• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arthritis Rheum. Author manuscript; available in PMC Aug 20, 2009.
Published in final edited form as:
PMCID: PMC2729701
NIHMSID: NIHMS117606

Age- and Sex-Related Patterns of Serum Interferon-α Activity in Lupus Families

Abstract

Objective

Interferon-α (IFNα) levels are elevated in many patients with systemic lupus erythematosus (SLE) and may play a primary role in its pathogenesis. The purpose of this study was to determine whether serum IFNα activity in SLE patients and their healthy first-degree relatives is highest in early adulthood, when the incidence of SLE is greatest.

Methods

Serum samples from 315 SLE patients, 359 healthy first-degree relatives, and 141 healthy unrelated donors were measured for IFNα activity using a functional reporter cell assay. IFNα activity was analyzed in relation to age, and subgroups with high levels of IFNα activity were identified within the large data sets using a Mann-Whitney sliding window segmentation algorithm. The significance of each subgrouping was ranked by Kruskal-Wallis testing.

Results

Age was inversely correlated with IFNα activity in female SLE patients (r = −0.20, P = 0.001) as well as their healthy female first-degree relatives (r = −0.16, P = 0.02). In male patients and their healthy male first-degree relatives, there was no significant overall correlation between age and serum IFNα activity. The segmentation algorithm revealed significantly increased IFNα activity between the ages of 12 and 22 years in female SLE patients and between the ages of 16 and 29 years in male SLE patients. Both male and female healthy first-degree relatives had significantly decreased IFNα activity after the age of 50 years.

Conclusion

Serum IFNα activity is higher in younger individuals in the SLE family cohorts, and this tendency is accentuated in affected individuals. This age-related pattern of IFNα activity may contribute to the increased incidence of SLE in early adulthood, and interestingly, males and females had similar age-related patterns of IFNα activity.

Systemic lupus erythematosus (SLE) is a prototype systemic autoimmune disease that is characterized by a disease incidence of 9:1 in females versus males (1). Peak disease incidence in women occurs during the early reproductive years (ages 20–30 years), and it may be later in men (ages 40–50 years) (2). The large sex differential and peak incidence rates in SLE hold great promise for understanding the pathogenesis of this disease. Current theories about the observed patterns of SLE incidence include the influence of female sex hormones (3), possible protection provided by male hormones (4), aberrant inactivation of the X chromosome or other X chromosome influences (5), or microchimerism in women who have been pregnant (6). While these hypotheses are all plausible and each is supported by published data, it seems likely that multiple factors will contribute and that other as yet undiscovered factors may be important.

Our group and others (7,8) have shown that SLE patients exhibit coordinate overexpression of interferon-α (IFNα)–induced genes in their peripheral blood mononuclear cells (PBMCs), as compared with PBMCs from healthy individuals and from patients with other inflammatory diseases, such as rheumatoid arthritis. Increased IFNα-induced gene expression correlates with particular autoantibody profiles and disease phenotypes in SLE patients (9,10). Additionally, our group has demonstrated familial aggregation of high levels of serum IFNα activity in SLE families, suggesting that high serum IFNα activity is a heritable risk factor for SLE (11). In vitro studies have shown that PBMCs from healthy female subjects produce much more IFNα after stimulation through Toll-like receptor 7 than do PBMCs from healthy male subjects (12). Collectively, these data indicate that IFNα activity is a quantitative trait with high relevance for the immunopathogenesis of SLE.

Given that the peak time frame for lupus onset in women is after menarche and during the prime reproductive years, we hypothesized that IFNα activity would be highest in female SLE patients during the reproductive years, corresponding to the life interval characterized by elevated levels of female sex hormones. Moreover, we predicted that IFNα activity would be greater in females than in males. In view of our recent documentation of increased serum IFNα activity in healthy first-degree relatives of lupus patients (11), we further anticipated that we would see a similar pattern of increased IFNα levels in healthy younger female first-degree relatives from lupus families. Our data demonstrated significantly higher IFNα activity during the ages corresponding to the period of typical onset of SLE. However, the skewing of disease toward females remains unexplained, since IFNα activity was not preferentially elevated in female patients or their healthy female first-degree relatives as compared with males.

