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A multi-phenotype genome-wide association study of clades causing tuberculosis in a Ghanaian- and South African cohort
medRxiv - Genetic and Genomic Medicine Pub Date : 2020-08-25 , DOI: 10.1101/2020.07.27.20162925
Stephanie Julia Müller , Haiko Schurz , Gerard Tromp , Gian van der Spuy , Eileen G Hoal , Paul D van Helden , Ellis Owusu-Dabo , Christian G Meyer , Thorsten Thye , Stefan Niemann , Robin M Warren , Elizabeth Streicher , Marlo Möller , Craig Kinnear

Despite decades of research and advancements in diagnostics and treatment, tuberculosis remains a major public health concern, particularly in low- and middle-income countries. New bioinformatics and computational methods are needed to interrogate the intersection of host- and bacterial genomes and identify novel targets for anti-tuberculosis drugs. Host genotype datum and paired infecting bacterial isolate information were analysed for associations using a multinomial logistic regression framework implemented in SNPTest. Two geographically distinct cohorts were evaluated: a cohort of 947 participants self-identifying as belonging to a five-way admixed South African population and a Ghanaian cohort consisting of 3 311 participants. We report potential associations between host genetic variants and multiple members of the Mycobacterium tuberculosis complex (MTBC). Although none of the variants analyzed in the South African cohort passed the GWAS cut off for significance, 32 single nucleotide polymorphisms were identified in the Ghanaian cohort as being statistically significantly associated with risk for infection with strains of different members of the MTBC. Further analysis revealed that two of these SNPs were directly genotyped, and the rest were imputed using the 1000 Genomes Phase 3 reference panel. The availability of paired host pathogen data is imperative for investigating strain-specific interactions between MTBC and its host. As demonstrated by this study, the implementation of a multinomial logistic regression using paired host pathogen data may prove valuable for further research investigating the complex relationships driving infectious disease.

中文翻译:

加纳和南非队列中引起肺结核的进化枝的多表型全基因组关联研究

尽管在诊断和治疗方面已有数十年的研究和进展,但结核病仍然是主要的公共卫生问题,特别是在中低收入国家。需要新的生物信息学和计算方法来询问宿主基因组和细菌基因组的交叉点,并确定抗结核药物的新靶标。使用在SNPTest中实施的多项逻辑回归框架,分析了宿主基因型数据和成对的感染细菌分离物信息的关联。对两个在地理上不同的队列进行了评估:947个参与者自我识别为属于五向混合南非人口,而加纳的队列则由3 311个参与者组成。我们报告宿主遗传变异与结核分枝杆菌复合体(MTBC)的多个成员之间的潜在关联。尽管在南非队列中分析的变体均未通过GWAS临界值检测,但在加纳队列中发现32种单核苷酸多态性与MTBC不同成员菌株的感染风险在统计学上显着相关。进一步的分析表明,这些SNP中有两个是直接基因分型的,其余的则使用1000个Genomes Phase 3参考标准品进行估算。配对宿主病原体数据的可用性对于调查MTBC及其宿主之间的菌株特异性相互作用至关重要。这项研究表明,
更新日期:2020-08-26
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