Elsevier Editorial System(tm) for Clinica Chimica Acta Manuscript Draft
Manuscript Number: CCA-D-10-01239R1
Title: Association of STAT4 Polymorphisms with Susceptibility to Primary Membranous Glomerulonephritis and Renal Failure
Article Type: Research Paper
Keywords: membranous glomerulonephritis (MGN); signal transducer and activator of transcription 4 (STAT4); Single nucleotide polymorphisms (SNPs); Haplotype.
Corresponding Author: Dr. Shih-Yin Chen,
Corresponding Author's Institution: Graduate Institute of Chinese Medical Science, First Author: Shih-Yin Chen
Order of Authors: Shih-Yin Chen; Cheng-Hsu Chen; Yu-Chuen Huang; Chia-Jung Chan; Yao-Yuan Hsieh; Min-Chien Yu; Chang-Hai Tsai; Fuu-Jen Tsai
Abstract: Background: Membranous glomerulonephritis (MGN) is one of common causes of idiopathic nephrotic syndrome in adults, and 25% of MGN patients proceed to end-stage renal disease. STAT4 gene polymorphisms have been reported to be associated with many inflammatory diseases. The objective of this study was to clarify the relationship between STAT4 gene polymorphisms and the pathogenesis of MGN.
Methods: We investigated the association of three STAT4 gene polymorphisms (rs3024912,
rs3024908, and rs3024877) with the susceptibility to MGN in 403 Taiwanese populations (138 MGN patients and 265 controls).
Results: The results indicated that the statistically significant difference in genotype frequency distribution was found at rs3024908 SNP in MGN patients and control groups (p = 0.014). In addition, the individuals with the GG genotype at rs3024912 SNP may have a higher risk in kidney failure of MGN patients (adjusted odds ratio [OR] = 3.255; 95% confidence interval [CI] = 1.155-9.176, p = 0.026).
Conclusions: Our data provide a new information that the STAT4 (rs3024912 and rs3024908)
polymorphisms may be the underlying cause of MGN, and these polymorphisms revealed by this study warrant further investigation.
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Article Title: Association of STAT4 Polymorphisms with Susceptibility to Primary Membranous Glomerulonephritis and Renal Failure.
Corresponding Author: Shih-Yin Chen ■ Structured abstract
■ Keywords
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Ching-Wan Lam, MBChB PhD Editor, Clinica Chimica Acta
ching-wanlam@pathology.hku.hk
Dear Prof. Lam Jun 03, 2011
Thank you so much for your letter and referee(s)' comments on our
manuscript (code CCA-D-10-01239). Enclosed please find a copy of the revised
manuscript and the point to point reply to the comments and questions raised by
reviewers.
If you have any further comments or questions, please feel free to contact me at
the following numbers: Phone: +886-4-22052121 ext 2033; email:
chenshihy@yahoo.com.tw; chenshihy@mail.cmu.edu.tw
Best regards
Sincerely,
Shih-Yin Chen, Ph.D. Assistant Professor,
Graduate Institute of Chinese Medical Science, China Medical University,
91 Hsueh-Shih Road,Taichung, Taiwan 40402, R.O.C *Response to Reviewers
Reviewer Comments 1:
Please clarify how the controls were obtained, and what workup was performed
to exclude occult renal disease.
Response:
We would like to thank the reviewer for these comments. For explaining the
point which reviewer mention about, we had some description in the section of
Materials and Methods (please see p. 6, line 5-8).
Reviewer Comments 2:
Is the distribution of polymorphism similar to other population / reported series?
Response:
We appreciate this helpful comment. To our knowledge, this is the first report
on STAT4 polymorphisms in MGN patients. Currently, compared with other studies
using Asian individual groups, the similarly distribution of these polymorphisms were
obtained. However, we have the biggest sample size.
Reviewer Comments 3:
Please provide more information on baseline clinical and pathological
information, including baseline proteinuria, renal function, blood pressure,
histological scarring, and treatment.
Response:
information in Table 4 (please see p. 29) and the description in the section of
Materials and Methods (please see p. 7, line 2-8), the section of Result (please see p.
12, line 7-17) and the section of Discussion (please see p. 16, line 11-16).
