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Original Contribution |

Association of Caveolin-1 Gene Polymorphism With Kidney Transplant Fibrosis and Allograft Failure FREE

Jason Moore, BMBS; Amy Jayne McKnight, PhD; Matthew J. Simmonds, PhD; Aisling E. Courtney, MD; Rajesh Hanvesakul, PhD; Oliver J. Brand, PhD; David Briggs, PhD; Simon Ball, PhD; Paul Cockwell, PhD; Christopher C. Patterson, PhD; Alexander P. Maxwell, PhD; Stephen C. L. Gough, MD; Richard Borrows, MB
[+] Author Affiliations

Author Affiliations: Department of Nephrology and Transplantation, Renal Institute of Birmingham, University Hospital Birmingham (Drs Moore, Hanvesakul, Ball, Cockwell, and Borrows), School of Clinical and Experimental Medicine, College of Medical and Dental Sciences, Institute of Biomedical Research, University of Birmingham (Drs Simmonds, Brand, and Gough), and National Blood Service (Dr Briggs), Birmingham, England; and Nephrology Research Group, Queen's University of Belfast, Belfast, Northern Ireland (Drs McKnight, Courtney, Patterson, and Maxwell).


JAMA. 2010;303(13):1282-1287. doi:10.1001/jama.2010.356.
Text Size: A A A
Published online

Context Caveolin-1 (CAV1) is an inhibitor of tissue fibrosis.

Objective To study the association of CAV1 gene variation with kidney transplant outcome, using kidney transplantation as a model of accelerated fibrosis.

Design, Setting, and Patients Candidate gene association and validation study. Genomic DNA from 785 white kidney transplant donors and their respective recipients (transplantations in Birmingham, England, between 1996 and 2006; median follow-up, 81 months) were analyzed for common variation in CAV1 using a single-nucleotide polymorphism (SNP) tagging approach. Validation of positive findings was sought in an independent kidney transplant donor-recipient cohort (transplantations in Belfast, Northern Ireland, between 1986 and 2005; n = 697; median follow-up, 69 months). Association between genotype and allograft failure was initially assessed by Kaplan-Meier analysis, then in an adjusted Cox model.

Main Outcome Measure Death-censored allograft failure, defined as a return to dialysis or retransplantation.

Results The presence of donor AA genotype for the CAV1 rs4730751 SNP was associated with increased risk of allograft failure in the Birmingham group (donor AA vs non-AA genotype in adjusted Cox model, hazard ratio [HR], 1.97; 95% confidence interval [CI], 1.29-3.16; P = .002). No other tag SNPs showed a significant association. This finding was validated in the Belfast cohort (in adjusted Cox model, HR, 1.56; 95% CI, 1.07-2.27; P = .02). Overall graft failure rates were as follows: for the Birmingham cohort, donor genotype AA, 22 of 57 (38.6%); genotype CC, 96 of 431 (22.3%); and genotype AC, 66 of 297 (22.2%); and for the Belfast cohort, donor genotype AA, 32 of 48 (67%); genotype CC, 150 of 358 (42%); and genotype AC, 119 of 273 (44%).

Conclusion Among kidney transplant donors, the CAV1 rs4730751 SNP was significantly associated with allograft failure in 2 independent cohorts.

Figures in this Article

Effective signaling at the plasma membrane is facilitated by the presence of domains such as galectin-based lattices, clathrin-coated pits, lipid rafts, and caveolae. The latter are 50- to 100-nm invaginations of the plasma membrane and, although expressed ubiquitously, are particularly abundant in endothelial cells, adipocytes, fibroblasts, and pneumocytes. It has been recognized for some time that caveolae mediate cholesterol transport within the cell, but an additional role in transmembrane signaling has become apparent more recently. This is mediated via interactions between caveolin-1 (CAV1), the primary structural component of caveolae, and a variety of membrane receptors, G proteins, kinases, and other enzymes.1,2

As expected from their function and tissue distribution, caveolae and CAV1 are implicated in a variety of diseases, including cancer, vascular disease and hypertension, insulin resistance, and diabetes.3 Particular attention has focused on the importance of CAV1 in fibrosing diseases such as scleroderma, pulmonary fibrosis, and fibrosing cardiomyopathy.35 Within caveolae, CAV1 is found in close proximity to cell membrane receptors for fibrotic mediators such as transforming growth factor β, epidermal growth factor, and platelet-derived growth factor. Classic transforming growth factor β signal transduction occurs via receptors associated with domains such as clathrin-coated pits, with subsequent formation of the early endosome and the characteristic downstream stimulus to promote tissue fibrosis. However, transduction via receptors associated with caveolae and CAV1 triggers receptor internalization and degradation, with a resultant antifibrotic effect.6 Indeed, tissue expression of CAV1 is known to be reduced in patients with scleroderma and idiopathic pulmonary fibrosis.5

