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Aims: Patients experiencing ischaemic heart failure with reduced ejection fraction (HFrEF) represent a diverse group. We hypothesize that machine learning clustering can help separate distinctive patient phenotypes, paving the way for personalized management., Methods and Results: A total of 8591 ischaemic HFrEF patients pooled from the EPHESUS and CAPRICORN trials (64 ± 12 years; 28% women) were included in this analysis. Clusters were identified using both clinical and biological variables. Association between clusters and the composite of (i) heart failure hospitalization or all-cause death, (ii) cardiovascular (CV) hospitalization or all-cause death, and (iii) major adverse CV events was assessed. The derived algorithm was applied in the COMMANDER-HF trial (n = 5022) for external validation. Five clinical distinctive clusters were identified: Cluster 1 (n = 2161) with the older patients, higher prevalence of atrial fibrillation and previous CV events; Cluster 2 (n = 1376) with the higher prevalence of older hypertensive women and smoking habit; Cluster 3 (n = 1157) with the higher prevalence of diabetes and peripheral artery disease; Cluster 4 (n = 2073) with relatively younger patients, mostly men and with the higher left ventricular ejection fraction; Cluster 5 (n = 1824) with the younger patients and lower CV events burden. Cluster membership was efficiently predicted by a random forest algorithm. Clusters were significantly associated with outcomes in derivation and validation datasets, with Cluster 1 having the highest risk, and Cluster 4 the lowest. Mineralocorticoid receptor antagonist benefit on CV hospitalization or all-cause death was magnified in clusters with the lowest risk of events (Clusters 2 and 4)., Conclusion: Clustering reveals distinct risk subgroups in the heterogeneous array of ischaemic HFrEF patients. This classification, accessible online, could enhance future outcome predictions for ischaemic HFrEF cases., (© 2024 The Author(s). European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims: Impaired left ventricular-arterial coupling (VAC) has been shown to correlate with worse prognosis in cardiac diseases and heart failure (HF). The extent of the relationship between VAC and circulating biomarkers associated with HF has been scarcely documented. We aimed to explore associations of VAC with proteins involved in HF pathophysiology within a large population-based cohort of middle-aged individuals., Methods and Results: In the forth visit of the STANISLAS family cohort, involving 1309 participants (mean age 48 ± 14 years; 48% male) from parent and children generations, we analysed the association of 32 HF-related proteins with non-invasively assessed VAC using pulse wave velocity (PWV)/global longitudinal strain (GLS) and arterial elastance (E a )/ventricular end-systolic elastance (E es ). Among the 32 tested proteins, fatty acid-binding protein adipocyte 4, interleukin-6, growth differentiation factor 15, matrix metalloproteinase (MMP)-1, and MMP-9 and adrenomedullin were positively associated with PWV/GLS whereas transforming growth factor beta receptor type 3, MMP-2 and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were negatively associated. In multivariable models, only MMP-2 and NT-proBNP were significantly and inversely associated with PWV/GLS in the whole population and in the parent generation. Higher levels of NT-proBNP were also negatively associated with E a /E es in the whole cohort but this association did not persist in the parent subgroup., Conclusion: Elevated MMP-2 and NT-proBNP levels correlate with better VAC (lower PWV/GLS), possibly indicating a compensatory cardiovascular response to regulate left ventricular pressure amidst cardiac remodelling and overload., (© 2024 The Author(s). European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: Identifying the biomarkers associated with new-onset glomerular filtration rate (GFR) decrease in an initially healthy population could offer a better understanding of kidney function decline and help improving patient management., Methods: Here we described the proteomic and transcriptomic footprints associated with new-onset kidney function decline in an initially healthy and well-characterized population with a 20-year follow-up. This study was based on 1087 individuals from the familial longitudinal Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux (STANISLAS) cohort who attended both visit 1 (from 1993 to 1995) and visit 4 (from 2011 to 2016). New-onset kidney function decline was approached both in quantitative (GFR slope for each individual) and qualitative (defined as a decrease in GFR of >15 ml/min/1.7 m 2 ) ways. We analysed associations of 445 proteins measured both at visit 1 and visit 4 using Olink Proseek ® panels and 119 765 genes expressions measured at visit 4 with GFR decline. Associations were assessed using multivariable models. The Bonferroni correction was applied., Results: We found several proteins (including PLC, placental growth factor (PGF), members of the tumour necrosis factor receptor superfamily), genes (including CCL18, SESN3 ), and a newly discovered miRNA-mRNA pair (MIR1205-DNAJC6) to be independently associated with new-onset kidney function decline. Complex network analysis highlighted both extracellular matrix and cardiovascular remodelling (since visit 1) as well as inflammation (at visit 4) as key features of early GFR decrease., Conclusions: These findings lay the foundation to further assess whether the proteins and genes herein identified may represent potential biomarkers or therapeutic targets to prevent renal function impairment., Competing Interests: The authors have nothing to disclose., (© The Author(s) 2024. Published by Oxford University Press on behalf of the ERA.)

