LIPIDOME ASSOCIATION WITH VASCULAR DISEASE AND INFLAMMATION IN HIV+ UGANDAN CHILDREN

Abstract

Objective:

HIV infection and antiretroviral therapy (ART) have both been linked to dyslipidemia and increased cardiovascular disease (CVD). The relationships among the lipidome, immune activation, and subclinical vascular disease in children with perinatally acquired HIV (PHIV) have not been investigated.

Methods:

Serum lipid composition, including 13 lipid classes constituting 850 different lipid species were measured by direct infusion-tandem mass spectrometry in samples from 20 ART-treated PHIV and 20 age- and sex-matched HIV- Ugandan children. All participants were between 10–18 years of age with no other known active infections. PHIVs had HIV-1 RNA level ≤50 copies/mL. In addition, common carotid artery intima-media thickness (IMT), as well as plasma marker of systemic inflammation (hsCRP, IL6, sTNFRa I), monocyte activation (soluble CD14 and CD163), and T-cell activation (expression of CD38 and HLA-DR on CD4+ and CD8+) were evaluated.

Results:

Median age (Q1,Q3) of study participants was 13 years (11, 15), 37% were males, 75% were on an NNRTI- based ART regimen. The concentrations of CE, LCER, PC, and SM lipid classes were significantly increased in serum of PHIV compared to HIV (P≤0.04). Biomarkers associated with CVD risk including hsCRP, sCD163, and T cell activation were directly correlated with lipid species in PHIV (P≤0.04). Contents of free fatty acids including palmitic (16:0), stearic (18:0), and arachidic acid (20:0) were positively correlated with IMT in PHIV.

Conclusion:

Serum lipidome is altered in young virally suppressed PHIV on ART. A direct association between inflammation and lipid species known to be associated with CVD was observed.

INTRODUCTION

The vast majority of people living with human immunodeficiency virus (HIV) reside in low-and-middle income countries-57% in eastern and southern Africa ^[1]. Children and adolescents living with perinatally acquired HIV (PHIV) are unique because they will reach adulthood with histories of in-utero exposure to HIV, immune activation, inflammation, and long-term antiretroviral therapy (ART)– all of which contribute to non-infectious complications, specifically cardiovascular and metabolic. Several studies have shown cardiometabolic complications in PHIV, including vascular dysfunction and insulin resistance ^[2–9]. There are no standards or thresholds used to characterize cardiometabolic complications in childhood.

Several comorbidities, including metabolic and cardiovascular diseases (CVD), have been associated with heightened immune activation and inflammation despite viral suppression in adults with HIV. Our prior data suggested that immune activation persists in PHIV despite viral suppression with ART ^[10]. Multiple factors likely contribute to immune activation in ART-treated HIV infection, including low level viral replication ^[11] gut dysfunction, and presence of pro-inflammatory lipids ^[12].

Lipidomic analyses have revealed associations of lipid classes and specific lipid species with several diseases, including CVD ^[13–18]. In this regard, ceramides and phosphatidylcholines (PCs) containing saturated (SaFA) and monounsaturated fatty acyl chains (MUFA) are associated with risks of CVD outcomes ^[19–21], while PCs containing polyunsaturated fatty acyl chains (PUFA) are inversely associated with risks of CVD outcomes ^{[22, 23]}. Importantly, these findings were independent of total cholesterol content ^[24]. Association of lipid profiles with HIV infection ^[25] and ART ^[26] have been limited to lipid categories ^{[27, 28]}, without identifying specific classes or individual species. Traditional lipid panels commonly obtained in clinical practice are insufficient to assess CVD risk in people living with HIV ^[29]. In addition, no studies have used lipidomics to assess the association of lipid biomarkers (SaFA, Ceramides, Cholesterol Esters) with CVD risk in PHIV or explored whether these associations are different compared to an HIV-uninfected population. In this pilot study, differences in the serum lipidome between PHIV on ART and HIV- children are described, and associations with subclinical vascular disease and markers of inflammation, immune activation, and gut integrity are examined.

