Targeted Proteomics Identifies Paraoxonase/Arylesterase 1 (PON1) and Apolipoprotein Cs as Potential Risk Factors for Hypoalphalipoproteinemia in Diabetic Subjects Treated with Fenofibrate and Rosiglitazone

Elevated levels of serum alpha-2-macroglobulin associate with diabetes status and incident CVD in type 1 diabetes

Atherosclerotic CVD is a major cause of death in individuals with type 1 diabetes mellitus (T1DM). However, conventional risk factors do not fully account for the increased risk. This study aimed to investigate whether serum proteins associate with diabetes status and the occurrence of CVD in T1DM. We used isotope dilution-MS/MS to quantify 28 serum proteins in 228 subjects participating in the prospective Coronary Artery Calcification in Type 1 Diabetes study. We used linear regression to analyze the association between serum protein levels and T1DM status using 47 healthy controls and 134 T1DM patients without CVD and Cox proportional hazards regression to assess their prediction for incident CVD by a case-cohort study using a subcohort of 145 T1DM subjects and a total of 47 CVD events. Of the 28 serum proteins studied, five of them-alpha-2-macroglobulin (A2M), apolipoprotein A-IV, apolipoprotein L1, insulin-like growth factor 2, and phospholipid transfer protein-were significantly associated with T1DM status, with A2M being 1.6-fold higher in T1DM. After adjusting for potential confounders, A2M independently predicted incident CVD, with a mean hazard ratio of 3.3 and 95% CI of 1.8-6.1. In our study, A2M showed the largest increase in serum levels when comparing patients with T1DM to control subjects. A2M also predicted incident CVD, suggesting that it could serve as both a marker and possibly a mediator of atherosclerosis in T1DM. These findings emphasize the importance of specific serum proteins in assessing and managing CVD risk in T1DM.

Human Carboxylesterase 1A Plays a Predominant Role in Hydrolysis of the Anti-Dyslipidemia Agent Fenofibrate in Humans

Fenofibrate, a marketed peroxisome proliferator-activated receptor-α (PPARα) agonist, has been widely used for treating severe hypertriglyceridemia and mixed dyslipidemia. As a canonical prodrug, fenofibrate can be rapidly hydrolyzed to release the active metabolite (fenofibric acid) in vivo, but the crucial enzyme(s) responsible for fenofibrate hydrolysis and the related hydrolytic kinetics have not been well-investigated. This study aimed to assign the key organs and crucial enzymes involved in fenofibrate hydrolysis in humans, as well as reveal the impact of fenofibrate hydrolysis on its non-PPAR-mediated biologic activities. Our results demonstrated that fenofibrate could be rapidly hydrolyzed in the preparations from both human liver and lung to release fenofibric acid. Reaction phenotyping assays coupling with chemical inhibition assays showed that human carboxylesterase 1A (hCES1A) played a predominant role in fenofibrate hydrolysis in human liver and lung, while human carboxylesterase 2A (hCES2A) and human monoacylglycerol esterase (hMAGL) contributed to a very lesser extent. Kinetic analyses showed that fenofibrate could be rapidly hydrolyzed by hCES1A in human liver preparations, while the inherent clearance of hCES1A-catalyzed fenofibrate hydrolysis is much higher (>200-fold) than than that of hCES2A or hMAGL. Biologic assays demonstrated that both fenofibrate and fenofibric acid showed very closed Nrf2 agonist effects, but fenofibrate hydrolysis strongly weakens its inhibitory effects against both hCES2A and hNtoum. Collectively, our findings reveal that the liver is the major organ and hCES1A is the predominant enzyme-catalyzing fenofibrate hydrolysis in humans, while fenofibrate hydrolysis significantly reduces inhibitory effects of fenofibrate against serine hydrolases. SIGNIFICANCE STATEMENT: Fenofibrate can be completely converted to fenofibric acid in humans and subsequently exert its pharmacological effects, but the hydrolytic pathways of fenofibrate in humans have not been well-investigated. This study reported that the liver was the predominant organ and human carboxylesterase 1A was the crucial enzyme involved in fenofibrate hydrolysis in humans.

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.

