Gene-gene interaction between tuberculosis candidate genes in a South African population

Abstract

In a complex disease such as tuberculosis (TB) it is increasingly evident that gene-gene interactions play a far more important role in an individual's susceptibility to develop the disease than single polymorphisms on their own, as one gene can enhance or hinder the expression of another gene. Gene-gene interaction analysis is a new approach to elucidate susceptibility to TB. The possibility of gene-gene interactions was assessed, focusing on 11 polymorphisms in nine genes (DC-SIGN, IFN-γ, IFNGR1, IL-8, IL-1Ra, MBL, NRAMP1, RANTES, and SP-D) that have been associated with TB, some repeatedly. An optimal model, which best describes and predicts TB case-control status, was constructed. Significant interactions were detected between eight pairs of variants. The models fitted the observed data extremely well, with p < 0.0001 for all eight models. A highly significant interaction was detected between INFGR1 and NRAMP1, which is not surprising because macrophage activation is greatly enhanced by IFN-γ and IFN-γ response elements that are present in the human NRAMP1 promoter region, providing further evidence for their interaction. This study enabled us to test the theory that disease outcome may be due to interaction of several gene effects. With eight instances of statistically significant gene-gene interactions, the importance of epistasis is clearly identifiable in this study. Methods for studying gene-gene interactions are based on a multilocus and multigene approach, consistent with the nature of complex-trait diseases, and may provide the paradigm for future genetic studies of TB.

Innate Immune Gene Polymorphisms in Tuberculosis

“…These findings are particularly interesting because the SNPs in TLR4 and IFNGR1 alone did not show significant effects and would not have been identified as associated with TB without the interaction with NOS2A. In a similar way, gene-gene interactions between variants of SLCA11A and TLR2 in African-Americans (249), SLCA11A1 and IFNGR1 in South Africans (62), and TNF and IL-10 in Tunisians (27) yielded significant associations with TB. Those multilocus and multigene approaches can identify critical variants that strongly influence the incidence of TB when combined with other gene variants, while alone they would not meet the criteria for statistical significance.…”

“…Few examples of such a systematic approach are available to date in any area, let alone in TB research. Logistic regression can be used as a preferable statistical method, as has been used in gene-gene interactions in TB (62) and other diseases (52).…”

Cortical bone histomorphology of known‐age skeletons from the Kirsten collection, Stellenbosch university, South Africa

“…In the Cape Town suburbs, the Colored genetic distribution has been characterized as foremost Khoesan, followed by Black African, White and Asian (de Wit et al, 2011; Daya et al, 2013). The Khoesan are the most ancient ancestral peoples of southern Africa, as reflected in their distinctive genome (Schlebusch et al, 2013).…”

Association of a disintegrin and metalloproteinase 33 (ADAM33) gene polymorphisms with chronic obstructive pulmonary disease in the Chinese population: A meta-analysis

“…Second, the combined ORs were based on unadjusted data. Third, lack of the original data of the reviewed studies limited further investigations of potential gene-gene and gene-environment interactions, because the expression of one gene may be enhanced or hindered by another gene or environmental factors (de Wit et al, 2011). Fourth, two studies included less than 100 cases in our meta-analysis (Qin et al, 2012;Zhou and Sun, 2012), which may have increased the chance of type 1 or type 2 errors, making the results potentially unreliable (Zhang et al, 2012).…”