METHODS

Study Design

This is a cross-sectional analysis of baseline data from an observational cohort study of PHIV and HIV- children prospectively enrolled at the Joint Clinical Research Center in Kampala, Uganda. The study was approved by the Research Ethics Committee of the Ugandan National Council of Science and Technology as well as the institutional review board of the University Hospitals Cleveland Medical Center, Cleveland, Ohio. All participants were 10–18 years of age. PHIV participants were on ART for at least 2 years with a stable regimen for at least the last 6 months with HIV-1 RNA < 50 copies/mL. HIV- children were tested during clinic visits to confirm HIV seronegative status. Participants who self-reported or were documented as having acute infection (malaria, tuberculosis, helminthiasis, pneumonia, meningitis), as well as moderate or severe malnutrition and diarrhea in the last 3 months were excluded from the study. In addition, participants with diabetes and heart disease and adolescents with pregnancy or intent to become pregnant were also excluded. For this substudy, we selected participants in the highest IMT quartile who also had samples available.

Study Evaluations

Blood was drawn after an 8-hour fast. Blood was processed and plasma, serum, and peripheral blood mononuclear cells (PBMCs) were cryopreserved for shipment to University Hospitals Cleveland Medical Center, Cleveland, Ohio. A Material Transfer Agreement, approval from the Uganda National Council of Science and Technology as well as a permit from the Center for Disease Control were obtained.

Cellular markers of monocyte and T-cell activation

Monocyte and T-cells were phenotyped by flow cytometry ^[30]. CD4⁺ and CD8⁺ T-cell activation was defined as co-expression of CD38 and HLA-DR. Monocyte subset proportions were determined by the relative expression of CD14 and CD16.

Inflammation, soluble immune activation, and gut markers

Biomarkers were selected based on prior data from PHIV individuals in Uganda as well as from adults living with HIV showing association with CVD and other end organ diseases. Soluble CD14 (sCD14, R &D Systems, Minneapolis, Minnesota) is a soluble marker of monocyte activation, and is associated with mortality and progression of atherosclerosis ^[26]. The remaining biomarkers correlate with cardiometabolic complications, or drive other hallmarks of immune dysregulation in HIV. Plasma markers of monocyte activation (sCD163), systemic inflammation (sTNFRI), high sensitivity C-reactive protein (hsCRP), IL-6 and oxidized lipids (oxidized LDL) were measured by ELISA (R &D Systems, Minneapolis, Minnesota, USA and ALPCO, Salem, New Hampshire, USA and Mercodia, Uppsala, Sweden). The intra-assay variability ranged between 4–8% and inter-assay variability was less than 10% for all markers. All assays were done at Dr Funderburg’s laboratory at Ohio State University, Columbus, OH. Laboratory personnel were blinded to group assignments.

Subclinical vascular disease

Intima media thickness (IMT) and pulse wave velocity (PWV) measurements were performed in a standardized fashion as previously described ^[31]. B mode ultrasound scan of the carotid arteries was performed using a Philips iU22 ultrasound system with 12–3 MHz broadband linear array probe (Philips, Andover, MA). An experienced reader (DL), blinded to HIV status, measured the IMT offline using semi-automated edge detection software (Medical Imaging Applications LLC, Coralville, IA). PWV was measured by applanation tonometry (Vicorder, SMT Medical, Wurzburg, Germany). An average of three measurements was used for data analyses. Higher velocity measurements correspond to greater arterial stiffness.

Lipidomic analysis

Lipidomic analysis of fasting serum samples were performed using the Sciex Lipidyzer platform (Sciex, MA, USA). Lipidyzer is a validated platform for quantitative lipidomics that utilizes a 5500 QTRAP-MS with SelexION differential ion mobility technology for sensitive and selective lipid analysis of the following lipid classes: cholesterol ester (CE), ceramide (CER), diacylglycerol (DAG), dihydroceramide (DCER), free fatty acid (FFA), hexosylceramide (HCER), lactosylceramide (LCER), lysophysophatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), and triacylglycerol (TAG). Lipids were extracted from serum samples using a modified Bligh-Dyer method where methylene chloride was used as one the extraction solvents instead of chloroform. Approximately 1,100 blood lipids spanning 13 lipid classes were profiled and quantitated using optimized mass spectrometry/mass spectrometry transitions for the targeted serum lipid species in addition to the stable isotope-labeled internal standards used for quantification. Results were expressed as concentration (μM) of individual lipid species, of lipids grouped by class, and overall fatty acid composition and fatty acid composition within each lipid class. In addition, lipid data was expressed as %mol contribution to the sum of all measured lipids. Lipidome assays were performed in the Nutrient and Phytochemical Analytic Shared Resource at the Ohio State University.

