Original Article

Genes and Immunity (2012) 13, 232–238; doi:10.1038/gene.2011.82; published online 22 December 2011

Role of MYH9 and APOL1 in African and non-African populations with lupus nephritis

C P Lin1, I Adrianto1, C J Lessard1,2, J A Kelly1, K M Kaufman1,2,3, J M Guthridge1, B I Freedman4, J-M Anaya5, M E Alarcón-Riquelme1,6, on behalf of the BIOLUPUS and GENLES Networks, B A Pons-Estel7, J Martin8, S Glenn1, A Adler1, S-C Bae9, S-Y Park9, S-Y Bang9, Y-W Song10, S A Boackle11, E E Brown12, J C Edberg12, G S Alarcón12, M A Petri13, L A Criswell14, R Ramsey-Goldman15, J D Reveille16, L M Vila17, G S Gilkeson18, D L Kamen18, J Ziegler19, C O Jacob20, A Rasmussen1, J A James1,2, R P Kimberly12, J T Merrill21, T B Niewold22, R H Scofield1,2,3, A M Stevens23,24, B P Tsao25, T J Vyse26, C D Langefeld19, K L Moser1,2, J B Harley27,28, P M Gaffney1 and C G Montgomery1

  1. 1Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
  2. 2College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
  3. 3US Department of Veterans Affairs Medical Center, Oklahoma City, OK, USA
  4. 4Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
  5. 5Center for Autoimmune Diseases Research (CREA), Universidad del Rosario, Bogota, Colombia
  6. 6Pfizer, Universidad de Granada - Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain
  7. 7Sanatorio Parque, Rosario, Argentina
  8. 8Instituto de Parasitologia y Biomedicina Lopez-Neyra, Consejo Superior de Investigaciones Cientificas (CSIC), Granada, Spain
  9. 9Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea
  10. 10Division of Rheumatology, Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
  11. 11Division of Rheumatology, University of Colorado Denver, Aurora, CO, USA
  12. 12Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
  13. 13Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
  14. 14Rosalind Russell Medical Research Center for Arthritis, University of California San Francisco, San Francisco, CA, USA
  15. 15Division of Rheumatology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
  16. 16Rheumatology and Clinical Immunogenetics, University of Texas Health Science Center at Houston, Houston, TX, USA
  17. 17Department of Medicine, Division of Rheumatology, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico
  18. 18Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
  19. 19Department of Biostatistical Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
  20. 20Department of Medicine, University of Southern California, Los Angeles, CA, USA
  21. 21Clinical Pharmacology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
  22. 22Section of Rheumatology and Gwen Knapp Center for Lupus and Immunology Research, University of Chicago, Chicago, IL, USA
  23. 23Division of Rheumatology, Department of Pediatrics, University of Washington, Seattle, WA, USA
  24. 24Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA
  25. 25Division of Rheumatology, Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA
  26. 26Divisions of Genetics and Molecular Medicine and Immunology, Infection and Inflammatory Disease, King's College London, London, UK
  27. 27Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
  28. 28US Department of Veterans Affairs Medical Center Cincinnati, Cincinnati, OH, USA

Correspondence: Dr CG Montgomery, Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, 825 N.E. 13th Street, MS #57, Oklahoma City, OK 73104, USA. E-mail: Courtney-Montgomery@omrf.org

Received 9 May 2011; Revised 4 November 2011; Accepted 14 November 2011
Advance online publication 22 December 2011

