Skip to content

Advertisement

You're viewing the new version of our site. Please leave us feedback.

Learn more

BMC Musculoskeletal Disorders

Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Associations of LBX1 gene and adolescent idiopathic scoliosis susceptibility: a meta-analysis based on 34,626 subjects

BMC Musculoskeletal DisordersBMC series – open, inclusive and trusted201617:309

https://doi.org/10.1186/s12891-016-1139-z

Received: 3 January 2016

Accepted: 29 June 2016

Published: 22 July 2016

Abstract

Background

The results of studies investigating the association between the ladybird homeobox 1 (LBX1) gene polymorphisms and the risk of adolescent idiopathic scoliosis (AIS) are not all the same. As such, we performed a meta-analysis to estimate the association between LBX1 gene polymorphisms and AIS susceptibility.

Methods

Relevant studies published before 15 November 2015 were identified by searching PubMed, EMBASE, ISI web of knowledge, EBSCO, CNKI and CBM. The strength of relationship was assessed by using odds ratios (ORs) and 95 % confidence interval (CI).

Results

A total number of eight case-control studies including 10,088 cases and 24,538 controls were identified. The results showed that T allele of rs111090870 increased AIS susceptibility in Asians (T vs. C, OR = 1.22, 95 % CI: 1.16–1.29, P < 0.001), Caucasians (T vs. C, OR = 1.17, 95 % CI: 1.14–1.21, P < 0.001) and in female (T vs. C, OR = 1.21, 95 % CI: 1.17–1.25, P < 0.001). The G allele of rs678741 decreased AIS risk in female (G vs. A, OR = 0.83, 95 % CI: 0.81–0.85, P < 0.001), and the G allele of the rs625039 increased AIS susceptibility in Asians (G vs. A, OR = 1.14, 95 % CI: 1.11–1.17, P < 0.001).

Conclusions

Our meta-analysis provides evidence that rs111090870, rs678741 and rs625039 polymorphisms near LBX1 gene are associated with AIS susceptibility in some populations. However, our findings are based on only a limited number of studies.

Keywords

LBX1 geneAdolescent idiopathic scoliosisGene polymorphismMeta-analysis

Background

Adolescent idiopathic scoliosis (AIS) is a medical condition which affects 1–4 % of children in the at-risk population of those aged 10–16 years, using a cut-off point of 10° Cobb angle or more [1, 2]. An X-ray of an AIS patient is showing in Additional file 1: Figure S1. Without a known cause, AIS has been simply defined as a structural lateral curvature. However, the deformity is three-dimensional, which entails the coronal, sagittal and transverse planes of the spine [3, 4]. AIS leads to significant functional disabilities, especially pulmonary impairment [5, 6]. It also causes pain and cosmetic problems [7, 8]. The cause of AIS is complex and possible ethiology pathogeneses include genetic factors, hormones and metabolic dysfunction, abnormal growth, and environmental and life style factors [912]. Of all these factors, genetic factors are widely-accepted and well-documented [1315]. Many genes involving in the initiation and evolution of AIS have been identified as its susceptible genes, such as Melatonin Receptor 1B (MTNR1B), ladybird homeobox 1 (LBX1), tryptophan hydroxylase 1 (TPH1), arylalkylamine N-acetyltransferase (AA-NAT) and Basonuclin 2 (BNC2) [1, 1618], and among them, the LBX1 gene is widely investigated.

The LBX1 gene locates on chromosome 10q24.31, and it is a hemeobox transcription factor [19, 20]. It takes part in spinal cord differentiation and patterning, and somatosensory signal transduction. Therefore, LBX1 is a strong biological candidate gene for AIS [21, 22]. LBX1 encodes ladybird homeobox 1, orthologous to Drosophila ladybird-late, which plays a key role in regulation of muscle precursor cell migration and highly functional in central nervous system [19]. Large-scale genome-wide (GWAS) association studies conducted in Japanese and Chinese have tried to identify single nucleotide polymorphisms (SNPs) in relation to AIS risk [19, 23]. In 2015, several new studies which concerned on LBX1 SNPs polymorphisms and AIS susceptibility have been published in Caucasian subjects [24, 25]. The results of these studies showed that several allelic polymorphisms near LBX1 gene may act as potential susceptible factors for AIS, such as rs111090870, rs11598564 and rs625039. However, the results are not all the same and with limited statistical power among these studies. In order to overcome the limitation of single studies, we performed this meta-analysis containing one widely studied locus (rs111090870) and three less studied loci (rs678741, rs11598564 and rs625039), to provide a more comprehensive and precise estimation of LBX1 gene and AIS susceptibility.

Methods

Data sources

Six databases were electronically searched, including PubMed, EMBASE, ISI web of knowledge, EBSCO, China National Knowledge Infrastructure (CNKI), and Chinese Biological and Medical Database (CBM), to retrieve studies analyzing the association between AIS susceptibility and LBX1 gene polymorphisms until 1 November 2015. Searching terms were: “adolescent idiopathic scoliosis” or “AIS”, in combination with “LBX1” or “ladybird homeobox 1” or “HPX6” or “homeobox”, and in combination with: “polymorphism” or “variant” or “genotype” or “allele”. We also checked the reference lists of all included studies to make sure no study was missed.

