Lipoprotein Insulin Resistance Research Articles

Lipoprotein Insulin Resistance Score and Mortality Risk Stratification in Heart Failure

BackgroundHigher total serum cholesterol is associated with lower mortality in heart failure. Evaluating associations between lipoprotein subfractions and mortality among people with heart failure may provide insights into this observation. MethodsWe prospectively enrolled a community cohort of people with heart failure from 2003 to 2012 and assessed vital status through 2021. Plasma collected at enrollment was used to measure lipoprotein subfractions via nuclear magnetic resonance spectroscopy. A composite score of 6 lipoprotein subfractions was generated using the lipoprotein insulin resistance index (LP-IR) algorithm. Using covariate-adjusted proportional hazards regression models, we evaluated associations between LP-IR score and all-cause mortality. ResultsAmong 1382 patients with heart failure (median follow-up 13.9 years), a one-standard-deviation (SD) increment in LP-IR score was associated with lower mortality (hazard ratio [HR] 0.93; 95% confidence interval [CI], 0.97-0.99). Among LP-IR parameters, mean high-density lipoprotein (HDL) particle size was significantly associated with lower mortality (HR per 1-SD decrement in mean HDL particle size = 0.83; 95% CI, 0.78-0.89), suggesting that the inverse association between LP-IR score and mortality may be driven by smaller mean HDL particle size. ConclusionsLP-IR score was inversely associated with mortality among patients with heart failure and may be driven by smaller HDL particle size.

The Nutri-Score nutrition label: Associations between the underlying nutritional profile of foods and lipoprotein particle subclass profiles in adults

Background and aimsLipoprotein particle concentrations and size are associated with increased risk for atherosclerosis and premature cardiovascular disease. Certain dietary behaviours may be cardioprotective and public health strategies are needed to guide consumers’ dietary choices and help prevent diet-related disease. The Food Standards Agency nutrient profiling system (FSAm-NPS) constitutes the basis of the five-colour front-of-pack Nutri-Score labelling system. No study has examined FSAm-NPS index associations with a wide range of lipoprotein particle subclasses. MethodsThis was a cross-sectional study of 2006 middle-to older-aged men and women randomly selected from a large primary care centre. Individual participant FSAm-NPS dietary scores were derived from validated food frequency questionnaires. Lipoprotein particle subclass concentrations and size were determined using nuclear magnetic resonance spectroscopy. Multivariate-adjusted linear regression analyses were performed to examine FSAm-NPS relationships with lipoprotein particle subclasses. ResultsIn fully adjusted models which accounted for multiple testing, higher FSAm-NPS scores, indicating poorer dietary quality, were positively associated with intermediate-density lipoprotein (β = 0.096, p = 0.005) and small high-density lipoprotein (HDL) (β = 0.492, p = 0.006) concentrations, a lipoprotein insulin resistance score (β = 0.063, p = 0.02), reflecting greater lipoprotein-related insulin resistance, and inversely associated with HDL size (β = −0.030, p = 0.045). ConclusionsA higher FSAm-NPS score is associated with a less favourable lipoprotein particle subclass profile in middle-to older-aged adults which may be a potential mechanism underlying reported health benefits of a healthy diet according to Nutri-Score rating.

Abstract P184: Association of Plasma Lipid Species With Lipoprotein Insulin Resistance Score Before and After Exercise Training

Background: The lipoprotein insulin resistance (LP-IR) score has been shown to assess insulin resistance, predict future type 2 diabetes, and improve with regular exercise. The lipidomic profile is known to differ with insulin resistance and type 2 diabetes, but few studies have examined lipidome associations with LP-IR, particularly in response to an exercise intervention. Methods: Plasma lipids were measured using the C8-positive LC-MS method in 671 participants from the HERITAGE Family Study (56% Female, 35% Black, 35.2 yrs) before and after a 20-week exercise intervention. LP-IR, a weighted index of six lipoprotein parameters, was measured before and after training through nuclear magnetic resonance spectroscopy (Labcorp, NC). Linear mixed models were used to test the associations of 193 known plasma lipids with LP-IR before and after exercise training. All models were adjusted for age, sex, and race, while post-training models also adjusted for baseline lipid and baseline LP-IR. Results: A total of 162 lipids (84%) were associated (FDR<0.05) with LP-IR at baseline ( Figure 1 ). The top positive associations were found for TG species, while cholesterol ester species showed the top inverse associations. Following training, the change in 143 (74%) lipids were associated (FDR<0.05) with change in LP-IR. There were 129 lipid species associated with both baseline and changes in LP-IR, while 33 were only associated with baseline measures and 14 only associated with changes in LP-IR following exercise ( Figure 1 ). Conclusions: We found that most lipids were associated with LP-IR regardless of exercise training status. Importantly, we identified a subset of lipids that were only associated with changes in LP-IR, which may represent exercise responsive biomarkers of exercise induced changes in LP-IR. However, further research is needed to identify the biological mechanisms connecting the changes in these lipid species and metabolic changes following exercise training.

Plasma Biomarker Profiles for Premature and Nonpremature Coronary Heart Disease in Women.

