Apolipoprotein E Gene Polymorphism Effects on Lipid Metabolism and Risk of Cerebral Infarction in Northwest Han Chinese Population

Apolipoprotein E Gene Polymorphism Effects on Lipid Metabolism and Risk of Cerebral Infarction in Northwest Han Chinese Population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Apolipoprotein E Gene Polymorphism Effects on Lipid Metabolism and Risk of Cerebral Infarction in Northwest Han Chinese Population Wenbing Ma, Liting Zhang, Shuang Yang, Suya Zhang, Haiyan Dong, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1094744/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The apolipoprotein E (ApoE) genetic variation may be involved in the development of Cerebral Infarction (CI). Serum lipid levels are known risk factors for CI, but the effect of the ApoE gene polymorphism on lipid metabolism remains unclear. This retrospective cohort study aimed to determine the role of ApoE genotypes in CI risk and the relationships between ApoE gene polymorphism and serum lipid levels among the population of northwest China. patients and methods: 517 CI patients and 517 non-CI controls were enrolled in the study. Polymerase chain reaction and hybridization were used to test the ApoE gene polymorphisms. results: Patients with CI had a significantly higher frequency of ε3/ε4 genotype (OR =2.057, 95% CI = 1.477–2.864, P <0.001) and ε4 allele (OR =1.818, 95% CI = 1.364–2.424, P <0.001) than control participants. When stratifying by age and sex, it was found that statistically significant differences in the distribution and frequencies of the ε3/ε4 genotype(OR =3.067, 95% CI = 1.675–5.614, P 60 years and OR =2.206, 95% CI = 1.474–3.301, P <0.001 in males) and ε4 allele (OR =1.709, 95% CI = 1.201–2.432, P =0.001) in males and ε4 allele (OR =2.072, 95% CI = 1.281–3.353, P =0.003 in age ≤60 years; OR =1.704, 95% CI = 1.189–2.444, P =0.003 in age>60 years; OR =1.709, 95% CI = 1.201–2.432, P =0.001 in males and OR =2.046, 95% CI = 1.246–3.361, P =0.004 in females ) were observed between patients and controls. ε4 carriers had significantly lower ApoE level and higher low-density lipoprotein cholesterol (LDL-C), ApoB and ApoB/ApoA-I levels than ε2 carriers in both two groups. Additionally, control participants with ε4 carriers had significantly higher levels of lipoprotein and lower total cholesterol (TC) levels than ε2 carriers, CI patients with ε4 carriers had significantly lower level of ApoA-I than ε2 carriers. After adjusting for other established risk factors, drinking, hypertension, lipoprotein, triglycerides (TG) and ε4 allele were significant independent risk factor for CAD. ε4 allele presence was associated with a nearly two-fold higher CI risk. Conclusions: This study provides evidence that ε4 allele, drinking, hypertension, lipoprotein and TG levels are independent risk factor for CI among patients in Northwest China. Also, these data might be clinically useful in allowing for more individualized preventive and therapeutic strategies. Cardiac & Cardiovascular Systems Endocrinology & Metabolism Apolipoprotein E Cerebral Infarction Gene polymorphism Northwest China Introduction CI also called ischemic stroke and is the most commonly reported cerebral vascular diseases, accounting for 70–80% of all strokes[ 1 ]. CI is a complex disease caused by multiple susceptibility genes and environmental factors[ 2 ]. A number of candidate genes have been investigated in CI through association studies, but with controversial results[ 3 ]. Recently, mounting evidence indicates that ApoE is a candidate gene in the development of CI. ApoE is an arginine-rich alkaline protein, which is present in plasma chylomicron, low-density lipoprotein and very low-density lipoprotein[ 4 ]. In humans, the APOE gene is located at chromosome 19q13.2 and is also found to be extensively expressed in the brain. Genotypes were also determined for the two functional single nucleotide polymorphisms (SNPs) rs429358 (388T > C) and rs7412 (526C > T), resulting in three different alleles (ε2, ε3 and ε4) and six different genotypes (ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4 and ε4/ε4). ApoE plays an important role in cholesterol transport, plasma lipoprotein metabolism and thus affects the serum lipid profiles in the body[ 4 ]. Several studies indicate that ε4 allele was associated with significantly higher serum TC and LDL-C and it thereby contributes to the increasing burden of cardiovascular diseases, including CI[ 5 ]. Although the mechanism responsible for the association between ApoE polymorphisms and CI, but the exact mechanism is still controversial. The distribution of ApoE allele frequencies can vary across different ethnic groups [ 6 ]. Furthermore, there are no studies that have addressed the relationship between ApoE polymorphism and the risk of developing CI in the Northwest of China. Therefore, the aim of the present study was to investigate the role of ApoE genotypes in the risk of CI in Northwest Chinese Han population. Methods Subjects A total of 517 Chinese CI patients (males: females = 344:173) and 517 controls (males: females = 332:185) were enrolled into the study. These two groups were gender and age matched. All participants were enrolled from May 2018 to May 2019 in the First Affiliated Hospital of Xi’an Jiao Tong University. Most of the study participants are ethnically Han Chinese and residents living in Northwest China. The demographic and clinical characteristics of study participants are presented in Table 1 . Diagnostic criteria of CI patients were as referred to in the Fourth National Cerebrovascular Disease Conference of China, and the diagnosis was confirmed by computed tomography or Magnetic Resonance Imaging. The exclusion criteria were as follows: patients with malignancy, autoimmune disease, chronic kidney disease, and incomplete heart function. This study was approved by the Ethical Committee of the First Affiliated Hospital of Xi’an Jiao Tong University and we got the informed consent of each patients. Table 1 Characteristics of the Study Population Factors Controls CI P value Age(years) 61.26±14.29 61.52±11.24 0.742 a Males/Females 332/185 344/173 0.472 b Smoking 187(36.17%) 189(36.56%) 0.948 b Drinking 99(19.15%) 142(27.47%) 0.002 b Diabetes 119(23.02%) 162(31.33%) 0.003 b Hypertension 265(51.26%) 356(68.86%) <0.001 b TC 3.78±0.86 3.81±0.92 0.560 a HDL 1.03±0.26 1.02±0.25 0.416 a LDL-C 2.19±0.73 2.21±0.79 0.740 a TG 1.37±0.76 1.50±0.95 0.011 a Cr 69.14±53.10 67.39±34.97 0.552 a Apolipoprotein A 1.15±0.21 1.15±0.20 0.994 a Apolipoprotein B 0.74±0.20 0.75±0.20 0.175 a ApoB/ApoA 0.66±0.28 0.67±0.21 0.321 a Apolipoprotein E 36.89±13.97 35.58±14.10 0.135 a Lipoprotein 194.88±202.30 211.94±205.38 0.179 a DB 4.71±4.72 4.50±2.37 0.395 a IB 9.15±4.79 9.13±4.75 0.996 a CI: cerebral infarction, TC: total cholesterol, HDL: high-density lipoproteins, LDL-C: low-density lipoprotein cholesterol, TG: triglyceride, Cr: creatinine, DB: direct bilirubin, IB: indirect bilirubin aP values were calculated by Student’s t-tests. bP values were calculated from two-sided chi-square test. DNA extraction and genotyping Blood samples from each participant were obtained from the cubital vein and collected in tubes containing ethylene diamine tetra acetic acid (EDTA). Genomic DNA was extracted using DNA isolation kits (Sinochips Bioscience Co., Ltd., Zhuhai, Guangdong, China) for peripheral blood and stored at -20°C. The genotypes of ApoE were detected using a commercially available kit (Sinochips Bioscience Co., Ltd., Zhuhai, Guangdong, China). PCR analysis was performed according to the manufacturer’s instructions: 50°C for two minutes, pre-denaturation at 95°C for 15 minutes, followed by 45 cycles at 94°C for 30 seconds and 65°C for 45 seconds. PCR products were then reversely hybridized with gene chip technology. Finally, we used a gene chip scanner to help interpret the data. Statistical analyses Data analysis was performed using SPSS statistical software version 16.0. Continuous variable data are presented as means ± standard deviation and as numbers and percentages for categorical variables. Student's t test and χ2 test were initially used to test the difference between CI and control groups. ApoE genotype and allele frequencies were tested for Hardy-Weinberg equilibrium by chi-square test. The chi-square test and ANOVA were used to analyze the association between specific ApoE genotypes and clinical characteristics. Logistic regression analysis was used to assess the interactions between ApoE genotypes and various factors. A value of p<0.05 was considered statistically significant. Results Baseline clinical characteristics of the CI and control groups Baseline clinical characteristics of the patients with CI and control groups are summarized in Table 1 . A total of 517 Chinese patients with CI, consisting of 344 males and 173 females aged 26-91 years (mean=61.52 years, SD=11.24), and 517 controls participants, comprising 332 males and 185 females aged 23-93 years (mean=61.26 years, SD=14.29), were included in the present study. Most of the study participants originate from northwest China. Age and sex distribution were not significantly different between the two groups ( P =0.742 and 0.472, respectively). The proportions of drinking ( P =0.002), hypertension ( P =0.003) and diabetes ( P <0.001) were significantly higher in the CI group than in the control group. TG level was significantly higher in the CI group compared to the control group ( P =0.011), no significant differences were found in TC, high-density lipoprotein (HDL), LDL-c, creatinine (Cr), ApoA-I, ApoB, ApoB/A-I, ApoE, lipoprotein, direct bilirubin (DB) and indirect bilirubin (IB) levels between the two groups (all P > 0.05). Allele And Genotype Frequencies Of Apoe And Ci Risk The distribution of the ApoE genotype and allele frequencies in CI cases and control subjects is summarized in Table 2 . The genotype distribution of this polymorphism in patients with CAD and control participants was in concordance with Hardy-Weinberg equilibrium ( P = 0.45 and 0.50, respectively). Genotype ε3/ε3 (63.8%) was the most common type in CI groups, followed by ε3/ε4 (22.8%), ε2/ε3 (9.9%), ε4/ε4 (1.5%), ε2/ε4 (1.2%), and ε2/ε2 (0.8%), whereas those in control participants were ε3/ε3 (71.0%), followed by ε2/ε3 (13.3%), ε3/ε4 (12.6%), ε2/ε4 (2.1%), ε4/ε4 (0.6%) and ε2/ε2 (0.4%). The allele frequency of ε2, ε3, and ε4 was 6.3%, 80.2% and 13.5% respectively in patients with CI; 8.1%, 83.9% and 7.9% respectively in control participants. The distribution of ApoE genotypes and alleles in the two groups was significantly different (χ2=24.424 and P <0.001, χ2=18.472 and P <0.001, respectively). Table 2 The distributions of genotypes and alleles of the ApoE gene in the CAD patients and controls Genotype, n (%) CI group(n=617) Control group(n=308) OR (95% CI) P a χ2 P E2/E2 4(0.8%) 2(0.4%) 2.010(0.366,11.010) 0.687 24.424 0.000 E2/E3 51(9.9%) 69(13.3%) 0.711(0.484,1.044) 0.099 E2/E4 6(1.2%) 11(2.1%) 0.540(0.198,1.472) 0.328 E3/E3 330(63.8%) 367(71.0%) 0.721(0.555,0.937) 0.017 E3/E4 118(22.8%) 65(12.6%) 2.057(1.477,2.864) 0.000 E4/E4 8(1.5%) 3(0.6%) 2.693(0.710,10.208) 0.224 HWE χ2 = 3.70, P = 0.45 χ2 = 3.33, P =0.50 Alleles, n (%) E2 65(6.3%) 84(8.1%) 0.759(0.542,1.062) 0.126 18.472 0.000 E3 829(80.2%) 868(83.9%) 0.773(0.617,0.969) 0.029 E4 140(13.5%) 82(7.9%) 1.818(1.364,2.424) 0.000 CI: cerebral infarction, HWE: Hardy-Weinberg equilibrium. a p and OR (95% CI) values were calculated by logistic regression adjusted for age, gender, and traditional cardiovascular risk factors. b p values were calculated from two-sided chi-square tests or Fisher’s exact tests. The frequencies of ε3/ε4 genotype (OR =2.057, 95% CI = 1.477–2.864, P <0.001) and ε4 allele (OR =1.818, 95% CI = 1.364–2.424, P <0.001) were significantly higher in CI patients than in control participants. Further, patients with CAD had a significantly lower ε3/ε3 (OR =0.721, 95% CI = 0.555–0.937, P =0.017) genotype and ε3 allele (OR =0.773, 95% CI = 0.617–0.969, P =0.029) frequencies than did the control participants. (P 60 years) and sex. The results showed that ε3/ε4 frequency was significantly higher in patients with CI compared to the control participants (OR =3.067, 95% CI = 1.675–5.614, P 60 years and OR =2.206, 95% CI = 1.474–3.301, P <0.001 in males), but not in females (OR =1.746, 95% CI = 0.973–3.134, P =0.078). Additionally, the variance in allele ε4 between patients with CI and controls was also statistically significant (OR =2.072, 95% CI = 1.281–3.353, P =0.003 in age ≤60 years; OR =1.704, 95% CI = 1.189–2.444, P =0.003 in age>60 years; OR =1.709, 95% CI = 1.201–2.432, P =0.001 in males and OR =2.046, 95% CI = 1.246–3.361, P =0.004 in females) (Table 3 ). Relationships between serum lipid profile and ApoE alleles. Table 4 describe the association between serum lipid profiles and allelic carrier status (ε2, ε3 and ε4 groups). Participants with ε2/ε4 genotype (n= 17) were excluded because play opposing roles in lipid metabolism and the incidence of CI. In the patients with CAD, ε4 carriers had significantly higher LDL-C, ApoB and ApoB/ApoA-I and lower levels of ApoA-I and ApoE levels than ε2 carriers. LDL-C, ApoB, ApoB/ApoA-I and ApoE levels of the control participants showed similar trends to those in CI groups. Additionally, control participants with ε4 carriers had significantly higher levels of lipoprotein and TC levels than ε2 carriers. Table 4 Relationships between serum lipid profile and ApoE allele in CI patients and control participants CI patient Control participants Factors ε2(ε2ε2 + ε2ε3) ε3(ε3) ε4(ε3ε4 + ε4ε4) P a P b P c P d ε2(ε2ε2 + ε2ε3) ε3(ε3) ε4(ε3ε4 + ε4ε4) P a P b P c P d TC 3.59±0.87 3.86±0.94 3.78±0.90 0.112 0.046 0.423 0.183 3.55±0.87 3.82±0.84 3.85±0.93 0.043 0.014 0.822 0.042 HDL 1.07±0.26 1.02±0.24 1.00±0.27 0.220 0.208 0.329 0.107 1.01±0.21 1.04±0.27 1.04±0.27 0.620 0.326 0.923 0.466 LDL-C 1.89±0.54 2.27±0.82 2.18±0.79 0.004 0.001 0.266 0.014 1.98±0.77 2.23±0.71 2.29±0.77 0.023 0.009 0.589 0.043 TG 1.55±1.23 1.45±0.80 1.61±1.16 0.245 0.435 0.090 0.740 1.55±0.84 1.36±0.76 1.23±0.60 0.039 0.057 0.184 0.011 Cr 64.91±20.61 67.69±36.85 68.36±34.85 0.854 0.622 0.870 0.537 65.53±21.07 70.03±60.95 69.91±26.78 0.820 0.553 0.987 0.302 Apolipoprotein A 1.26±0.23 1.16±0.20 1.12±0.21 0.000 0.002 0.061 0.000 1.17±0.18 1.16±0.21 1.13±0.22 0.514 0.710 0.139 0.263 Apolipoprotein B 0.64±0.14 0.77±0.20 0.77±0.21 0.000 0.000 0.944 0.000 0.66±0.21 0.75±0.20 0.76±0.21 0.001 0.000 0.535 0.003 ApoB/ApoA 0.54±0.14 0.68±0.21 0.70±0.20 0.000 0.000 0.274 0.000 0.56±0.20 0.67±0.31 0.68±0.21 0.012 0.005 0.807 0.001 Apolipoprotein E 49.03±21.64 34.61±10.89 32.04±14.05 0.000 0.000 0.039 0.000 50.24±17.97 34.99±11.75 32.11±12.09 0.000 0.000 0.066 0.000 Lipoprotein 215.81±213.97 210.85±207.31 212.14±201.12 0.986 0.870 0.952 0.912 133.86±109.56 203.59±216.48 213.16±182.36 0.021 0.008 0.732 0.002 DB 4.58±2.26 4.45±2.25 4.58±2.74 0.863 0.729 0.626 0.990 4.73±2.50 4.65±5.19 5.14±4.14 0.737 0.904 0.460 0.472 IB 9.08±5.26 9.14±4.58 9.13±5.12 0.998 0.943 0.991 0.959 9.14±4.41 9.06±4.79 9.78±5.04 0.526 0.890 0.263 0.434 CI: cerebral infarction, TC: total cholesterol, HDL: high-density lipoproteins, LDL-C: low-density lipoprotein cholesterol, TG: triglyceride, Cr: creatinine, DB: direct bilirubin, IB: indirect bilirubin a p value shows the differences compared between groups (ε2, ε3, ε4) b p values obtained when comparing ε2 subjects with ε3 subjects. c p values obtained when comparing ε4 subjects with ε3 subjects. d p values obtained when comparing ε2 subjects with ε4 subjects. Logistic Regression Analysis Of Ci Risk Factors We performed a multivariate logistic regression analysis to identify which variables with statistical significance from the univariate analysis could act as independent predictors of CI. Univariate logistic analysis showed that drinking (OR =1.701, 95% CI = 1.167–2.478, P =0.006), hypertension (OR =1.885, 95% CI = 1.417–2.508, P< 0.001), ApoE levels (OR =0.983, 95% CI = 0.969–0.997, P =0.017), lipoprotein (OR =1.001, 95% CI = 1.000–1.001, P =0.046), TG (OR =1.363, 95% CI = 1.035–1.797, P =0.028) and ε4 allele (OR =1.954, 95% CI = 1.359–2.810; P60 years) and sex, multivariate logistic regression analysis stratified according to age and sex was performed. In both age groups, ε4 carriers were associated with increased risk of CI (age ≤60 years: OR = 2.970, 95% CI = 1.553–5.678, P = 0.001; age >60 years: OR = 1.715, 95% CI = 1.082–2.719, P = 0.022). Also, ε4 carriers was significantly associated with a higher risk of CI in males (OR =2.182, 95% CI = 1.398–3.407, P =0.022), but not in females (OR =1.500, 95% CI = 0.779–2.887, P =0.225) (Table 6 ). Table 5 Logistic regression analysis of the risk of CI in Northwest of China population. Variables P- value OR (95% CI) Drinking 0.006 1.701(1.167-2.478) Hypertension 0.000 1.885(1.417-2.508) Lipoprotein 0.046 1.001(1.000-1.001) TG 0.028 1.363(1.035-1.797) ApoE 0.017 0.983(0.969-0.997) ε4 0.000 1.954(1.359-2.810) CI: cerebral infarction, TG: triglyceride Table 6 Multiple logistic regression analysis for CI patients and control subjects ε4 OR (95% CI) P -value Age≤60 2.970(1.553-5.678) 0.001 Age༞60 1.715(1.082-2.719) 0.022 males 2.182(1.398-3.407) 0.001 females 1.500(0.779-2.887) 0.225 Study Strength And Limitations The strength of this study is that this is the first study about the relationship of CI and ApoE gene polymorphism in Northwest Han Chinese population. Association of lipid levels with ApoE gene polymorphisms included in the final analysis and have excluded