Literature DB >> 24058403

Association study of polymorphisms in selenoprotein genes and Kashin-Beck disease and serum selenium/iodine concentration in a Tibetan population.

Lulin Huang1, Yi Shi, Fang Lu, Hong Zheng, Xiaoqi Liu, Bo Gong, Jiyun Yang, Ying Lin, Jing Cheng, Shi Ma, He Lin, Zhenglin Yang.   

Abstract

BACKGROUND: Kashin-Beck disease is a kind of degenerative osteoarthropathy. Genetic factors may play an important role in the pathogenesis of KBD.
OBJECTIVE: To investigate the association of the selenoprotein genes GPX1 (rs1050450, rs1800668, and rs3811699), TrxR2 (rs5748469), and DIO2 (rs225014) with Kashin-Beck disease (KBD) in a Tibetan population and to investigate the association of these SNPs with the serum iodine/selenium concentration in the Tibetan population.
DESIGN: Five SNPs including rs1050450, rs1800668, and rs3811699 in the GPX1 gene, rs5748469 in the TrxR2 gene, and rs225014 in the DIO2 gene were analyzed in Tibetan KBD patients and controls using the SNaPshot method. P trend values of the SNPs were calculated using an additive model.
RESULTS: None of the five SNPs in the three genes showed a significant association with KBD. Haplotypes TCC, TTC and TTT of rs1050450, rs1800668 and rs3811699 in GPX1 showed a significant association with KBD and controls with P value of 0.0421, 5.0E-4 and 0.0066, respectively. The GPX1 gene (rs1050450) showed a potential significant association with the iodine concentration in the Tibetan study population (P = 0.02726). However, no such association was detected with the selenium concentration (P = 0.2849).
CONCLUSIONS: In this study, we showed that single SNPs in the genes GPX1 (rs1050450, rs1800668 and rs3811699), TrxR2 (rs5748469), and DIO2 (rs225014) may not be significantly associated with KBD in a Tibetan population. However, haplotype analysis of SNPs rs1050450, rs1800668 and rs3811699 in GPX1 gene showed a significant association with KBD. The results suggested that GPX1 gene play a protective role in the susceptivity of KBD in Tibetans. Furthermore, the GPX1 gene (rs1050450) may be significantly associated with the serum iodine concentration in Tibetans.

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Year:  2013        PMID: 24058403      PMCID: PMC3751926          DOI: 10.1371/journal.pone.0071411

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Kashin–Beck Disease (KBD) is named after the two Russian Cossack doctors Nikolai Kashin and Evgeny Beck who first described bone deformities in patients in Russia in 1848 and 1906, respectively [1]. Today, KBD is known as an endemic, chronic, and degenerative osteoarthropathy, with the involvement of epiphyseal cartilage damage, joint damage, and gradual deformation of the bone and joints [2]–[4]. KBD is endemic in a crescent-shaped area encompassing South-Eastern Siberia to North China, Central China, and Chinese Tibet; it is also endemic in Mongolia and North Korea [5]. China has the most KBD patients in the world [1]. The most frequently involved joints are the ankles, knees, wrists, and elbows. The disease often occurs in children aged 5–15 years and is age related, and serious KBD is responsible for significant disability. In some KBD endemic regions in China, the incidence of KBD is about 8.3% (2.5 million of 30 million urban residents affected) [6]. The etiology of KBD is largely unknown. The risk factors are thought to include deficiency in trace elements, mainly selenium and iodine deficiency [7]–[14]. In addition, mycotoxins such as Trichothecene mycotoxin (T-2), which are produced by various fungi such as F. compactum, F. moniliforme, and F. oxysporum in contaminated storage grains, are also suspected factors in KBD susceptibility [15]–[17]. Organic substances such as humic acid and fulvic acid in drinking water have also been implicated in the disease [3], [18], [19]. Among all of these risk factors, selenium and iodine have been extensively studied. Recently we also confirmed that low selenium and iodine concentrations are associated with KBD [20]. Genetic factors also play an important role in the pathogenesis of KBD. Xiong et al. showed that the polymorphisms of the selenoprotein GPX1 gene (rs1050450 and Pro200Leu) were significantly different between patients with KBD and controls (P = 0.013) in a Han Chinese population [21]. To further investigate the potential relationship between selenoprotein genes and KBD susceptibility in Tibetans, we analyzed the association of the three selenoprotein genes GPX1 (rs1050450, rs1800668, and rs3811699), TrxR2 (rs5748469), and DIO2 (rs225014) with Tibetan KBD in this study. Moreover, we investigated the association between these SNPs and serum selenium and iodine concentrations in Tibetans.