Premature coronary heart disease (CHD) is a major cause of death in women. We aimed to characterize biomarker profiles of women who developed CHD before and after age 65 years. In the Women's Health Study (median follow-up 21.5 years), women were grouped by age and timing of incident CHD: baseline age <65 years with premature CHD by age 65 years (25 042 women; 447 events) and baseline age ≥65 years with nonpremature CHD (2982 women; 351 events). Associations of 44 baseline plasma biomarkers measured using standard assays and a nuclear magnetic resonance (NMR)-metabolomics assay were analyzed using Cox models adjusted for clinical risk factors. Twelve biomarkers showed associations only with premature CHD and included lipoprotein(a), which was associated with premature CHD [adjusted hazard ratio (HR) per SD: 1.29 (95% CI 1.17-1.42)] but not with nonpremature CHD [1.09(0.98-1.22)](Pinteraction = 0.02). NMR-measured lipoprotein insulin resistance was associated with the highest risk of premature CHD [1.92 (1.52-2.42)] but was not associated with nonpremature CHD (Pinteraction <0.001). Eleven biomarkers showed stronger associations with premature vs nonpremature CHD, including apolipoprotein B. Nine NMR biomarkers showed no association with premature or nonpremature CHD, whereas 12 biomarkers showed similar significant associations with premature and nonpremature CHD, respectively, including low-density lipoprotein (LDL) cholesterol [1.30(1.20-1.45) and 1.22(1.10-1.35)] and C-reactive protein [1.34(1.19-1.50) and 1.25(1.08-1.44)]. In women, a profile of 12 biomarkers was selectively associated with premature CHD, driven by lipoprotein(a) and insulin-resistant atherogenic dyslipoproteinemia. This has implications for the development of biomarker panels to screen for premature CHD.

Triglyceride/HDL cholesterol ratio and lipoprotein insulin resistance Score: Associations with subclinical atherosclerosis and incident cardiovascular disease

BackgroundThe triglyceride/HDL cholesterol (TG/HDL-C) ratio and the Lipoprotein Insulin Resistance (LP-IR) score are lipid markers of insulin resistance. Their associations with carotid intima media thickness (cIMT; subclinical atherosclerosis) and incident cardiovascular disease (CVD) have not been thoroughly investigated. MethodsIn a cross-sectional cohort (89 subjects without type 2 diabetes (T2D) and 81 subjects with T2D we determined cIMT (ultrasound), homeostasis model assessment of insulin resistance (HOMA-IR) and the TG/HDL-C ratio. The LP-IR score, based on 6 lipoprotein characteristics determined by nuclear magnetic resonance spectroscopy, was measured in 123 participants. A prospective study was carried out among 6232 participants (Prevention of REnal and Vascular ENd-stage Disease study). ResultsCross-sectionally, the adjusted associations of HOMA-IR, the TG/HDL-C ratio and the LP-IR score with cIMT were approximately similar (standardized β = 0.34 (95 % CI 0.19–0.48), 0.24 (95 % CI 0.09–039) and 0.41 (95 % CI 0.23––0.59), respectively). Prospectively, 507 new cases of CVD were observed after a median follow-up of 8.2 (interquartile range 7.5–8.8) years. HOMA-IR, the TG/HDL-C ratio and LP-IR were each associated with incident CVD independent of potential confounders (HR 1.12, 95 % CI 1.02–1.24;1.22, 95 % CI 1.11–1.35 and 1.15. 95 % CI 1.01–1.31, respectively). The association of the TG/HDL-C ratio with incident CVD was somewhat stronger than that of HOMA-IR. ConclusionLipoprotein-based markers of insulin resistance are at least as strongly associated with subclinical atherosclerosis and clinical atherosclerosis development as HOMA-IR, obviating the need to measure insulin to determine the impact of insulin resistance. For practical purposes, the easily obtainable TG/HDL-C ratio may suffice.

Abstract 14051: The Associations Between Loneliness and Circulating Lipoproteins as Well as Diabetes Risk in African-American Women Residing in Resource-Limited Neighborhoods: Data From the Step It Up Physical Activity Intervention

Background: Loneliness is a public health crisis and recent reports suggest that people suffering from loneliness have increased cardiovascular disease (CVD) risk. A potential link between loneliness and CVD is an atherogenic shift in the lipoprotein profile. We investigated associations between loneliness and lipoproteins in African American (AA) women residing in resource-limited neighborhoods of Washington, DC. Methods: Participants were enrolled in Step It Up, a technology-based, community-engaged PA intervention. Fasting blood samples were drawn at baseline to measure lipoproteins using nuclear magnetic resonance (NMR) technology. The Lipoprotein Insulin Resistance Index (LP-IR), a diabetes risk marker, was calculated. Loneliness was measured using the UCLA Loneliness scale. Associations between loneliness, lipoprotein particles and LP-IR were analyzed using multivariable regression adjusted for BMI, ASCVD 10-year risk score, and lipid-lowering therapy. Results: 106 AA women with CVD risk (Age 55.9±13, BMI 36.3±6.7) were enrolled into Step It Up. We found that higher loneliness at baseline was associated with higher Apo-B, LDL concentration (LDL-c), and LDL particle number (LDL-p) but not with LDL particle size (LDL-z, Table). We observed that higher loneliness associated with increased triglyceride rich lipoprotein size (TRL-z). This relationship seems to be due to very large and large TRL particles (TRL-p, Table). No significant associations were found with the HDL-related measures. Lastly, loneliness significantly associated with LP-IR, a new diabetes risk marker (Table). Conclusions: Thus, our data show that higher loneliness in AA women from under resourced neighborhoods is associated with increased hyperlipidemia and diabetes risk. This highlights a potential mechanism by which loneliness may accelerate CVD risk and support the urgent need for multilevel interventions to reduce loneliness and CVD risk in at-risk populations.

