Neuroendocrine gene polymorphisms and susceptibility to juvenile idiopathic arthritis

Paediatric Rheumatology/Series Editor: P. Woo

R. P. Donn, A. Farhan, A. Stevans, A. Ramanan, W. E. R. Ollier and W. Thomson The British Paediatric Rheumatology Study Group{dagger}

Arthritis Research Campaign Epidemiology Unit (ARC/EU), Stopford Building, Oxford Road, Manchester M13 9PT, UK

Abstract

Objective. To investigate the involvement of neuroendocrine candidate genes in the aetiopathogenesis of juvenile idiopathic arthritis (JIA).

Methods. Single-nucleotide polymorphisms and intragenic microsatellite markers within five neuroendocrine candidate genes (CRH, CBG, CYP19, ESR1, PRL) were investigated in 463 clinically characterized UK Caucasian JIA patients and a panel of 276 unrelated, healthy UK Caucasian controls.

Results. None of the polymorphisms investigated showed any statistically significant associations with JIA.

Conclusions. The lack of association with polymorphisms of these neuroendocrine genes suggests that they are not involved in susceptibility to JIA.

KEY WORDS: Neuroendocrine, Polymorphisms, Juvenile idiopathic arthritis.

Juvenile idiopathic arthritis (JIA), previously called juvenile chronic arthritis within Europe and juvenile rheumatoid arthritis in the USA, is the commonest chronic arthritic condition of childhood. Overall, JIA is predominantly a female disease, although the gender bias differs considerably between the different International League of Associations for Rheumatology (ILAR) categories of JIA [1]. The commonest presentation, oligoarthritis, affects significantly more girls than boys. Similarly, substantially more girls are affected by polyarthritis [both rheumatoid factor (RF)-positive and RF-negative disease] and by juvenile psoriatic arthritis. In contrast, enthesitis-related arthritis has a male preponderance and systemic arthritis affects males and females equally.

The genetic basis of JIA is complex. Extrapolating from their collection of affected sibling pairs, Glass and Giannini [2] have estimated the coefficient of familial clustering ({lambda}s) for JIA to be 15. Furthermore, the same group have now shown that the proportion of {lambda}s contributed by HLA-DR, the genetic factor most extensively researched in JIA, is approximately 17% [3]. Other HLA loci and non-major histocompatibility complex loci must therefore be involved in susceptibility to JIA. Of these, certain genes may contribute to factors common to all the JIA subgroups, such as chronic inflammation and osteopenia, whilst others influence a more limited phenotype.

Gender and sex hormones are known to exert powerful effects on susceptibility to and the progression of many human and experimental animal models of autoimmune diseases [reviewed in 4]. This is attributed to the direct immunological effects of sex hormones, which impose a clear gender dimorphism on the immune system. Several researchers have used biological assays in an attempt to identify endocrinological disturbances contributing to particular subgroups of juvenile onset arthritis [reviewed in 5]. No consensus has been reached regarding a possible role in JIA for any of the hormones so far studied. The interpretation of these studies is often difficult because the results of endocrinological investigations can be affected by various physiological factors which have not always been controlled for, such as stress and circadian variations in hormone levels. Studying genetic markers overcomes such potential difficulties. Polymorphism of genes of the hypothalamic–pituitary–adrenal (HPA) axis and the hypothalamic–pituitary gonadal (HPG) axis can affect the development of inflammatory and autoimmune conditions [6]. We studied single-nucleotide polymorphisms (SNPs), intragenic microsatellites and an intergenic microsatellite marker for five key genes found within the HPA or HPG axis.

Corticotrophin-releasing hormone (CRH) is the main mediator of cortisol secretion and subsequent anti-inflammatory activity. The sex hormones testosterone and oestradiol both exert their effects on the HPA axis principally by changing the production and secretion of CRH [4]. Corticosteroid-binding globulin (CBG) is the plasma transport protein that regulates the access of glucocorticoid hormones to target cells. Oestrogen synthase (CYP19) is a cytochrome p450 enzyme that catalyses the conversion of C19 androgens to C18 oestrogens. It is therefore critical in maintaining a balance between androgen and oestrogen levels. Oestrogen receptor 1 (ESR1) is both the main receptor for oestrogen and a member of a superfamily of nuclear receptors that transduce extracellular signals into transcriptional responses [7]. Prolactin (PRL), which maps to the extended major histocompatibility complex, is a hormone with potent immunoregulatory capacity [8]. Our approach was to investigate genetic markers within these neuroendocrine genes to determine if they have a role in susceptibility to JIA.