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Abstract

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by autoantibody production and organ damage. Lupus nephritis (LN) is one of the most severe manifestations of SLE. Multiple studies reported associations between renal diseases and variants in the non-muscle myosin heavy chain 9 (MYH9) and the neighboring apolipoprotein L 1 (APOL1) genes. We evaluated 167 variants spanning MYH9 for association with LN in a multiethnic sample. The two previously identified risk variants in APOL1 were also tested for association with LN in European-Americans (EAs) (N=579) and African-Americans (AAs) (N=407). Multiple peaks of association exceeding a Bonferroni corrected P-value of P<2.03 × 10−3 were observed between LN and MYH9 in EAs (N=4620), with the most pronounced association at rs2157257 (P=4.7 × 10−4, odds ratio (OR)=1.205). A modest effect with MYH9 was also detected in Gullah (rs8136069, P=0.0019, OR=2.304). No association between LN and MYH9 was found in AAs, Asians, Amerindians or Hispanics. This study provides the first investigation of MYH9 in LN in non-Africans and of APOL1 in LN in any population, and presents novel insight into the potential role of MYH9 in LN in EAs.

Keywords:

MYH9; APOL1; lupus nephritis; systemic lupus erythematosus; multiethnic association study

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Introduction

Systemic lupus erythematosus (SLE) is a prototypic systemic autoimmune disease characterized by multisystem involvement and the development of an immune response against self-antigens, leading to tissue inflammation, destruction and often end-organ damage. SLE is more prevalent in females compared with males (9:1) and in African-American (AA), Asian (AS) and Hispanic (HI) populations compared with EuropeanAmericans (EA).1, 2, 3 Patients classified with SLE manifest a minimum of 4 out of 11 criteria set by the American College of Rheumatology4, 5 with neurological, renal and hematological manifestations representing more severe disease. Lupus nephritis (LN) is one of the most severe complications, drastically increasing the morbidity and mortality of SLE patients,6 with up to 60% of adult and 80% of pediatric SLE cases developing renal abnormalities during the course of the disease.7, 8 The incidence of LN is higher in AA, HI and AS compared with populations of European ancestry: one study showed that incidences of renal disease for AA and HI are 68.9% and 60.6%, respectively, compared with EA (29.1%) after 5.5 years of follow-up;9 a similar elevated incidence in AS has also been confirmed.10, 11

Renal dysfunction is not an exclusive manifestation of SLE; it is a feature of a large number of diseases that may share underlying mechanisms or predisposing genetic factors. There have been recent reports of genetic association of variants located within the non-muscle myosin heavy chain 9 (MYH9) gene on chromosome 22 and a variety of renal diseases including focal segmental glomerulosclerosis (FSGS), HIV-associated nephropathy, hypertension-attributed end-stage renal disease (H-ESRD) and diabetic and non-diabetic ESRD in African-derived populations.12, 13, 14, 15 In addition, several monogenic syndromes with point mutations in MYH9 have been characterized by thrombocytopenia, leukocyte abnormalities and renal failure.16 Recent studies of FSGS and H-ESRD in AAs,17, 18 however, suggest that the pronounced association of the MYH9 E-1 risk haplotype (rs4821480, rs2032487, rs4821481 and rs3752462) is primarily due to strong linkage disequilibrium (LD) with two independent genetic variants (rs73885319 and rs71785313) within the neighboring apolipoprotein L1 (APOL1) gene.17, 18, 19 Although one study has assessed association between LN and MYH9 in AAs (and found none),20 no such study has been conducted for either MYH9 or APOL1 in non-African populations. It was therefore the aim of this study to investigate the role of these genes in African and non-African SLE populations with LN. Specifically, we sought to assess association of LN with MYH9 and evaluate the association between 2 variants within APOL1 in EA and AA samples and 167 MYH9 variants and LN in a large multiethnic group sample comprising of EA, AA, AS, HI, Amerindian and Gullah (a unique AA population from the coastal regions of South Carolina and Georgia) samples.

