Introduction

Alzheimer’s Disease (AD) is a commonest kind of neurodegenerative disorders with a complex pathogenesis, and has become one of the leading causes of death in elderly people1,2. It is characterized by accumulation and toxic effect of the amyloid β-peptide (Aβ) deposits and neurofibrillary tangles in brain3. Previous studies predict that the newly diagnosed AD patients are expected to reach as many as 135 million by 2050 from about 35 million in 2009 around the world if lack of the effective preventive measures4,5.

Clusterin (CLU) is considered one of the most important roles for pathogenesis of AD by influencing the structure and neurotoxic effects of Aβ deposits6,7,8, and some of the variants at CLU can affect its expression level in brain9,10. Two early genome-wide association studies (GWAS) identified a single nucleotide polymorphism (SNP) rs11136000 (T < C) significantly associated with AD in the CLU gene by analyzing the large-scale Caucasian populations11,12. In particular, Harold et al.11 and Lambert et al.12 analyzed 11,756 and 14,490 individuals from USA, UK, Ireland, Germany, France, Italy, Spain, Belgium and Finland, respectively, and both of them found that the minor allele variant of rs11136000 can reduce the risk of AD (95% confidence interval (CI) of odds ratio (OR) less than the value 1).

However, the subsequent studies report consistent13,14,15,16,17,18 and inconsistent19,20,21,22,23,24,25,26,27,28 results involved in Caucasian, Asian and African populations. For example, by analyzing 268 AD cases and 389 controls from China, Lin et al. find that the participants carrying 2 copies of minor allele in rs11136000 are associated with a decreased risk of AD17. The consistent result in North American Caucasian population is also identified by Carrasquillo et al.18. While in Canadian and Korean populations, the rs11136000 is found not associated with AD according to the studies of Bettens et al.24 and Chung et al.27, respectively. Then, two independent meta-analysis studies re-assess the results of these GWAS studies published before June 20, 2013 (18 studies) and August 31, 2014 (25 studies), respectively, and both of them found this SNP is significantly associated with AD in populations of Asian and Caucasian29,30. But among the subsequent 18 GWAS studies published after August 31, 2014, many of them report inconsistent results in the corresponding populations31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47. Moreover, by comparing the selected GWAS articles published before June 20, 2013 in the two meta-analysis studies, we find the selection is incomplete for both of them. In particular, Liu et al.29 miss two GWAS articles about Caucasian populations16,24, and Du et al.30 miss a GWAS article about Asian population27. In fact, through our further investigation, a total five related GWAS articles published before August 31, 2014 are not collected in the two meta-analysis studies48,49,50,51,52. In addition, a GWAS study about American and German populations is misclassified to the Asian ethnicity subgroup in Du et al.’s study22.

We suspected that the small-scale and incompletion or heterogeneity of the samples maybe lead to different results of these studies. In this study, we selected 50 related GWAS studies with large-scale samples from 40 articles (28,464 cases and 45,784 controls, about 40.3% increase over the total number of the previous two meta-analysis studies29,30) by searching the PubMed, ClinicalKey, AlzGene, Google Scholar, CNKI, Wanfang and VIP databases, and reevaluated the association between AD and rs11136000 polymorphism in Caucasian, Asian and Chinese population using the method of meta-analysis as previously described53,54,55,56,57,58,59,60,61,62,63. The use of more complete and larger scale samples would make the results more reliable.

Methods and Materials

Selection of literatures and GWAS studies

All of the possible studies were selected by searching the databases of PubMed (http://www.ncbi.nlm.nih.gov/pubmed, ClinicalKey (https://www.clinicalkey.com/), Wanfang (http://www.wanfangdata.com.cn/), CNKI (http://www.cnki.net/) and VIP (http://www.cqvip.com/) using the keywords: “Alzheimer’s disease”, “rs11136000”, “Clusterin” or “CLU”. The CNKI, Wanfang and VIP are very authoritative and reliable Chinese database. And then, we consulted the related studies collected in AlzGene database (http://www.alzgene.org/) which was a publicly available resource providing the information of AD genetic variants from 1,395 GWAS studies (updated April 18, 2011)64. In addition, we further queried references of these identified GWAS studies in previous steps and the articles citing them using the Google Scholar (http://scholar.google.com/).