Inclusion criteria

We first performed initial screening of titles and abstract. A second round screening was based on full-text reviews. Studies were considered eligible if they met the following criteria: (1) It was a case-control study in design; (2) It evaluated the LBX1 gene polymorphisms and AIS susceptibility; (3) AIS was diagnosed on the basis of clinical and radiologic examinations; (4) Individual genotype frequencies or allele frequencies in cases and controls were available.

Exclusion criteria

Researches were excluded if they met any one of the following criteria: (1) Data came from reviews or abstracts; (2) Genotype and allele frequencies were both unavailable; (3) Repeatedly published literature.

Data extraction and quality assessment

Two reviewers independently searched and selected literature, and then, extracted relevant data according to a data extraction form. Disagreements were solved by discussion until consensus was made. The extracted data included: the first author, year of publication, country of origin, ethnicity of the study population, genotyping method, source of control, sample size, the genotype and allele frequencies of the LBX1 gene polymorphisms, and information of Hardy-Weinberg equilibrium (HWE) in control group.

Quality assessment was conducted for each article according to a quality evaluation form base on Critical Appraisal Skills Programme (CASP) for case-control study, which containing eleven questions associated with information provided in single studies [26]. Each question has three degrees, “yes” (scored 2), “can’t tell” (scored 1), or “no” (scored 0). After evaluating each question, a total score from 0 to 22 was given to each article. Studies included in this meta-analysis were divided into 3 grades: Grade A (high quality, scored 15–22), Grade B (medium quality, scored 8–14), Grade C (inferior quality, scored 0–7).

Statistical analysis

Data analysis was conducted using STATA 11.0 software (Stata Statistical software, College Station, TX, USA, www.stata.com). Odds ratio (OR) and its corresponding 95 % confidence intervals (95 % CI) were used to evaluate the strength of association between LBX1 gene polymorphisms and AIS susceptibility. Heterogeneity among included studies was tested using chi-square-based Q test and I2 test. P het  < 0.05 and I 2  > 50 % were considered as statistically significant for heterogeneity. The Mantel-Haenszel method was used for fix effect model if no heterogeneity was found. Otherwise, the DerSimonian-Laird random effect model was used. Fix effect model considers that across all studies, the genetic factors have similar effects on genetic disorder susceptibility and the observed differences among studies are cause just by chance [27]. Random effect model considers that different studies may have substantial diversity, and it calculates within- as well as between- study difference [28]. Five comparison genetic models were used to assess the association between LBX1 gene polymorphisms and AIS susceptibility. For instance, for rs1190870 polymorphism, T allele, we assessed the dominant model (TT + CT vs. CC), the recessive model (TT vs. TC + CC), the allele contrast genetic model (T vs. C), the heterozygote comparison (CT vs. CC), and the homozygote comparison (TT vs. CC). HWE was tested for included studies if no relevant information was provided in original research. Sensitivity analyses were conducted by omitting individual studies sequentially. Moreover, we performed subgroup analysis stratified by ethnicity and gender. Publication bias was quantitatively assessed by Egger’s linear regression test [29] and visual inspection of Begg’s funnel plots.

Results

Literature search

We initially identified 86 potentially relevant studies from six databases searched. Firstly, we eliminate duplications, not case-control studies or irrelevant to LBX1 polymorphisms. After this procedure, ten studies were retained. Then, we read the full tests of these articles, and we finally identified 8 case control studies eligible for meta-analysis [1, 19, 23, 24, 3033], including 10,088 cases and 24,538 controls. One study [34] was excluded for it reported the same datasets as Takahashi et al., but was less detailed. Another study was excluded for genotype and allele frequencies were both unavailable in original research [35]. A flow chart of article selection process is described in Additional file 1: Figure S2.

Studies characteristics

Table 1 presents the main characteristics of included studies and genotype frequencies of included studies can be found in Additional file 1: Table S1. Of the eight studies, seven [1, 19, 23, 24, 30, 31, 33] were published in English and one [32] was a Chinese doctoral dissertation. There were six studies carried out among Asians [19, 23, 3033], and two among Caucasians [1, 24]. All studies included were case-control studies in design, and all patients with AIS fulfilled the diagnosis of scoliosis. The number ranged from 94 to 4317 for cases, and 182 to 9823 for controls. Controls were mainly normal healthy populations randomly recruited from general population, who were matched with cases in ethnicity, gender and age. Seven studies containing a total of 13 datasets tested the rs111090870 polymorphism and AIS susceptibility, including seven datasets for female, five for male and one mix gender dataset. Two studies analyzed rs678741, including five datasets for female. Two studies tested rs11598564, and they contained three datasets for female and two for male. Three studies tested rs625039 polymorphism, including three datasets for female, two for male and one mix gender dataset. In quality assessment, all studies included were categorized as grade A, with scores from 15 to 20 (Table 1). Only in one dataset, the genotype distributions in control groups were deviated from HWE.
Table 1

Characteristics of the datasets included in meta-analysis on association between LBX1 polymorphisms and AIS

First author

Year

Country

Ethnicity

Case number (all cases, male/female)

Control number (all controls, male/female)

Cobb angles degrees of the included patients

Genotyping method

Quality grade

SNP tested and included in meta-analysis

Chettier et al.

