Aissani, Brahim PhD*; Ogwaro, Kisani M MD#; Shrestha, Sadeep PhD*; Tang, Jianming PhD†††; Breen, Elizabeth C PhD‡; Wong, Hui-lee PhD§; Jacobson, Lisa P ScD‖; Rabkin, Charles S MD§; Ambinder, Richard F MD, PhD¶; Martinez-Maza, Otoniel PhD##**; Kaslow, Richard A MD*††#
In individuals not infected with HIV, single nucleotide polymorphisms (SNPs) in the gene encoding lymphotoxin alpha (LTA) and those in the gene for tumor necrosis factor (TNF) have been associated with non-Hodgkin lymphoma (NHL).1-8 Specifically, the ‘G’ allele at nucleotide position +252 (rs909253 A>G) of LTA alone or in combination with the ‘A’ allele at position −308 (rs1800629 G>A) of TNF have been repeatedly associated with NHL in some2-5,7 but not other1,6,8 studies. Associations with alleles at specific human leukocyte antigen (HLA) loci in the vicinity of TNF and LTA have also occasionally been reported.9-11 However, for several reasons, it remains uncertain whether variants in LTA (+252G) and TNF (−308A) or markers in adjacent loci represent true etiologic factors. First, NHL often occurs in the context of autoimmunity, immunosuppression, infection,12 and atopy13; but neither high levels of the immunostimulatory TNF and LTA molecules nor other indications of their direct involvement in NHL have been well documented. Second, although the −308A variant has been associated with high levels of TNF production, the numerous attempts to relate sequence variation in those genes to functional variation as measured by production, levels, or biologic activity of the molecules have been controversial.14-19 Finally, the SNPs in those 2 genes repeatedly associated with NHL most often occur on one of the most conserved extended haplotypes (CEH) yet found in the human genome-the primarily white HLA-B*08-containing ancestral haplotype CEH 8.120,21 spanning more than 2 megabases (Mb) in the major histocompatibility complex (MHC) region.
No study to date has examined the MHC-related genetic determinants of NHL in the context of HIV/AIDS; and no class III genetic markers other than those in the LTA-TNF have been examined, leaving unexplored a large (∼1 Mb) chromosomal region. We have sought to confirm the relationships seen in non-AIDS NHL through a case-control study of AIDS-NHL within a large cohort study by analyzing haplotypes formed by SNPs in the central MHC class III region. For this reason, we designed the present study to incorporate 2 sets of MHC class III SNPs in weak or no linkage disequilibrium (LD) with each other to evaluate the effects associated with extended haplotypes in central MHC. In addition to the target TNF-LTA gene cluster, we selected SNPs from 4 genes in the region that lies about 330 kilobase centromeric to TNF. We chose this region for the following reasons: (1) it is one of the most polymorphic regions of the human genome; (2) it hosts a complement gene cluster including complement factor B (CFB) involved in the proliferation of B-lymphocytes, a hallmark of NHL pathogenesis; and (3) it lies between TNF and HLA-DR, 2 loci previously associated with NHL.
Taken together, our observed association of AIDS-NHL with the same LTA (+252G)-TNF (-308A) haplotype repeatedly associated with non-AIDS NHL, along with a comparable association of a nearby segment of CEH 8.1 bearing the C2 and CFB genes, corroborates the overall haplotypic effect of CEH 8.1 on NHL pathogenesis in the context of HIV/AIDS.
