Association of PCSK6 polymorphisms with susceptibility risk of large artery atherosclerotic stroke

Association of PCSK6 polymorphisms with susceptibility risk of large artery atherosclerotic stroke | 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 Article Association of PCSK6 polymorphisms with susceptibility risk of large artery atherosclerotic stroke Haiyan Chen, Yanfang Yun, Guixin Yang, Huadan Yang, Yongming Jiang, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3847948/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 Recent studies have shown that PCSK6 is significantly associated with dyslipidemia, inflammatory reaction, cardiovascular diseases, atherosclerosis. However, the relationship between PCSK6 polymorphisms and large artery atherosclerosis stroke has not been reported. We performed this study to investigate whether the PCSK6 polymorphism is associated with risk of large artery atherosclerosis (LAA) stroke in the Chinese population. Methods Our study enrolled a total of 432 large artery atherosclerosis stroke cases and 448 healthy controls, cases and controls were genotyped at the polymorphic sites rs1135911 and rs20543. Multivariate logistic regression analyses were performed to analyze the associations between two snps and large artery atherosclerosis stroke susceptibility. Results Both rs1135911 and rs20543 were not associated with the distribution of responsible vessel stenosis in ischemic stroke. No significant effect was observed between the rs1135911 polymorphism and LAA stroke. Rs20543 was significantly correlated with LAA stroke ( P <0.001), such difference remained statistically significant after adjusting for smoking history, hypertension, hypertriglyceridemia, high density lipoprotein cholesterol, and hyperhomocysteinemia, the difference remained significant (Recessive model: P = 0.000, OR = 0.526, 95%CI = 0.396–0.699 ). Conclusion Rs20543 AA genotype may be a protective factor for LAA stroke in Chinese population. Figures Figure 1 Introduction Stroke is an acute cerebrovascular disease, including ischemic and hemorrhagic stroke, of which ischemic stroke accounts for 85% of all strokes, and is considered to be one of the leading causes of human death and disability worldwide [1]. According to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria[2], ischemic stroke etiologies are categorized as large artery atherosclerosis（LAA）, cardioembolism(CE), small artery occlusion(SAO), stroke of other determined etiology(SOE) and stroke of undetermined etiology(SUE). It is of vital significance to identify and diagnose ischemic stroke as early as possible. Large artery atherosclerosis (LAA) is the most common type of cerebral infarction which is characterized by high morbidity, high disability, high recurrence rate, and high mortality[3]. The risk factors of atherosclerosis include dyslipidemia，hypertension，diabetes mellitus and inflammatory stress[4, 5]. Besides environmental aspect, genetic factors also play a substantial role in the pathogenesis of atherosclerosis[6]. Single nucleotide polymorphism (snp) is the most common genetic variation in human body, account for much of the phenotypic diversity among individuals, and also closely related to numerous pathological states in humans[7, 8]. Proprotein convertases(PCs) are a class of Ca 2+ -dependent serine endoprotease, which can activate one or more endosite sites of precursor proteins by restriction proteolysis, involved in the regulation of cells proliferation, differentiation, adhesion and invasion, thus, it plays a significant role in the development of multiple disorders and diseases[9, 10]. At present, at least 9 members of PCs family have been identified, including PCSK1, PCSK2, PCSK3 (furin), PCSK4, PCSK5, PCSK6(PACE4) and PCSK7[10]. Proprotein convertase subtilisin/kexin type 6 (PCSK6) is one of the important members of the PCs, and is expressed broadly in various tissues such as the brain, liver, nervous system and intestine[11]. PCSK6 is an intercellular binding protein, which is localized to the cell membrane and binds to the membrane-associated substrates via its cysteine-rich regions, and converts inactive precursors such as nerve and peptide hormones, proteolytic enzymes, growth factors, type I membrane binding proteins including receptors, cell adhesion molecules, cell surface glycoproteins, cell signals and transcription factors into their active forms through the cleavage of coupled amino acids[12]. Previous investigations reported that PCSK6 is an oncogene which is overexpressed in many cancers such as breast cancer, prostate cancer and thyroid carcinomas, and play an important regulatory role in angiogenesis, tumor cell growth, and metastasis[13-16]. A previous study analyzed differential expression of the mRNA and protein expression levels of PCSK6 between unstable carotid plaque and stable carotid plaque using microarray analysis, and found that PCSK6 may be involved in atherosclerosis pathogenesis through the regulation of inflammatory responses and extracellular matrix remodeling[17]. Recently, the association between PCSK6 and vascular is becoming a research hotspot. In 2020, Rykaczewska et al [18]has identified that PCSK6 is associated with carotid intima-medial thickness, is an index for atherosclerosis, and immunohistochemistry confirmed that PCSK6 localize in smooth muscle actin positive cells of the fibrous cap and the neovascular, PCSK6 is increased after arterial injury in a mice carotid artery balloon injury model, and the levels positively correlate with the level of some inflammatory factors such as PDGFB, MMP2/MMP14. Similarly, another study[19] found the contractile markers, extracellular matrix remodeling enzymes and cytokines / receptors of carotid VSMC decreased significantly in PCSK6 knockout mice, and vascular intimal hyperplasia was significantly reduced. In view of the above facts, PCSK6 might favor cerebral arteriosclerosis by remodeling the cerebral vasculature, and promotes the development of LAA stroke（LAAS）, while the role of PCSK6 polymorphism in LAAS has rarely been reported, hence, in the present study, we determined the relevance between PCSK6 snps rs1135911, rs20543 and the susceptibility of LAAS. Methods 2.1 Study subject A total of 432 LAAS consecutive patients who were admitted into the Youjiang Medical University for nationalities between January 2018 to June 2022 were enrolled as a case group. Meanwhile, and 448 sex- and age-matched healthy adult volunteers were enrolled as a control group. The diagnosis of IS was made according to the World Health Organization criteria, the degree of cerebrovascular stenosis was assessed using digital subtraction angiography (DSA), and large-artery atherosclerosis stroke was derived from the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) stroke subtype classification system[2]. Exclusion criteria for all participants were as follows: intracranial hemorrhage, transient ischemic attack, atrial fibrillation, malignancy, severe hepatic, genetic diseases, cardiac or other organ impairment, infection and malignancy. During admission, all patients underwent computed tomography angiography or digital subtraction angiography to evaluated cerebral vascular stenosis. The main characteristics of all participants were collected including gender, age, BMI, blood routine examination, blood pressure, smoking status, lipid levels, and so on. This study was approved by the Ethics Review Board of he Affiliated Hospital of Youjiang Medical University for nationalities, and informed written consent was signed by all the participants. 2.2 Clinical data General information and related biochemical information including age, sex, diabetes duration, height, weight, body mass index (BMI), smoking history, and alcohol consumption of the participants were recorded. Fasting venous blood(8 ml) was drawn by venipuncture from all the participants, half of them were used for biochemical analyses, and the other half were reserved for DNA extraction. High blood pressure(HBP) was defined as a documented history of high blood pressure or treatment with anti-hypertensive medications or blood pressure ≥ 140/90mmHg(average of three independent measures). Diabetes mellitus(DM) was defined as typical polydipsia, polyuria, polyphagia, weight loss symptoms plus random blood glucose > 11.1mmol/L or fasting blood glucose ≥ 7.0mmol/L, or previous diabetes diagnosis was clear, and hypoglycemic drugs or insulin were used. Drinking history was defined as alcohol consumed >50 g per day lasting for at least 1 year, smoking history was defined as having smoked at least 100 cigarettes over the life time, respectively. High-density lipoprotein cholesterol (HDL-C) < 1.0 mmol/L was defined as abnormal HDL-C, triglyceride(TG) values ≥1.7 mmol/L was defined as abnormal TG. Hyperhomocysteinemia (HHcy) was defined as plasma Hcy level ＞15 μmol/L. Normal body mass index( BMI) was defined as 18.5 ≤ BMI < 25. 2.3 Cerebrovascular Stenosis assessment Patients included in the case group received cerebral angiography to assess stenosis of major cerebral vessels. According to Boutillier's seven-segment method of internal carotid artery, the composition of extracranial arteries includes the common carotid artery, internal carotid artery (C1-C5 segment), and vertebral artery (V1-V3 segment). The internal carotid artery (C6–C7 segments), vertebral artery (V4 segment), middle cerebral artery, anterior cerebral artery, posterior cerebral artery, and basilar artery constitute the intracranial vessels. 