Skip to main content

Low prevalence of CCR5-Δ32, CCR2-64I and SDF1-3′A alleles in the Baiga and Gond tribes of Central India


Human immunodeficiency virus-1 (HIV-1) which causes acquired immune deficiency syndrome (AIDS), by infecting CD4+ immune cells and hence weakening the host defense mechanism till death, is one of the major factor responsible for human demises worldwide. Both innate (monocytes and macrophages) and adaptive (T cells) immune cells expresses chemokines receptors (2 and 5) and stromal cell derived factor-1 (SDF-1) which play crucial role in HIV-1 virus entry and progression. Allele variants of genes CCR5 (CCR5-Δ32), CCR2 (CCR2-64I) and SDF1 (SDFA-3A; the ligand of CXCR4) are known to slow down the HIV-1 progression in infected individual. In the present study, the frequency of CCR5-Δ32, CCR2-64I and SDF1-3A alleles in primitive tribe (Baiga) and a non-primitive tribe (Gond) of central India were investigated. A total 200 seronegative samples for HIV from healthy individuals of tribes were analyzed and observed allele frequencies of CCR5-Δ32, CCR2-64I and SDF1-3A were (0, 0.035, 0.080) and (0, 0.110, 0.100) in Baiga and Gond respectively. Minor allele frequency of these alleles of Gond and Baiga tribes were compared with different populations of the world for relative hazard (RH), which indicate the risk of progression after infection of HIV1. The RH values were calculated based on genotypic frequency, showed the high RH value (RH1-AIDS1993-0.98, RH2-AIDS1987-0.98 and death/RH3-0.97) in Baiga tribe, indicates the low level of resistance against HIV-1 progression after infection.


It has been nearly three to four decade since the report of the first acquired immune deficiency syndrome (AIDS) case which attracted the world’s attention. The AIDS is caused by the human immunodeficiency virus (HIV) which targets various types of cells of host immunity such as dendritic cells, macrophages and T cell subtypes etc. and slowly weakens the host immune system leading to severe immunodeficiency. According to recent report, about 70 million people have been infected by the HIV which caused 35 million deaths worldwide (Horvath et al. 2012; Ruelas and Greene 2013). HIV-1 and HIV-2 are the two types of HIV (McCutchan 2006), of which, the former is found in majority of the AIDS cases and is considered to be highly pathogenic. Upon infection, progress of HIV-1 has been shown to be influenced by C–C family chemokine receptors (CCR) like CCR5, CCR2 and SDF1 (a ligand of CXCR4). These molecules have been shown to play an important role in the entry of HIV-1 into various cell types such as macrophages, monocytes and T-cells (CD4+) (Herbein and Varin 2010; Doitsh et al. 2014). A 32 bp deletion in CCR5 coding sequence is well known as CCR5-Δ32 polymorphism, was identified in case of near complete resistance from HIV1 in homozygous state and slower progression of HIV1 in heterozygote state (Dean et al. 1996; Liu et al. 1996; Samson et al. 1996). Many populations studies conducted worldwide have been shown that genetic variants CCR5-Δ32 (32-bp deletion), CCR2-64I (V → I) and SDF1-3A (G-801A) slower the rate of HIV-1 progression thus leading to delayed onset and reduced severity of AIDS. The risk of AIDS onset for populations is calculated through determination of relative hazard (RH) based on the occurrence of mutation in these three gene loci (Dean et al. 1996; Smith et al. 1997; Winkler et al. 1998).