Materials and Methods

Study population

KBD patients and matched normal controls in this study were recruited from Tibetan populations in the same endemic villages in Song Pan, Ruo Er Gai, and Hong Yuan counties in the Aba Tibetan Autonomous prefecture of Sichuan Province, China. Clinical examination was performed as the methods of Moreno-Reyes [7] and Greulich [22]. Patients show joint of fingers, toes, knees and ankles swelling (Figure 1). The KBD patients showed specific changes on X-ray photography; they did not have other arthritis diseases such as rheumatoid arthritis (RA), Osteoarthritis (OA), or local inflammation. Normal controls were individuals with a normal joint examination and no other bone or joint disease. Clinical information about the patients and the controls is listed in Table 1. Veinal bloods (5 ml) of the participants were collected for DNA extraction. The Institutional Review Boards of the Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital approved this study. All of the participants received and signed the informed consent.
Figure 1

Clinical features of KBD patients.

A. A female KBD patient with her knee, ankle and toe joints deformity, the arrows show multiple joints of this patient are affected. B. A male KBD patient with his fingers joints deformity. C. The X-ray picture of a KBD patient's hand.

Table 1

Characteristics of the KBD cases and controls.

CharacteristicsCases(n = 638)Controls(n = 324)
Age, mean ± SD53.3±13.0754.5±15.81
Sex, male/female244/394157/167
Degree
I241
II336
III60
IV1

Clinical features of KBD patients.

A. A female KBD patient with her knee, ankle and toe joints deformity, the arrows show multiple joints of this patient are affected. B. A male KBD patient with his fingers joints deformity. C. The X-ray picture of a KBD patient's hand.

Selection of SNPs

Following a review of the literature, we selected five single nucleotide polymorphisms (SNPs) in three selenoprotein genes to genotype: glutathione peroxidase 1 (GPX1, rs1050450), thioredoxin reductase 2 (TrxR2, rs5748469), and iodothyronine deiodinase type 2 (DIO2, rs225014) to genotype [21]. We also referenced the NCBI SNP database and selected rs1800668 and rs3811699 in the GPX1 gene for genotyping. Information pertaining to the five SNPs selected is shown in Table 2.
Table 2

Conditions used for genotyping assays.

SNPsPrimersTa(°C)
GPX1(rs1050450)FW:CGCCAAGAACGAAGAGATTC58
missense CCC⇒ CTC Pro200LeuRV:CTGACACCCGGCACTTTATT
S30-C/T:CTGACATCGAAGCCCTGCTGTCTCAAGGGC
SV40-A/G:CCAAGCAGCCGGGGTAGGAGGGGCGCCCTAGGCACAGCTG
GPX1(rs1800668)FW:ACAGGAGAGGAGGGCTGTTT63.5
UTR-5 C/TRV:AGAAGGCATACACCGACTGG
S60-C/T:CCTGTGCCACGTGACCCGCCGCCGGCCAGTTAAAAGGAGGCGCCTGCTGGCCTCCCCTTA
GPX1(rs3811699)FW:AGGACTTCCTGGCCTAGCTC63.3
nearGene-5 C/TRV:CCAGAGGGATCTAGGCTTCC
S50C/T:GCCAAGGAAACGCTGCCGGAGTCCTCCCTCCCTGGCCTCCTCAGGCTGCA
DIO2(rs225014)FW:TCGTGAAAGGAGGTCAAGT58
missense C/T ACA⇒ GCA Thr92Ala;Thr128AlaRV:GTGGCAATGTGTTTAATGTG
S50-C/T:CTCAGCTATCTTCTCCTGGGTACCATTGCCACTGTTGTCACCTCCTTCTG
TrxR2(rs5748469)FW:TCCCAAAGTGCTGTGAGT58
missense A/C GCC⇒ TCC Ala66SerRV:ACCTGCTGCTCTCCTTATC
S40-A/C:TGCCTACCTTGGGGAGAAGGTTCCACGTAGTCCACCACGG