Compared with these fibrosing disorders, the role of CAV1 in the development of renal fibrosis has received little attention, although a recent report described a model of ureteric obstruction, whereby reduced CAV1 expression promoted the ensuing renal fibrosis.7 We sought to further assess the role of CAV1 in renal fibrosis, with particular regard to variation in the encoding gene, CAV1. No studies to date have addressed whether genetic variation of CAV1 increases propensity toward fibrosis in general or renal fibrosis specifically. Although fibrosis is common to many renal pathologic states, it is particularly common in renal allografts,8 with often rapid progression early posttransplantation, resulting in subsequent allograft dysfunction and failure. Indeed, kidney transplantation may be considered a “human model” of accelerated tissue fibrosis.9

This study assessed the role of CAV1 variants in the development of renal allograft fibrosis and in renal transplantation outcome, using allograft failure as the primary end point of interest. Gene variation among both donors and recipients was investigated because cells derived from both may contribute to allograft fibrosis.10 The a priori strategy was to identify the CAV1 variant(s) associated with increased transplant failure rates in a large single-center transplant cohort, then validate any associations in an independent population using an “exact validation” approach.11

Patients

All consecutive kidney transplant procedures performed at the Queen Elizabeth Hospital, Birmingham, England, between 1996 and 2006 were considered (n = 890). Of these, genomic DNA was available and successfully genotyped for 785 white transplant donors and their respective recipients (Table 1). No donor or recipient demographic differences (age, sex, ethnicity, repeat transplantation, and proportion of live donors) were seen between those selected for analysis and those unsuitable for analysis by virtue of unavailable DNA (data not shown). The study was performed in accordance with the Declaration of Helsinki. The United Kingdom's National Research Ethics Service approved the study and waived requirement for individual patient consent.

Table Graphic Jump LocationTable 1. Characteristics of the Study Cohortsa
Tag SNP Selection and Genotyping

Genotyping data were downloaded for all single-nucleotide polymorphisms (SNPs) evaluated in CAV1 from the International HapMap Project Phase II CEU population (http://www.hapmap.org; release 24; CAV1 accession numbers: AF125348; NM_001753). Data were available for 70 SNPs, of which 53 met our inclusion criteria of minor allele frequency greater than 5%. Twelve tag SNPs were selected using the pairwise tagging approach implemented in Haploview12 (r2>0.8; minor allele frequency >5%). Together, these 12 SNPs (rs926198, rs4730748, rs3779512, rs3807986, rs4730751, rs959173, rs12672038, rs3801995, rs11773845, rs9886215, rs9920, and rs1049337) effectively evaluate all common sequence variation within CAV1. SNP assays were obtained from Applied Biosystems, Warrington, England, and genotyped on a 7900HT polymerase chain reaction system using Taqman technology. Genotyping results were tested for Hardy-Weinberg equilibrium. To minimize the confounding effect of population stratification, the effect of recipient CAV1 variation was restricted to a subgroup of 611 white recipients. All donors were white, and all underwent assessment for the effect of CAV1 variation. Individual ethnicity was classified according to categories set by the United Kingdom transplant regulatory authority and were recorded by the institutional transplant coordinator after agreement with the patient (or relative of deceased donor) at the point of transplantation.

Outcome Measures

The primary outcome measure was death-censored allograft failure, defined as the time from transplantation to dialysis requirement or retransplantation.

Initial positive results in the Birmingham cohort were validated in an independent cohort of patients who underwent transplantation at Belfast City Hospital, Belfast, Northern Ireland, between 1986 and 2005. From a total of 697 consecutive first deceased donor transplant procedures during this time, genomic DNA was available and successfully genotyped for 679 white recipients and their respective donors (Table 1). In this validation group, genotyping was performed using MassARRAY iPLEX (Sequenom, San Diego, California). Ethical approval and a waiver for patient consent were obtained for the Belfast cohort.

