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Distribution of CCR2-64I and SDF1-3′A Alleles and HIV Status in 7 Ethnic Populations of Cameroon

Ma, Liying PhD*†; Marmor, Michael PhD‡**; Zhong, Ping MD*∥; Ewane, Leonard BSc¶; Su, Bing PhD§#; Nyambi, Phillipe PhD*††**

JAIDS Journal of Acquired Immune Deficiency Syndromes: 1 September 2005 - Volume 40 - Issue 1 - pp 89-95
Epidemiology and Social Science

Limited information is available on the prevalence among rural Africans of host genetic polymorphisms conferring resistance to HIV-1 infection or slowing HIV disease progression. We report the allelic frequencies of the AIDS-related polymorphisms CCR2-64I, SDF1-3′A, and CCR5-Δ32 in 321 volunteers from 7 ethnic groups in Cameroon. Allelic frequencies differed among the 7 ethnic groups, ranging from 10.8% to 31.3% for CCR2-64I and 0.0% to 7.1% for SDF1-3′A. No CCR5-Δ32 alleles were found. HIV seroprevalence was 6.9% in the total population and peaked at younger ages in girls and women than in boys and men. Among 15- to 54-year-olds, HIV seroprevalence varied from 2.0% to 11.1% among the village populations. Conditional logistic regression analysis using data from boys and men aged 15 to 54 years showed the number of CCR2-64I alleles to be a significant risk factor for HIV seropositivity (odds ratio per allele adjusted for age and matched on ethnic group = 6.3, 95% confidence interval: 1.3-30.3); this association was not found in women. The findings are consistent with the hypothesis that CCR2-64I alleles may delay HIV disease progression without affecting susceptibility to infection among men. We did not observe this relation among women, and other factors, such as multiple pregnancies or maternal stressors (eg, breastfeeding), may have masked any protective effect of CCR2-64I alleles. Further study of this issue among women is warranted. SDF1-3′A did not differ between HIV-seropositive and HIV-seronegative individuals but was associated with increasing age among HIV-seronegative women, suggesting a protective effect against HIV-1 infection.

From the *Department of Pathology, New York University School of Medicine, New York, NY; †National Center for AIDS/STD Prevention and Control, China Center for Disease Control and Prevention, Beijing, China; ‡Department of Environmental Medicine and Medicine, New York University School of Medicine, New York, NY; §Center for Genome Information, University of Cincinnati, Cincinnati, OH; Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China; ¶Laboratoire de Santé Hygiene Mobile, Yaounde, Cameroon; #Key Laboratory of Cellular and Molecular Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; **Center for AIDS Research, New York University School of Medicine, New York, NY; and ††Research Enhancement Award Program, Veterans Affairs Medical Center, New York, NY.

Received for publication August 19, 2004; accepted January 12, 2005.

Supported in part by grants from the National Institutes of Health (AI47053, AI36085, AI27742 and HL59725) and the Fogarty International Center (TW01254 and TW01409) and by funds from the Department of Veterans Affairs (Merit Review Award and the Research Enhancement Program).

Reprints: Phillipe Nyambi, Department of Pathology, New York University School of Medicine, c/o Veterans Affairs Medical Center, 423 East 23rd Street, Room 18124N, New York, NY 10010 (e-mail:

The pathogenesis of HIV-1 infection begins and evolves with viral entry into the host cell by means of the CD4 receptor and at least 1 of several coreceptors in the CC and CXC chemokine receptor families expressed on the surface of the cell membrane.1,2 Two chemokine receptors, CCR5 and CXCR4, are major coreceptors required for entry of macrophage-tropic and T-cell-tropic viruses, respectively, into CD4+ cells.3-6 Individuals who are homozygous for a 32-base pair (bp) deletion in the CCR5 gene (CCR5-Δ32/Δ32) are resistant to HIV-1 infection, whereas heterozygous CCR5-Δ32/wild-type individuals seem to have less but still substantial resistance to HIV infection and delayed progression to AIDS.7-18 The prevalence of CCR5Δ32 varies by ethnicity, with 10% to 15% in whites and approximately 2% in African Americans, although it is virtually absent in native Africans and East Asians.17,19

