Study

  • Author Bio: CHEN Li, female, born in 1978, PhD, majoring in chronic disease epidemiology.;SUN Ke Xin, female, born in 1988, PhD, majoring in genetic epidemiology..
  • Corresponding author:

    HU Yong Hua, Professor, MD, Tel: 86-13501361139, Fax: 86-10-82801189.yhhu@bjmu.edu.cn

  • Received Date: 2016-10-03
    Fund Project:

    This study was supported by the Key Project of Natural Science Funds of China 81230066

    and the National Natural Science Fund Projects of China 81473043, 81573226

  • Objective To understand the relationships between CDH13 (T-cadherin) genetic polymorphisms, adiponectin levels and ischemic stroke, and possible interactions between CDH13 polymorphisms and other risk factors. Methods We recruited 342 Chinese ischemic stroke sib pairs. We genotyped rs4783244 and rs7193788 on CDH13 using time-of-flight mass spectrometry genotyping technology and measured total and high-molecular weight (HMW) adiponectin levels. We investigated associations between SNPs and ischemic stroke, and interactions between SNPs and other risk factors using multi-level mixed-effects regression model. Results In individuals without ischemic stroke, CDH13 rs4783244 was associated with total adiponectin levels (per T:Coef=-0.257, P=0.001). CDH13 rs7193788 was associated with total adiponectin levels (per A:Coef=-0.221, P=0.001) and HMW adiponectin levels (per A:Coef=-0.163, P=0.003). rs7193788 was significantly associated with ischemic stroke (GA/AA vs. GG:OR=1.55, 95% CI:1.07 to 2.24, P=0.020) after Bonferroni correction (α=0.025). There was an interaction between rs7193788 and diabetes (P=0.036). Compared to diabetes-free individuals with rs7193788 GG genotype, diabetes patients with rs7193788 GA/AA genotypes had higher risks for ischemic stroke (OR=2.64, 95% CI:1.58-4.40, P<0.001). Conclusion CDH13 genetic polymorphisms are associated with adiponectin levels and ischemic stroke. An interaction is found between CDH13 SNP and diabetes for ischemic stroke.
  • 加载中
  • [1]

    Mendis S, Davis S, Norrving B. Organizational update the world health organization global status report on noncommunicable diseases 2014; one more landmark step in the combat against stroke and vascular disease. Stroke, 2015; 46, e121-e2. doi: 10.1161/STROKEAHA.115.008097
    [2]

    Feigin VL, Krishnamurthi RV, Parmar P, et al. Update on the global burden of ischemic and hemorrhagic stroke in 1990-2013:the GBD 2013 study. Neuroepidemiology, 2015; 45, 161-76. doi: 10.1159/000441085
    [3]

    Zhao D, Liu J, Wang W, et al. Epidemiological transition of stroke in China twenty-one-year observational study from the sino-MONICA-Beijing project. Stroke, 2008; 39, 1668-74. doi: 10.1161/STROKEAHA.107.502807
    [4]

    Antoniades C, Antonopoulos AS, Tousoulis D, et al. Adiponectin:from obesity to cardiovascular disease. Obes Rev, 2009; 10, 269-79. doi: 10.1111/obr.2009.10.issue-3
    [5]

    Kazumi T, Kawaguchi A, Sakai K, et al. Young men with high-normal blood pressure have lower serum adiponectin, smaller LDL size, and higher elevated heart rate than those with optimal blood pressure. Diabetes Care, 2002; 25, 971-6. doi: 10.2337/diacare.25.6.971
    [6]

    Pischon T, Hu FB, Girman CJ, et al. Plasma total and high molecular weight adiponectin levels and risk of coronary heart disease in women. Atherosclerosis, 2011; 219, 322-9. doi: 10.1016/j.atherosclerosis.2011.07.011
    [7]

    Ouchi N, Kihara S, Funahashi T, et al. Obesity, adiponectin and vascular inflammatory disease. Curr Opin Lipidol, 2003; 14, 561-6. doi: 10.1097/00041433-200312000-00003
    [8]

    Tan KC, Xu A, Chow WS, et al. Hypoadiponectinemia is associated with impaired endothelium-dependent vasodilation. J Clin Endocrinol Metab, 2004; 89, 765-9. doi: 10.1210/jc.2003-031012
    [9]

    Nishimura M, Izumiya Y, Higuchi A, et al. Adiponectin prevents cerebral ischemic injury through endothelial nitric oxide synthase dependent mechanisms. Circulation, 2008; 117, 216-23. doi: 10.1161/CIRCULATIONAHA.107.725044
    [10]

    Savopoulos C, Michalakis K, Apostolopoulou M, et al. Adipokines and stroke:a review of the literature. Maturitas, 2011; 70, 322-7. doi: 10.1016/j.maturitas.2011.09.002
    [11]

    Ling H, Waterworth DM, Stirnadel HA, et al. Genome-wide Linkage and Association Analyses to Identify Genes Influencing Adiponectin Levels:The GEMS Stud. Obesity, 2009; 17, 737-44. doi: 10.1038/oby.2008.625
    [12]

