Distribution of CCR5-∆32 and HLA-B*57:01alleles in HIV-seropositive and HIV-exposed seronegative Peruvian individuals

Distribution of CCR5-∆32 and HLA-B*57:01alleles in HIV-seropositive and HIV-exposed seronegative Peruvian individuals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Distribution of CCR5-∆32 and HLA-B*57:01alleles in HIV-seropositive and HIV-exposed seronegative Peruvian individuals Carlos Yabar, Susan Echevarría-Correa, Daisy Obispo-Achallma, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6329775/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Aug, 2025 Read the published version in Human Genome Variation → Version 1 posted 5 You are reading this latest preprint version Abstract Little information is available about CCR5-Δ32 and HLA-B*57:01 alleles in the Peruvian population, especially in HIV-negative people with high-risk sexual behavior. In this study, we described the prevalence of these alleles in HIV-exposed seronegative individuals (PS) and HIV-seropositive individuals (PVV). For this purpose, 300 individuals were recruited: 150 from each group, and the selected alleles were characterized by endpoint PCR, real-time PCR, and DNA sequencing, respectively. According to our results, the prevalence of CCR5/CCR5-Δ32 heterozygous was 2.7%, and no homozygous cases were found. The population was in Hardy-Weinberg equilibrium for the CCR5 locus. Regarding HLA-B*57:01, only one case was found in the PS group, while no case was found from PVV group. No statistical difference was detected between both groups (p>0.05). In conclusion, we showed a low prevalence for CCR5-Δ32 as HLA-B*57:01 in Peruvian population. Since these alleles were also found indistinguishably from positives and negative Peruvian people with high-risk sexual behavior, it is possible that other genetic factor can play an important role to non-transmission of HIV in this population. Further cost-effectiveness studies are required to justify the genotyping test by using HLA-B*57:01 allele as routine test in Peru. Health sciences/Diseases/Infectious diseases/HIV infections Health sciences/Biomarkers/Prognostic markers Biological sciences/Genetics/Genetic markers CCR5-Δ32 HLA-B*57:01 prevalence HIV-1 seropositive individuals VIH exposed seronegative individuals Peruvian population. Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Genetics factor have been involved to show resistant subjects to HIV infection despite multiple high-risk exposures to HIV or different rates of progression to Acquired Immune Deficiency Syndrome (AIDS) from infected subjects [ 1 ]. Genes such as CCR5 Δ32 and HLA-B*57:01 have been implicated in viral entry and immune response processes, respectively [ 2 ]. In the first case, a 32bp deletion of CCR5 gene is sufficient to interfere with and even prevent viral entry into the cell, especially when homozygous. [ 1 ]. The HLA-B*57:01 allele is not only associated with slow progression to AIDS [ 3 ], but also with genetic susceptibility to the antiretroviral drug abacavir hypersensitivity reaction (ABC-HSR) [ 4 ], which is known to cause severe clinical manifestations [ 5 ], reason why HLA-B*57:01 genotyping is recommended before prescribing the drug [ 6 ]. In Peru, the Ministry of Health has developed the technical standard NTS N°169-MINSA/2020/DGIESP [ 7 ], which establishes the requirement to perform the HLA-B*57:01 genotyping test before administering abacavir. However, this political decision was made without having proven that HLA-B*57:01 frequency in the Peruvian population. In contrast to Europe, the prevalence of both CCR5-Δ32 and HLA-B*57:01 is low in African, Asian and Latin American populations [ 8 ]. In Peru, this mutation may have been introduced into the local population by gene flow through admixture with the European population [ 9 , 10 ]. This is supported by few reports found in some Peruvian subjects [ 8 , 11 ]. However, none these studies included geographic origin of the subjects recruited which difficult its interpretation since Peruvian population is a join of communities showing different degrees of ethnic admixture and consequently genetic variability [ 12 ]. Moreover, in the context of HIV/AIDS disease none of these studies included clinical and socio-epidemiological information that may be useful to know the importance of this alleles in the epidemic evolution in Peru. For this proposal, we recruited Peruvian individuals and requested data on their geographic origin and social, epidemiological and clinical characteristics that might provide more information to understand how the genetic characteristics of the Peruvian population might be related to the HIV/AIDS epidemic. MATERIALS AND METHODS Type and Design of Study Observational cross-sectional study performed between December 2020 and November 2021 Population and sample size The population corresponds to Peruvian individuals treated at the Asociación Civil Voluntades Lima Norte Non-Governmental Organization and the Santa Rosa Hospital. This population was divided into two groups: (1) HIV-exposed seronegative individuals (PS) and (2) HIV-seropositive individuals (PVV). The geographic origin of the participants was predominantly from Lima (71%), a city characterized by having a population with a high percentage of admixture and the greatest genetic diversity in the country [ 15 ]. From this population, the sample size was calculated using the proportion formula for finite population based on: i) an expected prevalence of 1% for HLA-B*57:01 and CCR5-Δ32 in a mixed population —mainly with native ancestry—¸ii) a population of 800 individuals, iii) a confidence level of 95%, and iv) margin of error of 1%. The minimum number of participants required to estimate the prevalence of CCR5-Δ32 and HLAB-57:01 alleles was 258; however, in this study a sample size of 300 individuals was used to increase the power and precision of the results. The selection criteria were the following: i) Peruvian nationality, iii) legal age (18 years and more), iii) both sexes (male and females), iv) agreement to participate in the study by signing an informed consent and completing a survey using a data collection instrument. Furthermore, for the PVV group, a diagnosis of HIV seropositivity was requested through confirmatory tests, whereas, for the PS group, seronegative diagnosis confirmed by both 3rd and 4th generation rapid tests, in addition to manifest characteristics of sexual behavior with a high risk of HIV transmission, such as a history of occasional sexual contact with sex workers, intermittent condom use, and multiple sexual partners. CCR5 Genotyping DNA was extracted using the NucleoSpin kit (Macherey-Nagel, Germany), according to the manufacturer's recommendations. CCR5 genotyping was based on Endpoint PCR assay using primers flanking the 32 bp deletion, CCR5 DELTA1 (5'-ACCAGATCTCTCAAAAAGAAGGTCT-3') and CCR5 DELTA2 (5'-CATGATGGTGAAGATAAGCCTCCACA-3') [ 16 ]. The reaction included 0.2 µM of each primer, 0.04 U of Velocity DNA polymerase enzyme, 2.5 mM Mg 2+ and 0.6 mM dNTP mixture in a final volume of 25 µL. The cycling parameters were: 1 cycle 98°C x 30 s; 35 cycles 98°C x 30 s, 60°C x 30 s, 72°C x 15 s; 1 cycle of 72°C x 3 min. The amplified products were visualized by 3% agarose gel electrophoresis. For the CCR5/CCR5 genotype a single band of 225 bp is expected, whereas for the CCR5/Δ32 genotype bands of 225 bp and 193 bp, and for CCR5-Δ32/ CCR5-Δ32 genotype a single band of 193 bp. HLA-B*57:01 allele Genotyping HLA-B*57:01 genotyping was a modified procedure based on Jung et al. [ 17 ]. The PCR reaction includes: 10–60 ng/µL of genomic DNA, 1X Kapa Probe Fast Master Mix (Roche), 0.3 µmol/L of each primer (B5071-T1F: AGGGTCTCACATCATCCAGGT and B5701-T3R: CGTTCAGGGCGATGTAATCCT), and 0.2 µmol/L of each probe (B5701-P2: 6FAM-CGCGGGCATGACCAGTC-MGBNFQ), with a final volume of 10 µL. The amplification program has the following parameters: 95° C for 5 min; and 45 cycles of 95° C for 15 s and 68° C for 30 s. Molecular grade water was used as a negative control and a sample with a previous HLA-B*57:01 (+) previously genotyped by a commercial kit as a positive control. Samples with a Ct value < 30 for both HLA-B*57:01 and the internal control (alpha-actine 1) will be considered as positive for the HLA-B*57:01 allele. Sanger Sequencing DNA samples whose PCR product revealed the presence of heterozygous genotype for CCR5-Δ32 were purified from gel. The primers described by Diaz et al. were used [ 16 ]. In the case of HLA-B*57:01 , the amplification products were directly purified using magnetic beads and primers described by Jung et al. [ 13 ]. In