Prevalence of MMP-8 gene polymorphisms in HIV-infected individuals and its association with HIV-associated neurocognitive disorder

Singh, HariOm; Samani, Dharmesh; Nambiar, Nayana; Ghate, Manisha; Gangakhedkar, Raman

doi:10.1016/j.gene.2017.12.061

Cited by 11 publications

(8 citation statements)

References 31 publications

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“…Additionally, several other most frequently selected genes have been linked to certain disease states in the literature. Particularly increased levels of MMP8 have been observed in HIV-infected patients, which cross-references well as a high proportion of samples in our modelling data coming from HIV viral studies (49). SIGLEC1 is a Type I transmembrane protein expressed by a subpopulation of macrophages and was one of fifteen genes found upregulated during in vivo respiratory syncytial virus infections (50), whilst also said to initiate the formation of the virus-containing compartment (51).…”

Section: Resultssupporting

confidence: 69%

Identifying robust biomarkers of infection through an omics-based meta-analysis

Myall

Perkins

Rushton

et al. 2020

Preprint

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A fundamental problem for disease treatment is that while antibiotics are a powerful counter to bacteria, they are ineffective against viruses. To ensure a given individual receives optimal treatment given their disease state and to reduce over-prescription of antibiotics leading to antimicrobial resistance, the host response can be measured to distinguish between the two states. To establish a predictive biomarker panel of disease state we conducted a meta-analysis of human blood infection studies using Machine Learning (ML). We focused on publicly available gene expression data from two widely used platforms, Affymetrix and Illumina microarrays, and integrated over 2000 samples for each platform to develop optimal gene panels. On average our models predicted 80% of bacterial and 85% viral samples correctly by class of infection type. For our best performing model, identified with an evolutionary algorithm, 93% of bacterial and 89% of viral samples were classified correctly. To enable comparison between the two differing microarray platforms, we reverse engineered the underlying molecular regulatory network and overlay the identified models. This revealed that although the exact gene-level overlap between models generated from the two technologies was relatively low, both models contained genes in the same areas of the network, indicating that the same functional changes in host biology were being detected, providing further confidence in the robustness of our models. Specifically, this convergence was to pathways including the Type I interferon Signalling Pathway, Chemotaxis, Apoptotic Processes, and Inflammatory / Innate Response. Amongst and related to these pathways we found three genes, IFI27, LY6E, and CD177, particularly prevalent throughout our analysis.

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Section: Resultssupporting

confidence: 69%

Identifying robust biomarkers of infection through an omics-based meta-analysis

Myall

Perkins

Rushton

et al. 2020

Preprint

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“…Tobacco smoke also stimulated the release of proinflammatory cytokines, matrix metalloproteinases (MMPs), and nitric oxide, as well as maturation of monocytes into macrophages that adhere to the vascular endotheliam (Hossain et al 2011). These products and events can lead to blood-brain barrier damage and promote microglial activation (Conant et al 2017), which may contribute to the pathogenesis of HAND (Xing et al 2017; Singh et al 2018). Furthermore, plasma MMPs were also associated with white matter diffusivity and viral load in HIV+ participants (Li et al 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Despite the higher prevalence of lifetime use marijuana or alcohol use in the HIV+ participants, covarying for these variables did not change our findings. Other potential confounding factors on the DTI measurements, such as other cardiovascular risk factors (e.g., fast blood glucose level) (Nakamoto et al 2012) and genetic vulnerability (Hoare et al 2013; Chang et al 2014; Singh et al 2018) were not considered in this study. We also did not exclude individuals with second hand smoke exposure; however, if we had excluded the non-smokers exposed to secondhand smoke, we might have found even stronger tobacco effects in the smoker groups.…”

Section: Discussionmentioning

confidence: 99%

Independent and Combined Effects of Chronic HIV-Infection and Tobacco Smoking on Brain Microstructure

