Pulmonary surfactant protein B carried by HDL predicts incident CVD in patients with type 1 diabetes

A targeted proteomics method for quantifying plasma apolipoprotein kinetics in individual mice using stable isotope labeling

Altered apolipoprotein kinetics play a critical role in promoting dyslipidemia and atherogenesis. Human apolipoprotein kinetics have been extensively evaluated, but similar studies in mice are hampered by the lack of robust methods suitable for the small amounts of blood that can be collected at sequential time points from individual mice. We describe a targeted liquid chromatography tandem mass spectrometry method for simultaneously quantifying the stable isotope enrichment of several apolipoproteins represented by multiple peptides in serial blood samples (15 μl each) obtained after retro-orbital injection of 13C6,15N2-lysine (Lys8) in mice. We determined apolipoprotein fractional clearance rates (FCRs) and production rates (PRs) in WT mice and in two genetic models widely used for atherosclerosis research, LDL receptor-deficient (Ldlr-/-) and apolipoprotein E-deficient (Apoe-/-) mice. Injection of Lys8 produced a unique and readily detectable mass shift of labeled compared with unlabeled peptides with sensitivity allowing robust kinetics analyses. Ldlr-/- mice showed slower FCRs of APOA1, APOA4, total APOB, APOB100, APOCs, APOE and APOM, while FCRs of APOA1, APOB100, APOC2, APOC3, and APOM were not lower in Apoe-/- mice versus WT mice. APOE PR was increased in Ldlr-/- mice, and APOB100 and APOA4 PRs were reduced in Apoe-/- mice. Thus, our method reproducibly quantifies plasma apolipoprotein kinetics in different mouse models. The method can easily be expanded to include a wide range of proteins in the same biospecimen and should be useful for determining the kinetics of apolipoproteins in animal models of human disease.

The alveolar-capillary unit in the physiopathological conditions of heart failure: identification of a potential marker

In this review, we describe the structure and function of the alveolar-capillary membrane and the identification of a novel potential marker of its integrity in the context of heart failure (HF). The alveolar-capillary membrane is indeed a crucial structure for the maintenance of the lung parenchyma gas exchange capacity, and the occurrence of pathological conditions determining lung fluids accumulation, such as HF, might significantly impair lung diffusion capacity altering the alveolar-capillary membrane protective functions. In the years, we found that the presence of immature forms of the surfactant protein-type B (proSP-B) in the circulation reflects alterations in the alveolar-capillary membrane integrity. We discussed our main achievements showing that proSP-B, due to its chemical properties, specifically binds to high-density lipoprotein, impairing their antioxidant activity, and likely contributing to the progression of the disease. Further, we found that immature proSP-B, not the mature protein, is related to lung abnormalities, more precisely than the lung function parameters. Thus, to the list of the potential proposed markers of HF, we add proSP-B, which represents a precise marker of alveolar-capillary membrane dysfunction in HF, correlates with prognosis, and represents a precocious marker of drug therapy.

Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition (DIA)

The introduction of mass spectrometry-based proteomics has revolutionized HDL field, with the description, characterization and implication of HDL-associated proteins in an array of pathologies. However, acquiring robust, reproducible data is still a challenge in the quantitative assessment of HDL proteome. Data-independent acquisition (DIA) is a mass spectrometry methodology that allows the acquisition of reproducible data, but data analysis remains a challenge in the field. Up to date, there is no consensus in how to process DIA-derived data for HDL proteomics. Here, we developed a pipeline aiming to standardize HDL proteome quantification. We optimized instrument parameters, and compared the performance of four freely available, user-friendly software tools (DIA-NN, EncyclopeDIA, MaxDIA and Skyline) in processing DIA data. Importantly, pooled samples were used as quality controls throughout our experimental setup. A carefully evaluation of precision, linearity, and detection limits, first using E. coli background for HDL proteomics, and second using HDL proteome and synthetic peptides, was undertaken. Finally, as a proof of concept, we employed our optimized and automated pipeline to quantify the proteome of HDL and apolipoprotein B (APOB)-containing lipoproteins. Our results show that determination of precision is key to confidently and consistently quantify HDL proteins. Taking this precaution, any of the available software tested here would be appropriate for quantification of HDL proteome, although their performance varied considerably.

Apolipoprotein C3 induces inflammasome activation only in its delipidated form

Matters arising regarding the lipidation form of plasma APOC3 that induces an alternative NLRP3 activation pathway.

The Remnant Lipoprotein Hypothesis of Diabetes-Associated Cardiovascular Disease

Both type 1 and type 2 diabetes are associated with an increased risk of atherosclerotic cardiovascular disease (CVD). Research based on human-first or bedside-to-bench approaches has provided new insights into likely mechanisms behind this increased risk. Although both forms of diabetes are associated with hyperglycemia, it is becoming increasingly clear that altered lipoprotein metabolism also plays a critical role in predicting CVD risk in people with diabetes. This review examines recent findings indicating that increased levels of circulating remnant lipoproteins could be a missing link between diabetes and CVD. Although CVD risk associated with diabetes is clearly multifactorial in nature, these findings suggest that we should increase efforts in evaluating whether remnant lipoproteins or the proteins that govern their metabolism are biomarkers of incident CVD in people living with diabetes and whether reducing remnant lipoproteins will prevent the increased CVD risk associated with diabetes.