India has the largest portion of the world’s primitive and non-primitive tribal populations, among which most of the tribal populations distributed mainly in eastern and central Indian states followed by Rajasthan and Gujarat states of India. According to census of 2011, the total populations of India estimated are 1.29 billion in which tribal populations contributed 0.1 billion. Tribal populations are distributed all over India except Punjab and Haryana, states of India. A significant part (14.7 %) of Indian tribal populations is distributed in the central Indian state Madhya Pradesh. A tribe is a group of people who are linguistically, socially and geographically isolated from modern human populations and for their livelihood, they are dependent on their land while primitive tribes are generally considered as those people who are isolated from tribes in past and are more backward with very low income, lived in difficult areas in small and scattered habitat therefore their social interaction with main stream is almost negligible. Baiga tribe is more geographically and socially isolated than Gond tribe from other caste populations of India. Consequently, there is less chance of Baiga tribe to share their gene pool with well developed human caste populations. Due to the same reason, on the basis of primitive and non primitive, we have selected Baiga and Gond tribes for present study. Baiga is a primitive tribe (Population size: approximately 0.5 million) mostly found in Mandla and Balaghat districts of a central Indian state, Madhya Pradesh. They practice consanguineous marriage and remain poorly informed about various infectious diseases including HIV/AIDS (Reddy and Modell 1997; Saha et al. 2013). Women of the tribe are known to sporting tattoos on their body using needles. The Gond is the tribal community mostly found in the forests of the central India. According to census 2011 Gond is a second largest tribe in Madhya Pradesh, a central Indian state with a population of 4.36 million. They are widely spread in the Chhindwara district of Madhya Pradesh, Bastar district of neighbouring Indian states of Chhattisgarh and also in parts of Maharashtra, Andhra Pradesh and Orissa states. The name by which the Gond calls themselves is Koi or Koitur which means unclear. They are one of the largest tribal groups in the world.

To date, no genetic studies have been conducted on chemokine marker polymorphism which related with HIV infection risk in primitive Baiga tribe and non-primitive Gond tribe.


CCR5-Δ32 mutant is well known to provide resistance from HIV-1 by preventing cell entry through expression of truncated protein. Therefore, individuals harbouring homozygous mutant allele (Δ32/Δ32) are highly resistant to HIV-1 infection whereas, heterozygous (Δ32/wt) have partial protection (Su et al. 2000). In this study, deletion mutant genotype (Δ32/Δ32) as well as (Δ32/wt) were not observed in both the tribal populations; (Table 1). CCR2-64I and SDF1-3A mutant alleles are also shown to be associated with suppression of HIV-1 progression to AIDS; however, the suppressive effect is lower in comparison to CCR5-Δ32. The suppressive effect exerted by the SDF1-3A mutation is recessive i.e., observed only in homozygote mutant (3′A/3′A) (Su et al. 1999). The frequency of SDF1 genotype (3′A/3′A) was found to be very less (1 %) in Gond and was not found in Baiga tribe. The CCR2 genotype (64I/64I) was not found in Baiga tribe; however, it is present in Gond tribe with a very low frequency (1 %) (Table 1). Additionally, the frequency of heterozygous (64V/64I) was observed less in Baiga (7 %) compared to the Gond tribe (20 %) (Table 1). Further analysis of genotype data did not show significant deviation from the Hardy–Weinberg expected frequency, indicating that the alleles are in genetic equilibrium (Table 1). Furthermore, we estimated the RH indices by using the three locus genotype data. RH values were calculated for all the three definitions, AIDS-1993, AIDS-1987 and Death by using formula RH = ∑(Wi*Pi); where Wi and Pi denotes the genotype specific RH and frequencies respectively. RH value vary from population to population, however geographically or ethically related populations tend to have similar RH values as they have comparable minor allele frequency (MAF) for three genes. Out of 27 possible three locus genotypes, we found only 4 in Baiga and 6 in Gond tribe (Additional file 1: Table S1). Detection of only 4 and 6 different genotypes is due to the fact that the CCR5-wt allele is fixed in these populations and also the homozygous genotypes of CCR2 genotype (64I/64I) and SDF1 (3A/3A) are not found in the Baiga population. Baiga tribe showed a high RH value [AIDS1993-0.98 (RH1), AIDS1987-0.98 (RH2) and Death-0.97 (RH3)] (Table 2).

