Skip to main content
Download PDF
Download ePub

MASLD in persons with HIV is associated with high cardiometabolic risk as evidenced by altered advanced lipoprotein profiles and targeted metabolomics

Lipids in Health and Disease volume 23, Article number: 339 (2024) Cite this article

Abstract

Background

Metabolic dysfunction associated steatotic liver disease (MASLD) is associated with increased cardiovascular disease (CVD) risk in persons with HIV (PWH). The lipidomic and metabolomic alterations contributing to this risk are poorly understood. We aimed to characterize the advanced lipoprotein and targeted metabolomic profiles in PWH and assess if the presence and severity of MASLD influence these profiles.

Methods

This is a cross-sectional analysis of a prospectively enrolled multicenter cohort. PWH without alcohol abuse or known liver disease underwent vibration-controlled transient elastography for controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Lipidomic and metabolomic profiling was undertaken with nuclear magnetic resonance (NMR) spectroscopy. Hepatic steatosis was defined as CAP ≥ 263 dB/m and clinically significant fibrosis (CSF) as LSM ≥ 8 kPa. Logistic regression models assessed associations between MASLD, CSF and lipidomic and metabolic parameters.

Results

Of 190 participants (71% cisgender male, 96% on antiretroviral therapy), 58% had MASLD and 12% CSF. Mean (SD) age was 48.9 (12.1) years and body mass index (BMI) 29.9 (6.4) kg/m2. Compared to PWH without MASLD (controls), PWH with MASLD had lower HDL-C but higher total triglyceride, VLDL-C, branched-chain amino acids, GlycA, trimethylamine N-oxide levels, Lipoprotein-Insulin Resistance and Diabetes Risk Indices. There were no significant differences in these parameters between participants with MASLD with or without CSF. In a multivariable regression analysis, MASLD was independently associated with changes in most of these parameters after adjustment for age, gender, race/ethnicity, type 2 diabetes mellitus, BMI, and lipid lowering medications use.

Conclusions

MASLD in PWH is independently associated with altered advanced lipoprotein and targeted metabolic profiles, indicating a higher CVD risk in this population.

Introduction

With improving access to antiretroviral therapy (ART), people with HIV (PWH) are aging and becoming at higher risk for cardiovascular disease (CVD) than the general population [1]. Established CVD risk factors, such as central obesity, hypertension, hyperglycemia, smoking, and abnormal lipids can help identify some patients at risk for CVD who may benefit from interventions. However, cardiovascular events may develop in people classified as being at low or intermediate CVD risk, or in patients already achieving target lipids goals with lipid-lowering therapy [2]. Recent lipidomic and metabolomic studies using quantitative nuclear magnetic resonance (NMR) spectroscopy have demonstrated an association between increased lipoprotein subclasses, such as triglyceride (TG)-rich lipoprotein (TRL), small low density lipoprotein (LDL) particles, as well as raised metabolites GlycA and branched chain amino acids (BCAA) with poor cardiometabolic outcomes [3,4,5,6,7]. In PWH, two nested case-controlled studies documented the adverse effects of small dense LDL and protective impact of large high-density lipoprotein (HDL) particles on CVD [8, 9].

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease worldwide, affecting an estimated 30% of the world population [10]. MASLD is also the most common liver disease in PWH, estimated to affect 50-64% of this population [11, 12]. Obesity, insulin resistance, metabolic syndrome, and genetic polymorphisms influence risk of development and progression of MASLD [13]. Variants in PNPLA3 and TM6SF2 are associated with the risk of steatosis, fibrosis, steatohepatitis, and liver cancer in the general population [14, 15]. PNPLA3 variants impede lipolysis, while the TM6SF2 variants impair lipidation and export of very low-density lipoproteins (VLDL) [16, 17]. In PWH, however, only a few limited studies investigated the effects of these genetic polymorphisms on MASLD risk and severity with conflicting signals [18,19,20] .

Patients with MASLD in either the general population or PWH are enriched with coexisting metabolic conditions and as a result are vulnerable to CVD [21, 22]. Lipidomic studies in patients with MASLD using NMR documented a characteristic atherogenic pattern, i.e. enrichment and enlargement of TRL, as well as a shift of LDL and HDL from large to small particles [23,24,25]. Among these lipoprotein derangements, small LDL particles had been documented to correlate with higher CVD risk [26]. A recent study demonstrated MASLD was associated with higher CVD risk in PWH as determined by Atherosclerotic Cardiovascular Disease Risk score [27]. However, little is known about lipidomic and metabolomic alterations associated with increased CVD risk in PWH who have MASLD.

Our aims were to investigate whether MASLD in PWH is associated with changes in lipidomic and metabolomic parameters linked to CVD, and whether MASLD severity, defined by absence or presence of clinically significant fibrosis (CSF), influenced these changes.