    Richards JB, Waterworth D, O'Rahilly S, et al. A genome-wide association study reveals variants in ARL15 that influence adiponectin levels. PLoS Genet, 2009; 5, e1000768. doi: 10.1371/journal.pgen.1000768
    [13]

    Qi L, Menzaghi C, Salvemini L, et al. Novel locus FER is associated with serum HMW adiponectin levels. Diabetes, 2011; 60, 2197-201. doi: 10.2337/db10-1645
    [14]

    Wu Y, Li Y, Lange EM, et al. Genome-wide association study for adiponectin levels in Filipino women identifies CDH13 and a novel uncommon haplotype at KNG1-ADIPOQ. Human molecular genetics, 2010; 19, 4955-64. doi: 10.1093/hmg/ddq423
    [15]

    Jee SH, Sull JW, Lee JE, et al. Adiponectin concentrations:a genome-wide association study. Am J Hum Genet, 2010; 87, 545-52. doi: 10.1016/j.ajhg.2010.09.004
    [16]

    Morisaki H, Yamanaka I, Iwai N, et al. CDH13 gene coding T-cadherin influences variations in plasma adiponectin levels in the Japanese population. Hum Mutat, 2012; 33, 402-10. doi: 10.1002/humu.21652
    [17]

    Chung CM, Lin TH, Chen JW, et al. A genome-wide association study reveals a quantitative trait locus of adiponectin on CDH13 that predicts cardiometabolic outcomes. Diabetes, 2011; 60, 2417-23. doi: 10.2337/db10-1321
    [18]

    Gao H, Kim YM, Chen P, et al. Genetic variation in CDH13 is associated with lower plasma adiponectin levels but greater adiponectin sensitivity in East Asian populations. Diabetes, 2013; 62, 4277-83. doi: 10.2337/db13-0129
    [19]

    Takeuchi T, Adachi Y, Ohtsuki Y, et al. Adiponectin receptors, with special focus on the role of the third receptor, T-cadherin, in vascular disease. Med Mol Morphol, 2007; 40, 115-20. doi: 10.1007/s00795-007-0364-9
    [20]

    Hug C, Wang J, Ahmad NS, et al. T-cadherin is a receptor for hexameric and high-molecular-weight forms of Acrp30/adiponectin. Proc Natl Acad Sci U S A, 2004; 101, 10308-13. doi: 10.1073/pnas.0403382101
    [21]

    Cheong MY, Bang OS, Cha MH, et al. Association of the adiponectin gene variations with risk of ischemic stroke in a Korean population. Yonsei Med J, 2011; 52, 20-5. doi: 10.3349/ymj.2011.52.1.20
    [22]

    Reich DE, Goldstein DB. Detecting association in a case-control study while correcting for population stratification. Genetic epidemiology, 2001; 20, 4-16. doi: 10.1002/(ISSN)1098-2272
    [23]

    Cordell HJ, Clayton DG. Genetic association studies. The Lancet, 2005; 366, 1121-31. doi: 10.1016/S0140-6736(05)67424-7
    [24]

    Tang X, Hu Y, Chen D, et al. The Fangshan/family-based Ischemic Stroke Study In China (FISSIC) protocol. BMC Med Genet, 2007; 8, 60.
    [25]

    Meschia JF, Brown RD Jr, Brott TG, et al. The Siblings With Ischemic Stroke Study (SWISS) protocol. BMC Med Genet, 2002; 3, 1.
    [26]

    Jones WJ, Williams LS, Meschia JF. Validating the Questionnaire for Verifying Stroke-Free Status (QVSFS) by neurological history and examination. Stroke, 2001; 32, 2232-6. doi: 10.1161/hs1001.096191
    [27]

    Meschia JF, Lojacono MA, Miller MJ, et al. Reliability of the questionnaire for verifying stroke-free status. Cerebrovasc Dis, 2004; 17, 218-23.
    [28]

    Gupta V, Vinay DG, Sovio U, et al. Association study of 25 type 2 diabetes related loci with measures of obesity in Indian sib pairs. PLoS One, 2013; 8, e53944. doi: 10.1371/journal.pone.0053944
    [29]

    Yamauchi T, Kamon J, Waki H, et al. The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med, 2001; 7, 941-6. doi: 10.1038/90984
    [30]

    Hotta K, Funahashi T, Arita Y, et al. Plasma concentrations of a novel, adipose-specific protein, adiponectin, in type 2 diabetic patients. Arterioscler Thromb Vasc Biol, 2000; 20, 1595-9. doi: 10.1161/01.ATV.20.6.1595
    [31]

    Pajvani UB, Du X, Combs TP, et al. Structure-function studies of the adipocyte-secreted hormone Acrp30/adiponectin. Implications fpr metabolic regulation and bioactivity. J Biol Chem, 2003; 278, 9073-85. doi: 10.1074/jbc.M207198200
    [32]

    Fisher FM, Trujillo ME, Hanif W, et al. Serum high molecular weight complex of adiponectin correlates better with glucose tolerance than total serum adiponectin in Indo-Asian males. Diabetologia, 2005; 48, 1084-7. doi: 10.1007/s00125-005-1758-7
    [33]