2015

USA

Caucasian

620 female cases

1287 female controls

More than 10 degrees

Affymetrix HuSNP 6.0 Microarray

A (scored 15)

rs111090870, rs678741

Fan et al.

2012

China

Asian

300, 52/248

788, 299/489

More than 35 degrees

PCR-based invader assay

A (scored 18)

rs111090870

Gao et al.

2013

China

Asian

513, 66/447

440, 151/289

25.57 ± 14.10 degrees

PCR-MassArray assay

A (scored 16)

rs111090870, rs11598564, rs625039

Grauers et al.

2015

Sweden and Denmark

Caucasian

1739, 241/1498

1812, 0/1812

38.8 ± 17.5 degrees

MassArray assay

A (scored 15)

rs111090870

Jiang et al.

2013

China

Asian

949, 129/820

976, 314/662

More than 20 degrees

PCR-based invader assay

A (scored 15)

rs111090870

Liu

2015

China

Asian

180, 29/151

182, 30/152

NA

PCR-MassArray assay

A (scored 17)

rs111090870, rs625039

Takahashi et al.

2012

Japan

Asian

1453, 94/1359

13127, 1849/11278

More than15 degrees

I PCR-based invader assay, llumina Human610 and HumanHap550v3 microarrays

A (scored 20)

rs111090870, rs11598564, rs625039

Zhu et al.

2015

China

Asian

4317 female cases

6016 female controls

37.2 ± 9.4 degrees

Affymetrix Genome-wide Human SNP array 6.0

A (scored 15)

rs678741

AIS adolescent idiopathic scoliosis; GWAS genome-wide association; USA United States of America; PCR polymorphism chain reaction; SNP single nucleotide polymorphism, NA not applicable

Quantitative data analysis

rs111090870 polymorphism and AIS susceptibility

Seven case-control studies [1, 19, 23, 24, 3032] containing 13 datasets on relationship between rs111090870 polymorphism and AIS susceptibility were identified, including 5754 cases and 18,628 controls. The results of five genetic models testing rs111090870 polymorphism and AIS susceptibility were showed in Table 2. A significant increase in AIS susceptibility was found in all of five genetic models. In the subgroup analysis stratified by gender, significant increasing AIS susceptibility was found for female in the dominant model (TT + TC vs. CC: OR = 1.13, 95 % CI: 1.09–1.16, P < 0.001) and allele contrast genetic model (T vs. C: OR = 1.21, 95 % CI: 1.17–1.25, P < 0.001). In mix gender subgroup, allele contrast genetic model also showed a significant increase (T vs. C: OR = 1.26, 95 % CI: 1.09–1.45, P = 0.001), but no significant association between rs111090870 and AIS risk was found in male subgroup. In subgroup analyses stratified by ethnicity, significant increasing AIS susceptibility was found for Asians and Caucasians in both genetic models (Table 3). Figure 1 shows the forest plot of allele contrast genetic model testing the association between rs11109070 polymorphism and AIS risk.
Table 2

Summary of different genetic model comparison results

SNP

Genetic model

OR (95 % CI)

Z

P value

I 2 %

P het

Effect model

Egger’s test

t value

P value

rs111090870

TT + TC vs. CC

1.12 (1.09–1.15)

7.66

0.000

68.8

<0.001

R

0.42

0.684

TT vs. TC + CC

1.42 (1.36–1.49)

15.49

0.000

42.6

0.058

F

0.92

0.378

TT vs. CC

1.36 (1.27–1.45)

9.07

0.000

73.2

<0.001

R

0.98

0.349

TC vs. CC

1.13 (1.09–1.18)

5.92

0.000

56.3

0.009

R

−0.07

0.949

T vs. C

1.21 (1.16–1.26)

9.52

0.000

68.7

<0.001

R

0.55

0.597

rs678741

GG + GA vs. AA

0.79 (0.77–9.82)

16.79

0.000

0.0

0.998

F

0.85

0.458

GG vs. GA + AA

0.69 (0.64–0.74)

10.98

0.000

0.0

0.880

F

−0.82

0.470

GG vs. AA

0.68 (0.65–0.72)

13.22

0.000

0.0

0.517

F

−1.09

0.356

GA vs. AA

0.88 (0.85–0.91)

8.12

0.000

0.0

0.904

F

−0.73

0.519

G vs. A

0.83 (0.81–0.85)

13.75

0.000

0.0

0.743

F

−0.69

0.542

rs11598564

GG + GA vs. AA

1.13 (1.10–1.16)

7.98

0.000

0.0

0.649

F

0.32

0.769

GG vs. GA + AA

1.09 (0.84–1.43)

0.64

0.519

88.8

<0.001

R

0.29

0.726

GG vs. AA

1.12 (1.33–1.52)

10.12

0.000

0.0

0.761

F

−0.71

0.526

GA vs. AA

1.13 (1.08–1.18)

5.34

0.000

0.0

0.739

F

1.02

0.384

G vs. A

1.21 (1.16–1.25)

10.03

0.000

22.2

0.273

F

0.66

0.557

rs625039

GG + GA vs. AA

1.07 (1.05–1.09)