Reviewer Comments 4:
What was the average duration of observation? Please provide Kaplan Meire
curve for different genotypes.
Response:
For this helpful comment, as the reviewer has suggested, we add the
information in Figure 2 (please see p. 25) and the description in the section of
Materials and Methods (please see p. 9, line 14-16) and the section of Result (please
see p. 13, line 14-19 and p. 14, line 1-7).
Reviewer Comments 5:
Is there any information of rate of GFR decline? Progress to renal failure is a
valid end point but would bias towards more severe / rapidly progressive cases.
Response:
We appreciate this helpful comment. We add table 5 and using pathological
features for data analysis. We also add the description in the section of Materials and
Methods (please see p. 7, line 9-17) and the section of Result (please see p. 12, line
ABSTRACT
Background: Membranous glomerulonephritis (MGN) is one of common causes of
idiopathic nephrotic syndrome in adults, and 25% of MGN patients proceed to
end-stage renal disease. STAT4 gene polymorphisms have been reported to be
associated with many inflammatory diseases. The objective of this study was to
clarify the relationship between STAT4 gene polymorphisms and the pathogenesis of
MGN.
Methods: We investigated the association of three STAT4 gene polymorphisms
(rs3024912, rs3024908, and rs3024877) with the susceptibility to MGN in 403
Taiwanese populations (138 MGN patients and 265 controls).
Results: The results indicated that the statistically significant difference in genotype
frequency distribution was found at rs3024908 SNP in MGN patients and control
groups (p = 0.014). In addition, the individuals with the GG genotype at rs3024912
SNP may have a higher risk in kidney failure of MGN patients (adjusted odds ratio
[OR] = 3.255; 95% confidence interval [CI] = 1.155-9.176, p = 0.026).
Conclusions: Our data provide a new information that the STAT4 (rs3024912 and
rs3024908) polymorphisms may be the underlying cause of MGN, and these
polymorphisms revealed by this study warrant further investigation. *Abstract
Association of STAT4 Polymorphisms with Susceptibility to
Primary Membranous Glomerulonephritis and Renal
Failure
Shih-Yin Chen a,d, Cheng-Hsu Chen e, Yu-Chuen Huang a,d, Chia-Jung Chan a,
Yao-Yuan Hsieh d,f, Min-Chien Yu h, Chang-Hai Tsai 2, Fuu-Jen Tsai b,c,g,*
a
Genetics Center, Department of Medical Research, China Medical University
Hospital, Taichung, Taiwan.
b
Department of Pediatrics, China Medical University Hospital, Taichung, Taiwan.
c
Department of Medical Genetics, China Medical University Hospital, Taichung,
Taiwan.
d
Graduate Institute of Chinese Medical Science, China Medical University, Taichung,
Taiwan.
e
Division of Nephrology, Department of Internal Medicine, Taichung Veterans
General Hospital, Taichung, Taiwan.
f
Division of Infertility Clinic, Hsieh Yao-Yuan Womens’ Hospital, Taichung, Taiwan.
g
Department of Biotechnology and Bioinformatics, Asia University, Taichung,
Taiwan.
h
School of Medicine, Chung Shan Medical University, Taichung, Taiwan.
*Manuscript
* Corresponding Author: Fuu-Jen Tsai, Department of Medical Research, China
Medical University Hospital, No. 2 Yuh Der Road, Taichung, Taiwan. E-mail:
d88905@yahoo.com.tw
E-mail addresses of the authors:
chenshihy@yahoo.com.tw (S-Y Chen)
g880715@mailsrv2.ym.edu.tw (C-Hsu Chen)
yuchuen@mail.cmu.edu.tw (Y-Chuen Huang)
melody700525@yahoo.com.tw (C-J Chan)
d3531@yahoo.com.tw (Y-Y Hsieh)
yu7777c@yahoo.com.tw (M-C Yu)
chchai@www.cmuh.org.tw (C-H Tsai)
ABSTRACT
Background: Membranous glomerulonephritis (MGN) is one of common causes of
idiopathic nephrotic syndrome in adults, and 25% of MGN patients proceed to
end-stage renal disease. STAT4 gene polymorphisms have been reported to be
associated with many inflammatory diseases. The objective of this study was to
clarify the relationship between STAT4 gene polymorphisms and the pathogenesis of
MGN.
