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Association between growth differentiation factor 5 rs143383 genetic polymorphism and the risk of knee osteoarthritis among Caucasian but not Asian: a meta-analysis

Arthritis Research & Therapy volume 22, Article number: 215 (2020) Cite this article

Abstract

Background

A few months ago, the Bioscience Reports journal showed that growth differentiation factor 5 (GDF5) rs143383 genetic polymorphism increases the susceptibility of knee osteoarthritis (KOA), but previous studies’ results have debates about available data. Considering the availability of more recent data, we focus on clarifying the relationship of KOA and GDF5 rs143383 genetic polymorphism by a meta-analysis of case-control trial data.

Methods

The eligible studies from the time of database established to Oct. 2019 were collected from PubMed, Springer, Cochrane library, Web of Science, China National Knowledge Infrastructure (CNKI), and Wan Fang library. Odds ratios (OR) and 95% confidence intervals (CI) were used to estimate the association between these polymorphisms and KOA risk. The meta-analysis was completed by STATA 18.0 software.

Results

A total of 196 studies were collected, 16 of them included in final meta-analysis (7997 cases and 12,684 controls). There was significant association between GDF5 rs143383 polymorphism and KOA in all genetic models (for Allele model (C versus T): OR = 0.84 (95% CI = 0.76–0.91); dominate model (CC+CT versus TT): OR = 0.80 (95% CI = 0.72–0.90); recessive model (CC versus CT+TT): OR = 0.79 (95% CI = 0.68–0.92); heterozygote model (CT versus CC+TT): OR = 0.89 (95% CI = 0.80–0.97); homozygous model (CC versus TT): OR = 0.71 (95% CI = 0.60–0.85)). In the subgroup analysis, we obtained the results that there is no significance among Asians.

Conclusion

GDF5 rs143383 genetic polymorphism increases the risk of KOA among Caucasians; CC genotype and C allele are protective factors for the susceptibility of KOA among Caucasians.

Introduction

Osteoarthritis (OA) is a chronic degenerative disease and is a very important factor for disability in worldwide [1,2,3]. OA involves the knee, hip, wrist, etc. Knee osteoarthritis (KOA) is a common degenerative joint disease among osteoarthritis diseases [4]. Knee osteoarthritis is a multi-factorial disease, and its pathogenesis is currently unclear. Current studies have shown that smoking, diet, exercise, and genes are all associated with osteoarthritis [5]. The diagnosis of knee osteoarthritis is currently mainly diagnosed by imaging. There is no good way to predict the incidence of knee osteoarthritis. Recently, more and more attention has been paid to the study of knee osteoarthritis genes. It may not only explain the problem in genetics but also provide strong treatment directions for clinical workers.

Growth differentiation factor 5 (GDF5) rs143383 genetic polymorphisms is the association of the susceptibility of knee osteoarthritis reported in Bioscience Reports [5]. GDF5, also known as cartilage derived morphogenetic protein 1 (CDMP1), is an extracellular signaling molecule that participates in the development maintenance and repair of bone, cartilage, and other tissues of the synovial joint, with penetrant and rare deleterious mutations of the GDF5 gene resulting in dominant skeletal defects [6]. GDF5 is overexpressed in articular cartilage relative to osteophytic cartilage of OA patients, suggesting that it may play an important role in maintaining the stable articular chondrocyte phenotype [7].

Although the association of the risk of knee osteoarthritis and GDF5 rs143383 genetic polymorphisms has been described in several meta-analyses [8,9,10,11,12], several recent trials also reported the risk of knee osteoarthritis and GDF5 rs143383 genetic polymorphisms [4,5,6]. On the other hand, prior meta-analyses have some limitations, such as low quality and lacking enough studies. Therefore, we needed to update the data of the relevant studies and aim to clarify the relationship of GDF5 rs143383 genetic polymorphisms and the risk of knee osteoarthritis. Our article showed a latest and comprehensive relationship of GDF5 rs143383 genetic polymorphisms by using the latest and comprehensive case-control studies (Registered number: CRD42020168180, http://www.crd.york.ac.uk/prospero/).