Table 1 Distribution of genotype and allele frequency of CCR5, CCR2 and SDF-1 genes in primitive tribe (Baiga) and non-primitive tribe (Gond) of Central India
Table 2 The RH values in Baiga and Gond tribes of Central India


HIV-1 is highly pathogenic and relatively modern virus compared to the several other pathogens. Progression of HIV-1 after infection in slow in those individuals who carries the mutant form of genes such as CCR5, CCR2 and SDF1. These mutational changes have originated outside India, however, due to social interaction among various world populations, the frequency of mutant alleles were raised in several populations. Earlier study on ethnic populations of India have shown that CCR5-Δ32 allele is completely absent in tribes, however it can be found very low in Caste populations (Majumder and Dey 2001). It can be predicted that endogamy practices, geographical isolation might be the factors for the low frequencies of CCR5-Δ32, CCR2-64I and SDF1-3A. Due to the absence of social interactions with modern populations, primitive tribes have not acquired the alleles that reduce the progression of HIV-1 infection making them highly susceptible. In this study all the individuals were expressing homozygous wild type allele (wt/wt) for the CCR5 gene (Table 1), indicating that the allele CCR5-Δ32 is completely absent in both the tribal groups and very low allele frequency of mutant alleles of CCR2 and SDF1 were recorded in Gond and Baiga tribes. All together our study indicates that the frequency of the alleles, CCR5-Δ32, CCR2-64I and SDF1-3A are significantly low in both the tribal populations (Table 1). The comparison of RH values of present studied tribe with earlier studied populations of India and the different populations (Su et al. 2000; Xiao et al. 2000; Ramana et al. 2001 and Salem et al. 2009) of the world showing the highest RH value in primitive tribe “Baiga” (Fig. 1; Additional file 1: Table S2).

Fig. 1
figure 1

Comparison of relative hazard (RH) in Baiga tribe with Gond tribe and rest of world populations (Ramana et al. 2001; Salem et al. 2009; Su et al. 2000; Xiao et al. 2000). RH1, RH2 and RH3 refer to AIDS-1993, AIDS-1987 and Death respectively


The frequency of CCR5-Δ32, CCR2-64I and SDF1-3A are recorded low in Gond and very low in the Baiga tribe. It can be predicted that endogamy practices, geographical isolation might be the factors for low frequencies of CCR5-Δ32, CCR2-64I and SDF1-3A. Due to absence of social interaction with modern populations, primitive tribes have not acquired the alleles that reduce the progression of HIV-1 infection making them highly susceptible to the same. The high RH of AIDS onset indicates very low resistance in Baiga against HIV-1 progression after infection. Therefore, present study showed that there are not enough protective shields against HIV-1 for central Indian tribes.


The 200 samples were obtained from unrelated healthy individuals of Baiga and Gond tribes of central India. All the samples were seronegative for HIV. This study was carried out according to the ethical guidelines of Institutional Ethical Committee (IEC), IISER Bhopal and with the written consent of all the participants. Blood samples from the individuals were spotted on Whatman FTA classic Cards (GE healthcare) and processed for PCR as per manufacturer instructions. The region containing the CCR5-Δ32, CCR2-64I and SDF1-3A were amplified using Phusion Blood Direct PCR Kit (Thermo scientific) as per manufacturer protocol with corresponding Primers (CCR5-Fw: 5′-GCTGTCGTCCATGCTGTGTTT-3′, Rv:5′-CAACCTGTTAGAGCTACTGCAATT-3′); (CCR2-Fw:5′ATCAGAAATACCAACGAGAGCGG-3′, Rv:5′-ACACCGAAGCAGGGTTTTCAGG-3′) and (SDF1-Fw:5′-CAGTCAACCTGGGCAAAGCC-3′, Rv:5′-AGCTTTGGTCCTGAGAGTCC-3′) (Struyfa et al. 2000; Junhua et al. 2000; Bhatnagar et al. 2009). The sequencing of PCR products were performed using 3730 DNA Analyzer (Applied Bio systems) sequencer using the Fw primer used in the PCR amplification. The SNPs were then analysed using Sequencing Analysis software v5.4. Allele frequencies were calculated using the formula, Allele Frequency = {(2 × Number of individuals having genotype homozygous for that particular allele) + (Number of individuals having heterozygous genotype)}/(2 × Total Number of individuals). RH values is estimated on based on genotype frequency and calculated for all the three definitions, AIDS-1993, AIDS-1987 and Death by using formula RH = ∑(Wi*Pi); where Wi and Pi denote the genotype specific RH and frequencies respectively.  


