AIMS:Acute myocardial infarction (MI) induces a systemic inflammatory response that usually resolves within days, but the prognostic impact of persistent inflammation is uncertain. We assessed whether sustained leukocytosis after ST-segment elevation myocardial infarction (STEMI) relates to infarct size, left ventricular function, and clinical outcomes. METHODS AND RESULTS:In >1,700 STEMI patients treated with primary percutaneous coronary intervention, leukocytes peaked on admission and typically normalized by day 3. Patients were stratified by leukocyte tertiles at admission and day 3. High day 3 leukocyte counts were associated with larger infarct size (scintigraphy; peak creatine kinase-myocardial band and troponin T), worse left ventricular function in hospital and at 6 months, and higher 1- and 5-year mortality. Patients whose leukocyte counts declined had better recovery, whereas persistent leukocytosis marked the poorest outcomes. Monocyte RNA sequencing showed post-MI transcriptomic reprogramming, and murine MI models recapitulated a similar systemic immune response. CONCLUSIONS:Persistent inflammation, particularly elevated leukocyte counts at day 3 post-MI, is associated with adverse remodeling and increased mortality after STEMI, identifying unresolved inflammation as a negative prognostic marker and potential therapeutic target.

Study objective:Polygenic risk scores (PRS) are increasingly recognized for their potential to improve coronary artery disease (CAD) prediction beyond traditional clinical models. This study evaluated the utility of genome-wide association study (GWAS) - derived PRS and pathway-specific PRS (PS-PRS) in the Latvian population, aiming to assess their association with CAD and compare their predictive performance with conventional risk factors. Design participants and main outcome measures:The study included 90 early-onset CAD patients and 43 controls with no evidence of atherosclerotic lesions on coronary angiography, with next-generation sequencing performed. PRS was calculated using 192 single nucleotide variants identified from the CARDIoGRAMplusC4D GWAS meta-analysis. The predictive accuracy of PRS, PS-PRS, clinical risk factors, and their combinations was analyzed via ROC curves. Results:The average age was 48.7 years in CAD patients and 49.8 in controls. CAD patients showed significantly higher PRS (mean 0.31) compared to controls (mean - 0.65; p < 0.0001). PRS alone had moderate discriminatory power (AUC = 0.773), slightly lower than LDL cholesterol (AUC = 0.775) and total cholesterol (AUC = 0.821). Combining clinical risk factors improved prediction (AUC = 0.872), with the highest accuracy when PRS was integrated with all clinical factors (AUC = 0.933). The PRS distributions were significantly elevated in early-onset CAD patients across the angiogenesis/tissue repair pathway (p = 0.00038), inflammation pathway (p = 0.043), vascular remodelling pathway (p = 0.0116), and pathway of genes with unknown function in atherosclerosis (p = 0.0035), but overall PRS demonstrated superior discrimination compared to pathway-specific PRS. Conclusions:Incorporating PRS enhances early-onset CAD risk prediction. Pathway specific PRS had lower discriminative ability than the overall PRS.

Mental stress is a major risk factor for cardiovascular disease, yet no targeted therapies exist to reduce stress-related vascular risk. We investigated whether physical activity mitigates the adverse cardiovascular effects of acute mental stress and explored the underlying mechanisms. Sedentary and physically active mice, following 6 weeks of voluntary treadmill running, were exposed to acute mental stress, and inflammatory responses within atherosclerotic plaques were assessed. Physically active mice exhibited markedly reduced stress-induced leukocyte infiltration into plaques compared with sedentary mice. This protective effect was associated with blunted stress-induced norepinephrine release and reduced endothelial activation, reflected by lower expression of adhesion molecules and chemokines. To assess translational relevance, physically active and inactive human participants were exposed to acute stress, revealing that physical activity similarly attenuated stress-induced leukocyte redistribution. These findings demonstrate that physical activity counteracts stress-induced vascular inflammation and highlight its potential as a preventive and therapeutic strategy to reduce stress-related cardiovascular risk.