Patients and Methods

Patients and samples

Serum and plasma samples were obtained from the Hospital for Special Surgery (HSS) Lupus Family Registry, the HSS Lupus Registry, and the Lupus Family Registry and Repository (LFRR) at the Oklahoma Medical Research Foundation. A total of 325 samples from the HSS registries were studied, including 160 SLE patients and 115 healthy first-degree relatives. A total of 431 samples from the LFRR were studied, including 155 SLE patients and 244 healthy first-degree relatives. Control samples from 141 healthy unrelated subjects (98 women and 43 men) were obtained commercially from healthy blood donors (n = 59), as well as from unrelated individuals who had donated to the 2 registries as control subjects (50 from the HSS registries and 32 from the LFRR). Both registries and the healthy donor cohort contain samples from individuals of diverse self-reported ancestries, and self-reported ancestral backgrounds are represented in similar proportions in the family cohorts and healthy donors. This study was approved by the institutional review boards at both institutions, and informed consent was obtained from all subjects in the study.

Stimulation of reporter cells

Enzyme-linked immunosorbent assay (ELISA) methods for the detection of IFNα in human serum have been complicated by their poor sensitivity. We have developed and validated a sensitive and reproducible bioassay for detecting serum IFNα activity (11,13). In this assay, reporter cells are used to measure the ability of patient sera to cause IFN-induced gene expression. The assay is thus able to detect total IFNα activity and may provide a better representation of in vivo conditions than ELISAs.

Briefly, the reporter cells used in our assay (WISH cells) were an epithelial-derived cell line (no. CCL-25; American Type Culture Collection, Rockville, MD) that is highly responsive to IFNα. Cells were cultured in minimum essential medium (Gibco, Grand Island, NY) with Earle's salts, 10% fetal bovine serum, 10 mM HEPES buffer, 2 mM l-glutamine, 100 units/ml of penicillin, and 100 μg/ml of streptomycin. WISH cells were plated in 96-well culture plates at a density of 5 × 105/ml and incubated with 50% patient plasma or serum for 6 hours. Recombinant IFNα was used as a positive control, and healthy sera and culture media were used as negative controls. After 6 hours, the cells were lysed.

The ability of sera to cause IFN-induced gene expression was largely abrogated by the addition of monoclonal anti-IFNα antibody, confirming that IFNα was the major active type I IFN causing the IFN-induced gene expression (11). In a set of samples that showed low IFNα activity, the addition of recombinant IFNα to the sample resulted in IFNα-induced gene expression proportional to the amount of IFNα added, excluding any frequent significant endogenous inhibitors of IFNα in the samples (11). Therefore, the results of the assay are expressed as IFNα activity because the anti-IFNα antibody blocked the majority of type I IFN–induced gene expression in the reporter cells in the subset of samples studied and recombinant IFNα recapitulated the expected type I IFN–induced gene expression in the reporter cells in a subset of samples with low IFNα activity. Further details on the validation of the assay are described elsewhere (11,13).

Purification of total cellular messenger RNA (mRNA) and synthesis of complementary DNA (cDNA)

Total cellular mRNA was purified from the WISH cell lysates using the Qiagen Turbocapture RNA purification kit (Qiagen, Chatsworth, CA) according to the manufacturer's protocol. The cDNA was produced from the mRNA using the Invitrogen oligo(dT) primer and Superscript III reverse transcriptase system (Invitrogen, Carlsbad, CA).

Real-time polymerase chain reaction (PCR) quantification of mRNA-derived cDNA

Ten microliters of a 1:40 dilution of the cDNA was quantified using real-time PCR with the Bio-Rad SYBR Green fluorophore system (Bio-Rad, Hercules, CA). Forward and reverse primers for the genes encoding myxovirus resistance 1 (MX-1), RNA-dependent protein kinase (PKR), and IFN-induced protein with tetratricopeptide repeats 1 (IFIT-1), which are known to be highly and specifically induced by IFNα (8), were used in the reaction: for MX1, 5′-TACCAGGACTACGAGATTG-3′ (forward) and 5′-TGCCAGGAAGGTCTATTAG-3′ (reverse); for PKR, 5′-CTTCCATCTGACTCAGGTTT-3′ (forward) and 5′-TGCTTCTGACGGTATGTATTA-3′ (reverse); and for IFIT1, 5′-CTCCTTGGGTTCGTCTATAAATTG-3′ (forward) and 5′-AGTCAGCAGCCAGTCTCAG-3′ (reverse). The housekeeping gene GAPDH was also amplified to control for background gene expression: 5′-CAACGGATTTGGTCGTATT-3′ (forward) and 5′-GATGGCAACAATATCCACTT-3′ (reverse). Each sample and control was run in duplicate. Melt curves were analyzed to ensure the specificity of the amplified product, and standard curves were generated for each PCR experiment.

