The bulk of cardiovascular disease risk is not explained by traditional risk factors. Recent advances in mass spectrometry allow the identification and quantification of hundreds of lipid species. ...Molecular lipid profiling by mass spectrometry may improve cardiovascular risk prediction.
Lipids were extracted from 685 plasma samples of the prospective population-based Bruneck Study (baseline evaluation in 2000). One hundred thirty-five lipid species from 8 different lipid classes were profiled by shotgun lipidomics with the use of a triple-quadrupole mass spectrometer. Levels of individual species of cholesterol esters (CEs), lysophosphatidylcholines, phosphatidylcholines, phosphatidylethanolamines (PEs), sphingomyelins, and triacylglycerols (TAGs) were associated with cardiovascular disease over a 10-year observation period (2000-2010, 90 incident events). Among the lipid species with the strongest predictive value were TAGs and CEs with a low carbon number and double-bond content, including TAG(54:2) and CE(16:1), as well as PE(36:5) (P=5.1 × 10⁻⁷, 2.2 × 10⁻⁴, and 2.5 × 10⁻³, respectively). Consideration of these 3 lipid species on top of traditional risk factors resulted in improved risk discrimination and classification for cardiovascular disease (cross-validated ΔC index, 0.0210 95% confidence interval, 0.0010-0.0422; integrated discrimination improvement, 0.0212 95% confidence interval, 0.0031-0.0406; and continuous net reclassification index, 0.398 95% confidence interval, 0.175-0.619). A similar shift in the plasma fatty acid composition was associated with cardiovascular disease in the UK Twin Registry (n=1453, 45 cases).
This study applied mass spectrometry-based lipidomics profiling to population-based cohorts and identified molecular lipid signatures for cardiovascular disease. Molecular lipid species constitute promising new biomarkers that outperform the conventional biochemical measurements of lipid classes currently used in clinics.
MicroRNA (miRNA) biomarkers are attracting considerable interest. Effects of medication, however, have not been investigated thus far.
To analyze changes in plasma miRNAs in response to antiplatelet ...therapy.
Profiling for 377 miRNAs was performed in platelets, platelet microparticles, platelet-rich plasma, platelet-poor plasma, and serum. Platelet-rich plasma showed markedly higher levels of miRNAs than serum and platelet-poor plasma. Few abundant platelet miRNAs, such as miR-24, miR-197, miR-191, and miR-223, were also increased in serum compared with platelet-poor plasma. In contrast, antiplatelet therapy significantly reduced miRNA levels. Using custom-made quantitative real-time polymerase chain reaction plates, 92 miRNAs were assessed in a dose-escalation study in healthy volunteers at 4 different time points: at baseline without therapy, at 1 week with 10 mg prasugrel, at 2 weeks with 10 mg prasugrel plus 75 mg aspirin, and at 3 weeks with 10 mg prasugrel plus 300 mg aspirin. Findings in healthy volunteers were confirmed by individual TaqMan quantitative real-time polymerase chain reaction assays (n=9). Validation was performed in an independent cohort of patients with symptomatic atherosclerosis (n=33), who received low-dose aspirin at baseline. Plasma levels of platelet miRNAs, such as miR-223, miR-191, and others, that is, miR-126 and miR-150, decreased on further platelet inhibition.
Our study demonstrated a substantial platelet contribution to the circulating miRNA pool and identified miRNAs responsive to antiplatelet therapy. It also highlights that antiplatelet therapy and preparation of blood samples could be confounding factors in case-control studies relating plasma miRNAs to cardiovascular disease.