    Pajvani UB, Hawkins M, Combs TP, et al. Complex distribution, not absolute amount of adiponectin, correlates with thiazolidinedione-mediated improvement in insulin sensitivity. J Biol Chem, 2004; 279, 12152-62. doi: 10.1074/jbc.M311113200
    [34]

    Otsuka I, Watanabe Y, Hishimoto A, et al. Association analysis of the Cadherin13 gene with schizophrenia in the Japanese population. Neuropsychiatr Dis Treat, 2015; 11, 1381-93.
    [35]

    Arregui M, Buijsse B, Fritsche A, et al. Adiponectin and risk of stroke:prospective study and meta-analysis. Stroke, 2014; 45, 10-7. doi: 10.1161/STROKEAHA.113.001851
    [36]

    Matsumoto M, Ishikawa S, Kajii E. Association of adiponectin with cerebrovascular disease:a nested case-control study. Stroke, 2008; 39, 323-8. doi: 10.1161/STROKEAHA.107.497552
    [37]

    Bidulescu A, Liu J, Chen Z, et al. Associations of adiponectin and leptin with incident coronary heart disease and ischemic stroke in african americans:the jackson heart study. Front Public Health, 2013; 1, 16.
    [38]

    Hao G, Li W, Guo R, et al. Serum total adiponectin level and the risk of cardiovascular disease in general population:a meta-analysis of 17 prospective studies. Atherosclerosis, 2013; 228, 29-35. doi: 10.1016/j.atherosclerosis.2013.02.018
    [39]

    Kanhai DA, Kranendonk ME, Uiterwaal CS, et al. Adiponectin and incident coronary heart disease and stroke. A systematic review and meta-analysis of prospective studies. Obes Rev, 2013; 14, 555-67. doi: 10.1111/obr.2013.14.issue-7
    [40]

    Soderberg S, Stegmayr B, Stenlund H, et al. Leptin, but not adiponectin, predicts stroke in males. J Intern Med, 2004; 256, 128-36. doi: 10.1111/jim.2004.256.issue-2
    [41]

    Hegener HH, Lee IM, Cook NR, et al. Association of adiponectin gene variations with risk of incident myocardial infarction and ischemic stroke:a nested case-control study. Clin Chem, 2006; 52, 2021-7. doi: 10.1373/clinchem.2006.074476
    [42]

    Liu F, He Z, Deng S, et al. Association of adiponectin gene polymorphisms with the risk of ischemic stroke in a Chinese Han population. Mol Biol Rep, 2011; 38, 1983-8. doi: 10.1007/s11033-010-0320-y
    [43]

    Jo J, Sull JW, Park EJ, et al. Effects of smoking and obesity on the association between CDH13 (rs3865188) and adiponectin among Korean men:the KARE study. Obesity (Silver Spring), 2012; 20, 1683-7. doi: 10.1038/oby.2011.128
    [44]

    Beckman JA, Creager MA, Libby P. Diabetes and atherosclerosis:epidemiology, pathophysiology, and management. Jama, 2002; 287, 2570-81. doi: 10.1001/jama.287.19.2570
    [45]

    Kuusisto J, Mykkanen L, Pyorala K, et al. Non-insulin-dependent diabetes and its metabolic control are important predictors of stroke in elderly subjects. Stroke, 1994; 25, 1157-64. doi: 10.1161/01.STR.25.6.1157
    [46]

    Folsom AR, Rasmussen ML, Chambless LE, et al. Prospective associations of fasting insulin, body fat distribution, and diabetes with risk of ischemic stroke. The atherosclerosis risk in communities (ARIC) study investigators. Diabetes Care, 1999; 22, 1077-83. doi: 10.2337/diacare.22.7.1077
    [47]

    Ouedraogo R, Gong Y, Berzins B, et al. Adiponectin deficiency increases leukocyte-endothelium interactions via upregulation of endothelial cell adhesion molecules in vivo. J Clin Invest, 2007; 117, 1718-26. doi: 10.1172/JCI29623
    [48]

    Laird NM, Lange C. Family-based designs in the age of large-scale gene-association studies. Nat Rev Genet, 2006; 7, 385-94.
    [49]

    Kim BJ, Lee SH, Ryu WS, et al. Adipocytokines and ischemic stroke:differential associations between stroke subtypes. J Neurol Sci, 2012; 312, 117-22. doi: 10.1016/j.jns.2011.08.007
  • 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

Tables(4)

Article Metrics

Article views(429) PDF downloads(8) Cited by()

Proportional views

CDH13 Genetic Polymorphisms, Adiponectin and Ischemic Stroke: a Chinese Family-based Sib-pair Study

    Corresponding author: HU Yong Hua, yhhu@bjmu.edu.cn
  • 1. Department of Epidemiology and Biostatistics, Peking University Health Science Center, Beijing 100191, China
  • 2. Beijing Center for Disease Prevention and Control, Beijing 100013, China
  • 3. Department of Epidemiology & Biostatistics, Capital Medical University, Beijing 100069, China
  • 4. Pingshan New District Center for Disease Control and Prevention, Shenzhen 518118, Guangdong, China
  • 5. Shilou Township Hospital, Beijing 102422, China
Fund Project:  This study was supported by the Key Project of Natural Science Funds of China 81230066and the National Natural Science Fund Projects of China 81473043, 81573226