2.4 PCSK6 Genotyping Genomic DNA was extracted from venous blood using a DNA extraction kit (Tiangen, Beijin, China), then PCR was performed to obtain the target gene fragments. Ligase detection reaction (LDR) was used to genotype rs1135911 and rs20543 variants. The primer and probe sequences, as well as the lengths of PCR and LDR for each variant, are listed in Table 1. The PCR reaction system included 1μL gDNA, 0.6 μL primer, 7.5μL PCR mix，5.9μL ddH2O. Further amplification was conducted in 10μL multiplex LDR reaction mixtures, containing 3μL of original PCR product, 1μL of 10×Taq DNA ligase buffer, 0.125μL of Taq DNA ligase, and 2.875μL of ddH2O, 3μL of probe mix. The conditions of LDR were as follows：denaturation at 94℃ for 20s, annealing at 58℃ for 90 s, with 30 cycles, then 1 μL reaction product plus with 9 μL HIDI, were denatured at 95℃ for 3 minutes，immediately ice bath，then samples were run on an ABI 3730 sequencer (Applied Biosystems). Results were analyzed using GeneMarker. 2.5 Statistical analysis The SPSS statistical software package version 26.0 (SPSS, Chicago, USA) was used for all of the statistical analysis. Student t test was used for continuous data and Pearson chi-square (χ2) test for categorical data. Univariate logistic regression was performed to examine the association between the genotypes of the different snps and LAAS. All statistical tests were two sided and statistical significance was measured by p -values less than 0.05. Results 3.1 Baseline characteristics of case and control groups The baseline characteristics of the LAS patients and control groups are listed in table2. Compared with the control group, the case group had a larger proportion of individuals with HBP, DM and smokers, and levels of HCY, TG were significantly increased, level of HDL-C were significantly decreased (All P＜0.05). No significant differences were found between the two groups in terms of sex, age, drinking history, TC, LDL-C and BMI. 3.2 Association between PCSK6 polymorphisms and LAAS risk All tested groups were in Hardy-Weinberg equilibrium(P=0.96 for rs20543, P=0.117 for rs1135911), indicating that the samples were from a population with genetic balance and had good representativeness. We conducted logistic regression analysis to compare snp genotype between cases and controls, genotype distributions of each snp and their associations with LAAS risk was shown in Table 3. As is shown in table 3, rs20543 polymorphisms are closely associated with LAAS disease susceptibility, after adjusted for HBP, DM, smoking, TG, HDL-C and HCY, subjects with the AA exhibited a significantly lower risk of LAAS compared with the GG genotype, GA genotype and GG+GA genotype (Recessive model: OR = 0.526, 95% CI =0.396-0.699, P ＜0.001). There was no significant difference in the distribution of rs1135911 between the case group and the control group. 3.3 Association between PCSK6 polymorphisms and Location of Cerebral Vascular Stenosis To understand association of rs20543 and rs1135911 with the location of the cerebrovascular stenosis, we subgrouped the subjects based on the status of cerebrovascular stenosis, and compared the genotype distribution of different groups(Table4 ). Unfortunately, we do not find any clear relationship between PCSK6 snps and location of cerebrovascular stenosis. 3.4 Bioinformatics analysis We examined the potential effects of snp rs20543 on gene expression in multiple tissues by the Genotype-Tissue Expression database (http://www.gtexportal.org/home/). The analysis of expression quantitative trait loci (eQTL) showed the rs20543 snp were associated with expression of PCSK6 in single tissue (Fig. 1A), and rs20543 GG genotype carriers having higher PCSK6 expression than the AA genotype carriers, in basal ganglia for example(Fig. 1B) (P < 0.005). Discussion In the current study,we explored the association between PCSK6 snps and the risk of AIS. Significant differences were observed in the distribution of the rs20543 GG/GA genotype between controls and cases. After adjusting for multiple cofactors such as HBP, DM, smoking, TG, HDL-C, HCY, the difference remained statistically significant. PCSK6 rs20543 GG, GA genotype were associated with increased risk of LAAS, AA genotype and recessive model might be a protective factor to decrease the risk of LAAS. We further analyzed the association of snps and the distribution of cerebral arterial stenosis. Besides, no statistical difference was found in the distribution of rs1135911 in two groups, either. PCSK6 is also named as PACE4, which encode a member of the subtilisin-like proprotein convertase family PCSK6. The encoded protease PCSK6 is constitutively secreted into the extracellular matrix and expressed in many tissues, including liver, gut, and brain. This gene encodes one of the seven basic amino acid-specific members which cleave their substrates at single or paired basic residues. Some of its substrates include transforming growth factor beta related proteins, proalbumin, and von Willebrand factor[20, 21]. PCSK6 is thought to play a role in tumor progression [22, 23]. Recent studies have found PCSK6 is closely associated with vascular remodeling and atherosclerotic processes[6, 24]. Vascular smooth muscle cells (VSMCs) are involved in all stages of the progression of atherosclerosis. When blood vessels are damaged, VSMCs can switch from the contractile to the synthetic phenotype, promote proliferation and migration of VSMCs. The development of atherosclerosis usually correlates with abnormal proliferation, migration and apoptosis of smooth muscle cells[25]. A recent study showed that PCSK6 gene silencing leads to downregulation of VSMC contractile markers and decreased MMP2 expression, instead, PCSK6 gene overexpression increases VSMC proliferation and migration induced by PDGFB[19]. A previous study[18] suggested that PCSK6 snps was associated with artery intima-media thickness, intimal thickening is considered to be a manifestation of atherosclerosis. Also, associations of PCSK6 snps with other diseases have been reported, such as, PCSK6 snp rs8029797 inflammasome-driven inflammatory response is implicated in rheumatoid arthritis[26], a variant rs900414 in PCSK6 is strongly associated with protection against pain in knee osteoarthritis pain[27], a number of snps of PCSK6 are associated with lipid metabolism and inflammation[28]. Based on the above facts, snps of PCSK6 may be associated with LAAS to some extent. Therefore, we performed our study, Our results confirmed our hypothesis. In our present study, we found rs20543 was associated with increased risk of LAAS. Rs20543 G>A is a synonymous mutation at the exon 13 of PCSK6 , which lead to a G to A，GAC/AAC, did not result in amino acid changes. Although the synonymous snps do not change the expression of amino acids, it may still play an important role in molecular genetics. Synonymous snps may represent genetic markers with functional molecular changes, and are in linkage disequilibrium with them; In addition, studies have shown that synonymous snps can directly change gene function and phenotype through various mechanisms, such as changing miRNA binding or protein folding, or by affecting mRNA splicing, stability or expression[29-31]. As far as we know, despite extensive literature searches, we could not find studies for the association of rs20543and stroke. A previous study [27] have reported on the associations between rs20543 and osteoarthritis, while other snps of PSCK6 was found to be associated with arthritis, rather than rs20543. Nevertheless, lots of studies have been done in the recent year between the PCSK6 snps and risk factors for acute cerebral infarction. In 2021, a GWAS studies suggested that the PCSK6 snps are linked to blood lipid metabolism and inflammatory[28]. What’s more，an recent research found PCSK6 snps were significantly associated with severe coronary artery stenosis[32].The analysis of expression quantitative trait loci (eQTL) showed the rs20543 snps were associated with expression of PCSK6 in single tissue (Fig. 1a), and the carriers with rsrs20543 GG increased expression of PCSK6 in Brian-caudate. Our findings are compatible with this, the GG genotypes as wll as GA genotypes showed increased risk for the LAAS, indicating that the GG genotype of rs20543 was a risk factor for LAAS susceptibility. Furthermore, we investigated whether this snp is a potential candidate affecting the position of the cerebrovascular stenosis, unfortunately, we detect no significant difference between the two snps and the position of the cerebrovascular stenosis. Our research may indicate that PCSK6 has no selective effect on vascular remodeling and has the same effect on intracranial and extracranial vessels. These findings will help improve our understanding of the role of PCSK6 genetic variants in the pathogenesis of LAAS. Although the results we got were promising, limitations still remained. Firstly, the sample size was small, which may limit the authenticity of the statistical analysis. Secondly, the analysis was hospital-based, potential selection bias may exist. In addition, the population we studied came from the southwest of China, which may give rise to some limitations. There are distribution differences in polymorphisms of the same locus among different races according to the 1000 Genomes Project Data, therefore, larger sample sizes from other medical centers of different races and ethnicities are needed to further confirm the role of PCSK6 snps in LAAS susceptibility. Finally, the effects of PCSK6 snps on LAAS are very exciting, but its mechanism is unclear, and further studies are needed. Declarations ETHICAL STATEMENT: Funding: This study was funded by National Natural Science Foundation of China (No.81860226) Conflict of Interest: The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or any financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. Ethical approval: The research followed the principles of the Helsinki Declaration, and the ethics committees of the affiliated Hospital of Youjiang Medical University for Nationalities have approved research protocols. Informed consent: Informed consent has been obtained from each subjects and agree to make the data public. Author contribution: Yanfang Yun and Haiyan Chen performed the experiments, interpreted the results of statistical analysis, and drafted the manuscript. Haiyan Chen and Yanfang Yun contributed equally to this work. Jianmin Huang and Xuebin Li designed the study and revised the manuscript. Guixin Yang, Yongming Jiang, Baoying Wei and Yingjie Zhou completed the majority of the experiments. Shengshan Yuan , Jianjun Huang, Huadan Yang and Yingning Wu provided materials. All authors read and approved the final manuscript. Data Availability Statement: All data are incorporated into the article. References Feigin VL, Nichols E, Alam T, Bannick MS, Beghi E, Blake N, Culpepper WJ, Dorsey ER, Elbaz A, Ellenbogen RG, et al. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):459–80. Adams HP, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh EE. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. STROKE 1993, 24(1). Zhou M, Wang H, Zeng X, Yin P, Zhu J, Chen W, Li X, Wang L, Wang L, Liu Y et al. Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. LANCET 2019, 394(10204):1145–1158. Lusis AJ. Atherosclerosis Nat. 2000;407(6801):233–41. Guo FX, Hu YW, Zheng L, Wang Q. Shear Stress in Autophagy and Its Possible Mechanisms in the Process of Atherosclerosis. DNA CELL BIOL. 2017;36(5):335–46. Boua PR, Brandenburg JT, Choudhury A, Sorgho H, Nonterah EA, Agongo G, Asiki G, Micklesfield L, Choma S, Gomez-Olive FX, et al. Genetic associations with carotid intima-media thickness link to atherosclerosis with sex-specific effects in sub-Saharan Africans. NAT COMMUN. 2022;13(1):855. Li HW, Shen M, Gao PY, Li ZR, Cao JL, Zhang WL, Sui BB, Wang YX, Wang YJ. Association between ADAMTS7 polymorphism and carotid artery plaque vulnerability. Med (Baltim). 2019;98(43):e17438. Zaragoza-Garcia O, Guzman-Guzman IP, Moreno-Godinez ME, Navarro-Zarza JE, Antonio-Vejar V, Ramirez M, Parra-Rojas I. PON-1 haplotype (-108C > T, L55M, and Q192R) modulates the serum levels and activity PONase promoting an atherogenic lipid profile in rheumatoid arthritis patients. CLIN RHEUMATOL. 2021;40(2):741–52. Stawowy P. Proprotein convertases in atherogenesis. CURR OPIN LIPIDOL. 2015;26(4):338–44. Artenstein AW, Opal SM. Proprotein convertases in health and disease. N Engl J Med. 2011;365(26):2507–18. Constam DB, Robertson EJ. SPC4/PACE4 regulates a TGFbeta signaling network during axis formation. Genes Dev. 2000;14(9):1146–55. Chen S, Cao P, Dong N, Peng J, Zhang C, Wang H, Zhou T, Yang J, Zhang Y, Martelli EE, et al. PCSK6-mediated corin activation is essential for normal blood pressure. NAT MED. 2015;21(9):1048–53. Mbikay M, Sirois F, Yao J, Seidah NG, Chretien M. Comparative analysis of expression of the proprotein convertases furin, PACE4, PC1 and PC2 in human lung tumours. Br J Cancer. 1997;75(10):1509–14. Hubbard FC, Goodrow TL, Liu SC, Brilliant MH, Basset P, Mains RE, Klein-Szanto AJ. Expression of PACE4 in chemically induced carcinomas is associated with spindle cell tumor conversion and increased invasive ability. CANCER RES. 1997;57(23):5226–31. Fradet L, Temmar R, Couture F, Belzile M, Fortier PH, Day R. Evaluation of PACE4 isoforms as biomarkers in thyroid cancer. J Otolaryngol Head Neck Surg. 2018;47(1):63. Bassi DE, Mahloogi H, Klein-Szanto AJ. The proprotein convertases furin and PACE4 play a significant role in tumor progression. Mol Carcinog. 2000;28(2):63–9. Perisic L, Hedin E, Razuvaev A, Lengquist M, Osterholm C, Folkersen L, Gillgren P, Paulsson-Berne G, Ponten F, Odeberg J, et al. Profiling of atherosclerotic lesions by gene and tissue microarrays reveals PCSK6 as a novel protease in unstable carotid atherosclerosis. Arterioscler Thromb Vasc Biol. 2013;33(10):2432–43. Rykaczewska U, Suur BE, Rohl S, Razuvaev A, Lengquist M, Sabater-Lleal M, van der Laan SW, Miller CL, Wirka RC, Kronqvist M, et al. PCSK6 Is a Key Protease in the Control of Smooth Muscle Cell Function in Vascular Remodeling. CIRC RES. 2020;126(5):571–85. Rohl S, Suur BE, Lengquist M, Seime T, Caidahl K, Hedin U, Arner A, Matic L, Razuvaev A. Lack of PCSK6 Increases Flow-Mediated Outward Arterial Remodeling in Mice. CELLS-BASEL 2020, 9(4). Li JJ, Liu J, Lupino K, Liu X, Zhang L, Pei L. Growth Differentiation Factor 15 Maturation Requires Proteolytic Cleavage by PCSK3, -5, and – 6. MOL CELL BIOL 2018, 38(21). Mori K, Kii S, Tsuji A, Nagahama M, Imamaki A, Hayashi K, Akamatsu T, Nagamune H, Matsuda Y. A novel human PACE4 isoform, PACE4E is an active processing protease containing a hydrophobic cluster at the carboxy terminus. J BIOCHEM. 1997;121(5):941–8. Panet F, Couture F, Kwiatkowska A, Desjardins R, Guerin B, Day R. PACE4 is an important driver of ZR-75-1 estrogen receptor-positive breast cancer proliferation and tumor progression. EUR J CELL BIOL. 2017;96(5):469–75. Bassi DE, Mahloogi H, Klein-Szanto AJ. The proprotein convertases furin and PACE4 play a significant role in tumor progression. Mol Carcinog. 2000;28(2):63–9. Testa G, Staurenghi E, Giannelli S, Sottero B, Gargiulo S, Poli G, Gamba P, Leonarduzzi G. Up-regulation of PCSK6 by lipid oxidation products: A possible role in atherosclerosis. Biochimie. 2021;181:191–203. Chistiakov DA, Orekhov AN, Bobryshev YV. Vascular smooth muscle cell in atherosclerosis. Acta Physiol (Oxf). 2015;214(1):33–50. Wang F, Wang L, Jiang H, Chang X, Pan J. Inhibition of PCSK6 may play a protective role in the development of rheumatoid arthritis. J RHEUMATOL. 2015;42(2):161–9. Malfait AM, Seymour AB, Gao F, Tortorella MD, Le Graverand-Gastineau MP, Wood LS, Doherty M, Doherty S, Zhang W, Arden NK, et al. A role for PACE4 in osteoarthritis pain: evidence from human genetic association and null mutant phenotype. ANN RHEUM DIS. 2012;71(6):1042–8. Ruotsalainen SE, Partanen JJ, Cichonska A, Lin J, Benner C, Surakka I, Reeve MP, Palta P, Salmi M, Jalkanen S, et al. An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease. EUR J HUM GENET. 2021;29(2):309–24. Hunt R, Sauna ZE, Ambudkar SV, Gottesman MM, Kimchi-Sarfaty C. Silent (Synonymous) SNPs: Should We Care About Them? Methods in Molecular Biology 2009, 578:23. Ho PA, Kuhn J, Gerbing RB, Pollard JA, Zeng R, Miller KL, Heerema NA, Raimondi SC, Hirsch BA, Franklin JL, et al. WT1 synonymous single nucleotide polymorphism rs16754 correlates with higher mRNA expression and predicts significantly improved outcome in favorable-risk pediatric acute myeloid leukemia: a report from the children's oncology group. J CLIN ONCOL. 2011;29(6):704–11. Gaither J, Lammi GE, Li JL, Gordon DM, Kuck HC, Kelly BJ, Fitch JR, White P. Synonymous variants that disrupt messenger RNA structure are significantly constrained in the human population. GIGASCIENCE 2021, 10(4). Wakim V, Abi KE, Salloum AK, Khazen G, Ghassibe-Sabbagh M, Zalloua PA. New susceptibility alleles associated with severe coronary artery stenosis in the Lebanese population. BMC MED GENOMICS. 2021;14(1):90. Tables Table1. Primer or probe sequences and PCR or LDR product length of the snps Variants Primer or Probe Sequence (5′–3′) PCR or LDR Rs1135911 Up CCCTTCCTACACATTCCA 35 Down ACCTGCTAGTGAAGACATC TC CTGACTGACGCACCTTTATGACCCGCGCCGTTC 30 TT CTGACTGACTGCGCACCTTTATGACCCGCGCCGTTT TR ACTTTCCAGTCGCTCGCTTTCAGGTCTGACT Up GCAGGGTCAATCTCAGTG 35 Down GTTCGCACCTCCATCTCA Rs20543 TA CTGACTGACTGACTGCCTCGCCTTACCTCTTTGCCAA 30 TG CTGACTGACTGACTGCTGCCTCGCCTTACCTCTTTGCCAG TR AAGTTGAGACTTGGTTCCCGAGGGACTGACTGAC Table2. Baseline characteristics of IS and control group Characteristics Cases ( n = 432) Controls ( n = 448) χ2或t P Sex(male)(%) 252(58.3） 267(59.6） 0.145 0.703 HBP(%) 328(75.9) 220(49.2) 67.329 0.000 * DM(%) 86(19.9) 56(12.5) 8.917 0.003 * Smoking(%) 133(30.8) 103(23.0) 6.811 0.009 * Drinking(%) 120(27.8) 108(24.1) 1.544 0.214 Age,year(mean + SD) 62.51±9.90 61.77±9.34 -1.082 0.280 TC(mean + SD) 4.36±1.12 4.36±1.02 -0.030 0.976 TG(mean + SD) 1.74±1.27 1.56±1.20 -2.082 0.038 * HDL-C(mean + SD) 1.12±0.32 1.22±0.41 4.014 0.000 * LDL-C(mean + SD) 2.84±1.00 2.78±0.91 -1.016 0.310 HCY(mean + SD) 15.29±8.43 13.08±4.14 -4.972 0.000 * BMI(mean + SD) 23.63±3.40 23.25±3.06 -1.723 0.085 * p＜0.05 Table3. Association of PCSK6 snps with susceptibility of LAS Control(n=448) Case(n=432) OR(95% CI) a P a rs1135911 CC 283（63.2%） 242（56.0%） 1.260(0.932-1.703) 1.111(0.633-1.950) CT 137（30.6%） 158（36.6%） 0.133 TT 28(6.3%) 32(7.4%) 0.715 rs20543 AA 242（54.0%） 168（38.9%） GA 170（37.9%） 214（49.5%） 1.925(1.427-2.596) 0.000 GG 36（8.0%） 50（11.6%） 1.802(1.099-2.956) 0.020 Dominant model GG 36 50 AA+GA 412 382 0.765(0.478-1.226) 0.266 Recessive model GG+GA AA 206 242 264 168 0.526(0.396-0.699) 0.000 a Data were calculated by logistic regression analysis with adjusted for HBP, DM, smoking, TG, HDL-C, HCY Table 4. Association of PCSK6 snps with the location of the cerebrovascular stenosis Rs1135911 CC CT TT χ2 P intracranial 121 83 23 7.697 0.103 extracranial 104 60 6 intracranial+ extracranial 17 15 3 anterior 168 102 17 4.908 0.297 posterior 70 53 15 anterior+posterior 4 3 0 Rs20543 AA GA GG intracranial 93 109 25 2.067 0.723 extracranial 60 90 20 intracranial+ extracranial 15 15 5 anterior 112 141 34 1.712 0.788 posterior 54 68 16 anterior+posterior 2 5 0 Additional Declarations No competing interests reported. 