Statistical Analyses

Data qualities were studied rigorously using frequency analysis, graphs and descriptive statistics. Prior to testing significant difference, statistical distributions of the variables were also examined. Differences in the concentration of lipids and free fatty acid levels between PHIV and HIV–were assessed using Fisher’s exact tests and Wilcoxon tests, as appropriate. Associations among lipid levels and immune activation marker and IMT were analyzed using Spearman correlations. P-value less than 0.05 is considered statistically significant. All the statistical analyses were performed using software R 3.4.1.

RESULTS

Patient Characteristics

Patient demographic information is provided in Table 1. There was no difference in age, sex, BMI and cholesterol between the 40 participants included in this substudy and the original 197 participants (p≥0.352). Median [interquartile range] age was 13 [11.42, 14.70] years and 62% were females. Among PHIV, all had undetectable viral load (<20 copies/mL) and median CD4 cell count was 1074.50 [597.00, 1485.50]. The majority were on a non-nucleotide reverse transcriptase inhibitor-based regimen (either nevirapine or efavirenz), 65% were on abacavir and 90% of participants on lamivudine. All PHIV patients were on cotrimoxazole.

Table 1:

Baseline Demographics

	Overall (n=40)	PHIV (n=20)	HIV− (n=20)	p
Age (years)	12.87 [11.42, 14.70]	12.74 [11.99, 14.47]	13.27 [11.26, 15.05]	0.892
Female sex (%)	25 (62.5)	11 (55.0)	14 (70.0)	0.514
Body mass index (kg/m2)	17.96 [15.86, 19.68]	17.43 [15.83, 18.32]	18.82 [16.19, 22.20]	0.074
Waist:hip ratio	0.87 [0.82, 0.90]	0.88 [0.87, 0.90]	0.82 [0.81, 0.88]	0.016
Systolic blood pressure (mmHg)	109.50 [102.75, 115.00]	103.00 [100.75, 109.25]	114.50 [110.50, 119.00]	0.001
Diastolic blood pressure (mmHg)	65.50 [61.00, 71.00]	63.50 [60.00, 66.25]	68.00 [62.75, 76.25]	0.045
Total Cholesterol (mg/dL)	147.00 [132.00, 169.00]	151.50 [139.25, 172.00]	142.00 [120.00, 156.50]	0.196
HDL (mg/dL)	47.20 [36.20, 55.30]	54.40 [46.58, 58.95]	39.60 [33.25, 47.25]	0.004
LDL (mg/dL)	81.00 [66.00, 103.00]	82.50 [66.75, 103.00]	81.00 [65.50, 103.00]	0.964
VLDL (mg/dL)	18.00 [13.25, 25.75]	20.00 [12.50, 27.50]	18.00 [15.00, 22.50]	0.671
Triglycerides (mg/dL)	92.00 [69.50, 127.00]	92.00 [62.75, 133.75]	92.00 [75.00, 112.50]	0.704
IMT (mm)	0.62 [0.56, 0.71]	0.72[0.68, 0.81]	0.56[0.54, 0.57]	<0.001
Viral load <50 copies/mL (%)	20 (100)	20 (100)
CD4 cell count (cells/uL)	1074.50 [597.00, 1485.50]	1074.50 [597.00, 1485.50]
CD4%	35.50 [27.75, 42.50]	35.50 [27.75, 42.50]
CD4 cell count nadir	715.50 [428.25, 1227.25]	715.50 [428.25, 1227.25]
Nucleotide Reverse
Transcriptase Inhibitor (%)
Abacavir		13 (65)
Lamivudine		18 (90)
Tenofovir		2 (10)
Zidovudine		4 (20)
Non Nucleotide Reverse
Transcriptase Inhibitor (%)
Nevirapine		2 (10)
Efavirenz		12 (60)
Lopinavir/ritonavir		6 (30%)

Median [interquartile range]

Lipidome alterations

There was no significant difference between levels of individual lipid species of PHIV and HIV- groups. However, the concentration of several lipid classes including CE, LCER, PC, and SM was greater among PHIV compared to HIV- participants (p≤0.043, Table 2). The fatty acid concentration of several lipid classes was also altered in HIV (Figure 1). Specifically, the serum concentration of SaFA-containing CER and PC, including CER 18:0 (p=0.030), 20:0 (p= 0.013) and 22:0 (p=0.042), and PC 14:0 (p=0.015), 16:0 (p=0.033), 17:0 (p=0.012) and 18:0 (p=0.009), lipids species known to be associated with CVD were significantly increased in PHIV.