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Results

Association analysis of single-nucleotide polymorphisms (SNPs) within MYH9 comparing LN cases and healthy controls resulted in no significance in the AA, HI, AS or Amerindian populations (Figure 1, Supplementary Figure 1 and Supplementary Table 5). The EA population yielded multiple SNPs exceeding the Bonferroni correction (P<2.03 × 10−3) with the significant signals of P-value<10−3 at rs2157257 (P=4.7 × 10−4, odds ratio (OR)=1.205), rs5750250 (P=5.4 × 10−4, OR=1.472), rs2413396 (P=6.74 × 10−4, OR=1.327) and rs4820232 (P=9.20 × 10−4, OR==1.196), all centered at approximately 35.04Mb (Figure 1 and Table 1). In addition, two of the E-1 haplotype14 SNPs (rs4821480, rs2032487) were also below the Bonferroni significance threshold (Table 1). A modest association was also detected in the Gullah (70 LN cases/122 healthy controls) at 35.05Mb, with the strongest association observed at rs8136069 (P=1.923 × 10−3, OR=2.304, 95% confidence interval=1.360–3.904). Results of analyses comparing LN cases with SLE cases without LN were very similar, save a slight increase in the number of significant SNPs (Supplementary Table 7a and b).

Figure 1.
Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Summary of association analysis for MYH9 SNPs. Plots of SNPs within the MYH9 gene associated with lupus nephritis in (a) European American, (b) African American and (c) Gullah populations. Genotyped SNPs are represented by circles and imputed SNPs are shown in rectangles. The recombination rate calculated from the combined CEU, YRI and JPT+CHB Hapmap data is denoted by the purple solid line. The dotted line refers to the Bonferroni threshold of significance.

Full figure and legend (223K)


To further elucidate the effects observed in EA and to determine if any particular SNP was driving the association observed in the region independently, conditional association analyses were performed. Based on LD (r2>0.8) (Figure 2), we incorporated each of the associated SNPs in the region with P-value<1 × 10−3 (rs2413396, rs2157257, rs5750250 or rs4820232) as covariates, one at a time in our model. The effect of rs2413396 became not significant (P>1 × 10−1) when conditioning on rs5750250 and the converse showed similar results (Table 2). Similarly, the signal diminished at rs2157257 when conditioning on rs4820232. This implies the effects of rs2413396 and rs5750250 or rs2157257 and rs4820232 are non-independent. Both rs2413396 and rs5750250 remained significant upon conditioned on any of rs2157257 and rs4820232B. Likewise, rs2157257 and rs4820232 were still significant after conditioning on either rs2413396 or rs5750250. Furthermore, conditioning on both rs2157257 and rs5750250, the association signals reduced to baseline (P>1 × 10−1) (Table 2). Therefore, the two main effects exist in the region tagged by (rs2413396, rs5750250) and (rs2157257, rs4820232) as effect 1 and effect 2, respectively, (Figure 2).

Figure 2.
Figure 2 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

The linkage disequilibrium for significant SNPs in European Americans. This plot shows the pair-wise LD between all markers given in the figure. SNPs in red box represent effect 1, and SNPs in green box represent effect 2. The intensities of the LD between SNPs are depicted in orange (effect 1), green (effect 2) and black (between effect 1 and effect 2).

Full figure and legend (248K)


In order to differentiate association signals observed between the AA and Gullah populations, we refined our analysis to include only those subjects with >90% African ancestry in the AA (105 LN cases/312 healthy controls) and Gullah (42 LN cases/69 healthy controls) samples. The association signals in the AA and the Gullah samples enriched for African ancestry were less significant than that of the full set of samples (Supplementary Figure 3), perhaps suggesting the influence of European admixture. While we were unable to examine variants within APOL1 in the Gullah, only a nominal effect at rs71785313 (P=0.023) of APOL1 was seen in the AA sample (Supplementary Table 6). Note too that the association P-values of our two genotyped SNPs within the MYH9 E-1 risk haplotype,14 known to tag APOL1 (Supplementary Figure 2), were also insignificant (rs4821481, P=0.1759; rs3752462, P=0.5104) in AA. These results support our above conclusion of no association between LN and either MYH9 or APOL1 in AA.