Modern clinical practice lacks rapid, reliable, and non-invasive methods to distinguish between bacterial and viral infections. It negatively impacts the effectiveness of treatment and increases the risk of unnecessary antibiotic administration and thus antibiotic resistance spread. Using microRNA (miRNA) biomarkers in urine may become the solution to the problems listed. miRNAs in urine are relatively stable and can provide an indirect yet specific insight into systemic infections, offering a promising diagnostic tool. In this pilot study, urine small RNA and blood full transcriptome sequencing data were analyzed in children with bacterial infections (n = 7), viral infections (n = 7), and controls (n = 8). The objectives were to identify exploratory urinary miRNA signatures and attempt to indirectly correlate differentially expressed (DE) urinary miRNAs with DE transcripts in blood. Using LASSO regularized logistic regression and ANOVA, miRNA biomarker candidates were prioritized. Cross-compartment miRNA: mRNA interactions were putatively evaluated using correlation analysis and target prediction. LASSO regularized regression identified a 5-miRNA signature yielding an apparent internal AUC score of 0.981, though wide confidence intervals reflect the exploratory nature of this small cohort. The prioritized miRNAs demonstrated a descriptive capacity to cluster the patient groups. Correlation analysis and target prediction highlighted parallel molecular patterns across biological fluids, mapping to key immune processes such as cytokine-cytokine receptor interactions and T-cell activation. Our pilot study suggests that prioritized urine miRNA biomarkers reflect host infectious etiology and merit further investigation. While internal performance metrics require validation in larger, independent cohorts, the non-invasive approach represents a promising step toward targeted, timely treatment and the reduction of antibiotic resistance.

BACKGROUND: The prevalence of coronary artery disease (CAD) is increasing among young adults. To improve CAD diagnosis, microRNAs are being explored as potential minimally invasive biomarkers. The aim of this study was to evaluate circulating microRNA (miRNA) expression profiles and assess their value in predicting the development of early-onset CAD. METHODS AND RESULTS: A total of 108 patients with early- and late-onset CAD and 29 individuals without CAD were included, and their miRNA expression was evaluated. The diagnostic value of differentially expressed miRNAs across the subgroups was tested by logistic regression models and ROC curve analysis. A total of 287 different circulating miRNAs were analysed following sequencing and preprocessing. Seven miRNAs (miR-10b-5p, miR-29c-3p, miR-142-5p, miR-320b, miR-451a, miR-486-3p, and miR-625-3p) were found to be differentially expressed across all the study groups, four of which (miR-142-5p, miR-29c-3p, miR-451a, and miR-486-3p) were significantly downregulated in the late-onset CAD group compared with the control group. ROC analysis demonstrated that the combination of the seven miRNAs had high diagnostic accuracy, with an AUC of 0.9924 for distinguishing late-onset CAD from the other groups, and moderate accuracy, with an AUC of 0.8235 for distinguishing early-onset CAD from the other groups. CONCLUSIONS: A combination of seven circulating miRNAs (miR-10b-5p, miR-29c-3p, miR-142-5p, miR-320b, miR-451a, miR-486-3p, and miR-625-3p) is a promising biomarker panel for CAD diagnosis, distinguishing between early-onset and late-onset disease. While the panel demonstrated high accuracy in classifying late-onset CAD, its ability to predict early-onset CAD requires further validation. Larger, independent populations are needed to validate the predictive ability of the panel for early disease detection, confirm these findings, and improve generalizability.