confounding factors or comorbidities affecting the results. There were some inherent limitations presented in our study. (1) Most ofthe present participants may receive lipid-lowering therapy at the time of inclusion, which may have potential impacts on the association of blood lipid profiles with adverse events. (2) As this is a large retrospective study, original data shortage constrained assessment of potential gene-environment interactions. (3) The small sample size of this study, which may lead to the instability of the results to some extent. (4) The study was conducted only in northwest Chinese populations, and whether these findings will also be true in other populations needs further investigation. Conclusions In conclusion, the present study suggests that ɛ4 allele is associated with CI in the Northwest Han Chinese population. When stratifying by age and sex, it was found that statistically significant differences in the distribution and frequencies of the ε3/ε4 genotype and ε4 allele in males and ε4 allele in females were observed between patients and controls; ε4 allele was a significant and independent risk factors in elderly and young patients. ApoE gene polymorphisms may be related to lipid metabolism in patients with CI. Since the limited sample size, and thus further studies with larger sample population are needed to clear our findings. Abbreviations ApoE apolipoprotein E CI cerebral infarction TC total cholesterol HDL high-density lipoproteins LDL-C low-density lipoprotein cholesterol TG triglyceride Cr creatinine DB direct bilirubin IB indirect bilirubin HWE Hardy-Weinberg equilibrium Declarations Acknowledgments We gratefully acknowledge all sample donors who participated in this study. Authors’ contributions Wenbing Ma and Xiaoyun Lu conceived and designed the experiments; Wenbing Ma and Weiyi Feng contributed to the writing of the manuscript. Liting Zhang, Shuang Yang, Houli Li and Suya Zhang recruited subjects and collected clinical data. Haiyan Dong and Weihua Dong helped to analyze the data. All authors read and approved the final manuscript. Funding This work was supported by the Key R & D Plan Projects in Shaanxi Province (grant number 2021-SF-130) and the Foundation of the First Affiliated Hospital of Xi'an Jiaotong University (grant number 2020ZYTS-08). Availability of data and materials All data generated or analyzed during this study are included in this published article. Ethics approval and consent to participate This study was approved by the Ethical Committee of the First Affiliated Hospital of Xi’an Jiao Tong University and we got the informed consent of each patients. Consent for publication Not applicable. 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Enas EA, Varkey B, Dharmarajan TS, Pare G, Bahl VK: Lipoprotein(a): An independent, genetic, and causal factor for cardiovascular disease and acute myocardial infarction. Indian Heart J. 2019;71:99–112. Koschinsky ML, Marcovina SM: Structure-function relationships in apolipoprotein(a): insights into lipoprotein(a) assembly and pathogenicity. Curr Opin Lipidol. 2004;15:167–174. Gaw A, Murray HM, Brown EA, Grp PS: Plasma lipoprotein(a) Lp(a) concentrations and cardiovascular events in the elderly: evidence from the prospective study of pravastatin in the elderly at risk (PROSPER). Atherosclerosis. 2005;180:381–388. Sun L, Li ZH, Zhang HY, Ma AQ, Liao YH, Wang DW, Zhao BR, Zhu ZM, Zhao JZ, Zhang Z, et al: Pentanucleotide TTTTA repeat polymorphism of apolipoprotein(a) gene and plasma lipoprotein(a) are associated with ischemic and hemorrhagic stroke in Chinese - A multicenter case-control study in China. Stroke.2003;34:1617–1622. Jurgens G, Taddeipeters WC, Koltringer P, Petek W, Chen Q, Greilberger J, Macomber PF, Butman BT, Stead AG, Ransom JH: lipoprotein (A) serum concentration AND apolipoprotein (A) phenotype correlate with severity AND presence of ischemic cerebrovascular disease. Stroke. 1995;26:1841–1848. Lv P, Jin HQ, Liu YY, Cui W, Peng Q, Liu R, Sun W, Fan CH, Teng YM, Sun WP, Huang YN: Comparison of Risk Factor between Lacunar Stroke and Large Artery Atherosclerosis Stroke: A Cross-Sectional Study in China. PLoS One. 2016;11:e0149605. Woltjer RL, Reese LC, Richardson BE, Tran H, Green S, Pham T, Chalupsky M, Gabriel I, Light T, Sanford L, et al: Pallidal neuronal apolipoprotein E in pantothenate kinase-associated neurodegeneration recapitulates ischemic injury to the globus pallidus. Mol Genet Metab. 2015;116:289–297. Wang Z, Xia Y, Zhao Y, Chen L, Zhu Y: Intestinal gutsfeature and role of ApoE and glucose metabolism in cerebral infarction patients. Int J Clin Exp Pathol. 2017;10:561–565. Tascilar N, Dursun A, Ankarali H, Mungan G, Sumbuloglu V, Ekem S, Bozdogan S, Baris S, Aciman E, Cabuk F: Relationship of apoE polymorphism with lipoprotein(a), apoA, apoB and lipid levels in atherosclerotic infarct. J Neurol Sci. 2009;277:17–21. Chou Y-C, Chan P-C, Yang T, You S-L, Bai C-H, Sun C-A: Apolipoprotein B Level and the Apolipoprotein B/Apolipoprotein A-I Ratio as a Harbinger of Ischemic Stroke: A Prospective Observation in Taiwan. Cerebrovasc Dis. 2020;49:487–494. Table Due to technical limitations, table 3 is only available as a download in the Supplemental Files section. Supplementary Files Table3.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1094744","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":65462479,"identity":"1c15c7dd-6dfa-4577-96b2-5fa855461afa","order_by":0,"name":"Wenbing Ma","email":"","orcid":"https://orcid.org/0000-0002-7053-8362","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wenbing","middleName":"","lastName":"Ma","suffix":""},{"id":65462480,"identity":"cdfe4eb0-1dda-4bbe-a3c6-77d988321bb6","order_by":1,"name":"Liting Zhang","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Liting","middleName":"","lastName":"Zhang","suffix":""},{"id":65462481,"identity":"20bcc7f8-5bf5-4e72-a051-4097078287ce","order_by":2,"name":"Shuang Yang","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Yang","suffix":""},{"id":65462482,"identity":"a2d489a9-6daa-490d-aea6-6d276f028e64","order_by":3,"name":"Suya Zhang","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Suya","middleName":"","lastName":"Zhang","suffix":""},{"id":65462483,"identity":"e4d18c9b-c06e-47f1-a9f7-f2d89309f4bf","order_by":4,"name":"Haiyan Dong","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Haiyan","middleName":"","lastName":"Dong","suffix":""},{"id":65462484,"identity":"e08c238c-d836-4b18-8414-7bbd6170ea16","order_by":5,"name":"Houli Li","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Houli","middleName":"","lastName":"Li","suffix":""},{"id":65462485,"identity":"107037cc-68dc-4fea-9334-5655f2f97101","order_by":6,"name":"Weihua Dong","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weihua","middleName":"","lastName":"Dong","suffix":""},{"id":65462486,"identity":"80671b08-3211-45c4-aad7-cf12c381b38a","order_by":7,"name":"Xiaoyun Lu","email":"","orcid":"","institution":"The First Affliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoyun","middleName":"","lastName":"Lu","suffix":""},{"id":65462487,"identity":"ed7a0da5-2ce1-4dd6-9bb1-560564d99a8c","order_by":8,"name":"Weiyi Feng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYLACxgYJBgb2BgYDBga5BCDfgEgtPAcYDA4wGBOtBUhIABUTpUW3/Yzh48IdFnnykW8Mij+2GeQxsDdvk2CouYNTi9mZHGPjmWckig1vpyUYHGwzKGbgOVYmwXDsGW4tB3K3SfO2SSRunJ18AKjlT2KDRI6ZBGPDYdxazr/d/husZebBBpAtiQ3ybwhouZG7jRmkZb4E8wGIFgkeQlref5bmPSORuIEH6Jcz5wwS23jSii0SjuFzWFriZ94ddYnz28+YGVSUGST2sx/eeONDDW4tcACMRjZwfLCBiATCGhgY5BsYmB8Qo3AUjIJRMApGHgAAvXxaDn+5yHkAAAAASUVORK5CYII=","orcid":"","institution":"Xi'an Jiaotong University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Weiyi","middleName":"","lastName":"Feng","suffix":""}],"badges":[],"createdAt":"2021-11-19 06:55:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1094744/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1094744/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":16384801,"identity":"81403324-da50-4597-b5ee-3823679876a4","added_by":"auto","created_at":"2021-12-13 05:29:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":365776,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1094744/v1/9e174028-8ed6-445d-99bb-11a1cd9d4fd4.pdf"},{"id":16018348,"identity":"e79207c1-a977-41e3-aa46-cf6cfcabdc9c","added_by":"auto","created_at":"2021-11-30 15:23:58","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15572,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.docx","url":"https://assets-eu.researchsquare.com/files/rs-1094744/v1/f184724c490f8e08e320407c.