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Peripartum cardiomyopathy (PPCM) is a rare form of acute onset heart failure that presents in otherwise healthy pregnant women around the time of delivery. While most of these women respond to early intervention, about 20% progress to end-stage heart failure that symptomatically resembles dilated cardiomyopathy (DCM). In this study, we examined two independent RNAseq datasets from the left ventricle of end-stage PPCM patients and compared gene expression profiles to female DCM and non-failing donors. Differential gene expression, enrichment analysis and cellular deconvolution were performed to identify key processes in disease pathology. PPCM and DCM display similar enrichment in metabolic pathways and extracellular matrix remodeling suggesting these are similar processes across end-stage systolic heart failure. Genes involved in golgi vesicles biogenesis and budding were enriched in PPCM left ventricles compared to healthy donors but were not found in DCM. Furthermore, changes in immune cell populations are evident in PPCM but to a lesser extent compared to DCM, where the latter is associated with pronounced pro-inflammatory and cytotoxic T cell activity. This study reveals several pathways that are common to end-stage heart failure but also identifies potential targets of disease that may be unique to PPCM and DCM.

As developments in artificial intelligence and machine learning become more widespread in healthcare, their potential to transform clinical outcomes also increases. Peripartum cardiomyopathy is a rare and poorly-characterised condition that presents as heart failure in the last trimester prior to delivery or within 5-6 months postpartum. The lack of a definitive understanding of the molecular causes and clinical progress of this condition suggests that bibliometrics will be well-suited to creating new insights into this serious clinical problem. We examine similarities and differences between peripartum and its closely related familial dilated cardiomyopathy and idiopathic dilated cardiomyopathy. Using PubMed as the source of bibliometric data, we apply artificial intelligence-supported natural language processing to compare extracted data and genes association with these cardiomyopathies. Gene data were enhanced with additional metadata from third-party datasets and then analysed for their impact and specificity for peripartum cardiomyopathy. Artificial intelligence identified 14 genes that distinguished peripartum from both dilated and familial dilated cardiomyopathy. They are as follows: CTSD, RLN2, MMP23B*, SLC17A5, ST2*, PTHLH, CFH*, CFI, GPT, MR1, Rln1, SRI, STAT5A* and THBD. We then used the Human Protein Atlas website that uses affinity-purified rabbit polyclonal antibodies to identify genes that are expressed at the protein level (bold), or as RNA transcripts (*) in healthy human left ventricles. Additional analysis focussed on the full set of peripartum genes on linkage and specificity to cardiomyopathy yielded a different set of thirteen genes (bold font indicates those expressed in cardiomyocytes: PRL, RLN2, PLN, ST2, CTSD, F2, ACE, STAT3, TTN, SPP1, LGALS3, miR-146a, GNB3, SRI). This type of analysis can highlight new avenues for research, aimed at improving genomics-driven peripartum cardiomyopathy diagnosis as well as potential pathological and clinic

Background: Despite in-depth knowledge of the molecular mechanisms controlling embryonic heart development, little is known about the signals governing postnatal maturation of the human heart. Methods: Single-nucleus RNA sequencing of 54 140 nuclei from 9 human donors was used to profile transcriptional changes in diverse cardiac cell types during maturation from fetal stages to adulthood. Bulk RNA sequencing and the Assay for Transposase-Accessible Chromatin using sequencing were used to further validate transcriptional changes and to profile alterations in the chromatin accessibility landscape in purified cardiomyocyte nuclei from 21 human donors. Functional validation studies of sex steroids implicated in cardiac maturation were performed in human pluripotent stem cell–derived cardiac organoids and mice. Results: Our data identify the progesterone receptor as a key mediator of sex-dependent transcriptional programs during cardiomyocyte maturation. Functional validation studies in human cardiac organoids and mice demonstrate that the progesterone receptor drives sex-specific metabolic programs and maturation of cardiac contractile properties. Conclusions: These data provide a blueprint for understanding human heart maturation in both sexes and reveal an important role for the progesterone receptor in human heart development.

