Plasmacytoid dendritic cells control homeostasis of megakaryopoiesis.

Platelet homeostasis is essential for vascular integrity and immune defence1,2. Although the process of platelet formation by fragmenting megakaryocytes (MKs; thrombopoiesis) has been extensively studied, the cellular and molecular mechanisms required to constantly replenish the pool of MKs by their progenitor cells (megakaryopoiesis) remains unclear3,4. Here we use intravital imaging to track the cellular dynamics of megakaryopoiesis over days. We identify plasmacytoid dendritic cells (pDCs) as homeostatic sensors that monitor the bone marrow for apoptotic MKs and deliver IFNα to the MK niche triggering local on-demand proliferation and maturation of MK progenitors. This pDC-dependent feedback loop is crucial for MK and platelet homeostasis at steady state and under stress. pDCs are best known for their ability to function as vigilant detectors of viral infection5. We show that virus-induced activation of pDCs interferes with their function as homeostatic sensors of megakaryopoiesis. Consequently, activation of pDCs by SARS-CoV-2 leads to excessive megakaryopoiesis. Together, we identify a pDC-dependent homeostatic circuit that involves innate immune sensing and demand-adapted release of inflammatory mediators to maintain homeostasis of the megakaryocytic lineage.

Cistromic Reprogramming of the Diurnal Glucocorticoid Hormone Response by High-Fat Diet.

The glucocorticoid receptor (GR) is a potent metabolic regulator and a major drug target. While GR is known to play integral roles in circadian biology, its rhythmic genomic actions have never been characterized. Here we mapped GR's chromatin occupancy in mouse livers throughout the day and night cycle. We show how GR partitions metabolic processes by time-dependent target gene regulation and controls circulating glucose and triglycerides differentially during feeding and fasting. Highlighting the dominant role GR plays in synchronizing circadian amplitudes, we find that the majority of oscillating genes are bound by and depend on GR. This rhythmic pattern is altered by high-fat diet in a ligand-independent manner. We find that the remodeling of oscillatory gene expression and postprandial GR binding results from a concomitant increase of STAT5 co-occupancy in obese mice. Altogether, our findings highlight GR's fundamental role in the rhythmic orchestration of hepatic metabolism.

Cells of the adult human heart.

Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies.

Predictive model of transcriptional elongation control identifies trans regulatory factors from chromatin signatures.

Promoter-proximal Polymerase II (Pol II) pausing is a key rate-limiting step for gene expression. DNA and RNA-binding trans-acting factors regulating the extent of pausing have been identified. However, we lack a quantitative model of how interactions of these factors determine pausing, therefore the relative importance of implicated factors is unknown. Moreover, previously unknown regulators might exist. Here we address this gap with a machine learning model that accurately predicts the extent of promoter-proximal Pol II pausing from large-scale genome and transcriptome binding maps and gene annotation and sequence composition features. We demonstrate high accuracy and generalizability of the model by validation on an independent cell line which reveals the model's cell line agnostic character. Model interpretation in light of prior knowledge about molecular functions of regulatory factors confirms the interconnection of pausing with other RNA processing steps. Harnessing underlying feature contributions, we assess the relative importance of each factor, quantify their predictive effects and systematically identify previously unknown regulators of pausing. We additionally identify 16 previously unknown 7SK ncRNA interacting RNA-binding proteins predictive of pausing. Our work provides a framework to further our understanding of the regulation of the critical early steps in transcriptional elongation.

DeepSom: a CNN-based approach to somatic variant calling in WGS samples without a matched normal.

MOTIVATION: Somatic mutations are usually called by analyzing the DNA sequence of a tumor sample in conjunction with a matched normal. However, a matched normal is not always available, for instance, in retrospective analysis or diagnostic settings. For such cases, tumor-only somatic variant calling tools need to be designed. Previously proposed approaches demonstrate inferior performance on whole-genome sequencing (WGS) samples. RESULTS: We present the convolutional neural network-based approach called DeepSom for detecting somatic single nucleotide polymorphism and short insertion and deletion variants in tumor WGS samples without a matched normal. We validate DeepSom by reporting its performance on five different cancer datasets. We also demonstrate that on WGS samples DeepSom outperforms previously proposed methods for tumor-only somatic variant calling. AVAILABILITY AND IMPLEMENTATION: DeepSom is available as a GitHub repository at https://github.com/heiniglab/DeepSom. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An arrhythmogenic metabolite in atrial fibrillation.

