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Human Molecular Genetics Pages 639-644  

Genome-wide screen for systemic lupus erythematosus susceptibility genes in multiplex families
Introduction
Results
Discussion
Materials And Methods
   Subjects
   PCR and genotyping
   Linkage analysis
Acknowledgements
References

Genome-wide screen for systemic lupus erythematosus susceptibility genes in multiplex families

Genome-wide screen for systemic lupus erythematosus susceptibility genes in multiplex families

Ruty Shai, Francisco P. Quismorio Jr, Lily Li, Oh-Joong Kwon, John Morrison1, Daniel J. Wallace2, C. Michael Neuwelt3, Chaim Brautbar4, W. James Gauderman1 and Chaim O. Jacob*

Division of Rheumatology, Department of Medicine and 1Division of Biostatistics, Department of Preventive Medicine, University of Southern California School of Medicine, 2011 Zonal Avenue, HMR 711, Los Angeles, CA 90033, USA, 2Cedar Sinai Rheumatology Group, Los Angeles, CA 90048, USA, 3The East Bay Rheumatology Medical Group, San Leandro, CA 94578, USA and 4Haddasa Medical School, Jerusalem, Israel

Received November 16, 1998; Revised and Accepted January 15, 1999

Systemic lupus erythematosus (SLE) is the prototype of human autoimmune diseases. Its genetic component has been suggested by familial aggregation ([lambda]s = 20) and twin studies. We have screened the human genome to localize genetic intervals that may contain lupus susceptibility loci in a sample of 188 lupus patients belonging to 80 lupus families with two or more affected relatives per family using the ABI Prism linkage mapping set which includes 350 polymorphic markers with an average spacing of 12 cM. Non-parametric multipoint linkage analysis suggests evidence for predisposing loci on chromosomes 1 and 18. However, no single locus with overwhelming evidence for linkage was found, suggesting that there are no ‘major’ susceptibility genes segregating in families with SLE, and that the genetic etiology is more likely to result from the action of several genes of moderate effect. Furthermore, the support for a gene in the 1q44 region as well as in the 1p36 region is clearly found only in the Mexican American families with SLE but not in families of Caucasian ethnicity, suggesting that consideration of each ethnic group separately is crucial.

INTRODUCTION

Autoimmune diseases are common chronic conditions which involve immune attack of one or more organ systems and affect almost 5% of the population. Systemic lupus erythematosus (SLE) is considered to be the prototype of human autoimmune diseases. It is a disorder of generalized autoimmunity with female predominance, and it is characterized by multisystem organ involvement, polyclonal B cell activation and the production of autoantibodies against a wide range of nuclear, cytoplasmic and cell surface autoantigens. The pathogenesis of SLE is not well understood, but a pronounced difference in concordance rates for SLE between monozygotic and dizygotic twins (1,2) provides strong evidence for the role of genetic factors in the etiology of SLE. Furthermore, clustering of disease in families, as observed for SLE, can be caused by sharing genetic factors. The degree of clustering of a disease in families can be estimated from the ratio of the risk to siblings of patients with the disease to the risk in the general population. If this ratio, [lambda]s, is close to 1.0, then there is no evidence for familial clustering. However, in most autoimmune diseases, the [lambda]s-value greatly exceeds 1.0 (3). The [lambda]s-value for SLE is estimated to be 20 (3,4). For comparison, the [lambda]s-values estimated for other autoimmune diseases are: 8 for rheumatoid arthritis, 15 for insulin-dependent diabetes mellitus (IDDM) and 20 for multiple sclerosis (MS) (3). It cannot be assumed that genes are fully responsible, because environmental factors can also cause familial clustering. However, by comparing the frequency of disease in biological and non-biological relatives, it has been shown, for example in MS, that familial clustering has a genetic basis (5).

Backcross studies in animal models of SLE suggest that multiple genes contribute to disease development (6-8). The precise nature of these genes currently is unknown. However, the results from the mouse studies could be useful as a guide for human studies (9), since the disease in mice is very similar to the human disease, and mouse chromosomal regions containing susceptibility genes have homologous regions in the human genome.

In the present study, we conducted a genome-wide search for SLE susceptibility loci in multiplex families with SLE using multipoint linkage analysis of affected relatives.