Despite striking successes in identifying novel biomarkers for improved patient stratification and predicting disease progression, numerous challenges remain in the effective integration and exploitation of multiomic data in biomedical applications beyond cancer, for which most bioinformatics strategies are developed and validated. That focus on cancer severely limits the effective development and advancement of algorithms in machine learning and artificial intelligence that do not suffer degraded out-of-domain performance. Generalizability and interpretability of models, however, are also required for robust insights that may translate into clinical practice. Work across different independent datasets is critical for establishing models robust towards unwanted variation in assays, protocols, and cohort populations. Disease-specific context like ethnicity, socioeconomic background, sex, lifestyle, disease phase, and tissue type also strongly affect molecular profiles. We here discuss atherosclerotic cardiovascular disease (ASCVD) as a high-impact non-cancer use case for the challenges remaining in the development and application of the latest bioinformatics approaches to multiomics data integration. ASCVD remains the leading cause of death globally. Disease aetiology, progression, and therapy outcome depend on a complex interplay of genetic, environmental, and lifestyle factors. Integrating these diverse data types effectively remains a challenge but holds transformative potential for personalized medicine. Discovery and access to data of sufficient diversity and extent form key bottlenecks. We here compile a first comprehensive overview of key data sets in ASCVD to complement the established cancer-focused resources as a foundation for future effective development and application of state-of-the-art bioinformatics tools for multiomic data integration.

Background Cigarette smoking is an established risk factor for coronary artery disease (CAD) and myocardial infarction. Genetic variants in the extracellular matrix protease ADAMTS-7 were also identified to increase CAD risk. Notably, ADAMTS7 represents the only genomic locus that revealed a gene-environment interaction with smoking. The underlying mechanisms of this interaction remain unclear. Methods and Results In a murine model, cigarette smoke exposure (CSE) led to an upregulation of vascular ADAMTS7 expression in wild type (WT) C57BL/6J mice. ADAMTS7 upregulation was also found in carotid plaques from ever-smokers undergoing carotid endarterectomy in humans. Bulk RNA sequencing of lung tissues from WT mice exposed to CS revealed a downregulation of 20 and an upregulation of 173 transcripts. Among upregulated transcripts in smoking-exposed lungs, we found C-C motif chemokine ligand 17 (CCL17), which was likewise upregulated in plasma from smoking mice and humans. In vitro , recombinant CCL17 upregulated ADAMTS7 expression in primary vascular smooth muscle cells (VSMC), which was inhibited secondary to silencing of CCL17’s bona fide receptor C-C Motif Chemokine Receptor 4 (CCR4). Conditioned media from CCL17-stimulated VSMC lacking ADAMTS-7 showed reduced release of inflammatory cytokines by endothelial cells (EC), reduced EC activation, and monocyte-to-EC adhesion. In proatherogenic Apoe -/- mice exposed to CS, more numerous neutrophils, inflammatory monocytes, and macrophages were found in atherosclerotic plaques as compared to room air exposition. This effect was blunted in Apoe -/- Adamts7 -/- mice. Conclusions For the first time, our findings link CSE to vascular inflammation via CCL17-mediated upregulation of the CAD risk factor ADAMTS7 and provide a mechanistic explanation for the gene-environment interaction between CS and ADAMTS7 in CAD. Targeting ADAMTS-7 might be a promising therapeutic strategy irrespective of smoking status. ![Figure][1] ### Competing Interest Statement T.K. received personal fees from Abbott, Astra-Zeneca, Bristol-Myers Squibb, Recor Medical, Shockwave Medical, and Translumina which are unrelated to this work. H.S. has received personal fees from MSD SHARP & DOHME, AMGEN, Bayer Vital GmbH, Boehringer Ingelheim, Daiichi-Sankyo, Novartis, Servier, Brahms, Bristol-Myers-Squibb, Medtronic, Sanofi Aventis, Synlab, Pfizer, and Vifor T as well as grants and personal fees from Astra-Zeneca which are unrelated to this work. H.S. and T.K. are named inventors on a patent application for prevention of restenosis after angioplasty and stent implantation which is unrelated to the submitted work. The other authors have nothing to disclose. [1]: pending:yes