BACKGROUND: Long-chain acyl-carnitines (ACs) are potential arrhythmogenic metabolites. Their role in atrial fibrillation (AF) remains incompletely understood. Using a systems medicine approach, we assessed the contribution of C18:1AC to AF by analysing its in vitro effects on cardiac electrophysiology and metabolism, and translated our findings into the human setting. METHODS AND RESULTS: Human iPSC-derived engineered heart tissue was exposed to C18:1AC. A biphasic effect on contractile force was observed: short exposure enhanced contractile force, but elicited spontaneous contractions and impaired Ca2+ handling. Continuous exposure provoked an impairment of contractile force. In human atrial mitochondria from AF individuals, C18:1AC inhibited respiration. In a population-based cohort as well as a cohort of patients, high C18:1AC serum concentrations were associated with the incidence and prevalence of AF. CONCLUSION: Our data provide evidence for an arrhythmogenic potential of the metabolite C18:1AC. The metabolite interferes with mitochondrial metabolism, thereby contributing to contractile dysfunction and shows predictive potential as novel circulating biomarker for risk of AF.

Probing cell identity hierarchies by fate titration and collision during direct reprogramming.

Despite the therapeutic promise of direct reprogramming, basic principles concerning fate erasure and the mechanisms to resolve cell identity conflicts remain unclear. To tackle these fundamental questions, we established a single-cell protocol for the simultaneous analysis of multiple cell fate conversion events based on combinatorial and traceable reprogramming factor expression: Collide-seq. Collide-seq revealed the lack of a common mechanism through which fibroblast-specific gene expression loss is initiated. Moreover, we found that the transcriptome of converting cells abruptly changes when a critical level of each reprogramming factor is attained, with higher or lower levels not contributing to major changes. By simultaneously inducing multiple competing reprogramming factors, we also found a deterministic system, in which titration of fates against each other yields dominant or colliding fates. By investigating one collision in detail, we show that reprogramming factors can disturb cell identity programs independent of their ability to bind their target genes. Taken together, Collide-seq has shed light on several fundamental principles of fate conversion that may aid in improving current reprogramming paradigms.

Inflammatory macrophage memory in nonsteroidal anti-inflammatory drug-exacerbated respiratory disease.

BACKGROUND: Nonsteroidal anti-inflammatory drug-exacerbated respiratory disease (N-ERD) is a chronic inflammatory condition, which is driven by an aberrant arachidonic acid metabolism. Macrophages are major producers of arachidonic acid metabolites and subject to metabolic reprogramming, but they have been neglected in N-ERD. OBJECTIVE: This study sought to elucidate a potential metabolic and epigenetic macrophage reprogramming in N-ERD. METHODS: Transcriptional, metabolic, and lipid mediator profiles in macrophages from patients with N-ERD and healthy controls were assessed by RNA sequencing, Seahorse assays, and LC-MS/MS. Metabolites in nasal lining fluid, sputum, and plasma from patients with N-ERD (n = 15) and healthy individuals (n = 10) were quantified by targeted metabolomics analyses. Genome-wide methylomics were deployed to define epigenetic mechanisms of macrophage reprogramming in N-ERD. RESULTS: This study shows that N-ERD monocytes/macrophages exhibit an overall reduction in DNA methylation, aberrant metabolic profiles, and an increased expression of chemokines, indicative of a persistent proinflammatory activation. Differentially methylated regions in N-ERD macrophages included genes involved in chemokine signaling and acylcarnitine metabolism. Acylcarnitines were increased in macrophages, sputum, nasal lining fluid, and plasma of patients with N-ERD. On inflammatory challenge, N-ERD macrophages produced increased levels of acylcarnitines, proinflammatory arachidonic acid metabolites, cytokines, and chemokines as compared to healthy macrophages. CONCLUSIONS: Together, these findings decipher a proinflammatory metabolic and epigenetic reprogramming of macrophages in N-ERD.

Polygenic risk for coronary artery disease in the Scottish and English population.