Abstract 17627: The Relationship Between Physical Activity, Extracellular Vesicles, and Diabetes Risk in African American Women at Risk for Cardiovascular Disease: Data From a Pilot Study of the Step It Up Physical Activity Intervention

Background: Diabetes and cardiovascular disease (CVD) disproportionally affect African American (AA) women. Prior studies suggest extracellular vesicles (EV) are involved in atherogenesis, but little is known about relationships between PA and EVs in AA women. Thus, we examined associations between diabetes risk markers, EV, and PA in a community-based cohort of AA women at risk for CVD from resource-limited Washington, D.C. neighborhoods. Methods: Participants were enrolled in pilot testing of Step It Up, a place-tailored mobile app designed to increase PA. Baseline daily step counts for PA were measured by Fitbit® (Charge 2) and fasting baseline blood samples were cryopreserved. NMR (Nuclear magnetic resonance) spectroscopy was used to measure Lipoprotein Insulin Resistance Index (LP-IR), a diabetes risk marker. EV were isolated from heparinized plasma using size exclusion chromatography with size and numbers determined by nanoparticle tracking analysis. Associations between LP-IR, EVs, and daily step count were analyzed using multivariable regressions adjusted for BMI and ASCVD 10-year risk score. Results: The study cohort was a convenience sample of AA women with overweight/obesity (N=24, Age: 57±12, BMI: 35±6, ASCVD: 9±5). Smaller EV size associated with higher LP-IR (β=-0.45, p=0.04) with EV concentration trending to a positive association with LP-IR (β=0.38, p=0.08). Higher daily step count associated with larger EV particle size (β=0.48, p=0.02) but not with EV concentration. Additionally, higher daily step count associated with lower LP-IR (β=-0.42, p=0.04). Conclusions: Our data show that reduced EV size and increased EV concentration associate with higher LP-IR, a diabetes index among a community-based cohort of AA women. Additionally, our findings suggest that PA might help mitigate these associations. More research is needed to understand the potential impact of PA on EV, diabetes risk and subsequent CVD. Future PA interventions in at-risk patients may reduce existing diabetes and CVD-related health disparities and EVs may emerge as a mechanistic link.

FRI099 Advanced Lipoprotein Analysis In Patients With Cushing’s Syndrome

Abstract Disclosure: R.T. Varghese: None. R. McGlotten: None. M. Sampson: None. A. Prakash: None. R. Shamburek: None. A.T. Remaley: None. R. Muniyappa: None. L.K. Nieman: None. Introduction: Cushing syndrome (CS) patients have a higher mortality rate due to increased cardiovascular disease (CVD). Analysis of lipoprotein particles with nuclear magnetic resonance (NMR) spectroscopy provides additional insights into CVD risk beyond the standard lipid panel. The goal of the study was to better characterize the lipid abnormalities in patients with CS by using high-resolution separation of lipoprotein particles. Methods: We measured plasma lipids (Cholesterol, TC; calculated low density lipoprotein, LDL; triglycerides, TG; high density lipoprotein, HDL) by the traditional enzymatic assay and lipoprotein particles by NMR spectroscopy. Measures of inflammation and insulin resistance were also derived from NMR spectra. Values are shown as mean ± SEM or median [IQR]. Results: After initial evaluation, 42 subjects (mean age 47.4 ± 2.5 years; 28 females; weight 85.0 ± 3.1 kg) had Cushing's disease (n=23), ectopic ACTH secretion (n=17), or adrenal adenoma (n=2). Ten patients were on chronic statin therapy, and 14 subjects had type 2 diabetes mellitus (T2DM). The control group comprised 45 subjects without T2DM [mean age 45.4 ± 2.1 years and weight (83.5 ± 2.7) kg]. None in the control group were on statin therapy. Compared to controls, CS patients had significantly higher systolic (135 ±2 vs. 119 ±2 mm Hg, p&amp;lt;0.001) and diastolic blood pressure (79 ±2 vs. 71 ±1 mm Hg, p&amp;lt;0.001), HbA1c (6.1 [5.4-7.5] vs. 5.4 [5.0-5.7], p&amp;lt;0.001), plasma glucose (103 [90-137] vs 94 [89-100] mg/dL, p=0.003), and insulin (17[12-26] vs 11[7-15] uU/mL, p=0.01) levels. Compared to controls, patients with CS had significantly higher triglyceride concentration (116 [84 -146] vs 87 [62-120] mg/dL, p=0.02) and lower LDL concentration (90 [69 -113] vs 108 [90 -125] mg/dL, p=0.04). However, total cholesterol and HDL cholesterol concentrations were not different. LDL particle size in CS was smaller (20.5[20.0-21.0] vs 21.0 [20.7-21.2] nm, p=0.01) and VLDL particle size was larger (49.8 ± 0.9 vs 45.7 ± 1.0 nm, p=0.002) than in controls. No difference was noted between groups in HDL particle number or size or in LDL and VLDL particle number. In the group with CS, a marker of inflammation, GlycA (Glycan N-acetylglucosamine) (494.5 ± 18.2 vs. 382.5 ± 9.0 µmol/L, p&amp;lt;0.001) and Lipoprotein Insulin Resistance score (LPIR) (46.4 ± 3.1 vs. 36.2 ± 3.1, p=0.02) were significantly higher. There were no group differences in branch-chained amino acids (BCCA) levels. These differences remained even when patients with type 2 diabetes and those on statin therapy were excluded. Conclusions: These data suggest that the higher inflammatory and insulin resistance state, dysglycemia, hypertension, and altered lipoprotein profiles may contribute to the increased CV risk in patients with Cushing’s syndrome. Early detection and treatment for these abnormalities may attenuate CV risk. Presentation: Friday, June 16, 2023

