Aims/hypothesis Adult pancreatic islets contain multiple cell types that produce and secrete well characterised hormones, including insulin, glucagon and somatostatin. Although it is increasingly apparent that islets release and respond to more secreted factors than previously thought, systematic analyses are lacking. We therefore sought to identify potential autocrine and/or paracrine islet growth factor loops, and to characterise the function of the netrin family of islet-secreted factors and their receptors, which have been previously unreported in adult islets. Methods Gene expression databases, islet-specific tag sequencing libraries and microarray datasets of FACS purified beta cells were used to compile a list of secreted factors and receptors present in mouse or human islets. Netrins and their receptors were further assessed using RT-PCR, Western blot analysis and immunofluorescence staining. The roles of netrin-1 and netrin-4 in beta cell function, apoptosis and proliferation were also examined. Results We identified 233 secreted factors and 234 secreted factor receptors in islets. The presence of netrins and their receptors was further confirmed. Downregulation of caspase-3 activation was observed when MIN6 cells were exposed to exogenous netrin-1 and netrin-4 under hyperglycaemic conditions. Reduction in caspase-3 cleavage was linked to the decrease in dependence receptors, neogenin and unc-5 homologue A, as well as the activation of Akt and extracellular signal-regulated protein kinase (ERK) signalling. Conclusions/interpretation Our results highlight the large number of potential islet growth factors and point to a context-dependent pro-survival role for netrins in adult beta cells. Since diabetes results from a deficiency in functional beta cell mass, these studies are important steps towards developing novel therapies to improve beta cell survival.

Identification of the four standard modifiable cardiovascular risk factors (SMuRFs)-diabetes mellitus, hyperlipidaemia, hypertension, and cigarette smoking-has allowed the development of risk scores. These have been used in conjunction with primary and secondary prevention strategies targeting SMuRFs to reduce the burden of CAD. Recent studies show that up to 25% of ACS patients do not have any SMuRFs. Thus, SMuRFs do not explain the entire burden of CAD. There appears to be variation at the individual level rendering some individuals relatively susceptible or resilient to developing atherosclerosis. Important disease pathways remain to be discovered, and there is renewed enthusiasm to discover novel biomarkers, biological mechanisms, and therapeutic targets for atherosclerosis. Two broad approaches are being taken: traditional approaches investigating known candidate pathways and unbiased omics approaches. We review recent progress in the field and discuss opportunities made possible by technological and data science advances. Developments in network analytics and machine learning algorithms used in conjunction with large-scale multi-omic platforms have the potential to uncover biological networks that may not have been identifiable using traditional approaches. These approaches are useful for both biomedical research and precision medicine strategies.

IntroductionCoronary artery disease (CAD) persists as a major cause of morbidity and mortality worldwide despite intensive identification and treatment of traditional risk factors. Data emerging over the past decade show a quarter of patients have disease in the absence of any known risk factor, and half have only one risk factor. Improvements in quantification and characterisation of coronary atherosclerosis by CT coronary angiography (CTCA) can provide quantitative measures of subclinical atherosclerosis—enhancing the power of unbiased ‘omics’ studies to unravel the missing biology of personal susceptibility, identify new biomarkers for early diagnosis and to suggest new targeted therapeutics.Methods and analysisBioHEART-CT is a longitudinal, prospective cohort study, aiming to recruit 5000 adult patients undergoing clinically indicated CTCA. After informed consent, patient data, blood samples and CTCA imaging data are recorded. Follow-up for all patients is conducted 1 month after recruitment, and then annually for the life of the study. CTCA data provide volumetric quantification of total calcified and non-calcified plaque, which will be assessed using established and novel scoring systems. Comprehensive molecular phenotyping will be performed using state-of-the-art genomics, metabolomics, proteomics and immunophenotyping. Complex network and machine learning approaches will be applied to biological and clinical datasets to identify novel pathophysiological pathways and to prioritise new biomarkers. Discovery analysis will be performed in the first 1000 patients of BioHEART-CT, with validation analysis in the following 4000 patients. Outcome data will be used to build improved risk models for CAD.Ethics and disseminationThe study protocol has been approved by the human research ethics committee of North Shore Local Health District in Sydney, Australia. All findings will be published in peer-reviewed journals or at scientific conferences.Trial registration numberACTRN12618001322224.

CD45 is a leukocyte-specific protein tyrosine phosphatase and an important regulator of AgR signaling in lymphocytes. However, its function in other leukocytes is not well-understood. In this study, we examine the function of CD45 in dendritic cells (DCs). Analysis of DCs from CD45-positive and CD45-null mice revealed that CD45 is not required for the development of DCs but does influence DC maturation induced by TLR agonists. CD45 affected the phosphorylation state of Lyn, Hck, and Fyn in bone marrow-derived DCs and dysregulated LPS-induced Lyn activation. CD45 affected TLR4-induced proinflammatory cytokine and IFN-β secretion and TLR4-activated CD45-null DCs had a reduced ability to activate NK and Th1 cells to produce IFN-γ. Interestingly, the effect of CD45 on TLR-induced cytokine secretion depended on the TLR activated. Analysis of CD45-negative DCs indicated a negative effect of CD45 on TLR2 and 9, MyD88-dependent cytokine production, and a positive effect on TLR3 and 4, MyD88-independent IFN-β secretion. This indicates a new role for CD45 in regulating TLR-induced responses in DCs and implicates CD45 in a wider regulatory role in innate and adaptive immunity.