Methods and study designs

The eligible studies from the time of database established to Oct. 2019 were collected from PubMed, Springer, Cochrane library, Web of Science, China National Knowledge Infrastructure (CNKI), and Wan Fang. Two independent authors extracted the data and assessed case-control trial quality.

In the meta-analysis, we made use of the Newcastle–Ottawa Scale in Epidemiology (NOS) group [13]. The PubMed, Springer, Cochrane library, Web of Science, China National Knowledge Infrastructure (CNKI), and Wan Fang library were searched (updated to October 20, 2019) with terms “differentiation factor 5,” “GDF5,” “rs143383,” “polymorphism,” “osteoarthritis,” and “OA,” as both medical subject heading (MeSH) terms and text words to find all papers that had studied the association of GDF5 with OA. A manual search was applied to finding unknown references to additional studies. English and Chinese language restrictions were applied. Studies were selected if they satisfy the following criteria: (1) case-control study; (2) sufficient published data for calculating the odds ratio and 95% confidence interval; (3) the association of GDF5 polymorphism with OA; (4) matched Hardy–Weinberg equilibrium (HWE) in control cases; and (5) having five models’ data of allelic model, homozygote model, heterozygote model, recessive model, and dominant model.

Data extraction and assess of quality

Two researchers (Lei Peng and Jiping Lu) conducted eligible studies based on the above inclusion criteria and collected information on each eligible study according to the inclusion criteria. The following items were extracted: first author, year of publication, country, population, genotype distribution, Hardy–Weinberg equilibrium (HWE), case, and control size. To avoid the wrong data, the researchers will examine the collected data and make a conclusion through discussion. The quality of studies was evaluated by two independent investigators (Peng and Lu) based on the Newcastle–Ottawa Scale (NOS) for case-control studies [14]. The study was considered high quality with the scores were ≥ 7. In the case of disputes, we settle disputes through discussion. A third investigator (Peng Wang) decided this on the basis of discussions.

Statistical methods

Pearson’s χ2 test estimates deviation from HWE in the control group according to genotype distributions. Crude OR with their 95% CI was estimated and used to assess the strength of association between GDF5 rs143383 polymorphism and KOA. The pooled OR was calculated respectively for allelic effect of C versus T, homozygote comparison of CC versus TT, heterozygote comparison of CT versus CC+TT, recessive model (CC versus TT+CT) and dominant model (CC+CT versus TT). The significance of the pooled OR was determined by the Z-test (P ≤ 0.05). Q statistics (P < 0.10) indicated the evidence of heterogeneity was used to assess heterogeneity between studies. When significant heterogeneity was achieved (P < 0.10), the effect size of the study was combined with the random effect model; otherwise, the fixed effect model was used. Subgroup analysis was performed according to population, and sensitivity analysis was performed to determine the impact of individual studies on the aggregated results and to test the reliability of the results. The potential publishing bias was estimated by Begg’s funnel plot and Egger regression test. All cases were analyzed by STATA 18.0 software (Stata Corporation, College Station, TX, USA). The P values were bilateral. This study followed the PRISMA standard.

Results

Studies extraction and characteristics of studies

Sixteen articles [5, 11, 15,16,17,18,19,20,21,22,23,24,25,26,27,28], including separate 20 studies (7997 cases and 12,684 controls), finally have been collected in the meta-analysis from 196 studies, which process is showed in Fig. 1. All studies’ details, including first author name, year of publication, ethnicity, country, sex, gender ration, evaluation of quality (NOS), HWE, study design, genotyping method, and mean age, are shown in Table 1.

