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Abstract Background Obesity is a complex, diverse and multifactorial disease that has become a major public health concern in the last decades. The current classification systems relies on anthropometric measurements, such as BMI, that are unable to capture the physiopathological diversity of this disease. The aim of this study was to redefine the classification of obesity based on the different H-NMR metabolomics profiles found in individuals with obesity to better assess the risk of future development of cardiometabolic disease. Materials and methods Serum samples of a subset of the Di@bet.es cohort consisting of 1387 individuals with obesity were analyzed by H-NMR. A K-means algorithm was deployed to define different H-NMR metabolomics-based clusters. Then, the association of these clusters with future development of cardiometabolic disease was evaluated using different univariate and multivariate statistical approaches. Moreover, machine learning-based models were built to predict the development of future cardiometabolic disease using BMI and waist-to-hip circumference ratio measures in combination with H-NMR metabolomics. Results Three clusters with no differences in BMI nor in waist-to-hip circumference ratio but with very different metabolomics profiles were obtained. The first cluster showed a metabolically healthy profile, whereas atherogenic dyslipidemia and hypercholesterolemia were predominant in the second and third clusters, respectively. Individuals within the cluster of atherogenic dyslipidemia were found to be at a higher risk of developing type 2 DM in a 8 years follow-up. On the other hand, individuals within the cluster of hypercholesterolemia showed a higher risk of suffering a cardiovascular event in the follow-up. The individuals with a metabolically healthy profile displayed a lower association with future cardiometabolic disease, even though some association with future development of type 2 DM was still observed. In addition, H-NMR metabolomics improved the prediction of future cardiometabolic disease in comparison with models relying on just anthropometric measures. Conclusions This study demonstrated the benefits of using precision techniques like H-NMR to better assess the risk of obesity-derived cardiometabolic disease.

Abstract Rheumatoid arthritis (RA) is a chronic autoimmune disease that causes joint pain and disability. The connection between RA and cardiovascular (CV) disease is still being studied. This research aims to explore the relationship between CV-related microRNAs, inflammation, and glycosylated proteins to understand RA’s inflammatory pathophysiology concerning CV disease. The study included 219 RA patients, 82 with metabolic disorders, and 64 controls. Clinical evaluations and blood samples were collected. Quantification of microRNAs (Let7a, 24, 96, 103, 125a, 125b, 132, 146, 191, 223, 425, 451) and measurement of glycoproteins (GlycA, GlycB, GlycF) using proton nuclear magnetic resonance (1 H-NMR) were performed. Multivariate linear models were applied. RA patients showed higher glycoprotein levels than those with metabolic disorders and controls. Significant associations between miRNAs 24, 451, Let7a and glycoprotein levels were found in RA patients, particularly in women. Glycoprotein levels were positively correlated with inflammatory markers, highlighting their role in indicating RA severity. This study highlights elevated glycoprotein levels in RA patients, indicating a severe inflammatory pattern. Moreover, glycoproteins were highly associated with CV-disease-related miRNAs, indicating that glycoproteins are involved in both inflammation and CV disease. Finally, the inflammatory profile of glycoproteins was validated as they were highly associated with inflammatory markers of RA.

Background: We scrutinized variations in the proton nuclear magnetic resonance (1H NMR) lipoprotein and glycoprotein profiles among hospitalized individuals with infectious diseases. Methods: We obtained sera from 124 patients with COVID-19, 50 patients with catheter-related bacterial infections, and 50 healthy volunteers. Results were interpreted using machine learning. Results: COVID-19 patients had bigger and more abundant VLDL particles than the control group and higher VLDL-cholesterol and VLDL-triglyceride concentrations. Patients with bacterial infections showed similar trends, but differences often did not reach statistical significance. Both types of patients showed lower LDL-cholesterol concentrations than the controls. LDL were larger, and the number of particles was lower than that of the healthy individuals. HDL particles had decreased cholesterol and increased triglycerides. Small particles were reduced. Glycoproteins were increased in both groups of patients. All these alterations were more pronounced in COVID-19 patients than those with bacterial infections. The diagnostic accuracy of these profiles exceeded 90 % when distinguishing between healthy individuals and patients, and 85 % when differentiating between the two patient groups. Conclusion: Our findings highlight the potential of 1H NMR analysis for lipoproteins and glycoproteins as infection biomarkers. Additionally, they reveal differences between viral and bacterial infections, shedding light on an area with promising clinical significance.

Abstract Background and aim Circulating biomarkers of metabolic and cardiovascular diseases can help in the early detection and prevention of those diseases. Using proton nuclear magnetic resonance (1H-NMR), we aimed to study the plasma levels of low-molecular-weight metabolites (LMWMs) in a cohort of 307 patients with metabolic diseases to assess their relationships with type-2 diabetes (T2D) and incident atherosclerotic cardiovascular disease (ASCVD). Methods We conducted a cross-sectional and prospective study. We included 307 patients attending the Lipid Unit of our University Hospital for the treatment of the following metabolic disturbances and associated disorders: T2D (73.9%), obesity (58.7%), and hypertension (55.1%). 1H-NMR was used to study the plasma levels of 13 LMWMs. LMWM serum concentrations were evaluated in patients with and without T2D. and the correlations with several parameters and their associations with T2D were analyzed. The association between LMWM levels at baseline and the development of ASCVD in patients with T2D after 10 years of follow-up was also evaluated. Results Among the LMWMs measured, the branched-chain amino acids (BCAAs) valine, leucine and isoleucine showed a positive association with several clinical and lipid-related biochemical parameters and inflammatory markers (p

Sexual dimorphism influences cardiovascular outcomes in type 1 diabetes (T1D), with women facing a higher relative risk of macrovascular events compared to men, especially after menopause. This study hypothesizes that abnormalities in intermediate metabolism may be associated with cardiac autonomic neuropathy (CAN) in T1D. We aim to assess low molecular weight metabolites (LMWM) as markers of CAN in T1D, considering the effects of sexual dimorphism and age. In this cross-sectional study, we included 323 subjects with T1D (147 women and 176 men), with a mean age of 41 ± 13 years. A total of 44 women and 41 men were over 50 years old. CAN was assessed using Ewing’s tests, and serum metabolites were analyzed by proton nuclear magnetic resonance spectroscopy (1H-NMR). Patients with CAN had lower levels of valine, isoleucine, and threonine, and higher levels of lactate, compared to those without CAN. These differences persisted after adjusting for BMI and estimated glucose disposal rate (eGDR). In a logistic regression model (R² = 0.178, p < 0.001), the main determinants of CAN included isoleucine [Exp(β) = 0.972 (95% CI 0.952; 0.003)], age [Exp(β) = 1.031 (95% CI 1.010; 1.053)], A1c [Exp(β) = 1.361 (95% CI 1.058; 1.752)], and microangiopathy [Exp(β) = 2.560 (95% CI 1.372; 4.778)]. Sex influenced LMWM profiles, with over half of the metabolites differing between men and women. However, no interactions were found between CAN and sex, or between sex, age, and CAN, on metabolomics profiles. Our findings suggest an association between CAN and LMWM levels in T1D. The sexual dimorphism observed in amino acid metabolites was unaffected by the presence of CAN.

