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Haplotype analysis of the SDF-1 (CXCL12) gene in a longitudinal HIV-1/AIDS cohort study


The stromal-derived factor-1 (SDF-1) chemokine gene encodes the only natural ligand for CXCR4, the coreceptor for the pathogenic X4 HIV-1 strains. A single-nucleotide polymorphism (SNP) in the 3′ untranslated region (SDF1-3′A=rs1801157) of SDF-1 was reported to be protective against infection and progression in some, but not other, epidemiological studies. To identify additional alleles that may influence HIV-1 infection and progression to AIDS, nine SNPs (including rs1801157) spanning 20.2 kb in and around the SDF-1 gene were genotyped in over 3000 African American (AA) and European American (EA) participants enrolled in five longitudinal HIV-1/AIDS natural cohort studies. Six or five haplotypes were present at frequencies greater than 5% in AA or EA, respectively. Six of the nine SNPs occur on only one common haplotype (>5%), while the remaining three SNPs were found on multiple haplotypes, suggesting a complex history of recombination. Among EA, rs754618 was associated with an increased risk of infection (OR=1.50, P=0.03), while rs1801157 (=SDF1-3′A) was associated with protection against infection (OR=0.63, P=0.01). In the MACS cohort, rs1801157 was associated with AIDS-87 (RH=0.31, P=0.02) and with death (RH=0.18, P=0.02). Significant associations to a single disease outcome were found for two SNPs and one haplotype in AA.


The chemokine stromal-derived factor-1 (SDF-1, gene symbol CXCL12) and its receptor CXCR4 play critical roles in developmental processes of the nervous, cardiovascular, and hematopoietic systems.1, 2, 3 SDF-1 is constitutively expressed by stromal, endothelial, dendritic, and other cells.4, 5, 6 It stimulates the motility of hematopoietic cells, lymphocytes, and monocytes,7, 8 thymocytes,9 and mediates leukocyte adhesion to the vascular endothelium.10 SDF-1 also influences the development of microglia, astrocytes, and neurons.11, 12

CXCR4 serves as a coreceptor along with CD4 for T-cell tropic X4 HIV-1 strains. In vitro, SDF-1 can block X4 HIV-1 entry into CD4-positive cells by binding to and internalizing CXCR4.13, 14, 15, 16 One single-nucleotide polymorphism (SNP), rs1801157 (=SDF1-3′A), in a conserved area of the 3′ untranslated region was associated with resistance to infection in heterozygotes in the MACS cohort and with delayed onset of AIDS in HIV-1-infected homozygote seroconvertors;17 however, subsequent work has reported opposite effects.18, 19, 20 In addition, studies that examined the relationship between circulating levels of SDF-1 and HIV-1 disease progression have obtained contrasting results.21, 22, 23 Similarly, other reports have proposed conflicting roles for SDF-1 in neuronal survival and apoptosis in patients with HIV-1 encephalitis.24, 25, 26, 27

Molecular genetic epidemiological studies have identified polymorphisms in more than 20 human genes, including several chemokines and their receptors, that are associated with HIV-1 infection and/or AIDS disease pathogenesis.28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 Given the importance of SDF-1 in various metabolic and developmental activities, we examined the allele frequencies and haplotype structure of nine SNPs in and around the SDF-1 gene. In addition, given the important role played by SDF-1 and CXCR4 in HIV-1/AIDS, we looked for the influence of genetic variation in these SNPs and haplotypes on disease in over 3000 subjects enrolled in five USA-based natural history HIV-1/AIDS cohorts.