Fig. 1
figure1

Studies identification diagram (from [13])

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Table 1 Relevant studies concerning relationships between GDF5 rs143383 polymorphisms and knee osteoarthritis
Full size table

Efficiency analysis

By comprehensive analysis, there is significant relationship between knee osteoarthritis and GDF5 rs143383 polymorphisms. Allele model (C versus T): OR = 0.84 (95% CI = 0.76–0.92); dominate model (CC+CT versus TT): OR = 0.80 (95% CI = 0.72–0.90); recessive model (CC versus CT+TT): OR = 0.79 (95% CI = 0.68–0.92); heterozygote model (CT versus CC+TT): OR = 0.88 (95% CI = 0.80–0.96); homozygous model (CC versus TT): OR = 0.88 (95% CI = 0.80–0.97). Overall analyses are showed in Table 2. OR value of genetic model crosses 1, which means that summary results are not of statistical significance. Summary heterogeneity of genetic model is > 50%, so we conducted subgroup analysis to explain the heterogeneity.

Table 2 Meta-analysis for GDF5 rs143383 polymorphisms and knee osteoarthritis risk
Full size table

Subgroup analysis by ethnicity

There is significant correlation between knee osteoarthritis and GDF5 rs1433383 polymorphisms in Caucasians. In Caucasians, all genetic model results are showed in Table 2 (C vs. T: OR = 0.79–0.91, P < 0.05; CC+CT vs. TT: OR = 0.71–0.92, P < 0.05; CC vs. CT+TT: OR = 0.72–0.90, P < 0.05; CT vs. CC+TT: OR = 0.79–1.02, P < 0.05; CC vs. TT: OR = 0.80–1.02, P < 0.05). But in Asians, there is no significant correlation between knee osteoarthritis and GDF5 rs143383 polymorphisms among all genetic model. We did not carry on the subgroup analysis by sex, because previous meta-analysis study conclude sex factor is not significant between GDF5 rs143383 polymorphism and the risk of knee osteoarthritis. A more obvious significant association was exploited for CC vs. TT+CT (OR = 0.81, P < 0.05) and C vs. T (OR = 0.84, P < 0.05) in comparison with other models in Caucasians (Table 2, Figs. 2 and 3). The results show CC genetic model and C allele are protective factors in KOA. All heterogeneity of genetic model still remains. To solve the heterogeneity, we use random effect model in the meta-analysis and make sensitivity analysis to ensure reliable results.

Fig. 2
figure2

Forest of GDF5 genetic polymorphism (C>T) and KOA (CC vs CT+TT)

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Fig. 3
figure3

Forest of GDF5 genetic polymorphism (C>T) and KOA (C vs T)

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Sensitivity analysis and publication Bias

The stableness of the results is estimated by sensitivity analysis. The sensitivity analysis procedure is a single study deleted from the meta-analysis every time, but the results remain unchanged (Fig. S1). The Begg’s funnel diagram does not show any obvious sign of dissymmetry in all genetic models (Fig. 4). Furthermore, Egger’s regression analysis did not show publication bias in the results (P = 0.707 for 2G versus 1G, P = 0.452 for 2G/2G versus 1G/1G, P = 0.452 for 1G/2G versus 1G/1G, P = 0.851 for recessive model, and P = 0.133 for dominant model, respectively). Figure 4 and Egger’s regression analysis describe that results are stable and reliable in the current meta-analysis.

Fig. 4
figure4

Funnel plots of the association between GDF5 rs143383 polymorphism and knee osteoarthritis (a allele model, b dominate model, c recessive model, d homozygote model, e heterozygote model)

Full size image

Discussion

In the research article, we firstly found that GDF5 rs143383 polymorphisms affect the risk of knee osteoarthritis in Caucasian but not in Asian, including detailed data from 16 studies in 7997 cases and 12,684 controls. The final results are new observations in previous studies. When carrying on the funnel plot to analyze some bias, the results still are very stable and reliable.

GDF5 is a member of bone morphogenetic proteins (BMP) family, which is located on chromosome 20q11.2 and spans 21.43 kb, from 34,042,573 to 34,021,146 and can form the earliest markers of joint morphology. BMP is an indispensable signal pathway molecule or protein in most kinds of bones [29,30,31,32,33,34,35,36,37]. There are many cells expressing the GDF5 gene, including articular cartilage, articular capsule, and ligament. GDF5 gene mutation may result in the downregulation of the transcription activity of articular chondrocytes [38,39,40]. Decreased GDF5 levels in fully formed adult knees may also influence OA risk by impairing homeostasis in healthy joints or by accelerating degeneration due to injury [41]. The growth differentiation factor 5 gene GDF5 was one of the first reported OA susceptibility signals that showed consistent association to OA, with the transcript single nucleotide polymorphism (SNP) rs143383 demonstrating association in Asians and Europeans [42].