CCR2-64I has been shown to vary among ethnic groups,20-24 with a frequency of 13% in South Africans and 21% to 23% in Kenyans.25,26 CCR2 is a minor coreceptor used by HIV for which a point mutation (a guanine-to-adenine transition at nucleotide position 190 that changes codon 64 of amino acid from valine to isoleucine) has been shown to prolong AIDS-free survival from 2 to 4 years in HIV-1 seroconvertors.21 A meta-analysis of data from 10 cohort studies showed individuals with 1 or 2 copies of CCR2-64I to have a 58% reduced risk of AIDS in the first 4 years after HIV seroconversion, followed by a 19% reduction in the next 4 years and no reduction thereafter.27 The same analysis showed reductions in the risk of death during the first 8 years after HIV seroconversion among carriers of the CCR2-64I allele. A recent study suggested that homozygosity of the CCR2-64I allele may be implicated in natural resistance to HIV-1 transmission through sexual contact in Asia.24 Furthermore, a higher prevalence of CCR2-64I alleles was found in HIV-uninfected children compared with HIV-infected children born to a cohort of HIV-1-infected women in Argentina.28

Another host genetic factor associated with altered HIV disease course is the stromal-derived factor 1 (SDF1) that is known to be the unique ligand of HIV-1 coreceptor CXCR4. A mutation from guanine to adenine at nucleotide position 801 in the 3′ untranslated region (3′UTR) of the SDF1 gene transcript (SDF1-3′A) has been associated with delayed progression to AIDS in homozygous individuals, particularly in the late stage of HIV-1 disease.22 The frequency of this gene (SDF1-3′A) ranges widely across ethnic groups from 3% to 71% worldwide and from 3% to 9% in Africans.23,26

There are more than 250 ethnic groups in Cameroon, most of whom live in homogeneous rural villages. A previous survey conducted in calendar year 2000 indicated substantial variation in HIV seroprevalence, ranging from 0% to 18% among ethnic groups in different villages of Cameroon.29 Socioeconomic factors associated with HIV transmission included age, marital status (in women), and sexual risk.29 Whether genetic variation among ethnic groups can account for or reflect important portions of the differences in HIV seroprevalence among groups in Cameroon is unknown. In the present study, we investigated 3 AIDS-resistant gene variants, CCR2-64I, SDF1-3′A, and CCR5-Δ32, in 7 ethnic groups from rural areas of Cameroon and analyzed the association of these host genetic polymorphisms with HIV seropositivity.

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Study Subjects

A total of 321 blood samples were obtained in calendar year 2002 from convenience sampling of the residents of 8 villages located in the equatorial rain forest regions of Cameroon (Table 1). On arriving in a village, the survey team would obtain approval for the study from the local chief, and community social workers would circulate in the village telling residents that the survey was being conducted. The team enrolled all volunteers who arrived at their location. Surveys were conducted in the early morning to reduce the chances that working adults would be missed. In general, persons in these villages have remained in stable residence for the last 5 years, with limited travel out of their villages. The ages of the studied subjects ranged from 10 to 70 years, with an average of 35 years. After assuring anonymity, oral informed consent to donate blood for HIV testing and to measure host genetic polymorphisms was obtained from each subject. Plasma samples were first tested for the presence of HIV-1 antibodies using the Abbott Determine HIV-1/2 rapid assay (Abbott, Wiesbaden, Germany), and samples that were reactive in this assay were retested with the BIO-RAD HIV-1 enzyme-linked immunosorbent assay kit (BIO-RAD Laboratory, Redmond, WA). Samples reactive in both assays were considered HIV-positive. Discrepant samples were tested by Western blot analysis (Sanofi Pasteur, Marnes La Coquette, France) to confirm HIV seropositivity.