both cases, Big Dye Terminator reagent was used, and the products were settled on the Applied Biosystems 3500 XL genetic analyzer. In the case of CCR5 , both forward and reverse sequences were edited and assembled with the software SeqTrace v.0.9.0, whereas, for HLA-57:01 , we used the free-access program Soap Typing V1.0.6.3. The resulting electropherograms were aligned and compared with the sequence deposited in GenBank (accession code LR961919). Statistics Analysis Comparison of categorical and quantitative variables was performed with the Chi-square test or Fisher’s test (f < 5), and the Mann-Whitney test, respectively. Deviations from Hardy-Weinberg equilibrium were calculated using the Chi-square test. Frequencies of each allele were compared between HIV-exposed seronegative and HIV-seropositive individuals, using Chi-square test or Fisher's test when appropriate. In all analyses, p value < 0.05 was considered statistically significant. The RStudio v. 4.1.2 software was used. RESULTS The data of the 300 participants are summarized in Table 1 . For the PVV groups, the mean age was 36 years (83.3% males and 16.7% females), while for the PS group, the mean age was 33 years (84.7% males and 15.3% females). Most of the participants in either the PVV or the PS came from Lima (64%), followed by Lambayeque (6%) for the PVV, Ica for the PVV and PS (4% each) and La Libertad and Loreto for the PVV and PS (3% each). Regarding risk behavior, there was no information available on PVV, however, in PS, 36% referred homosexual orientation (MSM and Trans H-M), 10.7% bisexual and 53.3% heterosexual. Both groups showed significant differences in chronological age (p = 0.02) and immunological status (p < 0.01), indicating immunological failure in PVV. Table 1 Sociodemographic, epidemiological, clinical and virological characteristics of both PVV and PS groups. Characteristics PVV (n = 150) PS (n = 150) p a Gender Male 83.3% 84.7% n.s. b Female 16.7% 15.3% Age (average) [IQR] 36 [29–45] 33 [26–41] 0.02 c Sexual Orientation MSM No data 20.7% Trans H-M No data 15.3% Bisexual No data 10.7% Heterosexual No data 53.3% Viral load (N° copies/mL) ≤ 50 54% Not applicable > 50 13.3% Not applicable Unknown 32.7% Not applicable CD4 recount (cell/µL) (average) [IQR] 618 [378.5-785.25] 862 [706–1086] < 0.01 c 500 66% 92% Unknown 0.67% 0% Place of birth Amazonas 0.6% 0 Ancash 4.7% 2% Apurímac 0.6% 1.3% Arequipa 2.0% 0.6% Cajamarca 2.7% 0 Callao 2% 2% Huánuco 2.7% 0.6% Ica 2% 4% Junín 1.3% 2.7% La Libertad 3.3% 0.6% Lambayeque 6% 1.3% Lima 64% 76.7% Loreto 2.7% 3.3% Pasco 0 0.6% Piura 2% 2% San Martin 1.3% 0.6% Tumbes 1.3% 0% Ucayali 0.6% 1.3% Abacavir treatment Si 6 Not applicable No 144 Not applicable a p-value using Chi-square, b Chi-square test, c Mann-Whitney U test (p < 0.05 denotes significant difference), n.s.=no significant difference, MSM: Men who have sex with men The CCR5/CCR5 genotype were observed as a single band of 225 bp, whereas the CCR5/CCR5-Δ32 genotype were visualized as two bands (225 and 193 bp) (Fig. 1 ). No CCR5-Δ32/ CCR5-Δ32 genotype were detected in the 300 samples. The mutated allele (CCR5-Δ32) was further confirmed by Sanger sequencing (Fig. 2 ). We found that the prevalence of CCR5 Δ32 heterozygotes was 2.7%, while the frequency of the allele was 1.3%. (Table 2 ). No homozygotes were found for the mutated allele. In the PVV group, 2% had the heterozygous genotype and the frequency of the CCR5-Δ32 allele was 1%. In the PS group, 3.3% had the heterozygous genotype and the frequency of the CCR5-Δ32 allele was 1.7%. The distribution of genotype and allele frequencies between the two groups was not significantly different (p > 0.05). Hardy-Weinberg analysis showed that the CCR5-Δ32 allele was in equilibrium in each group and in the total population (> 0.05) (Table 2 ). Table 2 Allele and genotype frequencies of CCR5 between PVV and PS and Hardy-Weinberg equilibrium (HW) Group n Genotypic frequencies Allelic frequencies H-W Equilibrium CCR5/ CCR5 CCR5/ CCR5-Δ32 CCR5- Δ32/ CCR5-Δ32 p a CCR5 CCR5- Δ32 p b ꭓ 2 p c PS 150 145 (0.967) 5 (0.033) 0 n.s. 0.983 0.017 n.s. 0.043 n.s. PVV 150 147 (0.98) 3 (0.02) 0 0.99 0.01 0.015 n.s. Total 300 292 (0.973) 8 (0.027) 0 (0) 0.987 0.013 0.055 ns. a,b p-value using Fisher's test , c p-value obtained by Chi-square; n.s: non-significant difference. Real-Time PCR results showed Ct values below 30 for both the HLA-B57:01 allele and the internal control in 5 of the 300 analyzed samples. However, only one of these samples (PS134) showed a fluorescence level comparable to the positive control (Fig. 3 A), hence Sanger sequencing was used to avoid false positives. Analysis using the SoapTyping program revealed matches to the HLA-B57:01 allele in only one of the five samples (data not shown). Based on the electropherograms, we confirmed that this sample had polymorphisms compatible with the sequence of the HLA-B*57:01:01 allele stored in the GenBank platform (accession number: LR961919), whereas the remaining four samples had non-compatible polymorphisms in the region complementary to the 3' end of the probe (Fig. 3 B). Therefore, we consider that sample PS134 carries the HLA-B*57:01 (+) genotype. Overall, the prevalence of the HLA-B*57:01 genotype was 0.33%. In the PS group, the prevalence was 0.67%. No HLA-B*57:01 genotype was identified among HIV-seropositive individuals (PVV). The prevalence between the two groups was not significantly different (p > 0.05) (Table 3 ). Table 3 Prevalence of HLA-B*57:01 in HIV-seropositive individuals (PVV) and HIV-exposed seronegative individuals (PS) Group N Genotype HLA-B*57:01 Prevalence (%) P* Positive Negative PVV 150 0 150 0 n.s. PS 150 1 149 0.67 Total 300 1 299 0.33 * p-value with Fisher’s test; n.s.: not significant DISCUSSION In the present study we have described for the first time the CCR5-Δ32 and HLA-B*57:01 alleles in HIV-exposed seronegative and HIV-1 seropositive Peruvian individuals, and collected social, clinical, and epidemiological information for each participant. In the case of CCR5-Δ32 , our findings reveal that the prevalence of this mutation was low, which could be related to the low degree of admixture detected between the current Peruvian population and the European population, mainly Spanish [ 10 ]. The sample of Peruvian individuals analyzed in this study did not present any homozygous case for the CCR5 mutation, consistent with the results from previous studies in Latin American countries [ 8 , 14 , 15 ]. Likewise, Hardy-Weinberg equilibrium for CCR5 in the Peruvian population showed the recent interbreeding event with the European population and also suggests that this mutation could have experienced a type of negative selection, since its presence could cause some physiological alterations such as alterations in the immune response mediators [ 16 ], mechanisms related to abdominal aortic aneurysm [ 17 ], development of susceptibility to lupus nephritis [ 18 ], among others. In contrast to our data, Solloch et al [ 8 ] reported a higher prevalence for CCR5-Δ32 (5% vs 3%). This difference, albeit small, could be related to the methodology used, the size of the sample, and the selection of the population. In addition, Solloch et al [ 8 ] did not report further information on the individuals to know how the degree of admixture of Peruvians would differ in terms of their geographical origin. In our study we included participants from eighteen cities in Peru, mainly from Lima, Lambayeque and Loreto, cities where Peruvians have been shown to have the highest rate of genetic variability in the country [ 12 ]. This data suggest that these chosen populations might be representative of Peru, however further studies to national level are needed to show this affirmation. Regarding the HLA B*5701 allele, our study showed a lower frequency than CCR5-Δ32, which could be due to its higher distribution in Caucasian populations than in Latin American or Native American populations [ 19 , 20 ]. The allele frequency in some Latin American countries ranged from 1–5.6% [ 19 , 20 , 21 , 22 ] suggesting that the degree of admixtures with the European lineage is variable. Martínez et al [ 20 ], who reported a prevalence of 2.7% among HIV-infected Colombians, found that when the sample was stratified according to ethnic characteristics, the prevalence was higher in whites (4%) than in other ethnic groups such as mestizos (2.6%) or Afro-Colombians (1.9%). These results show that the allele distribution in Latin America may differ depending on the local ethnic characteristics of each country, suggesting that the degree of admixture in this population is