Abstract:  Objective To understand the relationships between CDH13 (T-cadherin) genetic polymorphisms, adiponectin levels and ischemic stroke, and possible interactions between CDH13 polymorphisms and other risk factors. Methods We recruited 342 Chinese ischemic stroke sib pairs. We genotyped rs4783244 and rs7193788 on CDH13 using time-of-flight mass spectrometry genotyping technology and measured total and high-molecular weight (HMW) adiponectin levels. We investigated associations between SNPs and ischemic stroke, and interactions between SNPs and other risk factors using multi-level mixed-effects regression model. Results In individuals without ischemic stroke, CDH13 rs4783244 was associated with total adiponectin levels (per T:Coef=-0.257, P=0.001). CDH13 rs7193788 was associated with total adiponectin levels (per A:Coef=-0.221, P=0.001) and HMW adiponectin levels (per A:Coef=-0.163, P=0.003). rs7193788 was significantly associated with ischemic stroke (GA/AA vs. GG:OR=1.55, 95% CI:1.07 to 2.24, P=0.020) after Bonferroni correction (α=0.025). There was an interaction between rs7193788 and diabetes (P=0.036). Compared to diabetes-free individuals with rs7193788 GG genotype, diabetes patients with rs7193788 GA/AA genotypes had higher risks for ischemic stroke (OR=2.64, 95% CI:1.58-4.40, P<0.001). Conclusion CDH13 genetic polymorphisms are associated with adiponectin levels and ischemic stroke. An interaction is found between CDH13 SNP and diabetes for ischemic stroke.

INTRODUCTION
  • Stroke is the leading cause of disability and mortality worldwide [1]. Stroke burden continues to increase, especially in developing countries [2]. Incidence rate of ischemic stroke (IS) is high in China [3]. It is valuable to evaluate genetic and environmental risk factors for IS in Chinese population.

    Low serum adiponectin level is a predisposing factor for type 2 diabetes, hypertension and cardiovascular diseases [4-6]. Laboratory evidences suggest that the anti-inflammatory and anti-atherogenic properties of adiponectin can protect vascular system [7-9]. These favorable effects attributed to adiponectin intrigue people to investigate whether it can also lower the risk of ischemic stroke. However, the direct association between adiponectin and development of IS remains to be inconsistent [10]. This might due to possible confounding effect of environmental factors on adiponectin levels. Discussing associations between adiponectin related genetic polymorphisms and IS can avoid this problem.

    Genome-wide association studies (GWAS) concerning adiponectin levels identified some risk genetic polymorphisms. SNPs on ADIPOQ, ARL15 and FER genes were associated with plasma adiponectin levels in European population [11-13]. GWAS for Asian populations discovered novel risk loci on other genes, including rs3865188 on CDH13 (T-cadherin) gene in Filipino women [14] and Korean individuals [15], and rs4783244 on CDH13 gene in Japanese [16] and Chinese [17] populations. rs4783244 was further proved to be associated with high-molecular weight (HMW) adiponectin levels in East Asian populations [18]. CDH13 is the encoding gene of T-cadherin, which is a major ad iponectin receptor in vasculature [19-20]. GWAS results suggest that CDH13 may play an important role on adiponectin levels in Asian populations.

    Previous studies revealed some associations between adiponectin related SNPs and IS. Cheong et al. found that 6 polymorphisms on ADIPOQ were strongly associated with ischemic stroke [21]. Chung et al. reported associations between CDH13 rs4783244: rs8047711: rs7193788 and ischemic stroke [17]. However, most genetic epidemiological studies focusing on the association between CDH13 and stroke adopted population-based case-control study design. Its vulnerability to the problem of population stratification often undermined the accuracy of statistical analysis, and thus led to false negative findings [22]. Sib pair study design compares genetic polymorphisms between full siblings with same genetic backgrounds, which counteracts confounding due to population stratification [23]. What's more, the aggregation of risk genetic material in sib pairs prone to IS might be in favor of discovering de novo risk loci.

    To understand the relationships between CDH13 polymorphisms, adiponectin levels and IS, this study discussed: 1) the associations between CDH13 genetic polymorphisms and adiponectin levels; 2) the associations between CDH13 genetic polymorphisms and IS; 3) the interactions between CDH13 genetic polymorphisms and other risk factors for IS.