Methods

Study participants

We prospectively enrolled consecutive adult PWH who agreed to participate and provided written informed consent from outpatient HIV clinics at three centers (Indiana University, Massachusetts General Hospital, and UTHealth-Houston) between 2018 and 2022. The inclusion criteria included age 18 years and more; documented HIV infection defined by a positive HIV antibody assay and/or detectable HIV-1 RNA; stable antiretroviral (ART) regimen for 3 months before enrollment for those on ART at the time of study enrolling. We excluded those with evidence of or established hepatitis B or C co-infection or other liver diseases. To evaluate the amount of alcohol consumption, Alcohol Use Disorders Identification Test (AUDIT) questionnaire was provided to each participant. AUDIT is a well validated, simple test which contains 10 questions and allows the investigator to quantify participants’ daily drinks [28, 29], and to determine if a person has a risky drinking pattern or alcohol use disorder. Participants with a score of 8 or above were considered to have a strong likelihood of hazardous drinking, and therefore, were excluded from analysis. For this analysis, we included participants with fasting plasma samples. This study protocol had been reviewed and approved by each site’s the Institutional Review Board.

Lipoprotein and metabolite profiling by NMR spectroscopy

Venous blood was collected after a minimum fasting period of six hours. Ethylenediaminetetraacetic acid (EDTA) plasma samples were obtained and aliquots were frozen at -80 °C until analysis. NMR LipoProfile® testing [30, 31] was deployed on a Vantera® NMR Clinical Analyzer (Morrisville, NC) which provides average sizes for three lipoprotein classes, 33 concentrations of 24 lipoprotein particle subclasses, several small molecule metabolites, and GlycA in a single proton NMR spectrum from a plasma or serum specimen [30,31,32]. The results for these parameters were reported using the latest LP4 deconvolution algorithm [33]. Descriptions and diameter ranges of the lipoprotein classes and subclasses have been reported previously. Linear regression of the lipoprotein subclass signal areas against serum lipid and apolipoprotein levels measured by chemical assays in a large health study population (n = 698) provided the conversion factors to generate NMR-derived concentrations of total cholesterol, triglycerides (TG), the TG and cholesterol in the triglyceride-rich lipoproteins or TRL (TRL-TG and TRL-C). Results for LDL-C and HDL-C, apolipoprotein B (ApoB) and apolipoprotein A-I (ApoA-I) levels were determined using partial least square (PLS) regression method [34]. NMR-derived concentrations of these parameters are highly correlated with those measured by standard chemistry methods. Details regarding the NMR quantification of the BCAAs, citrate, and ketone bodies have been previously reported [35, 36]. Trimethylamine N-oxide (TMAO), betaine, and choline were quantified as previously described. Assay development, analytical performance evaluation and clinical validation of the Lipoprotein Insulin Resistance Index (LP-IR) (0 − 100; least to most insulin resistant), Diabetes Risk Index (DRI) (1 − 100; least to greatest risk of developing T2D), Metabolic Malnutrition Index (MMX), Inflammation Vulnerability Index (IVX), and Metabolic Vulnerability Index (MVX) have also been reported [6, 7, 37]. LP-IR is based on particle numbers of very large, large TRL, small LDLP, large HDLP, and mean sizes of TRL, HDL, and LDL [6]. DRI is based on LP-IR, valine and leucine [7]. IVX combines GlycA and small HDL particles. MMX combines valine, leucine, isoleucine, and citrate. MVX combines IVX and MMX [37].

Data collection and vibration controlled transient elastography (VCTE)

The study physicians took history and performed physical examinations for each participant. Medical problems, including hypertension, diabetes, hyperlipidemia, were collected from patients’ interview, and were verified in their electronic medical records. Extensive data collection was done, including demographic (age, sex, race, and ethnicity), anthropometrics (body mass index [BMI] and waist circumference), vital signs, medical and medicinal history, latest laboratory and HIV data (CD4 + T cell count, HIV-1 RNA) within 6 months of enrollment, and current and prior ART classes [ritonavir-boosted protease inhibitors (PI/r), non-nucleoside reverse transcriptase inhibitors (NNRTI), nucleoside reverse transcriptase inhibitors (NRTI), and integrase inhibitors (INSTI)]. Adequate viral suppression was defined as participants with HIV-1 RNA < 200 copies/mL. The participants also underwent VCTE by Fibroscan® (Echosens, Paris, France) for controlled attenuation parameters (CAP) and liver stiffness measurement (LSM) by trained study staff. Fasting for at least 3 h before VCTE was required. Fibroscan® was performed by a maximum of 2 trained study staff. The use of the M versus XL probe was notified by Fibroscan® automatically. The final CAP and LSM measurements were recorded as the median values of 10 consecutive valid measurements, and they were expressed in dB/m and kPa, respectively. The LSM values were considered unreliable as medians with the interquartile range (IQR)/median > 30%. Participants with CAP ≥ 263 dB/m and an AUDIT < 8 were determined to have MASLD [38]. Those with LSM ≥ 8.0 kPa were classified to have clinically significant fibrosis [39].

Statistical methods

Numbers and percentages for categorical variables and mean ± standard deviation (SD) were used to describe the baseline characteristics of the participants. Differences between groups were evaluated using One-Way ANOVA or Kruskal-Wallis Test if not normal distribution. Our composite and ordinal categorical study outcome is as follows: Controls (non-MASLD and non-CSF) (0) vs. MASLD including MASLD and non-CSF [1], MASLD and CSF [2]. Ordinal logistic regression models were implemented to examine the association between the study outcome and the select participants’ variables. Non-MASLD and non-CSF was the comparator for all logistic regression analyses. We adjusted for age, sex at birth, and race/ethnicity in model 1, and in model 2 we included variables in model 1 in addition to BMI, diabetes, and lipid-lowering agents use. A p-value < 0.05 was considered statistically significant All statistical analyses were performed using Stata software, version 17 (StataCorp, College Station, TX, US).