After that, the appropriate studies were identified by the following criteria: (1) The study is a GWAS to analysis the association of rs11136000 polymorphism and AD. (2) It is a case-control design study. (3) The study provides both of the numbers of cases and controls. (4) The study provides the information about the ethnicity of each individual. (5) The detailed data for rs11136000 genotypes are available in the study.

Extraction of the related data

We extracted the related data for subsequent analysis from these identified studies: (1) each study’s publication date. (2) The first the author’s name in each of these studies. (3) The numbers of AD patients and controls of each study. (4) The sample’s ethnicity of each study. (5) The detailed genotype data of rs11136000 polymorphism both in AD patients and controls. (6) The types of genotyping platforms. (7) The key results of each study (i.e. the OR value and its 95% CI, as well as the corresponding P value). Moreover, if these results are not provided in the study directly, we would calculate them by the genotype data using the R program (http://www.r-project.org/).

Genetic model choice

The rs11136000 polymorphism contains two types of variants (T and C). T is the minor allele and C is the major allele. We assumed that they are the lower and high risk factor for AD, respectively. Then, the dominant model (TT + TC allele versus CC allele), allele model (T versus C) and recessive model (TT versus TC + CC) were used in this study. According to Table 1, all these studies were meta-analyzed using allele model, while only the studies offering CC, CT and TT genotypes data were analyzed using dominant or recessive model.

Table 1 Main information of the studies included in this meta-analysis.
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Hardy–Weinberg equilibrium (HWE) test

The HWE test of the rs11136000 polymorphism in AD patient and control groups was performed using a non-continuity correction chi-squared method with the significance level P < 0.01 as previously described65. Briefly, for the SNP in each case and control group, the simulated P values were calculated to measure the deviation from HWE based on 10,000 iterations. The R package ‘Genetics’ was used to perform the HWE test (https://cran.r-project.org/web/packages/genetics/index.html).

Heterogeneity test

In this study, the heterogeneity among the kinds of populations was measured by the two parameters, I2 value and Cochran’s Q. I2 value range from 0 to 100%, and it is calculated by Cochran’s Q according to the formula \({I}^{2}=\frac{Q-(k-1)}{Q}\times 100 \% \). The Cochran’s Q is based on a chi-squared distribution with k − 1 degrees of freedom, and k means the number of studies. Usually, the extreme, high, moderate and low heterogeneity was considered corresponding to the I 2 value of >75%, 50–75%, 25–50%, and <25%, respectively. In this study, the threshold of significant heterogeneity was set as I2 > 50% and P < 0.01 according to previous studies53,54,55,56.

Meta-analysis in entirety and subgroup

According to the results of heterogeneity test, the random and the fixed effect model were performed when the heterogeneity was significant or not, respectively66. We used the R package ‘meta’ to perform the meta-analysis, and determine the significance level of association between rs11136000 and AD through the pooled OR value and its 95% CI, as well as the corresponding P value (http://cran.r-project.org/web/packages/meta/index.html). And then, the original samples were further split into Caucasian, Asian, East Asian and Chinese populations, and the meta-analysis was performed in these subgroups.

Publication bias analysis and sensitivity analysis

We first evaluated the publication bias of the studies used in dominant, allele and recessive model, respectively, by the two common checking methods, the Begg’s test67 and Egger’s test68. The threshold of significant publication bias was set as P < 0.05. Then, we used the asymmetry of the funnel plots to describ the results of the publication bias analysis. Finally, for sensitivity analyses, we excluded each study in turn from the whole sample to measure the influence of each study.

Data availability

All the datasets used in this are available from the corresponding author.

Results

Study acquisition and data extraction

By a keyword search in the publicly available databases and a screening according to the criteria, a total 46 studies from 36 articles were identified which mainly involved in Caucasian and Asian populations. Moreover, a study about Sweden population was selected from AlzGene database, and three studies involved in Asian populations were identified by the citation check using Google Scholar.

Figure 1 showed the workflow of selection. Then, the related data of these 50 studies were extracted, and the main information was described in Table 1 (the detailed genotype data, the OR value and its 95% CI, as well as the corresponding P value were shown in Supplementary Table S1).

Figure 1
figure 1

Flow chart of selecting studies for analyzing the association between rs11136000 polymorphism and AD.