RESULTS

The characteristics of the multiplex SLE family data set is shown in Table 1. The present study group consisted of 80 multiplex SLE families with a total of 188 patients that fulfilled strict American College of Rheumatology (ACR) criteria for SLE. Of these families, 61 (76%) included two affected relatives; 12 (15%) had three affected relatives, five families (6.25%) had four affected relatives and two families (2.5%) had five affected family members. Forty-two multiplex SLE families included only affected full siblings, while the remaining 38 families (47.5%) included other affected relatives beside siblings. Forty-three families were Mexican American, while 37 were of Caucasian descent. As shown in Table 2, there were no significant differences in the clinical characteristics of the Mexican American versus the Caucasian SLE subjects.

Table 1. Characteristics of the multiplex SLE family data set
Multiplex SLE families 80
Two affected relatives 61
Three affected relatives 12
Four affected relatives 5
Five affected relatives 2
Mexican American 43
Caucasian 37
Families with affected sib-pairs only 42
Families with affected relative pairs 38
Genotyped affected SLE patients 188
Genotyped unaffected family members 246

Table 2. Selected clinical characteristics of genotyped affected individuals
Characteristic Hispanic (n = 106) Caucasian(n = 82)
Age at diagnosis, mean ± SD (years) 31 ± 11 34 ± 12
Female (%) 93 91
ANA-positive (%) 100 100
Anti-dsDNA-positive (%) 55 51
Renal involvement (%) 31 34
Hematological manifestation (%) 59 56
CNS involvement (%) 9 12.50
ANA, antinuclear antibodies; anti-dsDNA, anti-double-stranded DNA antibodies; CNS, central nervous system.
The age given is the age at diagnosis, when the patient first fulfilled the ACR criteria for SLE.

A genome-wide linkage search was undertaken to localize genetic intervals that may contain SLE susceptibility loci using the ABI Prism linkage mapping set 2 (excluding the X chromosome). In addition to the 188 affected relatives, we have genotyped an additional 246 non-affected family members that could add information for identity-by-descent status. As the mode of inheritance of SLE is not known, the data were analyzed with the non-parametric method in GENEHUNTER (12).

Since the clinical characteristics as well as the structure of the Caucasian and the Mexican American SLE families were very similar, we originally analyzed the entire set of families together. However, because Mexican Americans are an admixture of Caucasians and Amerindians, the families were subgrouped by ethnicity and Mexican Americans and Caucasians were analyzed separately.

Results of multipoint linkage analysis shown in Figure 1 suggest that chromosome 1 contains several candidate regions for SLE susceptibility. The strongest evidence for linkage was detected with the markers D1S2785 and D1S2842 at the very distal region of chromosome 1, at 1q44. Thus, with the D1S2785 marker, we obtained a non-parametric linkage (NPL) Z-score of 3.33 and a corresponding P-value of 0.0006, which is highly suggestive of linkage. However, it is very clear that the effect comes from the Mexican American subgroup and there is little support for a gene in this region in the Caucasian SLE families.


Figure 1. Linkage analysis of SLE for chromosome 1, using GENEHUNTER software. A multipoint plot for the entire chromosome 1 is shown. The y-axis depicts the NPL Z-score. The x-axis represents the position of the markers used along chromosome 1.

The second peak on chromosome 1 was in the 1q23-1q24 region, with the strongest NPL value occurring at marker D1S484 (Z = 2.64, P = 0.005). It is noteworthy that support for a gene in this region comes from both the Caucasian and Mexican American subgroups. This region is of further interest because it corresponds to a syntenic region of the mouse containing a lupus susceptibility gene (13).

A third peak on chromosome 1 in the 1p21 region was also evident (Fig. 1). This region near marker D1S2868 yielded an NPL score of Z = 2.56, P = 0.006. The question is whether this peak reflects an additional locus or just a shoulder on the more distal peak. Given the large distance between the markers D1S2868 and D1S484, these peaks may represent distinct candidates for susceptibility loci. Obviously, further studies of these regions are necessary. As with the 1q23-q24 region, in the 1p21 region as well, the evidence for a possible susceptibility gene is supported in both ethnicities.

The 1p36 region is of interest because support for a susceptibility gene is found in the Mexican American families (NPL Z = 2.7, P = 0.0039 at the D1S2667 marker). Absolutely no evidence for a gene in this region is suggested in the Caucasian subgroup of lupus families (Fig. 1).

A genomic region on chromosome 18q21-22 also yielded significant NPL Z-scores. As shown in Figure 2, marker D18S64 resulted in an NPL Z-score of 2.54 (P = 0.006), with two flanking markers, D18S68 and D18S474, also showing positive scores (Z = 1.84, P = 0.03 and Z = 1.38, P = 0.05, respectively). Evidence for a possible susceptibility gene in this region is supported in both Mexican American and Caucasian ethnicities (Fig. 2).


Figure 2. Multipoint non-parametric linkage analysis curve for markers on chromosome 18q21-23 (D18S474, D18S64, D18S68 and D18S61), determined by use of genotypes from 80 families. The y-axis depicts the NPL Z-score.

Table 3. NPL Z-score and corresponding P-values of markers in regions of interest
Region Marker Map position (cM)a NPL Zall P-value
1p36 D1S468 13.6 1.65 0.050
1p21 D1S2868 124.7 2.26 0.006
1q24 D1S484 170.4 2.56 0.005
1q44 D1S2785 272.5 3.33 0.001
6p22 D6S276 51.4 1.60 0.060
14q23 D14S63 53.3 1.70 0.040
14q23 D14S258 59.1 2.02 0.020
16q13 D16S3136 61.1 2.14 0.017
18q21 D1S64 85.4 2.54 0.006
20p13 D20S115 26.9 2.28 0.012
20q11 D20S195 52.1 1.57 0.060
aGiven as sex-averaged distance from the telomere.


Several additional chromosomal regions showed positive NPL Z-scores (Table 3). Of these, only the chromosome 14q23 region shows two adjacent markers, D14S63 and D14S258, which lie 5 cM apart. Each attained significance at P < 0.05 and, therefore, suggested possible linkage. The other regions have a smaller genetic influence on susceptibility for SLE. One such region, chromosome 6p21 containing the major histocompatability complex (MHC) cluster of loci, is particularly noteworthy. We typed five microsatellite markers near or within this region: D6S276, D6S1019, D6S1610, D6S1017 and GATA11E02. The marker D6S276 adjacent to the MHC at 6p21 gave an NPL Z-score of 1.6, P = 0.06, suggesting that the overall contribution of MHC to SLE accounts for only a small fraction of inherited susceptibility.

DISCUSSION

Both genetic and environmental factors contribute to the development of SLE. However, the number of genes involved and the magnitude of their effects are unknown. Furthermore, virtually nothing is known about the underlying genetic model for SLE. We chose to utilize non-parametric methods to best reflect the state of uncertainty about the genetic model. The non-random aspect of our sample precluded unbiased estimation of the penetrance parameters using our own data.

It is also unknown whether SLE results from the action of one or more relatively major genes, or whether it is truly polygenic with susceptibility derived from a number of genes with relatively small effects. Therefore, one of the goals of the present study was to determine if there were major susceptibility genes for SLE.

Several candidate loci are suggested from the results presented here. However, no single locus with overwhelming evidence for linkage was found, suggesting that there are no ‘major’ susceptibility genes segregating in families with SLE, and that the genetic etiology more likely results from the action of several genes of moderate effect, possibly interacting. If this is the case, larger sample sizes will be required to dissect further the etiology of this complex disease. To this end, we are collecting additional multiplex families of both Caucasian and Mexican American descent for follow-up studies.

Several genome screens recently completed in another autoimmune disease, MS, have obtained results suggesting multiple regions that may be important for susceptibility to MS but there is lack of evidence for any one major susceptibility gene (14-16). Even in IDDM, in which there is evidence for a major susceptibility locus within the MHC, it is clear that there are many additional genes which exert moderate to small effects that are necessary for disease development. It seems likely, therefore, that most autoimmune diseases are polygenic, with no single gene being either necessary or sufficient for disease development (17).

An additional major point relates to consideration of genetic heterogeneity in SLE. As shown above, a susceptibility region is strongly suggested in the distal portion of human chromosome 1. However, the support for a gene in this area is clearly found only in the Mexican American families with SLE but not in families of Caucasian ethnicity. Tsao et al. utilized non-parametric methods and showed increased sharing of haplotypes in SLE-affected sib-pairs from three ethnic groups in the distal portion of human chromosome 1, and suggested the region 1q41-1q42 as the locus for a susceptibility gene (18). The present study confirms a susceptibility locus on the distal portion of human chromosome 1 though the location suggested is at 1q44 (Fig. 1). Given the experience in type 2 diabetes mellitus, an ‘equally’ complex disease, where strong support for a gene on chromosome 20 is found in Finnish and French populations (19,20) but for which there is absolutely no support in Mexican Americans (21), consideration of each ethnic group separately becomes almost mandatory. A similar situation exists in the 1p36 region in which evidence for a susceptibility gene was obtained in the Mexican American lupus families but not in the Caucasian subgroup (Fig. 1). On the other hand, a susceptibility gene in the region 1q23-1q24 and possibly in the 1p21 region is supported to a very similar extent in both ethnicities.

Regarding the locus mapped to 1q23-24, it is of interest that a potential mouse lupus susceptibility locus in a syntenic interval has been mapped as well. A locus designated as Sle1 which is New Zealand White (NZW) in origin (13), and a New Zealand Black (NZB) locus, Nba2 (22,23), have been mapped at the same genetic interval. It remains to be determined whether the NZW and NZB genes are different alleles of the same gene or are different genes (24). Potential candidate genes in this region include Fc[gamma]RII and Fc[gamma]RIII.

Interestingly, using molecular typing of Fc[gamma]RII alleles, Salmon et al. (25) showed an increase in the R131 (low response) allele and a decrease of the H131 (high response) allele in African Americans with SLE. The Fc[gamma]RII locus is within ~3 cM from the D1S484 marker (26) used in the present study.

The region 18q21-22 may be of further interest because the Bcl-2 gene is located in the interval between markers D18S64 and D18S68. The Bcl-2 gene enhances lymphocyte survival by inhibiting or delaying apoptosis (27). Defective apoptosis of autoreactive lymphocytes is an attractive mechanism contributing to SLE. It has been postulated that in SLE, dysfunction of apoptosis could result in the inappropriate longevity of autoreactive B lymphocytes, allowing autoantibody levels to reach pathogenic thresholds and breakdown of self-tolerance (28,29). Transgenic mice overexpressing Bcl-2 in their B lymphocytes exhibit polyclonal B cell expansion and extended survival in vitro. After a few months, these mice developed an autoimmune syndrome resembling SLE, including the appearance of anti-histones and anti-Sm autoantibodies and immune complex-mediated nephritis (30,31). In addition, studies in human SLE patients suggest that Bcl-2 expression is elevated in both B and T lymphocytes (32,33). Furthermore, in a large case-control study, we recently have shown a significant association between the Bcl-2 gene and SLE (34).

There are many common elements among clinically distinct autoimmune diseases including certain clinical features, female predominance, therapeutic strategies and altered functions of humoral or cellular immunity. The occurrence of shared features of autoimmune diseases and the co-association of multiple autoimmune diseases in the same family and occasionally in the same subject supports the notion that there may be common genetic factors that predispose to autoimmunity. In this regard, it is notable that certain loci implicated in SLE in this study potentially overlap with regions implicated in other autoimmune diseases. The 1p36 candidate region overlaps with a susceptibility locus for rheumatoid arthritis suggested recently by a genome-wide linkage study (35). The region 18q22 overlaps with the putative IDDM6 locus in type 1 diabetes (36) and also with a possible rheumatoid arthritis susceptibility locus (35).

One of the central genetic factors recognized in autoimmune diseases is the MHC. Candidate gene-directed approaches have implicated genes of the MHC as determinants of disease susceptibility in SLE (3735-41). Interestingly, certain MHC haplotypes show stronger association with autoantibodies in SLE than with the disease itself (42). The results presented here may, therefore, represent the possibility that the overall contribution of the MHC to the disease itself is much less than its contribution to certain clinical manifestations (such as the presence of certain types of autoantibodies) in SLE.