Genotyping

Genomic DNA was extracted using a Gentra Puregene Blood DNA kit (Minneapolis, MN). SNP genotyping was performed by the dye terminator-based SNaPshot method (Applied Biosystems, Foster City, CA). The SNP analysis was performed on the ABI 3130XL genetic analyzer (Applied Biosystems). The genotypes of the SNPs were determined by Genemapper software (Applied Biosystems). All of the SNPs reported in this manuscript had a genotyping success rate >96 percent and accuracy as judged by random regenotyping of 10 percent of the samples in the subject group. The PCR and SNaPshot primers are listed in Table 2.

Statistical analysis

The Hardy-Weinberg equilibrium (HWE) for each SNP polymorphism was tested by the χ2 test with df  = 1. The P values of the SNPs were calculated using an additive model. Unadjusted odds ratios of the alleles and genotypes were estimated by the χ2 test. The LD block structure was examined by using software Haploview Vision 4.2. The D and r2 values for all pairs of SNPs were calculated, and the haplotype blocks were estimated by using software Haploview Vision 4.2.All of the statistical analyses were performed using the software SPSS version 10.0. P<0.05 was considered statistically significant.

Results

Genotype analysis of the KBD group and the controls

All of the five SNPs selected were successfully genotyped. However, the results showed that none of these five SNPs were significantly associated with KBD (Table 3). Although the SNP rs1050450 (Pro200Leu) in the GPX1 gene was reported to be significantly associated with KBD in previous studies in a Han Chinese population (P = 0.013), this SNP did not show a significant association with KBD in the Tibetan population in this study (P =  0.1031) [21]. The other two SNPs in the GPX1 gene (rs1800668 at 5′UTR of the gene and rs3811699 at 3′upstream of the gene) also showed no association with KBD (P = 0.7614 and P = 0.8351, respectively). In contrast to the results that Xiong et al. reported in the Han population, neither the DIO2 gene (rs225014) nor the TrxR2 gene (rs5748469) showed significant differences in the Tibetan KBD group compared with the control group (P = 0.7287 and P = 0.4426, respectively).
Table 3

Genotype and allele frequencies of polymorphisms across selenoprotein genes in Tibetan.

SNPsControlsKBDTrend
numberFreqnumberFreq.p-value(OR)
GPX1(rs1050450)0.1031(0.74)
CC2710.8365590.876
CT530.164790.124
TT0000
C-allele5950.91811970.938
T-allele530.08270.062
P_HWE 0.10890.0956
GPX1(rs1800668)0.7614(1.06)
CC1830.8061970.804
CT400.176410.167
TT40.01870.029
C-allele4060.8944350.883
T-allele480.106550.112
P_HWE 0.30460.012
GPX1(rs3811699)0.8351(0.95)
TT2020.8382120.841
CT350.145370.147
CC40.01730.012
T-allele4390.9114610.915
C-allele430.089430.085
P_HWE 0.09880.3467
DIO2(rs225014)0.7287(1.04)
TT940.3881580.356
CT1130.4672280.514
CC350.145580.131
T-allele3010.6225440.613
C-allele1830.3783440.387
P_HWE 0.91210.0844
TrxR2(rs5748469)0.4426(0.86)
AA1370.7142090.749
AC500.26630.226
CC50.02670.025
A-allele3240.8444810.882
C-allele600.156770.138
P_HWE 0.86420.3958

Haplotype analysis of the three SNPs in the GPX1 gene

We examined the three SNPs in gene GPX1 (rs3811699, rs1050450, and rs1800668) in all tested samples using the program Haploview (Vision4.2). The haplotypes TCC, TTC and TTT generated from these three SNPs proved to be significantly different between the KBD cases and controls (P = 0.0421, 0.0005 and 0.0066, Table 4). These individuals showed protective feature in the susceptibility of KBD with the odds ratios of 0.69, 0.22 and 0.15 respectively.
Table 4

The haplotype association of gpx1 with KBD in this study.