Results

Patient characteristics

A total 190 patients were included (Table 1), with 135 cisgender males (71%), 59 (31%) Blacks, 67 (35%) Hispanic participants, mean (SD) age 48.9 (12.1) years, duration of HIV infection 14.1 (9.3) years, CD4 count 732.5 cells/mm3 (334.4), and BMI 29.9 (6.4) kg/m2. The prevalence of MASLD was 58%, CSF 12% and cirrhosis (LSM > 13 kPa) 3%. The majority of patients (96%) were on antiretroviral therapy.

Table 1 Characteristics of study participants
Full size table

There were 80 (42%) controls, 87 (46%) participants with MASLD without CSF, and 23 (12%) with MASLD and CSF (Table 1). There were significant differences between the groups in mean (SD) BMI, waist circumference, frequency of hypertension, diabetes and hyperlipidemia, use of statins or fibrates, levels of alanine transaminase (ALT), aspartate transaminase (AST), TG and HDL-C. There were no significant differences in mean age, sex at birth, ethnicity, time elapsed since diagnoses of HIV, HIV-RNA viral loads, mean CD4 + cell counts, the percentages of exposure to each ART class, or other laboratory parameters.

Lipidomic changes associated with MASLD

Compared to controls (Table 2), participants with MASLD (with or without CSF) had significantly higher total, very large, large, and medium TRL-P levels, higher mean TRL sizes, TRL-TG, TRL-C, TG, and VLDL-C levels, lower concentrations of large LDL-P, large HDL-P; H7P, H5P, and HDL, and lower mean sizes of LDL and HDL (all P < 0.05).

Table 2 Lipidomic parameters derived from NMR spectrometry, stratified by MASLD. Results based on univariate binary logistic regression models
Full size table

Differences in most of these lipidomic parameters between MASLD and controls remained significant after adjustment for age, sex at birth, race/ethnicity, BMI, diabetes, and statins/fibrates use (Table 3).

Table 3 Lipidomic parameters derived from NMR spectrometry, stratified by MASLD. Results based on multivariable ordinal logistic regression models
Full size table

In a sensitivity analysis (Supplemental Table 1), no significant differences were observed in lipoprotein parameters between participants with MASLD with or without CSF.

Metabolomic changes associated with MASLD

Compared to controls (Table 4), participants with MASLD (with or without CSF) had significantly higher levels of total BCAA, valine, leucine, isoleucine, alanine, GlycA, LP-IR index, and DRI, TMAO and choline concentrations.

Table 4 Metabolites derived from NMR spectrometry, stratified by MASLD. Results based on univariate binary logistic regression
Full size table

The differences in levels of total BCAA, valine and alanine, as well as LP-IR and DRI remained significantly higher in participants with MASLD after adjustment for age, sex at birth, race/ethnicity, BMI, diabetes, and statins/fibrates use (Table 5).

Table 5 Metabolites derived from NMR spectrometry, stratified by MASLD and clinically significant fibrosis. Results based on multivariable ordinal logistic regression models
Full size table

In a sensitivity analysis (Supplemental Table 2), no significant differences were observed in the metabolites levels between participants with MASLD with or without CSF.

Discussion

Both MASLD and HIV are associated with increased risk of CVD [40, 41]. Indeed, CVD is a leading cause of death in patients with MASLD [42, 43]. Thus, understanding the lipidomic and metabolomic alterations associated with CVD risk in PWH and MASLD is important. This study provides a detailed characterization of changes in advanced lipoprotein profiles and targeted metabolites associated with MASLD in a diverse cohort of PWH. Atherogenic alterations in lipids and lipoprotein parameters are observed in PWH who have MASLD but fibrosis severity in MASLD does not appear to accentuate these changes. Together with increases in different metabolite levels, these changes are associated with hepatic and peripheral insulin resistance and elevated risk for CVD in PWH.

In addition to rising serum TG and VLDL-C levels, lipidomic profiling in this study showed TG-rich lipoproteins increase, enlarge, and carry more TG and cholesterol in PWH with MASLD. It also showed a reduction in the number of large HDL and large LDL particles and size of HDL and LDL. These lipidomic derangements are characteristic of atherogenic dyslipidemia which is driven by insulin resistance [44]. Overproduction of VLDL/TRL and raised plasma TG levels enhance production of TG-rich LDL and HDL, both catabolized rapidly, resulting in a shift from larger towards small LDL and HDL particles, and a decrease in HDL [45, 46]. These derangements had been linked to CVD risk in patients with MASLD and other conditions such as diabetes, obesity, and polycystic ovarian syndrome [5, 26, 47].

