Multi-omic latent variable data integration reveals multicellular structure pathways associated with resistance to tuberculin skin test (TST)/interferon gamma release assay (IGRA) conversion in Uganda.

IF 3.5 2区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY BMC Genomics Pub Date : 2025-03-18 DOI:10.1186/s12864-025-11407-1
Madison S Cox, Kimberly A Dill-McFarland, Jason D Simmons, Penelope Benchek, Harriet Mayanja-Kizza, W Henry Boom, Catherine M Stein, Thomas R Hawn
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Abstract

Understanding the mechanisms of early clearance of Mycobacterium tuberculosis (Mtb) may illuminate new therapeutic strategies for tuberculosis (TB). We previously found genetic, epigenetic, and transcriptomic signatures associated with resistance (resister, RSTR) to tuberculin skin test (TST)/interferon gamma release assay (IGRA) conversion among highly exposed TB contacts. We hypothesized that integration of these datasets with multi-omic latent factor methods would detect pathways differentiating RSTR patients from those with asymptomatic TB infection (TBI, also known as latent TB infection or LTBI) that were not detected in individual dataset analyses. We pre-filtered and scaled features with the largest change between TBI and RSTR groups for 126 patients with data in at least two of five data modalities: single nucleotide polymorphisms (SNP), monocyte RNAseq (baseline and Mtb-stimulated conditions), and monocyte epigenetics (methylation and ATAC-seq). Using multiomic latent factor analysis (MOFA), we generated ten latent factors on the subset of 33 patients with all five datasets available, four of which differed by RSTR status (FDR < 0.1). Factor 4 showed the greatest difference between RSTR and TBI groups (FDR < 0.001). Three additional latent factor integration methods also distinguished the RSTR and TBI groups and identified overlapping features with MOFA. Using pathway analysis and a cluster-based enrichment method, we identified functions associated with latent factors and found that MOFA Factors 2-4 include functions related to cell-cell adhesion, cell shape, and multicellular structure development. In summary, latent variable integration methods uncovered signatures associated with resistance to TST/IGRA conversion that were not detected by individual dataset analyses and included pathways associated with cellular interactions and multicellular structures.

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了解结核分枝杆菌(Mtb)的早期清除机制可能有助于制定新的结核病(TB)治疗策略。我们之前发现了与结核菌素皮试(TST)/干扰素γ释放测定(IGRA)高暴露接触者耐药性(耐药者,RSTR)转换相关的遗传、表观遗传和转录组特征。我们假设,将这些数据集与多组学潜伏因子方法整合在一起,将能检测出单个数据集分析中未检测到的区分 RSTR 患者与无症状结核感染(TBI,又称潜伏结核感染或 LTBI)患者的途径。我们对 126 名患者的五种数据模式(单核苷酸多态性 (SNP)、单核细胞 RNAseq(基线和 Mtb 刺激条件)和单核细胞表观遗传学(甲基化和 ATAC-seq))中至少两种模式的数据进行了预过滤,并对 TBI 组和 RSTR 组之间变化最大的特征进行了缩放。利用多组学潜在因子分析(MOFA),我们在33名患者的子集上生成了10个潜在因子,这些子集拥有全部5个数据集,其中4个因子因RSTR状态而异(FDR为0.01)。
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来源期刊
BMC Genomics
BMC Genomics 生物-生物工程与应用微生物
CiteScore
7.40
自引率
4.50%
发文量
769
审稿时长
6.4 months
期刊介绍: BMC Genomics is an open access, peer-reviewed journal that considers articles on all aspects of genome-scale analysis, functional genomics, and proteomics. BMC Genomics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
期刊最新文献
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