HaplotypeFrequenciesChi SquareP valueOdds ratio (95% CI)
TCC0.8484.1320.04210.69(0.49–0.98)
CTT0.060.2220.63761.14(0.67–1.91)
TTC0.03212.1835.00E-040.22(0.088–0.553)
CCT0.0220.4360.50921.34(0.57–3.14)
TCT0.0160.2960.58611.32(0.49–3.57)
TTT0.0157.3710.00660.15(0.03–0.724)

Comparison of the Results of the Genotype Analysis Based on the Subjects' Iodine or Selenium Concentrations

Given that KBD is related to iodine or selenium deficiency, we analyzed the genotypes of the KBD group and the controls in relation to the subjects' serum iodine or selenium concentrations which were tested previously [23]. The results are shown in Table 5 and Table 6 for iodine and selenium, respectively. We found no significant differences between the KBD group and the controls, providing additional evidence for the absence of an association between the five SNPs and KBD in the Tibetan population. The power calculation results are shown in Table 7.
Table 5

Genotype and allele frequencies of polymorphisms across selenoprotein genes by serum iodine concentration in Tibetan population.

SNPsControlsKBDControlsKBDTrendHigher groupLower groupHigher groupLower groupTrend
numbernumberFreq.Freq.p-valuenumbernumberFreq.Freq.p-value
GPX1(rs1050450)0.9129*0.02726
CC1461550.8110.8161541470.770.865
CT34350.1890.18446230.230.135
TT00000000
C-allele3263450.9060.9083543170.8850.932
T-allele34350.0940.09246230.1150.068
P_HWE 0.16170.1620.06610.140130.3441
GPX1(rs1800668)0.14010.3982
CC2052070.8040.8811871810.3790.823
CT49220.1920.09448330.20.15
TT160.0040.026560.0210.027
C-allele4594360.90.9284223950.8790.898
T-allele51340.10.07258450.1210.102
P_HWE 0.280800.36340.0066
GPX1(rs3811699)0.87630.14013
TT2002120.840.8412052070.8040.881
CT34370.1430.14749220.1920.094
CC430.0170.012160.0040.026
T-allele4344610.9120.9154594360.90.928
C-allele42430.0880.08551340.10.072
P_HWE 0.083640.34670.28080
DIO2(rs225014)0.65740.4836
TT1701750.730.74270810.3480.382
CT56560.240.2371051060.5220.5
CC750.030.02126250.1290.118
T-allele3964060.850.862452680.6090.632
C-allele70660.150.141571580.3910.368
P_HWE 0.37120.83470.167480.2748
TrxR2(rs5748469)0.46890.6574
AA1362090.7160.7491701750.730.742
AC49630.2580.22656560.240.237
CC570.0260.025750.030.021
A-allele3214810.8450.8623964060.850.86
C-allele59770.1550.13870660.150.14
P_HWE 0.81640.39580.37120.8347
Table 6

Genotype and allele frequencies of polymorphisms across selenoprotein genes by serum selenium concentration in Tibetan population.

SNPsControlsKBDControlsKBDTrendHigher groupLower groupHigher groupLower groupTrend
numbernumberFreq.Freq.p-valuenumbernumberFreq.Freq.p-value
GPX1(rs1050450)0.9320.2849
CC1471550.8120.8161741250.7980.839
CT34350.1880.18444240.2020.161
TT00000000
C-allele3283450.9060.9083922740.8990.919
T-allele34350.0940.09244240.1010.081
P_HWE 0.16310.1620.28490.0975
GPX1(rs1800668)0.7010.924
CC1821970.8090.8041732060.7970.811
CT39410.1730.16741400.1890.157
TT470.0180.029380.0140.031
C-allele4034350.8960.8883874520.8920.89
T-allele47550.1040.11247560.1080.11
P_HWE 0.27060.01210.7490.002
GPX1(rs3811699)0.8870.8969
TT2012120.8410.8411852280.8330.848
CT34370.1420.14735360.1580.134
CC430.0170.012250.0090.019
T-allele4364610.9120.9154054920.9120.914
C-allele42430.0880.08539460.0880.086
P_HWE 0.0820.3470.0180.8099
DIO2(rs225014)0.190.6357
TT57940.4250.33763880.3890.351
CT611500.4550.538721390.4440.554
CC16350.1190.12527240.1670.096
T-allele1753380.6530.6061983150.6110.627
C-allele932200.3470.3941265020.3890.373
P_HWE 0.95850.03590.00350.4085
TrxR2(rs5748469)0.4610.6092
AA1362090.7160.7491541910.7480.726
AC49630.2580.22647650.2280.247
CC570.0260.025570.0240.027
A-allele3214810.8450.8623554470.8620.85
C-allele59770.1550.13857790.1380.15
P_HWE 0.81640.39580.53670.606
Table 7