Materials and methods

Study participants

Individuals were enrolled in five longitudinal cohorts. ALIVE—The ALIVE cohort is a community-based prospective cohort study of injecting drug users at least 18 years of age in Baltimore, Maryland. The study was initiated in 1988 and follow-up continued through 2000 with semiannual visits. The median age at seroconversion was 35 years of age, 24% are women. The racial distribution is 7.6% European American (EA) and 92.4% African American (AA).41 HGDS—The multicenter HGDS is a US-based hemophilia cohort study with participants ranging from 6 to 19 years in age. The cohort consists of 126 uninfected and 207 HIV-1-infected participants who became infected through exposure to blood products between 1982–1983. In the HIV-1-infected cohort, CD4+T cells were measured semi-annually and HIV-1 RNA and HCV RNA were collected annually for 7 years follow-up. The racial distribution is similar to the general population, with 72% European Americans, 15% Hispanic, 11% AA, and 2% other.42, 43 The Multicenter Hemophilia Cohort Study (MHCS)—MHCS is a multicenter prospective longitudinal cohort study enrolling hemophilia patients, 99% of whom are male, from 17 American or European treatment centers beginning in September 1982. CD4+T cells were measured at 6–12-month intervals. Approximately 32% of the cohort was less than 16 at the time of enrollment, 34% were between the ages of 16 and 26, and 34% were between 27–69. The racial distribution is 90% EA, 6% AA, 3% Hispanic, and 1% other.44 The Multicenter AIDS Cohort Study (MACS)—MACS is a US-based ongoing prospective study of HIV-1 infection in adult (ages 18–70) homosexual and bisexual men in Baltimore, Chicago, Pittsburgh, and Los Angeles enrolled between 1984 and 1991. The group consists of 2195 infected individuals, 575 seroconverters, and 3427 seronegatives at enrollment, of whom 575 subsequently seroconverted. CD4+T cells were obtained at semiannual visits. The racial distribution is 83.3% EA, 10% AA and 5% Hispanic, and 2% other.45, 46 SFCC—The SFCC is a prospective study of the natural history of HIV and AIDS conducted in adult homosexual and bisexual men enrolled in 1978–1980 for studies of hepatitis B (HBV), followed by a HBV vaccine trial in 1980–1983. Recruitment into the SFCC for follow-up studies of HIV and AIDS began in 1983–1992. CD4+T cell counts were measured at 6–12-month follow-up visits. The HIV-infected men included in this analysis were either HIV-positive at enrollment, or had intervals between the last negative and first positive HIV antibody test results of at most 2 years. This cohort contains 211 individuals, 203 of whom are EA.47

Individuals were classified as HIV-1 seroprevalents (infected at study enrollment), seroconvertors (infected after study enrollment), and seronegatives (negative result with HIV-1 antibody test). The seroconversion date was estimated as the midpoint between the first positive HIV-1 and last negative antibody test dates. The EA seroconvertors had a follow-up range of 0.83 months to 14.7 years, with a mean follow-up of 9.47 years. The high-risk exposed, uninfected (HREU) group contained homosexual men exposed through receptive anal intercourse with multiple partners,45 hemophiliacs who received contaminated factor VIII prior to the initiation of heat treatment in 1984,48 and needle-sharing injecting drug users.49 A total of 2003 EA (217 seronegatives, 1141 seroprevalents, and 668 seroconvertors) and 1073 AA (166 seronegatives, 626 seroprevalents, and 294 seroconvertors) were genotyped for nine SNPs (Figure 1, Table 1). A larger number of individuals was genotyped for rs1801157 (=SDF1-3′A) due to the availability of nonrenewable DNA (see Table 2).

Figure 1

Molecular map of the SDF-1 gene showing the positions of nine SNPs genotyped in over 3000 AA and EA HIV-1/AIDS cohort participants. Minor allele frequencies (MAFs) are the last two rows. Haplotypes (I–XXIII) and their frequencies are given. Minor alleles on each haplotype are underlined.

Table 1 Gene positions and PCR primer and probe sequences for nine SNPs genoytped in the SDF-1 gene
Table 2 Frequencies of dominant CXCL12 genotypes and haplotypes with results from comparing these frequencies between seroconvertors (HIV+) and high-risk exposed uninfected participants (HIV−)

SNP discovery and genotyping

The human SDF-1 gene contains four exons and is located at chromosome 10q12 (Figure 1). In order to identify SNPs that might significantly influence primary protein structure, the coding regions of all four exons and 600 bp of DNA upstream of the initiation codon and downstream of the termination codon were screened for SNPs in genomic DNAs from 72 AA and 72 EA using the single-strand confirmation polymorphism (SSCP) (described in Modi et al50)). In addition, the coding regions of 24 individuals from each racial group were resequenced. SNPs ultimately genotyped were obtained from these surveys, from dbSNP ( and from Applied Biosystems ( Genotyping was performed using PCR-RFLP followed by agarose gel electrophoresis or Taq Man allelic discrimination.36