Real-time PCR data analysis

The amount of PCR product from the IFNα-induced gene was normalized to the amount of product for the housekeeping gene GAPDH in the same sample. The relative expression of each of the 3 tested IFN-induced genes was calculated as the fold increase compared with its expression in WISH cells cultured with medium alone. Healthy unrelated donor sera were tested in the WISH assay to establish a normal value for IFNα activity, and the mean and SD values for the relative expression of the IFNα-induced gene induced by healthy donor sera in the WISH assay were calculated. The ability of patient and family member serum samples to cause IFN-induced gene expression in the reporter cells was then compared with the mean and SD induced by healthy unrelated donor sera. For each gene, the number of SDs of relative expression above that in healthy donors was calculated. This value was used to quantify IFNα activity instead of raw relative expression data because some genes were more highly induced than others, resulting in the more highly inducible genes being overrepresented in aggregate relative expression data.

Statistical analysis

Spearman's correlation coefficient r was used for correlations between age and serum IFNα activity. The data did not fit well with a monotone function such as Spearman's r, as evidenced by low r values despite significant P values (14). For this reason, a Mann-Whitney nonparametric sliding window technique was used to analyze serum IFNα activity data, which was arrayed by age in each cohort, to detect significant subgroups within the data that would not be well captured by Spearman's r. MatLab version 7.0 software (MathWorks, Natick, MA) was used to implement the sliding window.

The specifics of this segmentation algorithm are as follows: 1) IFNα activity data points were ordered by the age of the subject (1 data point for each subject), and subjects with the same age were placed in the same position in the sequence. 2) A sliding window using the Mann-Whitney nonparametric t-test was then moved through the data sequence from beginning to end to detect local changes in the data. Data segments ≥5 years in size with a P value of ≤0.05 as compared with the surrounding data were recorded. Data segments detected in this way represented an age range in the IFNα activity data, and change points were the ages that formed the boundaries of these segments. 3) All nonredundant combinations of data segments were generated. The Mann-Whitney t-test was then used to retest each boundary or change point in the data segmentation, and any change points having a P value of ≥0.05 were removed. 4) Kruskal-Wallis multivariate analysis was used to rank each segmentation of the data, resulting in a P value for the hypothesis that at least 1 of the segments has a median that is different from that of the other segments. 5) An expected number of change points could be estimated with the following equation, using the inverse of the Kruskal-Wallis P value as a likelihood ratio:

Expected number of change points=CPcpaαcp[KW(a)]1CPaαcp[KW(a)]1

where KW(a) represents the Kruskal-Wallis P value for segmentation a, CP represents the number of change points, and αcp represents the set of segmentations with cp change points. 6) The highest ranked segmentation of the data by Kruskal-Wallis analysis with the expected number of change points was then chosen as the best-fit segmentation of the data.

Results

Inverse correlation between IFNα activity and age in female SLE patients and healthy female first-degree relatives of SLE patients

Serum IFNα activity in female SLE patients was inversely correlated with age (Spearman's r = −0.20, P = 0.001). Interestingly, healthy female first-degree relatives of the SLE patients also demonstrated an inverse correlation between IFNα activity and age (Spearman's r = −0.16, P = 0.02). Healthy unrelated female donors did not show an overall correlation between age and serum IFNα activity; however, 6 of the 9 high IFNα activity outliers whose values were ≥2 SD above the group mean were between the ages of 20 and 33 years, and the other 3 outliers were between the ages of 34 and 50 years. The correlation coefficients and P values for these analyses are summarized in Table 1.

Table 1
Correlation between age and serum interferon-α activity in systemic lupus erythematosus (SLE) patients, their families, and unrelated healthy donors, by sex

No overall correlation between age and serum IFNα activity in males

Male SLE patients, healthy male first-degree relatives, and healthy unrelated male donors did not show any significant overall correlations between age and IFNα expression (Table 1). Many of the younger male SLE patients had higher serum IFNα activity than the older male patients; however, the low number of male SLE patients was statistically limiting. There was a nonsignificant trend toward an inverse correlation between age and serum IFNα activity in the healthy male first-degree relatives.

