Nuclear-Magnetic-Resonance-Spectroscopy-Derived Serum Biomarkers of Metabolic Vulnerability Are Associated with Disability and Neurodegeneration in Multiple Sclerosis.

PURPOSE: Metabolic vulnerabilities can exacerbate inflammatory injury and inhibit repair in multiple sclerosis (MS). The purpose was to evaluate whether blood biomarkers of inflammatory and metabolic vulnerability are associated with MS disability and neurodegeneration. METHODS: Proton nuclear magnetic resonance spectra were obtained from serum samples from 153 healthy controls, 187 relapsing-remitting, and 91 progressive MS patients. The spectra were analyzed to obtain concentrations of lipoprotein sub-classes, glycated acute-phase proteins, and small-molecule metabolites, including leucine, valine, isoleucine, alanine, and citrate. Composite indices for inflammatory vulnerability, metabolic malnutrition, and metabolic vulnerability were computed. MS disability was measured on the Expanded Disability Status Scale. MRI measures of lesions and whole-brain and tissue-specific volumes were acquired. RESULTS: Valine, leucine, isoleucine, alanine, the Inflammatory Vulnerability Index, the Metabolic Malnutrition Index, and the Metabolic Vulnerability Index differed between healthy control and MS groups in regression analyses adjusted for age, sex, and body mass index. The Expanded Disability Status Scale was associated with small HDL particle levels, inflammatory vulnerability, and metabolic vulnerability. Timed ambulation was associated with inflammatory vulnerability and metabolic vulnerability. Greater metabolic vulnerability and inflammatory vulnerability were associated with lower gray matter, deep gray matter volumes, and greater lateral ventricle volume. CONCLUSIONS: Serum-biomarker-derived indices of inflammatory and metabolic vulnerability are associated with disability and neurodegeneration in MS.

A global perspective on the status of clinical metabolomics in laboratory medicine - a survey by the IFCC metabolomics working group.

OBJECTIVES: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. METHODS: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. RESULTS: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. CONCLUSIONS: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.

Lipoprotein Insulin Resistance Score and Mortality Risk Stratification in Heart Failure.

BACKGROUND: Higher 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. METHODS: We 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. RESULTS: Among 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. CONCLUSIONS: LP-IR score was inversely associated with mortality among patients with heart failure and may be driven by smaller HDL particle size.

Incremental Value of a Metabolic Risk Score for Heart Failure Mortality: A Population-Based Study.

BACKGROUND: Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure. METHODS: Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA (glycoprotein acetylation), ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using least absolute shrinkage and selection operator penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed. RESULTS: The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%-51%). The MRS included 9 metabolites measured. In the validation data set, a 1 standard deviation increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9-2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3-1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno's C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP. CONCLUSIONS: This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.

Frailty and Metabolic Vulnerability in Heart Failure: A Community Cohort Study.

BACKGROUND: Frailty is common in heart failure (HF) and is associated with death but not routinely captured clinically. Frailty is linked with inflammation and malnutrition, which can be assessed by a novel plasma multimarker score: the metabolic vulnerability index (MVX). We sought to evaluate the associations between frailty and MVX and their prognostic impact. METHODS AND RESULTS: In an HF community cohort (2003-2012), we measured frailty as a proportion of deficits present out of 32 physical limitations and comorbidities, MVX by nuclear magnetic resonance spectroscopy, and collected extensive longitudinal clinical data. Patients were categorized by frailty score (≤0.14, >0.14 and ≤0.27, >0.27) and MVX score (≤50, >50 and ≤60, >60 and ≤70, >70). Cox models estimated associations of frailty and MVX with death, adjusted for Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Uno's C-statistic measured the incremental value of MVX beyond frailty and clinical factors. Weibull's accelerated failure time regression assessed whether MVX mediated the association between frailty and death. We studied 985 patients (median age, 77; 48% women). Frailty and MVX were weakly correlated (Spearman's ρ=0.21). The highest frailty group experienced an increased rate of death, independent of MVX, MAGGIC score, and NT-proBNP (hazard ratio, 3.3 [95% CI, 2.5-4.2]). Frailty improved Uno's c-statistic beyond MAGGIC score and NT-proBNP (0.69-0.73). MVX only mediated 3.3% and 4.5% of the association between high and medium frailty groups and death, respectively. CONCLUSIONS: In this HF cohort, frailty and MVX are weakly correlated. Both independently contribute to stratifying the risk of death, suggesting that they capture distinct domains of vulnerability in HF.