Patients and methods

Blood samples were obtained with written consent from 463 UK Caucasian JIA cases seen by paediatric rheumatologists at 17 UK hospitals and sent to the British Paediatric Rheumatology Group's National Repository for JIA, ARC/EU, Manchester. Ethics committee approval had been obtained for the study (North-West Multi-centre Research Ethics Committee (MREC 99/8/84) and the University of Manchester Committee on the ethics of research on human beings). A clinical data form was completed on every child. All the children were categorized according to the ILAR classification [1]. Patients falling into any one of seven ILAR categories were included in this study. Those children categorized as ‘other arthritis’ were not included. The numbers of males and females in the different categories are shown in Table 1Go. RF-positive disease and antinuclear antibody (ANA) positivity were each determined by at least two positive results, 3 months apart, during the first 6 months of observation. The control panel comprised 276 unrelated, healthy UK Caucasian individuals. Of these, 184 were UK Caucasian blood donors and 92 were UK Caucasian individuals selected from general practitioner registers as part of a population-based study [9].


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TABLE 1.  Numbers of males and female JIA patients in each subgroup

 
Genomic DNA was extracted from all the samples using DNAce MaxiBlood Purification System kits (Bioline, London, UK).

Primer sequences
For the majority of the polymorphisms studied, the primer sequences had been published previously [1015] (Table 2Go). The primers used for the 2942 polymorphism of CRH (reference sequence X67661) were redesigned from those described by Baerwald et al. [16].


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TABLE 2.  Characteristics of the neuroendocrine gene polymorphisms and the methods used to study them

 

Typing of single-nucleotide polymorphisms
Genomic DNA (50 ng) was amplified in a final reaction volume of 25 µl, containing 25 pmol forward and reverse primers, 0.2 nmol deoxynucleotide triphosphates (dNTPs), 10xKCl buffer, 1.5 mM MgCl2 and 0.5 U Taq polymerase (Bioline). The reactions were carried out in 96-well microtitre plates on a Tetrad thermal cycler (MJ Research, Waltham, MA, USA). The polymerase chain reaction (PCR) conditions were as follows: 95°C (5 min) for one cycle, followed by 95°C (1 min), the appropriate annealing temperature (Table 2Go) (1 min), and 72°C (1 min) for 35 cycles. A final cycle of 72°C (5 min) completed the reaction. Amplified product was digested with the appropriate enzyme (Table 2Go) at the correct temperature for optimal enzyme activity. Genotypes were also confirmed by sequencing a selection of samples.

Microsatellite genotyping
Genomic DNA (50 ng) was amplified by PCR in a total reaction volume of 10 µl containing 5 pmol of both the forward and the reverse primer, 4 nmol of each of the four dNTPs, 0.2 U Taq polymerase (Bioline), 1.5 mM MgCl2, 10xKCl buffer and 1 mM betaine. The PCRs were performed in 96-well microtitre plates on Tetrad thermal cyclers. The standard protocol was as follows: denaturation (1 min) at 95°C, primer annealing (1 min) at the appropriate annealing temperature (Table 2Go) and extension for 45 s at 72°C for a total of 40 cycles. A final extension step was conducted at 72°C for 5 min. The forward primers were each prelabelled with 6-FAM, HEX or TET fluorescent dyes. PCR reactions for each marker were performed separately. The markers were then pooled as appropriate and were mixed with Tamra 350 size standard (PE Biosystems, Foster City, CA, USA). Gel electrophoresis was performed on a 0.4 mm 6% polyacrylamide gel on a PE Biosystems 373 DNA sequencer. Gels were run at 1000 V for 4 h. PCR products from four DNA samples of known genotype were included on every gel. Semi-automated genotyping was carried out using Genscan analysis and Genotyper 1.1.1 software (Applied Biosystems, Foster City, CA, USA), and all genotyping was checked manually.

Statistical analysis
SNPs
The distribution of the three possible genotypes for each SNP was first compared between the total JIA case group and controls using the {chi}2 test or Fisher's exact test as appropriate. Comparing each of the JIA subgroups separately with controls for each of the markers of interest would generate a large number of tests and thus increase the possibility of type I error. We therefore adopted a strategy of first examining whether there was evidence of a difference in genotype frequencies between the seven ILAR subgroups studied. Only if evidence for a difference was found (at the 5% significance level) would tests be carried out separately comparing each JIA subgroup with controls. With this conservative strategy, there is a greater chance of failing to detect some associations but the problem of multiple testing is reduced. Differences between the subgroups were assessed using the {chi}2 test on the 7x3 tables; if numbers in some categories were small, Monte Carlo simulation was used to estimate exact P values.