Methods: We investigated the association of three STAT4 gene polymorphisms
(rs3024912, rs3024908, and rs3024877) with the susceptibility to MGN in 403
Taiwanese populations (138 MGN patients and 265 controls).
Results: The results indicated that the statistically significant difference in genotype
frequency distribution was found at rs3024908 SNP in MGN patients and control
groups (p = 0.014). In addition, the individuals with the GG genotype at rs3024912
SNP may have a higher risk in kidney failure of MGN patients (adjusted odds ratio
[OR] = 3.255; 95% confidence interval [CI] = 1.155-9.176, p = 0.026).
Conclusions: Our data provide a new information that the STAT4 (rs3024912 and
rs3024908) polymorphisms may be the underlying cause of MGN, and these
Key words:
membranous glomerulonephritis (MGN); signal transducer and activator of
transcription 4 (STAT4); Single nucleotide polymorphisms (SNPs); Haplotype.
1. Introduction
Membranous glomerulonephritis (MGN), the common cause of nephrotic
syndrome, accounts for approximately 40% of adult cases [1]. It is characterized by
basement membrane thickening and subepithelial immune deposits without cellular
proliferation or infiltration [2]. Previous study suggested MGN as causing chronic
kidney disease (CKD) and as a final result of end-stage renal disease (ESRD) [3].
Therapies for MGN that include the use of immunosuppressive drugs and nonspecific
antiproteinuric measures have led to disappointing results and prompted increased
interest in the discovery of new therapeutic targets [4]. Taiwan has the highest
prevalence of ESRD worldwide and MGN may be one cause [5-7]. Study of
inflammatory factors associated with MGN is helpful for the elucidating and
preventing of ESRD.
The signal transducer and activator of transcription 4 (STAT4) gene, located on
chromosome 2q32.2-32.3, encodes a transcription factor which plays an essential role
Likewise, STAT4 plays a crucial role in regulation of the immune response by
transmitting signals activated in response to several cytokines, including type 1 IFN,
IL-12, and IL-23 [9]. STAT4 is necessary for IL-12 induced differentiation of naïve
CD4+ T cells into Th1 cells, and activated Th1 cells drive chronic inflammation, by
secreting high levels of pro-inflammatory cytokines like IFN-γ and TNF-α [10]. In
addition, recent studies demonstrated that STAT4 is also responsible for the expansion
of Th17 cells activated by IL-23 [11], which promotes chronic inflammation in
adaptive and innate immunity and contributes to the development of a variety of
autoimmune diseases [9, 12-14]. Moreover, it was shown that STAT4 haplotype
characterized by the rs7574865 polymorphism was reported to be significantly
associated with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and
other autoimmune diseases such as Sjögren's syndrome, type I diabetes, and systemic
sclerosis [15-19], but no genetic study regarding the relationship of such
polymorphisms with MGN disease.
The present study aimed to identify genetic polymorphisms in potential
candidate genes for MGN, and we therefore investigated the association of STAT4
gene polymorphisms with MGN in a Taiwanese population. Our findings are expected
to help us understand the role of STAT4 gene polymorphisms in MGN disease and its
this common nephropathy.
2. Materials and Methods
2.1. Study Population
A gender-age-matched control group composed of 265 non-diabetic,
non-nephropathic, normotensive healthy unrelated control subjects, whom identified
through health examination at Taichung Veterans General Hospital in Taiwan, was
enrolled. We also recruited 138 patients with the previously renal biopsy-approved
membranous glomerulonephritis (MGN) in the same Hospital during 1982-2008. The
Patients with malignancy, chronic infection diseases (including infections with
hepatitis B and C viruses), lupus nephritis or drug-induced secondary MGN were
excluded from the study. The general data (gender, body weight, systolic/diastolic
pressure, and body height) and medical information (duration of follow-up, real
failure, and herbal use, etc.) of all the patients were reviewed. Patient characteristics
includes: demographic variables, clinical and laboratory data in the disease courses,
vascular events (cardiovascular disease and peripheral vascular events), and treatment
regimens as well as their responses. All participants signed informed consent. The
study was approved by the institutional review board of the hospital (VGHTC IRB No.