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eApolipoprotein E Gene Polymorphism Effects on Lipid Metabolism and Risk of Cerebral Infarction in Northwest Han Chinese Population\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCI also called ischemic stroke and is the most commonly reported cerebral vascular diseases, accounting for 70\u0026ndash;80% of all strokes[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. CI is a complex disease caused by multiple susceptibility genes and environmental factors[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A number of candidate genes have been investigated in CI through association studies, but with controversial results[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecently, mounting evidence indicates that ApoE is a candidate gene in the development of CI. ApoE is an arginine-rich alkaline protein, which is present in plasma chylomicron, low-density lipoprotein and very low-density lipoprotein[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In humans, the APOE gene is located at chromosome 19q13.2 and is also found to be extensively expressed in the brain. Genotypes were also determined for the two functional single nucleotide polymorphisms (SNPs) rs429358 (388T \u0026gt; C) and rs7412 (526C \u0026gt; T), resulting in three different alleles (ε2, ε3 and ε4) and six different genotypes (ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4 and ε4/ε4). ApoE plays an important role in cholesterol transport, plasma lipoprotein metabolism and thus affects the serum lipid profiles in the body[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Several studies indicate that ε4 allele was associated with significantly higher serum TC and LDL-C and it thereby contributes to the increasing burden of cardiovascular diseases, including CI[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although the mechanism responsible for the association between ApoE polymorphisms and CI, but the exact mechanism is still controversial. The distribution of ApoE allele frequencies can vary across different ethnic groups [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Furthermore, there are no studies that have addressed the relationship between ApoE polymorphism and the risk of developing CI in the Northwest of China. Therefore, the aim of the present study was to investigate the role of ApoE genotypes in the risk of CI in Northwest Chinese Han population.\u003c/p\u003e "},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eA total of 517 Chinese CI patients (males: females = 344:173) and 517 controls (males: females = 332:185) were enrolled into the study. These two groups were gender and age matched. All participants were enrolled from May 2018 to May 2019 in the First Affiliated Hospital of Xi\u0026rsquo;an Jiao Tong University. Most of the study participants are ethnically Han Chinese and residents living in Northwest China. The demographic and clinical characteristics of study participants are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Diagnostic criteria of CI patients were as referred to in the Fourth National Cerebrovascular Disease Conference of China, and the diagnosis was confirmed by computed tomography or Magnetic Resonance Imaging. The exclusion criteria were as follows: patients with malignancy, autoimmune disease, chronic kidney disease, and incomplete heart function. This study was approved by the Ethical Committee of the First Affiliated Hospital of Xi\u0026rsquo;an Jiao Tong University and we got the informed consent of each patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the Study Population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.26\u0026plusmn;14.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.52\u0026plusmn;11.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.742 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales/Females\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e332/185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e344/173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.472 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187(36.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189(36.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.948 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99(19.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142(27.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119(23.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162(31.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265(51.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e356(68.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.78\u0026plusmn;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.81\u0026plusmn;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.560 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u0026plusmn;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026plusmn;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.416 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.19\u0026plusmn;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.21\u0026plusmn;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.740 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.37\u0026plusmn;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50\u0026plusmn;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.14\u0026plusmn;53.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.39\u0026plusmn;34.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.552 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApolipoprotein A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15\u0026plusmn;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u0026plusmn;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.994 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApolipoprotein B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74\u0026plusmn;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u0026plusmn;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.175 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApoB/ApoA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.66\u0026plusmn;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u0026plusmn;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.321 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApolipoprotein E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.89\u0026plusmn;13.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.58\u0026plusmn;14.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.135 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipoprotein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194.88\u0026plusmn;202.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e211.94\u0026plusmn;205.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.179 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.71\u0026plusmn;4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.50\u0026plusmn;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.395 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.15\u0026plusmn;4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.13\u0026plusmn;4.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.996 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCI: cerebral infarction, TC: total cholesterol, HDL: high-density lipoproteins, LDL-C: low-density lipoprotein cholesterol, TG: triglyceride, Cr: creatinine, DB: direct bilirubin, IB: indirect bilirubin\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eaP values were calculated by Student\u0026rsquo;s t-tests.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ebP values were calculated from two-sided chi-square test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and genotyping\u003c/h2\u003e \u003cp\u003eBlood samples from each participant were obtained from the cubital vein and collected in tubes containing ethylene diamine tetra acetic acid (EDTA). Genomic DNA was extracted using DNA isolation kits (Sinochips Bioscience Co., Ltd., Zhuhai, Guangdong, China) for peripheral blood and stored at -20\u0026deg;C. The genotypes of ApoE were detected using a commercially available kit (Sinochips Bioscience Co., Ltd., Zhuhai, Guangdong, China). PCR analysis was performed according to the manufacturer\u0026rsquo;s instructions: 50\u0026deg;C for two minutes, pre-denaturation at 95\u0026deg;C for 15 minutes, followed by 45 cycles at 94\u0026deg;C for 30 seconds and 65\u0026deg;C for 45 seconds. PCR products were then reversely hybridized with gene chip technology. Finally, we used a gene chip scanner to help interpret the data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eData analysis was performed using SPSS statistical software version 16.0. Continuous variable data are presented as means \u0026plusmn; standard deviation and as numbers and percentages for categorical variables. Student's t test and χ2 test were initially used to test the difference between CI and control groups. ApoE genotype