7.45

0.000

0.0

0.648

F

0.20

0.850

GG vs. GA + AA

1.30 (1.23–1.37)

9.05

0.000

0.0

0.509

F

1.18

0.303

GG vs. AA

1.17 (1.13–1.21)

9.48

0.000

0.0

0.651

F

0.66

0.545

GA vs. AA

1.09 (1.05–1.12)

4.66

0.000

0.0

0.573

F

−0.35

0.747

G vs. A

1.14 (1.11–1.17)

10.14

0.000

0.0

0.584

F

1.10

0.333

SNP single nucleotide polymorphism; OR odds ratio; CI confidence interval; F fix-effect model; R random-effect model; P het P value for heterogeneity

P < 0.05 stands for statistical significance

Table 3

Results of subgroup analyses

SNP

Comparison

Number of datasets

Dominant genetic model

Allele contrast

OR (95 % CI)

P value

OR (95 % CI)

P value

rs111090870

Gender

 
 

Female

7

1.13 (1.09–1.16)

<0.001

1.21 (1.17–1.25)

0.000

 

Male

5

1.08 (0.93–1.25)

0.319

1.15 (0.95–1.40)

0.015

 

Mix gender

1

1.10 (0.99–1.23)

0.087

1.26 (1.09–1.45)

0.001

 

Ethnicity

 
 

Asian

10

1.13 (1.09–1.17)

<0.001

1.22 (1.16–1.29)

0.000

 

Caucasian

3

1.09 (1.08–1.22)

<0.001

1.17 (1.14–1.21)

0.000

rs678741

Ethnicity

 
 

Asian

4

0.79 (0.77–0.82)

<0.001

0.83 (0.81–0.86)

0.000

 

Caucasian

1

0.80 (0.74–0.86)

<0.001

0.79 (0.73–0.86)

0.000

rs11598564

Gender

 
 

Female

3

1.14 (1.09–1.16)

<0.001

1.20 (1.15–1.25)

0.000

 

Male

2

1.16 (1.08–1.23)

<0.001

1.27 (1.17–1.39)

0.000

rs625039

Gender

 
 

Female

3

1.07 (1.05–1.09)

<0.001

1.13 (1.10–1.17)

0.000

 

Male

2

1.07 (1.02–1.13)

0.010

1.20 (1.12–1.29)

0.000

 

Mix gender

1

1.05 (0.96–1.14)

0.256

1.14 (1.02–1.28)

0.025

Fig. 1

Meta-analysis forest plot of the association between rs11109070 polymorphism and AIS risk (allele contrast genetic model, T vs. C)

rs678741 polymorphism and AIS susceptibility

Two case-control studies [1, 33] containing five datasets on relationship between rs678741 polymorphism and AIS susceptibility were identified, including 4937 cases and 7303 controls, and the five datasets all contained female participants. The results of five genetic models testing rs678741 polymorphism and AIS susceptibility were showed in Table 2. A significant decrease in AIS susceptibility was found in all of five genetic models. In the subgroup analysis stratified by ethnicity, significant decreasing AIS susceptibility was found for both ethnicities in dominant and allele contrast genetic models (Table 3). Figure 2 shows the forest plot of allele contrast genetic model testing the association between rs678741 polymorphism and AIS risk.
Fig. 2

Meta-analysis forest plot of the association between rs678741 polymorphism and AIS risk (allele contrast genetic model, G vs. A)

rs11598564 polymorphism and AIS susceptibility

Two case-control studies [19, 30] containing five datasets on relationship between rs11598564 polymorphism and AIS susceptibility were identified, including 1966 cases and 13,585 controls and the five databases all contained Asian participants. The results of five genetic models testing rs11598564 polymorphism and AIS susceptibility were showed in Table 2. A significant increase in AIS susceptibility was found in all of five models except for recessive genetic model (GG vs. GA + AA, OR = 1.09, 95 % CI: 0.84–1.43, P = 0.519). In the subgroup analysis stratified by gender, significant increasing AIS susceptibility was found for both genders in the dominant model and allele contrast genetic model (Table 3). Figure 3 shows the forest plot of allele contrast genetic model testing the association between rs11598564 polymorphism and AIS risk.
Fig. 3

Meta-analysis forest plot of the association between rs11598546 polymorphism and AIS risk (allele contrast genetic model, G vs. A)

rs625039 polymorphism and AIS susceptibility

Three case-control studies [19, 30, 32] containing six datasets on relationship between rs678741 polymorphism and AIS susceptibility were identified, including 1, 646 cases and 13,749 controls, and the six datasets all contained Asians participants. The results of five genetic models testing rs625039 polymorphism and AIS susceptibility were showed in Table 2. A significant increase in AIS susceptibility was found in all of five genetic models. In the subgroup analysis stratified by gender, significant increasing AIS susceptibility was found for both genders allele contrast genetic models (Table 3). Figure 4 shows the forest plot of allele contrast genetic model testing the association between rs625039 polymorphism and AIS risk.
Fig. 4

Meta-analysis forest plot of the association between rs625039 polymorphism and AIS risk (allele contrast genetic model, G vs. A)

Sensitivity analysis and publication bias

Sensitivity analyses were conducted by omitting each dataset sequentially. For four SNP polymorphisms, the result did not change under any genetic model. For rs11090870, when we omitted the male dataset reported by Jiang et al. [31], the indicators for heterogeneity was reduced under dominant, heterozygote, homozygote and allele contrast genetic models. For rs11598564, when we reduce the female dataset reported by Gao et al. [30], the indicators for heterogeneity was reduced under recessive genetic model. Sensitivity analysis suggested that the results for LBX1 gene polymorphisms and AIS susceptibility were stable and statistically robust.