A High-Throughput NMR Method for Lipoprotein-X Quantification.

Lipoprotein X (LP-X) is an abnormal cholesterol-rich lipoprotein particle that accumulates in patients with cholestatic liver disease and familial lecithin-cholesterol acyltransferase deficiency (FLD). Because there are no high-throughput diagnostic tests for its detection, a proton nuclear magnetic resonance (NMR) spectroscopy-based method was developed for use on a clinical NMR analyzer commonly used for the quantification of lipoproteins and other cardiovascular biomarkers. The LP-X assay was linear from 89 to 1615 mg/dL (cholesterol units) and had a functional sensitivity of 44 mg/dL. The intra-assay coefficient of variation (CV) varied between 1.8 and 11.8%, depending on the value of LP-X, whereas the inter-assay CV varied between 1.5 and 15.4%. The assay showed no interference with bilirubin levels up to 317 mg/dL and was also unaffected by hemolysis for hemoglobin values up to 216 mg/dL. Samples were stable when stored for up to 6 days at 4 °C but were not stable when frozen. In a large general population cohort (n = 277,000), LP-X was detected in only 50 subjects. The majority of LP-X positive cases had liver disease (64%), and in seven cases, had genetic FLD (14%). In summary, we describe a new NMR-based assay for LP-X, which can be readily implemented for routine clinical laboratory testing.

Circulating ketone bodies and mortality in heart failure: a community cohort study.

Background: The relationship between ketone bodies (KB) and mortality in patients with heart failure (HF) syndrome has not been well established. Objectives: The aim of this study is to assess the distribution of KB in HF, identify clinical correlates, and examine the associations between plasma KB and all-cause mortality in a population-based HF cohort. Methods: The plasma KB levels were measured by nuclear magnetic resonance spectroscopy. Multivariable linear regression was used to examine associations between clinical correlates and KB levels. Proportional hazard regression was employed to examine associations between KB (represented as both continuous and categorical variables) and mortality, with adjustment for several clinical covariates. Results: Among the 1,382 HF patients with KB measurements, the median (IQR) age was 78 (68, 84) and 52% were men. The median (IQR) KB was found to be 180 (134, 308) µM. Higher KB levels were associated with advanced HF (NYHA class III-IV) and higher NT-proBNP levels (both P < 0.001). The median follow-up was 13.9 years, and the 5-year mortality rate was 51.8% [95% confidence interval (CI): 49.1%-54.4%]. The risk of death increased when KB levels were higher (HRhigh vs. low group 1.23; 95% CI: 1.05-1.44), independently of a validated clinical risk score. The association between higher KB and mortality differed by ejection fraction (EF) and was noticeably stronger among patients with preserved EF. Conclusions: Most patients with HF exhibited KB levels that were consistent with those found in healthy adults. Elevated levels of KB were observed in patients with advanced HF. Higher KB levels were found to be associated with an increased risk of death, particularly in patients with preserved EF.

Refinement of a published gene-physical activity interaction impacting HDL-cholesterol: role of sex and lipoprotein subfractions.

Large-scale gene-environment interaction (GxE) discovery efforts often involve compromises in the definition of outcomes and choice of covariates for the sake of data harmonization and statistical power. Consequently, refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C). This GxE was originally identified by Kilpeläinen et al., with the strongest cohort-specific signal coming from the Women's Genome Health Study (WGHS). We thus explored this GxE further in the WGHS (N = 23,294), with follow-up in the UK Biobank (UKB; N = 281,380), and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 4,587). Self-reported PA (MET-hrs/wk), genotypes at rs295849 (nearest gene: LHX1), and NMR metabolomics data were available in all three cohorts. As originally reported, minor allele carriers of rs295849 in WGHS had a stronger positive association between PA and HDL-C (pint = 0.002). When testing a range of NMR metabolites (primarily lipoprotein and lipid subfractions) to refine the HDL-C outcome, we found a stronger interaction effect on medium-sized HDL particle concentrations (M-HDL-P; pint = 1.0×10-4) than HDL-C. Meta-regression revealed a systematically larger interaction effect in cohorts from the original meta-analysis with a greater fraction of women (p = 0.018). In the UKB, GxE effects were stronger both in women and using M-HDL-P as the outcome. In MESA, the primary interaction for HDL-C showed nominal significance (pint = 0.013), but without clear differences by sex and with a greater magnitude using large, rather than medium, HDL-P as an outcome. Towards reconciling these observations, further exploration leveraging NMR platform-specific HDL subfraction diameter annotations revealed modest agreement across all cohorts in the interaction affecting medium-to-large particles. Taken together, our work provides additional insights into a specific known gene-PA interaction while illustrating the importance of phenotype and model refinement towards understanding and replicating GxEs.