Abstract Background Subjects with Type 1 diabetes mellitus (T1DM) have an increased incidence of heart failure (HF). Several pathophysiological mechanisms have been involved in its development. The aim of this study was to analyze the potential contribution of the advanced lipoprotein profile and plasma glycosylation (GlycA) to the presence of subclinical myocardial dysfunction in subjects with T1DM. Methods We included subjects from a Danish cohort of T1DM subjects (Thousand & 1 study) with either diastolic and/or systolic subclinical myocardial dysfunction, and a control group without myocardial dysfunction, matched by age, sex and HbA1c. All underwent a transthoracic echocardiogram and an advanced lipoprotein profile obtained by using the NMR-based Liposcale® test. GlycA NMR signal was also analyzed. Systolic dysfunction was defined as left ventricular ejection fraction ≤ 45% and diastolic dysfunction was considered as E/e′≥12 or E/e′ 8–12 + volume of the left atrium > 34 ml/m2. To identify a metabolic profile associated with the presence of subclinical myocardial dysfunction, a multivariate supervised model of classification based on least squares regression (PLS-DA regression) was performed. Results One-hundred forty-six subjects had diastolic dysfunction and 18 systolic dysfunction. Compared to the control group, patients with myocardial dysfunction had longer duration of diabetes (p = 0.005), and higher BMI (p = 0.013), serum NTproBNP concentration (p = 0.001), systolic blood pressure (p

IntroductionDyslipidemia secondary to obesity is a risk factor related to cardiovascular disease events, however a pathological conventional lipid profile (CLP) is infrequently found in obese children. The objective is to evaluate the advanced lipoprotein testing (ALT) and its relationship with cardiac changes, metabolic syndrome (MS) and inflammatory markers in a population of morbidly obese adolescents with normal CLP and without type 2 diabetes mellitus, the most common scenario in obese adolescents.MethodsProspective case-control research of 42 morbidly obese adolescents and 25 normal-weight adolescents, whose left ventricle (LV) morphology and function had been assessed. The ALT was obtained by proton nuclear magnetic resonance spectroscopy, and the results were compared according to the degree of cardiac involvement – normal heart, mild LV changes, and severe LV changes (specifically LV remodeling and systolic dysfunction) – and related to inflammation markers [highly-sensitive C-reactive protein and glycoprotein A (GlycA)] and insulin-resistance [homeostatic model assessment for insulin-resistance (HOMA-IR)]. A second analysis was performed to compare our results with the predominant ALT when only body mass index and metabolic syndrome criteria were considered.ResultsThe three cardiac involvement groups showed significant increases in HOMA-IR, inflammatory markers and ALT ratio LDL-P/HDL-P (40.0 vs. 43.9 vs. 47.1, p 0.012). When only cardiac change groups were considered, differences in small LDL-P (565.0 vs. 625.1 nmol/L, p 0.070), VLDL size and GlycA demonstrated better utility than just traditional risk factors to predict which subjects could present severe LV changes [AUC: 0.79 (95% CI: 0.54–1)]. In the second analysis, an atherosclerotic ALT was detected in morbidly obese subjects, characterized by a significant increase in large VLDL-P, small LDL-P, ratio LDL-P/HDL-P and ratio HDL-TG/HDL-C. Subjects with criteria for MS presented overall worse ALT (specially in triglyceride-enriched particles) and remnant cholesterol values.ConclusionsALT parameters and GlycA appear to be more reliable indicators of cardiac change severity than traditional CV risk factors. Particularly, the overage of LDL-P compared to HDL-P and the increase in small LDL-P with cholesterol-depleted LDL particles appear to be the key ALT's parameters involved in LV changes. Morbidly obese adolescents show an atherosclerotic ALT and those with MS present worse ALT values.

Abstract Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of Lewy-type synucleinopathies (LTS), which can present either with an initial predominant parkinsonism (Parkinson’s disease (PD)) or dementia (dementia with Lewy bodies (DLB)). To provide insights into the underlying pathogenic mechanisms, the lipoprotein and protein glycosylation profile of 82 iRBD patients, collected before and/or after their conversion to an overt LTS, and 29 matched control serum samples were assessed by nuclear magnetic resonance (NMR) spectroscopy. Data were statistically analyzed to identify altered metabolites and construct predictive models. Univariant analysis detected no differences between iRBD patients with an LTS compared to controls. However, significant differences were found when the analysis distinguished between iRBD patients that manifested initially predominant parkinsonism (pre-PD) or dementia (pre-DLB). Significant differences were also found in the analysis of paired iRBD samples pre- and post-LTS diagnosis. Predictive models were built and distinguished between controls and pre-DLB patients, and between pre-DLB and pre-PD patients. This allowed a prediction of the possible future clinical outcome of iRBD patients. We provide evidence of altered lipoprotein and glycosylation profiles in subgroups of iRBD patients. Our results indicate that metabolic alterations and inflammation are involved in iRBD pathophysiology, and suggest biological differences underlying the progression of LTS in iRBD patients. Our data also indicate that profiling of serum samples by NMR may be a useful tool for identifying short-term high-risk iRBD patients for conversion to parkinsonism or dementia.