Following validation of the association between a candidate SNP and death-censored graft failure, analysis was conducted to assess its relationship with all-cause mortality (defined as the time from transplantation to death) to ensure that the association between the SNP and death-censored graft failure was not due to increased risk of mortality (confounding by competing risks).

To assess the mechanism by which CAV1 variation might determine graft outcome, causes of graft failure in the Birmingham cohort were identified by clinical review using the methods and reporting strategy of El-Zoghby et al8. Robust data regarding the causes of graft failure in the Belfast cohort were not available. Additionally, associations between the candidate SNP and delayed graft function (defined as dialysis requirement in the first week after transplantation) and biopsy-proven acute rejection were evaluated.

Finally, genotype frequency in donors and recipients was compared to assess whether the candidate SNP might influence the development of end-stage renal disease per se.

Statistical Analysis

Data are shown as mean (SD) unless otherwise indicated. Group comparisons were assessed using the Fisher exact test and χ2 testing as appropriate. Cumulative events were analyzed with Kaplan-Meier methods, with the log-rank test used for intergroup comparison. Time-to-event analyses were performed using a Cox proportional hazards model. CAV1 variation and other relevant clinical and demographic characteristics were initially examined in a series of univariable analyses, followed by a multiple regression analysis incorporating variables that showed some evidence of univariate association (P ≤ .20). A stepwise backward selection process was undertaken to retain variables with a type I error rate of .05 or less in the final model. Colinearity was limited by avoiding entering highly correlated variables into the model. The functional form used for modeling donor and recipient age was investigated by fitting linear and quadratic terms in age. If the quadratic term was not significant (P > .05), this was omitted from the analysis, and the linear term alone was used. For variables with more than 2 categories or for which 2 functional forms were assessed, the likelihood ratio statistic was used to display the P value for the variable overall. A test based on Schonfeld residuals was used to confirm the assumption of proportional hazards. SPSS software, version 16 (SPSS Inc, Chicago, Illinois), and Stata software, release 11 (Stata Corp, College Station, Texas), were used for analysis.

For the primary (Birmingham) analysis, a type I error rate of .05 or less (P ≤ .05) in the Cox regression model was the criterion for pursuing validation.

Identification of Individual SNP Associations

In the Birmingham cohort, the genotyping success rate exceeded 98% and all SNPs were within Hardy-Weinberg equilibrium bounds (P > .05). During a total follow-up of 157 months (median, 81 months; interquartile range, 54-113 months), there were 184 death-censored graft failures. Kaplan-Meier analysis of death-censored allograft failure revealed significant differences in graft survival between donor genotypes for the tag SNP rs4730751 (log-rank P = .007) (Figure), with poorer graft survival in recipients whose donors displayed genotype AA. Overall graft failure rates were 38.6% (22/57) for donor genotype AA, 22.3% (96/431) for donor genotype CC, and 22.2% (66/297) for donor genotype AC. On the basis of the Kaplan-Meier analysis, the Cox model examined donor genotype as either AA or non-AA (ie, AC and CC combined). A univariable association was found between donor genotype and death-censored graft failure (for donor AA vs non-AA genotype, hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.29-3.16; P = .002). This effect persisted in the multiple regression model, where a similar HR was observed (for donor AA vs non-AA genotype, HR, 1.97; 95% CI, 1.26-3.11; P = .002), adjusted for donor age, sex, source (living vs deceased), serum creatinine level, hypertension history, and cause of death (cerebrovascular accident vs other); recipient age, ethnicity, cause of renal failure, and transplant number; panel-reactive anti-HLA antibody level; donor-recipient HLA mismatch; and cold ischemia time.

Place holder to copy figure label and caption
Figure. Association Between Donor CAV1 rs4730751 Single-Nucleotide Polymorphism Genotype and Death-Censored Allograft Failure in Original Birmingham Cohort and Independent Validation Population From Belfast
Graphic Jump Location

Data are censored when 10% of initial study numbers are reached.

The final model (Table 2) also showed relationships between increased death-censored graft failure rates and nonwhite recipient ethnicity, younger recipients, and female donors. A U-shaped relationship was seen between donor age and graft failure rates, with increased rates at the 2 extremes of donor age.