On the one hand, previous literatures have said that GDF5 rs143383 polymorphisms C allele is a protective factor for the susceptibility of knee osteoarthritis among Caucasian populations (OR = 0.74, P < 0.001) and Asian populations (OR = 0.87, P = 0.004) [9]. On the other hand, Zhang et al. holds that interaction of GDF5 rs143383 polymorphisms T allele increases the risk of knee osteoarthritis among Asian (OR = 1.62, P < 0.001) [5]. But now our research shows that GDF5 rs143383 polymorphisms are only related to knee osteoarthritis among Caucasian populations by subgroup analysis, not Asian populations.

Although previous meta-analysis literatures thought that high-expressed GDF5 rs143383(C/T) can reduce the risk of knee osteoarthritis, their limitations still remain. Firstly, Pan et al.’s meta-analysis has some shortcomings, including unmatching HWE studies in their meta-analysis [8], which results are unreliable. Secondly, Huang et al.’s meta-analysis explores the association between all kinds of osteoarthritis and GDF5 rs143383 polymorphisms, which cannot precisely describe the relationship between GDF5 rs143383 polymorphisms and the susceptibility of knee osteoarthritis [12]. Although genetic variants can have different effect sizes in different populations, as is shown for GDF5 for African populations vs Eurasian populations [43,44,45], it is highly unlikely that this is the case, based on the data presented by the authors. These studies focused on apes, so there is still a gap between apes and humans. In the discussion, the authors state that future studies should include more samples and examine more genetic variants. We did not use freely available data from large population association studies (GWAS) which have been published [46,47,48,49], because the data of the sample size of the five models cannot be extracted. The meta-analysis mainly focused on GDF5 rs143383, and no other variants of GDF5, because our aim is to solely clarify controversial GDF5 rs143383.

To sum it up, our final results, paralleling to previous results, are more reliable by comprehensive collection and assessment of quality. Furthermore, the association between osteoarthritis and GDF5 is more clear than previous studies.

Conclusions

Our article has found sufficient pieces of evidences to conclude that the risk of Caucasian’s knee osteoarthritis is the association with GDF5 rs143383 polymorphisms. To our knowledge, this result is the first discovery in which the risk of Asian knee osteoarthritis is not associated with GDF5 rs143383 polymorphisms by meta-analysis. The finding may indicate that GDF5 rs143383 polymorphism mutations are population specific. In the future, the potential study should increase more samples about knee osteoarthritis and more gene variants to precisely and comprehensively clarify the relationship between knee osteoarthritis and gene variants.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CI:

Confidence interval

HWE:

Hardy–Weinberg equilibrium

KOA:

Knee osteoarthritis

GDF:

Growth differentiation factor

NOS:

Newcastle–Ottawa Scale

OA:

Osteoarthritis

OR:

Odds ratio

BMP:

Bone morphogenetic protein

References

  1. 1.

    Gregori D, et al. Association of pharmacological treatments with long-term pain control in patients with knee osteoarthritis: a systematic review and meta-analysis. JAMA. 2018;320(24):2564–79.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Mokdad AH, et al. The state of US health, 1990-2016: burden of diseases, injuries, and risk factors among US states. JAMA. 2018;319(14):1444–72.

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Glyn-Jones S, et al. Osteoarthritis. Lancet. 2015;386(9991):376–87.

    CAS  PubMed  Google Scholar 

  4. 4.

    Peng L, et al. Lack of association between matrix metalloproteinase-1 gene rs1799750 polymorphism and osteoarthritis susceptibility: a meta-analysis. Biosci Rep. 2019;39(4). https://doi.org/10.1042/BSR20181960.