2.2. Response and Outcomes
The responses to therapy were defined as the follows: (a) no response, (b) partial
remission: a proteinuria reduction more than 50% or a final proteinuria between 0.2 to
2.0 g/day, and (c) complete remission: proteinuria less than 0.2 g/day. The
“progression of renal disease” was defined as a doubling of baseline serum creatinine (Cr) values or in ESRD. ESRD was defined as patient requiring renal replacement
therapy.
2.3. Renal Biopsy Review
Histological staging was based on histological lesion, including glomerular lesion
[20], tubulointerstitial lesion, focal glomerulosclerosis [21], and fibrointimal lesion.
Biopsy specimens were reviewed by a nephropathologist, who was unaware of
patients’ clinical history, renal function and STAT4 gene SNPs (rs3024912, rs3024908, and rs3024877). Semiquantitative scoring system used a scale of 0 (absent), 1 (mild:
<25%) and 2 (moderate to severe: >25%) for the assessment of tubulointerstitial
change and glomerular sclerosis/obsolescence under light microscopy. Staging of the
disease was determined according to finding under electron microscopy [22, 23].
2.4. SNP selection
the HapMap CHB + JPT population. HapMap genotypes were analyzed within
Haploview and Tag SNPs were selected using the Tagger function by applying the
following additional criteria: (i) a threshold minor allele frequency (MAF) in the
HapMap CHB + JPT population of 0.05 for “tag SNPs”; and (ii) probe/primers that
pass the qualification as recommended by the manufacturer (Applied Biosystems), to
ensure a high genotyping success rate. Three polymorphisms met the criteria and were
selected, including SNP rs3024912 (G/T) in 3’UTR, SNP rs3024908 (A/G) in 3’UTR,
and SNP rs3024877 (A/G) in intron 15 of STAT4 gene (Figure 1).
2.5. Genomic DNA Extraction and Genotyping of STAT4 Gene Genetic
Polymorphisms
Genomic DNA was extracted from peripheral blood leukocytes according to
standard protocols (Genomic DNA kit; Roche, USA). Genotypes of three SNPs
(rs3024912, rs3024908, and rs3024877) at chromosome positions 2:191893087
(3’UTR), 2:191894141 (3’UTR), and 52198412 (intron 15) in STAT4 gene (Figure 1)
were performed using the Taqman SNP genotyping assay (ABI: Applied Biosystems
Inc. Foster City, CA, USA). The primers and probes of SNPs were from the ABI
assay on demand (AOD) kit. Reactions were carried out according to the
the presence of 2× TaqMan® Universal PCR Master Mix (ABI, Foster City, CA,
USA), assay mix (Assay ID C_15984893_10, C_15984883_10, and C_15984786_10,
Applied Biosystems, USA) and genomic DNA (15 ng). After initial denaturation for
10 min at 95°C, 40 cycles were run, each consisting of denaturation (95°C for 15 s),
and annealing (60°C for 60 s). The probe fluorescence signal detection was performed
using the ABI Prism 7900 Real Time PCR System.
2.6. Statistical Analysis
Chi-square test or Fisher’s exact tests determined statistically significant
differences in allele/genotype frequencies between case and control groups. Allelic
frequencies were expressed as percentage of the total alleles. Hardy–Weinberg
equilibrium was tested for each marker using χ2-test. Odds ratios [ORs] and 95%
confidence intervals (95% CIs) were derived by logistic regressions to correlate
STAT4 alleles/genotypes/haplotypes with MGN susceptibility. The Kaplan-Meier
method was used to estimate cumulative survival. Differences in survival were
analyzed with the log-rank test. All data were analyzed with SPSS Version 15.0
software (SPSS Inc., Chicago, IL, USA). A p value < 0.05 was considered statistically
3. Results
3.1. Genotypic and allelic frequencies of STAT4 genetic polymorphisms in MGN
patients and controls
Table 1 plots allelic and genotypic frequencies of rs3024912, rs3024908, and
rs3024877, genotype distributions in Hardy-Weinberg equilibrium. We observed the
A allele as the major one at rs3024908 polymorphism both in MGN patients (85%;
233/274) and controls (85%; 453/530). There was no statistically significant
difference in allelic frequencies distributions at rs3024912 and rs3024877 SNP. When
we compared the genotype frequencies between MGN patients and control groups, a
statistically significant difference in genotype frequency distributions was noted for
rs3024908 SNP in MGN patients and controls (p = 0.014). Our data indicated that
individuals with the AA genotype at rs3024908 SNP may have a higher risk of
developing MGN.
