Abstract Background Evidence for persistent epigenetic changes in individuals who had a mild SARS-CoV-2 infection is limited, as most DNA methylation (DNAm) studies to date have focused on either the acute phase of infection or on the months following infection in severe cases requiring hospitalization. Methods and results Using the Infinium Human MethylationEPIC BeadChip, we investigated blood DNA methylation (DNAm) up to four months after SARS-CoV-2 infection in cases and controls from four population-based cohorts (NAKO, Lifelines, CON-VINCE, and TiKoCo; n = 675) within the framework of the ORCHESTRA Consortium. We observed DNAm changes at 16 differentially methylated positions (DMPs) and 21 differentially methylated regions (DMRs), with 89% of these DMPs/DMRs hypomethylated in cases compared to age- and sex-matched controls. Genes mapped to these CpGs were annotated with Gene Ontology terms and pathways related to immune responses to viral infection. eQTM analyses in whole blood from an independent cohort (KORA FF4 study) produced 49 significant CpG–transcript pairs, including IFI44L and GNA12. Despite inter-individual variability and cohort heterogeneity, our findings regarding four DMPs (IFI44L, MX1, DDX60, and RABGAP1L) and two DMRs (PARP9 and GNA12) replicate changes described both in the acute phase of infection and at long-term follow-up. Differential methylation at other novel loci may reflect the systemic nature of post-infection epigenetic changes. Conclusion Our findings suggest moderate but persistent epigenetic changes up to four months after SARS-CoV-2 infection in mild cases from population-based cohorts. These changes partially mirror those reported during the acute phase of both mild and severe COVID-19 and overlap with pathways dysregulated in autoimmune, metabolic and neurological disease. Future research should examine epigenetic changes associated with persisting symptoms in long COVID, investigate downstream effects of DNAm changes on other -omics, and consider longer follow-up periods to further elucidate the molecular mechanisms underlying SARS-CoV-2 induced epigenetic changes.

Structural brain alterations associated with depression and anxiety are subtle, heterogeneous, and difficult to characterize. We applied autoencoder-based normative modeling to contrastively learned structural MRI representations from two large population-based cohorts (German National Cohort, N ≈ 29,000; UK Biobank, N ≈ 25,000) to quantify individual deviations from normative brain structure across symptom dimensions of depression, anxiety, and, for contextualization, alcohol use.Deviation magnitude increased with symptom severity for depressive and anxiety symptoms and was most pronounced in individuals with high alcohol use. Directional analyses revealed shared deviation patterns for depression and anxiety that were largely distinct from alcohol-related deviations, and these patterns generalized across cohorts. These affective-symptom-related patterns implicated distributed regional brain-structural variation. Individual deviation profiles improved classification of symptomatic status beyond demographic covariates, with gains concentrated at higher symptom severity.Together, these findings indicate that affective symptoms are associated with reproducible, dimensional patterns of regional brain-structural deviation that extend beyond normative population variability, supporting transdiagnostic models of internalizing psychopathology.

BACKGROUND:Eosinopenia has been associated with adverse outcomes in community-acquired pneumonia (CAP). However, its relationship with hospital resource use remains unclear. RESEARCH QUESTION:What is the association between admission eosinophil counts and hospital resource use among adults with CAP? STUDY DESIGN AND METHODS:This prospective multicenter cohort study (Community-Acquired Pneumonia Network of Competence [CAPNETZ]; Identifier: 2024-07-11-CHV6) has enrolled patients ≥ 18 years of age with CAP in university hospitals in Germany since 2017. Associations between admission blood eosinophil counts and hospital resource use-ICU admission, mechanical ventilation, and length of stay-were assessed using multivariable regression models. The optimal eosinophil count threshold for stratifying patients by ICU admission and mechanical ventilation rates was identified, and outcomes were compared between patients above and below this threshold. RESULTS:Lower eosinophil counts at admission were associated with increased ICU admission (n = 1,639; P < .001), including among patients treated with systemic glucocorticoids (P = .002) and those not receiving glucocorticoids (P = .047). Lower eosinophil counts also were associated with higher rates of mechanical ventilation (P = .014) and longer hospital stays (P = .024). An eosinophil count threshold of 10 cells/μL was identified as the cutoff that best distinguished patients with higher vs lower risk of ICU admission and mechanical ventilation. Patients with eosinopenia (≤ 10 cells/μL) showed higher ICU admission rates (14.2% vs 8.5%; P < .001; adjusted OR, 1.78), increased mechanical ventilation rates (9.1% vs 5.2%; P = .003; adjusted OR, 1.82), and longer hospitalization (mean, 10.2 days vs 9.0 days; P = .013). INTERPRETATION:Our results show that admission eosinopenia (≤ 10 cells/μL) was associated with greater hospital resource use and may serve as a practical biomarker for health care resource planning. CLINICAL TRIAL REGISTRATION:German Clinical Trials Register; No.: DRKS00005274; URL: https://drks.de/.