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DNA Extraction and Polymerase Chain Reaction Amplification

Genomic DNA was extracted from whole blood anticoagulated with EDTA by the use of a QIAamp DNA Blood Mini kit (Qiagen, Valencia, CA) according to the manufacturer's recommendations. DNA concentration was measured by an ultraviolet spectrophotometer (Ultrospec 3000; Pharmacia Biotech). To detect the CCR2 mutation, a pair of primers (5′-GGATTGAAC AAGGACGCATTTCCCC-3′ and 5′-TGCACATTGCATTCCCAAAGACCC-3′)30 were used. The amplification was done for 5 minutes at 94°C, followed by 35 cycles for 60 seconds, 60 seconds, and 60 seconds at 94°C, 60°C, and 72°C, respectively, followed by an extension of 7 minutes at 72°C in a thermal cycler (MJ Research). To detect the SDF-1 mutation, a pair of primers (5′-CAGTCAACCTGGGCAAAGCC-3′ and 5′-GAAAGCTTTGGACCTGAGAG TCC-3′)22 were used. The amplification was done for 5 minutes at 94°C, followed by 25 cycles for 30 seconds, 30 seconds, and 30 seconds at 94°C, 55°C, and 72°C, respectively, followed by an extension of 7 minutes at 72°C. To detect the CCR5Δ32 mutation, the specific segment of the CCR5 gene was amplified using a pair of primers (5′-ACCAGATCTCAAAAAGAAGGTCT-3′ and 5′-CATGATGGTGAAG ATAAGCCTC ACA-3′). The amplification was done for 5 minutes at 94°C, followed by 35 cycles for 30 seconds, 30 seconds, and 30 seconds at 94°C, 55°C, and 72°C, respectively, followed by a final extension of 7 minutes at 72°C.

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Genotype Analysis

Genotyping was carried out using restriction fragment length polymorphism (RFLP) on the basis of the respective enzyme restriction site in 2 polymerase chain reaction (PCR) products, CCR2 and SDF1.22,30 Briefly, Fok I (Promega Corporation) and MspI (Promega Corporation) were used for digestion of PCR products of CCR2 and SDF1, respectively. After digestion, PCR products were genotyped by means of agarose gel electrophoresis. Fok I does not cut the wild type; instead, it cuts the mutant in CCR2. MspI cuts the wild type but not the mutant in SDF-1. Therefore, in CCR2 genotyping analysis, the resulting fragment of 379 bp is identified as CCR2 wild type, whereas 3 fragments of 164 bp, 215 bp, and 379 bp and 2 fragments of 164 bp and 215 bp are identified as CCR2-64I heterozygote and CCR2-64I homozygote, respectively.30 For SDF-1, wild type generates 2 fragments of 205 bp and 106 bp, whereas heterozygote wild type/mutant generates 3 fragments of 311 bp, 205 bp, and 106 bp and homozygote mutant/mutant generates 1 fragment of 311 bp.22 For identification of CCR5Δ32, the PCR amplicon was electrophoresed on a 2% agarose gel, stained with ethidium bromide, visualized under an ultraviolet transilluminator, and compared with control CCR5Δ32 mutant homozygote. The PCR product was 178 bp for the wild genotype (CCR5/CCR5), whereas a product of 156 bp indicated a mutant homozygote (CCR5Δ32/CCR5Δ32). The simultaneous presence of 178-bp and 156-bp bands indicated a heterozygous genotype (CCR5/CCR5Δ32).