The Metabolic Vulnerability Index: A Novel Marker for Mortality Prediction in Heart Failure.

BACKGROUND: Inflammation and protein energy malnutrition are associated with heart failure (HF) mortality. The metabolic vulnerability index (MVX) is derived from markers of inflammation and malnutrition and measured by nuclear magnetic resonance spectroscopy. MVX has not been examined in HF. OBJECTIVES: The authors sought to examine the prognostic value of MVX in patients with HF. METHODS: The authors prospectively assembled a population-based cohort of patients with HF from 2003 to 2012 and measured MVX scores with a nuclear magnetic resonance scan from plasma collected at enrollment. Patients were divided into 4 MVX score groups and followed until March 31, 2021. RESULTS: The authors studied 1,382 patients (median age: 78 years; 48% women). The median MVX score was 64.6. Patients with higher MVX were older, more likely to be male, have atrial fibrillation, have higher NYHA functional class, and have HF duration of >18 months. Higher MVX was associated with mortality independent of Meta-analysis Global Group in Chronic Heart Failure score, ejection fraction, and other prognostic biomarkers. Compared to those with the lowest MVX, the HRs for MVX groups 2, 3, and 4 were 1.2 (95% CI: 0.9-1.4), 1.6 (95% CI: 1.3-2.0), and 1.8 (95% CI: 1.4-2.2), respectively (Ptrend < 0.001). Measures of model improvement document the added value of MVX in HF for classifying the risk of death beyond the Meta-analysis Global Group in Chronic Heart Failure score and other biomarkers. CONCLUSIONS: In this HF community cohort, MVX was strongly associated with mortality independently of established clinical factors and improved mortality risk classification beyond clinically validated markers. These data underscore the potential of MVX to stratify risk in HF.

Novel Size-Based High-Density Lipoprotein Subspecies and Incident Vascular Events.

Background High-density lipoprotein (HDL) particle concentration likely outperforms HDL cholesterol in predicting atherosclerotic cardiovascular events. Whether size-based HDL subspecies explain the atheroprotective associations of HDL particle concentration remains unknown. Our objective was to assess whether levels of specific size-based HDL subspecies associate with atherosclerotic cardiovascular disease in a multiethnic pooled cohort and improve risk prediction beyond traditional atherosclerotic cardiovascular disease risk factors. Methods and Results Seven HDL size-based subspecies were quantified by nuclear magnetic resonance (LP4 algorithm; H1=smallest; H7=largest) among participants without prior atherosclerotic cardiovascular disease in ARIC (Atherosclerosis Risk in Communities), MESA (Multi-Ethnic Study of Atherosclerosis), PREVEND (Prevention of Renal and Vascular Endstage Disease), and DHS (Dallas Heart Study) cohorts (n=15 371 people). Multivariable Cox proportional hazards models were used to evaluate the association between HDL subspecies and incident myocardial infarction (MI) or ischemic stroke at follow-up (average 8-10 years) adjusting for HDL cholesterol and risk factors. Improvement in risk prediction was assessed via discrimination and reclassification analysis. Within the pooled cohort (median age 57 years; female 54%; Black 22%) higher H1 (small) and H4 (medium) concentrations were inversely associated with incident MI (hazard ratio [HR]/SD, H1 0.88 [95% CI, 0.81-0.94]; H4 0.89 [95% CI, 0.82-0.97]). H4 but not H1 improved risk prediction indices for incident MI. Increasing H2 and H4 were inversely associated with improved risk prediction indices for composite end point of stroke, MI, and cardiovascular death (HR/SD, H2 0.94 [95% CI, 0.88-0.99]; H4 0.91 [95% CI, 0.85-0.98]). Levels of the large subspecies (H6 and H7) were not associated with any vascular end point. Conclusions Two of 7 HDL size-based subspecies modestly improved risk prediction for MI and composite vascular end points in a large multiethnic pooled cohort. These findings support assessment of precise HDL subspecies for future studies regarding clinical utility.

Combined Association of Novel and Traditional Inflammatory Biomarkers With Carotid Artery Plaque: GlycA Versus C-Reactive Protein (ELSA-Brasil).