Background:Clinical decision-making for patients with community-acquired pneumonia (CAP) at risk of organ dysfunction and death is currently guided by clinical evaluation and scores. Every fifth patient with CAP requires admission to the ICU, with a subsequent high mortality; delayed admission to the ICU increases this risk. Research Question:Can a transcriptomic signature improve identification of at-risk patients compared with conventional scores and metrics? Study Design and Methods:Time-course transcriptomic data were obtained from blood samples taken from 455 participants in 41 centers enrolled in the Progression of Community-Acquired Pneumonia in the Hospital (PROGRESS) trial, a prospective observational cohort study of hospitalized patients with CAP who did not initially require organ support. Discovery (n = 240) and validation (n = 215) cohorts were randomly assigned. Transcriptome data were analyzed for association with a severe CAP course, defined as a composite of requirement for ICU admission or 28-day mortality. Predictive performance of the gene expression profiles was compared against clinical scores and serum markers, and validated in publicly available transcriptomic data sets. Results:A 5-gene signature consisting of SIGLEC14, TNFSF14, YOD1, CLEC4A, and KLRB1 (STYCK) was identified and validated to predict clinical deterioration with subsequent ICU admission or 28-day mortality (AUCdiscovery, 0.82; 95% CI, 0.71-0.90; P = 0.00000065; AUCvalidation, 0.81; 95% CI, 0.70-0.90; P = 0.0000013). The signature outperformed clinical scores in predicting severe CAP and improved prediction when added to the Sequential Organ Failure Assessment score (AUCSOFA, 0.70 vs AUCSOFA+STYCK, 0.83; P = .0002). Prognostic value was confirmed in 6 of 17 publicly available sepsis cohorts, particularly those with low case fatality. Interpretation:We identified a 5-gene transcriptomic signature that, taken soon after hospital admission, was shown to predict disease course of hospitalized patients with CAP. STYCK was superior to conventional, currently used scores and clinical metrics in predicting this deterioration and improved, if added to the Sequential Organ Failure Assessment, its performance. Clinical Trial Registration:ClinicalTrials.gov; No.: NCT02782013; URL: www.clinicaltrials.gov.

Post COVID-19 condition (PCC) is a substantial burden for patients, society, and the healthcare system. Participants of the German National Cohort (NAKO) were asked in an online survey about their self-perceived health, symptoms related to PCC, and infection status. PCC was defined as reporting symptoms for the time window 4-12 months after infection. Of 110,375 respondents (73% response), 86,833 were included in this analysis. Of these, 44,451 (51%) did not report a SARS-CoV-2 infection (no infection), 26,726 (31%) reported an infection but no symptoms 4-12 months after infection (infection/no PCC), and 15,656 (18%) reported an infection and symptoms (PCC). The median number of current symptoms at the time of the survey was two for the "no infection" and the "infection/no PCC" group, and five for the "PCC" group. Participants with PCC had a substantially higher probability of having worse self-perceived health (OR 1.84, 95% CI [1.75; 1.93] compared to the "no infection" group, adjusting for sex, age, education and chronic diseases with elevated risk for developing PCC. After adjusting for the number of current symptoms related to PCC, this difference disappeared, suggesting that the symptoms collected explain the impairment of self-perceived health in the PCC group.