Plant-based diet indices and lipoprotein particle subclass profiles: A cross-sectional analysis of middle- to older-aged adults

Background and aimsPlant-based diets (PBDs) are associated with favourable lipid profiles and cardiometabolic outcomes. However, limited data regarding PBD indices (PDIs) and lipoprotein subclasses exist. We examined overall PDI, healthful PDI (hPDI) and unhealthful PDI (uPDI) associations with lipid and lipoprotein profiles. MethodsThis cross-sectional analysis includes 1,986 middle- to older-aged adults from the Mitchelstown Cohort. The PDI, hPDI and uPDI scores were calculated from validated food frequency questionnaires. Higher PDI, hPDI and uPDI scores indicate a more PBD, healthful PBD and unhealthful PBD, respectively. Lipoprotein particle size and subclass concentrations were measured using nuclear magnetic resonance spectroscopy. Relationships between PDIs and lipid and lipoprotein profiles were examined via correlation and regression analyses adjusted for covariates. ResultsIn fully adjusted regression analyses, higher PDI scores were associated with lower high-density lipoprotein (HDL) cholesterol concentrations and more triglyceride-rich lipoprotein and small very low-density lipoprotein (VLDL) particles. Higher hPDI scores were negatively associated with non-HDL cholesterol concentrations, large VLDL and small HDL particles, the Lipoprotein Insulin Resistance Index (LP-IR) score and VLDL particle size. Higher uPDI scores were associated with lower HDL cholesterol and greater triglyceride concentrations and more medium and large VLDL, total LDL, small LDL and total non-HDL particles, less large LDL and large HDL particles, a greater LP-IR score, greater VLDL particle size and smaller LDL and HDL particle size. ConclusionsThis study provides novel evidence regarding associations between PBD quality and lipoprotein subclasses. A more unhealthful PBD was robustly associated with a more pro-atherogenic lipoprotein profile.

Association of Advanced Lipoprotein Subpopulation Profiles with Insulin Resistance and Inflammation in Patients with Type 2 Diabetes Mellitus.

Plasma lipoproteins exist as several subpopulations with distinct particle number and size that are not fully reflected in the conventional lipid panel. In this study, we sought to quantify lipoprotein subpopulations in patients with type 2 diabetes mellitus (T2DM) to determine whether specific lipoprotein subpopulations are associated with insulin resistance and inflammation markers. The study included 57 patients with T2DM (age, 61.14 ± 9.99 years; HbA1c, 8.66 ± 1.60%; mean body mass index, 35.15 ± 6.65 kg/m2). Plasma lipoprotein particles number and size were determined by nuclear magnetic resonance spectroscopy. Associations of different lipoprotein subpopulations with lipoprotein insulin resistance (LPIR) score and glycoprotein acetylation (GlycA) were assessed using multi-regression analysis. In stepwise regression analysis, VLDL and HDL large particle number and size showed the strongest associations with LPIR (R2 = 0.960; p = 0.0001), whereas the concentrations of the small VLDL and HDL particles were associated with GlycA (R2 = 0.190; p = 0.008 and p = 0.049, respectively). In adjusted multi-regression analysis, small and large VLDL particles and all sizes of lipoproteins independently predicted LPIR, whereas only the number of small LDL particles predicted GlycA. Conventional markers HbA1c and Hs-CRP did not exhibit any significant association with lipoprotein subpopulations. Our data suggest that monitoring insulin resistance-induced changes in lipoprotein subpopulations in T2DM might help to identify novel biomarkers that can be useful for effective clinical intervention.

Lipoprotein Insulin Resistance Index: A Simple, Accurate Method for Assessing Insulin Resistance in South Asians.

Identification of insulin resistance (IR) in South Asians, who are at a higher risk for type 2 diabetes, is important. Lack of standardization of insulin assays limits the clinical use of insulin-based surrogate indices. The lipoprotein insulin resistance index (LP-IR), a metabolomic marker, reflects the lipoprotein abnormalities observed in IR. The reliability of the LP-IR index in South Asians is unknown. We evaluated the predictive accuracy of LP-IR compared with other IR surrogate indices in South Asians. In a cross-sectional study (n = 55), we used calibration model analysis to assess the ability of the LP-IR score and other simple surrogate indices (Homeostatic Model Assessment of Insulin Resistance, Quantitative insulin sensitivity check index, Adipose insulin resistance index, and Matsuda Index) to predict insulin sensitivity (SI) derived from the reference frequently sampled intravenous glucose tolerance test. LP-IR index was derived from lipoprotein particle concentrations and sizes measured by nuclear magnetic resonance spectroscopy. Predictive accuracy was determined by root mean squared error (RMSE) of prediction and leave-one-out cross-validation type RMSE of prediction (CVPE). The optimal cut-off of the LP-IR index was determined by the area under the receiver operating characteristic curve (AUROC) and the Youden index. The simple surrogate indices showed moderate correlations with SI (r = 0.53-0.69, P < .0001). CVPE and RMSE were not different in any of the surrogate indices when compared with LP-IR. The AUROC was 0.77 (95% CI 0.64-0.89). The optimal cut-off for IR in South Asians was LP-IR >48 (sensitivity: 75%, specificity: 70%). The LP-IR index is a simple, accurate, and clinically useful test to assess IR in South Asians.