higher than in other regions of the world. On this last point, the study published by Vilcarino et al [ 11 ] found a frequency of 4% in a sample of 49 Peruvian subjects. However, the data on the geographical origin of these samples are limited, as most of them only included subjects from the same city. In addition, the sample size was very small, so this value could not be considered representative of the Peruvian population. In contrast, the sample size in this study was larger (n = 300) and from different regions of Peru (Table 1 ). Considering that the Allele Frequency Net database ( https://www.allelefrequencies.net/ ) has no information on the prevalence of this allele in Peru, this study could be the first to describe the more approximate data on the prevalence of HLA B*57:01 in the Peruvian population. From the clinical point of view, the presence of both CCR5-Δ32 and HLA-B*57:01 have been associated with slow progression to AIDS in carrier individuals [ 1 , 3 ]. Their presence in the Peruvian population opens the possibilities of finding a specific group of individuals with slow progression to AIDS. However, when the viral load (VL) results of the CCR5-Δ32 mutation carriers were analyzed, only one of them had a VL of less than 20 copies, while the rest exceeded 1000 copies. It is therefore possible that pharmacological and/or genetic factors may influence virological failure in carriers of this mutation. The CD4 count was significantly lower in PVV, which is to be expected since HIV infection is associated with a depletion of the CD4 lymphocyte population [ 23 ]. However, when analyzing the immune response status of CCR5-Δ32 mutation carriers in the PVV group (PVV CCR5/Δ32 , n = 3), they showed more than 400 CD4 cells / µL, a value outside the threshold for risk of developing AIDS [ 24 ], and above the average CD4 of those who did not carry this mutation. The high proportion of CD4 cells might be consequence of the CD30L overexpression associated to the 32-nucleotide deletion [ 16 ]. Another important detail related to the immune response is that the antiretroviral treatment currently being received by PVV CCR5/Δ32 based on a combination of dolutegravir, tenofovir, lamivudine and efavirenz, may also contribute to favoring the immune response against HIV, as has been described in several studies [ 25 ]. However, ex vivo experiments have shown that treatment with dolutegravir has the opposite effect, generating a decrease in the CD4 population [ 26 ]. Considering that two individuals in the PVV CCR5/Δ32 group were treated with this drug and still had a CD4 count greater than 400 cells/µL, we suggest that the CD4 population was restored due to the mutation We collected the data regarding the risk behavior of CCR5-Δ32 mutation carriers from PS group (PS CCR5/Δ32 , n = 5). They reported high-risk sexual behavior for HIV/STI infection such as multiple sexual partners, infection by sexual transmission, use of recreational drugs, and intermittent condom use. In spite of this, they had a good immune response (an average of 1011.4 cells/µL) and a negative diagnosis of HIV at quarterly or half-yearly monitoring tests. These findings suggest that other genetic or immunological factors may play an important role in the protection of these patients against HIV, since the heterozygous CCR5/Δ32 allele still allows viral interaction and internalization in the susceptible cell. Further research is needed at the genomic level to determine the presence of these factors and their role in protecting these individuals against HIV. The presence of a single individual carrying the HLA-B*57:01 allele among 300 HIV-exposed seronegative and HIV-seropositive individuals with high-risk sexual behavior, as well as the previous results reported by Vilcarino et al [ 11 ], underscores the need to continue routine detection of this allele within the surveillance and resistance monitoring system in Peru. To achieve this goal, it is essential to optimize the use and distribution of molecular tests for the detection of HLA-B57:01 in the different primary health centers in the country. The fact that only 6 of the 150 seropositive participants use abacavir for treatment may be related to the genetic risk of hypersensitivity to the drug and the limited availability of genotyping tests, among other factors. This situation may lead doctors to prefer not to prescribe abacavir, limiting its use despite its good pharmacological properties [ 5 ]. Although our results suggest that the risk of genetic hypersensitivity to abacavir is low in our population, these results should be taken with caution. Finally, this is the first study to focus on the genetic variants CCR5-Δ32 and HLA-B*57:01 in PVV and PS, so the results described will allow new calculations to be made for future studies to select a more representative sample size from the different geographical regions of Peru. It also demonstrates the need for local studies in search of markers to better understand HIV resistance in at-risk populations and to predict the prognosis of AIDS in the Peruvian population. The effects of CCR5-Δ32 in Peruvian subjects may be different from those already described in the European population, due to its heterogeneity, whose effects are not only due to its frequency, but also to the interaction with other genes that can modulate the expression of CCR5-Δ32 individually or in synergy [ 27 ]. In conclusion, we show that the prevalence of both CCR5-Δ32 and HLA-B*57:01 alleles is low, providing the strongest evidence for recent gene flow between European communities and indigenous populations living in Peru today. Similarly, the presence of one carrier of the HLA-B*57:01 allele - and two previously reported cases - demonstrates the ongoing surveillance of abacavir hypersensitivity in the Peruvian population. However, further nationwide investigation from each region of Peru is needed to have a truly representative sample of the Peruvian population. Declarations Conflict of Interest statement All authors have no conflicts of interest to disclose. AUTHOR CONTRIBUTON RFA, CAY, OAC, SEA and EMZ were involved in the study conception. SEC and CAY were involved in the analysis of the data as well as the redaction of the manuscript. SEC, SEA, DOA and MD were involved in data collection. All the authors read and approved the final version of the manuscript. COMPETING INTERESTS The authors declare have no conflicts of interest to report. ETHICS APPROVAL AND CONSENT TO PARTICIPATE The procotol of the present study was previously approbed by the Institutional Research Ethics Committee of the Instituto Nacional de Salud (Code Number: OT-023-20). FUNDING This research was funded by the Peruvian entity CONCYTEC through the Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT) with contract number 012-2019-FONDECYT. ACKNOWLEDGEMENTS We would like to thank Alberto Sánchez and Luis Castro (NGO MCC Voluntades Lima Norte) for their valuable efforts and support in the recruitment process of participants and collection data through the surveys References An P, Winkler CA. Host genes associated with HIV/AIDS: advances in gene discovery. Trends Genet. 2010; 26 (3):119–31. Langford SE, Ananworanich J, Cooper DA. Predictors of disease progression in HIV infection: a review. AIDS Res Ther. 2007; 4 :11. UK Collaborative HIV Cohort Study Steering Committee. HLA B*5701 status, disease progression, and response to antiretroviral therapy. AIDS . 2013; 27 (16):2587–92. Mallal S, Nolan D, Witt C, Masel G, Martin AM, Moore C, et al. 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Moragas M, Belloso WH, Baquedano MS, Gutierrez MI, Bissio E, Larriba JM, et al. Prevalence of HLA-B*57:01 allele in Argentinean HIV-1 infected patients. Tissue Antigens . 2015; 86 (1):28-31. Poggi H, Vera A, Lagos M, Solari S, Rodríguez P L, Pérez CM. HLA-B*5701 frequency in Chilean HIV-infected patients and in general population. Braz J Infect Dis. 2010; 14 (5):510-2. Zhao J, Cheng L, Wang H, Yu H, Tu B, Fu Q, et al. Infection and depletion of CD4+ group-1 innate lymphoid cells by HIV-1 via type-I interferon pathway. PLoS Pathog. 2018; 14 (1):e1006819. Noda A, Vidal L, Pérez J, Cañete R. Interpretación clínica del conteo de linfocitos T CD4 positivos en la infección por VIH. Rev. Cubana Med. 2024, 52 (2), 118-127. Corbeau P, Reynes J. Immune reconstitution under antiretroviral therapy: the new challenge in HIV-1 infection. Blood . 2011; 117 (21):5582-90. Korencak M, Byrne M, Richter E, Schultz BT, Juszczak P, Ake JA et al. Effect of HIV infection and antiretroviral therapy on immune cellular functions. JCI Insight. 