We applied deep normative modeling to structural MRI data from two large cohorts (German National Cohort, N ≈ 29,000 and UK Biobank, N ≈ 25,000) to characterize individual-level brain deviations along symptom dimensions of depression, anxiety, and alcohol use. Each brain was embedded into a 256-dimensional latent space, allowing us to quantify both the magnitude and direction of deviation from a normative reference trained on the non/low-symptomatic subpopulation. Deviation magnitude increased with symptom severity, and directional patterns separated mood-anxiety and alcohol-use tendencies. These deviation axes generalized across cohorts and supported individual-level classification of symptomatic group membership, especially at higher symptom levels. Combining deviations with polygenic risk scores improved classification performance, particularly for depressive and anxiety measures, indicating complementary contributions of imaging and genetics. Our findings demonstrate that structural brain deviations reflect meaningful, continuous variation in affective and behavioral symptoms. ### Competing Interest Statement HJG has received travel grants and speakers honoraria from Neuraxpharm, Servier, Indorsia and Janssen Cilag. ES received speaker fees from bfd buchholz-fachinformationsdienst GmbH, Lundbeckfonden, and Janssen-Cilag GmbH, as well as editorial fees from Lundbeckfonden and the Wellcome Trust. AML has received consultancy honoraria from AbbVie, Janssen-Cilag GmbH, Boehringer-Ingelheim, Daimler und Benz Stiftung, Helmut Horten Stiftung, Neurotorium/Lundbeckfonden, Hector Stiftung, Endosane Pharmaceuticals, Elsevier, von Behring-Roentgen-Stiftung, The LOOP Zuerich, ECNP, Teva, Medical Research Council/UKRI, Heinrich-Lanz-Stiftung, Johnson & Johnson, Lundbeckfonden, and the Wellcome Trust. He has receivedvlecture honoraria from pro Mente Akademie GmbH, Schoen Klinik, Janssen-Cilag, Evangelische Hochschule Ludwigsburg, Landesaerztekammer Baden-Wuerttemberg, Klinikum Ingolstadt, PSY (Psychiatrie und Psychotherapie Update Refresher, FOMF), Consorcio Mexicano de Neuropsico-farmacologia (MCNP), Universitaet Klagenfurt, and Universitaet Norwalk/USA. He has received editorial honoraria (as editor, etc.) from ECNP/Neuroscience Applied and JSPS. He has received authorship honoraria from Beltz Verlag, Thieme Verlag, and Kohlhammer Verlag. He has received project funding from BMBF, DFG, Hector Stiftung, Klaus Tschira Stiftung, and MWK. ### Funding Statement The project was conducted with data (NAKO-711) from the German National Cohort (NAKO) (http://www.nako.de/). The NAKO is funded by the Federal Ministry of Education and Research (BMBF) [project funding reference numbers: 01ER1301A/B/C, 01ER1511D, and 01ER1801A/B/C/D and 01ER2301A/B/C], federal states of Germany and the Helmholtz Association, the participating universities, and the institutes of the Leibniz Association. We thank all participants who took part in the NAKO study and the staff of this research initiative. We also thank the participants and scientists involved in making the UK Biobank resource available (http://www.ukbiobank.ac.uk/). This study was conducted under UK Biobank application number 162313. The project was supported by the DZPG (German Centre for Mental Health Research) and by the BMBF (German Ministry of Education and Research) grant 01EE2303E. Fabian Streit is supported by a 2023 NARSAD Young Investigator Grant (#31537) from the Brain & Behavior Research Foundation with support from the Families for Borderline Personality Disorder Research. This work was supported by the Hector foundation II and was endorsed by German Center for Mental Health (DZPG). ### 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: Ethics Committee II of Ruprecht-Karls-Universitaet Heidelberg (Medizinische Fakultaet Mannheim) gave ethical approval for this work 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 Access to and use of NAKO data and biosamples can be obtained via the electronic application portal (https://transfer.nako.de). Access to UK Biobank data requires application through the registration and application portal (http://ukbiobank.ac.uk/register-apply).