While some studies had investigated the associations between HIV or ART and atherogenic dyslipidemia [8], detailed characterization of the lipidomic profile of PWH and MASLD has not been explored. Khalili et al. recently reported that in patients with HIV-hepatitis B virus coinfection, fatty liver was significantly associated with higher concentrations of TG and small dense LDL particles [48]. The results from our HIV mono-infection cohort support these findings and more comprehensively demonstrate the alterations of TRL parameters and sizes of lipoprotein fractions.

It is interesting to note that the strength of association between MASLD and lipidomic and metabolomic parameters in this study showed minimal to small changes from the univariate to the multivariate models. This may suggest in this population of PWH on ART, MASLD is likely the main independent driver of these associations and highlights the key role of the liver in lipid metabolism and metabolite processing.

While some studies had demonstrated more pronounced atherogenic dyslipidemia in MASLD patients compared with those without, in either general population or PWH [24, 48], studies addressing the differences of lipidomic profile in MASLD patients with variable severity are sparse. DeFilippis et al. categorized 3362 participants in the Multi-Ethnic Study of Atherosclerosis cohort to no, mild, moderate, and severe MASLD according to their liver/spleen attenuation ratios on computed tomography and demonstrated an associations between the severity of steatosis with lipoprotein particle concentrations and sizes [49]. Amor et al. similarly reported more pronounced atherogenic lipidomic profile in the participants with more severe steatosis as estimated by the fatty liver index [23]. In this study, we assessed the association of MASLD severity as defined by presence or absence of CSF with lipids and lipoprotein parameters. While we show similar atherogenic lipidomic changes with the presence of MASLD, we did not observe a significant association between increasing severity of fibrosis in the setting of MASLD and these changes.

In patients with MASLD, elevation of some amino acids, including glutamate, tyrosine, alanine, and BCAAs correlated with disease severity, and was thought of as an adaptative response to hepatic inflammation and stress [50, 51]. Elevated circulating BCAA levels were also considered to reflect upregulation of muscle catabolism associated with insulin resistance [52]. In line with these studies, we observed increased circulating total BCAAs, valine, alanine, and TMAO levels in PWH who had MASLD in this study, but we did not detect an association between increasing levels of these metabolites and severity of MASLD. Data on the association between BCAA levels and severity of hepatic fibrosis are conflicting. In a study of patients with MASLD [52], BCAA levels showed a trend of increase with progression of fibrosis but differences between F1-2 and F3-4 group were not significant. In contrast, another study reported decreased BCAA levels with increasing fibrosis stage in patients with steatohepatitis [53].

Similarly, LP-IR, an index reflecting both hepatic and peripheral insulin resistance, was significantly higher in PWH with MASLD versus controls in this study. DRI, which correlates with risk of developing diabetes, was higher in PWH who had MASLD compared to controls. Other NMR-derived indices that were previously linked to long term all-cause mortality, IVX, MMX and MVX (combing IVX and MMX) were not significantly different among the study groups.

Data from a recent randomized trial in PWH who are on ART showed pitavastatin reduced both LDL levels and risk of major adverse cardiovascular events (MACE) compared to placebo [54]. Our data highlight the importance of MASLD as a factor associated with increased risk for CVD in PWH. PWH and MASLD may be prioritized for pitavastatin therapy or other interventions that reduce the risk of CVD and MACE.

Recently, a new nomenclature for steatotic liver disease has been proposed [55]. MASLD has been suggested as a replacement term for non-alcoholic fatty liver disease (NAFLD) with the diagnostic criteria requiring the co-existence of at least one cardiometabolic factor in addition to hepatic steatosis. We have recently shown that the new nomenclature definitions have had minimal effect on classification of NAFLD to MASLD in PWH [56] as well as in the general population with MASLD [57]. Therefore, the results of this analysis are probably applicable when either the MASLD or NAFLD terminology is used to characterize non-alcohol associated steatotic liver disease in PWH in this cohort.

Study strengths

The strengths of this study include the systematic phenotyping of all participants, use of reliable noninvasive tools, CAP and LSM, to assess MASLD severity, and the comprehensive lipidomic and metabolomic profiling using NMR, which allowed interrogation of large number of variables and indices relevant to CVD risk in PWH.

Study limitations

As with other cross-sectional studies, associations observed here do not reflect causative relationship with MASLD. PWH in this study were on suppressive ART, whether our findings apply to PWH not on ART is unclear. The study may be underpowered to reveal associations between altered lipidomic and metabolomic profiles and liver fibrosis. Finally, data on lifestyle factors such as diet quality and physical activity, which could confound the results, were not captured as part of this study.

Conclusions

PWH with MASLD have altered lipidomic and metabolomic profiles indicating a higher CVD risk in this population. To reduce their CVD risk, PWH and MASLD should be screened for and offered interventions to address these untoward lipidomic and metabolomic changes.

Data availability

No datasets were generated or analysed during the current study.

References

  1. So-Armah K, Benjamin LA, Bloomfield GS, Feinstein MJ, Hsue P, Njuguna B, Freiberg MS. HIV and cardiovascular disease. Lancet HIV. 2020;7:e279–93.

    Article  PubMed Central  Google Scholar 

  2. Lieb W, Enserro DM, Larson MG, Vasan RS. Residual cardiovascular risk in individuals on lipid-lowering treatment: quantifying absolute and relative risk in the community. Open Heart. 2018;5:e000722.