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-3847948","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269554176,"identity":"cd373eac-c4bc-4bfa-b1ca-4ff53937c658","order_by":0,"name":"Haiyan Chen","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Haiyan","middleName":"","lastName":"Chen","suffix":""},{"id":269554177,"identity":"31df8d89-f504-4bd4-aadb-0bd71b446b58","order_by":1,"name":"Yanfang Yun","email":"","orcid":"","institution":"The Third People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Yanfang","middleName":"","lastName":"Yun","suffix":""},{"id":269554178,"identity":"3d2e7602-d7b2-4b81-aecc-2dcfcfe7caf6","order_by":2,"name":"Guixin Yang","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Guixin","middleName":"","lastName":"Yang","suffix":""},{"id":269554179,"identity":"82cc8b9f-7a8b-4cb8-a33d-3db964ac3207","order_by":3,"name":"Huadan Yang","email":"","orcid":"","institution":"The Third People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Huadan","middleName":"","lastName":"Yang","suffix":""},{"id":269554180,"identity":"e1f38ff5-a977-44d7-b15d-2d6ee3fa7248","order_by":4,"name":"Yongming Jiang","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Yongming","middleName":"","lastName":"Jiang","suffix":""},{"id":269554181,"identity":"11fb55a3-65d7-47de-96dd-ae5637c8f4a2","order_by":5,"name":"Baoying Wei","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Baoying","middleName":"","lastName":"Wei","suffix":""},{"id":269554182,"identity":"95949ce4-750f-4129-90eb-14f6c79c65f0","order_by":6,"name":"Yingjie Zhou","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Yingjie","middleName":"","lastName":"Zhou","suffix":""},{"id":269554183,"identity":"c73960a2-0efa-4894-94eb-ec3309ae5178","order_by":7,"name":"Shengshan Yuan","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Shengshan","middleName":"","lastName":"Yuan","suffix":""},{"id":269554184,"identity":"baf5fb61-932b-45b4-af71-f4266eba999b","order_by":8,"name":"Jianjun Huang","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Jianjun","middleName":"","lastName":"Huang","suffix":""},{"id":269554185,"identity":"76192431-330a-4ff2-900c-7a052293c411","order_by":9,"name":"Yingning Wu","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Yingning","middleName":"","lastName":"Wu","suffix":""},{"id":269554186,"identity":"3199a0c0-d2fa-437c-8829-a398f6a35f65","order_by":10,"name":"Jianmin Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBACAwYeMM3MBiITGGx4+NkbSNOSJiPZc4A4LTBw2MbghgN+Leb8Z49J/NxRy87Hfvbohoc7zvMw3GBg/PAxB7cWyxl5aZK9Z44zs/Hkpd1IPHObh3F2A7PkzG14HHaDx0yCt+0Y0C85ZjcS227zMMscYGPmxafl/Bkzyb8gLfxvQFrO8bBJJBDQciDHTJq3rYaZTQJsywEeHkJaLGfkGFvLth0AagHbkswjwXOwGa9fzPnPGN5821aXLN+fY3bzZ5udvf3x5oMfPuLRAgWHk5E4jA0E1QNBnR0xqkbBKBgFo2CEAgAf/E6dPzHVEAAAAABJRU5ErkJggg==","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":true,"prefix":"","firstName":"Jianmin","middleName":"","lastName":"Huang","suffix":""},{"id":269554187,"identity":"6af8b7c3-b5ce-44ac-8688-c7a4db4acc54","order_by":11,"name":"Xuebin Li","email":"","orcid":"","institution":"the Affiliated Hospital of Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Xuebin","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-01-09 10:29:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3847948/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3847948/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50392720,"identity":"cca0595a-b1c9-4590-a04f-56f33bce09d9","added_by":"auto","created_at":"2024-01-30 19:40:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":252824,"visible":true,"origin":"","legend":"\u003cp\u003eExpression quantitative trait loci (eQTL) anlysis of rs20543 with gene expression in single tissue (A) and basal ganglia(B)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3847948/v1/159feec645cd809f8c6cc4b7.png"},{"id":51309509,"identity":"684f8420-164d-4fcd-b879-c10f96e18fe1","added_by":"auto","created_at":"2024-02-19 10:22:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":555937,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3847948/v1/29ed0c67-81af-402b-9618-47a6a9a46bab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of PCSK6 polymorphisms with susceptibility risk of large artery atherosclerotic stroke","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStroke is an acute cerebrovascular disease, including ischemic and hemorrhagic stroke, of which ischemic stroke accounts for 85% of all strokes, and is considered to be one of the leading causes of human death and disability worldwide\u0026nbsp;[1]. According to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria[2], ischemic stroke etiologies are categorized as large artery atherosclerosis（LAA）, cardioembolism(CE), small artery occlusion(SAO), stroke of other determined etiology(SOE) and stroke of undetermined etiology(SUE). It is of vital significance to identify and diagnose ischemic stroke as early as possible. Large artery atherosclerosis (LAA) is the most common type of cerebral infarction which is characterized by high morbidity, high disability, high recurrence rate, and high mortality[3]. The risk factors of atherosclerosis include dyslipidemia，hypertension，diabetes mellitus and inflammatory stress[4, 5]. Besides environmental aspect, genetic factors also play a substantial role in the pathogenesis of atherosclerosis[6]. Single nucleotide polymorphism (snp) is the most common genetic variation in human body, account for much of the phenotypic diversity among individuals, and also closely related to numerous pathological states in humans[7, 8].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProprotein convertases(PCs)\u0026nbsp;are a class of Ca\u003csup\u003e2+\u003c/sup\u003e-dependent serine endoprotease, which can activate one or more endosite sites of precursor proteins by restriction proteolysis, involved in the regulation of cells proliferation, differentiation, adhesion and invasion, thus, it plays a significant role in the development of multiple disorders and diseases[9, 10]. At present, at least 9 members of PCs family have been identified, including PCSK1, PCSK2, PCSK3 (furin), PCSK4, PCSK5, PCSK6(PACE4) and PCSK7[10].\u0026nbsp;Proprotein convertase subtilisin/kexin type 6 (PCSK6) is one of the important members of the PCs, and is expressed broadly in various tissues such as the brain, liver, nervous system and intestine[11].\u0026nbsp;PCSK6 is an intercellular binding protein, which is localized to the cell membrane and binds to the membrane-associated substrates via its cysteine-rich regions, and converts inactive precursors such as nerve and peptide hormones, proteolytic enzymes, growth factors, type I membrane binding proteins including receptors, cell adhesion molecules, cell surface glycoproteins, cell signals and transcription factors into their active forms through the cleavage of coupled amino acids[12].\u0026nbsp;Previous investigations reported that \u003cem\u003ePCSK6\u003c/em\u003e is an oncogene which is overexpressed in many cancers such as breast cancer, prostate cancer and thyroid carcinomas, and play an important regulatory role in angiogenesis, tumor cell growth, and metastasis[13-16]. A previous study analyzed differential expression of the mRNA and protein expression levels of PCSK6 between unstable carotid plaque and stable carotid plaque using microarray analysis, and found that PCSK6 may be involved in atherosclerosis pathogenesis through the regulation of inflammatory responses and extracellular matrix remodeling[17]. Recently, the association between PCSK6 and vascular is becoming a research hotspot. In 2020,\u0026nbsp;Rykaczewska\u0026nbsp;et al\u0026nbsp;[18]has identified that PCSK6 is associated with carotid intima-medial thickness, is an index for atherosclerosis, and immunohistochemistry confirmed that PCSK6 localize in smooth muscle actin positive cells of the fibrous cap and the neovascular, PCSK6 is increased after arterial injury in a mice carotid artery balloon injury model, and the levels positively correlate with the level of some inflammatory factors such as\u0026nbsp;PDGFB, MMP2/MMP14. Similarly, another study[19]\u0026nbsp;found the contractile markers, extracellular matrix remodeling enzymes and cytokines / receptors of carotid VSMC decreased significantly in \u003cem\u003ePCSK6\u003c/em\u003e knockout mice,\u0026nbsp;and vascular intimal hyperplasia was significantly reduced. In view of the above facts, \u003cem\u003ePCSK6\u003c/em\u003e might favor cerebral arteriosclerosis by remodeling the cerebral vasculature, and \u0026nbsp;promotes the development of LAA stroke（LAAS）, while the role of \u003cem\u003ePCSK6\u003c/em\u003e polymorphism in LAAS has rarely been reported, hence, in the present study, we determined the relevance between \u003cem\u003ePCSK6\u003c/em\u003e snps rs1135911, rs20543 and the susceptibility of LAAS.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e2.1 Study subject\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;A total of 432\u0026nbsp;LAAS\u0026nbsp;consecutive patients who were admitted into the Youjiang Medical University for nationalities between January 2018 to June 2022 were enrolled as a case group. Meanwhile, and 448 sex- and age-matched healthy adult volunteers were enrolled as a control group. The diagnosis of IS was made according to the World Health Organization criteria, the degree of cerebrovascular stenosis was assessed using digital subtraction angiography (DSA), and large-artery atherosclerosis stroke was derived from the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) stroke subtype classification system[2]. Exclusion criteria for all participants were as follows: intracranial hemorrhage, transient ischemic attack, atrial fibrillation, malignancy, severe hepatic, genetic diseases, cardiac or other organ impairment, infection and malignancy. During admission, all patients underwent computed tomography angiography or digital subtraction angiography to evaluated cerebral vascular stenosis. The main characteristics of all participants were collected including gender, age, BMI, blood routine examination, blood pressure, smoking status, lipid levels, and so on. This study was approved by the Ethics Review Board of he Affiliated Hospital of Youjiang Medical University for nationalities, and informed written consent was signed by all the participants.