Statistical analyses

Haplotypes were estimated in compound heterozygotes using the PHASE program.51 Genotype and haplotype frequencies were compared between HIV-1-infected seroconvertors and HREU with two-tailed Fisher's exact test (FET) and logistic regression assuming dominant, additive, and recessive genetic models using SAS (Statistical Analysis System, Cary, NC, USA) software, and nominal P-values are reported in Tables 2 and 3. Cox proportional hazards regression assessed rates of progression among HIV-1-infected seroconvertors using SAS. Three end points reflecting advancing HIV-1 disease progression were evaluated: AIDS 1993 (CD4<200 or AIDS-defining condition),52 AIDS 1987 (AIDS-defining condition),52 AIDS-related death during follow-up for an HIV-1-infected participant. Cox analyses were performed both for unadjusted (using the genotype or haplotype alone) or adjusted (considering the genotype or haplotype as a covariate along with the following AIDS-modifying genetic factors, for EA: CCR5-Δ32, CCR2-64I, HLA-B*27, HLA-B*57, HLA-B*35Px, and HLA class I zygosity; for AA: HLA-B*57, HLA-B*35Px, and HLA class I zygosity).17, 30, 31, 53, 54 Participants were stratified by sex (7.6% female), and age at seroconversion: 0<20, 20–40, and over 40 years. The censoring date was the earliest of the last recorded visit, or December 31, 1995 for the MACS, MHCS, HGDS, or SFCC, or July 31, 1997 for the ALIVE cohort to avoid potential confounding by highly effective antiretroviral therapy (HAART). A later date was used for the ALIVE cohort because administration of HAART was delayed in this group.55

Table 3 Survival analyses of progression to AIDS end points for CXCL12 SNPs and haplotypes using Cox proportional hazards regression under a dominant genetic model (Results include the covariates listed in materials and methods).

Results and discussion

Our SSCP and resequencing surveys, and inspection of build 122 from NBCI's dbSNP database, failed to identify any nonsynonymous SNPs in this gene. A total of nine SNPs spanning 20 230 bp were successfully genotyped in 3076 AA and EA DNA samples. Two of these SNPs were located in the 5′ region of the gene, four were in introns, and three were in the 3′ UTR (Table 1, Figure 1).

Allele frequencies for most of the nine SNPs differed substantially between AA and EA (Figure 1). For example, rs2297630 had a frequency of 0.056 in AA and 0.262 in EA. In total 23, haplotypes were estimated in both racial groups using the PHASE program; however, only six or five haplotypes were present at frequencies greater than 5% in AA and EA, respectively (Figure 1). As predicted from inter-racial differences in allele frequencies, haplotype frequencies differed considerably between AA and EA as well. For example, haplotypes V and VI were present at frequencies of 0.065 and 0.057 in AA, but at frequencies of 0.211 and 0.257 in EA. Variant alleles at six of the SNPs were found largely on only one haplotype in both racial groups: rs17156287 on haplotype VIII, ss46566436 on haplotype XX, rs2839693 on haplotype II, rs2297630 on haplotype VI, rs1801157 (SDF1-3′A) on haplotype V, and rs2522 on haplotype IV. On the other hand, the remaining three SNPs (rs754618, rs266085, rs1065297) occur at appreciable frequencies on more than one haplotype. For example, rs754618 was found on haplotypes VI and VII in AA at frequencies of 0.057 and 0.046, respectively, while rs266085 was found on haplotypes V, VIII, and XX in EA at frequencies of 0.211, 0.089, and 0.034, respectively. Interestingly, these three SNPS were the first, fifth, and ninth SNPs in the study, and thus their presence on multiple haplotypes in both racial groups cannot be explained by a simple pattern of recombination. As a result of the distribution of the nine SNPs on the common (>5%) haplotypes, only three haplotypes (I, III, and VII) had to be examined independently of the individual SNPs in the subsequent association analyses (Figure 1).

Although all of the individuals examined here were enrolled in HIV-1/AIDs cohorts, the results may be compared with a recent study that examined SDF-1 haplotype structure based upon 14 SNPs and one INDEL in an unaffected Indonesian population.56 Only three of their SNPs overlap those studied here (5887=rs2839693, 6201=rs266085, and 12197=rs1801157), and Indonesian allele frequencies of 0.067, 0.405, and 0.486 differ considerably from the frequencies seen in AA and EA (Figure 1). In all three racial groups (Indonesians, AA and EA) rs2839693 was found on only one common (>5%) haplotype, while rs1801157 was found on two common haplotypes in Indonesians and only on one in AA and EA. In the three populations, rs266085 was present on several haplotypes. Other haplotype variation was reported when two additional unaffected Indonesian subpopulations were compared.56 These results underscore the independent demographic and selective histories experienced by different populations throughout the world, and emphasize the need for carefully controlled disease association studies where population substructure is taken into consideration.