Abstract 13600: Performance of a Multi-Metabolite Score Added to a Risk Prediction Model for Incident Diabetes in Young Adults: The CARDIA Study

Introduction: The Finnish Diabetes Risk Score (FINDRISC) is a risk prediction tool used to estimate absolute risk for type 2 diabetes mellitus (DM), a critical risk factor for cardiovascular disease. The Diabetes Risk Index (DRI) is a multi-metabolite DM risk score developed by combining the Lipoprotein Insulin Resistance Index (LP-IR), calculated from six lipoproteins, and the branched chain amino acids, valine and leucine. Although the DRI is independently associated with future DM in middle-aged adults, the performance of this novel biomarker when added to FINDRISC to predict incident DM in young adults is not known. Hypothesis: The addition of DRI to FINDRISC will improve the 10-year(y) risk prediction of DM across all ages in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Methods: We measured the DRI using NMR spectroscopy in CARDIA participants across different age categories: 20-30y (n=1,911), 30-40y (n=2,716), 40-50y (n=2,232). We used Cox proportional hazards regression to evaluate the association of the DRI with incident 10-y DM risk. We assessed FINDRISC model performance using C-statistic and continuous Net Reclassification Index (NRI) with and without the addition of the DRI as a covariate. Results: DRI was associated with 10-y DM risk across all age categories. Addition of the DRI modestly improved the C-statistic in the 30-40-y age category. Addition of DRI to FINDRISC improved the overall NRI in the 30-40- and 40-50-y age categories. The non-event NRI was significant across all 3 age categories and reclassified 25-36% of participants who did not develop DM to a lower estimate of incident DM risk (Table). Conclusions: Among young and middle-aged adults, DRI scores were associated with 10-y risk of DM. The addition of DRI to FINDRISC led to improvements in reclassification of DM risk, as the addition of DRI to FINDRISC correctly classified up to 36% of participants who did not develop DM (over 10y) to a lower estimate of incident DM risk.

OR12-4 Metabolic Profiling in Adrenal Tumors Demonstrates Enhanced Chronic Inflammation, Branched Chain Amino Acids and Ketone Bodies, Biomarkers that Predict High Cardiometabolic Risk

Abstract Background Patients with adrenal hormone excess demonstrate an increased cardiovascular risk and mortality. We aimed to determine the impact of adrenal hormone excess on the metabolic profile that included plasma lipoproteins, total branched-chain amino acids (BCAA), ketone bodies, and GlycA (a proinflammatory glycoprotein biomarker). Method: We conducted a single-center cross-sectional study of consecutive patients with adrenal adenomas, Cushing syndrome (CS), and pheochromocytoma/paragangliomas (PPGL) between January 2015 and May 2021. Adrenal adenomas comprised nonfunctioning adenomas (NFA), adenomas with mild autonomous cortisol secretion (MACS), and primary aldosteronism (PA). Malignant and other benign tumors were excluded. Collected fasting plasma samples were measured using nuclear magnetic resonance spectroscopy for lipoproteins, BCCA, ketone bodies and GlycA. The results were compared to referent subjects from PREVEND (Prevention of Renal and Vascular End-stage Disease) study. Lipoprotein Insulin Resistance Index (LP-IR) which predicts incident diabetes was calculated based on 6 lipoprotein parameters. Results NFA (n=166, median age 60.1years, 63.3% women), MACS (n=158 (median age 61.8 years, 62. 0% women), CS (n=101, median age 43.8 years, 85.1% women), PA (n=71 (median age 55.8 years, 31. 0% women), PPGL (n=43, median age 55.5 years, 46.5% women) was diagnosed in 539 patients. Referent subjects (n=6540) were younger with a median age of 48.4, 50.2% women. When compared to referent subjects, and after age and sex-adjustment, GlycA was highest in patients with CS (OR 3.3, 95% CI 2.8-3.8), followed by PPGL (OR 2.3, 95%CI 1.8-2.9), MACS (OR 2, 95%CI 1.7-2.3), NFA (OR 1.9, 95%CI 1.7-2.2), and PA (OR 1.5, 95%CI 1.2-1.8). When compared to referent subjects, and after sex- and age adjustment, all patient groups demonstrated increase in BCAA: CS (OR 2.7 (95%CI 2.3-3.2), PPGL (OR 2.3, 95% CI 1.8-2.9), NFA (OR 2.4, 95% CI 2.1-2.7), PA (OR 2. 0, 95%CI 1.7-2.5), MACS (OR 2.2, 95% CI 1.7-2.6). Total ketone bodies were increased in patients with cortisol excess (OR of 1.4, 95%CI 1.2-1.5 in CS, and OR of 1.2, 95%CI 1-1.3 in MACS) and NFA (OR 1.2, 95%CI 1.1-1.3), but not in PA or PPGL. All patient groups except PPGL were more likely to have a higher LP-IR score. When compared to referent subjects, the highest sex- and age-adjusted LP-IR increase was in patients with CS (OR 1.9 (95%CI 1.5-2.2), followed by MACS (OR 1.4, 95% CI 1.2-1.7), PA (OR 1.4, 95%CI 1.1-1.8), and NFA (OR 1.4, 95% CI 1.2-1.7). Conclusion Patient with adrenal adenomas and PPGL demonstrate an increase in GlycA, BCAA, and ketone bodies - biomarkers associated with adverse cardiometabolic disorders and mortality. All patients except those with PPGL also demonstrated a higher LP-IR index that was reported to predict incident diabetes. Patients with NFA demonstrated an adverse metabolic profile similar to patients with MACS. Presentation: Sunday, June 12, 2022 11:45 a.m. - 12:00 p.m.