  • Bhatnagar I, Singh M, Mishra N, Saxena R, Thangaraj K, Singh L, Saxena SK (2009) The latitude wise prevalence of the ccr5-∆32-hiv resistance allele in India. Balk J Med Genet 12:17–27

    Google Scholar 

  • Dean M, Carrington M, Winkler C, Huttley GA, Smith MW, Allikmets R, Goedert JJ, Buchbinder SP, Vittinghoff E, Gomperts E et al (1996) Genetic restriction of HIV-1 infection and progression to AIDS by a deletion allele of the CKR5 structural gene. Hemophilia Growth and Development Study, Multicenter AIDS Cohort Study, Multicenter Hemophilia Cohort Study, San Francisco City Cohort, ALIVE Study. Science 273:1856–1862

    Article  Google Scholar 

  • Doitsh G, Galloway NL, Geng X, Yang Z, Monroe KM, Zepeda O, Hunt PW, Hatano H, Sowinski S, Munoz-Arias I et al (2014) Cell death by pyroptosis drives CD4 T-cell depletion in HIV-1 infection. Nature 505:509–514

    Article  Google Scholar 

  • Herbein G, Varin A (2010) The macrophage in HIV-1 infection: from activation to deactivation? Retrovirology 7:33

    Article  Google Scholar 

  • Horvath T, Azman H, Kennedy GE, Rutherford GW (2012) Mobile phone text messaging for promoting adherence to antiretroviral therapy in patients with HIV infection. Cochrane Database Syst Rev 3:CD009756

    Google Scholar 

  • Junhua X, Fang H, Hongyan X, Bing S, Yueming J, Jingchun L, Weiling Z, Jiazhen T, Li J, Daru L (2000) Provincial distribution of three HIV-1 resistant polymorphisms (CCR5- 32, CCR2-64I, and SDF1-3 A) in China. Sci China 43:16–21

    Article  Google Scholar 

  • Liu R, Paxton WA, Choe S, Ceradini D, Martin SR, Horuk R, MacDonald ME, Stuhlmann H, Koup RA, Landau NR (1996) Homozygous defect in HIV-1 coreceptor accounts for resistance of some multiply-exposed individuals to HIV-1 infection. Cell 86(3):367–377

    Article  Google Scholar 

  • Majumder PP, Dey B (2001) Absence of the HIV-1 protective Delta ccr5 allele in most ethnic populations of India. Eur J Hum Genet 9:794–796

    Article  Google Scholar 

  • McCutchan FE (2006) Global epidemiology of HIV. J Med Virol 78(Suppl 1):S7–S12

    Article  Google Scholar 

  • Ramana GV, Vasanthi A, Khaja M, Su B, Govindaiah V, Jin L, Singh L, Chakraborty R (2001) Distribution of HIV-1 resistance-conferring polymorphic alleles SDF-1-3′A, CCR2-64I and CCR5-Delta32 in diverse populations of Andhra Pradesh, South India. J Genet 80:137–140

    Article  Google Scholar 

  • Reddy PH, Modell B (1997) The Baigas of Madhya Pradesh: a demographic study. J Biosoc Sci 29:19–31

    Article  Google Scholar 

  • Ruelas DS, Greene WC (2013) An integrated overview of HIV-1 latency. Cell 155:519–529

    Article  Google Scholar 

  • Saha KB, Saha UC, Sharma RK, Pandey A (2013) Reaching tribal men to improve awareness to sexual morbidities: experience from Baiga tribe of central India. Indian J Med Res 137:928–934

    Google Scholar 

  • Salem AH, Farid E, Fadel R, Abu-Hijleh M, Almawi W, Han K, Batzer MA (2009) Distribution of four HIV type 1-resistance polymorphisms (CCR5-Delta32, CCR5-m303, CCR2-64I, and SDF1-3′A) in the Bahraini population. AIDS Res Hum Retrovir 25:973–977