To test for possible genetic influences on susceptibility to HIV-1 infection in the AA and EA populations, genotype and haplotype frequencies were compared between HIV-1-infected seroconvertors and HREU from the five cohorts combined stratified by race. No statistically significant associations with any SNP or haplotype were observed when 81 AA HREU were compared to 294 AA HIV-1-positive seroconvertors (AA are largely from the injecting drug using ALIVE, with about 10% from the homosexual MACS), assuming a dominant genetic model (Table 2).

However, among the EA from all cohorts combined (homosexual MACS, hemophilic MHCS, hemophilic HGDS and homosexual SFCC) when 145 HREU were compared with 668 EA HIV-1-positive seroconvertors, rs754618 was associated with increased susceptibility to infection (OR=1.50, P=0.03) (Table 2). rs754618 is present on five haplotypes, two of which (haplotypes VI and XX) are present at frequencies greater than 1%. However, neither haplotype VI nor XX is itself significant; thus, this association appears to be attributable to rs754618 itself. rs1801157 (=SDF1-3′A) was associated with protection against infection (OR=0.63, P=0.01) among all EA cohorts combined, and is present only on haplotype V. As a result, this protective effect appears to be attributable to rs1801157 itself. Since rs754618 and rs1801157 (=SDF1-3′A) show opposite results in the association tests and do not appear together on a common haplotype, their effects are complementary.

To address differences between EA cohorts in susceptibility to infection, the influence of each SNP was examined in the two larger cohorts separately, the MHCS (175 HIV-1-positive seroconvertors, 29 HREU) and the MACS (412 HIV-1-positive seroconvertors, 83 HREU). Under a dominant genetic model, only the MHCS showed a significant association for susceptibility to infection with rs754618 (MHCS: OR=2.41, P=0.05; MACS: OR=1.28, P=0.34). The MACS was significantly associated with rs1801157, whereas the MHCS was not (MHCS: OR=0.62, P=0.23; MACS: OR=0.56, P=0.02). These disparities between cohorts in significance of the observed associations may reflect differences in the mode of infection (mucosal vs parenteral), or differences in power due to size: the MACS is a larger cohort. However, in both the MHCS (OR=0.62) and the MACS (OR=0.56), the positive effects of rs 1801157 (SDF1-3′A) are remarkably similar.

Cox proportional hazards regression assessed rates of progression to AIDS and death for 668 EA and 294 AA seroconvertors from all cohorts combined stratified by race under a dominant genetic model (Table 3). In the AA, two SNPs were each associated with a single outcome (rs754618 with AIDS-93, RH=1.83, P=0.004; and rs2297630 with AIDS-93, RH=1.88, P=0.02). Haplotype VII, one of several haplotypes that carry the rs754618 and rs266085 alleles, was associated with an increased rate of progression to death (RH=3.30, P=0.02). Considering all EA cohorts combined, there were no significant associations between any SNP and disease progression, assuming a dominant genetic model (Table 3). Previously,17 we reported a significant influence of rs1801157 (=SDF1-3′A) on disease progression, assuming a recessive (homozygous) genetic model using a smaller number of EA seroconvertors (n=639) than that examined here (n=768). Repeating the analysis assuming a recessive model with the larger sample size, rs1801157 (=SDF1-3′A) was associated with decreased rates of progression to AIDS-87 (RH=0.45, P=0.04) and death (RH=0.37, P=0.03) (Table 3). Although not significant, we observed a similar trend between progression to AIDS and death for the group of participants added to the study after the 1998 publication (RH=0.4, 0.6, 0.4, P>0.07, for AIDS 1993, 1987, and death, respectively). In the MACS, this SNP was associated with decreased rates of progression to AIDS-87 (RH=0.31, P=0.02) and with death (RH=0.18, P=0.02), while none of the end points was significantly associated in the MHCS or any other individual cohort.