Nut consumption is associated with a shift of the NMR lipoprotein subfraction profile to a less atherogenic pattern among older individuals at high CVD risk

BackgroundScientific evidence has accumulated on the beneficial effects of nut consumption on cardiovascular risk and cholesterol reduction, but few studies have examined the effects of nuts on advanced measures of lipoprotein atherogenicity determined by nuclear magnetic resonance (NMR) spectroscopy. We analyzed associations between the amount and type of of nuts consumed and advanced measures of lipoprotein atherogenity and insulin resistance in older individuals at high cardiovascular risk.MethodsThe present observational study was carried out within the framework of the Prevención con Dieta Mediterránea (PREDIMED) trial. Cross-sectional and longitudinal analyses after 1-year of follow-up were conducted in 196 men and women recruited in the PREDIMED-Reus (Spain) center. Dietary intake was assessed using a validated semi-quantitative food questionnaire. Baseline and 1-year fasting plasma lipoprotein and metabolite profiling were performed in plasma using NMR spectra Vantera® Clinical Analyzer. Associations by tertiles of nut consumption between baseline and 1-year changes and advanced measures of lipoprotein atherogenicity, branched chain amminoacids, and measures of insulin resistance were tested by multivariable-adjusted ANCOVA models.ResultsCompared to paticipants in the bottom tertile, those in the top tertile of total nut consumption showed higher levels of large HDL particles and HDL-cholesterol, lower levels of branched-chain amino acids (BCAA) and GlycA, and reduced lipoprotein insulin resistance and diabetes risk index. Participants in the top tertile of walnut consumption disclosed lower levels of very large VLDL, total LDL particles, LDL-cholesterol, and GlycA. Participants in the top tertile of non-walnut nut consumption displayed higher levels of total HDL particles, HDL-cholesterol and apoliporotein A1, lower BCAA and GlycA, and reduced lipoprotein insulin resistance. Participants in the top tertile of 1-year changes in walnut consumption showed increases in medium-sized HDL particles in comparison to the bottom tertile.ConclusionsIn older individuals at high cardiovascular risk, increasing nut consumption was associated with a shift of the NMR lipoprotein subfraction profile to a less atherogenic pattern, as well as lower circulating concentrations of BCAA and decreased insulin resistance. These results provide novel mechanistic insight into the cardiovascular benefit of nut consumption.Trial registration ISRCTN35739639; registration date: 05/10/2005; recruitment start date 01/10/2003.

Elevated de novo lipogenesis, slow liver triglyceride turnover, and clinical correlations in nonalcoholic steatohepatitis patients

AbstractDe novo lipogenesis (DNL) converts carbon substrates to lipids. Increased hepatic DNL could contribute to pathogenic liver triglyceride accumulation in nonalcoholic steatohepatitis (NASH) and therefore may be a potential target for pharmacological intervention. Here, we measured hepatic DNL using heavy water in 123 patients with NASH with fibrosis or cirrhosis, calculated the turnover of hepatic triglycerides to allow repeat labeling studies, and determined the associations of hepatic DNL with metabolic, fibrotic, and imaging markers. We found that hepatic DNL was higher in patients with fibrotic NASH [median (IQR), 40.7% contribution to palmitate (32.1, 47.5), n=103] than has been previously reported in healthy volunteers and remained elevated [median (IQR), 36.8% (31.0, 44.5), n=20] in patients with cirrhosis, despite lower liver fat content. We also showed that turnover of intrahepatic triglyceride pools was slow (t½ >10 days). Furthermore, DNL contribution was determined to be independent of liver stiffness by magnetic resonance imaging but was positively associated with the number of large very low density lipoprotein (VLDL) particles, the size of VLDL, the lipoprotein insulin resistance score, and levels of ApoB100, and trended toward negative associations with the fibrosis markers FIB-4, FibroSure, and APRI. Finally, we found treatment with the acetyl-CoA carboxylase inhibitor firsocostat reduced hepatic DNL at 4 and 12 weeks, using a correction model for residual label that accounts for hepatic triglyceride turnover. Taken together, these data support an important pathophysiological role for elevated hepatic DNL in NASH and demonstrate that response to pharmacological agents targeting DNL can be correlated with pretreatment DNL.

