Network-Based Analysis on Orthogonal Separation of Human Plasma Uncovers Distinct High Density Lipoprotein Complexes

Proteomic Determinants of Variation in Cholesterol Efflux: Observations from the Dallas Heart Study

High-density lipoproteins (HDLs) are promising targets for predicting and treating atherosclerotic cardiovascular disease (ASCVD), as they mediate removal of excess cholesterol from lipid-laden macrophages that accumulate in the vasculature. This functional property of HDLs, termed cholesterol efflux capacity (CEC), is inversely associated with ASCVD. HDLs are compositionally diverse, associating with >250 different proteins, but their relative contribution to CEC remains poorly understood. Our goal was to identify and define key HDL-associated proteins that modulate CEC in humans. The proteomic signature of plasma HDL was quantified in 36 individuals in the multi-ethnic population-based Dallas Heart Study (DHS) cohort that exhibited persistent extremely high (>=90th%) or extremely low CEC (<=10th%) over 15 years. Levels of apolipoprotein (Apo)A-I associated ApoC-II, ApoC-III, and ApoA-IV were differentially correlated with CEC in high (r = 0.49, 0.41, and -0.21 respectively) and low (r = -0.46, -0.41, and 0.66 respectively) CEC groups (p for heterogeneity (pHet) = 0.03, 0.04, and 0.003 respectively). Further, we observed that levels of ApoA-I with ApoC-III, complement C3 (CO3), ApoE, and plasminogen (PLMG) were inversely associated with CEC in individuals within the low CEC group (r = -0.11 to -0.25 for subspecies with these proteins vs. r = 0.58 to 0.65 for subspecies lacking these proteins; p < 0.05 for heterogeneity). These findings suggest that enrichment of specific proteins on HDLs and, thus, different subspecies of HDLs, differentially modulate the removal of cholesterol from the vasculature.

Precision Nutrition and Cardiovascular Disease Risk Reduction: the Promise of High-Density Lipoproteins

PURPOSE OF REVIEW

Emerging evidence supports the promise of precision nutritional approaches for cardiovascular disease (CVD) prevention. Here, we discuss current findings from precision nutrition trials and studies reporting substantial inter-individual variability in responses to diets and dietary components relevant to CVD outcomes. We highlight examples where early precision nutrition research already points to actionable intervention targets tailored to an individual's biology and lifestyle. Finally, we make the case for high-density lipoproteins (HDL) as a compelling next generation target for precision nutrition aimed at CVD prevention. HDL possesses complex structural features including diverse protein components, lipids, size distribution, extensive glycosylation, and interacts with the gut microbiome, all of which influence HDL's anti-inflammatory, antioxidant, and cholesterol efflux properties. Elucidating the nuances of HDL structure and function at an individual level may unlock personalized dietary and lifestyle strategies to optimize HDL-mediated atheroprotection and reduce CVD risk.

RECENT FINDINGS

Recent human studies have demonstrated that HDL particles are key players in the reduction of CVD risk. Our review highlights the role of HDL and the importance of personalized therapeutic approaches to improve their potential for reducing CVD risk. Factors such as diet, genetics, glycosylation, and gut microbiome interactions can modulate HDL structure and function at the individual level. We emphasize that fractionating HDL into size-based subclasses and measuring particle concentration are necessary to understand HDL biology and for developing the next generation of diagnostics and biomarkers. These discoveries underscore the need to move beyond a one-size-fits-all approach to HDL management. Precision nutrition strategies that account for personalized metabolic, genetic, and lifestyle data hold promise for optimizing HDL therapies and function to mitigate CVD risk more potently. While human studies show HDL play a key role in reducing CVD risk, recent findings indicate that factors such as diet, genetics, glycosylation, and gut microbes modulate HDL function at the individual level, underscoring the need for precision nutrition strategies that account for personalized variability to optimize HDL's potential for mitigating CVD risk.