HDL cholesterol efflux capacity and phospholipid content are associated with the severity of acute ischemic stroke and predict its outcome

BACKGROUND/AIMS

Impaired high-density lipoprotein (HDL) function and composition are more strongly related to cardiovascular morbidity than HDL concentration. However, it is unclear whether HDL function and composition predict ischemic stroke severity and outcome. We aimed to evaluate these associations.

METHODS

We prospectively studied 199 consecutive patients who were admitted with acute ischemic stroke. The severity of stroke was evaluated at admission with the National Institutes of Health Stroke Scale (NIHSS). Severe stroke was defined as NIHSS ≥ 5. The outcome was assessed with dependency at discharge (modified Rankin scale 2-5) and in-hospital mortality. Cholesterol efflux capacity (CEC), phospholipid levels, lecithin:cholesterol acyl transferase (LCAT)-phospholipase activity, paraoxonase-1 (PON1)-arylesterase activity and serum amyloid A1 (SAA1) content of HDL were measured.

RESULTS

CEC, phospholipid levels and LCAT-phospholipase activity of HDL were lower and SAA1 content of HDL was higher in patients with severe stroke. Patients who were dependent at discharge had lower CEC, PON1-arylesterase activity, phospholipid content and LCAT-phospholipase activity of HDL and higher HDL-SAA1 content. Independent predictors of dependency at discharge were the NIHSS at admission (RR 2.60, 95% CI 1.39-4.87), lipid-lowering treatment (RR 0.17, 95% CI 0.01-0.75), HDL-CEC (RR 0.21, 95% CI 0.05-0.87) and HDL-associated PON1-arylesterase activity (RR 0.95, 95% CI 0.91-0.99). In patients who died during hospitalization, phospholipids, LCAT-phospholipase and PON1-arylesterase activities of HDL were lower.

CONCLUSIONS

Changes in CEC and composition of HDL appear to be associated with the severity and outcome of acute ischemic stroke and could represent biomarkers that may inform risk stratification and management strategies in these patients.

Multi-omics analysis reveals the pathogenesis of db/db mice diabetic kidney disease and the treatment mechanisms of multi-bioactive compounds combination from Salvia miltiorrhiza

Diabetic kidney disease (DKD) is a common diabetic complication. Salvia miltiorrhiza has significant therapeutic effects on diabetes complications, although the mechanism remains unclear. Here, biochemical indicators and pathological changes were used to screen out the optimal Salvia miltiorrhiza multi-bioactive compounds combination. Metabolomics, transcriptomics and proteomics were used to explore the pathogenesis of DKD. RT-PCR and parallel reaction monitoring targeted quantitative proteome analysis were utilized to investigate treatment mechanisms of the optimal Salvia miltiorrhiza multi-bioactive compounds combination. The db/db mice showed biochemical abnormalities and renal lesions. The possible metabolic pathways were steroid hormone biosynthesis and sphingolipid metabolism. The 727 differential genes found in transcriptomics were associated with biochemical indicators via gene network to finally screen 11 differential genes, which were mainly key genes of TGF-β/Smad and PI3K/Akt/FoxO signaling pathways. Salvia miltiorrhiza multi-bioactive compounds combination could significantly regulate the Egr1, Pik3r3 and Col1a1 genes. 11 differentially expressed proteins involved in the two pathways were selected, of which 9 were significantly altered in db/db mice compared to db/m mice. Salvia miltiorrhiza multi-bioactive compounds combination could callback Q9DBM2, S4R1W1, Q91Y97, P47738, A8DUK4, and A2ARV4. In summary, Salvia miltiorrhiza multi-bioactive compounds combination may ameliorate kidney injury in diabetes through regulation of TGF-β/Smad and PI3K/Akt/FoxO signaling pathways.

Drug repositioning based on multi-view learning with matrix completion

Determining drug indications is a critical part of the drug development process. However, traditional drug discovery is expensive and time-consuming. Drug repositioning aims to find potential indications for existing drugs, which is considered as an important alternative to the traditional drug discovery. In this article, we propose a multi-view learning with matrix completion (MLMC) method to predict the potential associations between drugs and diseases. Specifically, MLMC first learns the comprehensive similarity matrices from five drug similarity matrices and two disease similarity matrices based on the multi-view learning (ML) with Laplacian graph regularization, and updates the drug-disease association matrix simultaneously. Then, we introduce matrix completion (MC) to add some positive entries in original association matrix based on low-rank structure, and re-execute the multi-view learning algorithm for association prediction. At last, the prediction results of the above two operations are integrated as the final output. Evaluated by 10-fold cross-validation and de novo tests, MLMC achieves higher prediction accuracy than the current state-of-the-art methods. Moreover, case studies confirm the ability of our method in novel drug-disease association discovery. The codes of MLMC are available at https://github.com/BioinformaticsCSU/MLMC. Contact: jxwang@mail.csu.edu.cn.