Microsatellite markers
There are too many possible genotypes for each microsatellite marker to adopt the above analytical approach. Instead, allele frequencies of the microsatellite markers were compared between the cases (all JIA cases) and the controls using a global Pearson's {chi}2 test with exact significance levels determined by Monte Carlo simulation (SPSS version 9; SPSS, Chicago, IL, USA). The allele frequencies were also compared between the seven JIA subgroups using the same approach, to identify any differences between subgroups.

The ratio of males to females is known to differ between the JIA categories. To determine if any of the neuroendocrine markers we tested for were associated with gender, the frequencies in male and female patients were compared within each individual ILAR-coded category.

For both the SNP and microsatellite results, Bonferroni's correction was applied when any results were found to be positive at the nominal 5% significance level.

Results

For each of the markers investigated there was no evidence of departure from Hardy–Weinberg equilibrium in controls.

No differences between the genotypes for the SNP at position 2942 of the CRH gene were found between the total JIA patient group compared with the controls (P=1.0) (Table 3Go). In addition, comparison between the JIA subgroups showed no differences (Table 4Go). Similarly, the results for CBG and for the SNPs within ESR1 and PRL were non-significant when the genotype frequencies were compared between the total JIA cases and controls (Table 3Go) and between the JIA subgroups (Table 4Go).


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TABLE 3.  Distribution of genotypes for SNPs within CRH, ESR1 and PRL genes in the total JIA patient group compared with controls: n (%)

 

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TABLE 4.  Distribution of genotypes for polymorphisms within CRH, CBG, ESR1 and PRL in the different JIA subgroups: n (%)

 
Of the microsatellite markers studied, the ESR1 and CRH loci were both highly polymorphic, 19 and 12 alleles being observed respectively, although several of these were only seen at low frequency (Table 5Go). Seven alleles of CYP19 were observed. Only two alleles of the tetranucleotide repeat within CBG were seen. This allowed the CBG locus to be analysed as a biallelic polymorphism (data included in Table 4Go). We named the alleles 86 and 90 after their base-pair sizes.


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TABLE 5.  Microsatellite allele frequencies for CRH, CBG, ESR1 and CYP19 in the total JIA patient group compared with controls: 2n (%)

 
No significant differences in ESR1, CRH or CYP19 microsatellite allele frequencies were seen between the JIA cases and the controls (Table 5Go). Additionally, no differences were seen between the JIA subgroups for the ESR1 or CYP19 microsatellite alleles (ESR1 (2n=842); Puncorr=0.07; CYP19 (2n=670); Puncorr=0.48. Comparison between the JIA patients for the CRH microsatellite alleles (2n=884) did suggest differences between the subgroups (Puncorr=0.04); however, this was non-significant when Bonferroni correction for the number of markers tested (n=7) was applied (Pcorr=0.28).

For each of the polymorphisms investigated, frequencies were compared between the male and female JIA patients within each of the seven JIA subgroups. No statistically significant differences were found for any locus.

Discussion

The genetic component of JIA is complex [2]. In a clinically heterogeneous condition such as JIA it is reasonable to assume that certain genetic factors will contribute to susceptibility to features common to all the disease subgroups, such as chronic inflammation or osteopenia [17, 18]. Other genes will determine the precise phenotypic form that is expressed. JIA is predominately a female disease, but subgroups differ in their gender basis.

We investigated five neuroendocrine genes in JIA patients and controls in an association-based study. The genes selected were ones that could be contributing to the general processes of inflammation or to the low bone mineral density seen in all JIA patients, and/or be involved in influencing the difference in expression between females and males, which varies among subgroups. Even in a large series of well-characterized JIA patients, as included in this study, the numbers in the less clinically frequent subgroups are small. This may account for the lack of any gender-specific associations being found within the different JIA clinical groups.