    Article  Google Scholar 

  • Samson M, Libert F, Doranz BJ, Rucker J, Liesnard C, Farber CM, Saragosti S, Lapoumeroulie C, Cognaux J, Forceille C, Muyldermans G, Verhofstede C, Burtonboy G, Georges M, Imai T, Rana S, Yi Y, Smyth RJ, Collman RG, Doms RW, Vassart G, Parmentier M (1996) Resistance to HIV-1 infection in caucasian individuals bearing mutant alleles of the CCR-5 chemokine receptor gene. Nature 382(6593):722–725

    Article  Google Scholar 

  • Smith MW, Dean M, Carrington M, Winkler C, Huttley GA, Lomb DA, Goedert JJ, O’Brien TR, Jacobson LP, Kaslow R et al (1997) Contrasting genetic influence of CCR2 and CCR5 variants on HIV-1 infection and disease progression. Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC), ALIVE Study. Science 277:959–965

    Article  Google Scholar 

  • Struyfa F, Thoelena I, Charliera N, Keyaertsa E, Van der I, Joanne D, Marc W, Ransta V (2000) Ccr2 Prevalence of CCR5 and CCR2 HIV-Coreceptor Gene Polymorphisms in Belgium. Hum Hered 50:304–307

    Article  Google Scholar 

  • Su B, Jin L, Hu F, Xiao J, Luo J, Lu D, Zhang W, Chu J, Du R, Geng Z et al (1999) Distribution of two HIV-1-resistant polymorphisms (SDF1-3′A and CCR2-64I) in East Asian and world populations and its implication in AIDS epidemiology. Am J Hum Genet 65:1047–1053

    Article  Google Scholar 

  • Su B, Sun G, Lu D, Xiao J, Hu F, Chakraborty R, Deka R, Jin L (2000) Distribution of three HIV-1 resistance-conferring polymorphisms (SDF1-3′A, CCR2-641, and CCR5-delta32) in global populations. Eur J Hum Genet 8:975–979

    Article  Google Scholar 

  • Winkler C, Modi W, Smith MW, Nelson GW, Wu X, Carrington M, Dean M, Honjo T, Tashiro K, Yabe D et al (1998) Genetic restriction of AIDS pathogenesis by an SDF-1 chemokine gene variant. ALIVE Study, Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC). Science 279:389–393

    Article  Google Scholar 

  • Xiao JH, Hu F, Xu HY, Su B, Jiang YM, Luo JC, Zhang WL, Tan JZ, Jin L, Lu DR (2000) Provincial distribution of three HIV-1 resistant polymorphisms (CCR5-Delta 32, CCR2-64I, and SDF1-3′A) in China. Sci China Ser C 43:16–20

    Article  Google Scholar 

Download references

Authors’ contributions

HK and DB conceived the study. DB, RSM, SK, HI, TY, AM, AAR, collected tribal blood samples, extracted DNA and performed sequencing. DB and AK analysed the data. HK and AK wrote the manuscript. HK supervised the overall study. All authors read and approved the final manuscript.


This work is supported by research grants number SR/S2/RJN-55/2009 and BT/PR6009/GBD/27/382/2012 from Department of Science and technology (DST) and Department of Biotechnology (DBT), Government of India (H.K.); MPCST3657/CST/BTA (D.B.) and Intramural Research Grant of IISER, Bhopal, India, Authors would like to thank the sequencing facility of Department of Biological Sciences, IISER Bhopal. D.B. would like to thank the PDF support from IISER Bhopal.

Compliance with ethical guidelines

Competing interests The authors declare that they have no competing interests.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Himanshu Kumar.

Additional file

Additional file 1:

Table S1. The relative hazard (RH) value calculations based on the three-locus genotype for each individual of Primitive tribe, Baiga and Non primitive tribe, Gond. Table S2. The relative hazard values of the other populations of the world.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bharti, D., Kumar, A., Mahla, R.S. et al. Low prevalence of CCR5-Δ32, CCR2-64I and SDF1-3′A alleles in the Baiga and Gond tribes of Central India. SpringerPlus 4, 451 (2015).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: