Improved Quantitative Plant Proteomics via the Combination of Targeted and Untargeted Data Acquisition.

Quantitative proteomics strategies - which are playing important roles in the expanding field of plant molecular systems biology - are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically (15)N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) - referred to as TDA/DDA - to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10(-3)) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA experiments only (33.0 ± 2.6% versus 8.0 ± 2.7%, respectively; p = 0.011). These results were observed together with uncompromised broad-scale MS/MS data collection in TDA/DDA experiments relative to DDA experiments. Using our observations we provide guidelines for TDA/DDA method design for quantitative plant proteomics studies, and suggest that TDA/DDA is a broadly underutilized proteomics data acquisition strategy

Omada: robust clustering of transcriptomes through multiple testing

Background Cohort studies increasingly collect biosamples for molecular profiling and are observing molecular heterogeneity. High-throughput RNA sequencing is providing large datasets capable of reflecting disease mechanisms. Clustering approaches have produced a number of tools to help dissect complex heterogeneous datasets, but selecting the appropriate method and parameters to perform exploratory clustering analysis of transcriptomic data requires deep understanding of machine learning and extensive computational experimentation. Tools that assist with such decisions without prior field knowledge are nonexistent. To address this, we have developed Omada, a suite of tools aiming to automate these processes and make robust unsupervised clustering of transcriptomic data more accessible through automated machine learning–based functions. Findings The efficiency of each tool was tested with 7 datasets characterized by different expression signal strengths to capture a wide spectrum of RNA expression datasets. Our toolkit’s decisions reflected the real number of stable partitions in datasets where the subgroups are discernible. Within datasets with less clear biological distinctions, our tools either formed stable subgroups with different expression profiles and robust clinical associations or revealed signs of problematic data such as biased measurements. Conclusions In conclusion, Omada successfully automates the robust unsupervised clustering of transcriptomic data, making advanced analysis accessible and reliable even for those without extensive machine learning expertise. Implementation of Omada is available at http://bioconductor.org/packages/omada/

Plasma Metabolomics Implicate Modified Transfer RNAs and Altered Bioenergetics in the Outcome of Pulmonary Arterial Hypertension.

BACKGROUND: -Pulmonary arterial hypertension (PAH) is a heterogeneous disorder with high mortality. METHODS: -We conducted a comprehensive study of plasma metabolites using ultra-performance liquid chromatography mass-spectrometry to (1) identify patients at high risk of early death, (2) identify patients who respond well to treatment and (3) provide novel molecular insights into disease pathogenesis. RESULTS: -53 circulating metabolites distinguished well-phenotyped patients with idiopathic or heritable PAH (n=365) from healthy controls (n=121) following correction for multiple testing (p<7.3e-5) and confounding factors, including drug therapy, renal and hepatic impairment. A subset of 20/53 metabolites also discriminated PAH patients from disease controls (symptomatic patients without pulmonary hypertension, n=139). 62 metabolites were prognostic in PAH, with 36/62 independent of established prognostic markers. Increased levels of tRNA-specific modified nucleosides (N2,N2-dimethylguanosine, N1-methylinosine), TCA cycle intermediates (malate, fumarate), glutamate, fatty acid acylcarnitines, tryptophan and polyamine metabolites and decreased levels of steroids, sphingomyelins and phosphatidylcholines distinguished patients from controls. The largest differences correlated with increased risk of death and correction of several metabolites over time was associated with a better outcome. Patients who responded to calcium channel blocker therapy had metabolic profiles similar to healthy controls. CONCLUSIONS: -Metabolic profiles in PAH are strongly related to survival and should be considered part of the deep phenotypic characterisation of this disease. Our results support the investigation of targeted therapeutic strategies that seek to address the alterations in translational regulation and energy metabolism that characterize these patients

Two prospective, multicenter studies for the identification of biomarker signatures for early detection of pulmonary hypertension (PH): the CIPHER and CIPHER‐MRI studies

A blood test identifying patients at increased risk of pulmonary hypertension (PH) could streamline the investigative pathway. The prospective, multicenter CIPHER study aimed to develop a microRNA-based signature for detecting PH in breathless patients and enrolled adults with a high suspicion of PH who had undergone right heart catheterization (RHC). The CIPHER-MRI study was added to assess the performance of this CIPHER signature in a population with low probability of having PH who underwent cardiac magnetic resonance imaging (cMRI) instead of RHC. The microRNA signature was developed using a penalized linear regression (LASSO) model. Data were modeled both with and without N-terminal pro-brain natriuretic peptide (NT-proBNP). Signature performance was assessed against predefined thresholds (lower 98.7% CI bound of ≥0.73 for sensitivity and ≥0.53 for specificity, based on a meta-analysis of echocardiographic data), using RHC as the true diagnosis. Overall, 926 CIPHER participants were screened and 888 were included in the analysis. Of 688 RHC-confirmed PH cases, approximately 40% were already receiving PH treatment. Fifty microRNA (from 311 investigated) were algorithmically selected to be included in the signature. Sensitivity [97.5% CI] of the signature was 0.85 [0.80–0.89] for microRNA-alone and 0.90 [0.86–0.93] for microRNA+NT-proBNP, and the corresponding specificities were 0.33 [0.24–0.44] and 0.28 [0.20–0.39]. Of 80 CIPHER-MRI participants with evaluable data, 7 were considered PH-positive by cMRI whereas 52 were considered PH-positive by the microRNA signature. Due to low specificity, the CIPHER miRNA-based signature for PH (either with or without NT-proBNP in model) did not meet the prespecified diagnostic threshold for the primary analysis