3.2. Distribution of SATA4 haplotype frequencies in MGN patients and controls
The Haplotype frequencies were estimated using the rs3024912, rs3024908, and
rs3024877 SNPs (Table 2). Five haplotypes of STAT4 were present in our study
MGN patients (28.3% and 25.1%, respectively) and control groups (33.7% and 24.1%,
respectively). Comparison of the haplotype frequencies between case and control
groups indicated that the Ht 1 and Ht 5 haplotypes appeared to be the “protective”
haplotypes as compared with others (OR: 0.77, 95% CI: 0.56–1.05, p = 0.114 at Ht 1
haplotype; OR: 0.59, 95% CI: 0.31–1.31, p = 0.119 at Ht 5 haplotype). However, the
Ht 3 haplotype appeared to be an “at-risk” haplotype for MGN progression (OR: 1.34,
95% CI: 0.89–2.00; p = 0.163), although the difference was not statistically
significant (Table 2).
3.3. Association between STAT4 genotypes and MGN patients with/without kidney
failure
The Logistic Regression test was used for association analysis between STAT4
genotypes and MGN patients with/without kidney failure. Renal failure was observed
in 21 patients during the follow-up period with an incidence of 15.22 % (21/138)
(Table 3). Median and mean renal survival durations were 8.0 and 5.7 years,
respectively. In addition, 12 patients died during the follow-up period, and the
mortality in our population was 8.70 % (12/138). Median and mean survival durations
were 9.6 and 12.9 years, respectively. The longest follow-up period for patients who
died before the end-point of this study was 17.4 years; for surviving patients, the
frequencies between MGN patients and control groups, a statistically significant
difference was noted for rs3024912 SNP in MGN patients and controls (OR: 2.947,
95% CI: 1.074-8.092, p = 0.041). Yet, we also observed a strong correlation in MGN
patients and controls after adjusting gender and follow-up period effect (OR: 3.255,
95% CI: 1.155-9.176, p = 0.026). Our data indicated that individuals with the GG
genotype at rs3024912 SNP may have a higher risk in kidney failure of MGN patients
(Table 3).
3.4. Association between STAT4 major Ht 1 haplotype and clinical features in MGN
patients
A comparison of the clinical features of MGN patients with/without the major Ht
1 haplotype is shown in Table 4. There were no differences in age of onset, duration
of follow up, body mass index (BMI), mean blood pressure (MBP), and incidence of
hematuria or proteinuria. After a mean 12.9 ± 6.2 years follow-up period, we observed
the creatinine clearance (CCr) levels in the last laboratory test to be 64.2 ± 43.55
ml/min in MGN patients with Ht 1 haplotype and 47.07 ± 34.9 ml/min in those with
the non Ht 1 haplotype (p = 0.017). However, the initial laboratory tests revealed no
differences in the baseline creatinine levels (Cr) and daily urinary protein excretion
3.5. Association between STAT4 major Ht 1 haplotype and pathological features in
MGN patients
We also analyzed the relationship between the STAT4 major Ht 1 haplotype and
the pathological features of MGN. The scoring for MGN requires electron microscopy
images of the glomeruli; however, only 107 biopsy specimens were available for
review and scoring by the pathologist. There were 27 glomeruli (25.2%) at stage I, 55
(51.4%) at stage II, 18 (16.8%) at stage III, 5 (4.7%) at stage IV, and 2 (1.9%) at stage
V. As shown in Table 5, there were no differences in the results for histological
examination, percentage of global sclerosis, tubulointerstitial fibrosis and the
fibrointimal atherosclerosis score between with/without Ht 1 haplotype of MGN
patients.