Label-free LC-MS/MS proteomics has proven itself to be a powerful method for evaluating protein identification and quantification from complex samples. For comparative proteomics, several methods ...have been used to detect the differential expression of proteins from such data. We have assessed seven methods used across the literature for detecting differential expression from spectral count quantification: Student's t-test, significance analysis of microarrays (SAM), normalised spectral abundance factor (NSAF), normalised spectral abundance factor-power law global error model (NSAF-PLGEM), spectral index (SpI), DESeq and QSpec. We used 2000 simulated datasets as well as publicly available data from a proteomic standards study to assess the ability of these methods to detect differential expression in varying effect sizes and proportions of differentially expressed proteins. At two false discovery rate (FDR) levels, we find that several of the methods detect differential expression within the data with reasonable precision, others detect differential expression at the expense of low precision, and finally, others which fail to identify any differentially expressed proteins. The inability of these seven methods to fully capture the differential landscape, even at the largest effect size, illustrates some of the limitations of the existing technologies and the statistical methodologies.
In label-free mass spectrometry experiments, protein identification and quantification have always been important, but there is now a growing focus on comparative proteomics. Detecting differential expression in protein levels can inform on important biological mechanisms and provide direction for further study. Given the high cost and labour intensive nature of validation experiments, statistical methods are important for prioritising proteins of interest. Here, we have performed a comparative analysis to investigate the statistical methodologies for detecting differential expression and provide a reference for future experimental designs.
This article is part of a Special Issue entitled: Computational Proteomics.
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•Compare 7 statistical methods for detecting differential expression•Utilise 2000 simulated datasets and a published experimental dataset•Effect sizes and proportion of differentially expressed proteins impact results.•DESeq and QSpec provide a reasonable true to false positive rates•Discuss limitations and considerations for future experiments
Circulating microRNAs (miRNAs) have emerged as novel biomarkers of diabetes. The current study focuses on the role of circulating miRNAs in patients with type 1 diabetes and their association with ...diabetic retinopathy. A total of 29 miRNAs were quantified in serum samples (n = 300) using a nested case-control study design in two prospective cohorts of the DIabetic REtinopathy Candesartan Trial (DIRECT): PROTECT-1 and PREVENT-1. The PREVENT-1 trial included patients without retinopathy at baseline; the PROTECT-1 trial included patients with nonproliferative retinopathy at baseline. Two miRNAs previously implicated in angiogenesis, miR-27b and miR-320a, were associated with incidence and with progression of retinopathy: the odds ratio per SD higher miR-27b was 0.57 (95% CI 0.40, 0.82; P = 0.002) in PREVENT-1, 0.78 (0.57, 1.07; P = 0.124) in PROTECT-1, and 0.67 (0.50, 0.92; P = 0.012) combined. The respective odds ratios for higher miR-320a were 1.57 (1.07, 2.31; P = 0.020), 1.43 (1.05, 1.94; P = 0.021), and 1.48 (1.17, 1.88; P = 0.001). Proteomics analyses in endothelial cells returned the antiangiogenic protein thrombospondin-1 as a common target of both miRNAs. Our study identifies two angiogenic miRNAs, miR-320a and miR-27b, as potential biomarkers for diabetic retinopathy.
Fibrosis is a common pathology in many cardiac disorders and is driven by the activation of resident fibroblasts. The global posttranscriptional mechanisms underlying fibroblast-to-myofibroblast ...conversion in the heart have not been explored.
Genome-wide changes of RNA transcription and translation during human cardiac fibroblast activation were monitored with RNA sequencing and ribosome profiling. We then used RNA-binding protein-based analyses to identify translational regulators of fibrogenic genes. The integration with cardiac ribosome occupancy levels of 30 dilated cardiomyopathy patients demonstrates that these posttranscriptional mechanisms are also active in the diseased fibrotic human heart.
We generated nucleotide-resolution translatome data during the transforming growth factor β1-driven cellular transition of human cardiac fibroblasts to myofibroblasts. This identified dynamic changes of RNA transcription and translation at several time points during the fibrotic response, revealing transient and early-responder genes. Remarkably, about one-third of all changes in gene expression in activated fibroblasts are subject to translational regulation, and dynamic variation in ribosome occupancy affects protein abundance independent of RNA levels. Targets of RNA-binding proteins were strongly enriched in posttranscriptionally regulated genes, suggesting genes such as MBNL2 can act as translational activators or repressors. Ribosome occupancy in the hearts of patients with dilated cardiomyopathy suggested the same posttranscriptional regulatory network was underlying cardiac fibrosis. Key network hubs include RNA-binding proteins such as Pumilio RNA binding family member 2 (PUM2) and Quaking (QKI) that work in concert to regulate the translation of target transcripts in human diseased hearts. Furthermore, silencing of both PUM2 and QKI inhibits the transition of fibroblasts toward profibrotic myofibroblasts in response to transforming growth factor β1.