MATERIALS AND METHODS
  • The current study is a part of Fangshan Family-based Ischemic Stroke Study In China (FISSIC) program, which is an ongoing family-based genetic epidemiological study. The protocol was described in details elsewhere [24]. In brief, we recruited Northern Chinese Han pedigrees from Fangshan District, which is located in the southwest of Beijing, China. The inclusion criteria for IS patients were: 1) diagnosis of at least one ischemic stroke confirmed by the study neurologist on the basis of history, medical records, and head imaging by CT or MRI; 2) at least 18 years old by the time of enrolment in the study; 3) at least one full sibling or parent alive in areas nearby; 4) written informed consent by the patient or surrogate. The exclusion criteria for IS patients were: 1) diagnosis of TIA only; 2) diagnosis of vasospasm after subarachnoid hemorrhage; 3) diagnosis of Mendelian disorders: CADASIL, Fabry disease, MELAS, or sickle cell anaemia; 4) diagnosis of iatrogenic ischemic stroke associated with a surgical/ interventional procedure such as coronary artery bypass grafting, carotid endarterectomy, or heart valve surgery; 5) diagnosis of ischemic stroke associated with autoimmune condition or endocarditis. The inclusion criteria for IS-free siblings were: 1) over 18 years old; 2) had no medical history of IS. The exclusion criteria for IS-free siblings were: 1) uncapable of coorperating during physical examinations; 2) refused to provide blood samples.

    Since June 2005 to June 2013: we recruited 342 discordant IS sib pairs (684 individuals in total) using proband-initiated contact method [25]. Each discordant IS sib pair contained one confirmed IS patient and one IS-free full sibling.

  • Medical records including patient history, physical examination, laboratory testing and brain imaging data of every IS patient were collected from local hospitals and sent to study neurologists for stroke confirmation. The IS-free status was identified using the Questionnaire for Verifying Stroke-Free Status (QVSFS) [26-27]. Siblings with negative responses to all 8 questions and with no IS medical history were defined as IS-free siblings.

  • Fasting venous blood samples were collected from every participant. Blood samples were transferred into labeled vacuum tubes containing EDTA, and then they were centrifuged at 4000 rpm for 15 min to obtain serum.

    Total adiponectin and HMW adiponectin concen- trations (ng/mL) in serum were estimated by commer- cially available ELISA kits (EK0595: Boster, Wuhan, China; CSB-E13400h, Cusabio, Wuhan, China) using TECAN GENios Plus enzyme-linked immunosorbent assay reader (TECAN, Grödig, Austria).

  • Surveys were carried out by trained and qualified staffs. Demographic information was collected by a standard questionnaire. A current smoker was a person who had at least 1 cigarette per day. An ex-smoker was a person who had regularly smoked but had quitted smoking for at least 1 month. A non-smoker was a person who had never smoked. The current and ex-smokers were both treated as smokers during the analysis. A drinker was a person who had ever had at least 50 milliliter white spirit per week and lasted for at least 6 months. Sitting blood pressure was examined for 3 times using brachial blood pressure meters (HEM-7200: Omron Healthcare, Kyoto, Japan). The mean of the second and the third observed values was taken as one's final blood pressure. BMI was calculated as weight/height2 (kg/m2). BMI ≥ 25 was defined as overweight/obesity, while BMI < 25 was defined as normal. Hypertension was defined as a diagnosis of hypertension, antihypertensive therapy, SBP ≥ 140 mmHg or DBP ≥ 90 mmHg during examination. Diabetes was defined as a diagnosis of diabetes, antidiabetic therapy, or fast blood glucose (FBG) ≥ 7.0 mmol/L.

    Fasting venous blood samples were tested in Peking University Health Science Center Key Laboratory of Epidemiology for fast blood glucose (FBG, mmol/L), total cholesterol (TC, mmol/L), total triglycerides (TG, mmol/L), high density lipoprotein cholesterol (HDL-C, mmol/L), and low density lipoprotein cholesterol (LDL-C, mmol/L).

  • A GWAS performed in Chinese Han population identified three quantitative trait loci (QTL) regulating the adiponectin levels, i.e. rs4783244: rs8047711: and rs7193788 on CDH13 gene [17]. Another GWAS in Singaporean Chinese showed strong associations between CDH13 rs4783244 and adiponectin levels [18]. The minor allele frequency (MAF) of rs8047711 is relatively low. Considering the sample size of the present study, we selected CDH13 rs4783244 and rs7193788 as candidate SNPs.

    DNA was isolated from peripheral venous blood leucocytes. DNA genotyping was performed using time-of-flight mass spectrometry genotyping technology with MassARRAY iPLEX platform (Sequenom Inc, San Diego, California, USA) following the manufacturer's protocol. Genotypes were assessed by MassARRAY®Typer Analyzer version 4.0. The call rates for 2 SNPs were all above 99.0%. A randomly chosen subgroup of 5% of DNA samples went through repeat analysis to verify reproducibility. The results of duplicated samples were 100% consistent.

  • The study design was explained to every subject during recruitment. Every participant gave written informed consent. This project was approved by the Ethics Committee of Peking University Health Science Center, Beijing, China.

  • Adiponectin levels, HMW adiponectin levels and total triglycerides (TG) were analyzed on natural logarithmic scales because of their skewed distribution. Continuous variables were described as mean ± standard deviation and Student t-test was adopted to compare means across groups. Categorical variables were described as frequency and proportion, and Pearson's χ2 test was used for comparisons between groups.