Human cerebrospinal fluid contains diverse lipoprotein subspecies enriched in proteins implicated in central nervous system health

Lipoproteins in cerebrospinal fluid (CSF) of the central nervous system (CNS) resemble plasma high-density lipoproteins (HDLs), which are a compositionally and structurally diverse spectrum of nanoparticles with pleiotropic functionality. Whether CSF lipoproteins (CSF-Lps) exhibit similar heterogeneity is poorly understood because they are present at 100-fold lower concentrations than plasma HDL. To investigate the diversity of CSF-Lps, we developed a sensitive fluorescent technology to characterize lipoprotein subspecies in small volumes of human CSF. We identified 10 distinctly sized populations of CSF-Lps, most of which were larger than plasma HDL. Mass spectrometric analysis identified 303 proteins across the populations, over half of which have not been reported in plasma HDL. Computational analysis revealed that CSF-Lps are enriched in proteins important for wound healing, inflammation, immune response, and both neuron generation and development. Network analysis indicated that different subpopulations of CSF-Lps contain unique combinations of these proteins. Our study demonstrates that CSF-Lp subspecies likely exist that contain compositional signatures related to CNS health.

Protein-Defined Subspecies of HDLs (High-Density Lipoproteins) and Differential Risk of Coronary Heart Disease in 4 Prospective Studies

OBJECTIVE

HDL (high-density lipoprotein) contains functional proteins that define single subspecies, each comprising 1% to 12% of the total HDL. We studied the differential association with coronary heart disease (CHD) of 15 such subspecies. Approach and Results: We measured plasma apoA1 (apolipoprotein A1) concentrations of 15 protein-defined HDL subspecies in 4 US-based prospective studies. Among participants without CVD at baseline, 932 developed CHD during 10 to 25 years. They were matched 1:1 to controls who did not experience CHD. In each cohort, hazard ratios for each subspecies were computed by conditional logistic regression and combined by meta-analysis. Higher levels of HDL subspecies containing alpha-2 macroglobulin, CoC3 (complement C3), HP (haptoglobin), or PLMG (plasminogen) were associated with higher relative risk compared with the HDL counterpart lacking the defining protein (hazard ratio range, 0.96-1.11 per 1 SD increase versus 0.73-0.81, respectively; P for heterogeneity <0.05). In contrast, HDL containing apoC1 or apoE were associated with lower relative risk compared with the counterpart (hazard ratio, 0.74; P=0.002 and 0.77, P=0.001, respectively).

CONCLUSIONS

Several subspecies of HDL defined by single proteins that are involved in thrombosis, inflammation, immunity, and lipid metabolism are found in small fractions of total HDL and are associated with higher relative risk of CHD compared with HDL that lacks the defining protein. In contrast, HDL containing apoC1 or apoE are robustly associated with lower risk. The balance between beneficial and harmful subspecies in a person's HDL sample may determine the risk of CHD pertaining to HDL and paths to treatment.

Identification of breast cancer risk modules via an integrated strategy

Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.

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.

Rethinking good cholesterol: a clinicians' guide to understanding HDL

Low HDL cholesterol dyslipidaemia affects about half of people with type 2 diabetes and represents a major independent risk factor for atherosclerotic cardiovascular disease. The "good cholesterol" label was coined decades ago on the basis of a presumed causal role of HDL cholesterol in atherosclerotic cardiovascular disease. However, this view has been challenged by the negative results of several studies of HDL cholesterol-raising drugs, creating a paradox for clinicians regarding the value of HDL cholesterol as a risk biomarker and therapeutic target, and seemingly contradicting decades of evidence substantiating an inverse relation between HDL cholesterol and cardiovascular disease risk. We seek to resolve this issue by revisiting the history of the HDL hypothesis, chronicling how this paradox is ultimately rooted in the progressive erroneous blurring of the distinction between HDL and HDL cholesterol. We describe the compositional complexity of HDL particles beyond their cholesterol cargo and focus on their role in lipid transport. We discuss the evidence regarding novel HDL functions, including effects on glucose metabolism, and speculate on the implications for type 2 diabetes. HDL cholesterol is an imperfect biomarker of a highly complex and multifunctional lipid transport system, and we should now consider how new HDL markers more causally linked to cardiovascular complications could be adapted for clinical use. In the absence of a superior alternative, HDL cholesterol generally has value as a component of primary cardiovascular disease risk prediction models, including in people with type 2 diabetes. However, to avoid prognostic overgeneralisations, it is high time that the good cholesterol label is dropped.