Background: There is a lack of fast, reliable and non-invasive methods for distinguishing between bacterial and viral infections in modern clinical practice. It negatively impacts the effectiveness of treatment and increases the risk of unnecessary antibiotic administration and thus antibiotic resistance spread. Using microRNA biomarkers in urine may become the solution to the problems listed. miRNAs in urine are relatively stable and can provide an indirect yet specific insight into systemic infections, thus offering a promising diagnostic tool. Combining urine microRNA analysis with blood transcriptomics allows to explore systemic changes that are not limited to a single biological fluid, improving reliability by cross-verifying findings. Methods: In this pilot study, the analysis of urine microRNA and blood full transcriptome sequencing data was carried out in children with bacterial (n = 7), viral infections (n = 7) and controls (n = 8) with the goal of determining microRNA diagnostic signatures that distinguish between the said infections, and connecting differentially expressed urine microRNA with differentially expressed transcripts in blood. Using LASSO regularised regression and ANOVA statistical analysis, microRNA biomarker candidates were prioritised and miRNA:mRNA high-likelihood interactions were analysed using correlation analysis and target prediction to further explore systemic changes in response to infection. The differential expression analysis revealed unique features and common patterns in microRNA expression in infections with bacterial or viral etiology. Results: The resultant five microRNAs chosen by both feature selection methods have shown the ability to cluster bacterial infections patients, viral infections and controls. Subsequent correlation analysis and target prediction revealed the role of microRNA regulation in various immune processes such as the interaction of cytokine and cytokine receptors, as well as the regulation of T-cell activation. Conclusions: Our study suggests that prioritised urine microRNA biomarkers have a strong potential for implementation in clinical diagnostics. This could enable a targeted and timely treatment, potentially reducing the risk of spread of antibiotic resistance. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by funding from Riga Stradins University (project name "Identification of bacterial vs viral infection biomarkers in children with fever by transcriptome analysis in urine"). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the Ethics Committee of Riga Stradins University (Nr.6-2/4/ 2, dated 25.04.2019) and was carried out in accordance with the Declaration of Helsinki. All legal guardians of the recruited subjects gave their written informed consent to participate. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The gene expression datasets used and analysed during the current study is available in Gene Expression Omnibus under accession numbers GSE290693 and GSE290432 as well as in Riga Stradins University Dataverse from https://doi.org/10.48510/FK2/GZBT9C. The code used to generate and analyze the data is available on GitHub, DOI: 10.5281/zenodo.14845445

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative's FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present recommendations with commentary that reflects our discussions and justifies our choices and adaptations. These are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guidelines for adoption and fodder for discussion. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community.

Inborn errors of immunity (IEI), a diverse group of rare inborn disorders involving over 500 genes, pose diagnostic challenges despite next-generation sequencing advancements. Accurate molecular diagnosis is crucial for personalized treatment. This study aimed to assess the complementary role of genome and transcriptome sequencing in improving diagnostic yield for inborn errors of immunity. A cohort of 37 suspected IEI cases mainly consisting of predominantly primarily antibody deficiency (PAD) (27/37) underwent genome and transcriptome sequencing. We validated transcriptome sequencing analysis using positive controls and showed limitations of current methods. Among the 37 IEI cases, genetic etiology was identified in 14% (5/37). Genome and transcriptome sequencing prompted diagnostic changes in three initially diagnosed common variable immunodeficiency (CVID)/PAD cases, including showing RAS-associated autoimmune leukoproliferative disorder presenting as a novel CVID mimic disorder. The spectrum of identified pathogenic variants included STAT1, ADA2, SH2D1A, NRAS, and NR2F1. A complex structural variant in SH2D1A was characterized, demonstrating the significance of transcriptome sequencing in clarifying the genomic findings. While genome and transcriptome sequencing provided critical insights and allowed to provide correct diagnosis for at least 14% of the patients, the overall improvement in diagnostic yield over exome sequencing is limited. Transcriptome sequencing proved efficient in variant effect interpretation. Our findings underscore the evolving landscape of primary immunodeficiency genetics, necessitating ongoing exploration for novel genes and atypical phenotypes. The integration of genome and transcriptome sequencing holds promise but requires further refinement to enhance the diagnostic yield.