In this study, we report a comprehensive survey of SDF-1 SNP frequencies and haplotype structure in EA and AA HIV-1/AIDS cohort participants. The SDF-1 gene, like other chemokine genes, is highly conserved and no nonsynonymous SNPs have yet been reported. On the other hand, noncoding SNPs and haplotype frequencies are quite variable in AA, EA, and Indonesians, suggesting that genetic drift, recombination, and even natural selection have acted on these noncoding but potential regulatory regions to create substantial genetic variability throughout the world. In addition, the role of genetic variation in HIV-1 susceptibility and progression to AIDS in a prospective cohort study was presented. Although the function of genetic variants of SDF-1 on HIV-1 infection and progression to AIDS remains unclear, these data provide additional support that this gene has a modest influence on HIV-1 infection and progression to AIDS in EA and AA populations, particularly the effects of rs1801157 (=SDF1-3′A) with respect to protecting against infection and delaying disease progression in the MACS.

We observed different results for the effects of genetic factors on HIV-1 infection and progression to AIDS between EA and AA, and between the MACS and MHCS, the two larger EA cohorts. This is to be expected since we are considering a very complex biological system. The cohorts belong to different risk groups (gay men, hemophiliacs, injecting drug users) and thus have different routes of exposure, different age ranges, different access to medical care, different environmental exposures, different follow-up time, and different enrollment strategies. Also, the cohorts have inherent ascertainment biases that confound results. For example, seroprevalent studies usually have a frailty bias of over-representation of slow or nonprogressors and under-representation of very rapid progressors. In this regard, seroconverter cohort studies such as the one presented here are more robust, but they may be biased in different ways. For example, if samples were not collected or stored at early visits, rapid progressors may be under-represented. In this vein, we were unable to obtain DNA from the MHCS cohort members who already had advanced immunodeficiency upon enrollment: this created a frailty bias. In addition, the SFCC enrolled people who were among the earliest seroconverters (from late 1970s), but they had to be living in 1987 to provide a blood sample; thus, this cohort is strongly biased towards long-term survivors. However, this is not true for the ALIVE and the MACS, where nearly every seroconverter present in these cohorts is represented in our collection of DNA samples.


  1. 1

    Ma Q, Jones D, Borghesani PR et al. Impaired B-lymphopoiesis, myelopoiesis, and derailed cerebellar neuron migration in CXCR4- and SDF-1-deficient mice. Proc Natl Acad Sci USA 1998; 95: 9448–9453.

    CAS  Article  Google Scholar 

  2. 2

    Murdoch C, Monk PN, Finn A . Cxc chemokine receptor expression on human endothelial cells. Cytokine 1999; 11: 704–712.

    CAS  Article  Google Scholar 

  3. 3

    Tachibana K, Hirota S, Iizasa H et al. The chemokine receptor CXCR4 is essential for vascularization of the gastrointestinal tract. Nature 1998; 393: 591–594.

    CAS  Article  Google Scholar 

  4. 4

    Pablos JL, Amara A, Bouloc A et al. Stromal-cell derived factor is expressed by dendritic cells and endothelium in human skin. Am J Pathol 1999; 155: 1577–1586.

    CAS  Article  Google Scholar 

  5. 5

    Ponomaryov T, Peled A, Petit I et al. Induction of the chemokine stromal-derived factor-1 following DNA damage improves human stem cell function. J Clin Invest 2000; 106: 1331–1339.

    CAS  Article  Google Scholar 

  6. 6

    Tanabe S, Heesen M, Yoshizawa I et al. Functional expression of the CXC-chemokine receptor-4/fusin on mouse microglial cells and astrocytes. J Immunol 1997; 159: 905–911.

    CAS  PubMed  Google Scholar 

  7. 7

    Aiuti A, Webb IJ, Bleul C, Springer T, Gutierrez-Ramos JC . The chemokine SDF-1 is a chemoattractant for human CD34+ hematopoietic progenitor cells and provides a new mechanism to explain the mobilization of CD34+ progenitors to peripheral blood. J Exp Med 1997; 185: 111–120.

    CAS  Article  Google Scholar 

  8. 8

    Mohle R, Bautz F, Rafii S, Moore MA, Brugger W, Kanz L . The chemokine receptor CXCR-4 is expressed on CD34+ hematopoietic progenitors and leukemic cells and mediates transendothelial migration induced by stromal cell-derived factor-1. Blood 1998; 91: 4523–4530.

    CAS  Google Scholar 

  9. 9

    Poznansky MC, Olszak IT, Evans RH et al. Thymocyte emigration is mediated by active movement away from stroma-derived factors. J Clin Invest 2002; 109: 1101–1110.