and allele frequencies were tested for Hardy-Weinberg equilibrium by chi-square test. The chi-square test and ANOVA were used to analyze the association between specific ApoE genotypes and clinical characteristics. Logistic regression analysis was used to assess the interactions between ApoE genotypes and various factors. A value of p\u0026lt;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eBaseline clinical characteristics of the CI and control groups\u003c/h2\u003e\n\u003cp\u003eBaseline clinical characteristics of the patients with CI and control groups are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 517 Chinese patients with CI, consisting of 344 males and 173 females aged 26-91 years (mean=61.52 years, SD=11.24), and 517 controls participants, comprising 332 males and 185 females aged 23-93 years (mean=61.26 years, SD=14.29), were included in the present study. Most of the study participants originate from northwest China. Age and sex distribution were not significantly different between the two groups (\u003cem\u003eP\u003c/em\u003e=0.742 and 0.472, respectively). The proportions of drinking (\u003cem\u003eP\u003c/em\u003e=0.002), hypertension (\u003cem\u003eP\u003c/em\u003e=0.003) and diabetes (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) were significantly higher in the CI group than in the control group. TG level was significantly higher in the CI group compared to the control group (\u003cem\u003eP\u003c/em\u003e=0.011), no significant differences were found in TC, high-density lipoprotein (HDL), LDL-c, creatinine (Cr), ApoA-I, ApoB, ApoB/A-I, ApoE, lipoprotein, direct bilirubin (DB) and indirect bilirubin (IB) levels between the two groups (all \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eAllele And Genotype Frequencies Of Apoe And Ci Risk\u003c/h2\u003e\n\u003cp\u003eThe distribution of the ApoE genotype and allele frequencies in CI cases and control subjects is summarized in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The genotype distribution of this polymorphism in patients with CAD and control participants was in concordance with Hardy-Weinberg equilibrium (\u003cem\u003eP\u003c/em\u003e = 0.45 and 0.50, respectively). Genotype \u0026epsilon;3/\u0026epsilon;3 (63.8%) was the most common type in CI groups, followed by \u0026epsilon;3/\u0026epsilon;4 (22.8%), \u0026epsilon;2/\u0026epsilon;3 (9.9%), \u0026epsilon;4/\u0026epsilon;4 (1.5%), \u0026epsilon;2/\u0026epsilon;4 (1.2%), and \u0026epsilon;2/\u0026epsilon;2 (0.8%), whereas those in control participants were \u0026epsilon;3/\u0026epsilon;3 (71.0%), followed by \u0026epsilon;2/\u0026epsilon;3 (13.3%), \u0026epsilon;3/\u0026epsilon;4 (12.6%), \u0026epsilon;2/\u0026epsilon;4 (2.1%), \u0026epsilon;4/\u0026epsilon;4 (0.6%) and \u0026epsilon;2/\u0026epsilon;2 (0.4%). The allele frequency of \u0026epsilon;2, \u0026epsilon;3, and \u0026epsilon;4 was 6.3%, 80.2% and 13.5% respectively in patients with CI; 8.1%, 83.9% and 7.9% respectively in control participants. The distribution of ApoE genotypes and alleles in the two groups was significantly different (\u0026chi;2=24.424 and \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, \u0026chi;2=18.472 and \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, respectively).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe distributions of genotypes and alleles of the ApoE gene in the CAD patients and controls\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGenotype, n (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCI group(n=617)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eControl group(n=308)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026chi;2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE2/E2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4(0.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(0.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.010(0.366,11.010)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.687\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"6\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.424\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"6\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE2/E3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51(9.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69(13.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.711(0.484,1.044)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.099\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE2/E4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6(1.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11(2.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.540(0.198,1.472)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.328\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE3/E3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e330(63.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e367(71.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.721(0.555,0.937)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.017\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE3/E4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e118(22.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65(12.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.057(1.477,2.864)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE4/E4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(1.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(0.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.693(0.710,10.208)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.224\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eHWE\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026chi;2\u0026thinsp;=\u0026thinsp;3.70, \u003cem\u003eP\u003c/em\u003e = 0.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026chi;2\u0026thinsp;=\u0026thinsp;3.33, P =0.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlleles, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65(6.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84(8.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.759(0.542,1.062)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e18.472\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e829(80.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e868(83.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.773(0.617,0.969)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.029\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e140(13.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e82(7.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.818(1.364,2.424)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eCI: cerebral infarction, HWE: Hardy-Weinberg equilibrium.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003ea\u003cem\u003ep\u003c/em\u003e and OR (95% CI) values were calculated by logistic regression adjusted for age, gender, and traditional cardiovascular risk factors.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eb\u003cem\u003ep\u003c/em\u003e values were calculated from two-sided chi-square tests or Fisher\u0026rsquo;s exact tests.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe frequencies of \u0026epsilon;3/\u0026epsilon;4 genotype (OR =2.057, 95% CI = 1.477\u0026ndash;2.864, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and \u0026epsilon;4 allele (OR =1.818, 95% CI = 1.364\u0026ndash;2.424, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) were significantly higher in CI patients than in control participants. Further, patients with CAD had a significantly lower \u0026epsilon;3/\u0026epsilon;3 (OR =0.721, 95% CI = 0.555\u0026ndash;0.937, \u003cem\u003eP\u003c/em\u003e=0.017) genotype and \u0026epsilon;3 allele (OR =0.773, 95% CI = 0.617\u0026ndash;0.969, \u003cem\u003eP\u003c/em\u003e=0.029) frequencies than did the control participants. (P \u0026lt; 0.05)\u003c/p\u003e\n\u003cp\u003eTo explore the relationship between ApoE genotype and CI, we conducted further analysis stratified by age(dichotomized into \u0026le;60 years and \u0026gt;60 years) and sex. The results showed that \u0026epsilon;3/\u0026epsilon;4 frequency was significantly higher in patients with CI compared to the control participants (OR =3.067, 95% CI = 1.675\u0026ndash;5.614, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001 in age \u0026le;60 years; OR =1.735, 95% CI = 1.156\u0026ndash;2.604, \u003cem\u003eP\u003c/em\u003e=0.008 in age \u0026gt;60 years and OR =2.206, 95% CI = 1.474\u0026ndash;3.301, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001 in males), but not in females (OR =1.746, 95% CI = 0.973\u0026ndash;3.134, \u003cem\u003eP\u003c/em\u003e=0.078). Additionally, the variance in allele \u0026epsilon;4 between patients with CI and controls was also statistically significant (OR =2.072, 95% CI = 1.281\u0026ndash;3.353, \u003cem\u003eP\u003c/em\u003e=0.003 in age \u0026le;60 years; OR =1.704, 95% CI = 1.189\u0026ndash;2.444, \u003cem\u003eP\u003c/em\u003e=0.003 in age\u0026gt;60 years; OR =1.709, 95% CI = 1.201\u0026ndash;2.432, \u003cem\u003eP\u003c/em\u003e=0.001 in males and OR =2.046, 95% CI = 1.246\u0026ndash;3.361, \u003cem\u003eP\u003c/em\u003e=0.004 in females) (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eRelationships between serum lipid profile and ApoE alleles.