2019; 4 (12):e126675. Kulmann-Leal B, Ellwanger JH, Chies JAB. CCR5Δ32 in Brazil: Impacts of a European Genetic Variant on a Highly Admixed Population. Front Immunol . 2021; ; 12 :758358. Additional Declarations There is no conflict of interest Cite Share Download PDF Status: Published Journal Publication published 26 Aug, 2025 Read the published version in Human Genome Variation → Version 1 posted Editorial decision: revise 21 Apr, 2025 Submission checks completed at journal 02 Apr, 2025 First submitted to journal 01 Apr, 2025 Unknown event 30 Mar, 2025 Editor assigned by journal 28 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6329775","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":445599075,"identity":"ab082014-41c9-40af-a7f3-7e20796fcc48","order_by":0,"name":"Carlos Yabar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYHACNhAhR7oWY9K1JDYQrZ5/RvKzBz/3HE7fcP502gPGHTaEtUjcSDM37Hl2OHfDjdztBoxn0ghrMZBIMJPgOZAG1MK7TYKx7TAxWtK/Sf45kJZucP4sSMt/YrTkmEnzHLBJMDiQC9JygLAWiTNvyo1lDtgYzgT5JfFMMmEt/O3p2x6+OSAhzwd02IOPO+wIa2EQSIAz2YiMHf4DSFoYidIyCkbBKBgFIw0AAIZRPNMZr6QcAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9607-5693","institution":"Instituto Nacional de Salud-Universidad de San Martin de Porres","correspondingAuthor":true,"prefix":"","firstName":"Carlos","middleName":"","lastName":"Yabar","suffix":""},{"id":445599076,"identity":"cfa3d960-b498-4e6b-b1e5-7f87b8fda4f5","order_by":1,"name":"Susan Echevarría-Correa","email":"","orcid":"","institution":"Universidad Nacional Mayor de San Marcos","correspondingAuthor":false,"prefix":"","firstName":"Susan","middleName":"","lastName":"Echevarría-Correa","suffix":""},{"id":445599077,"identity":"fa946411-b119-4b75-92f6-71cbf2644eaa","order_by":2,"name":"Daisy Obispo-Achallma","email":"","orcid":"","institution":"Universidad de San Martín de Porres","correspondingAuthor":false,"prefix":"","firstName":"Daisy","middleName":"","lastName":"Obispo-Achallma","suffix":""},{"id":445599078,"identity":"dea50d6a-775b-4b55-93dd-af02c1af282b","order_by":3,"name":"Susan Espetia","email":"","orcid":"","institution":"Instituto Nacional de Salud","correspondingAuthor":false,"prefix":"","firstName":"Susan","middleName":"","lastName":"Espetia","suffix":""},{"id":445599079,"identity":"6618f083-d362-4d62-9d6b-630f6baa5c8c","order_by":4,"name":"Maria Luisa Guevara","email":"","orcid":"","institution":"Universidad de San Martín de Porres","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Luisa","lastName":"Guevara","suffix":""},{"id":445599080,"identity":"13ca593a-784e-48e2-a7a6-5bc8e688a472","order_by":5,"name":"Oscar Acosta","email":"","orcid":"","institution":"Universidad de San Martín de Porres","correspondingAuthor":false,"prefix":"","firstName":"Oscar","middleName":"","lastName":"Acosta","suffix":""},{"id":445599081,"identity":"37268819-e717-43cf-bc75-fc3cb2220cbf","order_by":6,"name":"María Dedios","email":"","orcid":"","institution":"Hospital Santa Rosa","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"","lastName":"Dedios","suffix":""},{"id":445599082,"identity":"d770db05-6917-4568-80bf-c50750e87bbf","order_by":7,"name":"Enrique Mamani","email":"","orcid":"","institution":"Universidad Nacional Mayor de San Marcos","correspondingAuthor":false,"prefix":"","firstName":"Enrique","middleName":"","lastName":"Mamani","suffix":""},{"id":445599083,"identity":"a7614fd1-1de7-40c3-9942-abc366620b18","order_by":8,"name":"Ricardo Fujita","email":"","orcid":"https://orcid.org/0000-0002-9617-5109","institution":"Universidad de San Martín de Porres","correspondingAuthor":false,"prefix":"","firstName":"Ricardo","middleName":"","lastName":"Fujita","suffix":""}],"badges":[],"createdAt":"2025-03-28 16:36:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6329775/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6329775/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41439-025-00321-3","type":"published","date":"2025-08-26T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81963630,"identity":"43a9bdad-3abc-4f4e-a18a-f3bf80b329bd","added_by":"auto","created_at":"2025-05-05 11:21:44","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55546,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCCR5 genotype. Lane 1: 100 bp ladder. Lanes 2 to 11 and 13 to 20: Homozygous genotype wild type CCR5/CCR5. Lanes 6, 7, and 12: Heterozygous genotype mutant (CCR5/CCR5-Δ32).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6329775/v1/db23dd4132ddcc4942ec4b11.jpg"},{"id":81962709,"identity":"22a1a9fe-5109-40af-af18-9bf4d3a85425","added_by":"auto","created_at":"2025-05-05 11:13:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":250070,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSanger sequencing of the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCCR5-Δ32 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eallele\u003c/strong\u003e\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eElectropherograms corresponding to \u003cem\u003eCCR5\u003c/em\u003e allele and \u003cem\u003eCCR5-Δ32\u003c/em\u003e allele visualized by \u003cem\u003eSeqTrace\u003c/em\u003esoftware\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB. \u003c/strong\u003eAlignments of \u003cem\u003eCCR5-Δ32\u003c/em\u003e using \u003cem\u003eBioedit \u003c/em\u003esoftware.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6329775/v1/eaf3dea5eb98aec0064a5bb2.jpg"},{"id":81963632,"identity":"99aa78e7-89eb-433b-bd8f-c0f982d9d811","added_by":"auto","created_at":"2025-05-05 11:21:45","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":292081,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGenotyping of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eHLA-B*57:01\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eReal-Time PCR results. The sample PS134 is the only one with a similar fluorescence level as the positive control (C+\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB. \u003c/strong\u003eComparison of nucleotides according to electropherogram peaks with the \u003cem\u003eHLA-B*57:01:01\u003c/em\u003esequence extracted from GenBank. The red rectangle indicates the position of the SNP (C/T) for \u003cem\u003eHLA-B*57:01:01\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6329775/v1/ad0f38c869a77bcebed3c5b4.jpg"},{"id":89990278,"identity":"584e8557-5054-4c1f-9df0-49697ba73fc9","added_by":"auto","created_at":"2025-08-27 07:10:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1493512,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6329775/v1/1f619f59-7fba-485b-bfd7-b49e6a949104.pdf"}],"financialInterests":"There is no conflict of interest","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDistribution of CCR5-∆32 and HLA-B*57:01alleles in HIV-seropositive and HIV-exposed seronegative Peruvian individuals\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGenetics factor have been involved to show resistant subjects to HIV infection despite multiple high-risk exposures to HIV or different rates of progression to Acquired Immune Deficiency Syndrome (AIDS) from infected subjects [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Genes such as CCR5 Δ32 and HLA-B*57:01 have been implicated in viral entry and immune response processes, respectively [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the first case, a 32bp deletion of CCR5 gene is sufficient to interfere with and even prevent viral entry into the cell, especially when homozygous. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The HLA-B*57:01 allele is not only associated with slow progression to AIDS [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], but also with genetic susceptibility to the antiretroviral drug abacavir hypersensitivity reaction (ABC-HSR) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which is known to cause severe clinical manifestations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], reason why HLA-B*57:01 genotyping is recommended before prescribing the drug [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In Peru, the Ministry of Health has developed the technical standard NTS N\u0026deg;169-MINSA/2020/DGIESP [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], which establishes the requirement to perform the HLA-B*57:01 genotyping test before administering abacavir. However, this political decision was made without having proven that HLA-B*57:01 frequency in the Peruvian population.