BACKGROUND: Epidemiological studies have repeatedly observed a markedly higher risk for coronary artery disease (CAD) in Scotland as compared to England. Up to now, it is unclear whether environmental or genetic factors might explain this phenomenon. METHODS: Using UK Biobank (UKB) data, we assessed CAD risk, based on the Framingham risk score (FRS) and common genetic variants, to explore the respective contribution to CAD prevalence in Scotland (n = 31,963) and England (n = 317,889). We calculated FRS based on sex, age, body mass index (BMI), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), antihypertensive medication, smoking status, and diabetes. We determined the allele frequency of published genome-wide significant risk CAD alleles and a weighted genetic risk score (wGRS) for quantifying genetic CAD risk. RESULTS: Prevalence of CAD was 16% higher in Scotland as compared to England (8.98% vs. 7.68%, P < 0.001). However, the FRS only predicted a marginally higher CAD risk (less than 1%) in Scotland (12.5 ± 10.5 vs.12.6 ± 10.6, P = 0.03). Likewise, the overall number of genome-wide significant variants affecting CAD risk (157.6 ± 7.7 and 157.5 ± 7.7; P = 0.12) and a wGRS for CAD (2.49 ± 0.25 in both populations, P = 0.14) were remarkably similar in the English and Scottish population. Interestingly, we observed substantial differences in the allele frequencies of individual risk variants. Of the previously described 163 genome-wide significant variants studied here, 35 variants had higher frequencies in Scotland, whereas 37 had higher frequencies in England (P < 0.001 each). CONCLUSIONS: Neither the traditional risk factors included in the FRS nor a genetic risk score (GRS) based on established common risk alleles explained the higher CAD prevalence in Scotland. However, we observed marked differences in the distribution of individual risk alleles, which emphasizes that even geographically and ethnically closely related populations may display relevant differences in the genetic architecture of a common disease.

Risk Prediction of Cardiovascular Events by Exploration of Molecular Data with Explainable Artificial Intelligence.

Cardiovascular diseases (CVD) annually take almost 18 million lives worldwide. Most lethal events occur months or years after the initial presentation. Indeed, many patients experience repeated complications or require multiple interventions (recurrent events). Apart from affecting the individual, this leads to high medical costs for society. Personalized treatment strategies aiming at prediction and prevention of recurrent events rely on early diagnosis and precise prognosis. Complementing the traditional environmental and clinical risk factors, multi-omics data provide a holistic view of the patient and disease progression, enabling studies to probe novel angles in risk stratification. Specifically, predictive molecular markers allow insights into regulatory networks, pathways, and mechanisms underlying disease. Moreover, artificial intelligence (AI) represents a powerful, yet adaptive, framework able to recognize complex patterns in large-scale clinical and molecular data with the potential to improve risk prediction. Here, we review the most recent advances in risk prediction of recurrent cardiovascular events, and discuss the value of molecular data and biomarkers for understanding patient risk in a systems biology context. Finally, we introduce explainable AI which may improve clinical decision systems by making predictions transparent to the medical practitioner.

Association of Human FOS Promoter Variants with the Occurrence of Knee-Osteoarthritis in a Case Control Association Study.

Our aim was to analyse (i) the presence of single nucleotide polymorphisms (SNPs) in the JUN and FOS core promoters in patients with rheumatoid arthritis (RA), knee-osteoarthritis (OA), and normal controls (NC); (ii) their functional influence on JUN/FOS transcription levels; and (iii) their associations with the occurrence of RA or knee-OA. JUN and FOS promoter SNPs were identified in an initial screening population using the Non-Isotopic RNase Cleavage Assay (NIRCA); their functional influence was analysed using reporter gene assays. Genotyping was done in RA (n = 298), knee-OA (n = 277), and NC (n = 484) samples. For replication, significant associations were validated in a Finnish cohort (OA: n = 72, NC: n = 548). Initially, two SNPs were detected in the JUN promoter and two additional SNPs in the FOS promoter in perfect linkage disequilibrium (LD). JUN promoter SNP rs4647009 caused significant downregulation of reporter gene expression, whereas reporter gene expression was significantly upregulated in the presence of the FOS promoter SNPs. The homozygous genotype of FOS promoter SNPs showed an association with the susceptibility for knee-OA (odds ratio (OR) 2.12, 95% confidence interval (CI) 1.2⁻3.7, p = 0.0086). This association was successfully replicated in the Finnish Health 2000 study cohort (allelic OR 1.72, 95% CI 1.2⁻2.5, p = 0.006). FOS Promoter variants may represent relevant susceptibility markers for knee-OA.

Unilateral temporal interictal epileptiform discharges correctly predict the epileptogenic zone in lesional temporal lobe epilepsy.

OBJECTIVE: To evaluate the necessity of recording ictal electroencephalography (EEG) in patients with temporal lobe epilepsy (TLE) considered for resective surgery who have unilateral temporal interictal epileptiform discharges (IEDs) and concordant ipsitemporal magnetic resonance imaging (MRI) pathology. To calculate the necessary number of recorded EEG seizure patterns (ESPs) to achieve adequate lateralization probability. METHODS: In a retrospective analysis, the localization and lateralization of interictal and ictal EEG of 304 patients with lesional TLE were analyzed. The probability of further contralateral ESPs was calculated based on a total of 1967 recorded ESPs, using Bayes' theorem. RESULTS: Two hundred seventy-one patients had unilateral TLE, and in 98% of them (265 of 271), IEDs were recorded during video-EEG monitoring. Purely unilateral temporal IEDs were present in 61% (166 of 271 patients). Ipsilateral temporal MRI pathology was found in 83% (138 of 166). Ictal EEG was concordant with the clinical side of TLE in 99% (136 of 138) of these patients. Two patients had discordant ictal EEG with both ipsilateral and contralateral ESPs. Epilepsy surgery with resection in the lesioned temporal lobe was still performed, and both patients remain seizure-free. Probability calculations demonstrate that at least 6 recorded unilateral ESPs result in a >95% probability for a concordance of >0.9 of any further ESPs. SIGNIFICANCE: The combination of purely unilateral temporal IED with ipsitemporal MRI pathology is sufficient to identify the epileptogenic zone, and the recording of ictal ESP did not add any surgically relevant information in these 138 patients. Rarely, discordant ESPs might be recorded, but the surgical outcome remains excellent after surgery on the lesioned side.

Natural variation of histone modification and its impact on gene expression in the rat genome.

Histone modifications are epigenetic marks that play fundamental roles in many biological processes including the control of chromatin-mediated regulation of gene expression. Little is known about interindividual variability of histone modification levels across the genome and to what extent they are influenced by genetic variation. We annotated the rat genome with histone modification maps, identified differences in histone trimethyl-lysine levels among strains, and described their underlying genetic basis at the genome-wide scale using ChIP-seq in heart and liver tissues in a panel of rat recombinant inbred and their progenitor strains. We identified extensive variation of histone methylation levels among individuals and mapped hundreds of underlying cis- and trans-acting loci throughout the genome that regulate histone methylation levels in an allele-specific manner. Interestingly, most histone methylation level variation was trans-linked and the most prominent QTL identified influenced H3K4me3 levels at 899 putative promoters throughout the genome in the heart. Cis- acting variation was enriched in binding sites of distinct transcription factors in heart and liver. The integrated analysis of DNA variation together with histone methylation and gene expression levels showed that histoneQTLs are an important predictor of gene expression and that a joint analysis significantly enhanced the prediction of gene expression traits (eQTLs). Our data suggest that genetic variation has a widespread impact on histone trimethylation marks that may help to uncover novel genotype-phenotype relationships.

Fine mapping of the 1p36 deletion syndrome identifies mutation of PRDM16 as a cause of cardiomyopathy.

Deletion 1p36 syndrome is recognized as the most common terminal deletion syndrome. Here, we describe the loss of a gene within the deletion that is responsible for the cardiomyopathy associated with monosomy 1p36, and we confirm its role in nonsyndromic left ventricular noncompaction cardiomyopathy (LVNC) and dilated cardiomyopathy (DCM). With our own data and publically available data from array comparative genomic hybridization (aCGH), we identified a minimal deletion for the cardiomyopathy associated with 1p36del syndrome that included only the terminal 14 exons of the transcription factor PRDM16 (PR domain containing 16), a gene that had previously been shown to direct brown fat determination and differentiation. Resequencing of PRDM16 in a cohort of 75 nonsyndromic individuals with LVNC detected three mutations, including one truncation mutant, one frameshift null mutation, and a single missense mutant. In addition, in a series of cardiac biopsies from 131 individuals with DCM, we found 5 individuals with 4 previously unreported nonsynonymous variants in the coding region of PRDM16. None of the PRDM16 mutations identified were observed in more than 6,400 controls. PRDM16 has not previously been associated with cardiac disease but is localized in the nuclei of cardiomyocytes throughout murine and human development and in the adult heart. Modeling of PRDM16 haploinsufficiency and a human truncation mutant in zebrafish resulted in both contractile dysfunction and partial uncoupling of cardiomyocytes and also revealed evidence of impaired cardiomyocyte proliferative capacity. In conclusion, mutation of PRDM16 causes the cardiomyopathy in 1p36 deletion syndrome as well as a proportion of nonsyndromic LVNC and DCM.

Unbiased expression mapping identifies a link between the complement and cholinergic systems in the rat central nervous system.