    Article  PubMed Central  Google Scholar 

  3. Otvos JD, Guyton JR, Connelly MA, Akapame S, Bittner V, Kopecky SL, Lacy M, et al. Relations of GlycA and lipoprotein particle subspecies with cardiovascular events and mortality: a post hoc analysis of the AIM-HIGH trial. J Clin Lipidol. 2018;12:348–55. e342.

    Article  PubMed Central  Google Scholar 

  4. Tikkanen E, Jagerroos V, Holmes MV, Sattar N, Ala-Korpela M, Jousilahti P, Lundqvist A, et al. Metabolic Biomarker Discovery for risk of Peripheral Artery Disease compared with coronary artery disease: lipoprotein and metabolite profiling of 31 657 individuals from 5 prospective cohorts. J Am Heart Assoc. 2021;10:e021995.

    Article  PubMed Central  CAS  Google Scholar 

  5. Quesada JA, Bertomeu-Gonzalez V, Orozco-Beltran D, Cordero A, Gil-Guillen VF, Lopez-Pineda A, Nouni-Garcia R et al. The benefits of measuring the size and number of lipoprotein particles for cardiovascular risk prediction: a systematic review and meta-analysis. Clin Investig Arterioscler 2022.

  6. Shalaurova I, Connelly MA, Garvey WT, Otvos JD. Lipoprotein insulin resistance index: a lipoprotein particle-derived measure of insulin resistance. Metab Syndr Relat Disord. 2014;12:422–9.

    Article  PubMed Central  CAS  Google Scholar 

  7. Flores-Guerrero JL, Gruppen EG, Connelly MA, Shalaurova I, Otvos JD, Garcia E, Bakker SJL et al. A newly developed diabetes risk index, based on Lipoprotein subfractions and branched chain amino acids, is Associated with Incident Type 2 diabetes Mellitus in the PREVEND Cohort. J Clin Med 2020;9.

  8. Duprez DA, Kuller LH, Tracy R, Otvos J, Cooper DA, Hoy J, Neuhaus J, et al. Lipoprotein particle subclasses, cardiovascular disease and HIV infection. Atherosclerosis. 2009;207:524–9.

    Article  PubMed Central  CAS  Google Scholar 

  9. Bucher HC, Richter W, Glass TR, Magenta L, Wang Q, Cavassini M, Vernazza P, et al. Small dense lipoproteins, apolipoprotein B, and risk of coronary events in HIV-infected patients on antiretroviral therapy: the Swiss HIV Cohort Study. J Acquir Immune Defic Syndr. 2012;60:135–42.

    Article  CAS  Google Scholar 

  10. Younossi ZM, Golabi P, Paik JM, Henry A, Van Dongen C, Henry L. The global epidemiology of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH): a systematic review. Hepatology. 2023;77:1335–47.

    Article  PubMed  Google Scholar 

  11. Gawrieh S, Lake JE, Debroy P, Sjoquist JA, Robison M, Tann M, Akisik F, et al. Burden of fatty liver and hepatic fibrosis in persons with HIV: a diverse cross-sectional US multicenter study. Hepatology. 2023;78:578–91.

    Article  Google Scholar 

  12. Lemoine M, Assoumou L, Girard PM, Valantin MA, Katlama C, De Wit S, Campa P, et al. Screening HIV patients at risk for NAFLD using MRI-PDFF and transient elastography: a European Multicenter prospective study. Clin Gastroenterol Hepatol. 2023;21:713–22. e713.

    Article  Google Scholar 

  13. Rinella ME, Neuschwander-Tetri BA, Siddiqui MS, Abdelmalek MF, Caldwell S, Barb D, Kleiner DE, et al. AASLD Practice Guidance on the clinical assessment and management of nonalcoholic fatty liver disease. Hepatology. 2023;77:1797–835.

    Article  PubMed  Google Scholar 

  14. Luo F, Oldoni F, Das A. TM6SF2: a Novel Genetic Player in nonalcoholic fatty liver and Cardiovascular Disease. Hepatol Commun. 2022;6:448–60.

    Article  CAS  Google Scholar 

  15. Ajmera V, Loomba R. Advances in the genetics of nonalcoholic fatty liver disease. Curr Opin Gastroenterol. 2023;39:150–5.

    Article  PubMed Central  Google Scholar 

  16. BasuRay S, Smagris E, Cohen JC, Hobbs HH. The PNPLA3 variant associated with fatty liver disease (I148M) accumulates on lipid droplets by evading ubiquitylation. Hepatology. 2017;66:1111–24.

    Article  CAS  Google Scholar 

  17. Luo F, Smagris E, Martin SA, Vale G, McDonald JG, Fletcher JA, Burgess SC, et al. Hepatic TM6SF2 is required for Lipidation of VLDL in a Pre-golgi Compartment in mice and rats. Cell Mol Gastroenterol Hepatol. 2022;13:879–99.

    Article  Google Scholar 

  18. Soti S, Corey KE, Lake JE, Erlandson KM. NAFLD and HIV: do sex, race, and ethnicity explain HIV-Related risk? Curr HIV/AIDS Rep. 2018;15:212–22.