    Hardy-Weinberg equilibrium (HWE) for each SNP was estimated, and no violation was found for any SNP. HWE P-values for all SNPs were shown in Table 3. To avoid reverse causality, we investigated the associations between 2 SNPs and total and HMW adiponectin levels in IS-free individuals and IS patients respectively. Because individuals in each group were unrelated individuals from different pedigrees, these associations were analyzed using linear regression model. Considering the shared genetic backgrounds of full siblings and the compromised individual independence, we applied multi-level mixed-effects regression models to investigate the associations between CDH13 SNPs and IS [28]. We employed Bonferroni correction due to multiple testing. SNPs with P < 0.05/2 = 0.025 were considered significant. We estimated interactions between two SNPs in CDH13 and smoking, drinking, BMI, history of hypertension, history of diabetes for IS by adding multiplicative terms in multi-level mixed-effects regression models. Statistical analyses were performed by STATA (version 13: Stata Corporation, Texas, USA).

RESULTS
  • A total of 342 Chinese Han discordant IS sib pairs consisting of 342 confirmed IS patients and 342 IS-free siblings were enrolled in the present study. The mean age at enrollment for IS patients was 61.09 ± 9.22. The mean age at enrollment for IS-free siblings was 57.52 ± 9.05. The mean age at onset for IS patients was 55.4 ± 9.09. Compared with IS-free siblings, IS patients were older, had a higher proportion of male, and had higher rates of diabetes mellitus and hypertension. IS patients also had higher smoking rate, as well as higher FBG levels, higher TG levels and lower HDL-C levels. The total adiponectin levels of IS patients were lower than IS-free siblings.

    There were no significant differences with respect to alcohol consumption, BMI, TC, LDL-C, and HMW adiponectin levels between IS patients and IS-free siblings (Table 1).

    Items IS IS-free Siblings P
    N 342 342 -
    Age 61.09 ± 9.22 57.52 ± 9.05 < 0.001^
    Male 223 (65.20) 170 (49.71) < 0.001^
    Diabetes mellitus 143 (41.81) 84 (24.56) < 0.001^
    Hypertension 297 (86.84) 213 (62.28) < 0.001^
    Smoker 203 (59.36) 150 (43.86) < 0.001^
    Drinker 127 (37.13) 105 (30.70) 0.063
    BMI 26.37 ± 3.57 26.18 ± 3.55 0.456
    FBG 6.51 ± 2.78 5.98 ± 2.48 0.005^
    TC 4.25 ± 1.23 4.27 ± 1.17 0.810
    ln TG 0.49 ± 0.58 0.36 ± 0.62 0.002^
    HDL-C 1.27 ± 0.44 1.40 ± 0.53 < 0.001^
    LDL-C 2.87 ± 0.86 2.87 ± 0.81 0.969
    ln total adiponectin 8.75 ± 0.89 8.92 ± 0.86 0.035^
    ln HMW adiponectin 7.46 ± 0.74 7.54 ± 0.70 0.180
    Note. Continuous variables were described as mean ± standard deviation. Categorical variables were described as frequency (proportion). IS: ischemic stroke; BMI: body mass index, kg/m2; FBG: fast blood glucose, mmol/L; TC: total cholesterol, mmol/L; ln TG: natural logarithmically transformed total triglycerides, mmol/L; HDL-C: high-density lipoprotein cholesterol, mmol/L; LDL-C: low-density lipoprotein cholesterol, mmol/L; ln total adiponectin: natural logarithmically transformed total adiponectin, ng/mL; ln HMW adiponectin: natural logarithmically transformed high-molecular weight adiponectin, ng/mL. ^P < 0.05.

    Table 1.  Anthropometric, Lifestyle Characteristics and Biochemical Indices of Ischemic Stroke Sib-pairs

    Associations between CDH13 SNPs and Adiponectin Levels In IS-free individuals, rs4783244 T allele was associated with total adiponectin levels (per T allele: Coef = -0.257: P = 0.001) but not HMW adiponectin levels (per T allele: Coef = -0.079 P = 0.204). Compared with rs4783244 GG genotype, GT/TT genotypes were associated with lower total adiponectin levels (GT/TT vs. GG: Coef = -0.265: P = 0.008).

    In IS-free siblings, rs7193788 A allele was associated with total adiponectin levels (per A allele: Coef = -0.221: P = 0.001) and HMW adiponectin levels (per A allele: Coef = -0.163: P = 0.003). Compared with rs7193788 GG genotype, GA/AA genotypes were associated with lower total adiponectin levels (GA/AA vs. GG: Coef = -0.303: P = 0.006) and lower HMW adiponectin levels (GA/AA vs. GG: Coef = -0.222: P = 0.013). However, these associations were not found in IS patients (Table 2).