\u003c/p\u003e\n\u003cp\u003e2.2 Clinical data\u003c/p\u003e\n\u003cp\u003eGeneral information and related biochemical information including age, sex, diabetes duration, height, weight, body mass index (BMI), smoking history, and alcohol consumption of the participants were recorded. Fasting venous blood(8 ml) was drawn by venipuncture from all the participants, half of them were used for biochemical analyses, and the other half were reserved for DNA extraction.\u0026nbsp;High blood pressure(HBP) was defined as a documented history of high blood pressure or treatment with anti-hypertensive medications or blood pressure \u0026ge; 140/90mmHg(average of three independent measures). Diabetes mellitus(DM) was defined as typical polydipsia, polyuria, polyphagia, weight loss symptoms plus random blood glucose \u0026gt; 11.1mmol/L or fasting blood glucose \u0026ge; 7.0mmol/L, or previous diabetes diagnosis was clear, and hypoglycemic drugs or insulin were used. Drinking history was defined as alcohol consumed \u0026gt;50 g per day lasting for at least 1 year, smoking history was defined as having smoked at least 100 cigarettes over the life time, respectively. High-density lipoprotein cholesterol (HDL-C) \u0026lt; 1.0 mmol/L was defined as abnormal HDL-C, triglyceride(TG) values \u0026ge;1.7 mmol/L was defined as abnormal TG. Hyperhomocysteinemia (HHcy) was defined as plasma Hcy level\u0026nbsp;＞15 \u0026mu;mol/L. Normal body mass index( BMI) was defined as 18.5 \u0026le; BMI \u0026lt; 25.\u003c/p\u003e\n\u003cp\u003e2.3 Cerebrovascular Stenosis assessment\u003c/p\u003e\n\u003cp\u003ePatients included in the case group received cerebral angiography to assess stenosis of major cerebral vessels.\u0026nbsp;According to Boutillier\u0026apos;s seven-segment method of internal carotid artery, the composition of extracranial arteries includes the common carotid artery, internal carotid artery (C1-C5 segment), and vertebral artery (V1-V3 segment). The internal carotid artery (C6\u0026ndash;C7 segments), vertebral artery (V4 segment), middle cerebral artery, anterior cerebral artery, posterior cerebral artery, and basilar artery constitute the intracranial vessels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.4 \u003cem\u003ePCSK6\u003c/em\u003e Genotyping\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from venous blood using a DNA extraction kit (Tiangen, Beijin, China), then PCR was performed to obtain the target gene fragments. Ligase detection reaction (LDR) was used to genotype rs1135911 and rs20543 variants. The primer and probe sequences, as well as the lengths of PCR and LDR for each variant, are listed in Table 1.\u0026nbsp;The PCR reaction system included 1\u0026mu;L gDNA, 0.6 \u0026mu;L primer, 7.5\u0026mu;L PCR mix，5.9\u0026mu;L ddH2O.\u0026nbsp;Further amplification was conducted in 10\u0026mu;L multiplex LDR reaction mixtures, containing 3\u0026mu;L of original PCR product, 1\u0026mu;L of 10\u0026times;Taq DNA ligase buffer, 0.125\u0026mu;L of Taq DNA ligase, and 2.875\u0026mu;L of ddH2O, 3\u0026mu;L of probe mix. The conditions of LDR were as follows：denaturation at 94℃ for 20s, annealing at 58℃ for 90 s, with 30 cycles, then 1 \u0026mu;L reaction product plus with 9 \u0026mu;L HIDI, were denatured at 95℃ for 3 minutes，immediately ice bath，then samples were run on an ABI 3730 sequencer (Applied Biosystems). Results were analyzed using GeneMarker.\u003c/p\u003e\n\u003cp\u003e2.5 Statistical analysis\u003c/p\u003e\n\u003cp\u003eThe SPSS statistical software package version 26.0 (SPSS, Chicago, USA) was used for all of the statistical analysis. Student t test was used for continuous data and Pearson chi-square (\u0026chi;2) test for categorical data. Univariate logistic regression was performed to examine the association between the genotypes of the different snps and LAAS. All statistical tests were two sided and statistical significance was measured by p -values less than 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e3.1 Baseline characteristics of case and control groups\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; The baseline characteristics of the LAS patients and control groups are listed in table2. Compared with the control group, the case group had a larger proportion of individuals with HBP, DM and smokers, and levels of HCY, TG were significantly increased, level of HDL-C were significantly decreased (All P＜0.05). No significant differences were found between the two groups in terms of sex, age, drinking history, TC, LDL-C and BMI.\u003c/p\u003e\n\u003cp\u003e3.2 Association between \u003cem\u003ePCSK6\u003c/em\u003e polymorphisms and LAAS risk\u003c/p\u003e\n\u003cp\u003eAll tested groups were in Hardy-Weinberg equilibrium(P=0.96 for rs20543, P=0.117 for rs1135911), indicating that the samples were from a population with genetic balance and had good representativeness. We conducted logistic regression analysis to compare snp genotype between cases and controls, genotype distributions of each snp and their associations with LAAS risk was shown in Table 3. As is shown in table 3, rs20543 polymorphisms are closely associated with LAAS disease susceptibility, after adjusted for HBP, DM, smoking, TG, HDL-C and HCY, subjects with the AA exhibited a significantly lower risk of LAAS compared with the GG genotype, GA genotype and GG+GA genotype (Recessive model:\u0026nbsp;OR = 0.526, 95% CI =0.396-0.699,\u0026nbsp;P\u0026nbsp;＜0.001). There was no significant difference in the distribution of rs1135911 between the case group and the control group.\u003c/p\u003e\n\u003cp\u003e3.3 Association between \u003cem\u003ePCSK6\u003c/em\u003e polymorphisms and Location of Cerebral Vascular Stenosis\u003c/p\u003e\n\u003cp\u003eTo understand association of rs20543 and rs1135911 with the location of the cerebrovascular stenosis, we subgrouped the subjects based on the status of cerebrovascular stenosis, and compared the genotype distribution of different groups(Table4 ). Unfortunately, we do not find any clear relationship between \u003cem\u003ePCSK6\u003c/em\u003e snps and location of cerebrovascular stenosis.\u003c/p\u003e\n\u003cp\u003e3.4 Bioinformatics analysis\u003c/p\u003e\n\u003cp\u003eWe examined the potential effects of snp rs20543 on gene expression in multiple tissues by the Genotype-Tissue Expression database (http://www.gtexportal.org/home/). The analysis of expression quantitative trait loci (eQTL) showed the rs20543 snp were associated with expression of PCSK6 in single tissue (Fig. 1A), and rs20543 GG genotype carriers having higher PCSK6 expression than the AA genotype carriers, in basal ganglia for example(Fig. 1B) (P \u0026lt; 0.005).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the current study,we explored the association between \u003cem\u003ePCSK6\u003c/em\u003e snps and the risk of AIS. Significant differences were observed in the distribution of the rs20543 GG/GA genotype between controls and cases. After adjusting for multiple cofactors such as\u0026nbsp;HBP, DM, smoking, TG, HDL-C, HCY, the difference remained statistically significant.\u0026nbsp;\u003cem\u003ePCSK6\u003c/em\u003e rs20543 GG, GA genotype were associated with increased risk of LAAS, AA genotype and recessive model might be a protective factor to decrease the risk of LAAS. We further analyzed the association of\u0026nbsp;snps and the distribution of cerebral arterial stenosis. Besides, no statistical difference was found in the distribution of rs1135911 in two groups, either.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePCSK6\u003c/em\u003e is\u0026nbsp;also named as PACE4, which encode a member of the subtilisin-like proprotein convertase family PCSK6. The encoded protease \u003cem\u003ePCSK6\u003c/em\u003e is constitutively secreted into the extracellular matrix and expressed in many tissues, including liver, gut, and brain.\u0026nbsp;This gene encodes one of the seven basic amino acid-specific members which cleave their substrates at single or paired basic residues.\u0026nbsp;Some of its substrates include transforming growth factor beta related proteins, proalbumin, and von Willebrand factor[20, 21].\u0026nbsp;PCSK6 is thought to play a role in tumor progression\u0026nbsp;[22, 23].\u0026nbsp;Recent studies have found PCSK6 is closely associated with vascular remodeling and atherosclerotic processes[6, 24]. Vascular smooth muscle cells (VSMCs) are involved in all stages of the progression of atherosclerosis.\u0026nbsp;When blood vessels are damaged,\u0026nbsp;VSMCs can switch from the contractile to the synthetic phenotype,\u0026nbsp;promote proliferation and migration of VSMCs. The development of atherosclerosis usually correlates with abnormal proliferation, migration and apoptosis of smooth muscle cells[25].\u0026nbsp;A recent study showed that \u003cem\u003ePCSK6\u003c/em\u003e gene silencing leads to downregulation of VSMC contractile markers and decreased MMP2 expression, instead, \u003cem\u003ePCSK6\u003c/em\u003e gene overexpression increases VSMC proliferation and migration induced by PDGFB[19].