Plasma lipopolysaccharide-binding protein is a biomarker for future venous thromboembolism: Results from discovery and validation studies.

BACKGROUND: Effect-size underestimation impedes biomarker identification. Long follow-up time in prospective studies attenuates effect-size estimates for transient biomarkers, while disease category-specific biomarkers are affected by merging of categories. Venous thromboembolism (VTE) encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE). OBJECTIVES: (i) To re-analyze untargeted proteomic data to identify biomarker candidates for future VTE that differ between DVT and PE and are attenuated by extended time between sampling and VTE. (ii) To perform targeted candidate validation. PATIENTS/METHODS: A VTE case-control discovery study and a nested case-control validation study were derived from the general population surveyed in 1994-95. Plasma was obtained at study enrollment, and VTE events were registered until 2007. Untargeted proteomic data were re-analyzed for candidate discovery. Lipopolysaccharide-binding protein (LBP) was validated by enzyme-linked immunosorbent assay. RESULTS: Elevated LBP was discovered as a candidate DVT biomarker in women with less than 3 years between blood sampling and DVT. In the validation study, the odds ratio (OR) for DVT was 2.03 (95% confidence intervals [CI]: 1.53-2.74) per standard deviation (SD) increase in LBP for women with less than 3 years between blood sampling and DVT. Adjustment for age, body mass index, and C-reactive protein attenuated the OR to 1.79 (95% CI: 1.25-2.62) per SD. In the validation study, we observed an OR for VTE of 0.47 (95% CI: 0.28-0.77) for men in the 25th to 50th percentiles when compared to the lowest quartile. CONCLUSIONS: We discovered and validated increased LBP as a predictive biomarker for DVT in women. We found an increased VTE risk for men in the lowest quartile of LBP.

Author Correction: STEEP mediates STING ER exit and activation of signaling.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

STEEP mediates STING ER exit and activation of signaling.

STING is essential for control of infections and for tumor immunosurveillance, but it can also drive pathological inflammation. STING resides on the endoplasmic reticulum (ER) and traffics following stimulation to the ERGIC/Golgi, where signaling occurs. Although STING ER exit is the rate-limiting step in STING signaling, the mechanism that drives this process is not understood. Here we identify STEEP as a positive regulator of STING signaling. STEEP was associated with STING and promoted trafficking from the ER. This was mediated through stimulation of phosphatidylinositol-3-phosphate (PtdIns(3)P) production and ER membrane curvature formation, thus inducing COPII-mediated ER-to-Golgi trafficking of STING. Depletion of STEEP impaired STING-driven gene expression in response to virus infection in brain tissue and in cells from patients with STING-associated diseases. Interestingly, STING gain-of-function mutants from patients interacted strongly with STEEP, leading to increased ER PtdIns(3)P levels and membrane curvature. Thus, STEEP enables STING signaling by promoting ER exit.

Identification of Common and Rare Genetic Variation Associated With Plasma Protein Levels Using Whole-Exome Sequencing and Mass Spectrometry.

BACKGROUND: Identifying genetic variation associated with plasma protein levels, and the mechanisms by which they act, could provide insight into alterable processes involved in regulation of protein levels. Although protein levels can be affected by genetic variants, their estimation can also be biased by missense variants in coding exons causing technical artifacts. Integrating genome sequence genotype data with mass spectrometry-based protein level estimation could reduce bias, thereby improving detection of variation that affects RNA or protein metabolism. METHODS: Here, we integrate the blood plasma protein levels of 664 proteins from 165 participants of the Tromsø Study, measured via tandem mass tag mass spectrometry, with whole-exome sequencing data to identify common and rare genetic variation associated with peptide and protein levels (protein quantitative trait loci [pQTLs]). We additionally use literature and database searches to prioritize putative functional variants for each pQTL. RESULTS: We identify 109 independent associations (36 protein and 73 peptide) and use genotype data to exclude 49 (4 protein and 45 peptide) as technical artifacts. We describe 2 particular cases of rare variation: 1 associated with the complement pathway and 1 with platelet degranulation. We identify putative functional variants and show that pQTLs act through diverse molecular mechanisms that affect both RNA and protein metabolism. CONCLUSIONS: We show that although the majority of pQTLs exert their effects by modulating RNA metabolism, many affect protein levels directly. Our work demonstrates the extent by which pQTL studies are affected by technical artifacts and highlights how prioritizing the functional variant in pQTL studies can lead to insights into the molecular steps by which a protein may be regulated.