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Reactivation of fetal-specific genes and isoforms occurs during heart failure. However, the underlying molecular mechanisms and the extent to which the fetal program switch occurs remains unclear. Limitations hindering transcriptome-wide analyses of alternative splicing differences (i.e. isoform switching) in cardiovascular system (CVS) tissues between fetal, healthy adult and heart failure have included both cellular heterogeneity across bulk RNA-seq samples and limited availability of fetal tissue for research. To overcome these limitations, we have deconvoluted the cellular compositions of 996 RNA-seq samples representing heart failure, healthy adult (heart and arteria), and fetal-like (iPSC-derived cardiovascular progenitor cells) CVS tissues. Comparison of the expression profiles revealed that reactivation of fetal-specific RNA-binding proteins (RBPs), and the accompanied re-expression of 1,523 fetal-specific isoforms, contribute to the transcriptome differences between heart failure and healthy adult heart. Of note, isoforms for 20 different RBPs were among those that reverted in heart failure to the fetal-like expression pattern. We determined that, compared with adult-specific isoforms, fetal-specific isoforms encode proteins that tend to have more functions, are more likely to harbor RBP binding sites, have canonical sequences at their splice sites, and contain typical upstream polypyrimidine tracts. Our study suggests that compared with healthy adult, fetal cardiac tissue requires stricter transcriptional regulation, and that during heart failure reversion to this stricter transcriptional regulation occurs. Furthermore, we provide a resource of cardiac developmental stage-specific and heart failure-associated genes and isoforms, which are largely unexplored and can be exploited to investigate novel therapeutics for heart failure.

The causal variants and genes underlying thousands of cardiac GWAS signals have yet to be identified. Here, we leverage spatiotemporal information on 966 RNA-seq cardiac samples and perform an expression quantitative trait locus (eQTL) analysis detecting eQTLs considering both eGenes and eIsoforms. We identify 2,578 eQTLs associated with a specific developmental stage-, tissue- and/or cell type. Colocalization between eQTL and GWAS signals of five cardiac traits identified variants with high posterior probabilities for being causal in 210 GWAS loci. Pulse pressure GWAS loci are enriched for colocalization with fetal- and smooth muscle- eQTLs; pulse rate with adult- and cardiac muscle- eQTLs; and atrial fibrillation with cardiac muscle- eQTLs. Fine mapping identifies 79 credible sets with five or fewer SNPs, of which 15 were associated with spatiotemporal eQTLs. Our study shows that many cardiac GWAS variants impact traits and disease in a developmental stage-, tissue- and/or cell type-specific fashion. The mechanisms underlying many genetic variants associated with human traits are often unknown. Here, the authors identify the developmental stage-, organ-, tissue- and cell type-specific associations between genetic variation and gene expression in cardiac tissues, and describe how these associations affect complex cardiac traits and disease.

Stem cells exist in vitro in a spectrum of interconvertible pluripotent states. Analyzing hundreds of hiPSCs derived from different individuals, we show the proportions of these pluripotent states vary considerably across lines. We discover 13 gene network modules (GNMs) and 13 regulatory network modules (RNMs), which are highly correlated with each other suggesting that the coordinated co-accessibility of regulatory elements in the RNMs likely underlie the coordinated expression of genes in the GNMs. Epigenetic analyses reveal that regulatory networks underlying self-renewal and pluripotency are more complex than previously realized. Genetic analyses identify thousands of regulatory variants that overlapped predicted transcription factor binding sites and are associated with chromatin accessibility in the hiPSCs. We show that the master regulator of pluripotency, the NANOG-OCT4 Complex, and its associated network are significantly enriched for regulatory variants with large effects, suggesting that they play a role in the varying cellular proportions of pluripotency states between hiPSCs. Our work bins tens of thousands of regulatory elements in hiPSCs into discrete regulatory networks, shows that pluripotency and self-renewal processes have a surprising level of regulatory complexity, and suggests that genetic factors may contribute to cell state transitions in human iPSC lines. Stem cells exist in vitro in a spectrum of interconvertible pluripotent states. Here, authors show that pluripotency and self-renewal processes have a high level of regulatory complexity and suggest that genetic factors contribute to cell state transitions in human iPSC lines.