Results of Mann-Whitney segmentation analysis

The correlation data did not fit a monotone function well, as evidenced by the low r values despite significant P values in some data sets (14). We therefore used a Mann-Whitney sliding window segmentation algorithm to search for significant age-related subgroupings within the IFNα data. The output of the segmentation algorithm is shown in Table 2, with individual data segments ranked by Kruskal-Wallis testing. There were a number of possible significant segmentations of the female SLE patient data, with the most significant high IFNα activity segment from age 12 to age 22 years. Although the male SLE patient data set was much smaller, IFNα activity was significantly higher in the data segment between the ages of 16 and 29 years. The single significant change point for male and female healthy first-degree relatives was very similar—age 48 for women and age 46 for men—with the younger relatives having higher serum IFNα activity. The data segmentations described above are illustrated in the data segmentation plot shown in Figure 1. No significant subgroups were found in male or female healthy unrelated donors.

Figure 1
Graphic representation of the best-fit segmentations of serum interferon-α (IFNα) activity data stratified by age in the female and male systemic lupus erythematosus (SLE) patients, their female and male healthy first-degree relatives, ...
Table 2
Output of the Mann-Whitney sliding window segmentation algorithm, with individual data segments ranked by Kruskal-Wallis testing*

Raw serum IFNα activity data stratified by change points for each of the study populations is shown in Figure 2. Wide variance was typical in the data sets, and the data were non-normally distributed; therefore, the nonparametric Mann-Whitney t-test was used to determine significance. Serum IFNα activity is a complex trait with a number of influences (11); so, as would be expected, the influence of age only partly accounts for the variance observed in the data sets. Nonparametric testing is robust with this type of data, and all of the differences by age groups illustrated were significant.

Figure 2
Serum interferon-α (IFNα) activity data stratified by individual change points (according to age) in female and male systemic lupus erythematosus (SLE) patients and their female and male healthy first-degree relatives. The age groupings ...

Serum IFNα activity in males as compared with females

There were no significant quantitative differences in IFNα activity between male and female SLE patients when the data were analyzed for the group of all male patients versus the group of all female patients (Figure 3). Interestingly, the peak age range for high IFNα activity in male patients detected by the sliding window analysis (ages 16–29 years) showed a trend toward being later than that in female patients (ages 12–22 years). This difference was not statistically significant, however, being limited by the smaller number of male patients analyzed. There were no significant differences in serum IFNα activity between male and female healthy first-degree relatives or between male and female healthy unrelated donors (Figure 3). Both male and female SLE patients had significantly higher IFNα activity than did the male or female first-degree relatives, and both male and female first-degree relatives had higher serum IFNα activity than did the male or female healthy unrelated donors (P < 0.05 for all comparisons, by Mann-Whitney t-test).

Figure 3
Serum interferon-α activity stratified by sex in systemic lupus erythematosus (SLE) patients, their healthy first-degree relatives, and in healthy unrelated donors. Values are the median and interquartile range. P values were determined by Mann-Whitney ...

Discussion

Age-related patterns of serum IFNα activity were present in our SLE family cohort, with the highest levels being found during the prime reproductive years, coinciding with the peak incidence of SLE. Interestingly, there were no significant differences in serum IFNα activity between males and females. The ratio of female to male SLE patients in the present study (85% female) is similar to that in general populations of SLE patients. While the smaller number of male SLE patients in the study may limit the statistical power to detect differences between male and female patients, it is interesting that the male healthy first-degree relatives shared a similar age-related IFNα activity pattern with female healthy first-degree relatives.

High levels of serum IFNα activity have been associated with higher levels of disease activity in SLE patients (9,10). A recent study showed an inverse correlation between the adjusted mean scores on the Systemic Lupus Erythematosus Disease Activity Index 2000 and age in female SLE patients, which was independent of menopause status (15). This is similar to the inverse correlation between age and serum IFNα activity in female SLE patients and their healthy female first-degree relatives in the present study. While it is not clear whether higher serum IFNα activity seen in young female SLE patients is a cause or a result of disease activity, the fact that healthy female first-degree relatives showed a similar inverse correlation between age and serum IFNα activity suggests that high serum IFNα activity could be a more primary event.