The HDL Proteome Watch: Compilation of studies leads to new insights on HDL function

PURPOSE OF REVIEW

High density lipoproteins (HDL) are a heterogeneous family of particles that contain distinct complements of proteins that define their function. Thus, it is important to accurately and sensitively identify proteins associated with HDL. Here we highlight the HDL Proteome Watch Database which tracks proteomics studies from different laboratories across the world.

RECENT FINDINGS

In 45 published reports, almost 1000 individual proteins have been detected in preparations of HDL. Of these, 251 have been identified in at least three different laboratories. The known functions of these consensus HDL proteins go well beyond traditionally recognized roles in lipid transport with many proteins pointing to HDL functions in innate immunity, inflammation, cell adhesion, hemostasis and protease regulation, and even vitamin and metal binding.

SUMMARY

The HDL proteome derived across multiple studies using various methodologies provides confidence in protein identifications that can offer interesting new insights into HDL function. We also point out significant issues that will require additional study going forward.

HDL proteome remodeling associates with COVID-19 severity

BACKGROUND

Besides the well-accepted role in lipid metabolism, high-density lipoprotein (HDL) also seems to participate in host immune response against infectious diseases.

OBJECTIVE

We used a quantitative proteomic approach to test the hypothesis that alterations in HDL proteome associate with severity of Coronavirus disease 2019 (COVID-19).

METHODS

Based on clinical criteria, subjects (n=41) diagnosed with COVID-19 were divided into two groups: a group of subjects presenting mild symptoms and a second group displaying severe symptoms and requiring hospitalization. Using a proteomic approach, we quantified the levels of 29 proteins in HDL particles derived from these subjects.

RESULTS

We showed that the levels of serum amyloid A 1 and 2 (SAA1 and SAA2, respectively), pulmonary surfactant-associated protein B (SFTPB), apolipoprotein F (APOF), and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) were increased by more than 50% in hospitalized patients, independently of sex, HDL-C or triglycerides when comparing with subjects presenting only mild symptoms. Altered HDL proteins were able to classify COVID-19 subjects according to the severity of the disease (error rate 4.9%). Moreover, apolipoprotein M (APOM) in HDL was inversely associated with odds of death due to COVID-19 complications (odds ratio [OR] per 1-SD increase in APOM was 0.27, with 95% confidence interval [CI] of 0.07 to 0.72, P=0.007).

CONCLUSION

Our results point to a profound inflammatory remodeling of HDL proteome tracking with severity of COVID-19 infection. They also raise the possibility that HDL particles could play an important role in infectious diseases.

Niacin Increases Atherogenic Proteins in High-Density Lipoprotein of Statin-Treated Subjects

[Figure: see text].

High-Density Lipoprotein Carries Markers That Track With Recovery From Stroke

RATIONALE

Prospective cohort studies question the value of HDL-C (high-density lipoprotein cholesterol) for stroke risk prediction.

OBJECTIVE

Investigate the relationship between long-term functional recovery and HDL proteome and function.

METHODS AND RESULTS

Changes in HDL protein composition and function (cholesterol efflux capacity) in patients after acute ischemic stroke at 2 time points (24 hours, 35 patients; 96 hours, 20 patients) and in 35 control subjects were measured. The recovery from stroke was assessed by 3 months, the National Institutes of Health Stroke Scale and modified Rankin scale scores. When compared with control subject after adjustments for sex and HDL-C levels, 12 proteins some of which participate in acute phase response and platelet activation (APMAP [adipocyte plasma membrane-associated protein], GPLD1 [phosphate inositol-glycan specific phospholipase D], APOE [apolipoprotein E], IHH [Indian hedgehog protein], ITIH4 [inter-alpha-trypsin inhibitor chain H4], SAA2 [serum amyloid A2], APOA4 [apolipoprotein A-IV], CLU [clusterin], ANTRX2 [anthrax toxin receptor 2], PON1 [serum paraoxonase/arylesterase], SERPINA1 [alpha-1-antitrypsin], and APOF [apolipoprotein F]) were significantly (adjusted P<0.05) altered in stroke HDL at 96 hours. The first 8 of these proteins were also significantly altered at 24 hours. Consistent with inflammatory remodeling, cholesterol efflux capacity was reduced by 32% (P<0.001) at both time points. Baseline stroke severity adjusted regression model showed that changes within 96-hour poststroke in APOF, APOL1, APMAP, APOC4 (apolipoprotein C4), APOM (apolipoprotein M), PCYOX1 (prenylcysteine oxidase 1), PON1, and APOE correlate with stroke recovery scores (R2=0.38-0.73, adjusted P<0.05). APOF (R2=0.73) and APOL1 (R2=0.60) continued to significantly correlate with recovery scores after accounting for tPA (tissue-type plasminogen activator) treatment.