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Statistical Analysis

Allele frequencies were calculated as (h + 2H)/2N, where H is the number of homozygous mutation genotypes, h is the number of heterozygous mutation genotypes, and N is the total number of the sample population. A Hardy-Weinberg equilibrium (HWE) exact analysis was performed for each ethnic population using PopGen software. This analysis describes the expected genotype frequencies in a large random-mating population, assuming that evolution is not occuring. The 95% confidence interval (CI) was calculated for the allelic frequencies and for difference in allelic frequencies between groups using the Jeffreys-Perks method.31 Comparison of genotype and allelic frequencies between the infected and uninfected populations and among different HIV-1-seroprevalent (≥10% or <10%) populations was calculated by the Fisher exact test. Associations between genetic polymorphisms and HIV infection were also investigated by conditional logistic regression analysis with matching on ethnic group and adjustment for differences in age.32 In a cross-sectional study conducted in an area with an HIV epidemic of long duration, we hypothesized that a protective effect of an allele on disease progression in the absence of an impact of that allele on susceptibility to infection would be manifested by an odds ratio (OR) for HIV infection significantly greater than 1.0 because of increased prevalence of a protective allele among long-term HIV-infected survivors. Conversely, an allele that protected against infection would be expected to be manifested by an OR for HIV infection significantly less than 1.0 because of increased prevalence of the allele among HIV-uninfected individuals.

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HIV-Seroprevalence Among Individuals in Rural Villages

The average HIV-1 seroprevalence was 6.9% in the total population studied: 6.5% among girls and women and 7.4% among boys and men (see Table 1). Seropositivity peaked at 25 to 34 years of age among women (10%) compared with 35 to 44 years of age among men (18.5%). HIV-seropositive men were significantly older than HIV-seropositive women (mean age among men was 36.9 ± 8.4 years compared with 27.2 ± 10.0 years among women; P = 0.02, t test). No HIV-1-seropositive individuals were found among 7 persons tested aged <15 years or among 44 persons tested aged ≥55 years. HIV seropositivity varied by ethnic group, from a minimum of 2.0% among Pygmies to 12.0% among Kaka. Data on subjects' numbers of children were missing for many subjects, but there was a suggestion of declining HIV seroprevalence with increasing numbers of children among women (P = 0.15, test for trend).

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Genotype and Allelic Frequencies

The HWE exact analysis for CCR2-64I and SDF1-3′A was performed for each ethnic population using PopGen software. The χ2 tests showed that both loci (CCR2-64I and SDF1-3′A) of the 7 ethnic groups are in equilibrium (P > 0.05). The observed genotype frequencies had no significant difference from the frequencies expected in each group.

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The genotype and allelic frequency distributions for CCR2-64I and SDF1-3′A are presented in Table 2. The prevalences of CCR2-64I/+ heterozygotes were 42.5%, 37.8%, 35.0%, 32.0%, 28.6%, 25.0%, and 21.6% in the Bidjouki, Sanaga, Zime, Kaka, Zamane, Baka, and Pygmie ethnic groups, respectively (average prevalence = 31.3%). The CCR2-64I homozygous mutation (64I/64I) was found in all ethnic groups except Pygmies and Sanaga. The 64I/64I prevalences of the Bidjouki, Zime, Baka, Kaka, and Zamane ethnic groups were 10.0%, 6.7%, 5.0%, 4.1%, and 4.0%, respectively (average = 4.3%). Between-group differences in allelic frequencies were significant for the following comparisons: Bidjouki and Pygmie populations (difference = 20%, 95% CI: 8.7%-32.3%), Bidjouki and Baka populations (13.5%, 95% CI: 1.3%-25.7%), Bidjouki and Zamane populations (12.9%, 95% CI: 0.2%-25.6%), and Zime and Pygmie populations (13.4%, 95% CI: 5.5%-21.3%; Table 3A).

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This study did not find SDF1-3′A homozygosity (3′A/3′A) in any ethnic groups of subjects studied, although heterozygosity (SDF-1/3′A) was found in all groups except the Pygmie population (see Table 2). The SDF-1/3′A prevalence rates of the Zamane, Zime, Bidjouki, Sanaga, Kaka, Baka, and Pygmie populations were 14.0%, 13.0%, 12.5%, 8.0%, 4.0%, 2.0%, and 0%, respectively (average allelic frequency = 3.8%). Significant differences between ethnic groups were found in the following comparisons: Bidjouki and Pygmie populations (6.3%, 95% CI: 1%-11.6%), Zime and Pygmie populations (6.7%, 95% CI: 2.2%-11.2%), Zime and Baka populations (5.9%, 95% CI: 1.2%-10.6%), Zamane and Pygmie populations (7.1%, 95% CI: 2.0%-12.2%), and Zamane and Baka populations (6.3%, 95% CI: 1.0%-11.6%; see Table 3B).