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e describe the association between serum lipid profiles and allelic carrier status (\u0026epsilon;2, \u0026epsilon;3 and \u0026epsilon;4 groups). Participants with \u0026epsilon;2/\u0026epsilon;4 genotype (n= 17) were excluded because play opposing roles in lipid metabolism and the incidence of CI. In the patients with CAD, \u0026epsilon;4 carriers had significantly higher LDL-C, ApoB and ApoB/ApoA-I and lower levels of ApoA-I and ApoE levels than \u0026epsilon;2 carriers. LDL-C, ApoB, ApoB/ApoA-I and ApoE levels of the control participants showed similar trends to those in CI groups. Additionally, control participants with \u0026epsilon;4 carriers had significantly higher levels of lipoprotein and TC levels than \u0026epsilon;2 carriers.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eRelationships between serum lipid profile and ApoE allele in CI patients and control participants\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eCI patient\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"7\" align=\"left\"\u003e\n\u003cp\u003eControl participants\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFactors\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;2(\u0026epsilon;2\u0026epsilon;2\u0026thinsp;+\u0026thinsp;\u0026epsilon;2\u0026epsilon;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;3(\u0026epsilon;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;4(\u0026epsilon;3\u0026epsilon;4\u0026thinsp;+\u0026thinsp;\u0026epsilon;4\u0026epsilon;4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;2(\u0026epsilon;2\u0026epsilon;2\u0026thinsp;+\u0026thinsp;\u0026epsilon;2\u0026epsilon;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;3(\u0026epsilon;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;4(\u0026epsilon;3\u0026epsilon;4\u0026thinsp;+\u0026thinsp;\u0026epsilon;4\u0026epsilon;4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.59\u0026plusmn;0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.86\u0026plusmn;0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.78\u0026plusmn;0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.112\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.423\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.183\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.55\u0026plusmn;0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.82\u0026plusmn;0.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.85\u0026plusmn;0.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.043\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.822\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHDL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.07\u0026plusmn;0.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.02\u0026plusmn;0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.00\u0026plusmn;0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.220\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.208\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.01\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.04\u0026plusmn;0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.04\u0026plusmn;0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.620\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.326\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.923\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.466\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLDL-C\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.89\u0026plusmn;0.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.27\u0026plusmn;0.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.18\u0026plusmn;0.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.266\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.98\u0026plusmn;0.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.23\u0026plusmn;0.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.29\u0026plusmn;0.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.589\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.043\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.55\u0026plusmn;1.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.45\u0026plusmn;0.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.61\u0026plusmn;1.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.245\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.435\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.090\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.740\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.55\u0026plusmn;0.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.36\u0026plusmn;0.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.23\u0026plusmn;0.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.039\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.184\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.011\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCr\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64.91\u0026plusmn;20.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e67.69\u0026plusmn;36.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68.36\u0026plusmn;34.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.854\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.622\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.870\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.537\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65.53\u0026plusmn;21.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70.03\u0026plusmn;60.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69.91\u0026plusmn;26.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.553\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.987\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.302\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApolipoprotein A\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.26\u0026plusmn;0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.16\u0026plusmn;0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.12\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.061\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.17\u0026plusmn;0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.16\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.13\u0026plusmn;0.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.514\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.710\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.139\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.263\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApolipoprotein B\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.64\u0026plusmn;0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.77\u0026plusmn;0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.77\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.944\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.66\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.75\u0026plusmn;0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.76\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.535\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApoB/ApoA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.54\u0026plusmn;0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.68\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.70\u0026plusmn;0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.56\u0026plusmn;0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.67\u0026plusmn;0.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.68\u0026plusmn;0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.807\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApolipoprotein E\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.03\u0026plusmn;21.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.61\u0026plusmn;10.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32.04\u0026plusmn;14.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.039\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.24\u0026plusmn;17.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.99\u0026plusmn;11.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32.11\u0026plusmn;12.