Visual inspection of Begg’s funnel plots did not identify substantial asymmetry for all SNPs under any genetic model (Additional file 1: Figure S3-S6). The Egger’s linear regression test also indicated no evidence of publication bias in studies testing LBX1 gene polymorphisms and AIS susceptibility (P > 0.05 for all models tested) (Table 2).

Discussion

Previous clinical and epidemiological studies found that about 27 % female offspring of female AIS patients would also suffer from AIS, but this phenomenon did not exist in male AIS patients, and that the pairwise concordance rate was higher in monozygotic twin pairs comparing with dizygotic twin pairs [36, 37]. So, the genetic factors play essential roles in pathogenesis of AIS. Preclinical medicine researches shows that, in LBX1 mutant mice, the morphology and neuronal circuitry of the dorsal horn are aberrant and in mice lacking LBX1, cells types that arise in the ventral alar plate acquire more dorsal identities [22, 38]. Therefore, LBX1 is essential for sensory pathways developments which relay touch and pain. In 1982, Pincott et al. found that the loss of proprioceptive innervation could result in asymmetrical weakness of the paraspinal muscles, and which may finally cause scoliosis [39]. As a result, it is quite reasonable to deduce that LBX1 gene may be a target spot in pathogenesis of AIS.

Case-control study is a useful tool to detect gene and disease susceptibility. GWAS is a kind of case-control cohort study in essential, which is a powerful method to identify genetic association with diseases and has been applied in genetic predisposition studies increasingly. Therefore, GWAS is widely used in AIS susceptibility study, to identity risk genes for this most common and complex musculoskeletal system polygenic disease [35, 40, 41]. Fan et al. and Takahashi et al. [19, 23] first reported results of a GWAS analyzing the association between LBX1 gene and AIS susceptibility in 2012 and their results showed statistical significant associations for rs111090870, rs11598564 and rs625039. From 2013 to 2015, several subsequent studies have conducted to investigate the LBX1 polymorphisms in pathogenesis of AIS. However, the results are inconsistent, with some datasets found positive associations, and other find no relevance or even negative association. Several reasons, including different recruitment criteria, subjects’ characteristics, sample size, different ethnic population and gender, may lead to the inconsistency.

In order to avoid limitations of individual case-control or GWA study, we conducted this meta-analysis to pool the findings of rs111090870, rs678741 rs11598564 and rs625039 polymorphisms in all original studies. As we reported in result part, the eight included studies were of high quality judged by CASP standard. They clearly reported their participants choosing criteria, sample sizes, characteristics of cases and controls and genotyping methods. Moreover, except one dataset cannot be tested for HWE, only one dataset was deviated from HWE in the control group. Gender and ethnicity were matched in case and control group. The results showed that T allele of rs111090870 is significant associated with increased AIS susceptibility in Asians (T vs. C, OR = 1.22, 95 % CI: 1.16–1.29, P < 0.001), Caucasians (T vs. C, OR = 1.17, 95 % CI: 1.14–1.21, P < 0.001) and in female (T vs. C, OR = 1.21, 95 % CI: 1.17–1.25, P < 0.001). The G allele of rs678741 decreased AIS risk in female (G vs. A, OR = 0.83, 95 % CI: 0.81–0.85, P < 0.001), and the G allele of the rs625039 polymorphism may increase AIS susceptibility in Asians (G vs. A, OR = 1.14, 95 % CI: 1.11–1.17, P < 0.001). For the rs11598564 polymorphism, G allele may also increase AIS risk, but in recessive model, no statistical significant association was detected and the result was with heterogeneity. So, the result of rs11598564 should be interpreted with caution.

We should notice the heterogeneity existed in this meta-analysis. For the rs111598564 and rs625039 polymorphisms, no heterogeneity was found among studies. However, in the rs111090870 polymorphism, significant heterogeneity was found in all models except the recessive model, and for the rs11598564 polymorphism, heterogeneity was detected in recessive genetic models. For rs111090870 polymorphism, the heterogeneity detected in four genetic models was effectively decreased in sensitivity analysis when the male dataset in study by Jiang et al. [31] was omitted. In this study, the genotype distribution in control group was deviated from HWE. For rs11598564 polymorphism, when we stratified by gender, the heterogeneity existed in female group only, and when omitted individual dataset sequentially, we find female group in study by Gao et al. [30] contributed to the heterogeneity. Moreover, the removal of these datasets did not materially change the overall results of any genetic models. Therefore, deviation from HWE and different genders may contribute to overall heterogeneity of this meta-analysis.