The previously reported associations of MYH9 and APOL1 with kidney disease were described in rather homogeneous phenotypes with severe renal failure (H-ESRD and FSGS); we speculated that the lack of significant association with MYH9 and APOL1 in the AA might be due to a wider severity spectrum of renal dysfunction associated with SLE. To explore this possibility, an analysis of a subset of patients for whom we had information on dialysis or kidney transplant (indicating ESRD) was performed. Fisher's exact tests of variants within MYH9 produced a nominally significant P-value of 0.041 at rs10483194 in the EA (30 LN cases/3,491 healthy controls) and P=0.044 at rs739095 in the AA (67 LN cases/1,811 healthy controls). However, we found no significant association within the APOL1 variants (57 LN cases/202 healthy controls) (Supplementary Table 8). We repeated Fisher's exact tests using non-LN SLE as controls, results were not considerably different, except a marginal P-value was found at an APOL1 variant rs71785313 (P=0.0418) (Supplementary Table 8). It should be noted that even with this small sample, given the magnitude of the ORs previously reported for APOL1,17 we had greater than 85% power to detect an effect at a P-value of 0.01. Thus it suggests there is no effect of APOL1 and only a slight potential for an effect of MYH9 in LN, ESRD patients.

Finally, on the basis of a previous report of germline MYH9 mutations in a patient with SLE and end-stage renal disease,21 we performed an exploratory analysis to address the potential role of MYH9 in a broader class of SLE-related target organ damage. Specifically, two subsets of SLE patients of European descent with renal disease and/or thrombocytopenia as well as with renal disease and/or serositis in addition to healthy controls were evaluated for association with MYH9. The significance of our strongest effect at rs2413396 was increased when adding cases with thrombocytopenia (P=2.46 × 10−4, 1351 cases/3491 healthy controls) compared with renal disease alone (P=6.74 × 10−4, 1129 LN cases/3491 healthy controls), with loss of significance when adding patients with serositis compared with renal disease alone (P=1.86 × 10−2, 1984 cases/3491 healthy controls) (Supplementary Table 9). The results of the same subgroup analyses using non-LN SLE cases as ‘controls’ were similar, an increase in significance by two orders of magnitude at rs10483194 was observed when adding cases with thrombocytopenia to the renal diseased patients (1351 cases/1006 non-LN SLE), however, when adding patients with serositis, significance increased marginally as well (1984 cases and 606 non-LN SLE) (Supplementary Table 9).

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Discussion

MYH9 encodes the motor protein MYH class II and isoform A, and is expressed mainly in podocytes, peritubular capillaries and tubules of mature kidney. It is responsible for cell polarity, trafficking and cell architecture. Dysregulation may lead to renal complications and eventual glomerulosclerosis. It may be implicated in SLE via its role in phagocytosis of apoptotic leukocytes.22 Further, MYH9 is associated with a variety of diverse syndromes that share leukocyte inclusions, abnormally large platelets, thrombocytopenia and bleeding tendency; many of which also include glomerulopathy with progressive renal failure.23, 24, 25 More recently, MYH9 was implicated in ESRD and FSGS in populations of African ancestry13, 15, 26 with even stronger association with two coding variants in the neighboring APOL1 gene.17, 18 Its involvement in LN in AA populations has previously been refuted, and the results of this study support this conclusion. However, the role of MYH9 in LN in non-African populations or of APOL1 in LN in any ethnic group has not been previously studied.

While potential weaknesses of this report include limited sample size for the Gullah, HI and Amerindian populations and further replication studies are needed, we interrogated the largest number of individuals of these ethnic groups available at the time. Further, the absence of information about dialysis and/or kidney transplant in the medical records for the AS, Gullah, HI and Amerindian limits the conclusions we can draw about those populations.