COVID-19 continuously causes severe disease conditions and significant mortality. We evaluate whether easily accessible biomarkers can improve risk prediction of severe disease outcomes. Our study analysed 426 COVID-19 patients collected by German CAPNETZ and PROGRESS study groups between 2020 and 2021. Troponin T high-sensitive (TnT-hs), procalcitonin (PCT), N-terminal pro brain natriuretic peptide, angiopoietin-2, copeptin, endothelin-1 (ET-1) and lipocalin-2 were measured at enrolment and related to 28d mortality/ICU admission endpoint. Logistic and relaxed LASSO regression were used to evaluate the added value of biomarkers compared to the CRB-65 score and to develop a combined risk prediction model for our endpoint. Of the 426 COVID-19 patients, 64 (15

Background Community-acquired pneumonia (CAP) remains a leading cause of infectious disease mortality globally, necessitating intensive care unit (ICU) admission for ∼10% of hospitalised patients. Accurate prediction of disease severity facilitates timely therapeutic interventions. Methods Our study aimed to enhance the predictive capacity of the clinical CRB-65 score by evaluating eight candidate biomarkers: troponin T high-sensitive (TnT-hs), procalcitonin (PCT), N-terminal pro-brain natriuretic peptide, angiopoietin-2, copeptin, endothelin-1, lipocalin-2 and mid-regional pro-adrenomedullin. We utilised a machine-learning approach on 800 samples from the German CAPNETZ network (competence network for CAP) to refine risk prediction models combining these biomarkers with the CRB-65 score regarding our defined end-point: death or ICU admission during the current CAP episode within 28 days after study inclusion. Results Elevated levels of biomarkers were associated with the end-point. TnT-hs exhibited the highest predictive performance among individual features (area under the receiver operating characteristic curve, AUC=0.74), followed closely by PCT (AUC=0.73). Combining biomarkers with the CRB-65 score significantly improved prediction accuracy. The combined model of CRB-65, TnT-hs and PCT demonstrated the best balance between high predictive value and parsimony, with an AUC of 0.77 (95% CI: 0.72–0.82), while CRB-65 alone achieved an AUC of 0.67 (95% CI: 0.64–0.73). Conclusion Our findings suggest that augmenting the CRB-65 score with TnT-hs and PCT enhances the prediction of death or ICU admission in hospitalised CAP patients. Validation of this improved risk score in additional CAP cohorts and prospective clinical studies is warranted to assess its broad clinical utility.

When infected with SARS-CoV-2, Syrian hamsters (Mesocricetus auratus) develop moderate disease severity presenting key features of human COVID-19. We here develop a biomathematical model of the disease course by translating known biological mechanisms of virus-host interactions and immune responses into ordinary differential equations. We explicitly describe the dynamics of virus population, affected alveolar epithelial cells, and involved relevant immune cells comprising for example CD4+ T cells, CD8+ T cells, macrophages, natural killer cells and B cells. We also describe the humoral response dynamics of neutralising antibodies and major regulatory cytokines including CCL8 and CXCL10. The model is developed and parametrized based on experimental data collected at days 2, 3, 5, and 14 post infection. Pulmonary cell composition and their transcriptional profiles were obtained by lung single-cell RNA (scRNA) sequencing analysis. Parametrization of the model resulted in a good agreement of model and data. The model can be used to predict, for example, the time course of the virus population, immune cell dynamics, antibody production and regeneration of alveolar cells for different therapy scenarios or after multiple-infection events. We aim to translate this model to the human situation in the future.

OBJECTIVES:The risk of Post-COVID-19 condition (PCC) under hybrid immunity remains unclear. METHODS:Using data from the German National Cohort (NAKO Gesundheitsstudie), we investigated risk factors for self-reported post-infection symptoms (any PCC is defined as having at least one symptom, and high symptom burden PCC as having nine or more symptoms). RESULTS:Sixty percent of 109,707 participants reported at least one previous SARS-CoV-2 infection; 35% reported having had any symptoms 4-12 months after infection; among them 23% reported nine or more symptoms. Individuals, who did not develop PCC after their first infection, had a strongly reduced risk for PCC after their second infection (50%) and a temporary risk reduction, which waned over 9 months after the preceding infection. The risk of developing PCC strongly depended on the virus variant. Within variants, there was no effect of the number of preceding vaccinations, apart from a strong protection by the fourth vaccination compared to three vaccinations for the Omicron variant (odds ratio = 0.52; 95% confidence interval 0.45-0.61). CONCLUSIONS:Previous infections without PCC and a fourth vaccination were associated with a lower risk of PCC after a new infection, indicating diminished risk under hybrid immunity. The two components of risk reduction after a preceding infection suggest different immunological mechanisms.