Two previous meta-analyses [42, 43] have tried to analyze the association between rs111090870 polymorphism and AIS susceptibility in East Asians. For these two studies, all of the genetic models provided statistically significant comparison results. For instance, the ORs and their corresponding 95 % CI of the dominant models were 2.04 (2.27–3.03) and 2.02 (1.78–2.30) respectively. The results of our study were quite similar to theses to studies, but the effect sizes were lower than theirs, as the effect size of the dominant model in our study were 1.13 (1.09–1.17) for Asians and 1.12 (1.09–1.15) for overall population. Comparing with them, our meta-analysis has some important improvements. For rs111090870 polymorphism, some new published researches were included in our meta-analysis polymorphism, and through strict methodological process, we provided a more comprehensive view of included studies. The above mentioned meta-analysis only focus on east Asian participants, but our study also included Caucasian subjects and in subgroup studies, we stratified by ethnicity to test if there existed differences in variant ethnicities. For rs678741, rs11598564 and rs625039 polymorphisms, to the best of our knowledge, no published combined study has detected their association with AIS.

Several limitations of this study may affect the results. Firstly, only published English and Chinese studies were included in this meta-analysis and we only included published studies from six databases. Relevant studies in other languages and databases may have been missed. Secondly, in our meta-analysis, all datasets included in rs11598564 and rs625039 were based on Asian subjects. Additional researches in other ethnicities are needed to generalize our finding for rs11598564 and rs625039. For rs678741, all included datasets were based on female subjects, and other researches for males are needed. Because the same polymorphism may act differently in different ethnical backgrounds genders, results from rs678741 cannot extend to male and results from rs11598564, rs625039 cannot extend to Caucasians or other ethnicities. Thirdly, most included studies did not distinguish between the magnitude or phenotype of scoliosis and genotyping results. Therefore, we were unable to provide different pooled ORs according to different magnitude or phenotype of AIS. Finally, the possible ethiology pathogenesis of AIS is complex, but due to insufficiency of included studies, we did not detect the interactions between genetic factors and other factors. Considering that meta analysis is a kind of retrospective research and may easily be affected by methodological deficiencies of included studies, we developed a detailed protocol before conducting this analysis, to ensure the quality of our meta-analysis.

Conclusion

From the combination results of currently included studies, our meta-analysis suggested that the T allele of rs111090870 polymorphism near LBX1 gene is significant associated with increased AIS susceptibility in Asians, Caucasians and in female. The G allele of rs678741 may decrease AIS risk in female and the G allele of rs625039 polymorphism may increase AIS susceptibility in Asians. More studies with multiple ethnics and different genders are needed to generalize the results.

Abbreviations

AA-NAT, arylalkylamine N-acetyltransferase; AIS, adolescent idiopathic scoliosis; BNC2, Basonuclin 2; CASP, Critical Appraisal Skills Programme; CBM, Chinese Biological and Medical Database; CI, confidence interval; CNKI, China National Knowledge Infrastructure; GWAS, Large-scale genome-wide; HWE, Hardy-Weinberg equilibrium; LBX1, ladybird homeobox 1; OR, odds ratios; PCR, Polymorphism chain reaction; SNP, single nucleotide polymorphism; TPH1, tryptophan hydroxylase 1

Declarations

Acknowledgments

We would like to acknowledge all authors of the original studies included in this meta-analysis.

Funding

This work was not supported by any fund.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article and in the Additional file 1.

Authors’ contributions

YC was the first author who conceived the study, took part in protocol making, articles searching, data extraction, data analyzing, and wrote the first draft of the manuscript. JM was the second author and corresponding author, who contributed to the article selection, data extraction, final interpretation, and commented on successive versions of the manuscript. QZ took part in protocol revising, article selection and helped in manuscript writing. HL and HL together produced the figures and tables in article, arbitrated studies for inclusion and commented on successive drafts of the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests. The authors alone are responsible for the content and the writing of the paper.

Consent for publication

Written informed consent was obtained from the parents of patient for publication of the accompanying image in Additional file 1.

Ethics approval and consent to participate

Not applicable as this is a meta-analysis of previously published papers.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Orthopaedics, the First People’s Hospital of Huzhou

