The association between single-nucleotide polymorphisms within type 1 interferon pathway genes and human immunodeficiency virus type 1 viral load in antiretroviral-naïve participants

被引:0
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作者
Morup, Sara Bohnstedt [1 ]
Leung, Preston [1 ]
Reilly, Cavan [2 ]
Sherman, Brad T. [3 ]
Chang, Weizhong [3 ]
Milojevic, Maja [1 ]
Milinkovic, Ana [4 ]
Liappis, Angelike [5 ,6 ]
Borgwardt, Line [7 ]
Petoumenos, Kathy [8 ]
Paredes, Roger [9 ,10 ]
Mistry, Shweta S. [2 ]
Macpherson, Cameron R. [1 ,11 ]
Lundgren, Jens [1 ,12 ]
Helleberg, Marie [1 ,12 ]
Reekie, Joanne [1 ]
Murray, Daniel D. [1 ]
机构
[1] Copenhagen Univ Hosp, Rigshosp, Rigshospitalet, Copenhagen, Denmark
[2] Univ Minnesota, Sch Publ Hlth, Div Biostat & Hlth Data Sci, Minneapolis, MN USA
[3] Lab Human Retrovirol & Immunoinformat, Frederick Natl Lab Canc Res, Frederick, MD USA
[4] Chelsea & Westminster Hosp NHS Fdn Trust, London, England
[5] Washington DC Vet Affairs Med Ctr, Washington, DC USA
[6] George Washington Univ, Sch Med & Hlth Sci, Washington, DC USA
[7] Copenhagen Univ Hosp, Rigshosp, Rigshospitalet, Copenhagen, Denmark
[8] Univ New South Wales, Kirby Inst, Sydney, NSW, Australia
[9] Hosp Univ Germans Trias i Pujol, Dept Infect Dis, Badalona, Spain
[10] Hosp Univ Germans Trias i Pujol, IrsiCaixa, Badalona, Spain
[11] Inst Roche, Boulogne Billancourt, France
[12] Copenhagen Univ Hosp, Rigshosp, Rigshospitalet, Copenhagen, Denmark
来源
AIDS RESEARCH AND THERAPY | 2024年 / 21卷 / 01期
基金
新加坡国家研究基金会;
关键词
HIV-1; Viral load; Pathway analysis; SKAT-O; Type; 1; interferon; Host genetics; HIV RNA LEVELS; GENOME; RARE; VARIANT; INFECTION; THERAPY; IMPACT; TESTS; HOST;
D O I
10.1186/s12981-024-00610-x
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Background Human genetic contribution to HIV progression remains inadequately explained. The type 1 interferon (IFN) pathway is important for host control of HIV and variation in type 1 IFN genes may contribute to disease progression. This study assessed the impact of variations at the gene and pathway level of type 1 IFN on HIV-1 viral load (VL). Methods Two cohorts of antiretroviral (ART) na & iuml;ve participants living with HIV (PLWH) with either early (START) or advanced infection (FIRST) were analysed separately. Type 1 IFN genes (n = 17) and receptor subunits (IFNAR1, IFNAR2) were examined for both cumulated type 1 IFN pathway analysis and individual gene analysis. SKAT-O was applied to detect associations between the genotype and HIV-1 study entry viral load (log10 transformed) as a proxy for set point VL; P-values were corrected using Bonferroni (P < 0.0025). Results The analyses among those with early infection included 2429 individuals from five continents. The median study entry HIV VL was 14,623 (IQR 3460-45100) copies/mL. Across 673 SNPs within 19 type 1 IFN genes, no significant association with study entry VL was detected. Conversely, examining individual genes in START showed a borderline significant association between IFNW1, and study entry VL (P = 0.0025). This significance remained after separate adjustments for age, CD4(+) T-cell count, CD4(+)/CD8(+) T-cell ratio and recent infection. When controlling for population structure using linear mixed effects models (LME), in addition to principal components used in the main model, this was no longer significant (p = 0.0244). In subgroup analyses stratified by geographical region, the association between IFNW1 and study entry VL was only observed among African participants, although, the association was not significant when controlling for population structure using LME. Of the 17 SNPs within the IFNW1 region, only rs79876898 (A > G) was associated with study entry VL (p = 0.0020, beta = 0.32; G associated with higher study entry VL than A) in single SNP association analyses. The findings were not reproduced in FIRST participants.<br /> Conclusion Across 19 type 1 IFN genes, only IFNW1 was associated with HIV-1 study entry VL in a cohort of ART-na & iuml;ve individuals in early stages of their infection, however, this was no longer significant in sensitivity analyses that controlled for population structures using LME.
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