Table 2:

Comparison of lipid class composition and concentrations between groups

	Lipid composition (mol %)			Lipid concentrations (μm)
Lipid Species	PHIV	HIV−	p	PHIV	HIV−	p
CE	39.85 [37.58, 42.35]	38.98 [36.69, 41.25]	0.445	4164.77 [3638.64, 5068.11]	3568.43 [3167.47, 4187.79]	0.043
CER	0.07 [0.05, 0.07]	0.06 [0.06, 0.07]	0.355	6.90 [5.61, 8.24]	5.97 [5.13, 6.40]	0.072
DAG	0.47 [0.36, 0.57]	0.48 [0.41, 0.63]	0.495	47.61 [35.82, 70.22]	45.35 [32.42, 58.69]	0.478
DCER	0.00 [0.00, 0.00]	0.00 [0.00, 0.00]	0.494	0.21 [0.19, 0.27]	0.21 [0.19, 0.30]	0.878
FFA	12.03 [8.93, 13.99]	12.19 [8.47, 14.03]	0.904	1318.37 [1048.96, 1416.64]	1094.17 [849.45, 1311.29]	0.081
HCER	0.04 [0.03, 0.04]	0.04 [0.04, 0.05]	0.133	3.82 [3.58, 4.45]	3.82 [3.11, 4.44]	0.718
LCER	0.04 [0.03, 0.05]	0.04 [0.03, 0.04]	0.351	4.16 [3.51, 4.83]	3.13 [2.82, 3.94]	0.002
LPC	3.38 [3.01, 3.73]	3.50 [3.23, 3.92]	0.383	361.68 [294.34, 416.20]	328.37 [269.74, 428.86]	0.478
LPE	0.03 [0.02, 0.03]	0.03 [0.02, 0.03]	0.882	2.92 [2.27, 3.43]	2.41 [2.21, 3.23]	0.314
PC	24.21 [22.23, 25.43]	22.56 [21.21, 25.44]	0.369	2555.17 [2239.23, 2785.93]	2166.49 [1972.78, 2335.45]	0.014
PE	1.24 [1.20, 1.38]	1.20 [1.14, 1.38]	0.341	140.64 [109.05, 155.89]	113.52 [99.76, 136.76]	0.072
SM	6.20 [5.90, 6.41]	6.03 [5.90, 6.63]	0.989	654.83 [578.43, 724.36]	591.81 [517.41, 641.29]	0.017
TAG	13.54 [10.76, 15.76]	15.14 [12.21, 18.49]	0.327	1326.86 [975.65, 2094.81]	1342.40 [1010.93, 1851.17]	0.862

cholesterol ester (CE), ceramide (CER), diacylglycerol (DAG), DCER, fatty acid (FFA), hexosylceramide (HCER), lactosylceramide (LCER), lysophysophatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), triacylglycerol (TAG)

Bolded values represent p≤0.05

Figure 1:

Median concentrations of lipids

CE: cholesterol esters; CER: Ceramides; FFA: Free Fatty Acids; LCER: Lactosylceramides; PC: Phosphatidylcholines; SM: sphingomyelins- Dot plots showing the median lipid levels in children with perinatally acquired HIV (PHIV) and HIV negative children (HIV-). Horizontal lines denote the interquartile range.

Associations with inflammatory markers

Considering each lipid species separately, LPCs and SMs correlated significantly with several markers of systemic inflammation, monocyte and T cell activation in PHIV as highlighted in figure 2a, 2c. Notable trends include PC 18:2, 20:1, SM 16:0, 20:1 and 26:0 which were correlated with the monocyte activation marker sCD163 (r=0.53–0.62, p≤0.01). PC18:2 and SM 26:0 were also correlated with hsCRP, a marker of systemic inflammation (r=0.45–0.48, p≤0.04). PC 22:4 correlated with activated CD8+ T cells expressing HLA-DR and CD38 (r=0.51, p=0.03).