    Article  PubMed Central  Google Scholar 

  19. Busca C, Arias P, Sanchez-Conde M, Rico M, Montejano R, Martin-Carbonero L, Valencia E, et al. Genetic variants associated with steatohepatitis and liver fibrosis in HIV-infected patients with NAFLD. Front Pharmacol. 2022;13:905126.

    Article  PubMed Central  CAS  Google Scholar 

  20. Sagnelli C, Merli M, Uberti-Foppa C, Hasson H, Grandone A, Cirillo G, Salpietro S, et al. TM6SF2 E167K variant predicts severe liver fibrosis for human immunodeficiency/hepatitis C virus co-infected patients, and severe steatosis only for a non-3 hepatitis C virus genotype. World J Gastroenterol. 2016;22:8509–18.

    Article  PubMed Central  CAS  Google Scholar 

  21. Krishnan A, Sims OT, Surapaneni PK, Woreta TA, Alqahtani SA. Risk of adverse cardiovascular outcomes among persons living with HIV and nonalcoholic fatty liver disease: a multicenter matched cohort study. AIDS; 2023.

  22. Duell PB, Welty FK, Miller M, Chait A, Hammond G, Ahmad Z, Cohen DE, et al. Nonalcoholic fatty liver Disease and Cardiovascular Risk: A Scientific Statement from the American Heart Association. Arterioscler Thromb Vasc Biol. 2022;42:e168–85.

    Article  CAS  Google Scholar 

  23. Amor AJ, Pinyol M, Sola E, Catalan M, Cofan M, Herreras Z, Amigo N, et al. Relationship between noninvasive scores of nonalcoholic fatty liver disease and nuclear magnetic resonance lipoprotein abnormalities: a focus on atherogenic dyslipidemia. J Clin Lipidol. 2017;11:551–61. e557.

    Article  Google Scholar 

  24. Siddiqui MS, Fuchs M, Idowu MO, Luketic VA, Boyett S, Sargeant C, Stravitz RT, et al. Severity of nonalcoholic fatty liver disease and progression to cirrhosis are associated with atherogenic lipoprotein profile. Clin Gastroenterol Hepatol. 2015;13:1000–8. e1003.

    Article  CAS  Google Scholar 

  25. Gnatiuc Friedrichs L, Trichia E, Aguilar-Ramirez D, Preiss D. Metabolic profiling of MRI-measured liver fat in the UK Biobank. Obes (Silver Spring). 2023;31:1121–32.

    Article  CAS  Google Scholar 

  26. Patel S, Siddiqui MB, Roman JH, Zhang E, Lee E, Shen S, Faridnia M, et al. Association between Lipoprotein Particles and atherosclerotic events in nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2021;19:2202–4.

    Article  CAS  Google Scholar 

  27. Cervo A, Sebastiani G, Milic J, Krahn T, Mazzola S, Petta S, Cascio A, et al. Dangerous liaisons: NAFLD and liver fibrosis increase cardiovascular risk in HIV. HIV Med. 2022;23:911–21.

    Article  CAS  Google Scholar 

  28. Knight JR, Sherritt L, Harris SK, Gates EC, Chang G. Validity of brief alcohol screening tests among adolescents: a comparison of the AUDIT, POSIT, CAGE, and CRAFFT. Alcohol Clin Exp Res. 2003;27:67–73.

    Article  Google Scholar 

  29. Frank D, DeBenedetti AF, Volk RJ, Williams EC, Kivlahan DR, Bradley KA. Effectiveness of the AUDIT-C as a screening test for alcohol misuse in three race/ethnic groups. J Gen Intern Med. 2008;23:781–7.

    Article  PubMed Central  Google Scholar 

  30. Jeyarajah EJ, Cromwell WC, Otvos JD. Lipoprotein particle analysis by nuclear magnetic resonance spectroscopy. Clin Lab Med. 2006;26:847–70.

    Article  Google Scholar 

  31. Matyus SP, Braun PJ, Wolak-Dinsmore J, Jeyarajah EJ, Shalaurova I, Xu Y, Warner SM, et al. NMR measurement of LDL particle number using the Vantera Clinical Analyzer. Clin Biochem. 2014;47:203–10.

    Article  CAS  Google Scholar 

  32. Otvos JD, Shalaurova I, Wolak-Dinsmore J, Connelly MA, Mackey RH, Stein JH, Tracy RP. GlycA: a Composite Nuclear magnetic resonance biomarker of systemic inflammation. Clin Chem. 2015;61:714–23.

    Article  CAS  Google Scholar 

  33. Huffman KM, Parker DC, Bhapkar M, Racette SB, Martin CK, Redman LM, Das SK, et al. Calorie restriction improves lipid-related emerging cardiometabolic risk factors in healthy adults without obesity: distinct influences of BMI and sex from CALERIE a multicentre, phase 2, randomised controlled trial. EClinicalMedicine. 2022;43:101261.

    Article  PubMed Central  Google Scholar 

  34. Garcia E, Bennett DW, Connelly MA, Jeyarajah EJ, Warf FC, Shalaurova I, Matyus SP, et al. The extended lipid panel assay: a clinically-deployed high-throughput nuclear magnetic resonance method for the simultaneous measurement of lipids and Apolipoprotein B. Lipids Health Dis. 2020;19:247.

