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

ABSTRACT 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, Sep 29, 2015
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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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    • "Many types of genetic variation such as single-nucleotide polymorphisms (SNPs) and copy number variations (CNVs) [2] [3] [4] [5] [6] [7] have been discovered to be associated with lung cancer. Copy number variations are prevalent in the genome, covering approximately 12% of the human genome [8], which may make it more likely to contribute to disease incidence [9] [10] [11] [12] [13] [14] [15]. Thus, a systematic survey of CNVs in lung cancer is essential. "
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    ABSTRACT: Background. Lung cancer is the most important cause of cancer mortality worldwide, but the underlying mechanisms of this disease are not fully understood. Copy number variations (CNVs) are promising genetic variations to study because of their potential effects on cancer. Methodology/Principal Findings. Here we conducted a pilot study in which we systematically analyzed the association of CNVs in two lung cancer datasets: the Environment And Genetics in Lung cancer Etiology (EAGLE) and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial datasets. We used a preestablished association method to test the datasets separately and conducted a combined analysis to test the association accordance between the two datasets. Finally, we identified 167 risk SNP loci and 22 CNVs associated with lung cancer and linked them with recombination hotspots. Functional annotation and biological relevance analyses implied that some of our predicted risk loci were supported by other studies and might be potential candidate loci for lung cancer studies. Conclusions/Significance. Our results further emphasized the importance of copy number variations in cancer and might be a valuable complement to current genome-wide association studies on cancer.
    BioMed Research International 07/2014; 2014:469103. DOI:10.1155/2014/469103 · 2.71 Impact Factor
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