In summary, this report provides the first evidence of association between LN and MYH9 variants in a large study population of EA cases and healthy controls. Two independent effects account for this association, located in the intronic region approximately 31kb away from the 3′ end of MYH9. Unlike previous studies in AAs, this signal is not explained by variants within the neighboring APOL1 gene. The two APOL1 coding variants accounting for association between MYH9 and renal disease in AAs were monomorphic in the EA sample as they are known to be present in very low frequencies (<0.5%) in general EA populations. Moreover, results of our analyses of SLE patients with SLE-related renal dysfunction and thrombocytopenia suggest a broader involvement of MYH9 in lupus complications. Finally, this report identified the first evidence of suggestive association between APOL1 and LN with a nominally significant P<0.05 in AAs. Our results highlight the complex behavior of a single gene across multiple disorders and racial groups, suggesting the need for additional genetic and combined gene-environment studies.

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Materials and methods

Study populations and SNP genotyping

Independent study participants were obtained through 19 national and international collaborators as part of the Large Lupus Association Study 2 (LLAS2). Their respective Institutional Review Boards approved all recruitment studies. Only subjects who signed informed consent forms were included in the study. All SLE patients fulfilled the revised 1997 American College of Rheumatology for classification of SLE5 and satisfied the renal criterion of either (1) persistent proteinuria >0.5g per day (24h) or persistent >3+ if quantification was not performed or (2) presence of urinary cellular casts.5 The LLAS2 study included 8922 SLE cases, 3212 of which fulfilled the renal ACR SLE criterion (Supplementary Table 1) and 4505 were classified as SLE without renal complication, thus comprising the sample analyzed in this report and referred to as renal cases and non-renal SLE cases, respectively. Renal failure documentation based on medical record information of dialysis and/or kidney transplantation identified a subset of 115 patients with severe LN. The control population consisted of 8077 unrelated, healthy, population-based controls with no blood relatives with SLE, bringing the total subjects studied herein to 15794.

A total of 78 MYH9 SNPs, including eight previously associated with ESRD,13 were genotyped in 7717 SLE cases and 8077 healthy controls from six different ethnic groups: EA, AA, AS, HI, Amerindian and Gullah (Supplementary Table 1). The Gullah are a population of AAs residing in the coastal regions of South Carolina and Georgia who exhibit both unique African ancestral origins and lesser European admixture.27 Note, that all SNPs in the NCBI 36 database, within the MYH9 region were submitted for inclusion in our custom genotyping assay. The 78 SNPs presented here were those that met Illumina QC standards. All SNPs were in moderate LD (r2 or D’<0.80) with one another. Data were generated using custom designed Illumina iSelect Infinium II genotyping arrays on the BeadStation iScan (Illumina, San Diego, CA, USA) at the Oklahoma Medical Research Foundation (OMRF). In addition, two APOL1 H-ESRD and FSGS risk variants (rs73885319 (G1) and rs71785313 (G2))17 were genotyped using custom TaqMan SNP genotyping Assays (Supplementary Method 1) in a subset of 407 AA (205 LN cases and 202 healthy controls) and 579 EA subjects (205 LN cases and 374 healthy controls) from the above cohort for which additional DNA was available.

Quality control

To perform global ancestry estimation, a panel of 347 genomic ancestry informative markers (Supplementary Table 2) was genotyped28, 29 to evaluate the population ancestry and any possible hidden population substructure. The SNPs available in the MYH9 region are 650kb away from the nearest ancestry informative markers, and we were therefore unable to accurately estimate the local ancestry in this region.

SNPs included in the analysis had a call rate >90%, P>0.001 for Hardy–Weinberg proportion in controls, and minor allele frequencies>0.001. Samples with low call rate (<90%), sample heterozygosity outliers (>5 standard deviations from the mean), extreme population outliers (based on global ancestry estimation and principal component analysis), sample duplicates (proportion of alleles shared identity-by-descent>0.4) and gender discrepancy between reported gender and genetic data were excluded from analysis (Supplementary Method 2 and Supplementary Table 3). After quality control, the final data set comprised 77 MYH9 SNPs, 2 APOL1 SNPs, 262 ancestry informative markers, 3013 LN cases, 4262 non-LN SLE cases and 7492 healthy controls (Table 3).