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.066\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLipoprotein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e215.81\u0026plusmn;213.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e210.85\u0026plusmn;207.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e212.14\u0026plusmn;201.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.986\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.870\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.952\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.912\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133.86\u0026plusmn;109.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e203.59\u0026plusmn;216.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213.16\u0026plusmn;182.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.008\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.732\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.58\u0026plusmn;2.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.45\u0026plusmn;2.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.58\u0026plusmn;2.74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.863\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.729\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.626\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.990\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.73\u0026plusmn;2.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.65\u0026plusmn;5.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.14\u0026plusmn;4.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.737\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.904\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.460\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.472\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.08\u0026plusmn;5.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.14\u0026plusmn;4.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.13\u0026plusmn;5.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.998\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.943\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.991\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.959\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.14\u0026plusmn;4.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.06\u0026plusmn;4.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.78\u0026plusmn;5.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.526\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.890\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.263\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.434\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003eCI: cerebral infarction, TC: total cholesterol, HDL: high-density lipoproteins, LDL-C: low-density lipoprotein cholesterol, TG: triglyceride, Cr: creatinine, DB: direct bilirubin, IB: indirect bilirubin\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003ea\u003cem\u003ep\u003c/em\u003e value shows the differences compared between groups (\u0026epsilon;2, \u0026epsilon;3, \u0026epsilon;4)\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003eb\u003cem\u003ep\u003c/em\u003e values obtained when comparing \u0026epsilon;2 subjects with \u0026epsilon;3 subjects.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003ec\u003cem\u003ep\u003c/em\u003e values obtained when comparing \u0026epsilon;4 subjects with \u0026epsilon;3 subjects.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003ed\u003cem\u003ep\u003c/em\u003e values obtained when comparing \u0026epsilon;2 subjects with \u0026epsilon;4 subjects.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eLogistic Regression Analysis Of Ci Risk Factors\u003c/h2\u003e\n\u003cp\u003eWe performed a multivariate logistic regression analysis to identify which variables with statistical significance from the univariate analysis could act as independent predictors of CI. Univariate logistic analysis showed that drinking (OR =1.701, 95% CI = 1.167\u0026ndash;2.478, \u003cem\u003eP\u003c/em\u003e=0.006), hypertension (OR =1.885, 95% CI = 1.417\u0026ndash;2.508, \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001), ApoE levels (OR =0.983, 95% CI = 0.969\u0026ndash;0.997, \u003cem\u003eP\u003c/em\u003e=0.017), lipoprotein (OR =1.001, 95% CI = 1.000\u0026ndash;1.001, \u003cem\u003eP\u003c/em\u003e=0.046), TG (OR =1.363, 95% CI = 1.035\u0026ndash;1.797, \u003cem\u003eP\u003c/em\u003e=0.028) and \u0026epsilon;4 allele (OR =1.954, 95% CI = 1.359\u0026ndash;2.810; \u003cem\u003eP\u0026lt;\u003c/em\u003e0.001) were significant independent risk factors for CI (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Furthermore, to exclude the confounding effect of age (\u0026le;60 years and \u0026gt;60 years) and sex, multivariate logistic regression analysis stratified according to age and sex was performed. In both age groups, \u0026epsilon;4 carriers were associated with increased risk of CI (age \u0026le;60 years: OR = 2.970, 95% CI = 1.553\u0026ndash;5.678, \u003cem\u003eP\u003c/em\u003e = 0.001; age \u0026gt;60 years: OR = 1.715, 95% CI = 1.082\u0026ndash;2.719, \u003cem\u003eP\u003c/em\u003e = 0.022). Also, \u0026epsilon;4 carriers was significantly associated with a higher risk of CI in males (OR =2.182, 95% CI = 1.398\u0026ndash;3.407, \u003cem\u003eP\u003c/em\u003e=0.022), but not in females (OR =1.500, 95% CI = 0.779\u0026ndash;2.887, \u003cem\u003eP\u003c/em\u003e=0.225) (Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eLogistic regression analysis of the risk of CI in Northwest of China population.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP-\u003c/em\u003e value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDrinking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.701(1.167-2.478)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.885(1.417-2.508)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLipoprotein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.001(1.000-1.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.363(1.035-1.797)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApoE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.017\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.983(0.969-0.997)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.954(1.359-2.810)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\"\u003eCI: cerebral infarction, TG: triglyceride\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eMultiple logistic regression analysis for CI patients and control subjects\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e\u0026epsilon;4\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge\u0026le;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.970(1.553-5.678)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge༞60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.715(1.082-2.719)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003emales\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.182(1.398-3.407)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003efemales\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.500(0.779-2.887)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.225\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e"},{"header":"Study Strength And Limitations","content":"\u003cp\u003eThe strength of this study is that this is the first study about the relationship of CI and ApoE gene polymorphism in Northwest Han Chinese population. Association of lipid levels with ApoE gene polymorphisms included in the final analysis and have excluded confounding factors or comorbidities affecting the results. There were some inherent limitations presented in our study. (1) Most ofthe present participants may receive lipid-lowering therapy at the time of inclusion, which may have potential impacts on the association of blood lipid profiles with adverse events. (2) As this is a large retrospective study, original data shortage constrained assessment of potential gene-environment interactions. (3) The small sample size of this study, which may lead to the instability of the results to some extent. (4) The study was conducted only in northwest Chinese populations, and whether these findings will also be true in other populations needs further investigation.