Aims: High left ventricular filling pressure increases left atrial volume and causes myocardial fibrosis, which may decrease with spironolactone. We studied clinical and proteomic characteristics associated with left atrial volume indexed by body surface area (LAVi), and whether LAVi influences the response to spironolactone on biomarker expression and clinical variables., Methods and Results: In the HOMAGE trial, where people at risk of heart failure were randomized to spironolactone or control, we analysed 421 participants with available LAVi and 276 proteomic measurements (Olink) at baseline, month 1 and 9 (mean age 73 ± 6 years; women 26%; LAVi 32 ± 9 ml/m 2 ). Circulating proteins associated with LAVi were also assessed in asymptomatic individuals from a population-based cohort (STANISLAS; n = 1640; mean age 49 ± 14 years; women 51%; LAVi 23 ± 7 ml/m 2 ). In both studies, greater LAVi was significantly associated with greater left ventricular masses and volumes. In HOMAGE, after adjustment and correction for multiple testing, greater LAVi was associated with higher concentrations of matrix metallopeptidase-2 (MMP-2), insulin-like growth factor binding protein-2 (IGFBP-2) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) (false discovery rates [FDR] <0.05). These associations were externally replicated in STANISLAS (all FDR <0.05). Among these biomarkers, spironolactone decreased concentrations of MMP-2 and NT-proBNP, regardless of baseline LAVi (p interaction  > 0.10). Spironolactone also significantly reduced LAVi, improved left ventricular ejection fraction, lowered E/e', blood pressure and serum procollagen type I C-terminal propeptide (PICP) concentration, a collagen synthesis marker, regardless of baseline LAVi (p interaction  > 0.10)., Conclusion: In individuals without heart failure, LAVi was associated with MMP-2, IGFBP-2 and NT-proBNP. Spironolactone reduced these biomarker concentrations as well as LAVi and PICP, irrespective of left atrial size., (© 2024 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: The associations between childhood adiposity and adult increased carotid intima-media thickness (cIMT) have been well established, which might be corroborated by the association between adiposity in children and inflammation in adults. However, longitudinal data regarding biological pathways associated with childhood adiposity are lacking., Methods: The current study included participants from the STANISLAS cohort who had adiposity measurements at age 5-18 years [ N  = 519, mean (SD) age, 13.0 (2.9) years; 46.4% male], and who were measured with cIMT, vascular-related and metabolic-related proteins at a median follow-up of 19 ± 2 years. BMI, waist-to-height ratio and waist circumference were converted to age-specific and sex-specific z -scores., Results: A minority of children were overweight/obese (16.2% overweight-BMI z -score >1; 1.3% obesity- z -score >2). Higher BMI, waist-height ratio and waist circumference in children were significantly associated with greater adult cIMT in univariable analysis, although not after adjusting for C-reactive protein. These associations were more pronounced in those with consistently high adiposity status from childhood to middle adulthood. Participants with higher adiposity during childhood (BMI or waist-height ratio) had higher levels of insulin-like growth factor-binding protein-1, protein-2, matrix metalloproteinase-3, osteopontin, hemoglobin and C-reactive protein in adulthood. Network analysis showed that IL-6, insulin-like growth factor-1 and fibronectin were the key proteins associated with childhood adiposity., Conclusion: In a population-based cohort followed for 20 years, higher BMI or waist-to-height ratio in childhood was significantly associated with greater cIMT and enhanced levels of proteins reflective of inflammation, supporting the importance of inflammation as progressive atherosclerosis in childhood adiposity., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Machine learning is now an essential part of any biomedical study but its integration into real effective Learning Health Systems, including the whole process of Knowledge Discovery from Data (KDD), is not yet realised. We propose an original extension of the KDD process model that involves an inductive database. We designed for the first time a generic model of Inductive Clinical DataBase (ICDB) aimed at hosting both patient data and learned models. We report experiments conducted on patient data in the frame of a project dedicated to fight heart failure. The results show how the ICDB approach allows to identify biomarker combinations, specific and predictive of heart fibrosis phenotype, that put forward hypotheses relative to underlying mechanisms. Two main scenarios were considered, a local-to-global KDD scenario and a trans-cohort alignment scenario. This promising proof of concept enables us to draw the contours of a next-generation Knowledge Discovery Environment (KDE)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Inc.)