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As expected, no CCR5Δ32 mutation with homozygote and heterozygote alleles was identified in any of the subjects analyzed in this study, which strongly supports earlier findings that the CCR5Δ32 mutation is rare in Africans.19,20

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HIV Serostatus and Prevalence of Genotype Alleles

Combined across all ethnic groups, the prevalence of the CCR2-64I/+ allele was higher among HIV-seropositive individuals (45.5%) than among HIV-seronegative individuals (29.8%), as was the frequency of the CCR2-64I/64I genotype (9.1% among HIV-seropositive individuals, 4.0% among HIV-seronegative individuals). Among the 10 HIV-1-seropositive men, the frequency of CCR2-64I (40%) was higher than among the 12 HIV-1-seropositive women (25%). Conditional logistic regression analysis (matched on ethnic group and adjusted for age) was conducted to investigate risk factors for HIV seropositivity. Data from individuals <15 and ≥55 years of age were deleted because of the lack of HIV-seropositive persons found in these age groups. Male and female data were analyzed separately because of the substantial differences in the epidemiology of HIV by gender. Among men aged 15 to 54 years, a significant association was found between HIV-1 seropositivity and the number of CCR2-64I alleles (OR per allele = 6.3, 95% CI: 1.3-30.3) after adjustment for age (Table 4). Treating CCR2-64I homozygotes and heterozygotes as a homogeneous group did not alter the results substantially (OR for HIV seropositivity among men associated with the presence of 1 or 2 CCR2-64I alleles = 6.5, 95% CI: 1.2-35 matched on village and adjusted for age). Conditional logistic regression among women did not yield any significant associations with CCR2-64I.

Summed across all ethnic groups, the allelic frequencies of SDF-1/3′A were not statistically different between HIV-seropositive (4.7%) and HIV-seronegative (4.0%) individuals (P > 0.05, Fisher exact test; Table 5). There was a significantly increased frequency of SDF-1, however, in the frequency of the SDF-1/3′A allele among ethnic groups with >10% HIV seroprevalence compared with those with <10% HIV seroprevalence. Conditional logistic regression analysis (matched on ethnic group and adjusted for age) found no association between SDF-1-3 alleles and HIV seropositivity among 15- to 54-year-olds overall or in the subsets of men and women. Among HIV-seronegative women aged 15 to 54 years, however, there was a significant association between increasing age and increasing SDF-1-3 positivity (OR per decade of age = 2.7, 95% CI: 1.1-6.6), suggesting an enrichment in the SDF-1-3 allele with increasing duration of HIV-uninfected survival. The SDF1-3′A/3′A genotype was not observed in any of the individuals in this study.

Interestingly, the Pygmie population had fewer genetic variants than we observed in other populations. We observed no HIV-seropositive Pygmies in our previous study,29 and only 1 (2%) of 51 Pygmies was HIV-1-seropositive in the present study.