Computational workflows represent major investments of effort and expertise. As first-class, publishable research objects of their own, they are key to sharing methodological know-how for reuse, reproducibility, and transparency. Thus, the application of the FAIR Principles to workflows is inevitable to enable them to be Findable, Accessible, Interoperable, and Reusable. Making workflows FAIR reduces duplication of effort, assists in the reuse of best practice approaches and community-supported standards, and ensures that workflows as digital objects can support reproducible, robust science. FAIR workflows draw from both FAIR data and software principles, and they help ensure and support data FAIRification. The FAIR Principles emphasize the association of persistent identifiers and machine-actionable metadata with workflows. Implementing the Principles requires a framework with appropriate programmatic protocols and an accompanying ecosystem of services, tools, policies, and best practices, as well the buy-in of existing workflow systems. The European EOSC-Life Workflow Collaboratory is an example of such a digital infrastructure for the Biosciences. It includes a metadata standards framework for describing workflows that is managed and used by dedicated new FAIR workflow services and programmatic APIs for interoperability and metadata access. It includes the WorkflowHub registry and LifeMonitor workflow testing service, and it incorporates existing workflow systems and packaging solutions. Here, we introduce the FAIR Principles for workflows and connect FAIR workflows with the FAIR ecosystems they inhabit with the EOSC-Life Collaboratory as a concrete example. We also introduce other community efforts that are easing the ways that workflows are shared and reused by others, and we discuss how the variations in different workflow settings impact their FAIR perspectives.

Coronary Artery Diseases (CAD) contribute significantly to the global morbidity and mortality. While genome-wide association studies have identified numerous nuclear genomic variants linked to CAD, these account for less than 20 % of the disease’s estimated heritability (variation in disease risk attributed to genetic factors), suggesting the potential contribution of non-nuclear genetic elements, such as mitochondrial single-nucleotide variants (MT-SNVs). MT-SNVs may also influence lifestyle-related traits, which often interact with genetic predisposition to modulate CAD risk.Hypothesis: MT-SNVs contribute to the unexplained heritability of CAD and may also be associated with lifestyle behaviours. Methods We analysed 203 high-quality common and low-frequency MT-SNVs (minor allele frequency > 0.01) in 20,400 CAD cases (myocardial infarction and/or revascularisation) from the UK Biobank after rigorous quality control and imputation. Associations between MT-SNVs and 85 quantitative food intake traits (FIQTs) and 23 established CAD risk factors (e.g., smoking status, lipid levels, physical activity) using both Frequentist and Bayesian methods. Correlation analyses were performed across these 108 lifestyle behaviours. Results Several MT-SNVs were nominally associated with the CAD status and lifestyle habits, including m.10873T > C (MT-ND4 gene), m.15301G > A (MT-CYB gene), m.8701A > G (MT-ATP6 gene), and m.9540T > C (MT-CO3). After adjusting for covariates, these associations did not remain statistically significant. CAD status was significantly but weakly correlated (|r| < 0.2) with 64 dietary preferences of the 108 lifestyle traits (Bonferroni-adjusted P < 0.05), indicating modest but widespread dietary pattern differences. Conclusions Our findings suggest that MT-SNVs may explain some of the CAD heritability. However, larger cohorts with more comprehensive mitochondrial data are needed to clarify their potential role.

Osteopenia and osteoporosis are common long-term complications of the cytotoxic conditioning regimen for hematopoietic stem cell transplantation (HSCT). We examined mesenchymal stem and progenitor cells (MSPCs) that include skeletal progenitors from mice undergoing HSCT. Such MSPCs showed reduced CFU-F frequency, increased DNA damage and enhanced occurrence of cellular senescence, while there was a reduced bone volume in animals that underwent HSCT. This reduced MSPC function correlated with elevated activation of the small RhoGTPAse Cdc42, disorganized F-actin distribution, mitochondrial abnormalities and impaired mitophagy in MSPCs. Changes and defects similar to those in mice were also observed in MSPCs from humans undergoing HSCT. A pharmacological treatment that attenuated the elevated activation of CDC42 restored F-actin fiber alignment, mitochondrial function, and mitophagy in MSPCs in vitro. Finally, targeting CDC42 activity in vivo in animals undergoing transplants improved MSPC quality to increase both bone volume and trabecular bone thickness. Our study shows that attenuation of CDC42 activity is sufficient to attenuate reduced function of MSPCs in a BM transplant setting.