Patients with heart failure (HF) and coronary artery disease (CAD) have a high risk for cardiovascular (CV) events including HF hospitalization, stroke, myocardial infarction (MI) and sudden cardiac death (SCD). The present study evaluated associations of proteomic biomarkers with CV outcome in patients with CAD and HF with reduced ejection fraction (HFrEF), shortly after a worsening HF episode. We performed a case-control study within the COMMANDER HF international, double-blind, randomized placebo-controlled trial investigating the effects of the factor-Xa inhibitor rivaroxaban. Patients with the following first clinical events: HF hospitalization, SCD and the composite of MI or stroke were matched with corresponding controls for age, sex and study drug. Plasma concentrations of 276 proteins with known associations with CV and cardiometabolic mechanisms were analyzed. Results were corrected for multiple testing using false discovery rate (FDR). In 485 cases and 455 controls, 49 proteins were significantly associated with clinical events of which seven had an adjusted FDR < 0.001 (NT-proBNP, BNP, T-cell immunoglobulin and mucin domain containing 4 (TIMD4), fibroblast growth factor 23 (FGF-23), growth differentiation factor-15 (GDF-15), pulmonary surfactant-associated protein D (PSP-D) and Spondin-1 (SPON1)). No significant interactions were identified between the type of clinical event (MI/stroke, SCD or HFH) and specific biomarkers (all interaction FDR > 0.20). When adding the biomarkers significantly associated with the above outcome to a clinical model (including NT-proBNP), the C-index increase was 0.057 (0.033-0.082), p < 0.0001 and the net reclassification index was 54.9 (42.5 to 67.3), p < 0.0001. In patients with HFrEF and CAD following HF hospitalization, we found that NT-proBNP, BNP, TIMD4, FGF-23, GDF-15, PSP-D and SPON1, biomarkers broadly associated with inflammation and remodeling mechanistic pathways, were strong but indiscriminate predictors of a variety of individual CV events., (© 2022. The Author(s).)

Cereal crops are frequently affected by toxigenic Fusarium species, among which the most common and worrying in Europe are Fusarium graminearum and Fusarium culmorum . These species are the causal agents of grain contamination with type B trichothecene (TCTB) mycotoxins. To help reduce the use of synthetic fungicides while guaranteeing low mycotoxin levels, there is an urgent need to develop new, efficient and environmentally-friendly plant protection solutions. Previously, F. graminearum proteins that could serve as putative targets to block the fungal spread and toxin production were identified and a virtual screening undertaken. Here, two selected compounds, M1 and M2, predicted, respectively, as the top compounds acting on the trichodiene synthase, a key enzyme of TCTB biosynthesis, and the 24-sterol-C-methyltransferase, a protein involved in ergosterol biosynthesis, were submitted for biological tests. Corroborating in silico predictions, M1 was shown to significantly inhibit TCTB yield by a panel of strains. Results were less obvious with M2 that induced only a slight reduction in fungal biomass. To go further, seven M1 analogs were assessed, which allowed evidencing of the physicochemical properties crucial for the anti-mycotoxin activity. Altogether, our results provide the first evidence of the promising potential of computational approaches to discover new anti-mycotoxin solutions.

Background and Aims: Smoking may lead to premature ageing, but the impact on the cardiovascular system and circulating proteins needs further investigation. In the present study, we aim to understand the impact of smoking on heart and vessels and circulating biomarkers of multiple domains including cardiovascular damage, premature ageing and cancer-related pathways., Methods: The STANISLAS Cohort is a longitudinal familial cohort with detailed cardiovascular examination and biomarker assessment. This study included all the participants enrolled in the fourth visit of the STANISLAS Cohort for whom information on smoking habits was available (n = 1696). We assessed pulse wave velocity, intima-media thickness, echocardiographic parameters and a total of 460 proteins to study the association of circulating plasma proteins with smoking status (never vs. past vs. current smoking) while adjusting for potential confounders., Results: Current smokers were approximately 18 years younger but had higher left ventricular mass index (LVMi) and similar pulse wave velocity (PWV), carotid intima media thickness (cIMT), frequency of hypertension, diabetes and carotid plaques compared to the much older never smokers. After multivariate selection, 25 proteins were independently associated with current or past smoking. Current smoking was strongly associated with higher levels of EDIL-3, CCL11, TNFSF13B, KIT, and lower levels of IL-12B and PLTP (p < 0.0001) while past smoking was associated with FGF-21, CHIT1, and lower