CONCLUSIONS

Changes in HDL proteins during early acute phase of stroke associate with recovery. Monitoring HDL proteins may provide clinical biomarkers that inform on stroke recuperation.

Diabetes Impairs Cellular Cholesterol Efflux From ABCA1 to Small HDL Particles

RATIONALE

HDL (high-density lipoprotein) may be cardioprotective because it accepts cholesterol from macrophages via the cholesterol transport proteins ABCA1 (ATP-binding cassette transporter A1) and ABCG1 (ATP-binding cassette transporter G1). The ABCA1-specific cellular cholesterol efflux capacity (ABCA1 CEC) of HDL strongly and negatively associates with cardiovascular disease risk, but how diabetes mellitus impacts that step is unclear.

OBJECTIVE

To test the hypothesis that HDL's cholesterol efflux capacity is impaired in subjects with type 2 diabetes mellitus.

METHODS AND RESULTS

We performed a case-control study with 19 subjects with type 2 diabetes mellitus and 20 control subjects. Three sizes of HDL particles, small HDL, medium HDL, and large HDL, were isolated by high-resolution size exclusion chromatography from study subjects. Then we assessed the ABCA1 CEC of equimolar concentrations of particles. Small HDL accounted for almost all of ABCA1 CEC activity of HDL. ABCA1 CEC-but not ABCG1 CEC-of small HDL was lower in the subjects with type 2 diabetes mellitus than the control subjects. Isotope dilution tandem mass spectrometry demonstrated that the concentration of SERPINA1 (serpin family A member 1) in small HDL was also lower in subjects with diabetes mellitus. Enriching small HDL with SERPINA1 enhanced ABCA1 CEC. Structural analysis of SERPINA1 identified 3 amphipathic α-helices clustered in the N-terminal domain of the protein; biochemical analyses demonstrated that SERPINA1 binds phospholipid vesicles.

CONCLUSIONS

The ABCA1 CEC of small HDL is selectively impaired in type 2 diabetes mellitus, likely because of lower levels of SERPINA1. SERPINA1 contains a cluster of amphipathic α-helices that enable apolipoproteins to bind phospholipid and promote ABCA1 activity. Thus, impaired ABCA1 activity of small HDL particles deficient in SERPINA1 could increase cardiovascular disease risk in subjects with diabetes mellitus.

Temporal Dynamics of High-Density Lipoprotein Proteome in Diet-Controlled Subjects with Type 2 Diabetes

We examined the effect of mild hyperglycemia on high-density lipoprotein (HDL) metabolism and kinetics in diet-controlled subjects with type 2 diabetes (T2D). ²H₂O-labeling coupled with mass spectrometry was applied to quantify HDL cholesterol turnover and HDL proteome dynamics in subjects with T2D (n = 9) and age- and BMI-matched healthy controls (n = 8). The activities of lecithin–cholesterol acyltransferase (LCAT), cholesterol ester transfer protein (CETP), and the proinflammatory index of HDL were quantified. Plasma adiponectin levels were reduced in subjects with T2D, which was directly associated with suppressed ABCA1-dependent cholesterol efflux capacity of HDL. The fractional catabolic rates of HDL cholesterol, apolipoprotein A-II (ApoA-II), ApoJ, ApoA-IV, transthyretin, complement C3, and vitamin D-binding protein (all p < 0.05) were increased in subjects with T2D. Despite increased HDL flux of acute-phase HDL proteins, there was no change in the proinflammatory index of HDL. Although LCAT and CETP activities were not affected in subjects with T2D, LCAT was inversely associated with blood glucose and CETP was inversely associated with plasma adiponectin. The degradation rates of ApoA-II and ApoA-IV were correlated with hemoglobin A_1c. In conclusion, there were in vivo impairments in HDL proteome dynamics and HDL metabolism in diet-controlled patients with T2D.