Figure 2:

Heat map correlations between lipids (photosphotidylcholine and sphingomyelin) and inflammatory markers in PHIV and HIV-

A) Heat map showing the correlation between phosphatidylcholine in children living with perinatally acquired HIV (PHIV) and B) HIV negative children and c) sphingomyelins in PHIV and D) HIV negative children

hsCRP: high sensitivity C reactive protein (ng/mL), IL-6: interleukin 6 (pg/mL), sCD14 and 163: soluble CD14 and soluble CD163 (pg/mL), sTNFR-I: soluble tumor nectrosis factor α I (pg/mL), CD4 and CD8 T cells and CD4CD38: CD4+HLA-DR+ T cells, CD8CD38:CD8+HLA-DR+ T cells; PC: phosphatidylcholine; SM: sphingomyelin

*for p <0.05;

On the other hand, several LPCs and SMs were inversely associated with hsCRP and sCD14 in HIV- participants (Figure 2 b, 2d).

Associations with subclinical vascular disease

Similarly, when considering each lipids species, FFA correlated significantly with IMT. By reporting each free fatty acid measured, the overall trends among the SaFAs and UFAs can be appreciated between PHIV and HIV-. We found direct, but not significantassociations among saturated FFA 16:0, 18:0, 20:0 and IMT in PHIV and only FFA 20:1 (r=0.48, p=0.03) was significantly associated with IMT in PHIV. No other lipid species were significantly correlated with IMT in PHIV.

Nearly all free fatty acids were inversely related to IMT in the HIV- participants (Figure 3). Additionally, CE (24:0), LCER (16:0, 24:1) were inversely related to IMT in HIV- (r≤0.40, p≤0.03).

Figure 3:

Correlation of Free Fatty Acids with IMT among PHIV and HIV- participants

A) Correlation of FFA with IMT in PHIV, B) Correlation of FFA with IMT in HIV-

FFA: Free Fatty Acids, IMT: intima media thickness, PUFA: polyunsaturated fatty acids, MUFA: monounsaturated fatty acids, SaFA: saturated fatty acids

*= p value ≤0.05, ** for p<0.01

Discussion

Association of lipid profiles with HIV infection and ART, are often limited to broad categories of lipids, without identifying specific classes and species. To our knowledge, no lipidomics investigations in conjunction with immune activation or subclinical vascular disease measurements have been published in PHIV either in industrialized countries or sub-Saharan Africa. In this pilot study, we found that the lipidome is altered in young virally suppressed PHIV on ART, with significant alterations in five major lipid classes. In addition, we found association between lipid species and marker of inflammation, immune activation and subclinical vascular disease in PHIV.

HIV infection, its treatment with ART, and the inflammatory consequences of HIV infection, all contribute to perturbations in metabolic and lipid profiles^{[32, 33]}. ART-treated HIV infection is often associated with decreases in high density lipoprotein (HDL) levels, and increases in low-density lipoprotein (LDL), triglycerides, and total cholesterol levels^[32]. Yet, these basic lipid panels provide insufficient characterization and insight as to the fundamental metabolic perturbations in HIV infection, and their relationship to both inflammation and CVD risk^[29]. The Lipidomic field in HIV is still in its infancy. Altered lipid classes have been associated with HIV infection^[34]. We have investigated the lipidome in a cross sectional study of HIV infected and uninfected adults and in a longitudinal study of adults initiating ART and found significantly elevated total free fatty acid levels in adults living with HIV despite similar traditional lipid panels between the groups ^{[35, 36]}. The chain length and saturation are two main characteristics of lipids and we found decreased proportional amounts of free PUFAs and PUFA containing LPC species in adults living with HIV. In this study in PHIV, we did not find a difference in lipid composition, however, we demonstrated several differences in the lipidomes of our participants, including significantly elevated SaFA concentrations in PHIV. In addition, we measured increased CER and LPC species enriched for SaFAs in PHIV. This is significant as fatty acyl composition in CER and LPC determine their atherogenic properties with SaFA-containing CERs and LPCs tend to have pro-atherogenic properties, and conversely, PUFA-containing CERs and LPCs tend to be anti-atherogenic^{[37, 38]}. When comparing serum fatty acids concentrations in PHIV to those in HIV+ adults on ART^[35], or adults with inflammatory conditions such as nonalcoholic fatty liver disease^[39], we find that levels of SaFA are nearly two folds higher in Ugandan PHIV, although the differences in methodology may account for some discrepancy, this suggests that this population likely has a unique lipidomic signature. We hypothesize that we several variables may influence lipid levels in this population including ART regimens, diet and physical activity which we were not able to explore in this pilot study.