levels of CXCL10, IL1RL2 and RAGE (p < 0.01)., Conclusions: Current smoking is associated with signs of early onset of cardiovascular ageing and protein biomarkers that regulate inflammation, endothelial function, metabolism, oncological processes and apoptosis., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Objectives: This study sought to identify homogenous echocardiographic phenotypes in community-based cohorts and assess their association with outcomes., Background: Asymptomatic cardiac dysfunction leads to a high risk of long-term cardiovascular morbidity and mortality; however, better echocardiographic classification of asymptomatic individuals remains a challenge., Methods: Echocardiographic phenotypes were identified using K-means clustering in the first generation of the STANISLAS (Yearly non-invasive follow-up of Health status of Lorraine insured inhabitants) cohort (N = 827; mean age: 60 ± 5 years; men: 48%), and their associations with vascular function and circulating biomarkers were also assessed. These phenotypes were externally validated in the Malmö Preventive Project cohort (N = 1,394; mean age: 67 ± 6 years; men: 70%), and their associations with the composite of cardiovascular mortality (CVM) or heart failure hospitalization (HFH) were assessed as well., Results: Three echocardiographic phenotypes were identified as "mostly normal (MN)" (n = 334), "diastolic changes (D)" (n = 323), and "diastolic changes with structural remodeling (D/S)" (n = 170). The D and D/S phenotypes had similar ages, body mass indices, cardiovascular risk factors, vascular impairments, and diastolic function changes. The D phenotype consisted mainly of women and featured increased levels of inflammatory biomarkers, whereas the D/S phenotype, consisted predominantly of men, displayed the highest values of left ventricular mass, volume, and remodeling biomarkers. The phenotypes were predicted based on a simple algorithm including e', left ventricular mass and volume (e'VM algorithm). In the Malmö cohort, subgroups derived from e'VM algorithm were significantly associated with a higher risk of CVM and HFH (adjusted HR in the D phenotype = 1.87; 95% CI: 1.04 to 3.37; adjusted HR in the D/S phenotype = 3.02; 95% CI: 1.71 to 5.34)., Conclusions: Among asymptomatic, middle-aged individuals, echocardiographic data-driven classification based on the simple e'VM algorithm identified profiles with different long-term HF risk. (4th Visit at 17 Years of Cohort STANISLAS-Stanislas Ancillary Study ESCIF [STANISLASV4]; NCT01391442)., Competing Interests: Funding Support and Author Disclosures The STANISLAS Cohort visit 4 was sponsored by the Nancy CHRU and was funded in part by the Programme Hospitalier de Recherche Clinique Interrégional. Biomarker studies are co-funded by the French National Research Agency Fighting Heart Failure (ANR-15-RHU-0004) and FEDER Lorraine, and all French co-authors are supported by the French Programme d'investissements d'avenir project “Lorraine Université d’Excellence” GEENAGE (ANR-15-IDEX-04-LUE) programs, and the Contrat de Plan Etat Région Lorraine and FEDER IT2MP. The research leading to these results also received support from the European Union Commission’s Seventh Framework program under grant 305507 (Heart OMics in Aging). Support was also provided from the “EXPERT” ERA-CVD 2016 and MR-Focus (both grants managed by the French National Research Agency). Drs. Girerd, Rossignol, and Zannad are supported by the French National Research Agency Fighting Heart Failure (ANR-15-RHU-0004), the French PIA project Lorraine Université d’Excellence GEENAGE (ANR-15-IDEX-04-LUE) programs, and the Contrat de Plan Etat Région Lorraine and FEDER IT2MP. Dr Girerd is a consultant for Novartis, AstraZeneca, and Boehringer Ingelheim. Dr Rossignol has received grants and personal fees from AstraZeneca, Bayer, CVRx, Fresenius, and Novartis; and personal fees from Grunenthal, Servier, Stealth Peptides, Vifor Fresenius Medical Care Renal Pharma, Idorsia, NovoNordisk, Ablative Solutions, G3P, Corvidia, and Relypsa. Dr Zannad has received personal fees from Boehringer Ingelheim, Janssen, Novartis, Boston Scientific, Amgen, CVRx, AstraZeneca, Vifor Fresenius, Cardior, Cereno Pharmaceutical, Applied Therapeutics, Merck Sharpe and Dohme, Bayer, and Cellprothera outside the submitted work; and has received other support from CVCT and Cardiorenal, outside the submitted work. Dr Ferreira is a consultant for Boehringer Ingelheim. Dr Magnusson is supported by grants from the Medical Faculty of Lund University; Skane University Hospital; the Crafoord Foundation; the Ernhold Lundstroms Research Foundation; the Region Skane; the Hulda and Conrad Mossfelt Foundation; the Southwest Skanes Diabetes Foundation; the Kockska Foundation; the Research Funds of Region Skåne; the Swedish Heart and Lung Foundation; and the Wallenberg Center for Molecular Medicine, Lund University. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)