Importance of paraoxonase 1 (PON1) as an antioxidant and antiatherogenic enzyme in the cardiovascular complications of type 2 diabetes: Genotypic and phenotypic evaluation

Oxidant-antioxidant imbalance is involved in the etiology of different diseases, including cardiovascular diseases (CVDs), liver disorders, kidney diseases, cancers and diabetes mellitus. Antioxidant enzymes play a key role in striking an oxidant-antioxidant balance. Moreover, paraoxonase 1 (PON1) is an antioxidant enzyme that binds with high-density lipoprotein (HDL) in the circulation, and antioxidant and antiaterogenic properties of this lipoprotein are significantly associated with PON1. Research suggests PON1 contributes to the pathogenesis of certain human diseases such as type 2 diabetes (T2D). The association between PON1 and T2D appear to be reciprocal so that the disease significantly decreases PON1 levels and in turn, the genetics of PON1 may have a role the risk of susceptibility to T2D. Several factors that reduce the activity and concentration of PON1 in patients with T2D include increased glycation and loss-of-function polymorphisms. The genotypic and phenotypic evaluations of PON1 are therefore crucial for assessing the risk of cardiovascular complications in these patients, and strategies for increasing or restoring PON1 levels are useful for reducing or preventing their cardiovascular complications as their main cause of mortality. The present review aimed at discussing and emphasizing the key role of PON1 in T2D as a silent and dangerous disease.

Comparing Data-Independent Acquisition and Parallel Reaction Monitoring in Their Abilities To Differentiate High-Density Lipoprotein Subclasses

High-density lipoprotein (HDL) is a diverse group of particles with multiple cardioprotective functions. HDL proteome follows HDL particle complexity. Many proteins were described in HDL, but consistent quantification of HDL protein cargo is still a challenge. To address this issue, the aim of this work was to compare data-independent acquisition (DIA) and parallel reaction monitoring (PRM) methodologies in their abilities to differentiate HDL subclasses through their proteomes. To this end, we first evaluated the analytical performances of DIA and PRM using labeled peptides in pooled digested HDL as a biological matrix. Next, we compared the quantification capabilities of the two methodologies for 24 proteins found in HDL₂ and HDL₃ from 19 apparently healthy subjects. DIA and PRM exhibited comparable linearity, accuracy, and precision. Moreover, both methodologies worked equally well, differentiating HDL subclasses' proteomes with high precision. Our findings may help to understand HDL functional diversity.

Deepening our understanding of HDL proteome

Introduction: High-density lipoprotein (HDL) particles are heterogeneous and their proteome is complex and distinct from HDL cholesterol. However, it is largely unknown whether HDL proteins are associated with cardiovascular protection. Areas covered: HDL isolation techniques and proteomic analyses are reviewed. A list of HDL proteins reported in 37 different studies was compiled and the effects of different isolation techniques on proteins attributed to HDL are discussed. Mass spectrometric techniques used for HDL analysis and the need for precise and robust methods for quantification of HDL proteins are discussed. Expert opinion: Proteins associated with HDL have the potential to be used as biomarkers and/or help to understand HDL functionality. To achieve this, large cohorts must be studied using precise quantification methods. Key factors in HDL proteome quantification are the isolation methodology and the mass spectrometry technique employed. Isolation methodology affects what proteins are identified in HDL and the specificity of association with HDL particles needs to be addressed. Shotgun proteomics yields imprecise quantification, but the majority of HDL studies relied on this approach. Few recent studies used targeted tandem mass spectrometry to quantify HDL proteins, and it is imperative that future studies focus on the application of these precise techniques.