Abstract Patients with morbid obesity frequently present non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH) associated with pro-atherogenic alterations. Laparoscopic sleeve gastrectomy (LSG) is an effective treatment for weight reduction, and for the remission of hepatic alterations. Using 1H-nuclear magnetic resonance (1H-NMR), we investigated the effects of LSG on lipoprotein and glycoprotein profile in patients with morbid obesity and liver disease. We included 154 patients with morbid obesity (49 non-NASH, 54 uncertain NASH, 51 definite NASH). A blood sample was obtained before surgery and, in patients with definite NASH, one year after surgery. Patients with NASH had increased concentrations of medium and small VLDL particles, VLDL and IDL cholesterol concentrations, IDL, LDL, and HDL triglyceride concentrations, and elevated glycoprotein levels. These changes were more marked in patients with type 2 diabetes mellitus. LSG produced significant decreases in the concentration of VLDL particles, VLDL cholesterol and triglycerides, an increase in the concentration LDL particles and LDL cholesterol concentrations, and a decrease in protein glycation. We conclude that patients with obesity and NASH had significant alterations in circulating levels of lipoproteins and glycoproteins that were associated with the severity of the disease. Most of these changes were reversed post-LSG.

Atherosclerosis is a chronic inflammatory disease caused by the accumulation of cholesterol in the intima. Proprotein convertase subtilisin/kexin type 9 inhibitors (iPCSK9) can reduce low-density lipoprotein (LDL) cholesterol levels by 60%, but there is still no evidence that they can lower markers of systemic inflammation such as high-sensitivity C-reactive protein (hsCRP). Acute-phase serum glycoproteins are upregulated in the liver during systemic inflammation, and their role as inflammatory biomarkers is under clinical evaluation. In this observational study, we evaluate the effects of iPCSK9 on glycoproteins (Glyc) A, B and F. Thirty-nine patients eligible for iPCSK9 therapy were enrolled. One sample before and after one to six months of iPCSK9 therapy with alirocumab was obtained from each patient. Lipids, apolipoproteins, hsCRP and PCSK9 levels were measured by biochemical analyses, and the lipoprotein and glycoprotein profiles were measured by 1H nuclear magnetic resonance (1H-NMR). The PCSK9 inhibitor reduced total (36.27%, p < 0.001), LDL (55.05%, p < 0.001) and non-high-density lipoprotein (HDL) (45.11%, p < 0.001) cholesterol, apolipoprotein (apo) C-III (10%, p < 0.001), triglycerides (9.92%, p < 0.001) and glycoprotein signals GlycA (11.97%, p < 0.001), GlycB (3.83%, p = 0.017) and GlycF (7.26%, p < 0.001). It also increased apoA-I (2.05%, p = 0.043) and HDL cholesterol levels (11.58%, p < 0.001). Circulating PCSK9 levels increased six-fold (626.28%, p < 0.001). The decrease in Glyc signals positively correlated with the decrease in triglycerides and apoC-III. In conclusion, in addition to LDL cholesterol, iPCSK9 therapy also induces a reduction in systemic inflammation measured by 1H-NMR glycoprotein signals, which correlates with a decrease in triglycerides and apoC-III.

Elite controllers (ECs) are an exceptional group of people living with HIV (PLWH) who maintain undetectable viral loads (VLs) despite not being on antiretroviral therapy (ART). However, this phenotype is heterogeneous, with some of these subjects losing virological control over time. In this longitudinal retrospective study, serum acute-phase glycoprotein profile assessed by proton nuclear magnetic resonance (1H-NMR) was determined in 11 transient controllers (TCs) who spontaneously lost virological control and 11 persistent controllers (PCs) who persistently maintained virological control over time. Both PCs and TCs showed similar acute-phase glycoprotein profiles, even when TCs lost the virological control (GlycB, p = 0.824 and GlycA, p = 0.710), and the serum acute-phase glycoprotein signature in PCs did not differ from that in HIV-negative subjects (GlycB, p = 0.151 and GlycA, p = 0.243). Differences in serum glycoproteins A and B were significant only in ECs compared to HIV-typical progressors (TPs) with < 100 CD4+ T-cells (p < 0.001). 1H-NMR acute-phase glycoprotein profile does not distinguish TCs form PCs before the loss of viral control. ECs maintain a low-grade inflammatory state compared to TPs. PCs revealed a closer serum signature to HIV-negative subjects, reaffirming this phenotype as a closer model of functional control of HIV.

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are serious health concerns for which lifestyle interventions are the only effective first-line treatment. Dietary interventions are effective in body weight reduction, but not in improving insulin sensitivity and hepatic lipid mobilization. Conversely, metformin increases insulin sensitivity and promotes the inhibition of de novo hepatic lipogenesis. In this study, we evaluated the metformin effectiveness in NASH prevention and treatment, when combined with dietary intervention in male mice fed a high-fat high-sucrose diet (HFHSD). Eighty 5-week-old C57BL/6J male mice were fed a chow or HFHSD diet and sacrificed at 20 or 40 weeks. The HFHSD-fed mice developed NASH after 20 weeks. Lipoprotein and lipidomic analyses showed that the changes associated with diet were not prevented by metformin administration. HFHSD-fed mice subject to dietary intervention combined with metformin showed a 19.6% body weight reduction compared to 9.8% in those mice subjected to dietary intervention alone. Lower hepatic steatosis scores were induced. We conclude that metformin should not be considered a preventive option for NAFLD, but it is effective in the treatment of this disorder when combined with dietary intervention.

Abnormal lipid metabolism is associated with gestational diabetes mellitus (GDM) and is observed in neonates with abnormal fetal growth. However, the underlying specific changes in the lipoprotein profile remain poorly understood. Thus, in the present study we used a novel nuclear magnetic resonance (NMR)-based approach to profile the umbilical cord serum lipoproteins. Two-dimensional diffusion-ordered 1H-NMR spectroscopy showed that size, lipid content, number and concentration of particles within their subclasses were similar between offspring born to control (n = 74) and GDM (n = 62) mothers. Subsequent data stratification according to newborn birth-weight categories, i.e., small (n = 39), appropriate (n = 50) or large (n = 49) for gestational age (SGA, AGA and LGA, respectively), showed an interaction between GDM and birth-weight categories for intermediate-density lipoproteins (IDL)-cholesterol content and IDL- and low-density lipoproteins (LDL)-triglyceride content, and the number of medium very low-density lipoproteins (VLDL) and LDL particles specifically in AGA neonates. Moreover, in a 2-year follow-up study, we observed that small LDL particles were independently associated with offspring obesity at 2 years (n = 103). Collectively, our data demonstrate that GDM disturbs triglyceride and cholesterol lipoprotein content across birth-weight categories, with AGA neonates born to GDM mothers displaying a profile more similar to that of adults with dyslipidemia. Furthermore, an altered fetal lipoprotein pattern was associated with the development of obesity at 2 years.