The complement system is activated in a wide spectrum of CNS diseases and is suggested to play a role in degenerative phenomena such as elimination of synaptic terminals. Still, little is known of mechanisms regulating complement activation in the CNS. Loss of synaptic terminals in the spinal cord after an experimental nerve injury is increased in the inbred DA strain compared with the PVG strain and is associated with expression of the upstream complement components C1q and C3, in the absence of membrane attack complex activation and neutrophil infiltration. To further dissect pathways regulating complement expression, we performed genome-wide expression profiling and linkage analysis in a large F2(DA × PVG) intercross, which identified quantitative trait loci regulating expression of C1qa, C1qb, C3, and C9. Unlike C1qa, C1qb, and C9, which all displayed distinct coregulation with different cis-regulated C-type lectins, C3 was regulated in a coexpression network immediately downstream of butyrylcholinesterase. Butyrylcholinesterase hydrolyses acetylcholine, which exerts immunoregulatory effects partly through TNF-α pathways. Accordingly, increased C3, but not C1q, expression was demonstrated in rat and mouse glia following TNF-α stimulation, which was abrogated in a dose-dependent manner by acetylcholine. These findings demonstrate new pathways regulating CNS complement expression using unbiased mapping in an experimental in vivo system. A direct link between cholinergic activity and complement activation is supported by in vitro experiments. The identification of distinct pathways subjected to regulation by naturally occurring genetic variability is of relevance for the understanding of disease mechanisms in neurologic conditions characterized by neuronal injury and complement activation.

A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.

Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 × 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 × 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.

histoneHMM: Differential analysis of histone modifications with broad genomic footprints.

BACKGROUND: ChIP-seq has become a routine method for interrogating the genome-wide distribution of various histone modifications. An important experimental goal is to compare the ChIP-seq profiles between an experimental sample and a reference sample, and to identify regions that show differential enrichment. However, comparative analysis of samples remains challenging for histone modifications with broad domains, such as heterochromatin-associated H3K27me3, as most ChIP-seq algorithms are designed to detect well defined peak-like features. RESULTS: To address this limitation we introduce histoneHMM, a powerful bivariate Hidden Markov Model for the differential analysis of histone modifications with broad genomic footprints. histoneHMM aggregates short-reads over larger regions and takes the resulting bivariate read counts as inputs for an unsupervised classification procedure, requiring no further tuning parameters. histoneHMM outputs probabilistic classifications of genomic regions as being either modified in both samples, unmodified in both samples or differentially modified between samples. We extensively tested histoneHMM in the context of two broad repressive marks, H3K27me3 and H3K9me3, and evaluated region calls with follow up qPCR as well as RNA-seq data. Our results show that histoneHMM outperforms competing methods in detecting functionally relevant differentially modified regions. CONCLUSION: histoneHMM is a fast algorithm written in C++ and compiled as an R package. It runs in the popular R computing environment and thus seamlessly integrates with the extensive bioinformatic tool sets available through Bioconductor. This makeshistoneHMM an attractive choice for the differential analysis of ChIP-seq data. Software is available from http://histonehmm.molgen.mpg.de .

Complement receptor 2 is up regulated in the spinal cord following nerve root injury and modulates the spinal cord response.

BACKGROUND: Activation of the complement system has been implicated in both acute and chronic states of neurodegeneration. However, a detailed understanding of this complex network of interacting components is still lacking. METHODS: Large-scale global expression profiling in a rat F2(DAxPVG) intercross identified a strong cis-regulatory influence on the local expression of complement receptor 2 (Cr2) in the spinal cord after ventral root avulsion (VRA). Expression of Cr2 in the spinal cord was studied in a separate cohort of DA and PVG rats at different time-points after VRA, and also following sciatic nerve transection (SNT) in the same strains. Consequently, Cr2 (-/-) mice and Wt controls were used to further explore the role of Cr2 in the spinal cord following SNT. The in vivo experiments were complemented by astrocyte and microglia cell cultures. RESULTS: Expression of Cr2 in naïve spinal cord was low but strongly up regulated at 5-7 days after both VRA and SNT. Levels of Cr2 expression, as well as astrocyte activation, was higher in PVG rats than DA rats following both VRA and SNT. Subsequent in vitro studies proposed astrocytes as the main source of Cr2 expression. A functional role for Cr2 is suggested by the finding that transgenic mice lacking Cr2 displayed increased loss of synaptic nerve terminals following nerve injury. We also detected increased levels of soluble CR2 (sCR2) in the cerebrospinal fluid of rats following VRA. CONCLUSIONS: These results demonstrate that local expression of Cr2 in the central nervous system is part of the axotomy reaction and is suggested to modulate subsequent complement mediated effects.

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction.

BACKGROUND: The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed. METHODS: For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells). RESULTS: Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies. CONCLUSIONS: Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes.

BACKGROUND: Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging. METHODS: To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes. RESULTS: We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities. CONCLUSIONS: Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.