\u0026nbsp;A previous study[18]\u0026nbsp;suggested that \u003cem\u003ePCSK6\u003c/em\u003e snps was associated with artery intima-media thickness, intimal thickening is considered to be a manifestation of atherosclerosis. Also, associations of \u003cem\u003ePCSK6\u003c/em\u003e snps with other diseases have been reported, such as, \u003cem\u003ePCSK6\u003c/em\u003e snp rs8029797 inflammasome-driven inflammatory response is implicated in rheumatoid arthritis[26], a variant rs900414 in \u003cem\u003ePCSK6\u003c/em\u003e is strongly associated with protection against pain in knee osteoarthritis pain[27], a number of\u0026nbsp;snps of \u003cem\u003ePCSK6\u003c/em\u003e are associated with lipid metabolism and inflammation[28]. Based on the above facts,\u0026nbsp;snps of \u003cem\u003ePCSK6\u003c/em\u003e may be associated with LAAS to some extent. Therefore, we performed our study, Our results confirmed our hypothesis. In our present study,\u0026nbsp;\u0026nbsp;we found rs20543 was associated with increased risk of LAAS.\u003c/p\u003e\n\u003cp\u003eRs20543 G\u0026gt;A is a synonymous mutation at the exon 13 of \u003cem\u003ePCSK6\u003c/em\u003e, which lead to a G to A，GAC/AAC,\u003c/p\u003e\n\u003cp\u003edid not result in amino acid changes. Although the synonymous snps do not change the expression of amino acids, it may still play an important role in molecular genetics. Synonymous snps may represent genetic markers with functional molecular changes, and are in linkage disequilibrium with them; In addition, studies have shown that synonymous snps can directly change gene function and phenotype through various mechanisms, such as changing miRNA binding or protein folding, or by affecting mRNA splicing, stability or expression[29-31].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; As far as we know, despite extensive literature searches, we could not find studies for the association of rs20543and stroke. A previous study\u0026nbsp;[27]\u0026nbsp;have reported on the associations between rs20543 and osteoarthritis, while other snps of PSCK6 was found to be associated with arthritis, rather than rs20543. Nevertheless, lots of studies have been done in the recent year between the \u003cem\u003ePCSK6\u003c/em\u003e snps and risk factors for acute cerebral infarction. In 2021, a GWAS studies suggested that the \u003cem\u003ePCSK6\u003c/em\u003e snps are linked to blood lipid metabolism and inflammatory[28]. What\u0026rsquo;s more，an recent research found \u003cem\u003ePCSK6\u003c/em\u003e snps were significantly associated with severe coronary artery stenosis[32].The analysis of expression quantitative trait loci (eQTL) showed the rs20543 snps were associated with expression of PCSK6 in single tissue (Fig. 1a), and the carriers with rsrs20543 GG increased expression of PCSK6 in Brian-caudate. Our findings are compatible with this, the GG genotypes as wll as GA genotypes showed increased risk for the LAAS, indicating that the GG genotype of rs20543 was a risk factor for LAAS susceptibility.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, we investigated whether this snp is a potential candidate affecting the position of the cerebrovascular stenosis, unfortunately, we detect no significant difference between the two snps and the position of the cerebrovascular stenosis. Our research may indicate that \u003cem\u003ePCSK6\u003c/em\u003e has no selective effect on vascular remodeling and has the same effect on intracranial and extracranial vessels. These findings will help improve our understanding of the role of \u003cem\u003ePCSK6\u003c/em\u003e genetic variants in the pathogenesis of LAAS.\u003c/p\u003e\n\u003cp\u003eAlthough the results we got were promising, limitations still remained. Firstly, the sample size was small, which may limit the authenticity of the statistical analysis.\u0026nbsp;Secondly, the analysis was hospital-based, potential selection bias may exist. In addition, the population we studied came from the southwest of China, which may give rise to some limitations. There are distribution differences in polymorphisms of the same locus among different races according to the 1000 Genomes Project Data, therefore, larger sample sizes from other medical centers of different races and ethnicities are needed to further confirm the role of \u003cem\u003ePCSK6\u003c/em\u003e snps in LAAS susceptibility. Finally, the effects of PCSK6 snps on LAAS are very exciting, but its mechanism is unclear, and further studies are needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eETHICAL STATEMENT:\u003c/p\u003e\n\u003cp\u003eFunding: This study was funded by National Natural Science Foundation of China (No.81860226)\u003c/p\u003e\n\u003cp\u003eConflict of Interest: The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or any financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.\u003c/p\u003e\n\u003cp\u003eEthical approval: The research followed the principles of the Helsinki Declaration, and the ethics committees of the affiliated Hospital of Youjiang Medical University for Nationalities have approved research protocols.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent: Informed consent has been obtained from each subjects and agree to make the data public.\u003c/p\u003e\n\u003cp\u003eAuthor contribution: Yanfang Yun and Haiyan Chen performed the experiments, interpreted the results of statistical analysis, and drafted the manuscript. Haiyan Chen and Yanfang Yun contributed equally to this work. Jianmin Huang and Xuebin Li designed the study and revised the manuscript. Guixin Yang, Yongming Jiang, Baoying Wei and Yingjie Zhou completed the majority of the experiments. Shengshan Yuan , Jianjun Huang, Huadan Yang and Yingning Wu provided materials. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eData Availability Statement: All data are incorporated into the article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFeigin VL, Nichols E, Alam T, Bannick MS, Beghi E, Blake N, Culpepper WJ, Dorsey ER, Elbaz A, Ellenbogen RG, et al. Global, regional, and national burden of neurological disorders, 1990\u0026ndash;2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):459\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdams HP, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh EE. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. \u003cem\u003eSTROKE\u003c/em\u003e 1993, 24(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou M, Wang H, Zeng X, Yin P, Zhu J, Chen W, Li X, Wang L, Wang L, Liu Y et al. Mortality, morbidity, and risk factors in China and its provinces, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. \u003cem\u003eLANCET\u003c/em\u003e 2019, 394(10204):1145\u0026ndash;1158.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLusis AJ. Atherosclerosis Nat. 2000;407(6801):233\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo FX, Hu YW, Zheng L, Wang Q. Shear Stress in Autophagy and Its Possible Mechanisms in the Process of Atherosclerosis. DNA CELL BIOL. 2017;36(5):335\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoua PR, Brandenburg JT, Choudhury A, Sorgho H, Nonterah EA, Agongo G, Asiki G, Micklesfield L, Choma S, Gomez-Olive FX, et al. Genetic associations with carotid intima-media thickness link to atherosclerosis with sex-specific effects in sub-Saharan Africans. NAT COMMUN. 2022;13(1):855.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi HW, Shen M, Gao PY, Li ZR, Cao JL, Zhang WL, Sui BB, Wang YX, Wang YJ. Association between ADAMTS7 polymorphism and carotid artery plaque vulnerability. Med (Baltim). 2019;98(43):e17438.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZaragoza-Garcia O, Guzman-Guzman IP, Moreno-Godinez ME, Navarro-Zarza JE, Antonio-Vejar V, Ramirez M, Parra-Rojas I. PON-1 haplotype (-108C\u0026thinsp;\u0026gt;\u0026thinsp;T, L55M, and Q192R) modulates the serum levels and activity PONase promoting an atherogenic lipid profile in rheumatoid arthritis patients. CLIN RHEUMATOL. 2021;40(2):741\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStawowy P. Proprotein convertases in atherogenesis. CURR OPIN LIPIDOL. 2015;26(4):338\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArtenstein AW, Opal SM. Proprotein convertases in health and disease. N Engl J Med. 2011;365(26):2507\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConstam DB, Robertson EJ. SPC4/PACE4 regulates a TGFbeta signaling network during axis formation. Genes Dev. 2000;14(9):1146\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen S, Cao P, Dong N, Peng J, Zhang C, Wang H, Zhou T, Yang J, Zhang Y, Martelli EE, et al. PCSK6-mediated corin activation is essential for normal blood pressure. NAT MED. 2015;21(9):1048\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMbikay M, Sirois F, Yao J, Seidah NG, Chretien M. Comparative analysis of expression of the proprotein convertases furin, PACE4, PC1 and PC2 in human lung tumours. Br J Cancer. 1997;75(10):1509\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubbard FC, Goodrow TL, Liu SC, Brilliant MH, Basset P, Mains RE, Klein-Szanto AJ. Expression of PACE4 in chemically induced carcinomas is associated with spindle cell tumor conversion and increased invasive ability. CANCER RES. 1997;57(23):5226\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFradet L, Temmar R, Couture F, Belzile M, Fortier PH, Day R. Evaluation of PACE4 isoforms as biomarkers in thyroid cancer. J Otolaryngol Head Neck Surg. 2018;47(1):63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBassi DE, Mahloogi H, Klein-Szanto AJ. The proprotein convertases furin and PACE4 play a significant role in tumor progression. Mol Carcinog. 