Ancestry estimation

We performed global ancestry estimation for every individual in our study using ADMIXMAP.30, 31, 32 This software adopts a combination of classical and Bayesian frameworks, and calculated ancestry information through a Markov Chain Monte Carlo (MCMC) simulation using 262 ancestry informative markers and the allele frequencies obtained from the HapMap release 27. Global ancestry estimates were computed for AS, European, Amerindian and West African ancestries.

Imputation method

Imputation was performed over a 105kb interval flanking the MYH9 gene on chromosome 22 from 35Mb to 35.15Mb using IMPUTE2.33, 34, 35 A collection of 77 SNPs was used as the source of observed genotypes and data from the 1000 Genomes Project and the Phase III HapMap release 2 were used as the reference panels. IMPUTE2 computes posterior probabilities for the three possible genotypes (that is, AA, AB and BB) and then converts posterior probabilities to the most likely genotypes with a threshold of 0.9. Imputed SNPs with low imputation accuracy (information measure <0.5 and <90% average certainty of the most probable genotypes) were removed from the analysis. We chose to call genotypes so as to be able to construct haplotypes and calculate LD. We did, however, verify that this was indeed a conservative approach by also analyzing SNP ‘dose’ using SNPTEST36, 37, 38 (Supplementary Table 10). After imputation and quality control evaluation, as described above, each data set comprised a minimum of 89 SNPs for each of the populations (the numbers varied based on LD structure) and is shown in Supplementary Table 4.

Association analysis

To investigate the genotype–phenotype relationship of MYH9 and APOL1 polymorphisms in different racial groups, logistic regression including adjustment for gender and global ancestry (quantified in terms of European, African and AS ancestry) was performed to test for association for MYH9 and APOL1 SNPs assuming additive, dominant and recessive modes of inheritance using PLINK.17, 18, 19, 39, 40 We performed analyses in two ways: (1) using healthy population-based participants as controls and (2) using SLE, non-renal cases as controls. However, because the results were not significantly different, we concentrate those from the former, much larger, data set in the main text. All reported Wald χ2 P-values, 95% confidence intervals and ORs were calculated from the logistic regression model. We controlled for experiment-wide type I error by establishing Bonferroni correction thresholds for significance of 2.03 × 10−3 for MYH9 and 3 × 10−2 for APOL1, based on the maximum average number of tests across all populations and weighted for non-independence (that is, D’>0.80). Pair-wise LD measures for the MYH9 and APOL1 SNPs were assessed by the D’ values using Haploview 4.2.41 Finally, we conducted a conditional association analysis using PLINK,17, 18, 19, 39, 40 adjusting for gender and global ancestry to determine whether the effects seen in EA were independent.

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Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