Abstract Introduction The COVID-19 pandemic had a huge impact on society and raised attention to the challenges related to infectious diseases. While a lot of research was initiated during the pandemic, the recruitment of participants in most instances started at the time point of infection. In contrast, the German National Cohort (NAKO Gesundheitsstudie) has the ability to study pre-existing risk factors. In order to obtain information about SARS-CoV-2 infections and the following sequelae a dedicated data collection was conducted. Methods An online survey was conducted in the NAKO between September 2022 and February 2023. Invitation via e-mail was followed by two reminders sent to all NAKO study participants who provided e-mail addresses. The questionnaire was implemented in LimeSurvey and included the following topics: current health status including mental health measurements, restrictions of health services during the pandemic, other collateral effects of the pandemic, reported infections with SARS-CoV-2 and symptoms of acute infection, 4-12 weeks, 12 or more weeks, and one year after infection as well as vaccination status. Results Of 150766 invited NAKO participants, 110362 responded to the second COVID-19 questionnaire. Respondents in 60% reported at least one SARS-CoV-2 infection, 59453 reported one, 6061 two, and 414 three or more infections. The time points of infections followed the general incidence in the German population and thus infections could be mapped to specific variants based on periods of dominance. Of those who reported an infection with SARS-CoV-2, 42% reported symptoms 4 to 12 weeks after infection (ongoing COVID-19), 35% reported symptoms 12 or more weeks after infection (Post-COVID-19), and 37% one year after infection. Conclusions Combined with existing biosamples and measurements prior to infection, NAKO offers an excellent opportunity to study risk factors for infection and post-infection syndromes.

Background: It remains unclear how preceding SARS-CoV-2 infections and vaccinations modify the risk of Post-COVID condition (PCC).Methods: Participants of the German National Cohort (NAKO Gesundheitsstudie) were invited to an online survey on SARS-CoV-2 infections, vaccinations, and symptoms. We investigated risk factors for self-reported post-infection symptoms (any PCC defined as having at least one out of 21 symptoms, and high symptom burden PCC defined as 9+ symptoms).Findings: Sixty percent of 109707 participants reported at least one previous SARS-CoV-2 infection; of infected observed at least 4 months, 35% reported having had any symptoms 4-12 months after infection; among them 23% reported 9+ symptoms. Individuals, who did not develop PCC after their first infection, had a strongly reduced risk for PCC after their second infection (about 50%). In addition, they had a temporary risk reduction, which waned over nine months after the preceding infection. Risk of developing PCC strongly depended on the virus variant. Within variants, there was no effect of the number of preceding vaccinations, apart from a strong protection by the fourth vaccination compared to three vaccinations preceding an infection with the Omicron variant (odds ratio=0·52; 95% confidence interval 0·45-0·61).Interpretation: Previous infections without PCC and a fourth vaccination were associated with a lower risk of PCC after a new infection, indicating diminished risk under hybrid immunity. The two components of risk reduction after a preceding infection suggest different immunological mechanisms.Funding: Federal Ministry of Education and Research, the Federal States, the Helmholtz Association, and the participating institutions. Declaration of Interest: We declare no competing interests. Ethical Approval: All participants provided written informed consent. The study was approved by the responsible ethic committees of the participating institutions.

Background: Community-acquired pneumonia (CAP) is an acute disease condition with a high risk of rapid deteriorations. We analysed the influence of genetics on cytokine regulation to obtain a better understanding of patient’s heterogeneity. Methods: For up to N = 389 genotyped participants of the PROGRESS study of hospitalised CAP patients, we performed a genome-wide association study of ten cytokines IL-1β, IL-6, IL-8, IL-10, IL-12, MCP-1 (MCAF), MIP-1α (CCL3), VEGF, VCAM-1, and ICAM-1. Consecutive secondary analyses were performed to identify independent hits and corresponding causal variants. Results: 102 SNPs from 14 loci showed genome-wide significant associations with five of the cytokines. The most interesting associations were found at 6p21.1 for VEGF (p = 1.58 × 10−20), at 17q21.32 (p = 1.51 × 10−9) and at 10p12.1 (p = 2.76 × 10−9) for IL-1β, at 10p13 for MIP-1α (CCL3) (p = 2.28 × 10−9), and at 9q34.12 for IL-10 (p = 4.52 × 10−8). Functionally plausible genes could be assigned to the majority of loci including genes involved in cytokine secretion, granulocyte function, and cilial kinetics. Conclusion: This is the first context-specific genetic association study of blood cytokine concentrations in CAP patients revealing numerous biologically plausible candidate genes. Two of the loci were also associated with atherosclerosis with probable common or consecutive pathomechanisms.