  5. 5.

    Zhang S, et al. Interaction between GDF5 gene polymorphisms and environment factors increased the risk of knee osteoarthritis: a case-control study. Biosci Rep. 2019;39(2). https://doi.org/10.1042/BSR20182423.

  6. 6.

    Dodd AW, et al. Deep sequencing of GDF5 reveals the absence of rare variants at this important osteoarthritis susceptibility locus. Osteoarthr Cartil. 2011;19(4):430–4.

    CAS  PubMed  Google Scholar 

  7. 7.

    Gelse K, et al. Molecular differentiation between osteophytic and articular cartilage--clues for a transient and permanent chondrocyte phenotype. Osteoarthr Cartil. 2012;20(2):162–71.

    CAS  PubMed  Google Scholar 

  8. 8.

    Pan F, et al. Association between GDF5 rs143383 polymorphism and knee osteoarthritis: an updated meta-analysis based on 23,995 subjects. BMC Musculoskelet Disord. 2014;15:404.

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Jiang D, et al. Association between GDF5 +104T/C polymorphism and knee osteoarthritis in Caucasian and Asian populations: a meta-analysis based on case-control studies. J Orthop Surg Res. 2016;11(1):104.

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    Mouallem M, et al. A man with a prosthetic valve, anaemia, fever, and splenomegaly. Lancet. 1996;348(9036):1216.

    CAS  PubMed  Google Scholar 

  11. 11.

    Chapman K, et al. A meta-analysis of European and Asian cohorts reveals a global role of a functional SNP in the 5′ UTR of GDF5 with osteoarthritis susceptibility. Hum Mol Genet. 2008;17(10):1497–504.

    CAS  PubMed  Google Scholar 

  12. 12.

    Huang X, Zhang W, Shao Z. Association between GDF5 rs143383 genetic polymorphism and musculoskeletal degenerative diseases susceptibility: a meta-analysis. BMC Med Genet. 2018;19(1):169.

    PubMed  PubMed Central  Google Scholar 

  13. 13.

    Moher D, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Mishra A, et al. Association of polymorphism in growth and differentiation factor 5 gene with osteoarthritis knee. Am J Biochem Biotechnol. 2013;91. https://doi.org/10.5152/eurjrheum.2017.160093.

  16. 16.

    Abd Elazeem MI, Abdelaleem EA, Mohamed RA. Genetic influence of growth and differentiation factor 5 gene polymorphism (+104T/C) on the development of knee osteoarthritis and its association with disease severity. Eur J Rheumatol. 2017;4(2):98–103.

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Ozcan SS, et al. Polymorphisms in the growth differentiation factor 5 (GDF 5) gene in knee osteoarthritis. J Coll Physicians Surg Pak. 2017;27(10):602–5.

    PubMed  Google Scholar 

  18. 18.

    Miyamoto Y, et al. A functional polymorphism in the 5′ UTR of GDF5 is associated with susceptibility to osteoarthritis. Nat Genet. 2007;39(4):529–33.

    CAS  PubMed  Google Scholar 

  19. 19.

    Tawonsawatruk T, et al. A genetic association study between growth differentiation factor 5 (GDF 5) polymorphism and knee osteoarthritis in Thai population. J Orthop Surg Res. 2011;6:47.

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Cao Z, et al. Growth differentiation factor 5 (GDF5) core promoter polymorphism is not associated with susceptibility to osteoarthritis of the knee in the Korean population. J Pathol Transl Med. 2010;44(4):404–9.

    Google Scholar 

  21. 21.

    Valdes AM, et al. Association of the DVWA and GDF5 polymorphisms with osteoarthritis in UK populations. Ann Rheum Dis. 2009;68(12):1916–20.

    CAS  PubMed  Google Scholar 

  22. 22.

    Tsezou A, et al. The growth differentiation factor 5 (GDF5) core promoter polymorphism is not associated with knee osteoarthritis in the Greek population. J Orthop Res. 2008;26(1):136–40.

    CAS  PubMed  Google Scholar 

  23. 23.