3.6. Association between STAT4 major Ht 1 haplotype and survival status in MGN
patients
The log-rank test was used for survival analysis of MGN patients with/without
the A-G haplotype of the STAT4 gene. As shown in Fig. 2A, renal failure was
observed in 21 patients during the follow-up period with an incidence of 15.79 %
respectively. In addition, 12 patients died during the follow-up period, and the
mortality in our population was 9.02 % (12/133). Median and mean survival durations
were 9.6 and 12.9 years, respectively. The longest follow-up period for patients who
died before the end-point of this study was 17.4 years; for surviving patients, the
longest period was 22.7 years (Fig. 2B). The Kaplan-Meier curves for renal and
patient survival showed that there was no statistically significant difference between
the Ht 1 and non Ht 1 haplotypes of the STAT4 gene in MGN patients (Fig. 2).
4. Discussion
Currently, MGN is considered to be an infectious disease with immunologic
expression that occurs in genetically susceptible individuals [24, 25]. Polymorphic
gene sequences of cytokines known to be involved in the pathogenesis of MGN are
potential markers of disease susceptibility. Previous studies relatied the incidence of
MGN and several polymorphisms, including TNF-α gene G-308A, ACE insertion or
deletion (ACE I/D), angiotensin II receptor 1 (AT1R 1166A/C), angiotensinogen
(AGT M235T), and NOS (ecNOS4b/a) [26-28]. In the present investigation we
observed a correlation between the risk genotype of STAT4 and a higher frequency of
kidney failure among MGN patients with the risk genotype, which suggests that
This effect could be due to the many different effects of STAT4 in the immune system.
Besides its role in type I IFN signaling, STAT4 also transmits signals from, e.g. IL-12
and IL-23, and is thus responsible for the IL-12-dependent activation of natural killer
(NK) cells and production of IFN-, as well as for polarization of naive CD4+ T-cells to IFN- producing Th1 effector cells [29].
STAT4, which plays a pivotal role in Th1 immune responses, enhances IFN- transcription in response to the interaction of IL-12 with the IL-12 receptor [30, 31].
Yet, STAT4-deficient mice lack many IL-12-stimulated responses, including the
inductionof IFN- secretion and the differentiation of Th1 cells [32, 33].These mice are generally resistant to autoimmune diseases suchas proteoglycan-induced arthritis,
experimental autoimmune encephalomyelitis, and diabetes [9]. Collectively, these
findings strongly indicate that a deficiency of STAT4expression is directly associated
with impaired Th1 responses and associated immune diseases. However, the
molecular mechanismsfor transcriptional or post-transcriptional regulation of STAT4
expression have not yet been elucidated.
In this study, we focused on the variants of the STAT4 gene (rs3024912,
rs3024908, and rs3024877) that had previously been investigated for systemic lupus
erythematosus (SLE) and cardiovascular disease events [34, 35]. We found a
The AA genotype frequency at rs3024908 was higher in MGN than in the control
participants (Table 1). Our results also indicated that the Ht1 haplotype of the STAT4
gene was estimated to be present in approximately 28.3% of MGN patients.
Compared with control group, the Ht1 haplotype seems appeared to be a susceptibility
factor for preventing MGN in our Taiwanese cohort, although the difference was not
statistically significant (Table 2).
The treatment strategies for patients with MGN have been a subject of much
controversy. In our series, most the patients were treated with ACE inhibitors (ACEIs)
or angiotensin receptor blockers (ARBs). Despite the similar mode of treatment given
to our patients, 15.22 % (21/138) kidney failure cases were observed in MGN
subgroup. As shown in Table 3, after considering the gender and follow-up period
effect, individuals with the GG genotype at rs3024912 SNP may have a higher risk in
kidney failure of MGN patients. We observed that the latest CCr level in MGN
patients with non Ht 1 haplotype was significantly lower than in patients with Ht 1
haplotype (47.07 ± 34.9 ml/min and 64.2 ± 43.55 ml/min, respectively) (p = 0.017).