\u003c/p\u003e \u003cp\u003eIn contrast to Europe, the prevalence of both \u003cem\u003eCCR5-Δ32\u003c/em\u003e and \u003cem\u003eHLA-B*57:01\u003c/em\u003e is low in African, Asian and Latin American populations [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In Peru, this mutation may have been introduced into the local population by gene flow through admixture with the European population [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This is supported by few reports found in some Peruvian subjects [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, none these studies included geographic origin of the subjects recruited which difficult its interpretation since Peruvian population is a join of communities showing different degrees of ethnic admixture and consequently genetic variability [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, in the context of HIV/AIDS disease none of these studies included clinical and socio-epidemiological information that may be useful to know the importance of this alleles in the epidemic evolution in Peru.\u003c/p\u003e \u003cp\u003eFor this proposal, we recruited Peruvian individuals and requested data on their geographic origin and social, epidemiological and clinical characteristics that might provide more information to understand how the genetic characteristics of the Peruvian population might be related to the HIV/AIDS epidemic.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eType and Design of Study\u003c/h2\u003e \u003cp\u003eObservational cross-sectional study performed between December 2020 and November 2021\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePopulation and sample size\u003c/h3\u003e\n\u003cp\u003eThe population corresponds to Peruvian individuals treated at the \u003cem\u003eAsociaci\u0026oacute;n Civil Voluntades Lima Norte\u003c/em\u003e Non-Governmental Organization and the \u003cem\u003eSanta Rosa\u003c/em\u003e Hospital. This population was divided into two groups: (1) HIV-exposed seronegative individuals (PS) and (2) HIV-seropositive individuals (PVV). The geographic origin of the participants was predominantly from Lima (71%), a city characterized by having a population with a high percentage of admixture and the greatest genetic diversity in the country [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. From this population, the sample size was calculated using the proportion formula for finite population based on: i) an expected prevalence of 1% for \u003cem\u003eHLA-B*57:01\u003c/em\u003e and \u003cem\u003eCCR5-Δ32\u003c/em\u003e in a mixed population \u0026mdash;mainly with native ancestry\u0026mdash;\u0026cedil;ii) a population of 800 individuals, iii) a confidence level of 95%, and iv) margin of error of 1%. The minimum number of participants required to estimate the prevalence of \u003cem\u003eCCR5-Δ32\u003c/em\u003e and \u003cem\u003eHLAB-57:01\u003c/em\u003e alleles was 258; however, in this study a sample size of 300 individuals was used to increase the power and precision of the results. The selection criteria were the following: i) Peruvian nationality, iii) legal age (18 years and more), iii) both sexes (male and females), iv) agreement to participate in the study by signing an informed consent and completing a survey using a data collection instrument. Furthermore, for the PVV group, a diagnosis of HIV seropositivity was requested through confirmatory tests, whereas, for the PS group, seronegative diagnosis confirmed by both 3rd and 4th generation rapid tests, in addition to manifest characteristics of sexual behavior with a high risk of HIV transmission, such as a history of occasional sexual contact with sex workers, intermittent condom use, and multiple sexual partners.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCCR5\u003c/b\u003e \u003cb\u003eGenotyping\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDNA was extracted using the NucleoSpin kit (Macherey-Nagel, Germany), according to the manufacturer's recommendations. \u003cem\u003eCCR5\u003c/em\u003e genotyping was based on Endpoint PCR assay using primers flanking the 32 bp deletion, CCR5 DELTA1 (5'-ACCAGATCTCTCAAAAAGAAGGTCT-3') and CCR5 DELTA2 (5'-CATGATGGTGAAGATAAGCCTCCACA-3') [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The reaction included 0.2 \u0026micro;M of each primer, 0.04 U of Velocity DNA polymerase enzyme, 2.5 mM Mg\u003csup\u003e2+\u003c/sup\u003e and 0.6 mM dNTP mixture in a final volume of 25 \u0026micro;L. The cycling parameters were: 1 cycle 98\u0026deg;C x 30 s; 35 cycles 98\u0026deg;C x 30 s, 60\u0026deg;C x 30 s, 72\u0026deg;C x 15 s; 1 cycle of 72\u0026deg;C x 3 min. The amplified products were visualized by 3% agarose gel electrophoresis. For the \u003cem\u003eCCR5/CCR5\u003c/em\u003e genotype a single band of 225 bp is expected, whereas for the \u003cem\u003eCCR5/Δ32\u003c/em\u003e genotype bands of 225 bp and 193 bp, and for \u003cem\u003eCCR5-Δ32/ CCR5-Δ32\u003c/em\u003e genotype a single band of 193 bp.\u003c/p\u003e\n\u003ch3\u003eHLA-B*57:01 allele Genotyping\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eHLA-B*57:01\u003c/em\u003e genotyping was a modified procedure based on Jung et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The PCR reaction includes: 10\u0026ndash;60 ng/\u0026micro;L of genomic DNA, 1X Kapa Probe Fast Master Mix (Roche), 0.3 \u0026micro;mol/L of each primer (B5071-T1F: AGGGTCTCACATCATCCAGGT and B5701-T3R: CGTTCAGGGCGATGTAATCCT), and 0.2 \u0026micro;mol/L of each probe (B5701-P2: 6FAM-CGCGGGCATGACCAGTC-MGBNFQ), with a final volume of 10 \u0026micro;L. The amplification program has the following parameters: 95\u0026deg; C for 5 min; and 45 cycles of 95\u0026deg; C for 15 s and 68\u0026deg; C for 30 s. Molecular grade water was used as a negative control and a sample with a previous \u003cem\u003eHLA-B*57:01\u003c/em\u003e (+) previously genotyped by a commercial kit as a positive control. Samples with a Ct value\u0026thinsp;\u0026lt;\u0026thinsp;30 for both \u003cem\u003eHLA-B*57:01\u003c/em\u003e and the internal control (alpha-actine 1) will be considered as positive for the \u003cem\u003eHLA-B*57:01\u003c/em\u003e allele.\u003c/p\u003e\n\u003ch3\u003eSanger Sequencing\u003c/h3\u003e\n\u003cp\u003eDNA samples whose PCR product revealed the presence of heterozygous genotype for \u003cem\u003eCCR5-Δ32\u003c/em\u003e were purified from gel. The primers described by Diaz \u003cem\u003eet al.\u003c/em\u003e were used [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In the case of \u003cem\u003eHLA-B*57:01\u003c/em\u003e, the amplification products were directly purified using magnetic beads and primers described by Jung et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In both cases, Big Dye Terminator reagent was used, and the products were settled on the Applied Biosystems 3500 XL genetic analyzer. In the case of \u003cem\u003eCCR5\u003c/em\u003e, both forward and reverse sequences were edited and assembled with the software \u003cem\u003eSeqTrace\u003c/em\u003e v.0.9.0, whereas, for \u003cem\u003eHLA-57:01\u003c/em\u003e, we used the free-access program Soap Typing V1.0.6.3. The resulting electropherograms were aligned and compared with the sequence deposited in GenBank (accession code LR961919).\u003c/p\u003e\n\u003ch3\u003eStatistics Analysis\u003c/h3\u003e\n\u003cp\u003eComparison of categorical and quantitative variables was performed with the Chi-square test or Fisher\u0026rsquo;s test (f\u0026thinsp;\u0026lt;\u0026thinsp;5), and the Mann-Whitney test, respectively. Deviations from Hardy-Weinberg equilibrium were calculated using the Chi-square test. Frequencies of each allele were compared between HIV-exposed seronegative and HIV-seropositive individuals, using Chi-square test or Fisher's test when appropriate. In all analyses, \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. The RStudio v. 4.1.2 software was used.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe data of the 300 participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For the PVV groups, the mean age was 36 years (83.3% males and 16.7% females), while for the PS group, the mean age was 33 years (84.7% males and 15.3% females). Most of the participants in either the PVV or the PS came from Lima (64%), followed by Lambayeque (6%) for the PVV, Ica for the PVV and PS (4% each) and La Libertad and Loreto for the PVV and PS (3% each). Regarding risk behavior, there was no information available on PVV, however, in PS, 36% referred homosexual orientation (MSM and Trans H-M), 10.7% bisexual and 53.3% heterosexual. Both groups showed significant differences in chronological age (p\u0026thinsp;=\u0026thinsp;0.02) and immunological status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating immunological failure in PVV.