Elevated levels of glycoprotein acetylation (GlycA) and C-reactive protein (CRP) have been associated with carotid artery plaque (CAP). However, it is not yet established if elevations in both inflammatory biomarkers provide incremental association with CAP. This study aimed evaluate the cross-sectional association of high CRP and GlycA with CAP at baseline participants from the ELSA-Brasil adult cohort. Participants with information on CRP, GlycA, and CAP with neither previous cardiovascular disease nor CRP >10 mg/L were included. High GlycA and CRP were defined as values within upper quintile and >3 mg/L, respectively. Participants were classified into 4 groups: 1. nonelevated CRP/GlycA (reference group); 2. elevated CRP alone; 3. elevated GlycA alone; and 4. both elevated. The analysis included 4,126 participants with median age of 50 years-old, being 54.2% of women. Prevalence of CAP was 36.1%. Participants with high CRP had the highest frequency of obesity, whereas participants with high GlycA presented higher cardiovascular risk factor burden and were more likely to have CAP than the reference group (odds ratio [OR] 1.39, 95% confidence interval [CI] 1.11 to 1.73), persisting after multivariable adjustment (OR 1.37, 95% CI 1.02 to 1.83). Participants with both elevated CRP and GlycA were more likely to have CAP in crude (OR 1.35, 95% CI 1.10 to 1.65) but not in adjusted models. The findings suggest potential different biologic pathways between inflammation and carotid atherosclerosis: high GlycA was associated with CAP whereas high CRP was more associated with obesity.

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

BACKGROUND AND AIMS: Plant-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. METHODS: This 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. RESULTS: In 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. CONCLUSIONS: This 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.

Longitudinal trajectories of branched chain amino acids through young adulthood and diabetes in later life.

BACKGROUNDElevated circulating branched chain amino acids (BCAAs), measured at a single time point in middle life, are strongly associated with an increased risk of developing type 2 diabetes mellitus (DM). However, the longitudinal patterns of change in BCAAs through young adulthood and their association with DM in later life are unknown.METHODSWe serially measured BCAAs over 28 years in the Coronary Artery Risk Development in Young Adults (CARDIA) study, a prospective cohort of apparently healthy Black and White young adults at baseline. Trajectories of circulating BCAA concentrations from years 2-30 (for prevalent DM) or years 2-20 (for incident DM) were determined by latent class modeling.RESULTSAmong 3,081 apparently healthy young adults, trajectory analysis from years 2-30 revealed 3 distinct BCAA trajectory groups: low-stable (n = 1,427), moderate-stable (n = 1,384), and high-increasing (n = 270) groups. Male sex, higher body mass index, and higher atherogenic lipid fractions were more common in the moderate-stable and high-increasing groups. Higher risk of prevalent DM was associated with the moderate-stable (OR = 2.59, 95% CI: 1.90-3.55) and high-increasing (OR = 6.03, 95% CI: 3.86-9.43) BCAA trajectory groups in adjusted models. A separate trajectory group analysis from years 2-20 for incident DM after year 20 showed that moderate-stable and high-increasing trajectory groups were also significantly associated with higher risk of incident DM, after adjustment for clinical variables and glucose levels.CONCLUSIONBCAA levels track over a 28-year span in most young adults, but serial clinical metabolomic measurements identify subpopulations with rising levels associated with high risk of DM in later life.FUNDINGThis research was supported by the NIH, under grants R01 HL146844 (JTW) and T32 HL069771 (MRC). The CARDIA study is conducted and supported by the NIH National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201800005I and HHSN268201800007I), Northwestern University (HHSN268201800003I), the University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I).

Multimarkers of metabolic malnutrition and inflammation and their association with mortality risk in cardiac catheterisation patients: a prospective, longitudinal, observational, cohort study.