    CAS  Article  Google Scholar 

  10. 10

    Grabovsky V, Feigelson S, Chen C et al. Subsecond induction of alpha4 integrin clustering by immobilized chemokines stimulates leukocyte tethering and rolling on endothelial vascular cell adhesion molecule 1 under flow conditions. J Exp Med 2000; 192: 495–506.

    CAS  Article  Google Scholar 

  11. 11

    Lavi E, Kolson DL, Ulrich AM, Fu L, Gonzalez-Scarano F . Chemokine receptors in the human brain and their relationship to HIV infection. J Neurovirol 1998; 4: 301–311.

    CAS  Article  Google Scholar 

  12. 12

    Tran PB, Miller RJ . Chemokine receptors: signposts to brain development and disease. Nat Rev Neurosci 2003; 4: 444–455.

    CAS  Article  Google Scholar 

  13. 13

    Amara A, Gall SL, Schwartz O et al. HIV coreceptor downregulation as antiviral principle: SDF-1alpha-dependent internalization of the chemokine receptor CXCR4 contributes to inhibition of HIV replication. J Exp Med 1997; 186: 139–146.

    CAS  Article  Google Scholar 

  14. 14

    Bleul CC, Farzan M, Choe H et al. The lymphocyte chemoattractant SDF-1 is a ligand for LESTR/fusin and blocks HIV-1 entry. Nature 1996; 382: 829–833.

    CAS  Article  Google Scholar 

  15. 15

    Feng Y, Broder CC, Kennedy PE, Berger EA . HIV-1 entry cofactor: functional cDNA cloning of a seven-transmembrane, G protein-coupled receptor. Science 1996; 272: 872–877.

    CAS  Article  Google Scholar 

  16. 16

    Oberlin E, Amara A, Bachelerie F et al. The CXC chemokine SDF-1 is the ligand for LESTR/fusin and prevents infection by T-cell-line-adapted HIV-1. Nature 1996; 382: 833–835.

    CAS  Article  Google Scholar 

  17. 17

    Winkler C, Modi W, Smith MW et al. Genetic restriction of AIDS pathogenesis by an SDF-1 chemokine gene variant. Science 1998; 279: 389–393.

    CAS  Article  Google Scholar 

  18. 18

    Mummidi S, Ahuja SS, Gonzalez E et al. Genealogy of the CCR5 locus and chemokine system gene variants associated with altered rates of HIV-1 disease progression. Nat Med 1998; 4: 786–793.

    CAS  Article  Google Scholar 

  19. 19

    van Rij RP, Broersen S, Goudsmit J, Coutinho RA, Schuitemaker H . The role of a stromal cell-derived factor-1 chemokine gene variant in the clinical course of HIV-1 infection. AIDS 1998; 12: F85–90.

    CAS  Article  Google Scholar 

  20. 20

    Ioanidis JP, Rosenberg PS, Goedert JJ et al. Effects of CCR5 Delta32, CCR2-741, and SDF1 3′A alleles on HIV-1 disease progression: an international meta-analysis of individual-patient data. Ann Intern Med 2001; 135: 782–795.

    Article  Google Scholar 

  21. 21

    Derdeyn CA, Costello C, Kilby JM et al. Correlation between circulating stromal cell-derived factor 1 levels and CD4+ cell count in human immunodeficiency virus type 1-infected individuals. AIDS Res Hum Retroviruses 1999; 15: 1063–1071.

    CAS  Article  Google Scholar 

  22. 22

    Ikegawa M, Yuan J, Matsumoto K et al. Elevated plasma stromal cell-derived factor 1 protein level in the progression of HIV type 1 infection/AIDS. AIDS Res Hum Retroviruses 2001; 17: 587–595.

    CAS  Article  Google Scholar 

  23. 23

    Soriano A, Martinez C, Garcia F et al. Plasma stromal cell-derived factor (SDF)-1 levels, SDF1-3′A genotype, and expression of CXCR4 on T lymphocytes: their impact on resistance to human immunodeficiency virus type 1 infection and its progression. J Infect Dis 2002; 186: 922–931.

    CAS  Article  Google Scholar 

  24. 24

    Bezzi P, Domercq M, Brambilla L et al. CXCR4-activated astrocyte glutamate release via TNFalpha: amplification by microglia triggers neurotoxicity. Nat Neurosci 2001; 4: 702–710.

    CAS  Article  Google Scholar 

  25. 25

    Langford D, Sanders VJ, Mallory M, Kaul M, Masliah E . Expression of stromal cell-derived factor 1alpha protein in HIV encephalitis. J Neuroimmunol 2002; 127: 115–126.