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Hardy–Weinberg equilibrium test

We calculated the P value of HWE to assess the genotype distribution of rs11136000 polymorphism in AD patients and controls separately. Using a significance level of P < 0.01, we observed that a few of the samples deviated from HWE, including the case samples from the study of Yu et al. (P = 9.0 × 10−3) and Gu et al. (P = 2.0 × 10−4), and the control samples from the study of Rezazadeh et al. (P = 1.0 × 10−4), Gu et al. (P = 1.0 × 10−4) and Lin et al. (P = 9.0 × 10−3). More detailed information about the results of the HWE test was described in Supplementary Table S2.

Heterogeneity Test and Meta-analysis

After the test, we found that there is no the significant genetic heterogeneity of rs11136000 polymorphism among all of the 50 selected studies using the dominant (I2 = 0% and P = 0.60), allele (I2 = 10% and P = 0.28) and recessive model (I2 = 33% and P = 0.04). Therefore, the meta-analysis with fixed effect model was performed to assess the association between rs11136000 and the risk of AD, and we found significant results in all the three models. In particular, the significant association between the minor allele (T) of rs11136000 and a decreased risk of AD was identified in the allele (OR = 0.875, 95% CI = 0.854–0.896, P < 0.0001) (Fig. 2), dominant (OR = 0.848, 95% CI = 0.817–0.879, P < 0.0001) and recessive model (OR = 0.822, 95% CI = 0.779–0.868, P < 0.0001) (Supplementary Figs S1 and S2).

Figure 2
figure 2

Forest plot for the meta-analysis of rs11136000 polymorphism using allele model. All the 50 selected studies are used to meta-analysis of the allele contrast (T versus C) by the fixed effect model (Mantel-Haenszel) because the genetic heterogeneity is not significant. The minor allele (T) of rs11136000 was significantly associated with a decreased risk of AD.

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Subgroup Analysis

We further performed the meta-analysis in the subgroups to assess the association between rs11136000 and the risk of AD in different ethnicities. Among all the 50 selected studies, the great majority of them involved in Caucasian or Asian ethnicity, except two studies about African and American population, respectively, and four mixed population studies (Table 1). Therefore, we first divided these studies into Caucasian or Asian ethnicity subgroups. We found a significant association between the minor allele (T) of rs11136000 and a decreased risk of AD in Caucasian ethnicity using the allele (OR = 0.864, 95% CI = 0.842–0.888, P < 0.0001), dominant (OR = 0.829, 95% CI = 0.796–0.864, P < 0.0001) and recessive model (OR = 0.819, 95% CI = 0.774–0.867, P < 0.0001) (Supplementary Figs S3–S5). For the Asian ethnicity, however, only a weak association was observed in allele model (OR = 0.921, 95% CI = 0.871–0.973, P = 0.0034) (Fig. 3a), but not the dominant (OR = 0.922, 95% CI = 0.846–1.005, P = 0.0649) (Fig. 3b) and recessive model (OR = 0.747, 95% CI = 0.511–1.092, P = 0.1326) (Fig. 3c).

Figure 3
figure 3

Forest plot for the meta-analysis of rs11136000 polymorphism in Asian population. Only a weak association between rs11136000 polymorphism and AD is observed in the allele model (a), but not the dominant (b) and recessive model (c).

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The Asian population in this study was composed of the Indian, Iranian, Korean and Japanese individuals separately from a GWAS study, and the Chinese individuals from 12 GWAS studies. Therefore, we then assessed the association between this SNP and risk of AD in East Asian and Chinese populations. Interestingly, the results of meta-analysis in East Asian population were similar to these in Asian population (Supplementary Figs S6–S8). However, the association was not significant in Chinese population using the allele (OR = 0.939, 95% CI = 0.878–1.004, P = 0.0654) (Fig. 4a), dominant (OR = 0.988, 95% CI = 0.887–1.101, P = 0.8270) (Fig. 4b) and recessive model (OR = 0.615, 95% CI = 0.355–1.068, P = 0.0841) (Fig. 4c), which was different from the findings in the previous studies29,30.

Figure 4
figure 4

Forest plot for the meta-analysis of rs11136000 polymorphism in Chinese population. The association between rs11136000 polymorphism and AD was not significant in the allele (a), dominant (b) and recessive model (c).