Table Graphic Jump LocationTable 2. Final Multivariate Cox Model of Death-Censored Renal Allograft Survivala

No other donor or recipient tag SNPs were associated with graft failure (log-rank P > .20 for all). Further analysis in a subgroup of 671 patients who were recipients of deceased donor kidney transplants revealed donor AA genotype (vs non-AA) to be associated with greater risk of graft failure in univariable and multiple regression analysis (HR, 1.85; 95% CI, 1.13-3.01; P = .01 and HR, 1.77; 95% CI, 1.08-2.90; P = .02, respectively) (Table 2).

Histological Assessment of Failed Allografts

Causes of graft failure in the Birmingham cohort were reviewed using the methods and reporting strategy of El-Zoghby et al8 (Table 3). Histological assessment had been performed in 155 of 184 grafts that failed, and graft loss due to predominant interstitial fibrosis was increased in recipients of genotype AA (13/22 [59%]) vs non-AA (42/162 [26%]) kidneys (P = .003). Other causes of graft failure (shown for comparison and consistency) were similar between donor genotypes. Biopsies demonstrating interstitial fibrosis usually also demonstrated arterial wall thickening (11/13 for donor genotype AA; 37/42 for non-AA donor genotype).

Table Graphic Jump LocationTable 3. Causes of Graft Failure Across Donor Genotype Groups
Validation Study

To validate the association of this gene region with graft survival, we sought independent validation at the rs4730751 locus in the Belfast cohort (Table 1). All donors and recipients were white and all donors were deceased. Greater than 98% of genotypes were successfully called and genotype distribution was within Hardy-Weinberg equilibrium. During a total follow-up of 238 months (median, 69 months; interquartile range, 24-124 months), there were 301 death-censored graft failures. Kaplan-Meier analysis of death-censored allograft failure revealed significant differences in graft survival between donor genotypes, and, as in the Birmingham cohort, poorer graft survival was seen in recipients whose donors displayed genotype AA (log-rank P = .001) (Figure). Overall graft failure rates were 67% (32/48) for donor genotype AA, 42% (150/358) for donor genotype CC, and 44% (119/273) for donor genotype AC. The multiple regression model (Table 2) also revealed donor AA genotype (vs non-AA) to be associated with greater risk of graft failure (HR, 1.56; 95% CI, 1.07-2.27; P = .02).

No association in either cohort was seen between all-cause mortality and polymorphism at the donor rs4730751 SNP (log-rank P > .20).

Secondary Analyses

In light of this validated finding, selected secondary analyses were conducted. In contrast to the Birmingham cohort, increased death-censored graft failure rates were also associated with recipient polymorphism at rs4730751 (for recipient AA vs non-AA genotype, HR, 2.23; 95% CI, 1.62-3.07; P < .001 [adjusted analysis]) in the Belfast group.

There was no difference in genotype frequency between white donors and white recipients in either cohort (χ2P > .20), suggesting that the rs4730751 SNP is not associated with end-stage renal disease.

In the Birmingham cohort, no association was seen between donor polymorphism at rs4730751 and either delayed graft function or biopsy-proven acute rejection in the first year (χ2= 0.745; P = .70 and χ2= 1.875; P = .80, respectively). This analysis was therefore not undertaken in the Belfast cohort.

To our knowledge, this is the first report to identify and validate an association between the genome of a renal transplant organ and long-term allograft survival. A tagging approach for a biologically plausible “candidate gene” was taken, investigating polymorphism of the gene encoding CAV1, which is involved in tissue fibrosis as well as vascular proliferation, important contributors to renal transplant failure. The association between donor and recipient polymorphism and graft outcome was investigated because both donor- and recipient-derived cells play a role in graft damage.10 The histological data lend support to the hypothesis that this polymorphism is likely in linkage disequilibrium with a DNA variant mediating its effect by promoting tissue fibrosis within the donor kidney. There was no evidence that the donor SNP (or one in linkage) exerted a deleterious effect by promoting either acute rejection or delayed graft function.

The potential clinical importance of this donor SNP is highlighted by the observation that it was associated with a risk of death-censored graft loss comparable with that of female donor sex (vs male) and donor hypertension, both established risk factors for graft loss.13 Although a minority of donors displayed the AA genotype (approximately 10%), this gene variant nevertheless shows potential in identifying a subpopulation at higher risk of allograft failure, and further investigation of its role in the etiology of renal fibrosis may be warranted.

The finding in the Belfast cohort that recipient (as well as donor) AA genotype at CAV1 was associated with graft failure is interesting in light of the observation that recipient cells may contribute to allograft fibrosis. However, this effect was not demonstrated in the Birmingham cohort; therefore, at this time no firm inference can be made with regard to this observation.