    CAS  Article  Google Scholar 

  26. 26

    Kaul M, Lipton SA . Chemokines and activated macrophages in HIV gp120-induced neuronal apoptosis. Proc Natl Acad Sci USA 1999; 96: 8212–8216.

    CAS  Article  Google Scholar 

  27. 27

    Zheng J, Thylin MR, Ghorpade A et al. Intracellular CXCR4 signaling, neuronal apoptosis and neuropathogenic mechanisms of HIV-1-associated dementia. J Neuroimmunol 1999; 98: 185–200.

    CAS  Article  Google Scholar 

  28. 28

    An P, Bleiber G, Duggal P et al. APOBEC3G genetic variants and their influence on the progression to AIDS. J Virol 2004; 78: 11070–11076.

    CAS  Article  Google Scholar 

  29. 29

    Amoroso A, Berrino M, Boniotto M et al. Polymorphism at codon 54 of mannose-binding protein gene influences AIDS progression but not HIV infection in exposed children. AIDS 1999; 13: 863–864.

    CAS  Article  Google Scholar 

  30. 30

    Carrington M, Nelson GW, Martin MP et al. HLA and HIV-1: heterozygote advantage and B*35–Cw*04 disadvantage. Science 1999; 283: 1748–1752.

    CAS  Article  Google Scholar 

  31. 31

    Dean M, Carrington M, Winkler C et al. Genetic restriction of HIV-1 infection and progression to AIDS by a deletion allele of the CKR5 structural gene. Science 1996; 273: 1856–1862.

    CAS  Article  Google Scholar 

  32. 32

    Faure S, Meyer L, Genin E et al. Deleterious genetic influence of CX3CR1 genotypes on HIV-1 disease progression. J Acquir Immune Defic Syndr 2003; 32: 335–337.

    CAS  Article  Google Scholar 

  33. 33

    Gonzalez E, Kulkarni H, Bolivar H et al. The influence of CCL3L1 gene-containing segmental duplications on HIV-1/AIDS susceptibility. Science 2005; 307: 1434–1440.

    CAS  Article  Google Scholar 

  34. 34

    Gonzalez E, Rovin BH, Sen L et al. HIV-1 infection and AIDS dementia are influenced by a mutant MCP-1 allele linked to increased monocyte infiltration of tissues and MCP-1 levels. Proc Natl Acad Sci USA 2002; 99: 13795–13800.

    CAS  Article  Google Scholar 

  35. 35

    McDermott DH, Zimmerman PA, Guignard F, Kleeberger CA, Leitman SF, Murphy PM . CCR5 promoter polymorphism and HIV-1 disease progression. Multicenter AIDS Cohort Study (MACS). Lancet 1998; 352: 866–870.

    CAS  Article  Google Scholar 

  36. 36

    Modi WS, Goedert JJ, Strathdee S et al. MCP-1–MCP-3–Eotaxin gene cluster influences HIV-1 transmission. AIDS 2003; 17: 2357–2365.

    CAS  Article  Google Scholar 

  37. 37

    Nakayama EE, Hoshino Y, Xin X et al. Polymorphism in the interleukin-4 promoter affects acquisition of human immunodeficiency virus type 1 syncytium-inducing phenotype. J Virol 2000; 74: 5452–5459.

    CAS  Article  Google Scholar 

  38. 38

    O’Brien SJ, Nelson GW, Winkler CA, Smith MW . Polygenic and multifactorial disease gene association in man: lessons from AIDS. Annu Rev Genet 2000; 34: 563–591.

    Article  Google Scholar 

  39. 39

    Smith MW, Dean M, Carrington M et al. Contrasting genetic influence of CCR2 and CCR5 variants on HIV-1 infection and disease progression. Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC), ALIVE Study. Science 1997b; 277: 959–965.

    CAS  Article  Google Scholar 

  40. 40

    Vasilescu A, Heath SC, Ivanova R et al. Genomic analysis of Th1-Th2 cytokine genes in an AIDS cohort: identification of IL4 and IL10 haplotypes associated with the disease progression. Genes Immun 2003; 4: 441–449.

    CAS  Article  Google Scholar 

  41. 41

    Vlahov D . The ALIVE study, a longitudinal study of HIV-1 infection in intravenous drug users: description of methods and characteristics of participants. NIDA Res Monogr Ser 103 1991; 109: 75–100.