Scoping future research for air pollution recovery indicators (APRI). (Workshop report)

Atmospheric nitrogen (N) pollution is a major and ongoing cause of biodiversity loss across the UK, but in some locations N pollution pressures have been declining. In response to these dynamics, JNCC requested a workshop to help to scope Phase 2 of the Air Pollution Recovery Indicators (APRI) project. The damaging effects of excess N load and of gaseous ammonia on many ecosystems are clear. However, the processes and timescales of ecosystem recovery following a decrease in pollution pressure are less well understood. The APRI project aims to take practical steps to fill this knowledge gap by delivering new scientific research focused on indicators of ecosystem and species recovery from N pollution. In Phase 1, predominantly below-ground responses are being studied at a dry heathland site where experimental additions of N were made between 1998 and 2011, revealing lingering effects on soil chemistry, the soil fungi community and vegetation structure (Kowal et al. 2024). The effect on mycorrhizal fungi, and using these fungi as recovery indicators, is being examined in more detail with recently established assessment methods (Arrigoni et al. 2023). Phase 2 of APRI will consider recovery from N impacts more broadly, e.g. by studying other habitats or species. Further empirical research may be commissioned to better understand recovery pathways from air pollution. A workshop was held on 7–8 November 2023 to help develop an action plan for the remainder of the APRI project. This report summarises the workshop discussion and ensuing work. We note that the focus of the APRI project is on assessing recovery. It is therefore essential to contrast responses of ecosystems subject to decreased pollution pressure with indicators from ecosystems experiencing ongoing pollution. Properties that have been used previously to assess impacts can be used to understand recovery, and novel indicators of ecosystem change are also likely to be useful for assessing recovery. Whatever indicators are chosen to assess change, benchmarking data will be needed to assess the range of potential values and relationships with N deposition. Results from the workshop and subsequent discussions include: • Eleven criteria to help choose appropriate indicators in relation to declining N deposition: Speed of response, Sensitivity of response, Specificity of response, Generality to multiple habitats, Relatedness to recovery endpoints, Previous use, Breadth of pollution gradient, Added value to other policy areas, Resilience in face of anticipated change, Feasibility of collection, Measurement uncertainty. • The need to consider a basket of indicators to indicate recovery from N pollution. Such a basket could include examples from different categories e.g. indicators of pressure, biogeochemical response indicators, and biotic response indicators, with individual indicators likely responding over different timescales. The exact choice may depend on the habitat concerned and the availability of prior data, as well as the question being posed and/or policy goal. • Explicit recommendations on sites to target in APRI Phase 2 to gain information on recovery indicator trajectories, namely (i) well-designed field experiments where N addition has ceased, and (ii) point sources of emissions that have ceased to operate, preferably with a super-imposition of an experimental treatment or treatments. Given uncertainties associated with modelled historical, contemporary, and future N deposition and the potential for confounding variables, analysing survey data from across the UK will be unlikely to provide robust information within the timeframes of the APRI Phase 2. We recommend further assessments may help develop detailed plans for empirical work in Phase 2 of APRI. Potential next steps are to: • Finalise a list of potential and priority indicators of recovery from air pollution (which may differ by habitat type), specifically from high levels of N deposition and/or high atmospheric reactive N concentrations. This finalisation could be done through active participation of the air pollution community and the completion of ‘live’ spreadsheets that address potential indicator criteria. • Summarise relevant data on recovery indicators, across key semi-natural habitats. This summary should include data available from other countries with similar environmental contexts, to help disentangle drivers of change in the UK context. This evidence will help understand recovery pathways from air pollution. As above, this could be done through the active participation of the air pollution community and the completion of ‘live’ spreadsheets. Such an approach could also enable gap analyses, for example identifying where we are missing information by habitat and/or environmental conditions. • Identify areas where co-located monitoring of N with existing habitat/species monitoring could enhance the likelihood for establishing recovery indicators. This should enhance other similar activity such as through the Natural Capital and Ecosystem Assessment programme and the UK Air Pollution Impacts on Ecosystems Networks (APIENs). • Develop a list of priority habitats and sites where empirical research is needed to better understand recovery pathways, including a gap analysis of habitats, methods and/or indicators. • Encourage activities that enhance understanding of ammonia emission sources at local scale (e.g. 1 km or less), to help better identify areas where N pollution has decreased, and recovery might be detected. This could include intensive monitoring or collating and sharing information about permitted N sources. • Develop case studies, including potentially from APRI Phase 1, to demonstrate how existing evidence on localised recovery in semi-natural habitats of conservation importance can be used by policy- and decision-makers to help drive policy toward continued reductions in emissions of reactive N