2000;28(2):63\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerisic L, Hedin E, Razuvaev A, Lengquist M, Osterholm C, Folkersen L, Gillgren P, Paulsson-Berne G, Ponten F, Odeberg J, et al. Profiling of atherosclerotic lesions by gene and tissue microarrays reveals PCSK6 as a novel protease in unstable carotid atherosclerosis. Arterioscler Thromb Vasc Biol. 2013;33(10):2432\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRykaczewska U, Suur BE, Rohl S, Razuvaev A, Lengquist M, Sabater-Lleal M, van der Laan SW, Miller CL, Wirka RC, Kronqvist M, et al. PCSK6 Is a Key Protease in the Control of Smooth Muscle Cell Function in Vascular Remodeling. CIRC RES. 2020;126(5):571\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRohl S, Suur BE, Lengquist M, Seime T, Caidahl K, Hedin U, Arner A, Matic L, Razuvaev A. Lack of PCSK6 Increases Flow-Mediated Outward Arterial Remodeling in Mice. CELLS-BASEL 2020, 9(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi JJ, Liu J, Lupino K, Liu X, Zhang L, Pei L. Growth Differentiation Factor 15 Maturation Requires Proteolytic Cleavage by PCSK3, -5, and \u0026ndash;\u0026thinsp;6. MOL CELL BIOL 2018, 38(21).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMori K, Kii S, Tsuji A, Nagahama M, Imamaki A, Hayashi K, Akamatsu T, Nagamune H, Matsuda Y. A novel human PACE4 isoform, PACE4E is an active processing protease containing a hydrophobic cluster at the carboxy terminus. J BIOCHEM. 1997;121(5):941\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanet F, Couture F, Kwiatkowska A, Desjardins R, Guerin B, Day R. PACE4 is an important driver of ZR-75-1 estrogen receptor-positive breast cancer proliferation and tumor progression. EUR J CELL BIOL. 2017;96(5):469\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBassi DE, Mahloogi H, Klein-Szanto AJ. The proprotein convertases furin and PACE4 play a significant role in tumor progression. Mol Carcinog. 2000;28(2):63\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTesta G, Staurenghi E, Giannelli S, Sottero B, Gargiulo S, Poli G, Gamba P, Leonarduzzi G. Up-regulation of PCSK6 by lipid oxidation products: A possible role in atherosclerosis. Biochimie. 2021;181:191\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChistiakov DA, Orekhov AN, Bobryshev YV. Vascular smooth muscle cell in atherosclerosis. Acta Physiol (Oxf). 2015;214(1):33\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang F, Wang L, Jiang H, Chang X, Pan J. Inhibition of PCSK6 may play a protective role in the development of rheumatoid arthritis. J RHEUMATOL. 2015;42(2):161\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalfait AM, Seymour AB, Gao F, Tortorella MD, Le Graverand-Gastineau MP, Wood LS, Doherty M, Doherty S, Zhang W, Arden NK, et al. A role for PACE4 in osteoarthritis pain: evidence from human genetic association and null mutant phenotype. ANN RHEUM DIS. 2012;71(6):1042\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuotsalainen SE, Partanen JJ, Cichonska A, Lin J, Benner C, Surakka I, Reeve MP, Palta P, Salmi M, Jalkanen S, et al. An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease. EUR J HUM GENET. 2021;29(2):309\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHunt R, Sauna ZE, Ambudkar SV, Gottesman MM, Kimchi-Sarfaty C. Silent (Synonymous) SNPs: Should We Care About Them? \u003cem\u003eMethods in Molecular Biology\u003c/em\u003e 2009, 578:23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHo PA, Kuhn J, Gerbing RB, Pollard JA, Zeng R, Miller KL, Heerema NA, Raimondi SC, Hirsch BA, Franklin JL, et al. WT1 synonymous single nucleotide polymorphism rs16754 correlates with higher mRNA expression and predicts significantly improved outcome in favorable-risk pediatric acute myeloid leukemia: a report from the children's oncology group. J CLIN ONCOL. 2011;29(6):704\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaither J, Lammi GE, Li JL, Gordon DM, Kuck HC, Kelly BJ, Fitch JR, White P. Synonymous variants that disrupt messenger RNA structure are significantly constrained in the human population. \u003cem\u003eGIGASCIENCE\u003c/em\u003e 2021, 10(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWakim V, Abi KE, Salloum AK, Khazen G, Ghassibe-Sabbagh M, Zalloua PA. New susceptibility alleles associated with severe coronary artery stenosis in the Lebanese population. BMC MED GENOMICS. 2021;14(1):90.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable1. Primer or probe sequences and PCR or LDR product length of the snps\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" valign=\"top\"\u003e\n \u003cp\u003eVariants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003ePrimer or Probe\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"top\"\u003e\n \u003cp\u003eSequence (5\u0026prime;\u0026ndash;3\u0026prime;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003ePCR or LDR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRs1135911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"top\"\u003e\n \u003cp\u003eCCCTTCCTACACATTCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.085889570552148%\" valign=\"top\"\u003e\n \u003cp\u003eDown\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.100204498977504%\" valign=\"bottom\"\u003e\n \u003cp\u003eACCTGCTAGTGAAGACATC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.813905930470348%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.085889570552148%\" valign=\"top\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.100204498977504%\" valign=\"top\"\u003e\n \u003cp\u003eCTGACTGACGCACCTTTATGACCCGCGCCGTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.813905930470348%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.085889570552148%\" valign=\"top\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.100204498977504%\" valign=\"top\"\u003e\n \u003cp\u003eCTGACTGACTGCGCACCTTTATGACCCGCGCCGTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.813905930470348%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.085889570552148%\" valign=\"top\"\u003e\n \u003cp\u003eTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.100204498977504%\" valign=\"top\"\u003e\n \u003cp\u003eACTTTCCAGTCGCTCGCTTTCAGGTCTGACT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.813905930470348%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003eUp\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"top\"\u003e\n \u003cp\u003eGCAGGGTCAATCTCAGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"bottom\"\u003e\n \u003cp\u003eGTTCGCACCTCCATCTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" valign=\"top\"\u003e\n \u003cp\u003eRs20543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003eTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"top\"\u003e\n \u003cp\u003eCTGACTGACTGACTGCCTCGCCTTACCTCTTTGCCAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003eTG \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"top\"\u003e\n \u003cp\u003eCTGACTGACTGACTGCTGCCTCGCCTTACCTCTTTGCCAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.908450704225352%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.014084507042252%\" valign=\"top\"\u003e\n \u003cp\u003eTR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.88028169014085%\" valign=\"top\"\u003e\n \u003cp\u003eAAGTTGAGACTTGGTTCCCGAGGGACTGACTGAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.197183098591548%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eTable2.\u0026nbsp;Baseline characteristics of IS and control group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003eCases (\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 432)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eControls (\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 448)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;2或t\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eSex(male)(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e252(58.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e267(59.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eHBP(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e328(75.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e220(49.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e67.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eDM(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e86(19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e56(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e8.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003csup\u003e*\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eSmoking(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e133(30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e103(23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e6.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003csup\u003e*\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eDrinking(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e120(27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e108(24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e1.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eAge,year(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e62.51\u0026plusmn;9.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e61.77\u0026plusmn;9.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e-1.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eTC(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e4.36\u0026plusmn;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e4.36\u0026plusmn;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eTG(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e1.74\u0026plusmn;1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1.56\u0026plusmn;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e-2.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eHDL-C(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e1.12\u0026plusmn;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1.22\u0026plusmn;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e4.