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Studies have revealed that the CCR2-64I allele is broadly distributed across the world's population, with frequencies varying from 10% to 26%.23 In particular, it was reported that the frequency of the CCR2-64I allele in South Africans is 13%, and in African populations in Kenya, it ranged from 21% to 23%.25,26 The frequency of the SDF1 variant SDF1-3′A has been shown to vary from 1% in South Africans to 6% in African Americans.23,26 Data on the different genetic frequencies of CCR2-64I and SDF1-3A reported in African populations living in different African countries are sparse, however. The present study is the first to describe the distribution of CCR2-64I, SDF1-3′A, and CCR5Δ32 polymorphisms in rural ethnic groups in Cameroon, a country inhabited by more than 250 ethnic groups. The study revealed differences in frequencies of CCR2-64I and SDF1-3A variants among ethnic populations, with a significantly higher allelic frequency of CCR2-64I in the Bidjouki population than in the Zamane (12.9%), Baka (13.5%), and Pygmie (20.5%) populations as well as in the Zime population compared with the Pygmie (13.4%) population (see Table 3A). The frequency (31.3%, 95% CI: 21.2-41.4) of CCR2-64I in the Bidjouki ethnic population is 3 times higher than that (10.8%, 95% CI: 5.0-16.0) in the Pygmie ethnic population (P < 0.05). The study also revealed a significantly higher allelic frequency of SDF1-3′A in the Bidjouki population than in the Pygmie (6.3%) population, in the Zime population compared with the Baka (5%) and Pygmie (6.7%) populations, and in the Zamane population compared with the Baka (1%) and Pygmie (2.0%) populations (see Table 3B). These studies strongly suggest that the allelic frequencies of CCR2-64I and SDF1-3′A are different among these ethnic groups in Cameroon. Interestingly, the Pygmie ethnic population had the lowest allelic frequencies of CCR2-64I and SDF1-3′A compared with other ethnic groups, whereas the prevalence of HIV infection in this ethnic group was the lowest in this study as well as in our previous report.29

Variation in HIV-1 transmission and/or disease progression has been associated with a combination of host genetic factors.8-10,21,22 An increasing number of genetic polymorphisms of chemokine and chemokine-receptor genes have been related to the risk of HIV-1 transmission and disease progression.33,34 The most studied mutation of importance in host genetic resistance to HIV infection is a 32-nucleotide deletion in the CCR5 gene (CCR5Δ32), which results in the truncation of the CCR5 protein and, ultimately, the abrogation of its HIV coreceptor function. Homozygous individuals (CCR5Δ32/CCR5Δ32) who lack a cell surface protein used as a viral receptor may be resistant to infection. The most common CCR5Δ32 gene variant was found in whites. As noted, none of CCR5Δ32 mutations with homozygote and heterozygote alleles was found in any of the 321 subjects from Cameroon who were analyzed in this study, which strongly supports earlier findings that the CCR5Δ32 mutation is rare in Africans.17,20

Our analysis revealed a higher CCR2-64I frequency among HIV-seropositive individuals compared with HIV-seronegative individuals (P < 0.05), suggesting that this variant has no natural resistance to HIV infection in the ethnic populations studied. Furthermore, we found a significantly elevated OR for HIV seropositivity associated with CCR2-64I positivity after adjusting for age and matching on ethnic group. No association was found, however, between CCR2-64I and HIV seropositivity in women. The finding in men would be expected under the hypothesis that CCR2-64I delays progression of HIV disease to AIDS and death, and thus increases the proportion of men with CCR2-64I alleles among survivors identified in cross-sectional sampling (and conducted at some unknown time after the onset of HIV disease in affected individuals). The failure to observe this relation among women may reflect an increased prevalence of superinfection with non-CCR5-dependent strains in women compared with men or other factors that may influence the survival of HIV-infected women, such as stresses of pregnancy or nursing among women, to which men are not subjected. Partial support of this hypothesis was found in an association between numbers of children and HIV seropositivity, with fewer HIV-infected women found among those with larger numbers of children. Long-term cohort studies are needed to investigate whether these hypotheses might be correct, however.

The present findings should be interpreted with some caution because of the small numbers of HIV-seropositive subjects on which the findings are based and the lack of comprehensive or random sampling of the populations of the villages studied. Participants included more women than men, which may have been the result of our convenience sampling, because the sampling techniques my have caused us to miss persons who might have been traveling when our team visited their village. It is possible that the sampling techniques could have thus affected our estimates of HIV seroprevalence, but it seems unlikely that the sampling could have introduced differential sampling of one genotype over another, which would be required to introduce bias into our main findings. Future studies with larger numbers of subjects would better allow statistical adjustment for marital status in addition to the demographic factors of age and ethnic group. The problems inherent in observations based on cross-sectional sampling also are important. Data from longitudinal studies would be more easily interpretable and, in particular, would allow separation of the possible impact of genotype on susceptibility to HIV infection from its possible impact on the rate of progression of HIV disease.