    Southam L, et al. An SNP in the 5′-UTR of GDF5 is associated with osteoarthritis susceptibility in Europeans and with in vivo differences in allelic expression in articular cartilage. Hum Mol Genet. 2007;16(18):2226–32.

    CAS  PubMed  Google Scholar 

  24. 24.

    Shin MH, et al. Genetic association analysis of GDF5 and ADAM12 for knee osteoarthritis. Joint Bone Spine. 2012;79(5):488–91.

    CAS  PubMed  Google Scholar 

  25. 25.

    Valdes AM, et al. The GDF5 rs143383 polymorphism is associated with osteoarthritis of the knee with genome-wide statistical significance. Ann Rheum Dis. 2011;70(5):873–5.

    CAS  PubMed  Google Scholar 

  26. 26.

    Vaes RB, et al. Genetic variation in the GDF5 region is associated with osteoarthritis, height, hip axis length and fracture risk: the Rotterdam study. Ann Rheum Dis. 2009;68(11):1754–60.

    CAS  PubMed  Google Scholar 

  27. 27.

    García-Alvarado F, et al. Association between the SNP rs143383 + 104T/C in the GDF5 gene and the risk of knee osteoarthritis in a population from northern Mexico-a case-control study. Genet Test Mol Biomarkers. 2018;22(8):503–6.

    PubMed  Google Scholar 

  28. 28.

    Yao C, Dai J, Qin J. A single nucleid polymorphisms (SNP) in the 5′UTR of GDF5 is associated with knee osteoarthritis. Jiangsu Med J. 2008;4(012):1198–9.

  29. 29.

    Francis-West PH, et al. Mechanisms of GDF-5 action during skeletal development. Development. 1999;126(6):1305–15.

    CAS  PubMed  Google Scholar 

  30. 30.

    Urist MR. Bone morphogenetic protein: the molecularization of skeletal system development. J Bone Miner Res. 1997;12(3):343–6.

    CAS  PubMed  Google Scholar 

  31. 31.

    Wozney JM, Rosen V. Bone morphogenetic protein and bone morphogenetic protein gene family in bone formation and repair. Clin Orthop Relat Res. 1998;346:26–37.

    Google Scholar 

  32. 32.

    Storm EE, et al. Limb alterations in brachypodism mice due to mutations in a new member of the TGF beta-superfamily. Nature. 1994;368(6472):639–43.

    CAS  PubMed  Google Scholar 

  33. 33.

    Chang SC, et al. Cartilage-derived morphogenetic proteins. New members of the transforming growth factor-beta superfamily predominantly expressed in long bones during human embryonic development. J Biol Chem. 1994;269(45):28227–34.

    CAS  PubMed  Google Scholar 

  34. 34.

    Storm EE, Kingsley DM. Joint patterning defects caused by single and double mutations in members of the bone morphogenetic protein (BMP) family. Development. 1996;122(12):3969–79.

    CAS  PubMed  Google Scholar 

  35. 35.

    Brunet LJ, et al. Noggin, cartilage morphogenesis, and joint formation in the mammalian skeleton. Science. 1998;280(5368):1455–7.

    CAS  PubMed  Google Scholar 

  36. 36.

    Merino R, et al. Expression and function of Gdf-5 during digit skeletogenesis in the embryonic chick leg bud. Dev Biol. 1999;206(1):33–45.

    CAS  PubMed  Google Scholar 

  37. 37.

    Hartmann C, Tabin CJ. Wnt-14 plays a pivotal role in inducing synovial joint formation in the developing appendicular skeleton. Cell. 2001;104(3):341–51.

    CAS  PubMed  Google Scholar 

  38. 38.

    Rountree RB, et al. BMP receptor signaling is required for postnatal maintenance of articular cartilage. PLoS Biol. 2004;2(11):e355.