We aimed to assess the potential relationship between dietary patterns (i.e., Mediterranean diet and healthy eating) and the advanced lipoprotein profile (ALP) in a representative cohort of the Mediterranean population. Thus, ALP data from 1142 participants, including 222 with type 1 (19.4%) and 252 type 2 diabetes (22.1%), and 668 subjects without diabetes were used to study cross-sectional associations between quantitative characteristics of lipoproteins and adherence to the Mediterranean diet. The alternate Mediterranean diet score (aMED) and the alternate healthy eating index (aHEI) were calculated. The ALP was determined by nuclear magnetic resonance (NMR) spectrometry. Bivariable and multivariable analyses were performed. Participants in the third tertile of the aMED showed higher levels of low-density lipoprotein triglycerides (LDL-TG) (mean (SD) 17.5 (5.0); p = 0.037), large high-density lipoprotein particles (HDL-P) (0.3 (0.1); p = 0.037), and medium low-density lipoprotein particles (LDL-P) (434.0 (143.0); p = 0.037). In comparison with participants in the second and first tertiles of the aHEI, participants in the third tertile had higher levels of LDL-TG (17.7 (5.0); p = 0.010), and large HDL-P (0.3 (0.1); p = 0.002), IDL-C (11.8 (5.0); p = 0.001), intermediate-density lipoprotein triglycerides (IDL-TG) (13.2 (4.2); p < 0.001), LDL-TG (17.7(5.0); p = 0.010), high-density lipoprotein triglycerides (HDL-TG) (14.5 (4.4); p = 0.029,) large HDL-P (0.3 (0.1); p = 0.002) and very–low-density lipoprotein particles (VLDL-P) size (42.1 (0.2); p = 0.011). The adjusted-multivariable analysis for potential confounding variables did not show any association between the lipoproteins and dietary patterns (i.e., aMED and aHEI). In conclusion, none of the quantitative characteristics of lipoproteins were concomitantly associated with the extent of adherence to the Mediterranean diet measured using the aMED or aHEI scores in the studied population. Our findings also revealed that people with the highest adherence were older, had a higher body mass index (BMI) and more frequently had dyslipidemia, hypertension, or diabetes than those with the lowest adherence to the Mediterranean diet (MDiet). Thus, further research may be needed to assess the potential role of the dietary pattern on the ALP.

Patients with type 2 diabetes mellitus (T2DM) and atherogenic dyslipidemia (AD) are at higher risk of developing cardiovascular diseases (CVDs), so an interest in discovering inflammation biomarkers as indicators of processes related to CVD progression is increasing. This study aims (a) to characterize the plasma glycoprotein profile of a cohort of 504 participants, including patients with and without T2DM and/or AD and controls, and (b) to study the associations between the glycoprotein profile and other lipid and clinical variables in these populations. We characterized the plasma glycoprotein profiles by using 1H-NMR. We quantified the two peaks associated with the concentration of plasma glycoproteins (GlycA and GlycB) and their height/width ratios (H/W GlycA and H/W GlycB), as higher and narrower signals have been related to inflammation. We also quantified GlycF, the signal of which is proportional to the concentration of the acetyl groups of free N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic in the samples. The lipoprotein profile was also determined (Liposcale®). Standard clinical and anthropometric measurements were taken. Multivariate classification models were developed to study the differences between the study groups. Reduced HDL-C levels, increased small dense LDL and HDL particles, and elevated TG levels were significantly associated with glycoprotein variables. Glycoprotein values in the diagnostic groups were significantly different from those in the CT groups. AD and DM conditions together contribute to a positive and significant synergetic effect on the GlycA area (1H-NMR-derived glycoproteins can be used as possible markers of the degree of inflammation associated with T2DM and AD.

Determination of lipoprotein particle size and number using advanced lipoprotein tests (ALTs) is of particular importance to improve cardiovascular risk prediction. Here we present the Liposcale test, a novel ALT based on 2D diffusion-ordered 1H NMR spectroscopy. Our method uses diffusion coefficients to provide a direct measure of the mean particle sizes and numbers. Using 177 plasma samples from healthy individuals and the concentration of ApoB and ApoA from isolated lipoprotein fractions, our test showed a stronger correlation between the NMR-derived lipoprotein particle numbers and apolipoprotein concentrations than the LipoProfile® test commercialized by Liposcience. We also converted LDL particle numbers to ApoB equivalents (milligrams per deciliter) and our test yielded similar values of LDL-ApoB to the LipoProfile® test (absolute mean bias of 8.5 and 7.4 mg/dl, respectively). In addition, our HDL particle number values were more concordant with the calibrated values determined recently using ion mobility. Finally, principal component analysis distinguished type 2 diabetic patients with and without atherogenic dyslipidemia (AD) on a second cohort of 307 subjects characterized using the Liposcale test (area under the curve = 0.88) and showed concordant relationships between variables explaining AD. Altogether, our method provides reproducible and reliable characterization of lipoprotein particles and it is applicable to pathological states such as AD.

We investigated alterations in the levels of the antioxidant paraoxonase-1 (PON1) and the lipoprotein profile (analyzed by nuclear magnetic resonance) in patients with lung cancer (LC) or head and neck cancer (HNC), and the effects produced thereon by radiotherapy (RT). We included 33 patients with LC and 28 patients with HNC. Before irradiation, and one month after completion of RT, blood samples were obtained. The control group was composed of 50 healthy subjects. Patients had significantly lower serum PON1 activity and concentration before RT than the control group. PON1-related variables were good predictors of the presence of LC or HNC, with analytical sensitivities and specificities greater than 80%. Patients showed a significant increase in the number of particles of all subclasses of very-low-density lipoproteins (large, medium and small). However, these changes were not maintained when adjusted for age, sex, and other clinical and demographic variables. Irradiation was associated with a significant increase in PON1 concentration and, only in patients with HNC, with an increase in high-density lipoprotein-cholesterol concentration. Our results suggest that determinations of the levels of PON1-related variables may constitute good biomarkers for the evaluation of these diseases. Studies with a larger number of patients are needed to fully confirm this hypothesis.