References

  1. Chettier R, Nelson L, Ogilvie JW, Albertsen HM, Ward K. Haplotypes at LBX1 have distinct inheritance patterns with opposite effects in adolescent idiopathic scoliosis. PLoS One. 2015;10(2):e0117708.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Weinstein SL, Dolan LA, Cheng JC, Danielsson A, Morcuende JA. Adolescent idiopathic scoliosis. Lancet. 2008;371(9623):1527–37.View ArticlePubMedGoogle Scholar
  3. Stokes IA. Three-dimensional terminology of spinal deformity. A report presented to the Scoliosis Research Society by the Scoliosis Research Society Working Group on 3-D terminology of spinal deformity. Spine. 1994;19(2):236–48.View ArticlePubMedGoogle Scholar
  4. Perdriolle R, Le Borgne P, Dansereau J, de Guise J, Labelle H. Idiopathic scoliosis in three dimensions: a succession of two-dimensional deformities? Spine. 2001;26(24):2719–26.View ArticlePubMedGoogle Scholar
  5. Dreimann M, Hoffmann M, Kossow K, Hitzl W, Meier O, Koller H. Scoliosis and chest cage deformity measures predicting impairments in pulmonary function: a cross-sectional study of 492 patients with scoliosis to improve the early identification of patients at risk. Spine. 2014;39(24):2024–33.View ArticlePubMedGoogle Scholar
  6. Newton PO, Faro FD, Gollogly S, Betz RR, Lenke LG, Lowe TG. Results of preoperative pulmonary function testing of adolescents with idiopathic scoliosis. A study of six hundred and thirty-one patients. J Bone Joint Surg Am. 2005;87(9):1937–46.PubMedGoogle Scholar
  7. White SF, Asher MA, Lai SM, Burton DC. Patients’ perceptions of overall function, pain, and appearance after primary posterior instrumentation and fusion for idiopathic scoliosis. Spine. 1999;24(16):1693–9. discussion 1699-1700.View ArticlePubMedGoogle Scholar
  8. Misterska E, Glowacki M. Assessment of pain severity and function of lumbar spine in idiopathic scoliosis. Ortopedia Traumatologia Rehabilitacja. 2009;11(5):433–7.Google Scholar
  9. McMaster ME, Lee AJ, Burwell RG. Physical activities of Patients with adolescent idiopathic scoliosis (AIS): preliminary longitudinal case-control study historical evaluation of possible risk factors. Scoliosis. 2015;10:6.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Kulis A, Gozdzialska A, Drag J, Jaskiewicz J, Knapik-Czajka M, Lipik E, Zarzycki D. Participation of sex hormones in multifactorial pathogenesis of adolescent idiopathic scoliosis. Int Orthop. 2015;39(6):1227–36.View ArticlePubMedGoogle Scholar
  11. Li W, Li Y, Zhang L, Guo H, Tian D, Li Y, Peng Y, Zheng Y, Dai Y, Xia K, et al. AKAP2 identified as a novel gene mutated in a Chinese family with adolescent idiopathic scoliosis. J Med Genet. 2016;53(7):448–93.View ArticleGoogle Scholar
  12. Xu JF, Yang GH, Pan XH, Zhang SJ, Zhao C, Qiu BS, Gu HF, Hong JF, Cao L, Chen Y, et al. Association of GPR126 gene polymorphism with adolescent idiopathic scoliosis in Chinese populations. Genomics. 2015;105(2):101–7.View ArticlePubMedGoogle Scholar
  13. Zhang Y, Gu Z, Qiu G. The association study of calmodulin 1 gene polymorphisms with susceptibility to adolescent idiopathic scoliosis. BioMed Res Int. 2014;2014:168106.PubMedPubMed CentralGoogle Scholar
  14. Bae JW, Cho CH, Min WK, Kim UK. Associations between matrilin-1 gene polymorphisms and adolescent idiopathic scoliosis curve patterns in a Korean population. Mol Biol Rep. 2012;39(5):5561–7.View ArticlePubMedGoogle Scholar
  15. Zhao D, Qiu GX, Wang YP, Zhang JG, Shen JX, Wu ZH. Association between adolescent idiopathic scoliosis with double curve and polymorphisms of calmodulin1 gene/estrogen receptor-alpha gene. Orthop Surg. 2009;1(3):222–30.View ArticlePubMedGoogle Scholar
  16. Ogura Y, Kou I, Miura S, Takahashi A, Xu L, Takeda K, Takahashi Y, Kono K, Kawakami N, Uno K, et al. A functional SNP in BNC2 is associated with adolescent idiopathic scoliosis. Am J Hum Genet. 2015;97(2):337–42.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Yang P, Liu H, Lin J, Yang H. The association of rs4753426 polymorphism in the melatonin receptor 1B (MTNR1B) gene and susceptibility to adolescent idiopathic scoliosis: a systematic review and meta-analysis. Pain Phys. 2015;18(5):419–31.Google Scholar
  18. Wang H, Wu Z, Zhuang Q, Fei Q, Zhang J, Liu Y, Wang Y, Ding Y, Qiu G. Association study of tryptophan hydroxylase 1 and arylalkylamine N-acetyltransferase polymorphisms with adolescent idiopathic scoliosis in Han Chinese. Spine. 2008;33(20):2199–203.View ArticlePubMedGoogle Scholar
  19. Takahashi Y, Kou I, Takahashi A, Johnson TA, Kono K, Kawakami N, Uno K, Ito M, Minami S, Yanagida H, et al. A genome-wide association study identifies common variants near LBX1 associated with adolescent idiopathic scoliosis. Nat Genet. 2011;43(12):1237–40.View ArticlePubMedGoogle Scholar