Liang

Chang

Chen

et al. 2018

J Neuroimmune Pharmacol

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HIV-infected individuals (HIV+) have 2-3 times higher prevalence of tobacco smoking than the general U.S. population. This study aims to evaluate the independent and combined effects of tobacco-smoking and HIV-infection on brain microstructure and cognition using a 2 × 2 design. 21 HIV + Smokers, 25 HIV + Nonsmokers, 25 Seronegative (SN)-Smokers and 23 SN-Nonsmokers were evaluated using diffusion tensor imaging. Fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivity were assessed in 8 major cerebral fiber tracts and 5 subcortical regions. Cognitive performance in 7 neurocognitive domains was also assessed. Compared to SN, HIV+ had higher AD in genu of corpus callosum (GCC, p = 0.002). Smokers also had higher diffusivities in GCC, splenium of corpus callosum (SCC), anterior corona radiata (ACR), sagittal stratum (SS) and superior fronto-occipital fasciculus (SFO), than Nonsmokers (p-values<0.001-0.003). Tobacco-Smoking and HIV-infection showed synergistic effects on AD_SS (p = 0.002) and RD_SFO (p = 0.02), but opposite effects in FA_putamen (p = 0.024). Additive effects from HIV+ and Tobacco-Smoking were observed in 9 other white matter tracts, with highest diffusivities and lowest FA in HIV + Smokers. Higher diffusivities in the GCC, SCC, ACR and SS predicted poorer cognitive performance across all participants (p ≤ 0.001). Higher AD_GCC also predicted slower Speed of information processing and poorer Fluency and Attention only in HIV + Smokers (p = 0.001-0.003). Chronic tobacco smoking and HIV-infection appear to have additive and synergistic adverse effects on brain diffusivities, suggesting greater neuroinflammation, which may contribute to poorer cognition. Therefore, chronic tobacco-smoking may be a risk factor for HIV-associated neurocognitive disorders. Graphical Abstract ᅟ.

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“…A SNP of the MMP-7 gene, resulting in MMP-7-181 A or G genotypes, was not associated with HAND, even though MMP-7 is upregulated by the Tat protein [ 130 ]. Similarly, MMP-8 gene polymorphisms (−799C/T and +17C/G) were not significantly associated with a risk of HAND [ 131 ]. All these case control studies included HAND of any severity, diagnosed by having an International HIV-associated Dementia Score (IHDS) of less than 9.5.…”

Section: Matrix Metalloproteinase (Mmp) Genesmentioning

confidence: 99%

Risk Factors and Pathogenesis of HIV-Associated Neurocognitive Disorder: The Role of Host Genetics

Olivier

Cacabelos

Naidoo

2018

IJMS

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Neurocognitive impairments associated with human immunodeficiency virus (HIV) infection remain a considerable health issue for almost half the people living with HIV, despite progress in HIV treatment through combination antiretroviral therapy (cART). The pathogenesis and risk factors of HIV-associated neurocognitive disorder (HAND) are still incompletely understood. This is partly due to the complexity of HAND diagnostics, as phenotypes present with high variability and change over time. Our current understanding is that HIV enters the central nervous system (CNS) during infection, persisting and replicating in resident immune and supporting cells, with the subsequent host immune response and inflammation likely adding to the development of HAND. Differences in host (human) genetics determine, in part, the effectiveness of the immune response and other factors that increase the vulnerability to HAND. This review describes findings from studies investigating the role of human host genetics in the pathogenesis of HAND, including potential risk factors for developing HAND. The similarities and differences between HAND and Alzheimer’s disease are also discussed. While some specific variations in host genes regulating immune responses and neurotransmission have been associated with protection or risk of HAND development, the effects are generally small and findings poorly replicated. Nevertheless, a few specific gene variants appear to affect the risk for developing HAND and aid our understanding of HAND pathogenesis.

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Prevalence of MMP-8 gene polymorphisms in HIV-infected individuals and its association with HIV-associated neurocognitive disorder

Cited by 11 publications

References 31 publications

Identifying robust biomarkers of infection through an omics-based meta-analysis

Identifying robust biomarkers of infection through an omics-based meta-analysis

Independent and Combined Effects of Chronic HIV-Infection and Tobacco Smoking on Brain Microstructure

Risk Factors and Pathogenesis of HIV-Associated Neurocognitive Disorder: The Role of Host Genetics

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