    CAS  Google Scholar 

  42. 42

    Daar ES, Lynn H, Donfield S et al. Relation between HIV-1 and hepatitis C viral load in patients with hemophilia. J Acquir Immune Defic Syndr 2001; 26: 466–472.

    CAS  Article  Google Scholar 

  43. 43

    Hilgartner MW, Donfield SM, Willoughby A et al. Hemophilia growth and development study. Design, methods, and entry data. Am J Pediatr Hematol Oncol 1993; 15: 208–218.

    CAS  Article  Google Scholar 

  44. 44

    Goedert JJ, Kessler CM, Aledort LM et al. A prospective study of human immunodeficiency virus type 1 infection and the development of AIDS in subjects with hemophilia (see comments). N Engl J Med 1989; 321: 1141–1148.

    CAS  Article  Google Scholar 

  45. 45

    Detels R, Liu Z, Hennessey K et al. Resistance to HIV-1 infection. Multicenter AIDS Cohort Study. J Acquir Immune Defic Syndr 1994; 7: 1263–1269.

    CAS  Article  Google Scholar 

  46. 46

    Kaslow RA, Ostrow DG, Detels R, Phair JP, Polk BF, Rinaldo Jr CR . The Multicenter AIDS Cohort Study: rationale, organization, and selected characteristics of the participants. Am J Epidemiol 1987; 126: 310–318.

    CAS  Article  Google Scholar 

  47. 47

    Rutherford GW, Lifson AR, Hessol NA et al. Course of HIV-I infection in a cohort of homosexual and bisexual men: an 11 year follow up study. BMJ 1990; 301: 1183–1188.

    CAS  Article  Google Scholar 

  48. 48

    Salkowitz JR, Purvis SF, Meyerson H et al. Characterization of high-risk HIV-1 seronegative hemophiliacs. Clin Immunol 2001; 98: 200–211.

    CAS  Article  Google Scholar 

  49. 49

    Vlahov D, Polk BF . Perspectives on infection with HIV-1 among intravenous drug users. Psychopharmacol Bull 1988; 24: 325–329.

    CAS  PubMed  Google Scholar 

  50. 50

    Modi WS, Bergeron J, Sanford M . The human MIP-1beta chemokine is encoded by two paralogous genes, ACT-2 and LAG-1. Immunogenetics 2001; 53: 543–549.

    CAS  Article  Google Scholar 

  51. 51

    Stephens M, Smith NJ, Donnelly P . A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 2001; 68: 978–989.

    CAS  Article  Google Scholar 

  52. 52

    Centers for Disease Control. Revision of the CDC surveillance case definition for acquired immunodeficiency syndrome. MMWR 1987; 36 (Suppl. 1): 1S–15S.

  53. 53

    Gao X, Nelson GW, Karacki P et al. Effect of a single amino acid change in MHC class I molecules on the rate of progression to AIDS. N Engl J Med 2001; 344: 1668–1675.

    CAS  Article  Google Scholar 

  54. 54

    Smith MW, Dean M, Carrington M et al. Contrasting genetic influence of CCR2 and CCR5 variants on HIV-1 infection and disease progression. Science 1997a; 277: 959–965.

    CAS  Article  Google Scholar 

  55. 55

    Celentano DD, Galai N, Sethi AK et al. Time to initiating highly active antiretroviral therapy among HIV-infected injection drug users. AIDS 2001; 15: 1707–1715.

    CAS  Article  Google Scholar 

  56. 56

    Kimura R, Nishioka T, Soemantri A, Ishida T . Allele-specific transcript quantification detects haplotypic variation in the levels of the SDF-1 transcripts. Hum Mol Genet 2005; 14: 1579–1585.

    CAS  Article  Google Scholar 

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Maidar Jamba, Elizabeth Binns-Roemer, and Mary McNally provided laboratory expertise. We also thank the participants enrolled in the MHCS, ALIVE, HGDS, MACS, and SFCC cohorts. This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. NO1-CO-56000.

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Correspondence to C Winkler.

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Modi, W., Scott, K., Goedert, J. et al. Haplotype analysis of the SDF-1 (CXCL12) gene in a longitudinal HIV-1/AIDS cohort study. Genes Immun 6, 691–698 (2005).

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  • SDF-1 chemokine
  • epidemiology
  • haplotypes
  • HIV-1
  • AIDS

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