Background The intricate molecular pathways and genetic factors that underlie the pathophysiology of cervical insufficiency (CI) remain largely unknown and understudied. Methods We sequenced exomes from 114 patients in Latvia and Lithuania, diagnosed with a short cervix, CI, or a history of CI in previous pregnancies. To probe the well-known link between CI and connective tissue dysfunction, we introduced a connective tissue dysfunction assessment questionnaire, incorporating Beighton and Brighton scores. The phenotypic data obtained from the questionnaire was correlated with the number of rare damaging variants identified in genes associated with connective tissue disorders (in silico NGS panel). SKAT, SKAT-O, and burden tests were performed to identify genes associated with CI without a priori hypotheses. Pathway enrichment analysis was conducted using both targeted and genome-wide approaches. Results No patient could be assigned monogenic connective tissue disorder neither genetically, neither clinically upon clinical geneticist evaluation. Expanding our exploration to a genome-wide perspective, pathway enrichment analysis replicated the significance of extracellular matrix-related pathways as important contributors to CI’s development. A genome-wide burden analysis unveiled a statistically significant prevalence of rare damaging variants in genes and pathways associated with steroids (p-adj = 5.37E-06). Rare damaging variants, absent in controls (internal database, n = 588), in the progesterone receptor (PGR) (six patients) and glucocorticoid receptor (NR3C1) (two patients) genes were identified within key functional domains, potentially disrupting the receptors’ affinity for DNA or ligands. Conclusion Cervical insufficiency in non-syndromic patients is not attributed to a single connective tissue gene variant in a Mendelian fashion but rather to the cumulative effect of multiple inherited gene variants highlighting the significance of the connective tissue pathway in the multifactorial nature of CI. PGR or NR3C1 variants may contribute to the pathophysiology of CI and/or preterm birth through the impaired progesterone action pathways, opening new perspectives for targeted interventions and enhanced clinical management strategies of this condition.

Abstract Background Up to 10% of atrial fibrillation (Afib) patients develop the condition in the young age and in the absence of any related risk factors. Recent publications emphasized the importance of genetic testing in this population. However, the yield of the investigation is highly variable and ranges from 1 to 24% precents. Purpose The purpose of this study is to evaluate the prevalence of causative genetic variants in young Afib patients without risk factors and evaluate any structural changes of the heart. Methods We performed whole exome sequencing in 54 young (age of Afib onset less than 65 years) Afib patients without any Afib related risk factors (original cohort). Using ACMG guidelines we performed analysis of 349 previously described cardiomyopathy and arrhythmia associated genes. If a pathogenic (P) or likely pathogenic (LP) variant was found, a cardiac magnetic resonance imaging (CMR) was performed to exclude any structural abnormalities of the heart. We also extracted 107 young Afib patients without any risk factors from UK Biobank (UK Biobank cohort) and performed analysis of the same genes in the subgroup. Results The prevalence of P and LP variants was 24% (13 cases) in the original cohort and 8% (9 cases) in the UK Biobank cohort (p=0.006). We observed variants in cardiac structural and developmental genes only in both cohorts (Table 1 and 2). In the original cohort there were nine (17%) patients with P and LP variant in TTN gene. Moreover, five patients were positive for the same TTN variant NM_001267550.2:c.13696C>T p.(Gln4566Ter). In six (46%) original cohort patients we observed structural changes of the heart on CMR – in five patients there was dilation of one or both ventricles and in one there was increased T1 mapping intensity of septal wall segments. Conclusions 1. There is a high prevalence of pathogenic and likely pathogenic causative genetic variants in young atrial fibrillation patients without any risk factors. 2. All variants are localized in cardiac structural or developmental genes only. 3. There is a high grade of structural changes of the heart observed on cardiac magnetic resonance imaging in patients with monogenic atrial fibrillation.Table 1.WES data in original cohortTable 2.WES data in UK Biobank cohort

Remodeling of the bone marrow microenvironment in chronic inflammation and in aging reduces hematopoietic stem cell (HSC) function. To assess the mechanisms of this functional decline of HSC and find strategies to counteract it, we established a model in which the Sfrp1 gene was deleted in Osterix+ osteolineage cells (OS1Δ/Δ mice). HSC from these mice showed severely diminished repopulating activity with associated DNA damage, enriched expression of the reactive oxygen species pathway and reduced single-cell proliferation. Interestingly, not only was the protein level of Catenin beta-1 (bcatenin) elevated, but so was its association with the phosphorylated co-activator p300 in the nucleus. Since these two proteins play a key role in promotion of differentiation and senescence, we inhibited in vivo phosphorylation of p300 through PP2A-PR72/130 by administration of IQ-1 in OS1Δ/Δ mice. This treatment not only reduced the b-catenin/phosphop300 association, but also decreased nuclear p300. More importantly, in vivo IQ-1 treatment fully restored HSC repopulating activity of the OS1Δ/Δ mice. Our findings show that the osteoprogenitor Sfrp1 is essential for maintaining HSC function. Furthermore, pharmacological downregulation of the nuclear b-catenin/phospho-p300 association is a new strategy to restore poor HSC function.

Some studies have found increased coronavirus disease-19 (COVID-19)-related morbidity and mortality in patients with primary antibody deficiencies. Immunization against COVID-19 may, therefore, be particularly important in these patients. However, the durability of the immune response remains unclear in such patients. In this study, we evaluated the cellular and humoral response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens in a cross-sectional study of 32 patients with primary antibody deficiency (n = 17 with common variable immunodeficiency (CVID) and n = 15 with selective IgA deficiency) and 15 healthy controls. Serological and cellular responses were determined using enzyme-linked immunosorbent assay and interferon-gamma release assays. The subsets of B and T lymphocytes were measured using flow cytometry. Of the 32 patients, 28 had completed the vaccination regimen with a median time after vaccination of 173 days (IQR = 142): 27 patients showed a positive spike-peptide-specific antibody response, and 26 patients showed a positive spike-peptide-specific T-cell response. The median level of antibody response in CVID patients (5.47 ratio (IQR = 4.08)) was lower compared to healthy controls (9.43 ratio (IQR = 2.13)). No difference in anti-spike T-cell response was found between the groups. The results of this study indicate that markers of the sustained SARS-CoV-2 spike-specific immune response are detectable several months after vaccination in patients with primary antibody deficiencies comparable to controls.

Solid cancers like pancreatic ductal adenocarcinoma (PDAC), a type of pancreatic cancer, frequently exploit nerves for rapid dissemination. This neural invasion (NI) is an independent prognostic factor in PDAC, but insufficiently modeled in genetically engineered mouse models (GEMM) of PDAC. Here, we systematically screened for human-like NI in Europe’s largest repository of GEMM of PDAC, comprising 295 different genotypes. This phenotype screen uncovered 2 GEMMs of PDAC with human-like NI, which are both characterized by pancreas-specific overexpression of transforming growth factor α (TGF-α) and conditional depletion of p53. Mechanistically, cancer-cell-derived TGF-α upregulated CCL2 secretion from sensory neurons, which induced hyperphosphorylation of the cytoskeletal protein paxillin via CCR4 on cancer cells. This activated the cancer migration machinery and filopodia formation toward neurons. Disrupting CCR4 or paxillin activity limited NI and dampened tumor size and tumor innervation. In human PDAC, phospho-paxillin and TGF-α–expression constituted strong prognostic factors. Therefore, we believe that the TGF-α-CCL2-CCR4-p-paxillin axis is a clinically actionable target for constraining NI and tumor progression in PDAC.