Traffic exposures, air pollution and outcomes in pulmonary arterial hypertension: A United Kingdom cohort study analysis

While traffic and air pollution exposure is associated with increased mortality in numerous diseases, its association with disease severity and outcomes in pulmonary arterial hypertension (PAH) remains unknown.Exposure to particulate matter ≤2.5 μm3 (PM2.5), nitrogen dioxide (NO2) and indirect measures of traffic-related air pollution (distance to main road and length of roads within buffer zones surrounding residential addresses) were estimated for 301 patients with idiopathic/heritable PAH recruited in the UK PAH national Cohort study. Associations with transplant-free survival and pulmonary hemodynamic severity at baseline were assessed, adjusting for confounding variables defined a priori.Higher estimated exposure to PM2.5 was associated with higher risk of death or lung transplant (Unadjusted hazard ratio (HR) 2.68; 95% CI 1.11-6.47 per 3 μg·m-3, p=0.028). This association remained similar when adjusted for potential confounding variables (HR 4.38; 95% CI 1.44-13.36 per 3 μg·m-3, p=0.009). No associations were found between NO2 exposure or other traffic pollution indicators and transplant-free survival Conversely, indirect measures of exposure to traffic-related air pollution within the 500-1000 m buffer zones correlated with the ERS/ESC risk categories as well as pulmonary hemodynamics at baseline. This association was strongest for pulmonary vascular resistance.In idiopathic/heritable PAH, indirect measures of exposure to traffic-related air pollution were associated with disease severity at baseline, whereas higher PM2.5 exposure may independently predict shorter transplant-free survival

Blood DNA methylation profiling identifies cathepsin Z dysregulation in pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is characterised by pulmonary vascular remodelling causing premature death from right heart failure. Established DNA variants influence PAH risk, but susceptibility from epigenetic changes is unknown. We addressed this through epigenome-wide association study (EWAS), testing 865,848 CpG sites for association with PAH in 429 individuals with PAH and 1226 controls. Three loci, at Cathepsin Z (CTSZ, cg04917472), Conserved oligomeric Golgi complex 6 (COG6, cg27396197), and Zinc Finger Protein 678 (ZNF678, cg03144189), reached epigenome-wide significance (p < 10−7) and are hypermethylated in PAH, including in individuals with PAH at 1-year follow-up. Of 16 established PAH genes, only cg10976975 in BMP10 shows hypermethylation in PAH. Hypermethylation at CTSZ is associated with decreased blood cathepsin Z mRNA levels. Knockdown of CTSZ expression in human pulmonary artery endothelial cells increases caspase-3/7 activity (p < 10−4). DNA methylation profiles are altered in PAH, exemplified by the pulmonary endothelial function modifier CTSZ, encoding protease cathepsin Z

Supplementation with iron in pulmonary arterial hypertension : two randomized crossover trials

Rationale: Iron deficiency, in the absence of anaemia, is common in patients with idiopathic and heritable pulmonary arterial hypertension (PAH) and is associated with a worse clinical outcome. Oral iron absorption may be impeded by elevated circulating hepcidin levels. The safety and benefit of parenteral iron replacement in this patient population is unclear. Objectives: To evaluate the safety and efficacy of parenteral iron replacement in pulmonary arterial hypertension. Methods: In two randomised, double blind, placebo-controlled 12 week crossover studies, 39 patients in Europe received a single infusion of ferric carboxymaltose (Ferinject®) 1000 mg (or 15 mg/kg if weight < 66.7Kg) or saline as placebo and 17 patients in China received iron dextran (Cosmofer®) 20 mg iron/kg body weight or saline placebo. All patients had idiopathic or heritable PAH and iron deficiency at entry as defined by: a serum ferritin < 37 µg/l or iron < 10.3 µmol/l or transferrin saturations < 16.4%. Results: Both iron treatments were well tolerated and improved iron status. Analysed separately and combined, there was no effect on any measure of exercise capacity (using cardiopulmonary exercise testing or 6 minute walk test) or cardio-pulmonary haemodynamics, as assessed by right heart catheterisation, cardiac magnetic resonance or plasma NT-proBNP, at 12 weeks. Conclusion: Iron repletion by administration of a slow release iron preparation as a single infusion to PAH patients with iron deficiency without overt anaemia was well tolerated but provided no significant clinical benefit at 12 weeks. Clinical trial registered with ClinicalTrials.gov (NCT01447628