Reed, E. F. | Search bioRxiv

bioRxiv2023

Spatial Multi-omics of Arterial Regions from Cardiac Allograft Vasculopathy Rejected Grafts

2. AbstractO_ST_ABSBackgroundC_ST_ABSCardiac allograft vasculopathy (CAV) is a major cause of late-graft failure and mortality following heart transplantation. The mechanisms underlying vascular remodeling are poorly understood. A major immune risk factor associated with the development of CAV is the presence of donor-specific antibodies (DSA) that induce chronic endothelial cell (EC) injury, leukocyte recruitment and inflammation resulting in thickening of arterial intima. Here, we molecularly characterized innate and adaptive immune cells present in the arteries of rejected cardiac allografts with DSA and identified protein and transcriptomic signatures distinguishing early and late CAV lesions. MethodsArterial areas of interest (AOIs) from CAV+DSA+ rejected cardiac allografts (N=3; 2 females, 1 male) were subjected to GeoMx digital spatial profiling (DSP). AOIs were scored on the level of CAV progression/neointimal thickening (22 AOIs total; 11 high and 11 low neointima) and were subjected to whole transcriptome and protein profiling. ResultsAOIs with low neointima significantly increased markers for activated inflammatory infiltrates, transcripts of EC activation and gene modules involved in activating metalloproteinases and TP53 regulation of caspases. Inflammatory and apoptotic protein markers significantly correlated with inflammatory modules in AOIs with low neointima. AOIs with high neointima increased TGF{beta}-regulated transcripts and modules enriched for platelet activation/aggregation. Proteins encoding SMCs and growth factors/survival correlated with modules enriched for proliferation/repair in AOIs with high neointima. Key transcripts in promoting proliferation, migration, and EndoMT were significantly associated with increasing neointima scores. ConclusionOur results reveal new protein and transcriptomic signatures associated with CAV progression. Lesions exhibiting inflammatory profiles appear to be early lesions that transition to later proliferative/pro-fibrotic phenotype CAV lesions. These findings should form the foundation for the identification of improved biomarkers to guide CAV treatment.

immunology↗

bioRxiv2022

Cytokine-expression patterns reveal coordinated immunological programs associated with persistent MRSA bacteremia

Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia is a common, life-threatening infection that imposes up to 30% mortality even when appropriate therapy is used. Despite in vitro efficacy, antibiotics often fail to resolve the infection in vivo, resulting in persistent MRSA bacteremia. Recently, several genetic, epigenetic, and proteomic correlates of persistent outcomes have been identified. However, the extent to which single variables or composite patterns operate as independent predictors of outcome or reflect shared underlying mechanisms of persistence is unknown. To explore this question, we employed a tensor-based integration of host transcriptional and proteomic data across a well-characterized cohort of patients with persistent and resolving MRSA bacteremia outcomes. Tensor-based data integration yielded high correlative accuracy with persistence and revealed immunologic signatures shared across both the transcriptomic and proteomic datasets. We find that elevated proliferation of mature granulocytes associates with resolving bacteremia outcomes. In contrast, patients with persistent bacteremia heterogeneously exhibit correlates of granulocyte dysfunction or immature granulocyte proliferation. Collectively, these results suggest that transcriptional and proteomic correlates of persistent versus resolving bacteremia outcomes are complex and may not be disclosed by conventional modeling. However, a tensor-based integration approach can help to reveal consensus molecular mechanisms in an interpretable manner. Significance StatementWhile antibacterial therapies effectively resolve MRSA in vitro, these treatments often fail to clear MRSA bacteremia in vivo, suggesting that host-pathogen interactions are essential to persistent MRSA bacteremia. Recent studies have identified genetic, transcriptomic, and proteomic determinants of MRSA persistence. These determinants independently, however, provide insufficient mechanistic insight and it is unclear if they indicate unique or overlapping persistence mechanisms. Here, we use tensor-based decomposition to jointly analyze cytokine and transcriptomic measurements from patients with MRSA bacteremia. Results indicate that persistence mechanisms integrated across biological modalities reflect diverging mechanisms of persistent bacteremia. Ultimately, these results may help to identify future therapeutic targets for treating persistent MRSA bacteremia.

immunology↗