Liquid chromatography-mass spectrometry-based metabolomics studies are increasingly applied to large population cohorts, which run for several weeks or even years in data acquisition. This inevitably introduces unwanted intra- and inter-batch variations over time that can overshadow true biological signals and thus hinder potential biological discoveries. To date, normalisation approaches have struggled to mitigate the variability introduced by technical factors whilst preserving biological variance, especially for protracted acquisitions. Here, we propose a study design framework with an arrangement for embedding biological sample replicates to quantify variance within and between batches and a workflow that uses these replicates to remove unwanted variation in a hierarchical manner (hRUV). We use this design to produce a dataset of more than 1000 human plasma samples run over an extended period of time. We demonstrate significant improvement of hRUV over existing methods in preserving biological signals whilst removing unwanted variation for large scale metabolomics studies. Our tools not only provide a strategy for large scale data normalisation, but also provides guidance on the design strategy for large omics studies.

Despite effective prevention programs targeting cardiovascular risk factors, coronary artery disease (CAD) remains the leading cause of death. Novel biomarkers are needed for improved risk stratification and primary prevention. To assess for independent associations between plasma metabolites and specific CAD plaque phenotypes we performed liquid chromatography mass-spectrometry on plasma from 1002 patients in the BioHEART-CT study. Four metabolites were examined as candidate biomarkers. Dimethylguanidino valerate (DMGV) was associated with presence and amount of CAD (OR) 1.41 (95% Confidence Interval [CI] 1.12–1.79, p = 0.004), calcified plaque, and obstructive CAD (p < 0.05 for both). The association with amount of plaque remained after adjustment for traditional risk factors, ß-coefficient 0.17 (95% CI 0.02–0.32, p = 0.026). Glutamate was associated with the presence of non-calcified plaque, OR 1.48 (95% CI 1.09–2.01, p = 0.011). Phenylalanine was associated with amount of CAD, ß-coefficient 0.33 (95% CI 0.04–0.62, p = 0.025), amount of calcified plaque, (ß-coefficient 0.88, 95% CI 0.23–1.53, p = 0.008), and obstructive CAD, OR 1.84 (95% CI 1.01–3.31, p = 0.046). Trimethylamine N-oxide was negatively associated non-calcified plaque OR 0.72 (95% CI 0.53–0.97, p = 0.029) and the association remained when adjusted for traditional risk factors. In targeted metabolomic analyses including 53 known metabolites and controlling for a 5% false discovery rate, DMGV was strongly associated with the presence of calcified plaque, OR 1.59 (95% CI 1.26–2.01, p = 0.006), obstructive CAD, OR 2.33 (95% CI 1.59–3.43, p = 0.0009), and amount of CAD, ß-coefficient 0.3 (95% CI 0.14–0.45, p = 0.014). In multivariate analyses the lipid and nucleotide metabolic pathways were both associated with the presence of CAD, after adjustment for traditional risk factors. We report novel associations between CAD plaque phenotypes and four metabolites previously associated with CAD. We also identified two metabolic pathways strongly associated with CAD, independent of traditional risk factors. These pathways warrant further investigation at both a biomarker and mechanistic level.

Coronary artery disease remains the leading cause of death globally and is a major burden to every health system in the world. There have been significant improvements in risk modification, treatments, and mortality; however, our ability to detect asymptomatic disease for early intervention remains limited. Recent discoveries regarding the inflammatory nature of atherosclerosis have prompted investigation into new methods of diagnosis and treatment of coronary artery disease. This article reviews some of the highlights of the important developments in cardioimmunology and summarizes the clinical evidence linking the immune system and atherosclerosis. It provides an overview of the major serological biomarkers that have been associated with atherosclerosis, noting the limitations of these markers attributable to low specificity, and then contrasts these serological markers with the circulating immune cell subtypes that have been found to be altered in coronary artery disease. This review then outlines the technique of mass cytometry and its ability to provide high‐dimensional single‐cell data and explores how this high‐resolution quantification of specific immune cell subpopulations may assist in the diagnosis of early atherosclerosis in combination with other complimentary techniques such as single‐cell RNA sequencing. We propose that this improved specificity has the potential to transform the detection of coronary artery disease in its early phases, facilitating targeted preventative approaches in the precision medicine era.

The predictors and prognostic implications of well-matured collaterals in those with a chronic total occlusion (CTO) are unknown. We sought to identify the determinants of collateral maturation and to determine its effects on procedural outcomes and prognosis. Patients presenting for CTO percutaneous coronary intervention (PCI) between April 2010 and July 2019 were included. Patients with a previous coronary artery bypass (CABG) to the CTO and those with only bridging collaterals were excluded. The degree of collateral maturation was determined by the Rentrop grading classification. Demographic, biochemical, and anatomical factors and procedural and longer-term outcomes were identified. A total of 212 patients were included in the study. Patients with well-matured collaterals were more likely to be females (29.7% versus 15.2% versus 0%, P < 0.005 for Rentrop grade 3, 2, and 0 or 1, respectively), less likely to have chronic kidney disease (CKD) (8.8% versus 4.5% versus 19.2%, P < 0.05) and less likely to have had a prior CABG (15.6% versus 18.7% versus 19.2%). Patients with well-matured collaterals had lower neutrophil-to-leukocyte ratio (NLR) (2.8 versus 4.0 versus 5.7, P < 0.0001). Patients with well-matured collaterals were more likely to have procedural success (90.5% versus 62.5% versus 34.6%, P < 0.0001). The degree of collateral maturation was not associated with longer-term mortality. Improved collateral maturation was associated with female sex and lower rates of CKD and CABG and a lower NLR. Those with well-matured collaterals had a significantly higher rate of procedural success but not improved prognosis.