    Article  PubMed Central  CAS  Google Scholar 

  35. Wolak-Dinsmore J, Gruppen EG, Shalaurova I, Matyus SP, Grant RP, Gegen R, Bakker SJL, et al. A novel NMR-based assay to measure circulating concentrations of branched-chain amino acids: Elevation in subjects with type 2 diabetes mellitus and association with carotid intima media thickness. Clin Biochem. 2018;54:92–9.

    Article  CAS  Google Scholar 

  36. Garcia E, Shalaurova I, Matyus SP, Oskardmay DN, Otvos JD, Dullaart RPF, Connelly MA. Ketone Bodies Are Mildly Elevated in subjects with type 2 diabetes Mellitus and are inversely Associated with insulin resistance as measured by the lipoprotein insulin Resistance Index. J Clin Med 2020;9.

  37. Otvos JD, Shalaurova I, May HT, Muhlestein JB, Wilkins JT, McGarrah RW 3rd, Kraus WE. Multimarkers of metabolic malnutrition and inflammation and their association with mortality risk in cardiac catheterisation patients: a prospective, longitudinal, observational, cohort study. Lancet Healthy Longev. 2023;4:e72–82.

    Article  Google Scholar 

  38. Siddiqui MS, Vuppalanchi R, Van Natta ML, Hallinan E, Kowdley KV, Abdelmalek M, Neuschwander-Tetri BA, et al. Vibration-controlled transient elastography to assess fibrosis and steatosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2019;17:156–63. e152.

    Article  Google Scholar 

  39. Wong VW, Vergniol J, Wong GL, Foucher J, Chan HL, Le Bail B, Choi PC, et al. Diagnosis of fibrosis and cirrhosis using liver stiffness measurement in nonalcoholic fatty liver disease. Hepatology. 2010;51:454–62.

    Article  CAS  Google Scholar 

  40. Josloff K, Beiriger J, Khan A, Gawel RJ, Kirby RS, Kendrick AD, Rao AK et al. Comprehensive Review of Cardiovascular Disease risk in nonalcoholic fatty liver disease. J Cardiovasc Dev Dis 2022;9.

  41. Shah ASV, Stelzle D, Lee KK, Beck EJ, Alam S, Clifford S, Longenecker CT, et al. Global Burden of Atherosclerotic Cardiovascular Disease in people living with HIV: systematic review and Meta-analysis. Circulation. 2018;138:1100–12.

    Article  PubMed Central  Google Scholar 

  42. Sanyal AJ, Van Natta ML, Clark J, Neuschwander-Tetri BA, Diehl A, Dasarathy S, Loomba R, et al. Prospective study of outcomes in adults with nonalcoholic fatty liver disease. N Engl J Med. 2021;385:1559–69.

    Article  PubMed Central  CAS  Google Scholar 

  43. Targher G, Day CP, Bonora E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl J Med. 2010;363:1341–50.

    Article  PubMed  CAS  Google Scholar 

  44. Wang J, Stancakova A, Soininen P, Kangas AJ, Paananen J, Kuusisto J, Ala-Korpela M, et al. Lipoprotein subclass profiles in individuals with varying degrees of glucose tolerance: a population-based study of 9399 Finnish men. J Intern Med. 2012;272:562–72.

    Article  CAS  Google Scholar 

  45. Rashid S, Watanabe T, Sakaue T, Lewis GF. Mechanisms of HDL lowering in insulin resistant, hypertriglyceridemic states: the combined effect of HDL triglyceride enrichment and elevated hepatic lipase activity. Clin Biochem. 2003;36:421–9.

    Article  CAS  Google Scholar 

  46. Packard CJ. Triacylglycerol-rich lipoproteins and the generation of small, dense low-density lipoprotein. Biochem Soc Trans. 2003;31:1066–9.

    Article  CAS  Google Scholar 

  47. Ginsberg HN, Packard CJ, Chapman MJ, Borén J, Aguilar-Salinas CA, Averna M, Ference BA, et al. Triglyceride-rich lipoproteins and their remnants: metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strategies-a consensus statement from the European Atherosclerosis Society. Eur Heart J. 2021;42:4791–806.

    Article  PubMed Central  CAS  Google Scholar 

  48. Khalili M, King WC, Kleiner DE, Jain MK, Chung RT, Sulkowski M, Lisker-Melman M, et al. Fatty liver disease in a prospective north American cohort of adults with Human Immunodeficiency Virus and Hepatitis B Virus Coinfection. Clin Infect Dis. 2021;73:e3275–85.

    Article  CAS  Google Scholar 

  49. DeFilippis AP, Blaha MJ, Martin SS, Reed RM, Jones SR, Nasir K, Blumenthal RS, et al. Nonalcoholic fatty liver disease and serum lipoproteins: the multi-ethnic study of atherosclerosis. Atherosclerosis. 2013;227:429–36.