In previous studies, we demonstrated familial clustering of high serum IFNα activity in SLE patients and their healthy first-degree relatives, suggesting that high serum IFNα activity is a heritable risk factor for SLE (11). In the present study, the pattern of higher IFNα activity earlier in life was both magnified and accelerated in the SLE patients as compared with their healthy first-degree relatives. This suggests the contribution of background SLE-related factors, such as disease activity, to the phenomenon, or possibly, it suggests that a greater number of genetic elements are acting coordinately to predispose to high IFNα activity in the SLE patients as compared with their healthy first-degree relatives. In the present study, the age group with the highest IFNα activity in male SLE patients (ages 16–29 years) was slightly older than that with the highest IFNα activity in female SLE patients (ages 12–22 years). While this difference was not statistically significant, if the pattern were robust with greater numbers of male patients, it could potentially be a cause of the later disease onset reported in males with SLE (2).

Serum IFNα activity was lower in the groups ages 50 years and older, both in healthy female first-degree relatives and in female SLE patients, which might suggest a hormonal influence due to menopause. However, in the female SLE patients, the change point at age 50 years was not as highly significant as other change points at younger ages. Earlier menopause in the SLE patients, due to cytotoxic therapy or SLE disease, is possible (16); however, data regarding menopause status are not available in the registries. Studies of other cytokines, such as IFNγ, have not shown an association with sex hormone levels in SLE (17), and in the study of age versus disease activity (15), there was no clear change in SLE disease activity at menopause despite an overall negative correlation between age and disease activity. In the present study, levels of serum IFNα activity were similar overall between male and female SLE patients as well as between male and female healthy first-degree relatives. The male healthy first-degree relatives also had significantly lower serum IFNα activity after the age of 46 years, suggesting that sex-independent factors may contribute to the change point in serum IFNα activity near the age 50 years that was observed in our data sets.

Our study design was cross sectional; however, the number of subjects was large and the patterns were robust, suggesting a primary difference in IFNα production in SLE patients and their family members at different ages. Data from a microarray study of pediatric patients with SLE (mean age 13–14 years) showed that 29 of 30 patients (97%) had evidence of high levels of serum type I IFN (7). This proportion is higher than that in published reports of adult SLE populations, in which 50% of patients typically have high levels of serum IFNα activity (9,11). These data support the general pattern of higher IFNα activity at a younger age observed in the SLE patients in this study. Longitudinal study of IFNα activity in individuals over time would be of great interest and could confirm our findings from this cross-sectional analysis. The observed patterns of serum IFNα activity in SLE patients resemble the previously published patterns of age-related SLE activity and disease incidence, which supports a primary pathogenic role of IFNα in SLE.

Acknowledgments

We would like to thank Karen Onel, MD, and Kenan Onel, MD, PhD, for their contribution in establishing the Hospital for Special Surgery Lupus Family Registry, and Marie Flesch for her assistance in obtaining materials from the Lupus Family Registry and Repository at Oklahoma Medical Research Foundation.

Dr. Niewold's work was supported by the NIH (grant T32-AR-07517 and Clinical Research Loan Repayment grant AI-071651 from the National Institute of Allergy and Infectious Diseases) and by an Arthritis Foundation Postdoctoral Fellowship award. Dr. Harley's work was supported by the Lupus Family Registry and Repository (NIH grant AR-62277) and by research grants from the NIH (AR-42460, AI-53747, AI-31584, DE-15223, RR-20143, AI-24717, AI-62629, AR-48940, and AR-49084), the US Department of Veterans Affairs, the Alliance for Lupus Research, and Rheuminations, Inc. Dr. Crow's work was supported by research grants from the NIH (R01-AI-059893 from the National Institute of Allergy and Infectious Diseases), the Alliance for Lupus Research, the Mary Kirkland Center for Lupus Research, and the Lupus Research Institute. The Hospital for Special Surgery Lupus Family Registry is supported by the Toys “R” Us Foundation and the SLE Foundation, Inc.

Footnotes

Dr. Crow has received consulting fees, speaking fees, and/or honoraria from Genentech and Novo Nordisk (less than $10,000 each), owns stock or stock options in XDx, Inc., and has a patent pending for an interferon assay.

Author Contributions: Dr. Niewold had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study design. Niewold, Harley, Crow.