We thank all study participants, SLE and controls in this study as well as all the staff who assisted in their recruitment. We gratefully acknowledge the following individuals for their generous contribution in genotyping samples: Dr Peter K Gregersen, Drs Sandra D’Alfonso (Italy), Rafaella Scorza (Italy), Peter Junker and Helle Laustrup (Denmark), Marc Bijl (Holland), Emoke Endreffy (Hungary), Carlos Vasconcelos and Berta Martins da Silva (Portugal), Ana Suarez and Carmen Gutierrez (Spain), Iñigo Rúa-Figueroa (Spain) and Dr Cintia Garcilazo (Argentina). For the AADEA collaboration: Norberto Ortego-Centeno (Spain), Juan Jimenez-Alonso (Spain), Enrique de Ramon (Spain) and Julio Sanchez-Roman (Spain). For the GENLES collaboration: Dr Mario Cardiel (Mexico), Dr Ignacio García de la Torre (Mexico), Marco Maradiaga (Mexico), José F Moctezuma (Mexico), Dr Eduardo Acevedo (Peru), Cecilia Castel and Mabel Busajm (Argentina), Jorge Musuruana (Argentina). Other participants from the Argentine Collaborative Group are: Hugo R Scherbarth MD, Pilar C Marino MD, Estela L Motta MD; Susana Gamron MD, Cristina Drenkard MD, Emilia Menso MD; Alberto Allievi MD, Guillermo A Tate MD; Jose L Presas MD; Simon A Palatnik MD, Marcelo Abdala MD, Mariela Bearzotti PhD; Alejandro Alvarellos MD, Francisco Caeiro MD, Ana Bertoli MD; Sergio Paira MD, Susana Roverano MD; Cesar E Graf MD, Estela Bertero PhD; Carolina Guillerón MD, Sebastian Grimaudo PhD, Jorge Manni MD; Luis J Catoggio MD, Enrique R Soriano MD, Carlos D Santos MD; Cristina Prigione MD, Fernando A Ramos MD, Sandra M Navarro MD; Guillermo A Berbotto MD, Marisa Jorfen MD, Elisa J Romero PhD; Mercedes A Garcia MD, Juan C Marcos MD, Ana I Marcos MD; Carlos E Perandones MD, Alicia Eimon MD; Cristina G Battagliotti MD. We also would like to knowledge Mary C Comeau MA; Miranda C Marion MA; Paula S Ramos PhD; Summer Frank MPH and Mai Li Zhu MS for their assistance in genotyping, quality control analyses and clinical data management, and everyone at the Lupus Family Registry and Repository (LFRR) for data collection and maintenance. The work has been funded principally by the US National Institutes of Health grants R01 AI063274 and R01 AR056360 (PMG); R01 AR043274 (KLM); N01 AR62277, R37 24717, R01 AR042460, P01 AI083194, P20 RR020143, R01 DE018209 (JBH); P01 AR49084 (RPK and EEB); R01 AR33062 (RPK); P30 AR055385 (EEB); K08 AI083790, LRP AI071651, UL1 RR024999 (TBN); R01CA141700, RC1 AR058621 (MEAR); R01AR051545-01A2, ULI RR025014-02 (AMS); P30 AR053483, N01 AI50026 (JAJ and JMG); P20 RR015577 (JAJ); R21 AI070304 (SAB); P30 RR031152, U19 AI082714, P30 AR053483, RC1 AR05884 (JAJ and JMG); R01 AR43814 (BPT); P60 AR053308, M01 RR-00079 (LAC); R01 AR043727, UL1 RR025005 (MAP); K24 AR002138, P60-2 AR30692, P01 AR49084, UL1RR025741 (RRG); UL1 RR029882, P60 AR049459 (GSG and DLK). A portion of this study was supported by a grant of the Korea Healthcare Technology R&D Project, Ministry for Health and Welfare, Republic of Korea (A080588; SCB). Additional support was granted from the Alliance for Lupus Research (KLM); Merit Award from the US Department of Veterans Affairs (JBH and GSG); the Swedish Research Council for Medicine, Gustaf Vth-80th Jubilee Fund and Swedish Association Against Rheumatism, Instituto de Salud Carlos III, Oklahoma Center for Advancement of Science and Technology (OCAST) HR09-106 (MEAR); the European Science Foundation funds the BIOLUPUS network (MEAR coordinator); Federico Wilhelm Agricola Foundation Research grant (BPE); The Barrett Scholarship Fund OMRF (CJL); Lupus Research Institute (TBN, BPT); The Alliance for Lupus Research (TBN, LAC, MEAR and COJ); the Arthritis National Research Foundation Eng Tan Scholar Award (TBN); Arthritis Foundation (PMG and AMS); the Lupus Foundation of Minnesota (PMG and KLM); the Wellcome Trust (TJV); Arthritis Research UK (TJV); Kirkland Scholar Award (LAC, JAJ) and Wake Forest University Health Sciences Center for Public Health Genomics (CDL). The work reported on in this publication has been in part financially supported by the ESF, in the framework of the Research Networking Programme European Science Foundation-The Identification of Novel Genes and Biomarkers for Systemic Lupus Erythematosus (BIOLUPUS) 07-RNP-083.

Supplementary Information accompanies the paper on Genes and Immunity website