Validation of disease-specific biomarkers for the early detection of bronchopulmonary dysplasia

OBJECTIVE: To demonstrate and validate the improvement of current risk stratification for bronchopulmonary dysplasia (BPD) early after birth by plasma protein markers (sialic acid-binding lg-like lectin 14 (SIGLEC-14), basal cell adhesion molecule (BCAM), angiopoietin-like 3 protein (ANGPTL-3)) in extremely premature infants.METHODS AND RESULTS: Proteome screening in first-week-of-life plasma samples of n- 52 preterm infants <32 weeks gestational age (GA) on two proteomic platforms (SomaLogic (R), Olink-Proteomics (R)) confirmed three biomarkers with significant predictive power: BCAM, SIGLEC-14, and ANGPTL-3. We demonstrate high sensitivity (0.92) and specificity (0.86) under consideration of GA, show the proteins' critical contribution to the predictive power of known clinical risk factors, e.g., birth weight and GA, and predicted the duration of mechanical ventilation, oxygen supplementation, as well as neonatal intensive care stay. We confirmed significant predictive power for BPD cases when switching to a clinically applicable method (enzyme-linked immunosorbent assay) in an independent sample set (n = 25, p < 0.001) and demonstrated disease specificity in different cohorts of neonatal and adult lung disease.CONCLUSION: While successfully addressing typical challenges of clinical biomarker studies, we demonstrated the potential of BCAM, SIGLEC-14, and ANGPTL-3 to inform future clinical decision making in the preterm infant at risk for BPD.Analytical BioScience

Amines and lipids metabolites in blood plasma and saliva samples in pigs.

The dataset presented in here is generated in a project named "Effects of sanitary and health status on amino acid and energy metabolism of growing-finishing pigs." The metabolomics data from two samples types in pigs were generated in collaboration with Metabolomics Facility Leiden, The Netherlands and Wageningen Livestock Research, The Netherlands. This collaboration was realized and funded by Enabling Technology Hotels programme, ZonMW, NWO, The Netherlands (project number: 435005015). Targeted quantification of metabolites in two metabolomic platforms covering amines and oxidative stress metabolites in the blood and saliva samples in pigs. The samples were collected from a feeding trial. Briefly, After weaning, i.e., at week 4, pigs were fed a starter (4-9 weeks), grower (9-14 weeks), and finisher (14-22 weeks) diet containing either starch or fat as an energy source. At week 9, before the pigs were fed the grower diet, blood plasma and saliva samples were collected from the pigs (n=6) and the animals were stratified according to different hygiene conditions. At week 14, i.e., before the pigs received the finisher diet, and at week 22, i.e., at the end of this experiment, blood plasma and saliva samples were collected from the pigs (n=6) in the cohort receiving a diet with a different energy source under contrasting sanitary status

Status of metabolomic measurement for insights in Alzheimer’s disease progression—what is missing?

PharmacologyAnalytical BioScience

High-throughput fractionation coupled to mass spectrometry for improved quantitation in metabolomics

Metabolomics is emerging as an important field in life sciences. However, a weakness of current mass spectrometry (MS) based metabolomics platforms is the time-consuming analysis and the occurrence of severe matrix effects in complex mixtures. To overcome this problem, we have developed an automated and fast fractionation module coupled online to MS. The fractionation is realized by the implementation of three consecutive high performance solid-phase extraction columns consisting of a reversed phase, mixed-mode anion exchange, and mixed-mode cation exchange sorbent chemistry. The different chemistries resulted in an efficient interaction with a wide range of metabolites based on polarity, charge, and allocation of important matrix interferences like salts and phospholipids. The use of short columns and direct solvent switches allowed for fast screening (3 min per polarity). In total, 50 commonly reported diagnostic or explorative biomarkers were validated with a limit of quantification that was comparable with conventional LC-MS(/MS). In comparison with a flow injection analysis without fractionation, ion suppression decreased from 89% to 25%, and the sensitivity was 21 times higher. The validated method was used to investigate the effects of circadian rhythm and food intake on several metabolite classes. The significant diurnal changes that were observed stress the importance of standardized sampling times and fasting states when metabolite biomarkers are used. Our method demonstrates a fast approach for global profiling of the metabolome. This brings metabolomics one step closer to implementation into the clinic.Analytical BioScience

Fast LC-ESI-MS/MS analysis and influence of sampling conditions for gut metabolites in plasma and serum

In the past few years, the gut microbiome has been shown to play an important role in various disorders including in particular cardiovascular diseases. Especially the metabolite trimethylamine-N-oxide (TMAO), which is produced by gut microbial metabolism, has repeatedly been associated with an increased risk for cardiovascular events. Here we report a fast liquid chromatography tandem mass spectrometry (LC-MS/MS) method that can analyze the five most important gut metabolites with regards to TMAO in three minutes. Fast liquid chromatography is unconventionally used in this method as an on-line cleanup step to remove the most important ion suppressors leaving the gut metabolites in a cleaned flow through fraction, also known as negative chromatography. We compared different blood matrix types to recommend best sampling practices and found citrated plasma samples demonstrated lower concentrations for all analytes and choline concentrations were significantly higher in serum samples. We demonstrated the applicability of our method by investigating the effect of a standardized liquid meal (SLM) after overnight fasting of 25 healthy individuals on the gut metabolite levels. The SLM did not significantly change the levels of gut metabolites in serum.Analytical BioScience

Expression quantitative trait loci acting across multiple tissues are enriched in inherited risk for coronary artery disease.

Background-Despite recent discoveries of new genetic risk factors, the majority of risk for coronary artery disease (CAD) remains elusive. As the most proximal sensor of DNA variation, RNA abundance can help identify subpopulations of genetic variants active in and across tissues mediating CAD risk through gene expression. Methods and Results-By generating new genomic data on DNA and RNA samples from the Stockholm Atherosclerosis Gene Expression (STAGE) study, 8156 cis-acting expression quantitative trait loci (eQTLs) for 6450 genes across 7 CAD-relevant tissues were detected. The inherited risk enrichments of tissue-defined sets of these eQTLs were assessed using 2 independent genome-wide association data sets. eQTLs acting across increasing numbers of tissues were found increasingly enriched for CAD risk and resided at regulatory hot spots. The risk enrichment of 42 eQTLs acting across 5 to 6 tissues was particularly high (&lt;= 7.3-fold) and confirmed in the combined genome-wide association data from Coronary Artery Disease Genome Wide Replication And Meta-Analysis Consortium. Sixteen of the 42 eQTLs associated with 19 master regulatory genes and 29 downstream gene sets (n&gt;30) were further risk enriched comparable to that of the 153 genome-wide association risk single-nucleotide polymorphisms established for CAD (8.4-fold versus 10-fold). Three gene sets, governed by the master regulators FLYWCH1, PSORSIC3, and G3BP1, segregated the STAGE patients according to extent of CAD, and small interfering RNA targeting of these master regulators affected cholesterol-ester accumulation in foam cells of the THP1 monocytic cell line. Conclusions-eQTLs acting across multiple tissues are significant carriers of inherited risk for CAD. FLYWCH1, PSORSIC3, and G3BP1 are novel master regulatory genes in CAD that may be suitable targets