Statistical Power Calculations for a Paired t Test and Their Effect on Desired Sample Size.

iodine(case/control)selenium(case/control)iodine(high/low)selenium(high/low)
α0.050.050.050.05
1-β0.80.80.80.8
n901337356

α, (alpha)the threshold value below which statistical significance will be declared.

1-β, (one minus beta) the statistical power.

n, the sample size.

α, (alpha)the threshold value below which statistical significance will be declared. 1-β, (one minus beta) the statistical power. n, the sample size.

Comparison of the Results of the Genotype Analysis Based on the Higher and Lower Serum Iodine or Selenium Concentration Groups

To further investigate the association of the five SNPs with the serum iodine or selenium concentration, we analyzed the genotype of those in the higher group and lower group of serum iodine or selenium concentration in the Tibetan population (subjects combined the patients and the controls). The mean serum iodine concentration of the combined samples including both cases and controls was 37.33 μg/L. The mean serum iodine concentration of the combined samples including both cases and controls was 37.33 μg/L. The mean serum iodine concentration in the lower group was 24.35 μg/L and 51.64 μg/L in the higher group. The mean serum selenium concentration was 28.65 μg/L. In the lower group, it was 18.18 μg/L, and in the higher group it was 44.40μg/L. The results are presented in the right column of Table 5 and Table 6 for iodine and selenium, respectively. The power calculation results are shown in Table 7. The GPX1 gene (rs1050450) showed a potential significant association with the iodine concentration, with trend p value of 0.02726. However, rs1050450 was not associated with the selenium concentration (trend p value  = 0.2849). These might be because the sample size is two less than the power calculated number size 1337 (Table 7). Other SNPs showed no significant association with either iodine or the selenium concentration.