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Moreover, given that a few samples from four GWAS studies (three Asian populations and a mixed population) deviated from HWE, we further tested whether they affected the accuracy of the results by removing these studies from whole sample, Asian, East Asian and Chinese subgroups, respectively. The results were consistent with what we had been observed previously in whole sample and the subgroups using allele, dominant and recessive model. Table 2 showed the detailed information of the results.

Table 2 The results of meta-analysis after removing the studies deviated from HWE.
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Publication bias analysis and sensitivity analysis

As the funnel plots show (Fig. 5), we did not identify the significant publication bias in the three genetic models. In particular, the P value of Begg’s and Egger’s test is 0.80 and 0.24, respectively, for dominant model. Similarly, the P value is 0.43 (Begg’s test) and 0.21 (Egger’s test) for the allele model, and 0.22 (Begg’s test) and 0.61 (Egger’s test) for the recessive model. Moreover, through the sensitivity analysis, for all the three genetic models, we did not found a significant change of the association level between rs11136000 and AD when excluding any of the studies. Supplementary Tables S3–S5 described the related information in detailed.

Figure 5
figure 5

Funnel plot for publication bias analysis of rs11136000 polymorphism in AD using allele, dominant and recessive models.

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Discussion

AD was characterized by accumulation and toxic effect of the Aβ deposits in brain3, and previous studies reported that the CLU could markedly influence the fibrillary Aβ formation and accumulation to mediate its toxicity in vivo, and likely as one of the most important roles for pathogenesis of AD6,7. Then, the subsequent GWAS studies found some variants in CLU were differently distributed between AD patients and controls11,12,13,14,15,16,17,18. Among these variants, a significant association was found between the minor allele (T) of rs11136000 and a decreased risk of AD by Harold et al.11, Lambert et al.12, Carrasquillo et al.13 and Seshadri et al.14. However, these results could not be repeated in other populations by the following studies19,20,21,22,23,24,25,26,27,28.

Although the two independent meta-analyses found a significant association between the minor allele (T) of rs11136000 and a decreased risk of AD in Caucasian and Asian ethnicities by integrating the data from related GWAS studies published before June 20, 2013 (18 studies) and August 31, 2014 (25 studies), respectively29,30, many of the following studies also reported the inconsistent results31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47. Moreover, according to our further investigation, the two meta-analyses missed out a total six related GWAS studies published before August 31, 201448,49,50,51,52, and a GWAS study about American and German populations is misclassified to the Asian ethnicity subgroup in Du et al.’s meta-analysis22. Therefore, we suspected that the small-scale and incompletion or heterogeneity of the samples maybe lead to different results of these studies.

In this study, 50 related GWAS studies (including the 6 missing and 18 novel studies) were selected afresh from seven authoritative sources, and the association level between rs11136000 and risk of AD in Caucasian, Asian and Chinese ethnicity was re-evaluated. We also found a significant association between rs11136000 polymorphism and the decreased risk of AD in Caucasian ethnicity using the dominant (OR = 0.829, 95% CI = 0.796–0.864, P < 0.0001), allele (OR = 0.864, 95% CI = 0.842−0.888, P < 0.0001) and recessive model (OR = 0.819, 95% CI = 0.774−0.867, P < 0.0001). Different from the results of the previous studies, however, rs11136000 polymorphism was found not associated with the risk of AD in Asian ethnicity using the dominant (OR = 0.922, 95% CI = 0.846–1.005, P = 0.0649) and recessive model (OR = 0.747, 95% CI = 0.511−1.092, P = 0.1326), as well as in Chinese population using the dominant (OR = 0.988, 95% CI = 0.887−1.101, P = 0.8270), allele (OR = 0.939, 95% CI = 0.878–1.004, P = 0.0654) and recessive model (OR = 0.615, 95% CI = 0.355−1.068, P = 0.0841).

As far as we know, our meta-analysis about the association of the CLU rs11136000 polymorphism with the risk of AD is by far the largest scale study. The results reveal a significant association between them in Caucasian ethnicity but not Chinese ethnicity, which is consistent with the findings of most of the corresponding GWAS studies. In summary, we believe that these findings can help to improve the understanding of the AD’s pathogenesis.