BACKGROUND: Complex and incompletely understood metabolic dysfunction associated with inflammation and protein-energy wasting contribute to the increased mortality risk of older patients and those with chronic organ diseases affected by cachexia, sarcopenia, malnutrition, and frailty. However, these wasting syndromes have uncertain relevance for patients with cardiovascular disease or people at lower risk. Studies are hampered by imperfect objective clinical assessment tools for these intertwined metabolic malnutrition and inflammation syndromes. We aimed to assess, in two independent cohorts of patients who underwent cardiac catheterisation, the mortality risk associated with the metabolic vulnerability index (MVX), a multimarker derived from six simultaneously measured serum biomarkers plausibly linked to these dysmetabolic syndromes. METHODS: In this prospective, longitudinal, observational study, we included patients aged ≥18 years recruited into the CATHGEN biorepository (Jan 2, 2001, to Dec 30, 2011) and the Intermountain Heart Collaborative Study (Sept 12, 2000, to Sept 21, 2006) who underwent coronary angiography and had clinical nuclear magnetic resonance metabolomic profiling done on frozen plasma obtained at catheterisation. We aggregated six mortality risk biomarkers (GlycA, small HDL, valine, leucine, isoleucine, and citrate concentrations) into sex-specific MVX multimarker scores using coefficients from predictive models for all-cause mortality in the CATHGEN cohort. We assessed associations of biomarkers and MVX with mortality in both cohorts using Cox proportional hazards models adjusted for 15 clinical covariates. FINDINGS: We included 5876 participants from the CATHGEN biorepository and 2888 from the Intermountain Heart study. Median follow-up was 6·2 years (IQR 4·4-8·9) in CATHGEN and 8·2 years (6·9-9·2) in the Intermountain Heart study. The six nuclear magnetic resonance biomarkers and MVX made strong, independent contributions to 5-year mortality risk prediction in both cohorts (hazard ratio 2·18 [95% CI 2·03-2·34] in the CATHGEN cohort and 1·67 [1·50-1·87] in the Intermountain Heart cohort). CATHGEN subgroup analyses showed similar MVX associations in men and women, older and younger individuals, for death from cardiovascular or non-cardiovascular causes, and in patients with or without multiple comorbidities. INTERPRETATION: MVX made a dominant contribution to mortality prediction in patients with cardiovascular disease and in low-risk subgroups without pre-existing disease, suggesting that metabolic malnutrition-inflammation syndromes might have a more universal role in survival than previously thought. FUNDING: Labcorp.

The Inflammation Biomarker GlycA Reflects Plasma N-Glycan Branching.

BACKGROUND: GlycA is a nuclear magnetic resonance (NMR) signal in plasma that correlates with inflammation and cardiovascular outcomes in large data sets. The signal is thought to originate from N-acetylglucosamine (GlcNAc) residues of branched plasma N-glycans, though direct experimental evidence is limited. Trace element concentrations affect plasma glycosylation patterns and may thereby also influence GlycA. METHODS: NMR GlycA signal was measured in plasma samples from 87 individuals and correlated with MALDI-MS N-glycomics and trace element analysis. We further evaluated the genetic association with GlycA at rs13107325, a single nucleotide polymorphism resulting in a missense variant within SLC39A8, a manganese transporter that influences N-glycan branching, both in our samples and existing genome-wide association studies data from 22 835 participants in the Women's Health Study (WHS). RESULTS: GlycA signal was correlated with both N-glycan branching (r2 ranging from 0.125-0.265; all P < 0.001) and copper concentration (r2 = 0.348, P < 0.0001). In addition, GlycA levels were associated with rs13107325 genotype in the WHS (ß [standard error of the mean] = -4.66 [1.2674], P = 0.0002). CONCLUSIONS: These results provide the first direct experimental evidence linking the GlycA NMR signal to N-glycan branching commonly associated with acute phase reactive proteins involved in inflammation.

Accuracy and Clinical Impact of Estimating Low-Density Lipoprotein-Cholesterol at High and Low Levels by Different Equations.

New more effective lipid-lowering therapies have made it important to accurately determine Low-density lipoprotein-cholesterol (LDL-C) at both high and low levels. LDL-C was measured by the ß-quantification reference method (BQ) (N = 40,346) and compared to Friedewald (F-LDL-C), Martin (M-LDL-C), extended Martin (eM-LDL-C) and Sampson (S-LDL-C) equations by regression analysis, error-grid analysis, and concordance with the BQ method for classification into different LDL-C treatment intervals. For triglycerides (TG) < 175 mg/dL, the four LDL-C equations yielded similarly accurate results, but for TG between 175 and 800 mg/dL, the S-LDL-C equation when compared to the BQ method had a lower mean absolute difference (mg/dL) (MAD = 10.66) than F-LDL-C (MAD = 13.09), M-LDL-C (MAD = 13.16) or eM-LDL-C (MAD = 12.70) equations. By error-grid analysis, the S-LDL-C equation for TG > 400 mg/dL not only had the least analytical errors but also the lowest frequency of clinically relevant errors at the low (<70 mg/dL) and high (>190 mg/dL) LDL-C cut-points (S-LDL-C: 13.5%, F-LDL-C: 23.0%, M-LDL-C: 20.5%) and eM-LDL-C: 20.0%) equations. The S-LDL-C equation also had the best overall concordance to the BQ reference method for classifying patients into different LDL-C treatment intervals. The S-LDL-C equation is both more analytically accurate than alternative equations and results in less clinically relevant errors at high and low LDL-C levels.

