The influence of CCL3L1 gene-containing segmental duplications on HIV-1/AIDS susceptibility

The Ohio State University, Columbus, Ohio, United States
Science (Impact Factor: 33.61). 04/2005; 307(5714):1434-40. DOI: 10.1126/science.1101160
Source: PubMed


Segmental duplications in the human genome are selectively enriched for genes involved in immunity, although the phenotypic consequences for host defense are unknown. We show that there are significant interindividual and interpopulation differences in the copy number of a segmental duplication encompassing the gene encoding CCL3L1 (MIP-1alphaP), a potent human immunodeficiency virus-1 (HIV-1)-suppressive chemokine and ligand for the HIV coreceptor CCR5. Possession of a CCL3L1 copy number lower than the population average is associated with markedly enhanced HIV/acquired immunodeficiency syndrome (AIDS) susceptibility. This susceptibility is even greater in individuals who also possess disease-accelerating CCR5 genotypes. This relationship between CCL3L1 dose and altered HIV/AIDS susceptibility points to a central role for CCL3L1 in HIV/AIDS pathogenesis and indicates that differences in the dose of immune response genes may constitute a genetic basis for variable responses to infectious diseases.

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Available from: Luisa Sen,
    • "Recent studies have shown that around 12 percent of the human genome vary in copy number [32] which includes important genetic information. Furthermore, it has been identified that CNV plays an important role in genetic susceptibility to common diseases [41] such as cancer [1], [6], [19], [28], autism [35], HIV [16], immune disorders [13], intellectual disabilities [21], etc. Comparative genome hybridization to DNA microarrays (aCGH) is one of the most popular techniques that can be utilized to detect and map CNV in DNA sequences. "
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    ABSTRACT: Unlabelled: Array comparative genome hybridization (aCGH) is a widely used methodology to detect copy number variations of a genome in high resolution. Knowing the number of break-points and their corresponding locations in genomic sequences serves different biological needs. Primarily, it helps to identify disease-causing genes that have functional importance in characterizing genome wide diseases. For human autosomes the normal copy number is two, whereas at the sites of oncogenes it increases (gain of DNA) and at the tumour suppressor genes it decreases (loss of DNA). The majority of the current detection methods are deterministic in their set-up and use dynamic programming or different smoothing techniques to obtain the estimates of copy number variations. These approaches limit the search space of the problem due to different assumptions considered in the methods and do not represent the true nature of the uncertainty associated with the unknown break-points in genomic sequences. We propose the Cross-Entropy method, which is a model-based stochastic optimization technique as an exact search method, to estimate both the number and locations of the break-points in aCGH data. We model the continuous scale log-ratio data obtained by the aCGH technique as a multiple break-point problem. The proposed methodology is compared with well established publicly available methods using both artificially generated data and real data. Results show that the proposed procedure is an effective way of estimating number and especially the locations of break-points with high level of precision. Availability: The methods described in this article are implemented in the new R package breakpoint and it is available from the Comprehensive R Archive Network at
    IEEE/ACM Transactions on Computational Biology and Bioinformatics 11/2014; DOI:10.1109/TCBB.2014.2361639 · 1.44 Impact Factor
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    • "CCL3L1 gene dose has been associated with intersubject differences in susceptibility to HIV acquisition in European, African, and Hispanic-American adults, intravenous drug users from Estonia, and hemophiliacs from Japan [13] [28] [29]. The average copy number of CCL3L1 varies among populations [13]. A study in Central African Pygmies indicated that there might be a CCL3L1-CCR5- dependent biological basis for interpopulation differences in HIV prevalence and concluded that the copy number of CCL3L1 genes is determinant of HIV-AIDS susceptibility [30]. "
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    ABSTRACT: Sub-Saharan Africa has continued leading in prevalence and incidence of major infectious disease killers such as HIV/AIDS, tuberculosis, and malaria. Epidemiological triad of infectious diseases includes susceptible host, pathogen, and environment. It is imperative that all aspects of vertices of the infectious disease triad are analysed to better understand why this is so. Studies done to address this intriguing reality though have mainly addressed pathogen and environmental components of the triad. Africa is the most genetically diverse region of the world as well as being the origin of modern humans. Malaria is relatively an ancient infection in this region as compared to TB and HIV/AIDS; from the evolutionary perspective, we would draw lessons that this ancestrally unique population now under three important infectious diseases both ancient and exotic will be skewed into increased genetic diversity; moreover, other evolutionary forces are also still at play. Host genetic diversity resulting from many years of malaria infection has been well documented in this population; we are yet to account for genetic diversity from the trio of these infections. Effect of host genetics on treatment outcome has been documented. Host genetics of sub-Saharan African population and its implication to infectious diseases are an important aspect that this review seeks to address.
    08/2014; 2014(108291). DOI:10.1155/2014/108291
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    • "Copy number variation at CCL3L1 has been associated with susceptibility to HIV infection (Liu et al., 2010), autoimmune disease (Burns et al., 2005; Mamtani et al., 2008; McKinney et al., 2008) and asthma (Lee et al., 2011). The median CN of CCL3L1 is 2 in European populations and >2 in other populations (Gonzalez et al., 2005). Evaluation of the role of CCL3L1 CNV in common disease has been hampered by robustness of methodology, particularly that based on Q-PCR (He et al., 2009; Carpenter et al., 2011). "
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    ABSTRACT: Recent advances in high-throughout sequencing technologies have made it possible to accurately assign copy number (CN) at CN variable loci. However, current analytic methods often perform poorly in regions in which complex CN variation is observed. Here we report the development of a read depth-based approach, CNVrd2, for investigation of CN variation using high-throughput sequencing data. This methodology was developed using data from the 1000 Genomes Project from the CCL3L1 locus, and tested using data from the DEFB103A locus. In both cases, samples were selected for which paralog ratio test data were also available for comparison. The CNVrd2 method first uses observed read-count ratios to refine segmentation results in one population. Then a linear regression model is applied to adjust the results across multiple populations, in combination with a Bayesian normal mixture model to cluster segmentation scores into groups for individual CN counts. The performance of CNVrd2 was compared to that of two other read depth-based methods (CNVnator, cn.mops) at the CCL3L1 and DEFB103A loci. The highest concordance with the paralog ratio test method was observed for CNVrd2 (77.8/90.4% for CNVrd2, 36.7/4.8% for cn.mops and 7.2/1% for CNVnator at CCL3L1 and DEF103A). CNVrd2 is available as an R package as part of the Bioconductor project:
    Frontiers in Genetics 08/2014; 5:248. DOI:10.3389/fgene.2014.00248
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