MATERIAL AND METHODS
Cohort Characteristics and Study Design
We studied participants in the Multicenter AIDS Cohort Study (MACS), a prospective investigation of the natural history of HIV infection and AIDS22 among 4954 homosexual men enrolled in 1984-1985 plus 668 men enrolled in 1987-1991 at 4 study centers in the United States (Baltimore, Chicago, Los Angeles, and Pittsburgh). Clinical information and blood samples were obtained at 6-month intervals. The MACS cohort study was approved by the Institutional Review Board at each center, where individual participants gave informed consent, and testing for genetic variants potentially related to HIV/AIDS outcomes was included. Within the cohort, a case-control study was designed to compare serologic features in NHL cases and HIV-infected controls.23 Cases were participants who were diagnosed with AIDS-NHL as of April 2003, had at least 1 serum sample from a time point preceding the diagnosis, and could be matched with HIV-infected control as described below (n = 180). Longitudinal serum samples were available at all or at any of the 3 designed time points before NHL diagnosis: >3 years pre-NHL (closest to 4 years), 1-3 years pre-NHL (closest to 2 years), and/or 0-1 year pre-NHL (closest to 0.5 year).
Controls were HIV-positive participants who had not been diagnosed with NHL as of April 2003. Matching criteria were as follows: (1) duration of HIV infection based on the known date of seroconversion (n = 21) or date of entry to the study as HIV seroprevalent (n = 159) and (2) expected sample availability at equivalent time points (± 1 year). One-to-one matching of a case with a control minimized the case-control differences in the duration of HIV infection (6.7 and 6.9 years, respectively).
To facilitate control for confounding by HIV duration, up to 39 serial measurements of CD4+ count for each subject permitted estimation of a slope of the CD4+ count over time and backward imputation of the count in the control at the time of diagnosis in the index case (see Statistical Analyses). Eleven matched pairs had no CD4+ count measurement in the cases (n = 7) or in the controls (n = 2) or in both cases and controls (n = 2) within 2 years preceding the NHL diagnosis. Exclusion of these subjects led to a total of 169 matched case-control pairs.
Subphenotypic classification based on 112 of the NHL cases (67%) identified diffuse large B cell (28.0%); large B cell diffuse, immunoblastic (22%); Burkitt lymphoma and Burkitt lymphoma like (17%); lymphoma/NHL, not otherwise specified (22%); and other (11%). An overlapping subset of NHL cases (n = 95) were further classified as either systemic (56%) or central nervous system (CNS) (44%). Finally, 46 controls (29%) and 73 cases (44%) were also diagnosed with Kaposi sarcoma (KS) during the course of their HIV infection.
The analysis reported here was restricted to subjects of non-Hispanic European ancestry (n = 140 pairs) because of the strong differentiation of HLA genes in ethnically diverse populations and because of insufficient numbers of subjects in other ethnic groups. Only crude screening analysis of NHL subphenotypes could be conducted in a study of this size and degree of histologic heterogeneity.
DNA polymorphisms at candidate MHC class III genes were genotyped using a commercially available genotyping platform (BeadArray, Illumina Inc, San Diego, CA).
SNP Selection and Genotyping
A total of 63 SNPs were selected in candidate genes clustering in 2 regions of central MHC (Fig. 1). A first telomeric set of 27 SNPs were selected from across LTA and TNF and extending up to NCR3 (natural cytotoxicity triggering receptor 3 gene) and a second centromeric set of 36 SNPs in the region containing genes from C2 (complement component 2) to cytochrome P450 family 21, subfamily A, polypeptide 2 gene (CYP21A2). Within each candidate gene, a systematic search for informative SNPs in populations of Western European ancestry was conducted in public databases (HapMap I and SNP500 cancer database) and in private databases (Illumina Technologies, San Diego, CA, and Applied Biosystems Inc, Foster City, CA). Primary criteria for SNP selection included (a) aggressive (r2 > 0.80) haplotype tagging potential (htSNP) across gene loci,24 (b) minor allele frequency (MAF) >5%, (c) predicted functionality (identified in PupaSuite)25 or documented association with NHL or location in genes relevant to B-cell activation and lymphomagenesis, and (d) 2-hit SNPs (or Illumina validated) with a “designability” score of 1 (anticipated success rate >80%). Quantification of DNA was performed with Molecular Probes (Invitrogen, Carlsbad, CA) before genotyping on the Illumina platform.
Portions of the subjects had previously been typed at HLA class I and class II loci for several different studies of HIV-related outcomes. HLA typing methods and the relationship between the effects at the HLA loci and the effects of the MHC class III loci are detailed in Supplemental Digital Content 2, http://links.lww.com/QAI/A15.
Reliability of SNP typing was assessed through comparisons of duplicate data available for an average of 31 SNPs typed in a parallel study including a subset of NHL cases (n = 65) and controls (n = 44). Whenever departure from Hardy-Weinberg equilibrium (HWE) was observed for a SNP, the genotypic call score was checked before including a given SNP for analyses.
Statistical tests were performed in SAS 9.1 (SAS Institute Inc., Cary, NC), unless otherwise indicated. The effects of the genetic variants were evaluated in a case-control design after adjustment for other covariates as shown below.
The distributions of ages between cases and controls were comparable in a previous study of these subjects.23 To control for potential confounding by differential decline in CD4+ count during HIV disease progression, a well known effect of variants in HLA class I genes,26 we assumed that the raw CD4+ count declined according to a linear function and used regression methods to impute the CD4+ count in each control at the time of NHL diagnosis in his matched case. In a minority of subjects (n = 13) where data were insufficient to estimate the slopes reliably, the actual CD4+ count at the study visit closest to but preceding (within 2 years) NHL diagnosis was used. For the seroprevalent subjects we included all available CD4+ counts in the estimation of the slopes; for the seroconverters we included counts during the interval between one year post-seroconversion and the NHL diagnosis. Following log-transformation, standardization of the raw CD4+ counts and removal of the outliers (>3 standard errors from zero), backward imputations of the CD4+ counts in the matched controls at the date of the index diagnoses were performed. The resulting covariate was included in the multivariate models for estimating the risk associated with selected DNA polymorphisms.
Because cases and controls were selected from the same large cohorts of heterogeneous non-Hispanic European Americans recruited into the study before any NHL occurred, inadvertent bias due to systematic population stratification should have been minimal. Although we did not include standard genomic control markers27 in this analysis, the contribution of population structure among those of non-Hispanic European descent was nevertheless evaluated by testing the allelic diversity at the highly polymorphic and population-specific HLA class I and II loci among cases and controls (Supplemental Digital Content 1, http://links.lww.com/QAI/A14). We estimated the degree of gene differentiation among cases and controls using Weir and Cockerham variance-based method28 to estimate θs, an approximation of the Wright F-statistic,29 and to assess the correlation of pairs of alleles between cases and controls. Confidence intervals (95% CIs) around the estimates of θs were assessed with 10,000 bootstrap replicates and differences in overall allelic distributions among cases and controls were assessed using a G-like exact test as implemented in Genepop 4.0.30
Single Locus Analysis
SNP markers were examined separately in case and control groups for adherence to HWE using Pearson χ2 test. Pairwise LD between SNPs were measured using the coefficient of determination r2. Graphical representations of LD patterns across the central MHC were obtained separately for cases and controls using Haploview.31 Estimates of the risk associated with each marker genotype were determined by the prevalence odds ratio (OR) and corresponding 95% CI using logistic regression with or without adjustment for the imputed CD4+ counts. In the OR calculations, the most frequent homozygous genotype in the controls served as the referent genotype. If a high level of heterozygosity or a low level of homozygosity was observed, dominant and additive (P for trend) genetic models were considered.
Multiple Locus Analysis
Haplotypes were assigned from the unphased genotypes at SNPs showing significant association (P < 0.05) in the single-locus tests. Haplotype frequencies were estimated using the expectation-maximization (EM) algorithm.32 To account for the long-range LD in the MHC, maximum likelihood estimates of haplotype frequencies were obtained iteratively starting with initial frequencies of 1/h per haplotype, where h denotes the number of possible haplotypes in the sample. The 95% CIs for haplotype frequencies were calculated using a binomial method.33 Frequency estimates were calculated for the common haplotypes (>3%).34 MHC haplotypes were constructed by expanding the associated TNF-LTA haplotypes to include haplotypes formed by the associated SNPs in the complement region.
Overall differences in the distribution of haplotypes between cases and controls were assessed using the haplotype trend regression approach.35 This approach, assuming an additive model, estimates posterior probabilities for each subject for all EM-inferred haplotypes. These posterior probabilities were treated as independent variables in the haplotype trend regression model with the weights in the design matrix reflecting various alternative inferences about haplotypes. A logistic regression model containing weighted haplotypes was applied to accommodate our case-control design36 and to allow control for confounding by differential CD4 effects. In the multivariate logistic model, the adjusted ORs represent the risk increase per haplotype copy. Haplotypes with a frequency <3% were aggregated as a single term in the model. Haplotype associations were tested using the most prevalent haplotype in the controls as reference.
No formal correction for comparison of multiple class III SNPs was applied because the primary objective of the study was to test the prior hypothesis that the 2 linked SNPs previously associated with non-AIDS NHL (LTA +252 and TNF −308), along with others in CEH 8.1, were also associated with AIDS NHL.
Of the 63 SNPs assayed in the central MHC, 47 could be amplified and were polymorphic. For those SNPs, we compared 137 cases and 140 controls. The estimated average frequency of typing error (2%-4%) was unlikely to affect the results materially.
Allele Frequency and HWE
The panel of 47 SNPs analyzed is shown in Table 1. The SNPs (m30-m76) are shown ordered in telomere-to-centromere orientation from the LTA/TNF region (top) toward the complement gene region located 333 kilobases away (bottom). MAF and deviation from HWE are shown separately for the cases and controls. Several markers (∼38%) that had MAFs <5% in cases and controls were excluded from further analyses. We considered the SNPs whose proportions departed from HWE only in cases or controls but not in both as potentially indicative of marker-disease associations (cases) or signs for selective constraints (controls) and analyzed them carefully. No significant (P < 0.05) departure from HWE was found in both cases and controls at any SNP loci, with exception to TNF-863 SNP (P = 0.078 and P = 0.004 in the cases and controls, respectively).
Single Locus Analysis
Globally, 9 SNPs were found to be associated with increased risk for AIDS-NHL (Table 2). Of these, 4 located in the LTA/TNF gene cluster (m33, m34, m37, and m39) included the commonly studied LTA +252G (m34) and TNF-308A (m39) polymorphisms and 5 other polymorphisms (m51, m67, m70, m71, and m75) occurred in genes in and around the complement gene cluster. Three LTA markers (m33, m34, and m37) were in complete LD, and LTA +252G (m34) was subsequently used to tag all 3 in analyses. In univariate logistic models with matched data and adjustment for the CD4+ counts, 4 of these SNPs (m39, m67, m70, and m71) were found to be associated with increased risk for NHL (OR = 2.1-3.2). With the exception of SNP m70, the elevations of the ORs were of modest significance (0.01 < P < 0.06) and occurred with the heterozygous genotype at every marker. The low frequencies of the variant homozygotes and the excess of heterozygotes observed at several SNPs supported analyses under dominance and additive genetic models. Similar increases of ORs were observed under dominant and additive genetic models (P for trend: 0.009-0.08). We excluded possible distortion of estimates due to a combination of matching by duration of HIV infection and controlling for the rate CD4+ change by comparing risk estimates from a model tested without adjustment for the CD4+ count with those obtained from a logistic model using unmatched data and adjustment for the effect of CD4+ counts. The 2 models yielded comparable risk estimates and more consistent trends in the genotypic risks (Table 2). We have concentrated on the unconditional model with adjustment for the CD4+ counts because it was based on a larger sample size (n = 277 vs. n = 238). Markers that significantly (P for trend <0.05) modified the risk for NHL (LTA m34, TNF m39, CFB m67 and m70, RD RNA binding protein [RDBP] m71 and CYP21A2 m75) were selected for multilocus-based tests of association.
To examine the relationships among the tested SNPs, long-range LD patterns were examined separately for cases and controls (see Figures, Supplemental Digital Contents 3 and 4, http://links.lww.com/QAI/A16 and http://links.lww.com/QAI/A17). The LD patterns and haploblock37 structures indicated that LTA/TNF markers are not in strong LD with markers in the complement gene cluster, with the exception of the TNF m39 and CFB m70 markers (r2 = 0.54 and r2 = 0.58 in cases and controls, respectively).
With no overall correlation found between markers of the LTA/TNF and the complement gene clusters, we evaluated the risk associated with the MHC haplotypes separately across the 2 gene clusters. We first inferred haplotypes across the well-studied markers LTA +252G (m34) and TNF −308A (m39) and tested whether specific haplotypes containing these 2 SNPs were associated with AIDS-NHL. Sixty-one cases (44.5%) and 32 controls (22.8%) carried the LTA+252(G)-TNF-308(A) haplotype (henceforth haplotype G-A or hap1) (Table 3A). Consistent with previous studies of non-AIDS NHL,1 the haplotype G-A conferred a 2.7-fold increase of risk (P = 0.0009).
For haplotypes across the complement gene region, we found a unique haplotype [CFB m67(A)-CFB m70(G)-RDBP m71(A)-CYP21A2 m75(C)] (hap2) associated with a 3-fold increase in risk (OR = 3.2; 95% CI: 1.6 to 6.6; P = 0.0008). To determine whether the risk haplotypes hap1 and hap2 are independent of each other, we evaluated the association with the combined 6-locus haplotypes (m34-m39-m67-m70-m71-m75). A haplotype formed by the juxtaposition of hap1 and hap2 [(m34(G)-m39(A)-m67(A)-m70(G)-m71(A)-m75(C)] (hap3) was the only haplotype that modified the risk for AIDS-NHL (OR = 4.2; 95% CI: 2.0 to 8.9; P = 0.0002).
The apparent discrepancy between the estimated ORs for hap3 and hap2 in all of the 3 sets A, B, and C is due to the varying frequencies of the referent haplotype; adjustment had only a minor effect. Referent haplotype G-A-G-A used to estimate the OR for hap2 in the set A occurred in 28.7% of cases and 38.7% of controls. Referent haplotype A-G-G-A-G-A occurred in 19.3% of cases and 32.5% of controls.
Examination of the haplo-specific alleles at the 6 SNP sites on the CEH 8.1 contig NT_113891 (c6_COX cell line-derived genomic contig38) revealed that this haplotype is part of the conserved CEH 8.1. Interestingly, approximately one third of the cases with G-A carried this haplotype in combination with haplotypes other than hap2 suggesting that the G-A haplotype may occur on other common haplotypes across the class I and III regions of the MHC.
With the partial existing HLA data, we examined the connection between the early reported associations of NHL with HLA-DR3 and HLA-B8 and the more recently reported MHC class III associations. To this end, we expanded hap3 to include the closest telomeric (HLA-B) and centromeric (HLA-DRB1) HLA genes and found that hap4 (a CEH 8.1-specific haplotype formed by the combination of HLA-B*0801, hap3, and HLA-DRB1*0301) is the only 8-locus haplotype that was significantly associated (OR = 7.8; 95% CI: 2.5 to 24.0, P = 0.0004) with the NHL (see Table, Supplemental Digital Content 5, http://links.lww.com/QAI/A18). Further support for a CEH 8.1 effect comes from analyses that included partial data from other HLA class I (namely HLA-Cw) and class II (HLA-DQA1 and HLA-DQB1) genes (see Table, Supplemental Digital Content 5, http://links.lww.com/QAI/A18).
We evaluated the potential confounding or additional risk associated with comorbidity due to KS in a subset of cases (n = 62) and controls (n = 44) who also developed that condition during the course of their HIV infection. In the KS-free subset, the associations with haplotypes hap1-3 remained significant (Table 3B). The subset of subjects who developed KS was too small to permit meaningful estimates of risk (data not shown).
The availability of subphenotypic data for the anatomic location of AIDS-NHL (systemic vs. CNS) permitted limited analysis of stratified data. For the subset of systemic cases, all 3 haplotypes (hap1-3) were positively associated with AIDS-NHL (Table 3C), whereas for the much smaller subset of CNS cases (n = 45), the ORs could not be calculated with confidence (see Table, Supplemental Digital Content 6, http://links.lww.com/QAI/A19).
In our case-control study of homosexual men in the MACS, carriage of LTA (+252G) and TNF (−308A), which closely tag the conserved extended MHC haplotype CEH 8.1, were associated with an approximately 2-fold higher risk of AIDS-NHL. These LTA and TNF variants have repeatedly been reported in association with NHL unrelated to HIV infection.2-5,7 We detected associations of similar magnitude with SNPs tagging a nearby segment of the CEH 8.1 that contains a complement gene cluster. Alleles of HLA genes present on CEH 8.1 and less frequently studied in association with non-AIDS NHL9-11 also showed comparable relationships among the subset of MACS subjects with available HLA typing. This first study of MHC effects in AIDS-NHL thus succeeded in its purpose of replicating the established association with non-AIDS NHL.
The multiple previous positive studies of the associated SNPs may have focused attention on TNF because its encoded protein is involved in a range of neoplastic processes39,40 and because its promoter variant −308A has been implicated, albeit not invariably, in relatively high TNF production.15,16 However, that TNF marker and its companion in LTA are well documented elements of the most extensively conserved haplotype in the genome yet observed. CEH 8.1 stretches for at least 2 Mb between HLA class I and class II loci.20,21 Although this inordinately strong conservation of the haplotypic relationships of those 2 SNPs to CEH 8.1 is not in doubt, we nevertheless verified that our observed associations did not mainly reflect unusual recombinant events in that central MHC region. We demonstrated that more cases than controls who displayed the LTA-TNF G-A combination carried other alleles in the neighboring loci from LTA to CYP21A2 that are also recognized CEH 8.1 variants.38 Although these associations increase the likelihood that 1 or more causal loci in this extended haplotype will be implicated in NHL, they also diminish the probability that any population association with a given marker in that haplotype will actually signify a causal relationship. To emphasize the CEH 8.1-wide effect, we have reported associations with haplotypes rather than with SNPs.
Our study tested a specific hypothesis, and it is most unlikely that our detection of the identical associations seen multiple times before in non-AIDS NHL represents a chance finding.
On the other hand, the small size of our study sample may have led to unstable and potentially inflated risk estimates; replication in another HIV cohort would not only confirm but also better quantify the risk.
We analyzed different groups of cases and controls and applied alternative statistical models to ensure that our results were not method-dependent. We have emphasized the unmatched case-control design with adjustment for the CD4+ count because it provided greater statistical power and probably yielded a less conservative statistical test. Further, the CEH 8.1 was earlier thought to be associated with a rapid decline of CD4+ cells in HIV-1 infection.26 It was therefore important that an analysis of cases and controls matched by duration of HIV infection effectively eliminated the possibility of confounding by differential decline of CD4+ cells among pairs with CEH 8.1-positive NHL cases.
The extraordinary conservation in CEH 8.1 will make identification of the precise causal determinant on this haplotype by typical genetic approaches more difficult. By the same token, we documented that one third of the G and A alleles were carried on non-HLA-B*08 lineages. Smaller numbers of subjects seem to carry both G and A alleles either on the same or the opposite chromosome but in the absence of the full CEH 8.1. If these cases represent recombinant chromosomes carrying CEH 8.1 with reduced conservation, they could be highly informative for fine mapping of the candidate region of the central MHC. However, since the EM-inferred haplotypes may not be entirely accurate for LTA +252 and TNF −308 double heterozygotes, direct experimental assessment of the phase in such subjects is warranted for future studies.
NHL is a neoplasm for which the strongest risk factors identified to date reflect dysregulation of the immune system. However, regardless of whether immune deficiency is congenital, iatrogenic in the setting of posttransplant immunosuppression, or acquired as a consequence of HIV infection, its presence could complicate the evaluation of true causal factor(s) whose function is altered in NHL. In the context of HIV/AIDS, factors other than the decline of CD4+ count with disease progression are suggested by (1) a disproportionally higher risk of NHL (10-fold to 100-fold higher than the population risk) in HIV-infected individuals even in the setting of moderate immune deficiency41,42 and (2) a less dramatic decline of systemic NHL incidence as compared with that of KS and primary CNS lymphoma in the era of highly active antiretroviral therapy.43-45 Prolonged immune deficiency and low CD4+ count 1 year before the time of NHL diagnosis have also been reported as independent predictors of NHL outcome.46 As noted above, we controlled for possible confounding of the observed genetic relationships by the underlying decline in immunity.
Inclusion of a substantial proportion of subjects who also developed KS did not distort the association with CEH 8.1 because the HLA alleles of that haplotype have not been associated with HIV-related KS in the MACS.47 Clinical information on the histological type was available for only a subset of our cases; that limitation precluded statistically meaningful tests by tumor type. Likewise, the study showed a clear association with systemic AIDS-NHL, but that with CNS AIDS-NHL could not be accurately assessed because of the small sample size; however, the trend was similar to that observed with the unstratified sample (Supplementary Table S2).
Recent reports1,6,8 have described a protective association with TNF −857T, a SNP that was not included in our genotyping scheme. Although no earlier study detected significant associations with both the TNF −308A LTA +252G haplotype and the TNF −857 SNP, we cannot exclude a protective role for the latter in our AIDS-NHL. The documented occurrence of the 2 TNF SNPs on distinct MHC lineages8 suggests that they are differentially distributed in different white populations. That may explain the consistency in the findings for the haplotype containing −308A in our study and the others including relatively heterogeneous European populations and the contrasting −857T association in subjects of predominantly British ancestry. Moreover, the -857T association has appeared stronger with follicular lymphoma,1,8 whereas the −308A association has appeared stronger with diffuse large B-cell disease,4,6 the form more frequently represented in our population as well.
The pathogenetic mechanisms underlying the increased susceptibility of CEH 8.1 carriers to NHL and to a number of other conditions of autoimmunity and immune dysfunction21 are poorly understood. Adaptive and demographic considerations have been invoked to account for the apparent contrast between increased disease susceptibility and high population frequency (selective advantages) of CEH 8.1.48 Our data show that, except for TNF −308A and CFB m70, the remaining 4 SNPs associated with AIDS-NHL have elevated minor allele frequencies in both the controls (MAF ≥ 0.27) and the cases (MAF ≥ 0.38), emphasizing the necessity to focus future mapping efforts on those MHC markers in strong LD with the presumably less extended TNF −308(A)-CFB m70(G) subhaplotype.
To summarize, the present study extends previously reported association of LTA +252G and TNF −308A from non-AIDS to AIDS-NHL and, as with the recent observations in non-AIDS NHL,10,11 shows that the positive association with these 2 polymorphisms extends across CEH 8.1. In light of the extraordinary allelic invariance across several megabases of central and extended MHC of CEH 8.1-bearing chromosomes,20,38,49-51 our results and those reported for non-AIDS NHL strongly support an association with 1 or more genetic variants somewhere in the G-A-bearing haplotypes rather than suggesting an LTA-TNF-specific causal relationship. Fortunately, few large HIV-infected populations now go untreated for long enough to permit NHL to develop in numbers sufficient for an investigation similar to ours. It could therefore be difficult to use another population study to confirm our observation of an MHC haplotype determinant common to the pathogenesis of AIDS NHL and non-AIDS NHL alike.
Data in this article were collected by the MACS with centers (Principal Investigators) at The Johns Hopkins University Bloomberg School of Public Health (Joseph B. Margolick, Lisa Jacobson), Howard Brown Health Center and Northwestern University Medical School (John Phair), University of California, Los Angeles (Roger Detels), and University of Pittsburgh (Charles Rinaldo). Website located at: http://www.statepi.jhsph.edu/macs/macs.html.
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