The relationship between the HPA axis, the HPG axis and the immune system is only now beginning to be understood [6]. CRH is the principal modulator of the production of endogenous glucocorticoids, primarily cortisol. Broadly, cortisol stimulates a TH2 as opposed to a TH1 cytokine-type immune response, enhancing humoral and suppressing cellular immunity. Failure to mount an adequate cortisol response to immune challenge can result in unrestrained amplification of the immune response and subsequent autoimmune disease [19]. The sex hormones testosterone and oestradiol exert their effects on the HPA axis mainly by changing the production and secretion of CRH. Very few studies have attempted to measure cortisol secretion in patients with juvenile arthritis [2022]. Chikanza [22] reports observing normal to low levels of cortisol in patients with active arthritis. This was despite a concomitant increase in serum levels of the cytokines interleukin (IL)-6, IL-1ß and tumour necrosis factor {alpha}, which activate the HPA axis. He concludes that the cortisol levels were subnormal. We found no association with either a polymorphic microsatellite marker within CRH or with the 2942 SNP. This is in contrast to recent reports of potential linkage and association with the CRH locus in adult rheumatoid arthritis (RA) [23]. Similarly, we found no significant association between JIA and CBG.

CYP19 is responsible for the conversion of certain androgens to oestrogens. An alteration in the balance between circulating androgens and oestrogens could have significant effects on cortisol production and the subsequent immune response. Furthermore, Khalkhali-Ellis et al. [24] have observed an association between low androgen level and disease in children affected by arthritis. The lowest androgen levels were found in children with disease extending into their adult life. We studied the same polymorphism of CYP19 as that reported by John et al. [25] to be linked with RA. No association was seen between CYP19 and JIA. Specifically, no differences in the microsatellite allele frequencies were found between male and female RF-positive polyarticular JIA patients, the subgroup most like adult RA clinically and immunogenetically [male RF-positive polyarticular JIA (2n=2) vs female RF-positive polyarticular JIA (2n=48), Puncorr=1.0]. However, there was only one male affected in our series of patients. There was also no association seen when the frequencies of the CYP19 alleles were compared between the whole RF-positive polyarticular JIA patient group and the control panel (Puncorr=0.25).

Osteopenia, or low bone mineral content for age, is recognized as an important antecedent to juvenile arthritis [26, 27]. It affects all the JIA subgroups [27] and has been shown to develop independently of corticosteroid therapy [28]. Work on aromatase-deficient mice implies that oestrogens are important for attaining peak bone mass in both males and females [29]. Polymorphisms of the ESR1 gene could affect the bioefficiency of oestrogen. This could have immunological consequences, as discussed above, and may also have an effect on bone mineral content in the growing child. We used both a microsatellite marker and an SNP within the ESR1 gene. Each of these has been found previously to have associations with adult RA [14, 30] and also with osteoporosis, although not consistently in all populations studied [3134]. We found no associations with either polymorphic marker of ESR1 and JIA. We have not collected bone mineral content data on the JIA cases included in this study. Therefore, we are able only to make the broad observation that these ESR1 polymorphisms are not contributing to JIA, either in a general or a subgroup-specific way.

Finally, we studied a recently identified polymorphism in the lymphoid promoter of the PRL gene. The functional relevance of this polymorphism has been described by Stevens et al., who also observed an association with adult systemic lupus erythematosus [15]. Several serological studies of PRL and juvenile arthritis have been carried out [reviewed in reference 5]. Bravo et al. [35] found raised levels of PRL in male patients with juvenile ankylosing spondylitis. This raised level of PRL also correlated with disease activity. In addition, a proportion of these patients showed a good clinical response when the PRL inhibitor bromocriptine was given as an adjuvant therapy. McMurray et al. [36] also report an association between PRL and juvenile arthritis. This work found the mean serum PRL concentration to be significantly higher in ANA-positive patients. Unlike other hormones, PRL maintains a physiological concentration in the blood that is largely constant up to puberty. This would imply that the elevations in PRL concentrations observed were disease-specific. However, we did not find an association of the -1149 PRL polymorphism with JIA, even when the patients were divided according to the presence or absence of ANA [ANA-negative JIA (n=281) vs ANA-positive JIA (n=123), Puncorr=0.26].

In conclusion, we studied a combination of microsatellites and SNPs within neuroendocrine genes not previously investigated in JIA. No significant associations were observed. The polymorphisms we investigated within the CRH, CBG, CYP19, ESR1 and PRL genes do not appear to have a role in susceptibility to JIA.

Acknowledgments

We thank Emma Shelley and Lynne Pepper for excellent technical assistance. We are also indebted to the children who donated blood samples to the British Paediatric Rheumatology Group National Repository. This work had core grant support from the Arthritis Research Campaign of Great Britain.