Cameroon consists of more than 250 different ethnic populations, most of whom live in rural villages. Genotype analysis of CCR5Δ32, CCR2-64I, and SDF1-3′A gene variants among 7 different ethnic populations living in rural villages of Cameroon revealed that there are differences in the prevalence of polymorphisms among these ethnic groups. Analysis of the CCR2-64I and SDF1-3′A variants with HIV seropositivity and disease progression did not suggest any natural resistance to infection but supported a role for CCR2-64I in delaying the progression of HIV disease. This study strongly suggests that CCR2-64I and perhaps unknown but HIV-relevant host genes occur at different frequencies in different ethnic groups in Cameroon and, most likely, elsewhere in Africa. Genetic variability may need to be taken into consideration when vaccine trials are conducted in Africa, especially because altered progression to disease may be an end point in initial vaccine trials.

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The authors thank the individual volunteers who provided their samples for these studies. They also thank the Minister of Public Health, Urbain Olanguena Awono, for his support in these studies.

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1. Berger EA, Murphy PM, Farber JM. Chemokine receptors as HIV-1 coreceptors: roles in viral entry, tropism, and disease. Annu Rev Immunol. 1999;17:657-700.
2. McNicholl JM, Smith DK, Qari SH, et al. Host genes and HIV: the role of the chemokine receptor gene CCR5 and its allele. Emerg Infect Dis. 1997;3:261-271.
3. Cocchi F, DeVico AL, Garzino-Demo A, et al. Identification of RANTES, MIP-1 alpha, and MIP-1 beta as the major HIV-suppressive factors produced by CD8+ T cells. Science. 1995;270:1811-1815.
4. Feng Y, Broder CC, Kennedy PE, et al. HIV-1 entry cofactor: functional cDNA cloning of a seven-transmembrane, G protein-coupled receptor. Science. 1996;272:872-877.
5. Deng H, Liu R, Ellmeier W, et al. Identification of a major co-receptor for primary isolates of HIV-1. Nature. 1996;381:661-666.
6. Doranz BJ, Rucker J, Yi Y, et al. A dual-tropic primary HIV-1 isolate that uses fusin and the beta-chemokine receptors CKR-5, CKR-3, and CKR-2b as fusion cofactors. Cell. 1996;85:1149-1158.
7. O'Brien SJ, Nelson GW, Winkler CA, et al. Polygenic and multifactorial disease gene association in man: lessons from AIDS. Annu Rev Genet. 2000;34:563-591.
8. Ioannidis JP, Rosenberg PS, Goedert JJ, et al. Effects of CCR5-Delta32, CCR2-64I, 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.
9. Ahuja S. Genetic condoms of HIV-1 infection: using host genetics to dissect HIV-1 pathogenesis. Presented at: 10th Conference on Retroviruses and Opportunistic Infections; 2003; Boston.
10. Kaslow RA, Tang J, Dorak MT. Comparison of effects on infection and disease progression. Presented at: 10th Conference on Retroviruses and Opportunistic Infections; 2003; Boston.
11. Liu R, Paxton WA, Choe S, et al. Homozygous defect in HIV-1 coreceptor accounts for resistance of some multiply-exposed individuals to HIV-1 infection. Cell. 1996;86:367-377.
12. Barroga CF, Raskino C, Fangon MC, et al. The CCR5Delta32 allele slows disease progression of human immunodeficiency virus-1-infected children receiving antiretroviral treatment. J Infect Dis. 2000;182:413-419.
13. 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.
14. Munoz A, Kirby AJ, He YD, et al. Long-term survivors with HIV-1 infection: incubation period and longitudinal patterns of CD4+ lymphocytes. J Acquir Immune Defic Syndr Hum Retrovirol. 1995;8:496-505.