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the present study suggests that ɛ4 allele is associated with CI in the Northwest Han Chinese population. When stratifying by age and sex, it was found that statistically significant differences in the distribution and frequencies of the ε3/ε4 genotype and ε4 allele in males and ε4 allele in females were observed between patients and controls; ε4 allele was a significant and independent risk factors in elderly and young patients. ApoE gene polymorphisms may be related to lipid metabolism in patients with CI. Since the limited sample size, and thus further studies with larger sample population are needed to clear our findings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eApoE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eapolipoprotein E\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecerebral infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etotal cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHDL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehigh-density lipoproteins\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLDL-C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elow-density lipoprotein cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etriglyceride\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCr\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecreatinine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edirect bilirubin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eindirect bilirubin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHWE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHardy-Weinberg equilibrium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge all sample donors who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWenbing Ma and Xiaoyun Lu conceived and designed the experiments; Wenbing Ma and Weiyi Feng contributed to the writing of the manuscript. Liting Zhang, Shuang Yang, Houli Li and Suya Zhang recruited subjects and collected clinical data. Haiyan Dong and Weihua Dong helped to analyze the data. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Key R \u0026amp; D Plan Projects in Shaanxi Province (grant number 2021-SF-130) and the Foundation of the First Affiliated Hospital of Xi\u0026apos;an Jiaotong University (grant number 2020ZYTS-08).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethical Committee of the First Affiliated Hospital of Xi\u0026rsquo;an Jiao Tong University and we got the informed consent of each patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Pharmacology,\u0026nbsp;The First Affliated Hospital of Xi\u0026apos;an Jiaotong University, Xi\u0026apos;an, People\u0026rsquo;s Republic of China;\u0026nbsp;\u003csup\u003e2\u003c/sup\u003eThe school of Life Science and technonlogy, \u0026nbsp;Xi\u0026apos;an Jiaotong University, Xi\u0026apos;an, People\u0026rsquo;s Republic of China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWang H, Fu X, Ju J, Meng D, Sun S, Guo C, Jia H, Sun Q: Acupuncture for patients recovering from lacunar infarction A protocol for systematic review and meta-analysis. 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Stroke.2003;34:1617\u0026ndash;1622.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJurgens G, Taddeipeters WC, Koltringer P, Petek W, Chen Q, Greilberger J, Macomber PF, Butman BT, Stead AG, Ransom JH: lipoprotein (A) serum concentration AND apolipoprotein (A) phenotype correlate with severity AND presence of ischemic cerebrovascular disease. Stroke. 1995;26:1841\u0026ndash;1848.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv P, Jin HQ, Liu YY, Cui W, Peng Q, Liu R, Sun W, Fan CH, Teng YM, Sun WP, Huang YN: Comparison of Risk Factor between Lacunar Stroke and Large Artery Atherosclerosis Stroke: A Cross-Sectional Study in China. PLoS One. 2016;11:e0149605.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoltjer RL, Reese LC, Richardson BE, Tran H, Green S, Pham T, Chalupsky M, Gabriel I, Light T, Sanford L, et al: Pallidal neuronal apolipoprotein E in pantothenate kinase-associated neurodegeneration recapitulates ischemic injury to the globus pallidus. Mol Genet Metab. 2015;116:289\u0026ndash;297.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Xia Y, Zhao Y, Chen L, Zhu Y: Intestinal gutsfeature and role of ApoE and glucose metabolism in cerebral infarction patients. Int J Clin Exp Pathol. 2017;10:561\u0026ndash;565.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTascilar N, Dursun A, Ankarali H, Mungan G, Sumbuloglu V, Ekem S, Bozdogan S, Baris S, Aciman E, Cabuk F: Relationship of apoE polymorphism with lipoprotein(a), apoA, apoB and lipid levels in atherosclerotic infarct. J Neurol Sci. 2009;277:17\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChou Y-C, Chan P-C, Yang T, You S-L, Bai C-H, Sun C-A: Apolipoprotein B Level and the Apolipoprotein B/Apolipoprotein A-I Ratio as a Harbinger of Ischemic Stroke: A Prospective Observation in Taiwan. Cerebrovasc Dis. 2020;49:487\u0026ndash;494.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eDue to technical limitations, table 3 is only available as a download in the Supplemental Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Apolipoprotein E, Cerebral Infarction, Gene polymorphism, Northwest China","lastPublishedDoi":"10.21203/rs.3.rs-1094744/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1094744/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The apolipoprotein E (ApoE) genetic variation may be involved in the development of Cerebral Infarction (CI). Serum lipid levels are known risk factors for CI, but the effect of the ApoE gene polymorphism on lipid metabolism remains unclear. This retrospective cohort study aimed to determine the role of ApoE genotypes in CI risk and the relationships between ApoE gene polymorphism and serum lipid levels among the population of northwest China.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003epatients and methods: \u003c/strong\u003e517 CI patients and 517 non-CI controls were enrolled in the study. Polymerase chain reaction and hybridization were used to test the ApoE gene polymorphisms.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eresults: \u003c/strong\u003ePatients with CI had a significantly higher frequency of ε3/ε4 genotype (OR =2.057, 95% CI = 1.477–2.864, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and ε4 allele (OR =1.818, 95% CI = 1.364–2.424, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) than control participants. When stratifying by age and sex, it was found that statistically significant differences in the distribution and frequencies of the ε3/ε4 genotype(OR =3.067, 95% CI = 1.675–5.614, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001 in age ≤60 years; OR =1.735, 95% CI = 1.156–2.604, \u003cem\u003eP\u003c/em\u003e=0.008 in age \u0026gt;60 years and OR =2.206, 95% CI = 1.474–3.301, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001 in males) and ε4 allele (OR =1.709, 95% CI = 1.201–2.432, \u003cem\u003eP\u003c/em\u003e=0.001) in males and ε4 allele (OR =2.072, 95% CI = 1.281–3.353, \u003cem\u003eP\u003c/em\u003e=0.003 in age ≤60 years; OR =1.704, 95% CI = 1.189–2.444, \u003cem\u003eP\u003c/em\u003e=0.003 in age\u0026gt;60 years; OR =1.709, 95% CI = 1.201–2.432, \u003cem\u003eP\u003c/em\u003e=0.001 in males and OR =2.046, 95% CI = 1.246–3.361, \u003cem\u003eP\u003c/em\u003e=0.004 in females ) were observed between patients and controls. ε4 carriers had significantly lower ApoE level and higher low-density lipoprotein cholesterol (LDL-C), ApoB and ApoB/ApoA-I levels than ε2 carriers in both two groups. Additionally, control participants with ε4 carriers had significantly higher levels of lipoprotein and lower total cholesterol (TC) levels than ε2 carriers, CI patients with ε4 carriers had significantly lower level of ApoA-I than ε2 carriers. After adjusting for other established risk factors, drinking, hypertension, lipoprotein, triglycerides (TG) and ε4 allele were significant independent risk factor for CAD. ε4 allele presence was associated with a nearly two-fold higher CI risk.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThis study provides evidence that ε4 allele, drinking, hypertension, lipoprotein and TG levels are independent risk factor for CI among patients in Northwest China. Also, these data might be clinically useful in allowing for more individualized preventive and therapeutic strategies.\u003c/p\u003e","manuscriptTitle":"Apolipoprotein E Gene Polymorphism Effects on Lipid Metabolism and Risk of Cerebral Infarction in Northwest Han Chinese Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-30 15:23:56","doi":"10.21203/rs.3.rs-1094744/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"977a4f20-09eb-4a03-badf-db10501c301b","owner":[],"postedDate":"November 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":8741545,"name":"Cardiac \u0026 Cardiovascular Systems"},{"id":8741546,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2021-12-13T05:29:14+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-30 15:23:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1094744","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1094744","identity":"rs-1094744","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}