 Contributors to The British Paediatric Rheumatology Study Group: M. Abinun, M. Becker, A. Bell, A. Craft, E. Crawley, J. David, H. Foster, J. Gardener-Medwin, J. Griffin, A. Hall, M. Hall, A. Herrick, P. Hollingworth, L. Holt, S. Jones, G. Pountain, C. Ryder, T. Southwood, I. Stewart, H. Venning, L. Wedderburn, P. Woo, S. Wyatt.

Notes

{dagger}Contributors to The British Paediatric Rheumatology Study Group are listed in the Acknowledgements. Back

Correspondence to: R. P. Donn. Back

References

  1. Petty RE, Southwood TR, Baum J et al. Revision of the Proposed Classification Criteria for Juvenile Idiopathic Arthritis, Durban, 1997. J Rheumatol1998;25:1991–4.[Medline]
  2. Glass DN, Giannini EH. Juvenile rheumatoid arthritis as a complex genetic trait. Arthritis Rheum1999;42:2261–8.[ISI][Medline]
  3. Prahalad S, Ryan MH, Shear ES, Thompson SD, Giannini EH, Glass DN. Juvenile rheumatoid arthritis: linkage to HLA demonstrated by allele sharing in affected sibpairs. Arthritis Rheum2000;43:2335–8.[ISI][Medline]
  4. Da Silva JA. Sex hormones and glucocorticoids: interactions with the immune system. Ann NY Acad Sci1999;876:102–17.[Abstract/Free Full Text]
  5. Neeck G, Michels H. Endocrine aspects of paediatric rheumatic diseases. Bailliere's Clin Rheumatol1996;10:349–63.[ISI][Medline]
  6. Straub RH, Cutolo M. Involvement of the hypothalamic– pituitary–adrenal/gonadal axis and the peripheral nervous system in rheumatoid arthritis: viewpoint based on a systemic pathogenetic role. Arthritis Rheum2001;44:493–507.[ISI][Medline]
  7. Mangelsdorf DJ, Thummel C, Beato M et al. The nuclear receptor superfamily: the second decade. Cell1995;83:835–9.[ISI][Medline]
  8. Walker SE, Jacobson JD. Roles of prolactin and gonadotropin-releasing hormone in rheumatic diseases. Rheum Dis Clin North Am2000;26:713–36.[ISI][Medline]
  9. Thomson W, Harrison B, Ollier B et al. Quantifying the exact role of HLA-DRB1 alleles in susceptibility to inflammatory polyarthritis: results from a large, population-based study. Arthritis Rheum1999;42:757–62.[ISI][Medline]
  10. Gu J, Sadler L, Daiger S, Wells D, Wagner M. Dinucleotide repeat polymorphism at the CRH gene [abstract]. Human Mol Genet1993;2:85.[ISI][Medline]
  11. Byth BC, Billingsley GD, Cox DW. Physical and genetic mapping of the serpin gene cluster at 14q32.1: allelic association and a unique haplotype associated with {alpha}1-antitrypsin deficiency. Am J Hum Genet1994;55:126–33.[ISI][Medline]
  12. Polymeropoulos MH, Xiao H, Rath DS, Merril CR. Tetranucleotide repeat polymorphism at the human aromatase cytochrome P-450 gene (CYP19). Nucleic Acids Res1991;19:195.
  13. Castagnoli A, Maestri I, Bernardi F, Del Senno L. PvuII RFLP inside the human estrogen receptor gene. Nucleic Acids Res1987;15:866.[ISI][Medline]
  14. Takagi H, Ishiguro N, Iwata H, Kanamono T. Genetic association between rheumatoid arthritis and estrogen receptor microsatellite polymorphism. J Rheumatol2000;27:1638–42.[ISI][Medline]
  15. Stevens A, Ray D, Alansari A et al. Characterisation of a prolactin gene polymorphism and its association with systemic lupus erythematosus. Arthritis Rheum2001;44:2358–66.[ISI][Medline]
  16. Baerwald CGO, Panayi GS, Lanchbury JS. Corticotropin releasing hormone promoter region polymorphisms in rheumatoid arthritis. J Rheumatol1997;24:215–6.[ISI][Medline]
  17. Wedderburn LR, Woo P. Type 1 and type 2 immune responses in children: their relevance in juvenile arthritis. Springer Semin Immunopathol1999;21:361–74.[ISI][Medline]
  18. Cassidy JT. Osteopenia and osteoporosis in children. Clin Exp Rheumatol1999;17:245–50.[ISI][Medline]
  19. Elenkov IJ, Webster EL, Torpy DJ, Chrousos GP. Stress, corticotropin-releasing hormone, glucocorticoids, and the immune inflammatory response: acute and chronic effects. Ann NY Acad Sci1999;876:1–11.[Abstract/Free Full Text]