    SNP Genotype IS Patients IS-free Siblings
    Mean ± SD Coef P* Mean ± SD Coef P*
    Total adiponectin
    rs4783244 per T - -0.062 0.473 - -0.257 0.001^
    GG 8.83 ± 0.97 Ref - 9.05 ± 0.91 Ref -
    GT/TT 8.69 ± 0.83 -0.137 0.241 8.83 ±0.82 -0.265 0.008^
    rs7193788 per A - -0.086 0.302 - -0.221 0.001^
    GG 8.98 ± 0.76 Ref - 9.00 ± 0.86 Ref -
    GA/AA 8.70 ± 0.93 -0.274 0.051 8.71 ± 0.85 -0.303 0.006^
    HMW adiponectin
    rs4783244 per T - -0.034 0.649 - -0.079 0.204
    GG 7.49 ± 0.74 Ref - 7.56 ± 0.76 Ref -
    GT/TT 7.43 ± 0.74 -0.063 0.529 7.53 ± 0.64 -0.073 0.366
    rs7193788 per A - -0.017 0.816 - -0.163 0.003^
    GG 7.46 ± 0.73 Ref - 7.61 ± 0.70 Ref -
    GA/AA 7.43 ± 0.81 -0.037 0.759 7.36 ± 0.66 -0.222 0.013^
    Note. *Adjusting for age, sex, diabetes mellitus, hypertension, smoking status, drinking status, BMI, ln TG, HDL-C. HMW adiponectin: high-molecular weight adiponectin. ^P < 0.05.

    Table 2.  Associations between CDH13 SNPs and Adiponectin Levels in IS patients and IS-free Siblings

    Associations between CDH13 SNPs and Ischemic Stroke CDH13 rs7193788 was significantly associated with IS after Bonferroni correction (α = 0.025). Compared with individuals of rs7193788 GG genotype, those of GA/AA genotypes had higher risks of IS (GA/AA vs. GG: unadjusted: OR = 1.48: 95% CI: 1.05-2.09: P = 0.025, adjusted: OR = 1.55: 95% CI: 1.07-2.24: P = 0.020). No association was found between rs4783244 and IS (Table 3).

    SNP Location MAF HWE P-Value Genotype Unadjusted Adjusted*
    OR 95% CI P OR 95% CI P
    rs4783244 16:82628663 T (0.348) 0.818 GG Ref - - Ref - -
    GT/TT 1.05 0.79: 1.40 0.736 1.09 0.80: 1.49 0.582
    rs7193788 16:82622555 G (0.478) 0.666 GG Ref - - Ref - -
    GA/AA 1.48 1.05: 2.09 0.025^ 1.55 1.07: 2.24 0.020^
    Note. *Adjusting for age, sex, diabetes mellitus, hypertension, smoking status, drinking status, BMI, lnTG, HDL-C. MAF: minor allele frequency. ^P < 0.05.

    Table 3.  Associations between CDH13 SNPs and Ischemic Stroke

    Interactions between CDH13 SNPs and Other Risk Factors for IS We investigated interactions between 2 CDH13 SNPs and smoking, drinking, BMI, history of hypertension, history of diabetes for IS. We observed a statistically significant interaction between CDH13 rs7193788 and diabetes (P = 0.036). Compared to diabetes-free individuals with rs7193788 GG genotype, diabetes patients with rs7193788 GA/AA genotypes had higher risks for IS (unadjusted: OR = 3.17: 95% CI: 1.96-5.12: P < 0.001, adjusted: OR = 2.64: 95% CI: 1.58-4.40: P < 0.001)

    No interaction was found between CDH13 rs4783244 and diabetes for IS (P = 0.268). However, compared to diabetes-free individuals with rs4783244 GG genotype, diabetes patients with rs4783244 GT/TT genotypes had higher risks for IS (Unadjusted: OR = 2.50: 95% CI: 1.62-3.86: P < 0.001, adjusted: OR = 2.03: 95% CI: 1.27-3.24: P = 0.003) (Table 4).

    Diabetes Genotype Unadjusted Adjusted P for Interaction
    OR 95% CI P* OR 95% CI P*
    rs4783244
    No GG Ref - - Ref - - 0.268
    GT/TT 0.96 0.67: 1.37 0.825 0.99 0.67: 1.45 0.941
    Yes GG 1.78 1.12: 2.83 0.015^ 1.53 0.93: 2.52 0.092
    GT/TT 2.50 1.62: 3.86 < 0.001^ 2.03 1.27: 3.24 0.003^
    rs7193788
    No GG Ref - - Ref - - 0.036^
    GA/AA 1.19 0.78: 1.83 0.421 1.20 0.76: 1.89 0.425
    Yes GG 1.30 0.68: 2.46 0.424 1.12 0.57: 2.21 0.735
    GA/AA 3.17 1.96: 5.12 < 0.001^ 2.64 1.58: 4.40 < 0.001^
    Adjusting for age, sex, hypertension, smoking status, drinking status, BMI, lnTG, HDL-C. ^P < 0.05.

    Table 4.  Interactions between CDH13 SNPs and Diabetes for Ischemic Stroke

DISCUSSION
  • The present study explored the relationships between 2 CDH13 genetic polymorphisms (rs4783244 and rs7193788), adiponectin levels and ischemic stroke. We also discussed the interactions between SNPs and other risk factors for IS. The results suggested significant associations between 2 SNPs and adiponectin levels, an association between rs7193788 and IS, and an interaction between rs7193788 and history of diabetes for IS.