Causal analysis identifies small HDL particles and physical activity as key determinants of longevity of older adults.

BACKGROUND: The hard endpoint of death is one of the most significant outcomes in both clinical practice and research settings. Our goal was to discover direct causes of longevity from medically accessible data. METHODS: Using a framework that combines local causal discovery algorithms with discovery of maximally predictive and compact feature sets (the "Markov boundaries" of the response) and equivalence classes, we examined 186 variables and their relationships with survival over 27 years in 1507 participants, aged ≥71 years, of the longitudinal, community-based D-EPESE study. FINDINGS: As few as 8-15 variables predicted longevity at 2-, 5- and 10-years with predictive performance (area under receiver operator characteristic curve) of 0·76 (95% CIs 0·69, 0·83), 0·76 (0·72, 0·81) and 0·66 (0·61, 0·71), respectively. Numbers of small high-density lipoprotein particles, younger age, and fewer pack years of cigarette smoking were the strongest determinants of longevity at 2-, 5- and 10-years, respectively. Physical function was a prominent predictor of longevity at all time horizons. Age and cognitive function contributed to predictions at 5 and 10 years. Age was not among the local 2-year prediction variables (although significant in univariable analysis), thus establishing that age is not a direct cause of 2-year longevity in the context of measured factors in our data that determine longevity. INTERPRETATION: The discoveries in this study proceed from causal data science analyses of deep clinical and molecular phenotyping data in a community-based cohort of older adults with known lifespan. FUNDING: NIH/NIA R01AG054840, R01AG12765, and P30-AG028716, NIH/NIA Contract N01-AG-12102 and NCRR 1UL1TR002494-01.

Changes in HDL cholesterol, particles, and function associate with pediatric COVID-19 severity.

Background: Myriad roles for high-density lipoprotein (HDL) beyond atheroprotection include immunologic functions implicated in the severity of coronavirus disease-2019 (COVID-19) in adults. We explored whether there is an association between HDL and COVID-19 severity in youth. Methods: A pediatric cohort (N = 102), who tested positive for COVID-19 across a range of disease manifestations from mild or no symptoms, to acute severe symptoms, to the multisystem inflammatory syndrome of children (MIS-C) was identified. Clinical data were collected from the medical record and reserve plasma aliquots were assessed for lipoproteins by NMR spectroscopy and assayed for HDL functional cholesterol efflux capacity (CEC). Findings were compared by COVID-19 status and symptom severity. Lipoprotein, NMR spectroscopy and CEC data were compared with 30 outpatient COVID negative children. Results: Decreasing HDL cholesterol (HDL-c), apolipoprotein AI (ApoA-I), total, large and small HDL particles and HDL CEC showed a strong and direct linear dose-response relationship with increasing severity of COVID-19 symptoms. Youth with mild or no symptoms closely resembled the uninfected. An atypical lipoprotein that arises in the presence of severe hepatic inflammation, lipoprotein Z (LP-Z), was absent in COVID-19 negative controls but identified more often in youth with the most severe infections and the lowest HDL parameters. The relationship between HDL CEC and symptom severity and ApoA-I remained significant in a multiply adjusted model that also incorporated age, race/ethnicity, the presence of LP-Z and of GlycA, a composite biomarker reflecting multiple acute phase proteins. Conclusion: HDL parameters, especially HDL function, may help identify youth at risk of more severe consequences of COVID-19 and other novel infectious pathogens.

Lipoprotein-X and Lipoprotein-Z Induced Hyperviscosity Syndrome in the Setting of Cholestatic Liver Failure.

We describe a case referred for worsening hypercholesterolemia in the setting of atorvastatin and fenofibrate-induced liver injury. The patient reported neurological complaints attributed to hyperviscosity syndrome (induced by lipoprotein-X and lipoprotein-Z). Hepatic recovery was associated with reduction of whole blood viscosity and amelioration of neurological symptoms. (Level of Difficulty: Advanced.).