We reveal widespread translational effects of transforming growth factor β1 and define novel posttranscriptional regulatory networks that control the fibroblast-to-myofibroblast transition. These networks are active in human heart disease, and silencing of hub genes limits fibroblast activation. Our findings show the central importance of translational control in fibrosis and highlight novel pathogenic mechanisms in heart failure.
Osteoarthritis is the most common form of arthritis and a major socioeconomic burden. Our study is the first to explore the association between serum microRNA levels and the development of severe ...osteoarthritis of the knee and hip joint in the general population.
We followed 816 Caucasian individuals from 1995 to 2010 and assessed joint arthroplasty as a definitive outcome of severe osteoarthritis of the knee and hip. After a microarray screen, we validated 12 microRNAs by real-time PCR in the entire cohort at baseline.
In Cox regression analysis, three microRNAs were associated with severe knee and hip osteoarthritis. let-7e was a negative predictor for total joint arthroplasty with an adjusted HR of 0.75 (95% CI 0.58 to 0.96; p=0.021) when normalised to U6, and 0.76 (95% CI 0.6 to 0.97; p=0.026) after normalisation to the Ct average. miRNA-454 was inversely correlated with severe knee or hip osteoarthritis with an adjusted HR of 0.77 (95% CI 0.61 to 0.97; p=0.028) when normalised to U6. This correlation was lost when data were normalised to Ct average (p=0.118). Finally, miRNA-885-5p showed a trend towards a positive relationship with arthroplasty when normalised to U6 (HR 1.24; 95% CI 0.95 to 1.62; p=0.107) or to Ct average (HR 1.30; 95% CI 0.99 to 1.70; p=0.056).
Our study is the first to identify differentially expressed circulating microRNAs in osteoarthritis patients necessitating arthroplasty in a large, population-based cohort. Among these microRNAs, let-7e emerged as potential predictor for severe knee or hip osteoarthritis.
Translated small open reading frames (smORFs) can have important regulatory roles and encode microproteins, yet their genome-wide identification has been challenging. We determined the ribosome ...locations across six primary human cell types and five tissues and detected 7,767 smORFs with translational profiles matching those of known proteins. The human genome was found to contain highly cell-type- and tissue-specific smORFs and a subset that encodes highly conserved amino acid sequences. Changes in the translational efficiency of upstream-encoded smORFs (uORFs) and the corresponding main ORFs predominantly occur in the same direction. Integration with 456 mass-spectrometry datasets confirms the presence of 603 small peptides at the protein level in humans and provides insights into the subcellular localization of these small proteins. This study provides a comprehensive atlas of high-confidence translated smORFs derived from primary human cells and tissues in order to provide a more complete understanding of the translated human genome.
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•Ribosome profiling (Ribo-seq) of 11 human primary cells and tissues reveals 7,767 high-confidence smORFs•smORFs exhibit cell-type/tissue specificity, and 603 SEPs were detected in MS data•Dynamic changes in the TE of uORF and main ORF pairs are mostly homodirectional•An interactive browser for this study can be found at https://smorfs.ddnetbio.com
Chothani et al. evaluate ribosome-mRNA interactions across six cell types and five tissues and reveal 7,767 small regions outside of the protein-coding genome that are actively translated in humans. These include specifically expressed and highly conserved small open reading frames. The integration of proteomics reveals more than 600 small proteins.
Platelets shed microRNAs (miRNAs). Plasma miRNAs change on platelet inhibition. It is unclear whether plasma miRNA levels correlate with platelet function.
To link small RNAs to platelet reactivity.