The face validity of the study is strengthened by the observation that variables commonly accepted to be associated with graft failure from prior studies were also identified in this study, in particular the effect of donor age, donor sex, and recipient ethnicity.

In conclusion, these studies suggest that polymorphism at rs4730751 of CAV1 may play a role in kidney transplant outcomes. This finding has implications for renal transplantation with regard to the mechanisms underlying graft failure and in the identification of genetic biomarkers. In addition, because renal transplantation may be viewed as an in vivo model of accelerated tissue fibrosis, this study may have relevance for other renal and nonrenal diseases characterized by tissue fibrosis. Finally, this study may also have implications for other conditions in which CAV1 is thought to play a role, in particular vascular disease and neoplasia.1

Corresponding Author: Richard Borrows, MB, Department of Nephrology and Kidney Transplantation, University Hospital Birmingham, Queen Elizabeth Hospital, Birmingham B15 2TH, England (richard.borrows@uhb.nhs.uk).

Author Contributions: Dr Borrows 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 concept and design: Moore, Simmonds, Briggs, Ball, Cockwell, Gough, Borrows.

Acquisition of data: Moore, McKnight, Simmonds, Courtney, Hanvesakul, Brand, Briggs, Maxwell, Borrows.

Analysis and interpretation of data: Moore, McKnight, Simmonds, Brand, Ball, Patterson, Maxwell, Gough, Borrows.

Drafting of the manuscript: Moore, Hanvesakul, Gough, Borrows.

Critical revision of the manuscript for important intellectual content: Moore, McKnight, Simmonds, Courtney, Brand, Briggs, Ball, Cockwell, Patterson, Maxwell, Gough, Borrows.

Statistical analysis: McKnight, Brand, Patterson.

Obtained funding: McKnight, Cockwell, Maxwell, Borrows.

Administrative, technical, or material support: Moore, McKnight, Simmonds, Hanvesakul, Brand, Briggs, Maxwell, Gough.

Study supervision: Simmonds, Brand, Briggs, Ball, Cockwell, Maxwell, Gough, Borrows.

Financial Disclosures: None reported.

Funding/Support: Funding was provided by the University Hospital Birmingham Charities. Dr Moore is funded by an unrestricted educational grant from Novartis Pharmaceuticals.

Role of the Sponsor: The funders had no involvement in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.

Thomas CM, Smart EJ. Caveolae structure and function.  J Cell Mol Med. 2008;12(3):796-809
PubMed   |  Link to Article
Razani B, Woodman SE, Lisanti MP. Caveolae: from cell biology to animal physiology.  Pharmacol Rev. 2002;54(3):431-467
PubMed   |  Link to Article
Schwencke C, Braun-Dullaeus RC, Wunderlich C, Strasser RH. Caveolae and caveolin in transmembrane signaling: implications for human disease.  Cardiovasc Res. 2006;70(1):42-49
PubMed   |  Link to Article
Wang XM, Zhang Y, Kim HP,  et al.  Caveolin-1: a critical regulator of lung fibrosis in idiopathic pulmonary fibrosis.  J Exp Med. 2006;203(13):2895-2906
PubMed   |  Link to Article
Del Galdo F, Lisanti MP, Jimenez SA. Caveolin-1, transforming growth factor-β receptor internalization, and the pathogenesis of systemic sclerosis.  Curr Opin Rheumatol. 2008;20(6):713-719
PubMed   |  Link to Article
Di Guglielmo GM, Le Roy C, Goodfellow AF, Wrana JL. Distinct endocytic pathways regulate TGF-β receptor signalling and turnover.  Nat Cell Biol. 2003;5(5):410-421
PubMed   |  Link to Article
Park HC, Yasuda K, Ratliff B,  et al.  Postobstructive regeneration of kidney is derailed when surge in renal stem cells during course of unilateral ureteral obstruction is halted.  Am J Physiol Renal Physiol. 2010;298(2):F357-F364
PubMed   |  Link to Article
El-Zoghby ZM, Stegall MD, Lager DJ,  et al.  Identifying specific causes of kidney allograft loss.  Am J Transplant. 2009;9(3):527-535
PubMed   |  Link to Article
Nankivell BJ, Borrows RJ, Fung CL, O’Connell PJ, Allen RD, Chapman JR. The natural history of chronic allograft nephropathy.  N Engl J Med. 2003;349(24):2326-2333
PubMed   |  Link to Article
Rienstra H, Boersema M, Onuta G,  et al.  Donor and recipient origin of mesenchymal and endothelial cells in chronic renal allograft remodeling.  Am J Transplant. 2009;9(3):463-472
PubMed   |  Link to Article
Clarke GM, Carter KW, Palmer LJ, Morris AP, Cardon LR. Fine mapping versus replication in whole-genome association studies.  Am J Hum Genet. 2007;81(5):995-1005
PubMed   |  Link to Article
de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies.  Nat Genet. 2005;37(11):1217-1223
PubMed   |  Link to Article
Saidi RF, Elias N, Kawai T,  et al.  Outcome of kidney transplantation using expanded criteria donors and donation after cardiac death kidneys: realities and costs.  Am J Transplant. 2007;7(12):2769-2774
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure. Association Between Donor CAV1 rs4730751 Single-Nucleotide Polymorphism Genotype and Death-Censored Allograft Failure in Original Birmingham Cohort and Independent Validation Population From Belfast
Graphic Jump Location