Despite the similar mode of treatment given to our patients, greater disease
progression was observed in the non Ht 1 subgroup than in the subgroups with the Ht
1 haplotype, although the difference was not statistically significant (Table 4). These
the different genotypes and haplotypes. In addition, more specific drugs that interact
with STAT4 could be given in addition to regular immunosuppressive regimens,
especially in patients with GG genotype at rs3024912 SNP and the major Ht 1
haplotype.
The interpretation of our study results is limited because the patients were
recruited from just one center in Taiwan. Our results suggest a significant role of
STAT4 polymorphisms in the risk of developing MGN of Taiwan. To the best of our
knowledge, this is the first report on STAT4 polymorphisms in MGN patients.
However, the identification of STAT4 as genetic risk factors for MGN susceptibility in
Taiwan may be further evaluated as prognostic markers for predictive clinical testing
in MGN worldwide, especially in ethnically disparate populations.
In summary, our study firstly demonstrated the different genotype distribution
between normal controls and patients with MGN of STAT4 gene. The data show that
STAT4 gene is one of an important inflammatory related gene and may be associated
with renal deterioration in MGN patients.
Acknowledgements
We acknowledge the excellent assistances of Ms Hsuan-Min Chuang and
supported by China Medical University (CMU98-N1-18 and CMU99-N1-21) and
Asia University (CMU-asia-05) in Taiwan.
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Figure legend:
Figure 1. Map of STAT4 (rs3024912, rs3024908, rs3024877) located within
Chromosome 2q32.3 region (191,894,302-192,016,322 bp).
Figure 2. The log-rank test was used for (A) renal and (B) patients survival analysis
Table 1
Genotypic and allelic frequencies of SATA4 genetic polymorphisms in MGN patients and controls.
dbSNP ID MGN patients Controls p value OR (95% CI)
rs3024912 Genotype (N =136) (N = 264) GG 30 (0.22) 71 (0.27) 0.388a GT 75 (0.55) 127 (0.48) TT 31 (0.23) 66 (0.25) Allele frequency G 137 (0.50) 259 (0.49) 0.725 1.05(0.79-1.41) T 135 (0.50) 269 (0.51) 1 rs3024908 Genotype (N =137) (N = 265) AA 100 (0.73) 188 (0.71) 0.014a AG 33 (0.24) 77 (0.29) GG 4 (0.03) 0 (0) Allele frequency G 41 (0.15) 77 (0.15) 0.869 1.04(0.69-1.56) A 233 (0.85) 453 (0.85) 1 rs3024877 Genotype (N =138) (N= 264) GG 36 (0.26) 61 (0.23) 0.797a AG 70 (0.51) 138 (0.52) AA 32 (0.23) 65 (0.25) Allele frequency G 142 (0.51) 260 (0.49) 0.552 1.09 (0.82-1.46) A 134 (0.49) 268 (0.51) 1 a
Genotype distribution between patients and control were calculated by 2 x 3 chi-square test
Table 2
Distribution of SATA4 haplotype frequencies in MGN patients and controls.
Haplotype
aMGN patients (%)
bControl (%)
p value
OR (95% CI)
(n=136)
(n=264)
Ht 1 (G-A-A)
28.3%
33.7%
0.114
0.77 (0.56-1.05)
Ht 2 (T-A-G)
25.1%
24.1%
0.749
1.06 (0.75-1.48)
Ht 3 (G-A-G)
17.0%
13.3%
0.163
1.34 (0.89-2.00)
Ht 4 (T-A-A)
14.7%
14.3%
0.891
1.02 (0.67-1.54)
Ht 5 (T-G-G)
4.8%
7.7%
0.119
0.59 (0.31-1.31)
CI, confidence interval; OR, odds ratio.
a
Order of single nucleotide polymorphisms comprising the SATA4 haplotypes: rs3024912, rs3024908 and rs3024877.
b
Table 3
Association between STAT4 genotypes and MGN patients with/without kidney failure.
dbSNP ID OR (95% CI) p value Adjusted OR (95% CI)a p value
no yes rs3024912 GG (n=27) 19 (17.3) 8 (38.1) 2.947(1.074-8.092) 0.041 3.255(1.155-9.176) 0.026 non GG (n=104) 91 (82.7) 13 (61.9) 1 1 rs3024908 AA (n=96) 82 (73.9) 14 (66.7) 0.707(0.260-1.927) 0.498 0.635(0.227-1.773) 0.386 non AA (n=36) 29 (26.1) 7 (33.3) 1 1 rs3024877 GG (n=35) 29 (25.9) 6 (28.6) 1.145(0.406-3.229) 0.798 1.350(0.461-3.957) 0.585 non GG (n=98) 83 (74.1) 15 (71.4) 1 1 Patients with MGN kidney failure
The Logistic Regression test was used
a
Table 4
Comparison of the clinical features of MGN patients with/without the major Ht1 haplotype of STAT4 gene.