While cholesterol content in high-density lipoproteins (HDLs) is a well-established inverse marker of cardiovascular risk, the importance of HDL−triglyceride (HDL-TG) concentration is not well known. We aim to examine plasma HDL-TG concentrations, assessed by 1H-NMR, in patients with metabolic diseases and their association with classical biomarkers. In this cross-sectional study, we included 502 patients with type 2 diabetes or metabolic syndrome attending the lipid unit of our University Hospital. The presence of arteriosclerotic plaques was assessed by ultrasonography. A complete lipoprotein profile was performed by 1H-NMR (Liposcale test). HDL-TG was strongly positively correlated with total triglycerides, glycerol, and fatty liver index, while a strong negative correlation was observed with HDL-cholesterol (HDL-C) and HDL-particle number (HDL-P). HDL-TG was associated with all triglyceride-rich lipoprotein parameters and had an opposite association with HDL-C and HDL-P. It was also significantly correlated with circulating cholesterol ester transfer protein (CETP). HDL-TG concentrations were higher as metabolic syndrome components increased. HDL-TG was also higher with worsening glucose metabolism. Patients with carotid plaques also showed higher HDL-TG. In contrast to HDL-C, HDL-TG is directly associated with metabolism and arteriosclerotic vascular alterations. HDL-TG should be considered a biomarker of metabolic and cardiovascular risk and could be a marker of HDL dysfunction.

Background The familial hypercholesterolemia (FH) diagnosis is based on clinical and genetic criteria. A relevant proportion of FH patients fulfilling the criteria for definite FH have negative genetic testing. Increasing the identification of true genetic-based FH is a clinical challenge. Deepening the analysis of lipoprotein alterations could help increase the yield of genetic testing. We evaluated whether the number, size, and composition of lipoproteins assessed by 1H-NMR could increase the identification of FH patients with pathogenic gene variants. Methods We studied 294 clinically definite FH patients, 222 (75.5%) with positive genetic testing, as the discovery cohort. As an external validation cohort, we studied 88 children with FH, 72 (81%) with positive genetic testing. The advanced lipoprotein test based on 1H-NMR (Liposcale®) was performed at baseline after a lipid-lowering drug washout of at least 6 weeks. The association of variables with genetic variants was evaluated by random forest and logistic regression. Areas under the curve (AUCs) were calculated. A predictive formula was developed and applied to the validation cohort. Results A formula derived from nuclear magnetic resonance (NMR) lipoprotein analyses improved the identification of genetically positive FH patients beyond low-density lipoprotein (LDL)-cholesterol levels (AUC = 0.87). The parameters contributing the most to the identification formula were LDL particle number, high-density lipoprotein size, and remnant cholesterol. The formula also increases the classification of FH children with a pathogenic genetic variation. Conclusion NMR lipoprotein profile analysis identifies differences beyond standard lipid parameters that help identify FH with a positive pathogenic gene variant, increasing the yield of genetic testing in FH patients. [ABSTRACT FROM AUTHOR]

This prospective observational study compared the 1H NMR blood lipidomes and metabolomes of 71 patients with community-acquired pneumonia (CAP), 75 patients with COVID-19 pneumonia, and 75 healthy controls (matched by age and sex) to identify potential biomarkers and pathways associated with respiratory infections. Both pneumonia groups had comparable severity indices, including mortality, invasive mechanical ventilation, and intensive care unit admission rates. Patients with COVID-19 pneumonia exhibited more pronounced hypolipidemia, with significantly lower levels of total cholesterol and LDL-c compared to patients with CAP. Atherogenic lipoprotein subclasses (VLDL-cholesterol, IDL-cholesterol, IDL-triglyceride, and LDL-triglyceride/LDL-cholesterol) were significantly increased in severe cases of both pneumonia types, while lower HDL-c and small, dense HDL particles were associated with more severe illness. Both infected groups showed decreased esterified cholesterol and increased triglycerides, along with reduced phosphatidylcholine, lysophosphatidylcholine, PUFA, omega-3 fatty acids, and DHA. Additionally, infected patients had elevated levels of glucose, lactate, 3-hydroxybutyrate, and acetone, which are linked to inflammation, hypoxemia, and sepsis. Increased levels of branched-chain amino acids, alanine, glycine, and creatine, which are involved in energy metabolism and protein catabolism, were also observed. Neurotransmitter synthesis metabolites like histidine and glutamate were higher in infected patients, especially those with COVID-19. Notably, severe infections showed a significant decrease in glutamine, essential for lymphocyte and macrophage energy. The severity of COVID-19 pneumonia was also associated with elevated glycoprotein levels (glycoprotein A, glycoprotein B, and glycoprotein F), indicating an inflammatory state. These findings suggest that metabolomic and lipidomic changes in pneumonia are connected to bioenergetic pathways regulating the immune response.

Background and aims: Mastitis is one of the main complications during breastfeeding and contributes to the cessation of breastfeeding. However, the etiopathogenesis and diagnosis of mastitis are complex and not yet well defined. We aimed to identify metabolic and lipidic changes in human milk during acute and subacute mastitis in order to detect potential biomarkers of mastitis. Methods: We conducted a pilot case–control study including 14 breastfeeding women with acute mastitis, 32 with subacute mastitis symptoms, and 19 without any mastitis symptoms (control). Milk samples were collected and analyzed by proton nuclear magnetic resonance (H-NMR) for metabolomics analysis. To assess the association between the significant metabolites and lipids and the development of acute and subacute mastitis, multi-adjusted logistic regression models were developed. Results: The NMR-based metabolomics approach was able to identify and quantify a total of 40 metabolites in breast milk samples. After adjusting for confounding variables, acute mastitis was significantly associated with acetate (OR 3.9 IC 1.4–10.8), total cholesterol (OR 14 CI 3.2–62), esterified cholesterol (OR 3.3 CI 1.9–5.8), and sphingomyelin (OR 2.6 CI 1.2–5.8). The other metabolites presented weak association (OR < 2.5). Subacute mastitis was significantly associated with glutamine, lysophosphatidylcholine, phosphatidylcholine, plasmalogen, and total polyunsaturated fatty acids, but only cholesterol showed a strong association (OR > 2.5) with an OR of 2.6 (IC 1.1–6.6). Conclusions: Metabolic alteration in breast milk occurs during a process of both acute and subacute mastitis. Acetate, esterified cholesterol, lysophostidylcholine, and polyunsaturated fatty acids increased in both acute and subacute mastitis. However, according to the multi-adjusted regression logistic models, the candidate biomarkers for acute and subacute mastitis are cholesterol, lysophosphatidylcoholine, phosphatidylcholine, plasmalogen, and polyunsaturated fatty acids.