Apolipoprotein A1 Forms 5/5 and 5/4 Antiparallel Dimers in Human High-density Lipoprotein

Apolipoprotein A1 (APOA1), the major protein of high-density lipoprotein (HDL), contains 10 helical repeats that play key roles in protein-protein and protein-lipid interactions. The current structural model for HDL proposes that APOA1 forms an antiparallel dimer in which helix 5 in monomer 1 associates with helix 5 in monomer 2 along a left-left (LL5/5) interface, forming a protein complex with a 2-fold axis of symmetry centered on helix 5. However, computational studies suggest that other orientations are possible. To test this idea, we used a zero-length chemical cross-linking reagent that forms covalent bonds between closely apposed basic and acidic residues. Using proteolytic digestion and tandem mass spectrometry, we identified amino acids in the central region of the antiparallel APOA1 dimer of HDL that were in close contact. As predicted by the current model, we found six intermolecular cross-links that were consistent with the antiparallel LL5/5 registry. However, we also identified three intermolecular cross-links that were consistent with the antiparallel LL5/4 registry. The LL5/5 is the major structural conformation of the two complexes in both reconstituted discoidal HDL particles and in spherical HDL from human plasma. Molecular dynamic simulations suggest that that LL5/5 and LL5/4 APOA1 dimers possess similar free energies of dimerization, with LL5/5 having the lowest free energy. Our observations indicate that phospholipidated APOA1 in HDL forms different antiparallel dimers that could play distinct roles in enzyme regulation, assembly of specific protein complexes, and the functional properties of HDL in humans.

Plasma lipoproteome in Alzheimer's disease: a proof-of-concept study

Background

Although total plasma lipoproteome consists of proteins that have shown promises as biomarkers that can identify Alzheimer's disease (AD), effect sizes are modest. The objective of this study is to provide initial proof-of-concept that the plasma lipoproteome more likely differ between AD cases and controls when measured in individual plasma lipoprotein fractions than when measured as total in immunodepleted plasma.

Methods

We first developed a targeted proteomics method based on selected reaction monitoring (SRM) and liquid chromatography and tandem mass spectrometry for measurement of 120 tryptic peptides from 79 proteins that are commonly present in plasma lipoproteins. Then in a proof-of concept case-control study of 5 AD cases and 5 sex- and age-matched controls, we applied the targeted proteomic method and performed relatively quantification of 120 tryptic peptides in plasma lipoprotein fractions (fractionated by sequential gradient ultracentrifugation) and in immunodepleted plasma (of albumin and IgG). Unadjusted p values from two-sample t-tests and overall fold change was used to evaluate a peptide relative difference between AD cases and controls, with lower p values (< 0.05) or greater fold differences (> 1.05 or < 0.95) suggestive of greater peptide/protein differences.

Results

Within-day and between-days technical precisions (mean %CV [SD] of all SRM transitions) of the targeted proteomic method were 3.95% (2.65) and 9.31% (5.59), respectively. Between-days technical precisions (mean % CV [SD]) of the entire plasma lipoproteomic workflow including plasma lipoprotein fractionation was 27.90% (14.61). Ten tryptic peptides that belonged to 5 proteins in plasma lipoproteins had unadjusted p values < 0.05, compared to no peptides in immunodepleted plasma. Furthermore, 27, 32, 17, and 20 tryptic peptides in VLDL, IDL, LDL and HDL, demonstrated overall peptide fold differences > 1.05 or < 0.95, compared to only 6 tryptic peptides in immunodepleted plasma. The overall comparisons, therefore, suggested greater peptide/protein differences in plasma lipoproteome when measured in individual plasma lipoproteins than as total in immunodepleted plasma. Specifically, protein complement C3's peptide IHWESASLLR, had unadjusted p values of 0.00007, 0.00012, and 0.0006 and overall 1.25, 1.17, 1.14-fold changes in VLDL, IDL, and LDL, respectively. After positive False Discovery Rate (pFDR) adjustment, the complement C3 peptide IHWESASLLR in VLDL remained statistically different (adjusted p value < 0.05).

Discussion

The findings may warrant future studies to investigate plasma lipoproteome when measured in individual plasma lipoprotein fractions for AD diagnosis.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Quantifying HDL proteins by mass spectrometry: how many proteins are there and what are their functions?