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic, epidemiological, clinical and virological characteristics of both PVV and PS groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePVV\u0026nbsp;(n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePS (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (average) [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 [29\u0026ndash;45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 [26\u0026ndash;41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual Orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrans H-M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eViral load (N\u0026deg; copies/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4 recount (cell/\u0026micro;L)\u003c/p\u003e \u003cp\u003e(average) [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e618\u003c/p\u003e \u003cp\u003e[378.5-785.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e862\u003c/p\u003e \u003cp\u003e[706\u0026ndash;1086]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u0026ndash;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmazonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAncash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApur\u0026iacute;mac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArequipa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCajamarca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCallao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHu\u0026aacute;nuco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJun\u0026iacute;n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLa Libertad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLambayeque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLima\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoreto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePasco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePiura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSan Martin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumbes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUcayali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003e\u003cem\u003ep-value\u003c/em\u003e using Chi-square, \u003csup\u003eb\u003c/sup\u003eChi-square test, \u003csup\u003ec\u003c/sup\u003eMann-Whitney U test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 denotes significant difference), n.s.=no significant difference, MSM: Men who have sex with men\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe \u003cem\u003eCCR5/CCR5\u003c/em\u003e genotype were observed as a single band of 225 bp, whereas the \u003cem\u003eCCR5/CCR5-Δ32\u003c/em\u003e genotype were visualized as two bands (225 and 193 bp) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No \u003cem\u003eCCR5-Δ32/ CCR5-Δ32\u003c/em\u003e genotype were detected in the 300 samples. The mutated allele (CCR5-Δ32) was further confirmed by Sanger sequencing (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe found that the prevalence of CCR5 Δ32 heterozygotes was 2.7%, while the frequency of the allele was 1.3%. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No homozygotes were found for the mutated allele. In the PVV group, 2% had the heterozygous genotype and the frequency of the CCR5-Δ32 allele was 1%. In the PS group, 3.3% had the heterozygous genotype and the frequency of the CCR5-Δ32 allele was 1.7%. The distribution of genotype and allele frequencies between the two groups was not significantly different (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Hardy-Weinberg analysis showed that the CCR5-Δ32 allele was in equilibrium in each group and in the total population (\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllele and genotype frequencies of \u003cem\u003eCCR5\u003c/em\u003e between PVV and PS and Hardy-Weinberg equilibrium (HW)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eGenotypic frequencies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eAllelic frequencies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003eH-W Equilibrium\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCCR5/\u003c/p\u003e \u003cp\u003eCCR5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eCCR5/\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCCR5-Δ32\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCCR5- Δ32/\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCCR5-Δ32\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eCCR5\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eCCR5- Δ32\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145 (0.967)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e(0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePVV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147 (0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292 (0.973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003ens.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003e\u003csup\u003e\u003cem\u003ea,b\u003c/em\u003e\u003c/sup\u003e\u003cem\u003ep-value using Fisher's test\u003c/em\u003e, \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003cem\u003ep-value obtained by Chi-square; n.s: non-significant difference.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eReal-Time PCR results showed Ct values below 30 for both the \u003cem\u003eHLA-B57:01\u003c/em\u003e allele and the internal control in 5 of the 300 analyzed samples. However, only one of these samples (PS134) showed a fluorescence level comparable to the positive control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), hence Sanger sequencing was used to avoid false positives.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalysis using the \u003cem\u003eSoapTyping\u003c/em\u003e program revealed matches to the \u003cem\u003eHLA-B57:01\u003c/em\u003e allele in only one of the five samples (data not shown). Based on the electropherograms, we confirmed that this sample had polymorphisms compatible with the sequence of the HLA-B*57:01:01 allele stored in the GenBank platform (accession number: LR961919), whereas the remaining four samples had non-compatible polymorphisms in the region complementary to the 3' end of the probe (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Therefore, we consider that sample PS134 carries the HLA-B*57:01 (+) genotype.\u003c/p\u003e \u003cp\u003eOverall, the prevalence of the HLA-B*57:01 genotype was 0.33%. In the PS group, the prevalence was 0.67%. No HLA-B*57:01 genotype was identified among HIV-seropositive individuals (PVV). The prevalence between the two groups was not significantly different (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of \u003cem\u003eHLA-B*57:01\u003c/em\u003e in HIV-seropositive individuals (PVV) and HIV-exposed seronegative individuals (PS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eGenotype \u003cem\u003eHLA-B*57:01\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePrevalence (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep-value\u003c/em\u003e with Fisher\u0026rsquo;s test; n.s.: not significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn the present study we have described for the first time the \u003cem\u003eCCR5-Δ32\u003c/em\u003e and HLA-B*57:01 alleles in HIV-exposed seronegative and HIV-1 seropositive Peruvian individuals, and collected social, clinical, and epidemiological information for each participant. In the case of \u003cem\u003eCCR5-Δ32\u003c/em\u003e, our findings reveal that the prevalence of this mutation was low, which could be related to the low degree of admixture detected between the current Peruvian population and the European population, mainly Spanish [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The sample of Peruvian individuals analyzed in this study did not present any homozygous case for the CCR5 mutation, consistent with the results from previous studies in Latin American countries [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Likewise, Hardy-Weinberg equilibrium for \u003cem\u003eCCR5\u003c/em\u003e in the Peruvian population showed the recent interbreeding event with the European population and also suggests that this mutation could have experienced a type of negative selection, since its presence could cause some physiological alterations such as alterations in the immune response mediators [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], mechanisms related to abdominal aortic aneurysm [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], development of susceptibility to lupus nephritis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], among others.