Hibernation is a period of metabolic suppression utilized by many small and large mammal species to survive during winter periods. As the underlying cellular and molecular mechanisms remain incompletely understood, our study aimed to determine whether skeletal muscle myosin and its metabolic efficiency undergo alterations during hibernation to optimize energy utilization. We isolated muscle fibers from small hibernators, Ictidomys tridecemlineatus and Eliomys quercinus and larger hibernators, Ursus arctos and Ursus americanus. We then conducted loaded Mant-ATP chase experiments alongside X-ray diffraction to measure resting myosin dynamics and its ATP demand. In parallel, we performed multiple proteomics analyses. Our results showed a preservation of myosin structure in U. arctos and U. americanus during hibernation, whilst in I. tridecemlineatus and E. quercinus, changes in myosin metabolic states during torpor unexpectedly led to higher levels in energy expenditure of type II, fast-twitch muscle fibers at ambient lab temperatures (20 °C). Upon repeating loaded Mant-ATP chase experiments at 8 °C (near the body temperature of torpid animals), we found that myosin ATP consumption in type II muscle fibers was reduced by 77–107% during torpor compared to active periods. Additionally, we observed Myh2 hyper-phosphorylation during torpor in I. tridecemilineatus, which was predicted to stabilize the myosin molecule. This may act as a potential molecular mechanism mitigating myosin-associated increases in skeletal muscle energy expenditure during periods of torpor in response to cold exposure. Altogether, we demonstrate that resting myosin is altered in hibernating mammals, contributing to significant changes to the ATP consumption of skeletal muscle. Additionally, we observe that it is further altered in response to cold exposure and highlight myosin as a potentially contributor to skeletal muscle non-shivering thermogenesis.

Summary: Fetal growth restriction (FGR) affects 5–10% of pregnancies, is the largest contributor to fetal death, and can have long-term consequences for the child. Implementation of a standard clinical classification system is hampered by the multiphenotypic spectrum of small fetuses with substantial differences in perinatal risks. Machine learning and multiomics data can potentially revolutionize clinical decision-making in FGR by identifying new phenotypes. Herein, we describe a cluster analysis of FGR based on an unbiased machine-learning method. Our results confirm the existence of two subtypes of human FGR with distinct molecular and clinical features based on multiomic analysis. In addition, we demonstrated that clusters generated by machine learning significantly outperform single data subtype analysis and biologically support the current clinical classification in predicting adverse maternal and neonatal outcomes. Our approach can aid in the refinement of clinical classification systems for FGR supported by molecular and clinical signatures.

Exposure to traffic-related air pollution (TRAP) generates oxidative stress, with downstream effects at the metabolic level. Human studies of traffic density and metabolomic markers, however, are rare. The main objective of this study was to evaluate the cross-sectional association between traffic density in the street of residence with oxidative stress and metabolomic profiles measured in a population-based sample from Spain. We also explored in silico the potential biological implications of the findings. Secondarily, we assessed the contribution of oxidative stress to the association between exposure to traffic density and variation in plasma metabolite levels. Traffic density was defined as the average daily traffic volume over an entire year within a buffer of 50 m around the participants’ residence. Plasma metabolomic profiles and urine oxidative stress biomarkers were measured in samples from 1181 Hortega Study participants by nuclear magnetic resonance spectroscopy and high-performance liquid chromatography, respectively. Traffic density was associated with 7 (out of 49) plasma metabolites, including amino acids, fatty acids, products of bacterial and energy metabolism and fluid balance metabolites. Regarding urine oxidative stress biomarkers, traffic associations were positive for GSSG/GSH% and negative for MDA. A total of 12 KEGG pathways were linked to traffic-related metabolites. In a protein network from genes included in over-represented pathways and 63 redox-related candidate genes, we observed relevant proteins from the glutathione cycle. GSSG/GSH% and MDA accounted for 14.6% and 12.2% of changes in isobutyrate and the CH2CH2CO fatty acid moiety, respectively, which is attributable to traffic exposure. At the population level, exposure to traffic density was associated with specific urine oxidative stress and plasma metabolites. Although our results support a role of oxidative stress as a biological intermediary of traffic-related metabolic alterations, with potential implications for the co-bacterial and lipid metabolism, additional mechanistic and prospective studies are needed to confirm our findings.

Abstract Background The contribution of metabolomic factors to the association of healthy lifestyle with type 2 diabetes risk is unknown. We assessed the association of a composite measure of lifestyle with plasma metabolite profiles and incident type 2 diabetes, and whether relevant metabolites can explain the prospective association between healthy lifestyle and incident type 2 diabetes. Methods A Healthy Lifestyle Score (HLS) (5-point scale including diet, physical activity, smoking status, alcohol consumption and BMI) was estimated in 1016 Hortega Study participants, who had targeted plasma metabolomic determinations at baseline examination in 2001–2003, and were followed-up to 2015 to ascertain incident type 2 diabetes. Results The HLS was cross-sectionally associated with 32 (out of 49) plasma metabolites (2.5% false discovery rate). In the subset of 830 participants without prevalent type 2 diabetes, the rate ratio (RR) and rate difference (RD) of incident type 2 diabetes (n cases = 51) per one-point increase in HLS was, respectively, 0.69 (95% CI, 0.51, 0.93), and − 8.23 (95% CI, − 16.34, − 0.13)/10,000 person-years. In single-metabolite models, most of the HLS-related metabolites were prospectively associated with incident type 2 diabetes. In probit Bayesian Kernel Machine Regression, these prospective associations were mostly driven by medium HDL particle concentration and phenylpropionate, followed by small LDL particle concentration, which jointly accounted for ~ 50% of the HLS-related decrease in incident type 2 diabetes. Conclusions The HLS showed a strong inverse association with incident type 2 diabetes, which was largely explained by plasma metabolites measured years before the clinical diagnosis.