Lipids and their metabolites can affect the differentiation of immune cells, particularly, monocytes and T cells, as well as their activation and function, with important consequences for the balance between anti- and pro-inflammatory signals in diseases. SaFA induce inflammasome activation and Toll like receptor signaling^[40], in contrast PUFAs inhibit inflammation and modulate fatty acid oxidation pathway ^[41]. To our knowledge, only a few studies have investigated the role of the lipidome and inflammation in HIV. Dr. Funderburg has reported that biomarkers associated with CVD risk (IL-6, sCD14, TNFR1),^[42–47] were directly related to SaFA composition, and inversely to PUFA composition in both HIV- individuals and HIV+^{[35, 36]}. Further, FFA and CER levels were associated with a pro-atherogenic transcriptional and functional phenotype of monocyte derived macrophages in HIV+ adults^[48]. In the Women’s Interagency HIV Study and Multicenter AIDS Cohort study, ceramides showed strong correlations with monocyte/macrophage activation inflammatory markers^[49]. We found that PCs and SMs were positively associated with systemic inflammation, monocyte and T cell activation in PHIV, but an inverse relationship with hsCRP was found in HIV- participants regardless of the number of double bonds.

Plasma levels of SaFA and UFA have been associated with CVD^[16], including non-calcified coronary plaque^[18], in HIV uninfected participants. Increased levels of PUFAs, including eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) are associated with reduced risk of myocardial infarction,^[17] and serum EPA and DHA levels are inversely associated with soft coronary plaque scores^[18]. The concentrations of CER and LPCs and their FA composition, are also linked to disease risk; levels of LPC are increased in CVD^{[50, 51]}, renal failure^[52], diabetes^[53], and ovarian cancer^[54]. In a large study of 990 uninfected adolescents (12–18 years), LPCs, shown to predict CVD outcomes in older adults, were associated with multiple CVD risk factors including visceral abdominal fat, blood pressure, insulin resistance and atherogenic dyslipidemia^[55]. In HIV, a prospective analysis in the Women’s Interagency HIV Study and Multicenter AIDS Cohort study, triacylglycerol (TAG) and PC with saturated chains showed an association with increased risk of carotid artery plaque as measured by IMT over time ^[56]. In these cohorts, elevated plasma levels of CERs were associated with progression of carotid artery atherosclerosis ^[49]. In our study, we found direct, although not statistically significant,associationsamong free fatty acids palmitic, stearic and arachidic acid and IMT in PHIV, lipids that have been previously associated with inflammation^{[35, 36]} and CVD risk^[57–59]. Surprisingly, nearly all associations were inversely related in HIV-. This suggests that even without traditional risk factors, and despite normal total cholesterol and LDL levels, advancements in mass spectrometry may enable the identification and quantification of new, low abundance, lipid species in youth that may be associated with CVD risk factors and serve as novel biomarkers of preclinical CVD.

The inclusion of a well matched control group from the same area in Uganda is a strength of our study, as participants did not differ in demographics and important risk factors. The comprehensive evaluation of inflammation and immune activation is an additional strength. We cannot prove causal relationships or exclude the possibility of residual confounding due to the cross sectional nature of our analysis. Additionally, due to the small sample size, we were unable to assess the relationship of ART on the lipidome and may have been underpowered to truly detect differences in lipid species.

Further studies are needed to extend our findings and investigate the complex and in-depth interactions among the lipid, immune activation, specific ART regimens and subclinical vascular disease in ART- treated PHIV in Uganda in a longitudinal fashion. This may reveal the identification and quantification of new lipid species in PHIV that may serve as novel biomarkers of preclinical CVD.