The impact of genetic regulatory variation active in early pancreatic development on adult pancreatic disease and traits is not well understood. Here, we generate a panel of 107 fetal-like iPSC-derived pancreatic progenitor cells (iPSC-PPCs) from whole genome-sequenced individuals and identify 4065 genes and 4016 isoforms whose expression and/or alternative splicing are affected by regulatory variation. We integrate eQTLs identified in adult islets and whole pancreas samples, which reveal 1805 eQTL associations that are unique to the fetal-like iPSC-PPCs and 1043 eQTLs that exhibit regulatory plasticity across the fetal-like and adult pancreas tissues. Colocalization with GWAS risk loci for pancreatic diseases and traits show that some putative causal regulatory variants are active only in the fetal-like iPSC-PPCs and likely influence disease by modulating expression of disease-associated genes in early development, while others with regulatory plasticity likely exert their effects in both the fetal and adult pancreas by modulating expression of different disease genes in the two developmental stages. Fetal development plays an important role in defining adult diabetes risk. Here, authors identified a genetic link between fetal pancreatic gene expression, obesity, and diabetes risk through eQTL mapping of iPSC-derived pancreatic progenitor cells.

Systemic juvenile idiopathic arthritis (sJIA) begins with fever, rash, and high-grade systemic inflammation but commonly progresses to a persistent afebrile arthritis. The basis for this transition is unknown. To evaluate a role for lymphocyte polarization, we characterized T cells from patients with acute and chronic sJIA using flow cytometry, mass cytometry, and RNA sequencing. Acute and chronic sJIA each featured an expanded population of activated Tregs uncommon in healthy controls or in children with nonsystemic JIA. In acute sJIA, Tregs expressed IL-17A and a gene expression signature reflecting Th17 polarization. In chronic sJIA, the Th17 transcriptional signature was identified in T effector cells (Teffs), although expression of IL-17A at the protein level remained rare. Th17 polarization was abrogated in patients responding to IL-1 blockade. These findings identify evolving Th17 polarization in sJIA that begins in Tregs and progresses to Teffs, likely reflecting the impact of the cytokine milieu and consistent with a biphasic model of disease pathogenesis. The results support T cells as a potential treatment target in sJIA.

Signal transducers and activators of transcription (STATs) are the final “switches” that activate gene expression patterns that lead to human malignancy. Extracellular signal-regulated kinases (ERK 1/2) activate STAT 3; four cardiovascular hormones inhibit ERK 1/2 kinases, leading to the hypothesis that they may also inhibit STATs. These four cardiac hormones, i.e., vessel dilator, long-acting natriuretic peptide (LANP), kaliuretic peptide, and atrial natriuretic peptide (ANP), eliminate human cancers growing in mice. These four cardiac hormones’ effects on STATs 1 and 3 were examined in human small-cell lung cancer and human pancreatic adenocarcinoma cells. Vessel dilator, LANP, kaliuretic peptide, and ANP maximally decreased STAT 3 by 88, 54, 55, and 65 %, respectively, at their 1 μM concentrations in human small-cell lung cancer cells and STAT 3 by 66, 57, 70, and 77 % in human pancreatic adenocarcinoma cells, respectively. The cardiac hormones (except LANP) also significantly decreased STAT 3 measured by Western blots. These cardiac hormones did not decrease STAT 1 in either human small-cell lung cancer or pancreatic adenocarcinoma cells. We conclude that these four cardiac hormones are significant inhibitors of STAT 3, but not STAT 1, in human small-cell lung cancer and pancreatic adenocarcinoma cells, which suggests a specificity for these hormones’ anticancer mechanism(s) of action enzymology in human cancer cells.

The regulatory mechanisms underlying the response to pro-inflammatory cytokines in cardiac diseases are poorly understood. Here, we use iPSC-derived cardiovascular progenitor cells (CVPCs) to model the response to interferon gamma (IFNγ) in human cardiac tissue. We generate RNA-seq and ATAC-seq for four CVPCs that were treated with IFNγ and compare them with paired untreated controls. Transcriptional differences after treatment show that IFNγ initiates an innate immune cell-like response, shifts the CVPC transcriptome towards coronary artery and aorta profiles, and stimulates expression of endothelial cell-specific genes. Analysis of the accessible chromatin shows that IFNγ is a potent chromatin remodeler and establishes an IRF-STAT immune-cell like regulatory network. Finally, we show that 11 GWAS risk variants for 8 common cardiac diseases overlap IFNγ-upregulated ATAC-seq peaks. Our findings reveal insights into IFNγ-induced activation of an immune-like regulatory network in the cardiac vascular endothelium and the potential role that regulatory elements in this pathway play in common cardiac diseases.

Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research. Automated pathotyping of synovial tissue in arthritis is a major unmet need. Here, the authors develop and demonstrate the efficacy of an automated tissue and cellular pathotyping tool for inflammatory arthritis.