    Article  PubMed Central  CAS  Google Scholar 

  50. Iwasa M, Ishihara T, Mifuji-Moroka R, Fujita N, Kobayashi Y, Hasegawa H, Iwata K, et al. Elevation of branched-chain amino acid levels in diabetes and NAFL and changes with antidiabetic drug treatment. Obes Res Clin Pract. 2015;9:293–7.

    Article  Google Scholar 

  51. Lake AD, Novak P, Shipkova P, Aranibar N, Robertson DG, Reily MD, Lehman-McKeeman LD, et al. Branched chain amino acid metabolism profiles in progressive human nonalcoholic fatty liver disease. Amino Acids. 2015;47:603–15.

    Article  CAS  Google Scholar 

  52. Gaggini M, Carli F, Rosso C, Buzzigoli E, Marietti M, Della Latta V, Ciociaro D, et al. Altered amino acid concentrations in NAFLD: impact of obesity and insulin resistance. Hepatology. 2018;67:145–58.

    Article  CAS  Google Scholar 

  53. Kawanaka M, Nishino K, Oka T, Urata N, Nakamura J, Suehiro M, Kawamoto H, et al. Tyrosine levels are associated with insulin resistance in patients with nonalcoholic fatty liver disease. Hepat Med. 2015;7:29–35.

    Article  PubMed Central  Google Scholar 

  54. Grinspoon SK, Fitch KV, Zanni MV, Fichtenbaum CJ, Umbleja T, Aberg JA, Overton ET, et al. Pitavastatin to Prevent Cardiovascular Disease in HIV infection. N Engl J Med. 2023;389:687–99.

    Article  PubMed Central  CAS  Google Scholar 

  55. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, Romero D, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol. 2023;79:1542–56.

    Article  CAS  Google Scholar 

  56. Gawrieh S, Vilar-Gomez E, Woreta TA, Lake JE, Wilson LA, Price JC, Naggie S, et al. Prevalence of steatotic liver disease, MASLD, MetALD and significant fibrosis in people with HIV in the United States. Aliment Pharmacol Ther. 2024;59:666–79.

    Article  CAS  Google Scholar 

  57. Gawrieh S, Vilar-Gomez E, Wilson LA, Pike F, Kleiner DE, Neuschwander-Tetri BA, Diehl AM et al. Increases and decreases in liver stiffness measurement are independently associated with the risk of liver-related events in NAFLD. J Hepatol 2024.

Download references

Funding

This work was supported by National Institutes of Health [grant number R01 DK112293 to SG and R01 DK126042 to JEL].

Author information

Authors and Affiliations

  1. Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, 702 Rotary Circle, Indianapolis, Indianapolis, IN, 46202, USA

    Kung-Hung Lin, Eduardo Vilar-Gomez, Naga Chalasani & Samer Gawrieh

  2. Division of Gastroenterology, Department of Medicine, Liver Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Kathleen E. Corey

  3. LabCorp, Morrisville, NC, USA

    Margery A. Connelly

  4. Division of Infectious Diseases, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

    Samir K. Gupta

  5. Division of Infectious Diseases, Department of Medicine, UTHealth Science Center at Houston, Houston, TX, USA

    Jordan E. Lake

Authors
  1. Kung-Hung Lin
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Eduardo Vilar-Gomez
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Kathleen E. Corey
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Margery A. Connelly
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Samir K. Gupta
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Jordan E. Lake
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Naga Chalasani
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Samer Gawrieh
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Study concept (KL, NC, SG); manuscript preparation (KL, SG); data acquisition (All authors), statistical analysis (EV), data interpretation and critical review of manuscript (All authors).

Corresponding author

Correspondence to Samer Gawrieh.

Ethics declarations

Ethical approval

This study protocol had been reviewed and approved by each site’s the Institutional Review Board (Indiana University School of Medicine, Massachusetts General Hospital, and, UTHealth Science Center). Each participant provided written informed consent.

Conflict of interest

Dr. Lin and Dr. Vilar-Gomez declare no conflicts of interest. Dr. Corey serves on the scientific advisory board for Theratechnologies, Novo Nordisk and BMS and has received grant funding from Boehringer-Ingelheim, BMS and Novartis, Dr. Connelly is an employee of and holds stock in Labcorp, Dr. Gupta receives consultancy fees from ViiV Healthcare and Gilead Sciences and unrestricted research grant funding from ViiV Healthcare, Dr. Lake serves as a consultant to CytoDyn and Theratechnologies, and receives research support from Gilead Sciences and Zydus Pharmaceuticals, Dr. Chalasani declares none for this paper. For full disclosure, he has had paid consulting agreements with Madrigal, GSK, Galectin, Zydus, Altimune, Foresite, Ventyx, Merck and Pfizer. He has research grants from DSM and Exact Sciences. He has equity ownership in Avant Sante Therapeutics, a contract research organization., Dr. Gawrieh consulting: TransMedics, Pfizer. Research grant support: Viking and Zydus.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, KH., Vilar-Gomez, E., Corey, K.E. et al. MASLD in persons with HIV is associated with high cardiometabolic risk as evidenced by altered advanced lipoprotein profiles and targeted metabolomics. Lipids Health Dis 23, 339 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-024-02317-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-024-02317-4

Keywords

Lipids in Health and Disease

ISSN: 1476-511X