15. Pantaleo G, Menzo S, Vaccarezza M, et al. Studies in subjects with long-term nonprogressive human immunodeficiency virus infection. N Engl J Med. 1995;332:209-216.
16. Gonzalez E, Dhanda R, Bamshad M, et al. Global survey of genetic variation in CCR5, RANTES, and MIP-1alpha: impact on the epidemiology of the HIV-1 pandemic. Proc Natl Acad Sci USA. 2001;98:5199-5204.
17. O'Brien SJ, Moore JP. The effect of genetic variation in chemokines and their receptors on HIV transmission and progression to AIDS. Immunol Rev. 2000;177:99-111.
18. Marmor M, Sheppard HW, Donnell D, et al. Homozygous and heterozygous CCR5-Δ32 genotypes are associated with resistance to HIV infection. J Acquir Immune Defic Syndr. 2001;27:472-481.
19. Martinson JJ, Chapman NH, Rees DC, et al. Global distribution of the CCR5 gene 32-basepair deletion. Nat Genet. 1997;16:100-103.
20. Ramaley PA, French N, Kaleebu P, et al. HIV in Africa (communication arising): chemokine-receptor genes and AIDS risk. Nature. 2002;417:140.
21. 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. 1997;277:959-965.
22. Winkler C, Modi W, Smith MW, et al. Genetic restriction of AIDS pathogenesis by an SDF-1 chemokine gene variant. ALIVE Study, Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC). Science. 1998;279:389-393.
23. Su B, Jin L, Hu F, et al. Distribution of two HIV-1-resistant polymorphisms (SDF1-3′A and CCR2-64I) in East Asian and world populations and its implication in AIDS epidemiology. Am J Hum Genet. 1999;65:1047-1053.
24. Louisirirotchanakul S, Liu H, Roongpisuthipong A, et al. Genetic analysis of HIV-1 discordant couples in Thailand: association of CCR2 64I homozygosity with HIV-1-negative status. J Acquir Immune Defic Syndr. 2002;29:314-315.
25. Anzala AO, Ball TB, Rostron T, et al. CCR2-64I allele and genotype association with delayed AIDS progression in African women. University of Nairobi Collaboration for HIV Research. Lancet. 1998;351:1632-1633.
26. Williamson C, Loubser SA, Brice B, et al. Allelic frequencies of host genetic variants influencing susceptibility to HIV-1 infection and disease in South African populations. AIDS. 2000;14:449-451.
27. Mulherin SA, O'Brien TR, Ioannidis JP, et al. Effects of CCR5-Delta32 and CCR2-64I alleles on HIV-1 disease progression: the protection varies with duration of infection. AIDS. 2003;17:377-387.
28. Mangano A, Kopka J, Batalla M, et al. Protective effect of CCR2-64I and not of CCR5-Δ32 and SDF1-3′A in pediatric HIV-1 infection. J Acquir Immune Defic Syndr. 2000;23:52-57.
29. Nyambi P, Zekeng L, Kenfack H, et al. HIV infection in rural villages of Cameroon. J Acquir Immune Defic Syndr. 2002;31:506-513.
30. Magierowska M, Theodorou I, Debre P, et al. Combined genotypes of CCR5, CCR2, SDF1, and HLA genes can predict the long-term nonprogressor status in human immunodeficiency virus-1-infected individuals. Blood. 1999;93:936-941.
31. Beal SL. Asymptotic confidence intervals for the difference between two binomial parameters for use with small samples. Biometrics. 1987;43:941-950.
32. Corporation CS. Egret for Windows [computer program]. Cambridge, MA: Cytel Software Corporation; 1991.
33. Tang J, Shelton B, Makhatadze NJ, et al. Distribution of chemokine receptor CCR2 and CCR5 genotypes and their relative contribution to human immunodeficiency virus type 1 (HIV-1) seroconversion, early HIV-1 RNA concentration in plasma, and later disease progression. J Virol. 2002;76:662-672.
34. Michael NL. Host genetic influences on HIV-1 pathogenesis. Curr Opin Immunol. 1999;11:466-474.

CCR2-64I; SDF1-3′A; CCR5Δ32; allelic frequency; HIV-1; ethnic groups

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