INTRODUCTION

Many lines of evidence indicate that low levels of HDL cholesterol increase the risk of cardiovascular disease (CVD). However, recent clinical studies of statin-treated subjects with established atherosclerosis cast doubt on the hypothesis that elevating HDL cholesterol levels reduces CVD risk. Areas covered: It is critical to identify new HDL metrics that capture HDL's proposed cardioprotective effects. One promising approach is quantitative MS/MS-based HDL proteomics. This article focuses on recent studies of the feasibility and challenges of using this strategy in translational studies. It also discusses how lipid-lowering therapy and renal disease alter HDL's functions and proteome, and how HDL might serve as a platform for binding proteins with specific functional properties. Expert commentary: It is clear that HDL has a diverse protein cargo and that its functions extend well beyond its classic role in lipid transport and reverse cholesterol transport. MS/MS analysis has demonstrated that HDL might contain >80 different proteins. Key challenges are demonstrating that these proteins truly associate with HDL, are functionally important, and that MS-based HDL proteomics can reproducibly detect biomarkers in translational studies of disease risk.

Time to ditch HDL-C as a measure of HDL function?

PURPOSE OF REVIEW

Epidemiological and clinical studies link low levels of HDL cholesterol (HDL-C) with increased risk of atherosclerotic cardiovascular disease (CVD). However, genetic polymorphisms linked to HDL-C do not associate consistently with CVD risk, and randomized clinical studies of drugs that elevate HDL-C via different mechanisms failed to reduce CVD risk in statin-treated patients with established CVD. New metrics that capture HDL's proposed cardioprotective effects are therefore urgently needed.

RECENT FINDINGS

Recent studies demonstrate cholesterol efflux capacity (CEC) of serum HDL (serum depleted of cholesterol-rich atherogenic lipoproteins) is an independent and better predictor of incident and prevalent CVD risk than HDL-C. However, it remains unclear whether therapies that increase CEC are cardioprotective. Other key issues are the impact of HDL-targeted therapies on HDL particle size and concentration and the relationship of those changes to CEC and cardioprotection.

SUMMARY

It is time to end the clinical focus on HDL-C and to understand how HDL's function, protein composition and size contribute to CVD risk. It will also be important to link variations in function and size to HDL-targeted therapies. Developing new metrics for quantifying HDL function, based on better understanding HDL metabolism and macrophage CEC, is critical for achieving these goals.

Severe decrease in high-density lipoprotein cholesterol with the combination of fibrates and ezetimibe: A case series

A sudden and severe drug-induced decrease in plasma high-density lipoprotein cholesterol (HDL-C) is a rare condition. We report 2 patients with familial hypercholesterolemia treated with statins and fibrates and 2 others with mixed dyslipidemia treated with fibrates, who presented with a sudden and severe decrease in HDL-C (from -44% to -95%, compared with baseline). Three of the patients were treated with fibrates and had a sudden decrease in HDL-C after the adjunction of ezetimibe. HDL-C returned to normal levels after discontinuation of the offending therapies. In 2 of these patients, the reintroduction of ezetimibe with no fibrates did not affect HDL-C. In conclusion, we report a new profile of patients who are at risk for a sudden drop of HDL-C related to treatment with a combination of fibrates and ezetimibe. Although a sudden drop of HDL-C is a rare event, we recommend to carefully monitor plasma HDL-C in patients submitted to both drugs.

Unbiased and targeted mass spectrometry for the HDL proteome

PURPOSE OF REVIEW

Mass spectrometry is an ever evolving technology that is equipped with a variety of tools for protein research. Some lipoprotein studies, especially those pertaining to HDL biology, have been exploiting the versatility of mass spectrometry to understand HDL function through its proteome. Despite the role of mass spectrometry in advancing research as a whole, however, the technology remains obscure to those without hands on experience, but still wishing to understand it. In this review, we walk the reader through the coevolution of common mass spectrometry workflows and HDL research, starting from the basic unbiased mass spectrometry methods used to profile the HDL proteome to the most recent targeted methods that have enabled an unprecedented view of HDL metabolism.

RECENT FINDINGS

Unbiased global proteomics have demonstrated that the HDL proteome is organized into subgroups across the HDL size fractions providing further evidence that HDL functional heterogeneity is in part governed by its varying protein constituents. Parallel reaction monitoring, a novel targeted mass spectrometry method, was used to monitor the metabolism of HDL apolipoproteins in humans and revealed that apolipoproteins contained within the same HDL size fraction exhibit diverse metabolic properties.

SUMMARY

Mass spectrometry provides a variety of tools and strategies to facilitate understanding, through its proteins, the complex biology of HDL.