\u003c/p\u003e \u003cp\u003eIn contrast to our data, Solloch et al [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] reported a higher prevalence for CCR5-Δ32 (5% vs 3%). This difference, albeit small, could be related to the methodology used, the size of the sample, and the selection of the population. In addition, Solloch et al [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] did not report further information on the individuals to know how the degree of admixture of Peruvians would differ in terms of their geographical origin. In our study we included participants from eighteen cities in Peru, mainly from Lima, Lambayeque and Loreto, cities where Peruvians have been shown to have the highest rate of genetic variability in the country [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This data suggest that these chosen populations might be representative of Peru, however further studies to national level are needed to show this affirmation.\u003c/p\u003e \u003cp\u003eRegarding the HLA B*5701 allele, our study showed a lower frequency than CCR5-Δ32, which could be due to its higher distribution in Caucasian populations than in Latin American or Native American populations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The allele frequency in some Latin American countries ranged from 1\u0026ndash;5.6% [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] suggesting that the degree of admixtures with the European lineage is variable. Mart\u0026iacute;nez et al [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], who reported a prevalence of 2.7% among HIV-infected Colombians, found that when the sample was stratified according to ethnic characteristics, the prevalence was higher in whites (4%) than in other ethnic groups such as mestizos (2.6%) or Afro-Colombians (1.9%). These results show that the allele distribution in Latin America may differ depending on the local ethnic characteristics of each country, suggesting that the degree of admixture in this population is higher than in other regions of the world.\u003c/p\u003e \u003cp\u003eOn this last point, the study published by Vilcarino et al [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] found a frequency of 4% in a sample of 49 Peruvian subjects. However, the data on the geographical origin of these samples are limited, as most of them only included subjects from the same city. In addition, the sample size was very small, so this value could not be considered representative of the Peruvian population. In contrast, the sample size in this study was larger (n\u0026thinsp;=\u0026thinsp;300) and from different regions of Peru (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Considering that the Allele Frequency Net database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.allelefrequencies.net/\u003c/span\u003e\u003cspan address=\"https://www.allelefrequencies.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) has no information on the prevalence of this allele in Peru, this study could be the first to describe the more approximate data on the prevalence of HLA B*57:01 in the Peruvian population.\u003c/p\u003e \u003cp\u003eFrom the clinical point of view, the presence of both \u003cem\u003eCCR5-Δ32\u003c/em\u003e and \u003cem\u003eHLA-B*57:01\u003c/em\u003e have been associated with slow progression to AIDS in carrier individuals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Their presence in the Peruvian population opens the possibilities of finding a specific group of individuals with slow progression to AIDS. However, when the viral load (VL) results of the CCR5-Δ32 mutation carriers were analyzed, only one of them had a VL of less than 20 copies, while the rest exceeded 1000 copies. It is therefore possible that pharmacological and/or genetic factors may influence virological failure in carriers of this mutation.\u003c/p\u003e \u003cp\u003eThe CD4 count was significantly lower in PVV, which is to be expected since HIV infection is associated with a depletion of the CD4 lymphocyte population [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, when analyzing the immune response status of \u003cem\u003eCCR5-Δ32\u003c/em\u003e mutation carriers in the PVV group (PVV\u003csup\u003eCCR5/Δ32\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;3), they showed more than 400 CD4 cells / \u0026micro;L, a value outside the threshold for risk of developing AIDS [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and above the average CD4 of those who did not carry this mutation. The high proportion of CD4 cells might be consequence of the CD30L overexpression associated to the 32-nucleotide deletion [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Another important detail related to the immune response is that the antiretroviral treatment currently being received by PVV\u003csup\u003eCCR5/Δ32\u003c/sup\u003e based on a combination of dolutegravir, tenofovir, lamivudine and efavirenz, may also contribute to favoring the immune response against HIV, as has been described in several studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, \u003cem\u003eex vivo\u003c/em\u003e experiments have shown that treatment with dolutegravir has the opposite effect, generating a decrease in the CD4 population [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Considering that two individuals in the PVV\u003csup\u003eCCR5/Δ32\u003c/sup\u003e group were treated with this drug and still had a CD4 count greater than 400 cells/\u0026micro;L, we suggest that the CD4 population was restored due to the mutation\u003c/p\u003e \u003cp\u003eWe collected the data regarding the risk behavior of CCR5-Δ32 mutation carriers from PS group (PS\u003csup\u003eCCR5/Δ32\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;5). They reported high-risk sexual behavior for HIV/STI infection such as multiple sexual partners, infection by sexual transmission, use of recreational drugs, and intermittent condom use. In spite of this, they had a good immune response (an average of 1011.4 cells/\u0026micro;L) and a negative diagnosis of HIV at quarterly or half-yearly monitoring tests. These findings suggest that other genetic or immunological factors may play an important role in the protection of these patients against HIV, since the heterozygous CCR5/Δ32 allele still allows viral interaction and internalization in the susceptible cell. Further research is needed at the genomic level to determine the presence of these factors and their role in protecting these individuals against HIV.\u003c/p\u003e \u003cp\u003eThe presence of a single individual carrying the HLA-B*57:01 allele among 300 HIV-exposed seronegative and HIV-seropositive individuals with high-risk sexual behavior, as well as the previous results reported by Vilcarino et al [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], underscores the need to continue routine detection of this allele within the surveillance and resistance monitoring system in Peru. To achieve this goal, it is essential to optimize the use and distribution of molecular tests for the detection of HLA-B57:01 in the different primary health centers in the country. The fact that only 6 of the 150 seropositive participants use abacavir for treatment may be related to the genetic risk of hypersensitivity to the drug and the limited availability of genotyping tests, among other factors. This situation may lead doctors to prefer not to prescribe abacavir, limiting its use despite its good pharmacological properties [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although our results suggest that the risk of genetic hypersensitivity to abacavir is low in our population, these results should be taken with caution.\u003c/p\u003e \u003cp\u003eFinally, this is the first study to focus on the genetic variants CCR5-Δ32 and HLA-B*57:01 in PVV and PS, so the results described will allow new calculations to be made for future studies to select a more representative sample size from the different geographical regions of Peru. It also demonstrates the need for local studies in search of markers to better understand HIV resistance in at-risk populations and to predict the prognosis of AIDS in the Peruvian population. The effects of \u003cem\u003eCCR5-Δ32\u003c/em\u003e in Peruvian subjects may be different from those already described in the European population, due to its heterogeneity, whose effects are not only due to its frequency, but also to the interaction with other genes that can modulate the expression of \u003cem\u003eCCR5-Δ32\u003c/em\u003e individually or in synergy [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn conclusion, we show that the prevalence of both CCR5-Δ32 and HLA-B*57:01 alleles is low, providing the strongest evidence for recent gene flow between European communities and indigenous populations living in Peru today. Similarly, the presence of one carrier of the HLA-B*57:01 allele - and two previously reported cases - demonstrates the ongoing surveillance of abacavir hypersensitivity in the Peruvian population. However, further nationwide investigation from each region of Peru is needed to have a truly representative sample of the Peruvian population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest statement\u003c/h2\u003e \u003cp\u003eAll authors have no conflicts of interest to disclose.