Discussion

KBD is believed to be a complex disease involving genetic factors, as well as environmental factors such as selenium and iodine deficiency [1]. Based on a candidate gene approach, Xiong et al. reported that SNP rs1050450 in the selenoprotein Gpx1 gene was significantly associated with KBD in a Han Chinese population [21], potentially linked this genetic variant to selenium and iodine deficiency in patients. In China, Tibetans who live in the plateau region are one of the most susceptible populations to KBD. Thus, in this study, we examined the genotype of five selenoprotein SNPs including rs1050450, rs1800668, and rs3811699 in the Gpx1gene, rs225014 in the Dio2 gene, and rs5748569 in the TrxR2 gene in KBD patients and controls in a Tibetan population. Our results provided no support for any one of the five SNPs being significantly associated with KBD in the Tibetan population. However, haplotype analysis of SNPs rs1050450, rs1800668 and rs3811699 in GPX1 gene showed a significant association of KBD. Our previous study indicated that the concentrations of serum selenium and iodine in KBD patients were significantly lower than that of controls living in the same village [23], suggesting that genetic variants may affect selenium and/or iodine metabolism. In this study, by haplotype analysis, we found haplotypes TCC, TTC and TTT generated from three SNPs rs1050450, rs1800668, and rs3811699 of gpx1 gene proved to be significantly associated with KBD and play a protective role from the disease. This is consistent with the fact that supplement of selenium is beneficial for KBD children [13]. In this study, for the first time, we observed that the GPX1 gene rs1050450 is significantly associated with the serum iodine concentration (P trend  = 0.027). The GPX1 gene encodes a member of the glutathione peroxidase family; SNP rs1050450 in this gene is polymorphic at codon 200, resulting in either a proline or a leucine at that position. Previous studies have suggested that the GPX1-200Leu variant has about 10% lower GPX activity than the wild-type enzyme [24] and that the frequency of the Leu allele is strongly associated with the risk of cancer, such as lung cancer, breast cancer, meningioma, and prostate cancer [25]–[29]. In the present study, we observed that the frequency of the Leu allele of rs1050450 is associated with a relatively higher iodine concentration. Iodine is an essential component of the hormones produced by the thyroid gland. Therefore, iodine is essential for mammalian life [30]. In mammals, after iodine is absorbed and distributed in the serum, most of it will be transported by the sodium/iodide symporter (NIS) symporter into the thyrocyte where iodine is oxidated in a reaction catalyzed by the hemoprotein thyroid peroxidase (TPO) and then incorporated into the thyroglobulin molecule (Tg-I) [30]–[32] (Fig. 2). In this reaction, H2O2 is generated by the NADPH-dependent thyroxidase (ThOx) and is required as a substrate by TPO for the iodination in Tg. The thyroid hormones triiodothyronine (T3) and tetraiodothyronine (T4) are then released into the bloodstream. When the iodine supply is sufficient, this H2O2 generation is the limiting step for thyroid hormone synthesis. Therefore, if the KM of TPO for H2O2 is very high, the higher amounts of H2O2 are produced than be consumed by the iodination process [34], the more likely potentially exposing the thyroid gland to free radical damage can be produced. Thus, to prevent organ damage, H2O2, H2O2 should be reduced to H2O immediately after the iodination process. Several selenoproteins participate in the protection of thyrocytes and the prevention of damage to the thyroid gland of H2O2 by catalyzing glutathione and H2O2 to glutathione disulfide and H2O [30]. Selenium-dependent GPX gene is one of the first and most important antioxidant enzymes identified in humans and one of only a few proteins known in higher vertebrates to contain selenocysteine. GPX1 can remove H2O2 from many tissues and cells to decrease oxidative damage. By searching human genes' expression data, we observed that GPX1 is very highly expressed in thyroid tissue (http://www.genecards.org/cgi-bin/carddisp.pl?gene=GPX1&search=GPX1). This suggests that this gene is an important H2O2 remover in the thyroid gland. When iodine is deficient, the thyroid would increase the generation of H2O2 to maintain the balance of thyroid hormone synthesis. Therefore, the gland requires a higher level of GPX activity to clear the H2O2 and prevent H2O2-induced damage. In contrast, when iodine is sufficient, less H2O2 and GPX are needed to maintain the hormone balance. Thus, we suspect that the iodine concentration and GPX1 genetic variant might have undergone adaptive evolution in the distant past.
Figure 2

Iodine and GPXs involved in Thyroid Hormones Biosynthesis.

The serum sodium iodide is transported into the thyrocyte and then iodine is incorporated into the thyroglobulin molecule (Tg) in a reaction catalyzed by the hemoprotein thyroid peroxidase (TPO). In this reaction, H2O2 generated by the NADPH-dependent thyroxidase (ThOx) is required as substrate by TPO for the iodination and coupling of tyrosyl residues in Tg. Then, thyroid hormones triiodothyronine (T3) and tetraiodothyronine (T4) are released into the bloodstream. H2O2 used in this reaction decreases the amount of H2O2 that would otherwise be available for damaging oxidation reactions. Selenium-dependent glutathione peroxidase 1 (GPX 1) and other GPX s remove H2O2 from the tissues, also decreasing oxidative damage. (Modified from: J. Köhrle et al. Selenium, the thyroid, and the endocrine system. Endocrine Reviews, December 2005, 26(7):944–984; Lyn Patrick, ND. Iodine: deficiency and therapeutic considerations. Alternative Medicine Review, 2008, 13(2):116–127).

Iodine and GPXs involved in Thyroid Hormones Biosynthesis.