Traditional body measurement techniques are commonly used to assess physical health; however, these approaches do not fully represent the complex shape of the human body. Three-dimensional (3D) imaging systems capture rich point cloud data that provides a representation of the surface of 3D objects and have been shown to be a potential anthropometric tool for use within health applications. Previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of traditional body measures, such as lengths, widths and girths. Geometric morphometrics (GM) is an established framework used for the statistical analysis of biological shape variation. These methods quantify biological shape variation after the effects of non-shape variation–location, rotation and scale–have been mathematically held constant, otherwise known as the Procrustes paradigm. The aim of this study was to determine whether shape measures, identified using geometric morphometrics, can provide additional information about the complexity of human morphology and underlying mass distribution compared to traditional body measures. Scale-invariant features of torso shape were extracted from 3D imaging data of 9,209 participants form the LIFE-Adult study. Partial least squares regression (PLSR) models were created to determine the extent to which variations in human torso shape are explained by existing techniques. The results of this investigation suggest that linear combinations of body measures can explain 49.92% and 47.46% of the total variation in male and female body shape features, respectively. However, there are also significant amounts of variation in human morphology which cannot be identified by current methods. These results indicate that Geometric morphometric methods can identify measures of human body shape which provide complementary information about the human body. The aim of future studies will be to investigate the utility of these measures in clinical epidemiology and the assessment of health risk.

Atherosclerosis is one of the leading causes of death worldwide. Biomathematical modelling of the underlying disease and therapy processes might be a useful aid to develop and improve preventive and treatment concepts of atherosclerosis. We here propose a biomathematical model of murine atherosclerosis under different diet and treatment conditions including lipid modulating compound and antibiotics. The model is derived by translating known biological mechanisms into ordinary differential equations and by assuming appropriate response kinetics to the applied interventions. We explicitly describe the dynamics of relevant immune cells and lipid species in atherosclerotic lesions including the degree of blood vessel occlusion due to growing plaques. Unknown model parameters were determined by fitting the predictions of model simulations to time series data derived from mice experiments. Parameter fittings resulted in a good agreement of model and data for all 13 experimental scenarios considered. The model can be used to predict the outcome of alternative treatment schedules of combined antibiotic, immune modulating, and lipid lowering agents under high fat or normal diet. We conclude that we established a comprehensive biomathematical model of atherosclerosis in mice. We aim to validate the model on the basis of further experimental data.

Introduction Chronic lung disease, that is, bronchopulmonary dysplasia (BPD) is the most common complication in preterm infants and develops as a consequence of the misguided formation of the gas-exchange area undergoing prenatal and postnatal injury. Subsequent vascular disease and its progression into pulmonary arterial hypertension critically determines long-term outcome in the BPD infant but lacks identification of early, disease-defining changes. Methods We link impaired bone morphogenetic protein (BMP) signalling to the earliest onset of vascular pathology in the human preterm lung and delineate the specific effects of the most prevalent prenatal and postnatal clinical risk factors for lung injury mimicking clinically relevant conditions in a multilayered animal model using wild-type and transgenic neonatal mice. Results We demonstrate (1) the significant reduction in BMP receptor 2 (BMPR2) expression at the onset of vascular pathology in the lung of preterm infants, later mirrored by reduced plasma BMP protein levels in infants with developing BPD, (2) the rapid impairment (and persistent change) of BMPR2 signalling on postnatal exposure to hyperoxia and mechanical ventilation, aggravated by prenatal cigarette smoke in a preclinical mouse model and (3) a link to defective alveolar septation and matrix remodelling through platelet derived growth factor-receptor alpha deficiency. In a treatment approach, we partially reversed vascular pathology by BMPR2-targeted treatment with FK506 in vitro and in vivo. Conclusion We identified impaired BMP signalling as a hallmark of early vascular disease in the injured neonatal lung while outlining its promising potential as a future biomarker or therapeutic target in this growing, high-risk patient population.