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eLDL-C(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e2.84\u0026plusmn;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e2.78\u0026plusmn;0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e-1.016\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eHCY(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e15.29\u0026plusmn;8.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e13.08\u0026plusmn;4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e-4.972\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.6984126984127%\" valign=\"top\"\u003e\n \u003cp\u003eBMI(mean + SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.682539682539684%\" valign=\"top\"\u003e\n \u003cp\u003e23.63\u0026plusmn;3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e23.25\u0026plusmn;3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e-1.723\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063492063492063%\" valign=\"top\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003ep＜0.05\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eTable3. Association of \u003cem\u003ePCSK6\u003c/em\u003e snps with susceptibility of LAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003eControl(n=448)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003eCase(n=432)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.74647887323944%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eOR(95% CI)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003ers1135911 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e283（63.2%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e242（56.0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.654929577464788%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.260(0.932-1.703)\u003c/p\u003e\n \u003cp\u003e1.111(0.633-1.950)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.161971830985915%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.804878048780488%\" valign=\"top\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.365853658536587%\" valign=\"top\"\u003e\n \u003cp\u003e137（30.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.365853658536587%\" valign=\"top\"\u003e\n \u003cp\u003e158（36.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.463414634146343%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.133 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.804878048780488%\" valign=\"top\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.365853658536587%\" valign=\"top\"\u003e\n \u003cp\u003e28(6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.365853658536587%\" valign=\"top\"\u003e\n \u003cp\u003e32(7.4%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.463414634146343%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003ers20543\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e242（54.0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e168（38.9%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e170（37.9%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e214（49.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.925(1.427-2.596)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e36（8.0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e50（11.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.802(1.099-2.956)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eDominant model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eAA+GA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.765(0.478-1.226)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eRecessive model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.74647887323944%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.070422535211268%\" valign=\"top\"\u003e\n \u003cp\u003eGG+GA\u003c/p\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.309859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.816901408450704%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.526(0.396-0.699)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eData were calculated by logistic regression analysis with adjusted for HBP, DM, smoking, TG, HDL-C, HCY\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eTable 4. Association of \u003cem\u003ePCSK6\u003c/em\u003e snps with the location of the cerebrovascular stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eRs1135911\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.809859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.035211267605634%\" valign=\"top\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.809859154929576%\" valign=\"top\"\u003e\n \u003cp\u003eintracranial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.035211267605634%\" valign=\"top\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e7.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eextracranial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eintracranial+ extracranial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.809859154929576%\" valign=\"top\"\u003e\n \u003cp\u003eanterior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.035211267605634%\" valign=\"top\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e4.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eposterior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eanterior+posterior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eRs20543\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.809859154929576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.035211267605634%\" valign=\"top\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.809859154929576%\" valign=\"top\"\u003e\n \u003cp\u003eintracranial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.035211267605634%\" valign=\"top\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e2.067\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.723\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eextracranial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eintracranial+ extracranial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.809859154929576%\" valign=\"top\"\u003e\n \u003cp\u003eanterior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.035211267605634%\" valign=\"top\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.56338028169014%\" valign=\"top\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e1.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37323943661972%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.788\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eposterior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.81151832460733%\" valign=\"top\"\u003e\n \u003cp\u003eanterior+posterior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.921465968586388%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.706806282722512%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.56020942408377%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"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":"","lastPublishedDoi":"10.21203/rs.3.rs-3847948/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3847948/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRecent studies have shown that \u003cem\u003ePCSK6\u003c/em\u003e is significantly associated with dyslipidemia, inflammatory reaction, cardiovascular diseases, atherosclerosis. However, the relationship between \u003cem\u003ePCSK6\u003c/em\u003e polymorphisms and large artery atherosclerosis stroke has not been reported. We performed this study to investigate whether the \u003cem\u003ePCSK6\u003c/em\u003e polymorphism is associated with risk of large artery atherosclerosis (LAA) stroke in the Chinese population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eOur study enrolled a total of 432 large artery atherosclerosis stroke cases and 448 healthy controls, cases and controls were genotyped at the polymorphic sites rs1135911 and rs20543. Multivariate logistic regression analyses were performed to analyze the associations between two snps and large artery atherosclerosis stroke susceptibility.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBoth rs1135911 and rs20543 were not associated with the distribution of responsible vessel stenosis in ischemic stroke. No significant effect was observed between the rs1135911 polymorphism and LAA stroke. Rs20543 was significantly correlated with LAA stroke (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), such difference remained statistically significant after adjusting for smoking history, hypertension, hypertriglyceridemia, high density lipoprotein cholesterol, and hyperhomocysteinemia, the difference remained significant (Recessive model: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000, OR\u0026thinsp;=\u0026thinsp;0.526, 95%CI\u0026thinsp;=\u0026thinsp;0.396\u0026ndash;0.699 ).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRs20543 AA genotype may be a protective factor for LAA stroke in Chinese population.\u003c/p\u003e","manuscriptTitle":"Association of PCSK6 polymorphisms with susceptibility risk of large artery atherosclerotic stroke","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-30 19:40:20","doi":"10.21203/rs.3.rs-3847948/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":"4671e7af-0503-477f-89e1-e936fddbf34c","owner":[],"postedDate":"January 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-18T10:42:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-30 19:40:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3847948","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3847948","identity":"rs-3847948","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}