Metabolic reprogramming is required to fight infections and thyroid hormones are key regulators of metabolism. We have analyzed in hospitalized COVID-19 patients: 40 euthyroid and 39 levothyroxine (LT4)-treated patients in the ward and 29 euthyroid and 9 LT4-treated patients in the intensive care unit (ICU), the baseline characteristics, laboratory data, thyroid-stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), the FT3/FT4 ratio, 11 antiviral cytokines and 74 metabolomic parameters. No evidence for significant differences between euthyroid and LT4-treated patients were found in the biochemical, metabolomic and cytokines parameters analyzed. Only TSH (p=0.009) and ferritin (p=0.031) showed significant differences between euthyroid and LT4-treated patients in the ward, and TSH (p=0.044) and FT4 (p=0.012) in the ICU. Accordingly, severity and mortality were similar in euthyroid and LT4-treated patients. On the other hand, FT3 was negatively related to age (p=0.012), independently of sex and body mass index in hospitalized COVID-19 patients. Patients with low FT3 and older age showed a worse prognosis and higher levels of the COVID-19 severity markers IL-6 and IL-10 than patients with high FT3. IL-6 negatively correlated with FT3 (p=0.023) independently of age, body mass index and sex, whereas IL-10 positively associated with age (p=0.035) independently of FT3, body mass index and sex. A metabolomic cluster of 6 parameters defined low FT3 ward patients. Two parameters, esterified cholesterol (p=4.1x10-4) and small HDL particles (p=6.0x10-5) correlated with FT3 independently of age, body mass index and sex, whereas 3-hydroxybutyrate (p=0.010), acetone (p=0.076), creatinine (p=0.017) and high-density-lipoprotein (HDL) diameter (p=8.3x10-3) were associated to FT3 and also to age, with p-values of 0.030, 0.026, 0.017 and 8.3x10-3, respectively. In conclusion, no significant differences in FT3, cytokines, and metabolomic profile, or in severity and outcome of COVID-19, were found during hospitalization between euthyroid patients and hypothyroid patients treated with LT4. In addition, FT3 and age negatively correlate in COVID-19 patients and parameters that predict poor prognosis were associated with low FT3, and/or with age. A metabolomic cluster indicative of a high ketogenic profile defines non-critical hospitalized patients with low FT3 levels.

Abstract Preeclampsia (PE) and fetal growth restriction (FGR) are both placenta-mediated disorders with unclear pathogenesis. Metabolomics of maternal and fetal pairs might help in understanding these disorders. We recruited prospectively pregnancies with normotensive FGR, PE without FGR, PE + FGR and uncomplicated pregnancies as controls. Nuclear magnetic resonance metabolomics were applied on plasma samples collected at delivery. Advanced lipoprotein, glycoprotein and choline profiling was performed using the Liposcale test. The software package Dolphin was used to quantify 24 low-molecular-weight metabolites. Statistical analysis comprised the comparison between each group of complicated pregnancies versus controls, considering 5% false discovery rate correction. Lipid profiles were altered in accordance with the clinical presentation of these disorders. Specifically, PE mothers and FGR fetuses (with or without FGR or PE, respectively) exhibited a pro-atherogenic and pro-inflammatory profile, with higher concentrations of triglycerides, remnant cholesterol (VLDL, IDL) and Glc/GalNAc-linked and lipid-associated glycoproteins compared to controls. Low-molecular-weight metabolites were extensively disturbed in preeclamptic mothers, with or without FGR. Growth restricted fetuses in the presence of PE showed changes in low-molecular-weight metabolites similar to their mothers (increased creatine and creatinine), while normotensive FGR fetuses presented scarce differences, consistent with undernutrition (lower isoleucine). Further research is warranted to clarify maternal and fetal adaptations to PE and FGR.

Background: Limited studies have evaluated the joint influence of redox-related metals and genetic variation on metabolic pathways. We analyzed the association of 11 metals with metabolic patterns, and the interacting role of candidate genetic variants, in 1145 participants from the Hortega Study, a population-based sample from Spain. Methods: Urine antimony (Sb), arsenic, barium (Ba), cadmium (Cd), chromium (Cr), cobalt (Co), molybdenum (Mo) and vanadium (V), and plasma copper (Cu), selenium (Se) and zinc (Zn) were measured by ICP-MS and AAS, respectively. We summarized 54 plasma metabolites, measured with targeted NMR, by estimating metabolic principal components (mPC). Redox-related SNPs (N = 291) were measured by oligo-ligation assay. Results: In our study, the association with metabolic principal component (mPC) 1 (reflecting non-essential and essential amino acids, including branched chain, and bacterial co-metabolism versus fatty acids and VLDL subclasses) was positive for Se and Zn, but inverse for Cu, arsenobetaine-corrected arsenic (As) and Sb. The association with mPC2 (reflecting essential amino acids, including aromatic, and bacterial co-metabolism) was inverse for Se, Zn and Cd. The association with mPC3 (reflecting LDL subclasses) was positive for Cu, Se and Zn, but inverse for Co. The association for mPC4 (reflecting HDL subclasses) was positive for Sb, but inverse for plasma Zn. These associations were mainly driven by Cu and Sb for mPC1; Se, Zn and Cd for mPC2; Co, Se and Zn for mPC3; and Zn for mPC4. The most SNP-metal interacting genes were NOX1, GSR, GCLC, AGT and REN. Co and Zn showed the highest number of interactions with genetic variants associated to enriched endocrine, cardiovascular and neurological pathways. Conclusions: Exposures to Co, Cu, Se, Zn, As, Cd and Sb were associated with several metabolic patterns involved in chronic disease. Carriers of redox-related variants may have differential susceptibility to metabolic alterations associated to excessive exposure to metals.

Cocoa constitutes one of the richest sources of dietary flavonoids with demonstrated anti-diabetic potential. However, the metabolic impact of cocoa intake in a diabetic context remains unexplored. In this study, metabolomics tools have been used to investigate the potential metabolic changes induced by cocoa in type 2 diabetes (T2D). To this end, male Zucker diabetic fatty rats were fed on standard (ZDF) or 10% cocoa-rich diet (ZDF-C) from week 10 to 20 of life. Cocoa supplementation clearly decreased serum glucose levels, improved glucose metabolism and produced significant changes in the urine metabolome of ZDF animals. Fourteen differential urinary metabolites were identified, with eight of them significantly modified by cocoa. An analysis of pathways revealed that butanoate metabolism and the synthesis and degradation of branched-chain amino acids and ketone bodies are involved in the beneficial impact of cocoa on diabetes. Moreover, correlation analysis indicated major associations between some of these urine metabolites (mainly valine, leucine, and isoleucine) and body weight, glycemia, insulin sensitivity, and glycated hemoglobin levels. Overall, this untargeted metabolomics approach provides a clear metabolic fingerprint associated to chronic cocoa intake that can be used as a marker for the improvement of glucose homeostasis in a diabetic context.