Electronic health records analytics to identify cancer patients with metabolic syndrome.

e18649 Background: Metabolic syndrome, defined as the presence of at least 3 of 5 clinical factors including hypertension, elevated triglyceride levels, low high-density lipoprotein level, insulin resistance, and central obesity, increases the risk of heart disease, fatty liver, and multiple cancers. Metabolic syndrome in cancer patients has been associated with poor cancer-specific and overall survival. Lifestyle modification in patients with metabolic syndrome may reduce the risk of poor outcomes. In this quality improvement project, we aimed to determine the prevalence of metabolic syndrome among cancer patients and survivors seen in an outpatient general internal medicine (GIM) clinic and to determine the feasibility of using electronic health records (EHR) analytics to systematically identify such patients and refer them to lifestyle interventions and liver imaging. Methods: Study period was January-December 2021. During this period, an EHR algorithm was used to identify patients with metabolic syndrome based on the presence of ICD-10 diagnoses of metabolic conditions (diabetes, hypertension, lipid disease, and obesity). This algorithm was used to direct data from patient visits into an interactive dashboard to track metabolic syndrome prevalence and continuously monitor referrals to interventions. In September 2021, a best practice alert based on the EHR algorithm was created to identify patients with metabolic syndrome and prompt providers to refer them to nutrition counseling, liver ultrasound with elastography, and/or a community-based active-living support group for cancer survivors. GIM clinic nurses also reviewed medications and utilized an EPIC SmartPhrase that incorporated laboratory values (e.g., glucose, A1c, and lipids), blood pressure, and body mass index to confirm whether patients actually met the criteria for metabolic syndrome, and if so, they notified medical providers who then ordered the interventions. Patients confirmed to have metabolic syndrome received educational materials about lifestyle modifications. Data extracted from the dashboard were analyzed using Minitab 17 statistical software. Results: Among 1133 patients seen in the GIM clinic during 2021, 609 (54%) had metabolic syndrome. A total of 1045 patients (92%) had hypertension, 802 (71%) had hyperlipidemia, 571 (50%) had obesity, and 483 (43%) had diabetes. Among the 609 patients with metabolic syndrome, 148 (24%) were referred to liver ultrasound with elastography, 124 (20%) to nutrition counseling, and 21 (3%) to the support group. Beginning September 1, the best practice alert was triggered for 1131 clinical encounters meeting criteria for metabolic syndrome. Conclusions: The prevalence of metabolic syndrome among cancer patients seen in a GIM clinic was high. EHR analytics can lead to systematic identification and referral of patients with metabolic syndrome to lifestyle interventions and liver imaging.

1092-P: Lipoprotein Insulin Resistance Index and Mortality in Heart Failure: A Population Study

Heart failure (HF) is associated with metabolic alterations, including insulin resistance (IR) . Perturbations in lipid metabolism and insulin signaling may impact outcomes, but the relationship between IR and mortality is not well characterized. The Lipoprotein Insulin Resistance Index (LPIR) is a score (0-100; higher values signify greater IR) calculated from 6 lipoprotein subclass/size parameters measured by nuclear magnetic resonance (NMR) . We examined the association between LPIR and death in a HF community cohort. LPIR was measured by NMR LipoProfile®. Meta-Analysis Global Group in Chronic HF (MAGGIC) scores were calculated from clinical data. Kaplan-Meier curves were used to evaluate survival; Cox regression was used to estimate risk of death by LPIR quartile. Among 1,381 community-dwelling persons with HF, the median LPIR score was 38 (IQR 21-56) . Higher LPIR was associated with younger age, diabetes, smoking, obesity, and lower MAGGIC scores, but not ejection fraction. Survival increased by LPIR quartile (p&amp;lt;0.001) and at 5 years was 36% [95% CI 31-42], 42% [95% CI 38-48], 51% [95% CI 46-56], and 65% [95% CI 60-70] for quartile 1-4, respectively. The association between LPIR and death was independent of MAGGIC score (Figure) . Higher LPIR was associated with better survival in HF, independently of a validated clinical risk score. More research is needed to examine this paradoxically protective association. Disclosure S. Turecamo: None. A. Wolska: None. J.D. Otvos: Employee; LabCorp. K. Conners: None. S.J. Bielinski: Consultant; Novartis Pharmaceuticals Corporation. J. St Sauver: Research Support; Exact Sciences. V.L. Roger: None. Funding Research was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute (NHLBI) at National Institutes of Health and by the NIH Medical Research Scholars Program, a public-private partnership supported jointly by the NIH and contributions to the Foundation for the NIH from the Doris Duke Charitable Foundation, the American Association for Dental Research, and the Colgate-Palmolive Company.

Sex Differences in Vascular Endothelial Function After Liver Transplant

INTRODUCTIONLiver transplant (LT) recipients have an increased risk of developing cardiovascular disease (CVD) after transplant. Sex differences may be a significant determinant in the pathophysiology of CVD. However, sex‐differences in vascular dysfunction, an established precursor to CVD, have not been explored in LT recipients. The purpose of this study was to investigate the sex differences in vascular function and cardiometabolic risk‐factors to CVD among LT patients.METHODSConduit artery endothelial function was measured via flow‐mediated dilation of the brachial artery (FMDBA) with duplex ultrasound in 23 age‐matched LT patients (11 Male, 12 Female; Mean ± SEM: Age 55 ± 2 years). Aortic pressure waves were synthesized from radial artery waveforms acquired by applanation tonometry and the use of a generalized transfer function. Novel plasma based cardiometabolic risk factors were assessed with nuclear magnetic resonance spectroscopy. Lipoprotein insulin resistance index (LPIR) was calculated as a weighted combination of concentrations and particle sizes of very low‐density, low‐density, and high‐density lipoproteins. Diabetes risk index (DRI) factors LPIR and branched‐chain amino acid levels to predict the risk of type 2 diabetes. Metabolic inflammation index (INFX) combines concentrations of the inflammation biomarker GlycA and high‐density lipoprotein particle subspecies.RESULTSMales had lower FMDBA than females (3.98 ± 0.63 vs 6.27 ± 0.43%, p &lt; 0.01). There were no sex differences in aortic systolic pressure (Male vs Female; 129 ± 3 vs 118 ± 5 mmHg, p = 0.09), body mass index (38 ± 2 vs 36 ± 2 kg/m2, p = 0.61), LPIR (57 ± 7 vs 55 ± 7, p = 0.89), DRI (53 ± 7 vs 44 ± 6, p = 0.38), or INFX (47 ± 2 vs 54 ± 3, p = 0.13).CONCLUSIONSMales had poorer vascular endothelial function compared to females following LT, suggesting that males may be more susceptible to the development of CVD after LT. However, this increased risk cannot be explained by differences in traditional cardiometabolic risk factors. Future research should identify non‐traditional CVD risk factors that contribute to sex differences in vascular function towards implementing precision medicine for the prevention and management of CVD in LT patients.