MATERIALS AND METHODS

Subjects

Subjects with SLE (index subjects) who were confirmed to meet the ACR criteria for SLE were identified from the University of Southern California (USC) School of Medicine clinics. A minority of the patients came from Dr Dan Wallace’s clinic in Los Angeles, CA, and Dr Michael Neuwelt’s clinic in San Leandro, CA. We used semi-structured personal or telephone interviews to obtain a complete family history of each SLE patient. Through these interviews, disease information was collected for a fixed set of relatives of the index subject (grandparents, parents, siblings, offspring, aunts, uncles and cousins), and for any other family member with a more distant relationship with SLE diagnosis. Whenever possible, we also obtained family history information on the subjects from an additional informant (other than the index subject). A strict definition of SLE which included four or more of the 11 ACR criteria for SLE, with the 1995 new revision eliminating LE cells but adding anti-cardiolipin and lupus coagulants as criteria (10), was used. All affected individuals had medical records reviewed by a rheumatologist at USC for confirmation of the diagnosis. Families with a total of at least two affected individuals based on these criteria were recruited for study (n = 80 families, 188 affected individuals). In keeping with the variety of family structures seen in the general population, ascertainment was not restricted to a single family type, but included both affected siblings and extended families. The study protocol was approved by the Institutional Review Board of USC School of Medicine.

PCR and genotyping

Blood samples were collected from all participants, and genomic DNA was extracted from the peripheral blood mononuclear cells by standard procedures. DNA was used for polymerase chain reaction (PCR) with fluorescently labeled primers from the Applied Biosystems PRISM linkage mapping set version 2 comprising 350 highly polymorphic markers, arranged in panels of compatible markers and having an average spacing of 12 cM and average heterozygosity of 0.73. The loci have been selected from the Genethon linkage map (11), based on chromosomal location and heterozygosity.

PCR amplification was carried out using 40 ng of genomic DNA, 0.4 U of Amplitaq Gold (Applied Biosystems), 0.2 mM deoxynucleotides and 2.5 mM MgCl2 in a total reaction volume of 10 µl. PCR conditions used were 95°C for 12 min to activate the Amplitaq Gold, then 10 cycles of denaturation at 94°C for 15 s, annealing at 55°C for 15 s, extension at 72°C for 30 s, followed by 20 cycles of denaturation at 89°C for 15 s, annealing at 55°C for 15 s and elongation at 72°C for 30 s. Final extension was at 72°C for 10 min. PCRs were run in a Gene Amp PCR 9600 thermocycler (Perkin Elmer, Foster City, CA). Aliquots of pooled PCR products were supplemented with internal size standard ROX (Applied Biosystems) and electrophoresed on a 377 ABI PRISM sequencer, and the fluorescent signal was recorded and analyzed by the GENESCAN version 2.1 software. Different fluorescent dyes were plotted separately, and the sizes of fluorescent peaks estimated in base pairs by reference to the in-lane size standard. Marker alleles were classified according to their size using the GENOTYPER version 2 software. On every gel, a control DNA from CEPH individual 1347-02 was used to control gel to gel variation and to aid in allele calling. In addition to the automated allele calling, we performed manual surveillance of each and every genotype. Additional polymorphic markers obtained from Research Genetics (Huntsville, AL) were used on chromosome 6.

Linkage analysis

As the mode of inheritance of SLE including the penetrance, environmental and other modifiers, and the genetic homogeneity is unknown, we chose a non-parametric method for linkage analysis. We used GENEHUNTER (12) version 1.1, which performs complete multipoint analysis to infer the degree of identity-by-descent sharing among all affected family members at each location in the genome and then computes appropriate non-parametric measures of linkage. We used the NPL Zall statistic, which compares the observed set-wise identity-by-descent sharing among all affected family members with that expected under the null hypothesis of no linkage. P-values are computed assuming that the Zall statistic follows a standard normal distribution.

ACKNOWLEDGEMENTS

This study was supported by NIH grant RO1 AR43815 to C.O.J. Molecular core laboratory facilities of the General Clinical Research Center (GCRC) were provided by NIH grant NCRR GCRC MO1 RR-43.

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*To whom correspondence should be addressed. Tel: +1 323 442 1822; Fax: +1 323 442 2874; Email: jacob@usc.hsc.edu

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