This study aimed to assess whether the advanced characteristics of serum lipoprotein subclasses could better predict the risk of developing diabetic retinopathy (DR) and its severity compared to other established risk factors in subjects with type 1 (T1D) and type 2 (T2D) diabetes. This observational, cross-sectional substudy analyzed DR-related data from 309 T1D and 264 T2D subjects. The advanced lipoprotein and glycoprotein profile was determined by nuclear magnetic resonance (NMR) spectroscopy (Liposcale test). NMR analysis of lipoproteins revealed that T1D subjects with DR showed standard non-HDL particles, despite higher IDL lipid concentrations. Notably, IDL lipids were elevated in T1D subjects with worsened DR. VLDL and LDL were smaller, whereas HDL triglycerides were increased in DR compared with non-DR. On the other hand, the T2D subjects with DR showed altered characteristics in the LDL fraction, mainly revealed by a significant decrease in smaller LDL and a reduction in LDL-C. Moreover, the glycoprotein profile did not reveal significant changes among DR groups, regardless of the type of diabetes. However, lipoprotein characteristics and glycoproteins unveiled by NMR analysis did not improve the predictive value of conventional lipids or other traditional, well-established biomarkers of DR in our cohorts.

Background Supplementation with omega‐3 (n‐3) fatty acid or dietary fish may protect against atherosclerosis, but the potential mechanisms are unclear. Prior studies found modest triglyceride‐lowering effects and slight increases in LDL (low‐density lipoprotein) cholesterol. Limited evidence has examined n‐3 effects on more detailed lipoprotein biomarkers. Methods and Results We conducted a study of 26 034 healthy women who reported information on fish and n‐3 intake from a 131‐item food‐frequency questionnaire. We measured plasma lipids, apolipoproteins, and nuclear magnetic resonance spectroscopy lipoproteins and examined their associations with dietary intake of fish, total n‐3, and the n‐3 subtypes (eicosapentaenoic, docosahexaenoic, and α‐linolenic acids). Top‐ versus bottom‐quintile intake of fish and n‐3 were significantly associated with lower triglyceride and large VLDL (very‐low‐density lipoprotein) particles. Fish intake, but not total n‐3, was positively associated with total cholesterol, LDL cholesterol, apolipoprotein B, and larger LDL size, but only α‐linolenic acid was associated with lower LDL cholesterol. Total n‐3, docosahexaenoic acid, and α‐linolenic acid intake were also positively associated with larger HDL (high‐density lipoprotein) size and large HDL particles. High eicosapentaenoic acid intake was significantly associated with only a decreased level of VLDL particle concentration and VLDL triglyceride content. The n‐3 fatty acids had some similarities but also differed in their associations with prospective cardiovascular disease risk patterns. Conclusions Higher consumption of fish and n‐3 fatty acids were associated with multiple measures of lipoproteins that were mostly consistent with cardiovascular prevention, with differences noted for high intake of eicosapentaenoic acid versus docosahexaenoic acid and α‐linolenic acid that were apparent with more detailed lipoprotein phenotyping. These hypothesis‐generating findings warrant further study in clinical trials. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00000479.

In a previous study, we demonstrated that women enjoyed and tolerated lower meal loads than men. Hence, we hypothesized that with the same meal load, their postprandial response is more pronounced than in men. We performed a randomized parallel trial in 12 women and 12 men comparing the postprandial responses to a palatable comfort meal. We measured homeostatic sensations (hunger/satiety, fullness) and hedonic sensations (digestive well-being, mood) on 10 cm scales, vagal tone by heart ratio variability and the metabolomic profile before and after meal ingestion. Gender differences were analyzed by repeated measures ANCOVA. Overall (n = 24), ingestion of the probe meal induced satiation, fullness, digestive well-being and improved mood (main time-effect p ≤ 0.005 for all). Women exhibited a more intense sensory experience, specially more postprandial fullness, than men [main gender-effect F (1, 21) = 7.14; p = 0.014]; hedonic responses in women also tended to be stronger than in men. Women exhibited more pronounced effects on vagal tone [main gender-effect F (1, 21) = 5.5; p = 0.029] and a different lipoprotein response than men. In conclusion, our data indicate that gender influences the responses to meal ingestion, and these differences may explain the predisposition and higher incidence in women of meal-related functional disorders.

Various conditioning factors influence the sensory response to a meal (inducible factors). We hypothesized that inherent characteristics of the eater (constitutive factors) also play a role. The aim of this proof-of-concept study was to determine the role of gender, as an individual constitutive factor, on the meal-related experience. Randomized parallel trial in 10 women and 10 men, comparing the sensations before, during, and after stepwise ingestion of a comfort meal up to full satiation. Comparisons were performed by repeated Analysis of Covariance (ANCOVA) measures. During stepwise ingestion, satisfaction initially increased up to a peak, and later decreased down to a nadir at the point of full satiation. Interestingly, the amount of food consumed at the well-being peak was lower, and induced significantly less fullness in women than in men. Hence, men required a larger meal load and stronger homeostatic sensations to achieve satisfaction. The same pattern was observed at the level of full satiation: men ate more and still experienced positive well-being, whereas in women, well-being scores dropped below pre-meal level. The effect of gender on the ingestion experience suggests that other constitutive factors of the eater may also influence responses to meals.

Resumen Dos aspectos relevantes de la medicina laboral son estudiar la salud del individuo en su ámbito de trabajo y promover entornos laborales saludables. Actualmente, los factores de riesgo cardiovascular siguen liderando la morbi-mortalidad en nuestra sociedad. El entorno laboral es la oportunidad de conocer la situación real e iniciar estrategias de prevención precoz. Uno de los factores más prevalentes son las alteraciones de los lípidos, siendo el colesterol LDL el que define el riesgo del paciente, pero sabemos que no identifica a todos los pacientes en riesgo de padecer un evento, persistiendo un riesgo residual. Determinar el número y tamaño de partículas de lipoproteínas mediante resonancia magnética nuclear, aporta valor añadido en la identificación de pacientes con riesgo lipídico. Esta revisión presenta una actualización de la situación del riesgo lipídico y muestra las características de un nuevo método para la caracterización de las lipoproteínas basada en espectroscopia de RMN de difusión 2D.