Data are censored when 10% of initial study numbers are reached.

Tables

Table Graphic Jump LocationTable 1. Characteristics of the Study Cohortsa
Table Graphic Jump LocationTable 3. Causes of Graft Failure Across Donor Genotype Groups
Table Graphic Jump LocationTable 2. Final Multivariate Cox Model of Death-Censored Renal Allograft Survivala

References

Thomas CM, Smart EJ. Caveolae structure and function.  J Cell Mol Med. 2008;12(3):796-809
PubMed   |  Link to Article
Razani B, Woodman SE, Lisanti MP. Caveolae: from cell biology to animal physiology.  Pharmacol Rev. 2002;54(3):431-467
PubMed   |  Link to Article
Schwencke C, Braun-Dullaeus RC, Wunderlich C, Strasser RH. Caveolae and caveolin in transmembrane signaling: implications for human disease.  Cardiovasc Res. 2006;70(1):42-49
PubMed   |  Link to Article
Wang XM, Zhang Y, Kim HP,  et al.  Caveolin-1: a critical regulator of lung fibrosis in idiopathic pulmonary fibrosis.  J Exp Med. 2006;203(13):2895-2906
PubMed   |  Link to Article
Del Galdo F, Lisanti MP, Jimenez SA. Caveolin-1, transforming growth factor-β receptor internalization, and the pathogenesis of systemic sclerosis.  Curr Opin Rheumatol. 2008;20(6):713-719
PubMed   |  Link to Article
Di Guglielmo GM, Le Roy C, Goodfellow AF, Wrana JL. Distinct endocytic pathways regulate TGF-β receptor signalling and turnover.  Nat Cell Biol. 2003;5(5):410-421
PubMed   |  Link to Article
Park HC, Yasuda K, Ratliff B,  et al.  Postobstructive regeneration of kidney is derailed when surge in renal stem cells during course of unilateral ureteral obstruction is halted.  Am J Physiol Renal Physiol. 2010;298(2):F357-F364
PubMed   |  Link to Article
El-Zoghby ZM, Stegall MD, Lager DJ,  et al.  Identifying specific causes of kidney allograft loss.  Am J Transplant. 2009;9(3):527-535
PubMed   |  Link to Article
Nankivell BJ, Borrows RJ, Fung CL, O’Connell PJ, Allen RD, Chapman JR. The natural history of chronic allograft nephropathy.  N Engl J Med. 2003;349(24):2326-2333
PubMed   |  Link to Article
Rienstra H, Boersema M, Onuta G,  et al.  Donor and recipient origin of mesenchymal and endothelial cells in chronic renal allograft remodeling.  Am J Transplant. 2009;9(3):463-472
PubMed   |  Link to Article
Clarke GM, Carter KW, Palmer LJ, Morris AP, Cardon LR. Fine mapping versus replication in whole-genome association studies.  Am J Hum Genet. 2007;81(5):995-1005
PubMed   |  Link to Article
de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies.  Nat Genet. 2005;37(11):1217-1223
PubMed   |  Link to Article
Saidi RF, Elias N, Kawai T,  et al.  Outcome of kidney transplantation using expanded criteria donors and donation after cardiac death kidneys: realities and costs.  Am J Transplant. 2007;7(12):2769-2774
PubMed   |  Link to Article

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