Biological vascular age and its relationship with cardiovascular risk factors

Aim. To study of the relationship between cardiovascular risk factors and biological vascular age.Material and methods. The biological vascular age was estimated using models based on the arterial wall parameters. Using multiple logistic and linear regression, we studied the relationship between the biological vascular age and cardiovascular risk factors in 143 people without cardiovascular disease (CVD). Persons with a positive difference between the vascular and chronological age were assigned to the “old” vascular group, and persons with no or negative difference between the vascular and chronological age were assigned to the “young” vascular group.Results. Linear regression in the “young” vascular group showed an inverse relationship between the difference between the vascular and chronological age with the levels of low-density lipoprotein cholesterol (p=0,001; β±SE=-1,67±0,47), triglycerides (p=0,017; β±SE=-1,66±0,68), urea (p=0,025; β±SE=-0,89±0,39) and insulin resistance index (p=0,001; β±SE=-1,22±0,36). In the “old” vascular group, a direct relationship was found between the difference between the vascular and chronological age and central systolic blood pressure (p=0,015; β±SE=0,10±0,04). According to logistic regression, the likelihood of having “old” vessels increased by 1,23 times with an increase in blood glucose levels by 0,5 mmol/l (p=0,044; odds ratio (OR)=1,23; 95% confidence interval (CI): 1,011,51), the presence of hypertension (p=0,034; OR=3,11; 95% CI: 1,09-8,86) and type 2 diabetes (p=0,025; OR=3,61; 95% CI: 1,1711,09), as well as decreased by 2 times with an increase in high-density lipoprotein cholesterol by 0,3 mmol/l (p=0,003; OR=0,5; 95% CI: 0,32-0,79).Conclusion. The difference between the biological vascular age and chronological age is associated with traditional CVD risk factors.

Effects of a low-carbohydrate diet on insulin-resistant dyslipoproteinemia—a randomized controlled feeding trial

ABSTRACTBackgroundCarbohydrate restriction shows promise for diabetes, but concerns regarding high saturated fat content of low-carbohydrate diets limit widespread adoption.ObjectivesThis preplanned ancillary study aimed to determine how diets varying widely in carbohydrate and saturated fat affect cardiovascular disease (CVD) risk factors during weight-loss maintenance.MethodsAfter 10–14% weight loss on a run-in diet, 164 participants (70% female; BMI = 32.4 ± 4.8 kg/m2) were randomly assigned to 3 weight-loss maintenance diets for 20 wk. The prepared diets contained 20% protein and differed 3-fold in carbohydrate (Carb) and saturated fat as a proportion of energy (Low-Carb: 20% carbohydrate, 21% saturated fat; Moderate-Carb: 40%, 14%; High-Carb: 60%, 7%). Fasting plasma samples were collected prerandomization and at 20 wk. Lipoprotein insulin resistance (LPIR) score was calculated from triglyceride-rich, high-density, and low-density lipoprotein particle (TRL-P, HDL-P, LDL-P) sizes and subfraction concentrations (large/very large TRL-P, large HDL-P, small LDL-P). Other outcomes included lipoprotein(a), triglycerides, HDL cholesterol, LDL cholesterol, adiponectin, and inflammatory markers. Repeated measures ANOVA was used for intention-to-treat analysis.ResultsRetention was 90%. Mean change in LPIR (scale 0–100) differed by diet in a dose-dependent fashion: Low-Carb (–5.3; 95% CI: –9.2, –1.5), Moderate-Carb (–0.02; 95% CI: –4.1, 4.1), High-Carb (3.6; 95% CI: –0.6, 7.7), P = 0.009. Low-Carb also favorably affected lipoprotein(a) [–14.7% (95% CI: –19.5, –9.5), –2.1 (95% CI: –8.2, 4.3), and 0.2 (95% CI: –6.0, 6.8), respectively; P = 0.0005], triglycerides, HDL cholesterol, large/very large TRL-P, large HDL-P, and adiponectin. LDL cholesterol, LDL-P, and inflammatory markers did not differ by diet.ConclusionsA low-carbohydrate diet, high in saturated fat, improved insulin-resistant dyslipoproteinemia and lipoprotein(a), without adverse effect on LDL cholesterol. Carbohydrate restriction might lower CVD risk independently of body weight, a possibility that warrants study in major multicentered trials powered on hard outcomes. The registry is available through ClinicialTrials.gov: https://clinicaltrials.gov/ct2/show/NCT02068885.