BACKGROUND: Despite in-depth knowledge of the molecular mechanisms controlling embryonic heart development, little is known about the signals governing postnatal maturation of the human heart. METHODS: Single-nucleus RNA sequencing of 54 140 nuclei from 9 human donors was used to profile transcriptional changes in diverse cardiac cell types during maturation from fetal stages to adulthood. Bulk RNA sequencing and the Assay for Transposase-Accessible Chromatin using sequencing were used to further validate transcriptional changes and to profile alterations in the chromatin accessibility landscape in purified cardiomyocyte nuclei from 21 human donors. Functional validation studies of sex steroids implicated in cardiac maturation were performed in human pluripotent stem cell-derived cardiac organoids and mice. RESULTS: Our data identify the progesterone receptor as a key mediator of sex-dependent transcriptional programs during cardiomyocyte maturation. Functional validation studies in human cardiac organoids and mice demonstrate that the progesterone receptor drives sex-specific metabolic programs and maturation of cardiac contractile properties. CONCLUSIONS: These data provide a blueprint for understanding human heart maturation in both sexes and reveal an important role for the progesterone receptor in human heart development.

Background: Over 100 mammalian G protein-coupled receptors are yet to be matched with endogenous ligands; these so-called orphans are prospective drug targets for the treatment of disease. GPR37L1 is one such orphan, abundant in the brain and detectable as mRNA in the heart and kidney. GPR37L1 ablation was reported to cause hypertension and left ventricular hypertrophy, and thus, we sought to further define the role of GPR37L1 in blood pressure homeostasis. Methods: We investigated the cardiovascular effects of GPR37L1 using wild-type (GPR37L1wt/wt) and null (GPR37L1KO/KO) mice established on a C57BL/6J background, both under baseline conditions and during AngII infusion. We profiled GPR37L1 tissue expression, examining the endogenous receptor by immunoblotting and a β-galactosidase reporter mouse by immunohistochemistry. Results: GPR37L1 protein was abundant in the brain but not detectable in the heart and kidney. We measured blood pressure in GPR37L1wt/wt and GPR37L1KO/KO mice and found that deletion of GPR37L1 causes a female-specific increase in systolic, diastolic, and mean arterial pressures. When challenged with short-term AngII infusion, only male GPR37L1KO/KO mice developed exacerbated left ventricular hypertrophy and evidence of heart failure, while the female GPR37L1KO/KO mice were protected from cardiac fibrosis. Conclusions: Despite its absence in the heart and kidney, GPR37L1 regulates baseline blood pressure in female mice and is crucial for cardiovascular compensatory responses in males. The expression of GPR37L1 in the brain, yet absence from peripheral cardiovascular tissues, suggests this orphan receptor is a hitherto unknown contributor to central cardiovascular control.

The diagnosis of Systemic Lupus Erythematosus (SLE) is challenging due to its heterogeneous clinical presentation and the lack of robust biomarkers to distinguish it from other autoimmune diseases. Further, currently used laboratory tests do not readily distinguish active and inactive disease. Several groups have attempted to apply emerging high throughput profiling technologies to diagnose and monitor SLE. Despite showing promise, many are expensive and technically challenging for routine clinical use. The goal of this work is to develop a better diagnostic and monitoring tool for SLE. We report a highly customisable antibody microarray that consists of a duplicate arrangement of 82 antibodies directed against surface antigens on peripheral blood mononuclear cells (PMBCs). This high-throughput array was used to profile SLE patients (n = 60) with varying disease activity, compared to healthy controls (n = 24), patients with rheumatoid arthritis (n = 25), and other autoimmune diseases (n = 28). We used a computational algorithm to calculate a score from the entire microarray profile and correlated it with SLE disease activity. Our results demonstrate that leukocyte-capture microarray profiles can readily distinguish active SLE patients from healthy controls (AUROC = 0.84). When combined with the standard laboratory tests (serum anti-dsDNA, complements C3 and C4), the microarrays provide significantly increased discrimination. The antibody microarrays can be enhanced by the addition of other markers for potential application to the diagnosis and stratification of SLE, paving the way for the customised and accurate diagnosis and monitoring of SLE.