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAUTHOR CONTRIBUTON\u003c/h2\u003e \u003cp\u003eRFA, CAY, OAC, SEA and EMZ were involved in the study conception. SEC and CAY were involved in the analysis of the data as well as the redaction of the manuscript. SEC, SEA, DOA and MD were involved in data collection. All the authors read and approved the final version of the manuscript.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e \u003cp\u003eThe authors declare have no conflicts of interest to report.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/strong\u003e \u003cp\u003eThe procotol of the present study was previously approbed by the Institutional Research Ethics Committee of the \u003cem\u003eInstituto Nacional de Salud\u003c/em\u003e (Code Number: OT-023-20).\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e \u003cp\u003eThis research was funded by the Peruvian entity CONCYTEC through the \u003cem\u003eFondo Nacional de Desarrollo Cientifico y Tecnologico\u003c/em\u003e (FONDECYT) with contract number 012-2019-FONDECYT.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e \u003cp\u003e We would like to thank Alberto S\u0026aacute;nchez and Luis Castro (NGO MCC Voluntades Lima Norte) for their valuable efforts and support in the recruitment process of participants and collection data through the surveys\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAn P, Winkler CA. Host genes associated with HIV/AIDS: advances in gene discovery. \u003cem\u003eTrends Genet.\u003c/em\u003e 2010;\u003cstrong\u003e26\u003c/strong\u003e(3):119\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003eLangford SE, Ananworanich J, Cooper DA. Predictors of disease progression in HIV infection: a review. \u003cem\u003eAIDS Res Ther.\u003c/em\u003e 2007;\u003cstrong\u003e4\u003c/strong\u003e:11.\u003c/li\u003e\n\u003cli\u003eUK Collaborative HIV Cohort Study Steering Committee. HLA B*5701 status, disease progression, and response to antiretroviral therapy. \u003cem\u003eAIDS\u003c/em\u003e. 2013;\u003cstrong\u003e27\u003c/strong\u003e(16):2587\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eMallal S, Nolan D, Witt C, Masel G, Martin AM, Moore C, \u003cem\u003eet al.\u003c/em\u003e Association between presence of HLA-B*5701, HLA-DR7, and HLA-DQ3 and hypersensitivity to HIV-1 reverse-transcriptase inhibitor abacavir. \u003cem\u003eLancet\u003c/em\u003e. 2002; \u003cstrong\u003e359\u003c/strong\u003e(9308):727-32. \u003c/li\u003e\n\u003cli\u003eQuiros-Roldan E, Gardini G, Properzi M, Ferraresi A, Carella G, Marchi A, \u003cem\u003eet al\u003c/em\u003e. Abacavir adverse reactions related with HLA-B*57: 01 haplotype in a large cohort of patients infected with HIV. \u003cem\u003ePharmacogenet Genomics\u003c/em\u003e. 2020; \u003cstrong\u003e30\u003c/strong\u003e(8):167-174. d \u003c/li\u003e\n\u003cli\u003eMallal S, Phillips E, Carosi G, Molina JM, Workman C, Tomazic J, et al. PREDICT-1 Study Team. HLA-B*5701 screening for hypersensitivity to abacavir. \u003cem\u003eN Engl J Med. \u003c/em\u003e2008; \u003cstrong\u003e358\u003c/strong\u003e(6):568-79. \u003c/li\u003e\n\u003cli\u003eMinisterio de Salud. Norma T\u0026eacute;cnica de Salud de Atenci\u0026oacute;n Integral del Adulto con Infecci\u0026oacute;n por el Virus de la Inmunodeficiencia Humana (VIH). Resoluci\u0026oacute;n Ministerial N.\u0026deg; 1024-2020-MINSA. https://www.gob.pe/institucion/minsa/normas-legales/1422592-1024-2020-minsa. 12 December 2020.\u003c/li\u003e\n\u003cli\u003eSolloch UV, Lang K, Lange V, B\u0026ouml;hme I, Schmidt AH, Sauter J. 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Effect of HIV infection and antiretroviral therapy on immune cellular functions. \u003cem\u003eJCI Insight. \u003c/em\u003e2019;\u003cstrong\u003e4\u003c/strong\u003e(12):e126675. \u003c/li\u003e\n\u003cli\u003eKulmann-Leal B, Ellwanger JH, Chies JAB. CCR5\u0026Delta;32 in Brazil: Impacts of a European Genetic Variant on a Highly Admixed Population.\u003cem\u003e Front Immunol\u003c/em\u003e. 2021; ;\u003cstrong\u003e12\u003c/strong\u003e:758358. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"human-genome-variation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"hgv","sideBox":"Learn more about [Human Genome Variation](http://www.nature.com/hgv/)","snPcode":"41439","submissionUrl":"https://mts-hgv.nature.com/","title":"Human Genome Variation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CCR5-Δ32, HLA-B*57:01, prevalence, HIV-1, seropositive individuals, VIH exposed seronegative individuals, Peruvian population.","lastPublishedDoi":"10.21203/rs.3.rs-6329775/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6329775/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLittle information is available about CCR5-Δ32 and HLA-B*57:01 alleles in the Peruvian population, especially in HIV-negative people with high-risk sexual behavior. In this study, we described the prevalence of these alleles in HIV-exposed seronegative individuals (PS) and HIV-seropositive individuals (PVV). For this purpose, 300 individuals were recruited: 150 from each group, and the selected alleles were characterized by endpoint PCR, real-time PCR, and DNA sequencing, respectively.\u003c/p\u003e\n\u003cp\u003eAccording to our results, the prevalence of CCR5/CCR5-Δ32 heterozygous was 2.7%, and no homozygous cases were found. The population was in Hardy-Weinberg equilibrium for the CCR5 locus. Regarding HLA-B*57:01, only one case was found in the PS group, while no case was found from PVV group. No statistical difference was detected between both groups (p\u0026gt;0.05). In conclusion, we showed a low prevalence for CCR5-Δ32 as HLA-B*57:01 in Peruvian population. Since these alleles were also found indistinguishably from positives and negative Peruvian people with high-risk sexual behavior, it is possible that other genetic factor can play an important role to non-transmission of HIV in this population. Further cost-effectiveness studies are required to justify the genotyping test by using HLA-B*57:01 allele as routine test in Peru.\u003c/p\u003e","manuscriptTitle":"Distribution of CCR5-∆32 and HLA-B*57:01alleles in HIV-seropositive and HIV-exposed seronegative Peruvian individuals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 11:13:40","doi":"10.21203/rs.3.rs-6329775/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-04-21T07:06:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-03T02:14:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Human Genome Variation","date":"2025-04-01T17:46:16+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-03-31T02:42:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-28T16:32:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"human-genome-variation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"hgv","sideBox":"Learn more about [Human Genome Variation](http://www.nature.com/hgv/)","snPcode":"41439","submissionUrl":"https://mts-hgv.nature.com/","title":"Human Genome Variation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6a7ab24f-7f9f-4392-85a8-4c37c8e41843","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47671638,"name":"Health sciences/Diseases/Infectious diseases/HIV infections"},{"id":47671639,"name":"Health sciences/Biomarkers/Prognostic markers"},{"id":47671640,"name":"Biological sciences/Genetics/Genetic markers"}],"tags":[],"updatedAt":"2025-08-27T07:10:17+00:00","versionOfRecord":{"articleIdentity":"rs-6329775","link":"https://doi.org/10.1038/s41439-025-00321-3","journal":{"identity":"human-genome-variation","isVorOnly":false,"title":"Human Genome Variation"},"publishedOn":"2025-08-26 04:00:00","publishedOnDateReadable":"August 26th, 2025"},"versionCreatedAt":"2025-05-05 11:13:40","video":"","vorDoi":"10.1038/s41439-025-00321-3","vorDoiUrl":"https://doi.org/10.1038/s41439-025-00321-3","workflowStages":[]},"version":"v1","identity":"rs-6329775","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6329775","identity":"rs-6329775","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}