...Next-generation sequencing of small RNAs in plasma revealed 2 peaks at 22 to 23 and 32 to 33 nucleotides corresponding to miRNAs and YRNAs, respectively. Among YRNAs, predominantly, fragments of RNY4 and RNY5 were detected. Plasma miRNAs and YRNAs were measured in 125 patients with a history of acute coronary syndrome who had undergone detailed assessment of platelet function 30 days after the acute event. Using quantitative real-time polymerase chain reactions, 92 miRNAs were assessed in patients with acute coronary syndrome on different antiplatelet therapies. Key platelet-related miRNAs and YRNAs were correlated with platelet function tests. MiR-223 (rp=0.28; n=121; P=0.002), miR-126 (rp=0.22; n=121; P=0.016), and other abundant platelet miRNAs and YRNAs showed significant positive correlations with the vasodilator-stimulated phosphoprotein phosphorylation assay. YRNAs, miR-126, and miR-223 were also among the small RNAs showing the greatest dependency on platelets and strongly correlated with plasma levels of P-selectin, platelet factor 4, and platelet basic protein in the population-based Bruneck study (n=669). A single-nucleotide polymorphism that facilitates processing of pri-miR-126 to mature miR-126 accounted for a rise in circulating platelet activation markers. Inhibition of miR-126 in mice reduced platelet aggregation. MiR-126 directly and indirectly affects ADAM9 and P2Y12 receptor expression.
Levels of platelet-related plasma miRNAs and YRNAs correlate with platelet function tests in patients with acute coronary syndrome and platelet activation markers in the general population. Alterations in miR-126 affect platelet reactivity.
The conventional reductionist approach to cardiovascular research investigates individual candidate factors or linear signalling pathways but ignores more complex interactions in biological systems. ...The advent of molecular profiling technologies that focus on a global characterization of whole complements allows an exploration of the interconnectivity of pathways during pathophysiologically relevant processes, but has brought about the issue of statistical analysis and data integration. Proteins identified by differential expression as well as those in protein-protein interaction networks identified through experiments and through computational modelling techniques can be used as an initial starting point for functional analyses. In combination with other '-omics' technologies, such as transcriptomics and metabolomics, proteomics explores different aspects of disease, and the different pillars of observations facilitate the data integration in disease-specific networks. Ultimately, a systems biology approach may advance our understanding of cardiovascular disease processes at a 'biological pathway' instead of a 'single molecule' level and accelerate progress towards disease-modifying interventions.
Abdominal aortic aneurysms constitute a degenerative process in the aortic wall. Both the miR-29 and miR-15 families have been implicated in regulating the vascular extracellular matrix.
Our aim was ...to assess the effect of the miR-15 family on aortic aneurysm development.
Among the miR-15 family members, miR-195 was differentially expressed in aortas of apolipoprotein E-deficient mice on angiotensin II infusion. Proteomics analysis of the secretome of murine aortic smooth muscle cells, after miR-195 manipulation, revealed that miR-195 targets a cadre of extracellular matrix proteins, including collagens, proteoglycans, elastin, and proteins associated with elastic microfibrils, albeit miR-29b showed a stronger effect, particularly in regulating collagens. Systemic and local administration of cholesterol-conjugated antagomiRs revealed better inhibition of miR-195 compared with miR-29b in the uninjured aorta. However, in apolipoprotein E-deficient mice receiving angiotensin II, silencing of miR-29b, but not miR-195, led to an attenuation of aortic dilation. Higher aortic elastin expression was accompanied by an increase of matrix metalloproteinases 2 and 9 in mice treated with antagomiR-195. In human plasma, an inverse correlation of miR-195 was observed with the presence of abdominal aortic aneurysms and aortic diameter.
We provide the first evidence that miR-195 may contribute to the pathogenesis of aortic aneurysmal disease. Although inhibition of miR-29b proved more effective in preventing aneurysm formation in a preclinical model, miR-195 represents a potent regulator of the aortic extracellular matrix. Notably, plasma levels of miR-195 were reduced in patients with abdominal aortic aneurysms suggesting that microRNAs might serve as a noninvasive biomarker of abdominal aortic aneurysms.
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