Ht 1 non Ht 1
(N = 78) (N =58) p value Age of biopsy (yrs)a 51.01 ± 17.79 56.11 ± 15.96 0.089 Duration of follow-up (yrs)a 6.6 ± 5.48 5.69 ± 4.55 0.311 BMI (Kg/M2)a 24.66 ± 3.62 25.03 ± 3.42 0.547 Mean BP (mmHg)a 99.84 ± 15.93 101.77 ± 11.24 0.436 Albumin (gm/dl)a 2.53 ± 0.63 2.47 ± 0.62 0.583 Cholesterol (mg/dl)a 327.91 ± 132.29 320.55 ± 123.18 0.744 Triglyceride (mg/dl) )a 202.61 ± 144.88 243.57 ± 165.39 0.132 Baseline serum Cr (mg/dl)a 1.42 ± 1.53 1.49 ± 1 0.746 Baseline DUP (gm/day)a 7.78 ± 11.91 7.94 ± 5.6 0.925 Baseline CCr (ml/min)a 85.7 ± 42.29 73.19 ± 37.46 0.080 Serum Cr at latest
(mg/dl)a
2.68 ± 4.02 3 ± 3.01 0.617 Latest DUP (gm/day)a 2.47 ± 3.63 4.05 ± 5.37 0.064 Latest CCr (ml/min)a 64.2 ± 43.55 47.07 ± 34.9 0.017 Cardiovascular events
(%)b
14 (18.7) 15 (25.9) 0.319 Other vascular events
(%)c
18 (24.0) 15 (25.9) 0.805 Hematuria (%) 50 (66.7) 35 (60.3) 0.452 Lower leg edema (%) 64 (85.3) 54 (93.1) 0.160 Proteiuria ≧ 3.5 g/day
(%)
71 (94.7) 54 (93.1) 0.728 Malignancy (%) 7 (9.3) 4 (6.9) 0.755 Disease Progression (%) 34 (45.3) 28 (48.3) 0.736 BMI: body mass index; MBP: mean blood pressure; DUP: daily urinary protein excretion; CCr: creatinine clearance
a
Data were presented as Mean ± SD (standard deviation)
b
Cardiovascular events including: unstable angina, coronary artery disease, ischemic heart disease.
c
Other vascular events including: renal artery or vein thrombosis, deep vein thrombosis and cranial vascular events
Table 5
STAT4 major Ht1 haplotype distribution and severity of pathological findings
Ht 1 non Ht 1 p value Histological Stage (N =60 ) (N = 47) 1 19 (31.7) 8 (17.0) 0.126 2 29 (48.3) 26 (55.3) 3 8 (13.3) 10 (21.3) 4 4 (6.7) 1 (2.1) 5 0 (0) 2 (4.3) Global sclerosis* (N = 68) (N =50 ) 0 36 (52.9) 19 (38.0) 0.249 1 20 (29.4) 21 (42.0) 2 12 (17.6) 10(20.0) Tubule-interstitial fibrosis* (N =67 ) (N =50 ) 0 47 (70.1) 29 (58.0) 0.281 1 14 (20.9) 17 (34.0) 2 6 (9.0) 4 (8.0)
Intima fibroplasia of vessel* (N = 65) (N =50 )
0 49 (75.4) 35 (70.0) 0.525 1 13 (20.0) 10 (20.0)
2 3 (4.6) 5 (10.0)
The Chi-square test was used
*A semiquantitative scoring system was adopted, using a scale of 0 (absent), 1 (mild: <25%) and 2 (moderate to severe: >25%) for the assessment under the light microscopy.
Figure(s)
Figure(s)