The association between the DNAH11 rs10248618 SNP and serum lipid traits, the risk of coronary artery disease, and ischemic stroke

Previous genome-wide association studies have shown that the rs10248618 single nucleotide polymorphism (SNP) in the dynein axonemal heavy chain 11 gene (DNAH11) has been associated with serum high-density lipoprotein cholesterol (HDL-C) levels. However, little is known about such association in the Chinese population. The present study was performed to clarify the association between the DNAH11 rs10248618 SNP and serum lipid traits and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Guangxi Han population. Genotypes of the DNAH11 rs10248618 SNP in 1,213 unrelated patients (CAD, 600 and IS, 613) and 631 healthy controls were determined by snapshot technology. The genotypic and allelic frequencies of the SNP were significantly different between the CAD/IS patients and the controls (P < 0.01 for all). The CT/TT genotypes and the T allele were associated with an increased risk of CAD and IS (CAD: P < 0.01 for CT/TT vs. CC and T vs. C; IS: P < 0.01 for CT/TT vs. CC and T vs. C). The CT/TT genotypes in the healthy controls, but not in CAD or IS patients, were associated with a decreased serum HDL-C and apolipoprotein (Apo) A1 concentration. These results suggest that the DNAH11 rs10248618 SNP is associated with the risk of CAD and IS in our study population. It is likely to increase the risk of CAD and IS by reducing serum HDL-C and ApoA1 levels.

From High-Density Lipoprotein Cholesterol to Measurements of Function: Prospects for the Development of Tests for High-Density Lipoprotein Functionality in Cardiovascular Disease

The evidence is strong that biological functions contained in high-density lipoproteins (HDL) are antiatherogenic. These functions may track with HDL cholesterol or apolipoprotein A1 concentration to explain the strongly inverse risk curve for cardiovascular disease. Moreover, there are harmful as well as protective HDL subspecies in regard to cardiovascular disease, which could be responsible for paradoxical responses to HDL-directed treatments. Recent metabolic studies show that apolipoprotein A1-containing HDL is secreted into the circulation as mostly spherical cholesterol ester-rich lipoproteins that span the HDL size range. Most of the flux of apolipoprotein A1 HDL into and out of the circulation occurs in these spherical cholesterol-replete particles. Discoidal cholesterol-poor HDL comprises a minority of HDL secretion. We propose that much cholesterol in reverse cholesterol transport enters and exits medium and large size HDL without changing a size category, and its flux may be estimated provisionally from holoparticle clearance of cholesterol ester-rich HDL. An accurate framework for metabolism of HDL is essential to finding steady-state biomarkers that reflect HDL function in vivo. Whereas cholesterol efflux from cells to mainly discoidal HDL, mediated by ABCA1 (ATP-binding cassette transporter ABCA1), predicts cardiovascular disease, cholesterol transfers to spherical HDL also can be measured and may be relevant to protection against atherosclerosis. We propose several investigative paths on which human HDL biology may be investigated leading to convenient biomarkers of HDL quality and function having potential not only to improve risk prediction but also to more accurately target drug treatments.

Circulating metabolites and general cognitive ability and dementia: Evidence from 11 cohort studies

INTRODUCTION

Identifying circulating metabolites that are associated with cognition and dementia may improve our understanding of the pathogenesis of dementia and provide crucial readouts for preventive and therapeutic interventions.

METHODS

We studied 299 metabolites in relation to cognition (general cognitive ability) in two discovery cohorts (N total = 5658). Metabolites significantly associated with cognition after adjusting for multiple testing were replicated in four independent cohorts (N total = 6652), and the associations with dementia and Alzheimer's disease (N = 25,872) and lifestyle factors (N = 5168) were examined.

RESULTS

We discovered and replicated 15 metabolites associated with cognition including subfractions of high-density lipoprotein, docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. These associations were independent of classical risk factors including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and apolipoprotein E (APOE) genotypes. Six of the cognition-associated metabolites were related to the risk of dementia and lifestyle factors.