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Koyama E, et al. A distinct cohort of progenitor cells participates in synovial joint and articular cartilage formation during mouse limb skeletogenesis. Dev Biol. 2008;316(1):62–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Egli RJ, et al. Functional analysis of the osteoarthritis susceptibility-associated GDF5 regulatory polymorphism. Arthritis Rheum. 2009;60(7):2055–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Pregizer SK, et al. Impact of broad regulatory regions on Gdf5 expression and function in knee development and susceptibility to osteoarthritis. Ann Rheum Dis. 2018;77(3):450.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Ratnayake M, et al. A consistent and potentially exploitable response during chondrogenesis of mesenchymal stem cells from osteoarthritis patients to the protein encoded by the susceptibility gene GDF5. PLoS One. 2017;12(5):e0176523.

    PubMed  PubMed Central  Google Scholar 

  43. 43.

    Lewis CM, Knight J. Introduction to genetic association studies. Cold Spring Harb Protoc. 2012;2012(3):297–306.

    PubMed  Google Scholar 

  44. 44.

    Richard D, et al. Evolutionary selection and constraint on human knee chondrocyte regulation impacts osteoarthritis risk. Cell. 2020;181(2):362–381.e28.

    CAS  PubMed  Google Scholar 

  45. 45.

    Capellini TD, et al. Ancient selection for derived alleles at a GDF5 enhancer influencing human growth and osteoarthritis risk. Nat Genet. 2017;49(8):1202–10.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Tachmazidou I, et al. Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data. Nat Genet. 2019;51(2):230–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Zengini E, et al. Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis. Nat Genet. 2018;50(4):549–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Zeggini E, et al. Identification of new susceptibility loci for osteoarthritis (arcOGEN): a genome-wide association study. Lancet. 2012;380(9844):815–23.

    PubMed  Google Scholar 

  49. 49.

    Styrkarsdottir U, et al. Meta-analysis of Icelandic and UK data sets identifies missense variants in SMO, IL11, COL11A1 and 13 more new loci associated with osteoarthritis. Nat Genet. 2018;50(12):1681–7.

    CAS  PubMed  Google Scholar 

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Acknowledgements

We thank LU Jiping, JIN Song, and WANG Peng for the assistance with the collection of data and genetic details for this study.

Funding

This study is supported by National Natural Science Foundation of China, Nos.81672097, 81672128, and 81702120.

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Author notes

  1. Lei Peng, Song Jin and Jiping Lu contributed equally to this work.

Affiliations

  1. Department of Orthopedics, The Eighth Affiliated Hospital, Sun Yat-sen University, 3025# Shen Nan Road, Shenzhen, 518033, People’s Republic of China

    Lei Peng, Song Jin, Jiang Guo, Zhongyu Xie, Huiyong Shen & Peng Wang

  2. Department of Orthopedics, The Second Affiliated Hospital, Sun Yat-sen University, 107# Yan Jiang Road West, Guangzhou, 510120, People’s Republic of China

    Lei Peng, Jiang Guo, Zhongyu Xie, Huiyong Shen & Peng Wang

  3. Department of Orthopedics, The Second Affiliated Hospital of Hunan Normal University, The 921 Central Hospital of the People’s Liberation Army, Hongshan bridge, Changsha, People’s Republic of China

    Lei Peng, Jiping Lu & Chao Ouyang

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Contributions

L.P. and P. W. designed the meta-analysis. L. P., J. L., C. O., and J. G. searched aimed studies and extracted corresponding data. All authors helped prepare the manuscript and approved the manuscript for submission.

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Correspondence to Huiyong Shen or Peng Wang.

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Supplementary information

Additional file 1: Fig. S1.

Sensitivity analysis of the pooled ORs and 95% CI for the overall analysis.

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Peng, L., Jin, S., Lu, J. et al. Association between growth differentiation factor 5 rs143383 genetic polymorphism and the risk of knee osteoarthritis among Caucasian but not Asian: a meta-analysis. Arthritis Res Ther 22, 215 (2020). https://doi.org/10.1186/s13075-020-02306-9

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Keywords

  • Knee osteoarthritis
  • Polymorphism
  • Growth differentiation factor 5, rs143383
  • Caucasian

Arthritis Research & Therapy

ISSN: 1478-6362

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