Acquisition of data. Niewold, Glenn, Lehman, Harley.

Analysis and interpretation of data. Niewold, Adler, Lehman, Crow.

Manuscript preparation. Niewold, Adler, Lehman, Crow.

Statistical analysis. Niewold, Adler.

References

1. Petri M. Epidemiology of systemic lupus erythematosus. Best Pract Res Clin Rheumatol. 2002;16:847–58. [PubMed]
2. Lopez P, Mozo L, Gutierrez C, Suarez A. Epidemiology of systemic lupus erythematosus in a northern Spanish population: gender and age influence on immunological features. Lupus. 2003;12:860–5. [PubMed]
3. Szyper-Kravitz M, Zandman-Goddard G, Lahita RG, Shoenfeld Y. The neuroendocrine-immune interactions in systemic lupus erythematosus: a basis for understanding disease pathogenesis and complexity. Rheum Dis Clin North Am. 2005;31:161–75. x. [PubMed]
4. Van Vollenhoven RF, Engleman EG, McGuire JL. An open study of dehydroepiandrosterone in systemic lupus erythematosus. Arthritis Rheum. 1994;37:1305–10. [PubMed]
5. Chagnon P, Schneider R, Hebert J, Fortin PR, Provost S, Belisle C, et al. Identification and characterization of an Xp22.33;Yp11.2 translocation causing a triplication of several genes of the pseudoautosomal region 1 in an XX male patient with severe systemic lupus erythematosus. Arthritis Rheum. 2006;54:1270–8. [PubMed]
6. Stevens AM, Tsao BP, Hahn BH, Guthrie K, Lambert NC, Porter AJ, et al. Maternal HLA class II compatibility in men with systemic lupus erythematosus. Arthritis Rheum. 2005;52:2768–73. [PubMed]
7. Bennett L, Palucka AK, Arce E, Cantrell V, Borvak J, Banchereau J, et al. Interferon and granulopoiesis signatures in systemic lupus erythematosus blood. J Exp Med. 2003;197:711–23. [PMC free article] [PubMed]
8. Kirou KA, Lee C, George S, Louca K, Papagiannis IG, Peterson MG, et al. Coordinate overexpression of interferon-α–induced genes in systemic lupus erythematosus. Arthritis Rheum. 2004;50:3958–67. [PubMed]
9. Kirou KA, Lee C, George S, Louca K, Peterson MG, Crow MK. Activation of the interferon-α pathway identifies a subgroup of systemic lupus erythematosus patients with distinct serologic features and active disease. Arthritis Rheum. 2005;52:1491–503. [PubMed]
10. Baechler EC, Batliwalla FM, Karypis G, Gaffney PM, Ortmann WA, Espe KJ, et al. Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus. Proc Natl Acad Sci U S A. 2003;100:2610–5. [PMC free article] [PubMed]
11. Niewold TB, Hua J, Lehman TJ, Harley JB, Crow MK. High serum IFN-α activity is a heritable risk factor for systemic lupus erythematosus. Genes Immun. 2007;8:492–502. [PMC free article] [PubMed]
12. Berghofer B, Frommer T, Haley G, Fink L, Bein G, Hackstein H. TLR7 ligands induce higher IFN-α production in females. J Immunol. 2006;177:2088–96. [PubMed]
13. Hua J, Kirou K, Lee C, Crow MK. Functional assay of type I interferon in systemic lupus erythematosus plasma and association with anti–RNA binding protein autoantibodies. Arthritis Rheum. 2006;54:1906–16. [PubMed]
14. Lieberson S. Limitations in the application of non-parametric coefficients of correlation. Am Sociol Rev. 1964;29:744–6.
15. Urowitz MB, Ibanez D, Jerome D, Gladman DD. The effect of menopause on disease activity in systemic lupus erythematosus. J Rheumatol. 2006;33:2192–8. [PubMed]
16. McDermott EM, Powell RJ. Incidence of ovarian failure in systemic lupus erythematosus after treatment with pulse cyclophosphamide. Ann Rheum Dis. 1996;55:224–9. [PMC free article] [PubMed]
17. Verthelyi D, Petri M, Ylamus M, Klinman DM. Disassociation of sex hormone levels and cytokine production in SLE patients. Lupus. 2001;10:352–8. [PubMed]
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...