    Adiponectin is a secretory adipocyte-derived endocrine with antiatherogenic and anti-inflamatory properties [29-30]. Adiponectin exists in two forms in serum, as lower molecular weight (LMW) species or as high molecular weight (HMW) complex consisting of 12-18 subunits [31]. HMW adiponectin is biologically active. HMW-to-total adiponectin ratio is a good determinant of glucose intolerance or insulin sensitivity [32-33]. Adiponectin levels were associated with genetic polymorphisms. Genome-wide association studies (GWAS) identified several SNPs located on CDH13 gene as possible causal factors in Asian populations. CDH13 is the coding gene for T-cadherin, which is a receptor for hexameric and HMW adiponectin and is mainly expressed in endothelial and smooth muscle cells [20]. We observed the associations between CDH13 polymorphisms and total and HMW adiponectin levels in IS-free siblings but not IS patients, indicating that the onset of IS may have a significant influence on adiponectin levels.

    rs4783244 located in intron 1 of the CDH13 gene. rs7193788 located in promoter region of CDH13 gene. A GWAS in Chinese Han population suggested that G allele of rs4783244 and G allele of rs7193788 were associated with higher adiponectin levels [17]. In another GWAS concerning Singaporean Chinese, rs4783244 showed strong associations both with total adiponectin levels and HMW adiponectin levels [18]. We replicated these findings in the present sib pair study. Otsuka et al. found an association between schizophrenia and a GACAG haplotype consisted of rs7193788 and four other SNPs in promoter region of CDH13. The nucleotide substitutions in this region might influence the transcriptional activity of CDH13 promoter [34]. This potential biological function of rs7193788 might be an explanation for its associations with total and HMW adiponectin levels found in our study.

    Although adiponectin was associated with traditional cardiovascular risk factors, the association between adiponectin and ischemic stroke remained controversial [35-40]. Adiponectin levels can be influenced by many changeable factors, which made it hard to eliminate the effect of environmental confounders in cross-sectional studies. To verify the causal relationship between adiponectin and IS, it was reasonable to discuss the associations between adiponectin related genetic polymorphisms and IS. ADIPOQ rs266729 was a well-studied SNP which showed an association with decreased risk of ischemic stroke [41-42]. 6 SNPs in ADIPOQ gene were associatied with IS risk in Korean population [21]. Chung et al. reported that rs4783244 was associated with ischemic stroke in Chinese population [17]. However, we didn't draw the same conclusion in the present study. Instead, we found that rs7193788 was associated with IS. Individuals with rs7193788 GA/AA genotypes endured lower adipone ctin levels, and had higher risks of IS compared with individuals with GG genotypes, which was compatible with the hypothesis that CDH13 genetic polymorphisms can impact the risk of ischemic stroke through its influence on adiponectin levels.

    Interactions between CDH13 polymorphisms and environmental factors were studied before. Jo et al. observed that the association between CDH13 and adiponectin can be modified by smoking and obesity. Obese smokers with risk CDH13 rs3865188 polymorphisms were at 6.2-fold higher risk for hypoadiponectinemia [43]. Chung et al. reported an interaction between CDH13 rs4783244 and sex for HOMA-IR/T2DM. However, no interactions were found between rs4783244 and smoking for T2DM or stroke [17]. Diabetes impairs endothelium function and augments the formation of atherosclerotic lesions [44]. The presence of diabetes can significantly increase the risk of stroke [45-46]. Adiponectin played a vascular protective role by preserving endothelial cell function [47]. It is of value to discuss the joint effect of CDH13 SNPs and diab etes for IS. An interaction between rs7193788 and diabetes for IS was found in this study. Individuals with rs7193788 risk genotypes, as well as diabetes, had higher risks of IS.

    The present study applied a sib pair design. This design provided resistance to problems associated with population stratification that can occur in case-control studies, while the unique family-based design lowered the possibility of false positive discoveries [48]. We applied multi-level mixed-effects regression model to analyze sib pair data, for it can gain more power than traditional family based algorithms. Considering the limited sample size, using multi-level mixed-effects regression model may increase the possibility of true positive discoveries.

    However, there were still some limitations. The main limitation of this study was its sample size. The small sample size could decrease statistical power. However, because of the strict recruitment requirement of eligible patients and full siblings, sib pair studies are far more difficult and expensive to undertake than case control studies [23]. Second, considering the small sample size, we didn't analyze the relationships between SNPs and IS subtypes. The associations between adiponectin and different etiologic subtypes of IS may be different, for low adiponectin levels were found to be significantly associated with increased risk of large artery atherosclerosis (LAA) stroke but not non-LAA stroke [49]. Third, given the cross-sectional nature of our data, the relationships between adiponectin levels and IS were not analyzed. Thus, further studies will be needed to confirm the results.

CONCLUSIONS
  • CDH13 genetic polymorphisms are associated with adiponectin levels in IS free individuals. CDH13 rs7193788 is associated with IS. An interaction is found between CDH13 SNP and diabetes for IS.

ACKNOWLEDGMENTS
  • We are grateful to the participants, the FISSIC study group, field staffs and volunteers, doctors from the First Hospital of Fangshan District, Liangxiang Hospital of Fangshan District, Traditional Chinese Medicine Hospital of Fangshan District, 401 Hospital of China Nuclear Industry and Peking University Third Hospital.

CONFLICTS OF INTEREST
  • The authors declare no conflict of interest.

Reference (49)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return