DISCUSSION

Circulating metabolites were consistently associated with cognition, dementia, and lifestyle factors, opening new avenues for prevention of cognitive decline and dementia.

Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease

Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field.

Mapping Atheroprotective Functions and Related Proteins/Lipoproteins in Size Fractionated Human Plasma

HDL has been shown to possess a variety of cardio-protective functions, including removal of excess cholesterol from the periphery, and inhibition of lipoprotein oxidation. It has been proposed that various HDL subparticles exist, each with distinct protein and lipid compositions, which may be responsible for HDL's many functions. We hypothesized that HDL functions will co-migrate with the operational lipoprotein subspecies when separated by gel filtration chromatography. Plasma from 10 healthy male donors was fractionated and the protein composition of the phospholipid containing fractions was analyzed by mass spectrometry (MS). Each fraction was evaluated for its proteomic content as well as its ability to promote cholesterol efflux and protect low density lipoprotein (LDL) from free radical oxidation. For each function, several peaks of activity were identified across the plasma size gradient. Neither cholesterol efflux or LDL antioxidation activity correlated strongly with any single protein across the fractions. However, we identified multiple proteins that had strong correlations (r values >0.7, p < 0.01) with individual peaks of activity. These proteins fell into diverse functional categories, including those traditionally associated with lipid metabolism, as well as alternative complement cascade, innate immunity and clotting cascades and immunoglobulins. Additionally, the phospholipid and cholesterol concentration of the fractions correlated strongly with cholesterol efflux (r = 0.95 and 0.82 respectively), whereas the total protein content of the fractions correlated best with antioxidant activity across all fractions (r = 0.746). Furthermore, two previously postulated subspecies (apoA-I, apoA-II and apoC-1; as well as apoA-I, apoC-I and apoJ) were found to have strong correlations with both cholesterol efflux and antioxidation activity. Up till now, very little has been known about how lipoprotein composition mediates functions like cholesterol efflux and antioxidation.

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.

Identification of Critical Paraoxonase 1 Residues Involved in High Density Lipoprotein Interaction

Paraoxonase 1 (PON1) is a high density lipoprotein (HDL)-associated protein with atherosclerosis-protective and systemic anti-oxidant functions. We recently showed that PON1, myeloperoxidase, and HDL bind to one another in vivo forming a functional ternary complex (Huang, Y., Wu, Z., Riwanto, M., Gao, S., Levison, B. S., Gu, X., Fu, X., Wagner, M. A., Besler, C., Gerstenecker, G., Zhang, R., Li, X. M., Didonato, A. J., Gogonea, V., Tang, W. H., et al. (2013) J. Clin. Invest. 123, 3815-3828). However, specific residues on PON1 involved in the HDL-PON1 interaction remain unclear. Unambiguous identification of protein residues involved in docking interactions to lipid surfaces poses considerable methodological challenges. Here we describe a new strategy that uses a novel synthetic photoactivatable and click chemistry-taggable phospholipid probe, which, when incorporated into HDL, was used to identify amino acid residues on PON1 that directly interact with the lipoprotein phospholipid surface. Several specific PON1 residues (Leu-9, Tyr-185, and Tyr-293) were identified through covalent cross-links with the lipid probes using affinity isolation coupled to liquid chromatography with on-line tandem mass spectrometry. Based upon the crystal structure for PON1, the identified residues are all localized in relatively close proximity on the surface of PON1, defining a domain that binds to the HDL lipid surface. Site-specific mutagenesis of the identified PON1 residues (Leu-9, Tyr-185, and Tyr-293), coupled with functional studies, reveals their importance in PON1 binding to HDL and both PON1 catalytic activity and stability. Specifically, the residues identified on PON1 provide important structural insights into the PON1-HDL interaction. More generally, the new photoactivatable and affinity-tagged lipid probe developed herein should prove to be a valuable tool for identifying contact sites supporting protein interactions with lipid interfaces such as found on cell membranes or lipoproteins.