The serum sodium iodide is transported into the thyrocyte and then iodine is incorporated into the thyroglobulin molecule (Tg) in a reaction catalyzed by the hemoprotein thyroid peroxidase (TPO). In this reaction, H2O2 generated by the NADPH-dependent thyroxidase (ThOx) is required as substrate by TPO for the iodination and coupling of tyrosyl residues in Tg. Then, thyroid hormones triiodothyronine (T3) and tetraiodothyronine (T4) are released into the bloodstream. H2O2 used in this reaction decreases the amount of H2O2 that would otherwise be available for damaging oxidation reactions. Selenium-dependent glutathione peroxidase 1 (GPX 1) and other GPX s remove H2O2 from the tissues, also decreasing oxidative damage. (Modified from: J. Köhrle et al. Selenium, the thyroid, and the endocrine system. Endocrine Reviews, December 2005, 26(7):944–984; Lyn Patrick, ND. Iodine: deficiency and therapeutic considerations. Alternative Medicine Review, 2008, 13(2):116–127). The biosynthesis of selenoproteins is highly regulated by its upstream effectors [33], [34] and by the supply of selenium, which acts as a substrate for the first step in the biosynthesis of Sec-containing proteins. Yet we found no association between the genetic variant Sec-containing coding gene GPX1 and the selenium concentration in this study. This might because the variant of rs1050450 does not affect the yield of GPX, although it does affect the activity of GPX1. As the selenium concentration can affect the mole yield of Sec-containing GPX, it can, therefore, influence the activity of the enzymes. Thus, iodine deficiency increases H2O2 generation, whereas selenium deficiency decreases H2O2 disposal [30]. This results in oxidative cell damage causing chronic inflammation or autoimmune diseases. This linkage may explain why selenium and iodine deficiency are associated with many diseases, such as KBD and other impaired immune function–related disease [14], [32].
  32 in total

1.  Genetic variants in the HLA-DRB1 gene are associated with Kashin-Beck disease in the Tibetan population.

Authors:  Yi Shi; Fang Lu; Xin Liu; Yao Wang; Lulin Huang; Xiaoqi Liu; Wubin Long; Bo Lv; Kun Zhang; Shi Ma; He Lin; Jing Cheng; Bin Zhou; Mei Hu; Jiayun Deng; Jianxin Zhu; Peng Hao; Xiao Yang; Mingcai Zeng; Xiaoquan Wang; Sikui Shen; Zhenglin Yang
Journal:  Arthritis Rheum       Date:  2011-11

2.  Selenium, boron, and germanium deficiency in the etiology of Kashin-Beck disease.

Authors:  X Peng; Z Lingxia; G N Schrauzer; G Xiong
Journal:  Biol Trace Elem Res       Date:  2000-12       Impact factor: 3.738

3.  Effect of fusarochromanone and T-2 toxin on articular chondrocytes in monolayer culture.

Authors:  G C Wright; W F Marasas; L Sokoloff
Journal:  Fundam Appl Toxicol       Date:  1987-10

4.  Selenium deficiency-induced growth retardation is associated with an impaired bone metabolism and osteopenia.

Authors:  R Moreno-Reyes; D Egrise; J Nève; J L Pasteels; A Schoutens
Journal:  J Bone Miner Res       Date:  2001-08       Impact factor: 6.741

5.  Selenium, iodine and fungal contamination in Yulin District (People's Republic of China) endemic for Kashin-Beck disease.

Authors:  W H Zhang; J Neve; J P Xu; J Vanderpas; Z L Wang
Journal:  Int Orthop       Date:  2001       Impact factor: 3.075

6.  Histology of Kashin-Beck lesions.

Authors:  J L Pasteels; F D Liu; M Hinsenkamp; M Rooze; F Mathieu; N Perlmutter
Journal:  Int Orthop       Date:  2001       Impact factor: 3.075

7.  Study on the pathogenic factors of Kashin-Beck disease.

Authors:  A Peng; C Yang; H Rui; H Li
Journal:  J Toxicol Environ Health       Date:  1992-02

8.  Selenium and iodine supplementation of rural Tibetan children affected by Kashin-Beck osteoarthropathy.

Authors:  Rodrigo Moreno-Reyes; Françoise Mathieu; Marleen Boelaert; Françoise Begaux; Carl Suetens; Maria T Rivera; Jean Nève; Noémi Perlmutter; Jean Vanderpas
Journal:  Am J Clin Nutr       Date:  2003-07       Impact factor: 7.045

Review 9.  Selenocysteine: the 21st amino acid.