  20. Laaksonen AL, Sunell JE, Westeren H, Mulder J. Adrenocortical function in children with juvenile rheumatoid arthritis and other connective tissue disorders. Scand J Rheumatol1974;3:137–44.[ISI][Medline]
  21. Tsvetkova V. Daily fluctuations in the plasma cortisol level of children with rheumatoid arthritis before and after treatment with tetracosactrin (‘Cortrosyn Depot’) and corticosteroid hormones. Curr Med Res Opin1977;4:477–84.[ISI][Medline]
  22. Chikanza IC. Neuroendocrine immune features of pediatric inflammatory rheumatic diseases. Ann NY Acad Sci1999;876:71–80.[Abstract/Free Full Text]
  23. Fife MS, Fisher SA, John S et al. Multipoint linkage analysis of a candidate gene locus in rheumatoid arthritis demonstrates significant evidence of linkage and association with the corticotropin-releasing hormone genomic region. Arthritis Rheum2000;43:1673–8.[ISI][Medline]
  24. Khalkhali-Ellis Z, Moore TL, Hendrix MJC. Reduced levels of testosterone and dehydro-epiandrosterone sulphate in the serum and synovial fluid of juvenile rheumatoid arthritis patients correlate with disease severity. Clin Exp Rheumatol1998;16:753–6.[ISI][Medline]
  25. John S, Myerscough A, Eyre S et al. Linkage of a marker in intron D of the estrogen synthase locus to rheumatoid arthritis. Arthritis Rheum1999;42:1617–20.[ISI][Medline]
  26. Rabinovich CE. Bone mineral status in juvenile rheumatoid arthritis. J Rheumatol2000;27:34–7.[ISI][Medline]
  27. Cassidy JT, Hillman LS. Abnormalities in skeletal growth in children with juvenile rheumatoid arthritis. Rheum Dis Clin North Am1997;23:499–522.[ISI][Medline]
  28. Henderson CJ, Specker BL, Sierra RI, Campaigne BN, Lovell DJ. Total-body bone mineral content in non-corticosteroid-treated postpubertal females with juvenile rheumatoid arthritis. Arthritis Rheum2000;43:531–40.[ISI][Medline]
  29. Oz O, Zerwekh JE, Fisher C et al. Bone has a sexually dimorphic response to aromatase deficiency. J Bone Miner Res2000;15:507–14.[ISI][Medline]
  30. Ushiyama T, Mori K, Inoue K, Huang J, Nishioka J, Hukuda S. Association of oestrogen receptor gene polymorphisms with age at onset of rheumatoid arthritis. Ann Rheum Dis1999;58:7–10.[Abstract/Free Full Text]
  31. Bacherini L, Gannari L, Masi L et al. Evidence of a linkage disequilibrium between polymorphisms of the human estrogen receptor alpha gene and their relationship to bone mass variation in postmenopausal Italian women. Hum Mol Genet2000;9:2043–50.[Abstract/Free Full Text]
  32. Salmen T, Heikkinen AM, Mahonen A, Kroger H, Komulainen M, Saarikoski S. Early postmenopausal bone loss is associated with PvuII estrogen receptor polymorphism in Finnish women: effect of hormone replacement therapy. J Bone Miner Res2000;15:315–21.[ISI][Medline]
  33. Bagger YZ, Jorgensen HL, Heegaard AM, Bayer L, Hansen L, Hassager C. No major effect of estrogen receptor gene polymorphisms on bone mineral density or bone loss in postmenopausal Danish women. Bone2000;26:111–6.[ISI][Medline]
  34. Aerssens J, Dequeker J, Peeters J, Breemans S, Broos P, Boonen S. Polymorphisms of the VDR, ER and COLIA1 genes and osteoporotic hip fracture in elderly postmenopausal women. Osteoporosis Int2000;11:583–91.[ISI][Medline]
  35. Bravo G, Zazueta B, Felix A. Juvenile ankylosing spondylitis. Direct relationship between hyperprolactinemia and interleukin 6 [abstract]. Arthritis Rheum1994;37(Suppl.):S428.
  36. McMurray RW, Allen SH, Hickman-Pepmuller P, Keisler D, Cassidy JT. Elevated serum prolactin levels in children with juvenile rheumatoid arthritis and antinuclear antibody seropositivity. J Rheumatol1995;22:1577–80.[ISI][Medline]
Submitted 23 August 2001; Accepted 28 February 2002