  20. Xu J, Nonogaki M, Madhira R, Ma HY, Hermanson O, Kioussi C, Gross MK. Population-specific regulation of Chmp2b by Lbx1 during onset of synaptogenesis in lateral association interneurons. PLoS One. 2012;7(12):e48573.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Jagla K, Dolle P, Mattei MG, Jagla T, Schuhbaur B, Dretzen G, Bellard F, Bellard M. Mouse Lbx1 and human LBX1 define a novel mammalian homeobox gene family related to the Drosophila lady bird genes. Mech Dev. 1995;53(3):345–56.View ArticlePubMedGoogle Scholar
  22. Gross MK, Dottori M, Goulding M. Lbx1 specifies somatosensory association interneurons in the dorsal spinal cord. Neuron. 2002;34(4):535–49.View ArticlePubMedGoogle Scholar
  23. Fan YH, Song YQ, Chan D, Takahashi Y, Ikegawa S, Matsumoto M, Kou I, Cheah KS, Sham P, Cheung KM, et al. SNP rs11190870 near LBX1 is associated with adolescent idiopathic scoliosis in southern Chinese. J Hum Genet. 2012;57(4):244–6.View ArticlePubMedGoogle Scholar
  24. Grauers A, Wang J, Einarsdottir E, Simony A, Danielsson A, Akesson K, Ohlin A, Halldin K, Grabowski P, Tenne M, et al. Candidate gene analysis and exome sequencing confirm LBX1 as a susceptibility gene for idiopathic scoliosis. Spine J. 2015;15(10):2239–46.View ArticlePubMedGoogle Scholar
  25. Wise CA, Gao X, Shoemaker S, Gordon D, Herring JA. Understanding genetic factors in idiopathic scoliosis, a complex disease of childhood. Curr Genomics. 2008;9(1):51–9.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Critical Appraisal Skills Programme (CASP) 2014. 11 questions to help you make sense of Case Control Study. [http://media.wix.com/ugd/dded87_63fb65dd4e0548e2bfd0a982295f839e.pdf]. Accessed 1 Nov 2015.
  27. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.View ArticlePubMedGoogle Scholar
  28. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.View ArticlePubMedGoogle Scholar
  29. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Gao W, Peng Y, Liang G, Liang A, Ye W, Zhang L, Sharma S, Su P, Huang D. Association between common variants near LBX1 and adolescent idiopathic scoliosis replicated in the Chinese Han population. PLoS One. 2013;8(1):e53234.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Jiang H, Qiu X, Dai J, Yan H, Zhu Z, Qian B, Qiu Y. Association of rs11190870 near LBX1 with adolescent idiopathic scoliosis susceptibility in a Han Chinese population. Eur Spine J. 2013;22(2):282–6.View ArticlePubMedGoogle Scholar
  32. Liu S. Association study of gene polymorphisms with adolescent idopathic scoliosis susceptibility in a Northern Han Chinese population. (Doctor Thesis). Doctor. China: Peking Union Medical College; 2015.Google Scholar
  33. Zhu Z, Tang NL, Xu L, Qin X, Mao S, Song Y, Liu L, Li F, Liu P, Yi L, et al. Genome-wide association study identifies new susceptibility loci for adolescent idiopathic scoliosis in Chinese girls. Nat Commun. 2015;6:8355.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Miyake A, Kou I, Takahashi Y, Johnson TA, Ogura Y, Dai J, Qiu X, Takahashi A, Jiang H, Yan H, et al. Identification of a susceptibility locus for severe adolescent idiopathic scoliosis on chromosome 17q24.3. PLoS One. 2013;8(9):e72802.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Sharma S, Gao X, Londono D, Devroy SE, Mauldin KN, Frankel JT, Brandon JM, Zhang D, Li QZ, Dobbs MB, et al. Genome-wide association studies of adolescent idiopathic scoliosis suggest candidate susceptibility genes. Hum Mol Genet. 2011;20(7):1456–66.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Andersen MO, Thomsen K, Kyvik KO. Adolescent idiopathic scoliosis in twins: a population-based survey. Spine. 2007;32(8):927–30.View ArticlePubMedGoogle Scholar
  37. Harrington PR. The etiology of idiopathic scoliosis. Clin Orthop Relat Res. 1977;126:17–25.Google Scholar
  38. Muller T, Brohmann H, Pierani A, Heppenstall PA, Lewin GR, Jessell TM, Birchmeier C. The homeodomain factor lbx1 distinguishes two major programs of neuronal differentiation in the dorsal spinal cord. Neuron. 2002;34(4):551–62.View ArticlePubMedGoogle Scholar
  39. Pincott JR, Taffs LF. Experimental scoliosis in primates: a neurological cause. J Bone Joint Surg (Br). 1982;64(4):503–7.Google Scholar
  40. Kingsmore SF, Lindquist IE, Mudge J, Beavis WD. Genome-wide association studies: progress in identifying genetic biomarkers in common, complex diseases. Biomark Insights. 2007;2:283–92.PubMedPubMed CentralGoogle Scholar
  41. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, Hirschhorn JN. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet. 2008;9(5):356–69.View ArticlePubMedGoogle Scholar
  42. Chen S, Zhao L, Roffey DM, Phan P, Wai EK. Association of rs11190870 near LBX1 with adolescent idiopathic scoliosis in East Asians: a systematic review and meta-analysis. Spine J. 2014;14(12):2968–75.View ArticlePubMedGoogle Scholar
  43. Liang J, Xing D, Li Z, Chua S, Li S. Association between rs11190870 polymorphism near LBX1 and susceptibility to adolescent idiopathic scoliosis in East Asian population: a genetic meta-analysis. Spine. 2014. [Epub ahead of print].Google Scholar

Copyright

© The Author(s). 2016

Advertisement