Authors:  A Böck; K Forchhammer; J Heider; W Leinfelder; G Sawers; B Veprek; F Zinoni
Journal:  Mol Microbiol       Date:  1991-03       Impact factor: 3.501

10.  Mycotoxicological investigations on maize and groundnuts from the endemic area of Mseleni joint disease in Kwazulu.

Authors:  W F Marasas; S J Van Rensburg
Journal:  S Afr Med J       Date:  1986-03-15
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  12 in total

Review 1.  Selenium at the redox interface of the genome, metabolome and exposome.

Authors:  Jolyn Fernandes; Xin Hu; M Ryan Smith; Young-Mi Go; Dean P Jones
Journal:  Free Radic Biol Med       Date:  2018-06-05       Impact factor: 7.376

2.  Exome sequencing identified FGF12 as a novel candidate gene for Kashin-Beck disease.

Authors:  Feng Zhang; Lanlan Dai; Weimin Lin; Wenyu Wang; Xuanzhu Liu; Jianguo Zhang; Tielin Yang; Xiaogang Liu; Hui Shen; Xiangding Chen; Lijun Tan; Qing Tian; Hong-Wen Deng; Xun Xu; Xiong Guo
Journal:  Funct Integr Genomics       Date:  2015-08-20       Impact factor: 3.410

3.  Field synopsis and meta-analyses of genetic epidemiological evidence for Kashin-Beck disease, an endemic osteoarthropathy in China.

Authors:  Lei Yang; Guang-Hui Zhao; Huan Liu; Xi Wang; Xiong Guo; Mikko J Lammi
Journal:  Mol Genet Genomics       Date:  2016-06-02       Impact factor: 3.291

Review 4.  Selenium and chronic diseases: a nutritional genomics perspective.

Authors:  Catherine Méplan
Journal:  Nutrients       Date:  2015-05-15       Impact factor: 5.717

Review 5.  The Type 2 Deiodinase Thr92Ala Polymorphism Is Associated with Worse Glycemic Control in Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Authors:  Xiaowen Zhang; Jie Sun; Wenqing Han; Yaqiu Jiang; Shiqiao Peng; Zhongyan Shan; Weiping Teng
Journal:  J Diabetes Res       Date:  2016-09-29       Impact factor: 4.011

6.  Association of rs1800668 polymorphism in glutathione peroxidase- 1 gene and risk of rheumatoid arthritis in Pakistani population.

Authors:  Shazia Irfan; Asima Rani; Maryam Sameem; Syed Kashif Nawaz; Iram Liaqat; Muhammad Arshad
Journal:  Pak J Med Sci       Date:  2016 Sep-Oct       Impact factor: 1.088

7.  Association study of candidate genes for susceptibility to Kashin-Beck disease in a Tibetan population.

Authors:  Zhengfu Tai; Lulin Huang; Fang Lu; Yi Shi; Shi Ma; Jing Cheng; He Lin; Xin Liu; Yuanfeng Li; Zhenglin Yang
Journal:  BMC Med Genet       Date:  2017-06-26       Impact factor: 2.103

8.  Genome-wide association study identifies COL2A1 locus involved in the hand development failure of Kashin-Beck disease.

Authors:  Jingcan Hao; Wenyu Wang; Yan Wen; Xiao Xiao; Awen He; Cuiyan Wu; Sen Wang; Xiong Guo; Feng Zhang
Journal:  Sci Rep       Date:  2017-01-06       Impact factor: 4.379

Review 9.  Pathway-based network analyses and candidate genes associated with Kashin-Beck disease.

Authors:  Rongqiang Zhang; Hao Guo; Xiaoli Yang; Dandan Zhang; Baorong Li; Zhaofang Li; Yongmin Xiong
Journal:  Medicine (Baltimore)       Date:  2019-05       Impact factor: 1.817

Review 10.  The role of selenium metabolism and selenoproteins in cartilage homeostasis and arthropathies.

Authors:  Donghyun Kang; Jeeyeon Lee; Cuiyan Wu; Xiong Guo; Byeong Jae Lee; Jang-Soo Chun; Jin-Hong Kim
Journal:  Exp Mol Med       Date:  2020-08-13       Impact factor: 8.718

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