Differential analysis of lipoprotein and glycoprotein profiles in bacterial infections and COVID-19 using proton nuclear magnetic resonance and machine learning.

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.

Lipidomic and metabolomic changes in community-acquired and COVID-19 pneumonia.

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.

Investigating the Link between Intermediate Metabolism, Sexual Dimorphism, and Cardiac Autonomic Dysfunction in Patients with Type 1 Diabetes.

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(ß) = 0.972 (95% CI 0.952; 0.003)], age [Exp(ß) = 1.031 (95% CI 1.010; 1.053)], A1c [Exp(ß) = 1.361 (95% CI 1.058; 1.752)], and microangiopathy [Exp(ß) = 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.

The athero-contour: A novel tool for global and rapid assessment of atherogenic parameters. A use case in saroglitazar treatment of MAFLD patients.

BACKGROUND AND AIMS: Comprehensive assessment of pharmacotherapy effects on atherogenic parameters (AP) that influence the risk of cardiovascular disease (CVD) is challenging due to interactions among a large number of parameters that modulate CVD risk. METHODS: We developed an illustrative tool, athero-contour (AC), which incorporates weighted key lipid, lipo- and glycoprotein parameters, to readily illustrate their overall changes following pharmacotherapy. We demonstrate the applicability of AC to assess changes in AP in response to saroglitazar treatment in patients with metabolic associated fatty liver disease (MAFLD) in the EVIDENCES IV study. RESULTS: The baseline AC of saroglitazar and placebo groups was worse than the mean of the general population. After 16-week treatment, AC improved significantly in the saroglitazar group due to alterations in very low-density lipoprotein, triglyceride, and glycoproteins. CONCLUSION: Using AC, we could readily and globally evaluate and visualize changes in AP. AC improved in patients with MAFLD following saroglitazar therapy.

Remodeling of skeletal muscle myosin metabolic states in hibernating mammals.

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.

Many animals use hibernation as a tactic to survive harsh winters. During this dormant, inactive state, animals reduce or limit body processes, such as heart rate and body temperature, to minimise their energy use. To conserve energy during hibernation, animals can use different approaches. For example, garden dormice undergo periodic states of extremely low core temperatures (down to 4­8^oC); whereas Eurasian brown bears see milder temperature drops (down to 23­25^oC). An important organ that changes during hibernation is skeletal muscle. Skeletal muscle typically uses large amounts of energy, making up around 50% of body mass. To survive, hibernating animals must change how their skeletal muscle uses energy. Traditionally, active myosin ­ a protein found in muscles that helps muscles to contract ­ was thought to be responsible for most of the energy use by skeletal muscle. But, more recently, resting myosin has also been found to use energy when muscles are relaxed. Lewis et al. studied myosin and skeletal muscle energy use changes during hibernation and whether they could impact the metabolism of hibernating animals. Lewis et al. assessed myosin changes in muscle samples from squirrels, dormice and bears during hibernation and during activity. Experiments showed changes in resting myosin in squirrels and dormice (whose temperature drops to 4­8^oC during hibernation) but not in bears. Further analysis revealed that cooling samples from non-hibernating muscle to 4­8^oC increased energy use in resting myosin, thereby generating heat. However, no increase in energy use was found after cooling hibernating muscle samples to 4­8^oC. This suggest that resting myosin generates heat at cool temperatures ­ a mechanism that is switched off in hibernating animals to allow them to cool their body temperature. These findings reveal key insights into how animals conserve energy during hibernation. In addition, the results show that myosin regulates energy use in skeletal muscles, which indicates myosin may be a potential drug target in metabolic diseases, such as obesity.

Increasing the complexity of lipoprotein characterization for cardiovascular risk in type 2 diabetes.

The burden of cardiovascular disease is particularly high among individuals with diabetes, even when LDL cholesterol is normal or within the therapeutic target. Despite this, cholesterol accumulates in their arteries, in part, due to persistent atherogenic dyslipidaemia characterized by elevated triglycerides, remnant cholesterol, smaller LDL particles and reduced HDL cholesterol. The causal link between dyslipidaemia and atherosclerosis in T2DM is complex, and our contention is that a deeper understanding of lipoprotein composition and functionality, the vehicle that delivers cholesterol to the artery, will provide insight for improving our understanding of the hidden cardiovascular risk of diabetes. This narrative review covers three levels of complexity in lipoprotein characterization: 1-the information provided by routine clinical biochemistry, 2-advanced nuclear magnetic resonance (NMR)-based lipoprotein profiling and 3-the identification of minor components or physical properties of lipoproteins that can help explain arterial accumulation in individuals with normal LDLc levels, which is typically the case in individuals with T2DM. This document highlights the importance of incorporating these three layers of lipoprotein-related information into population-based studies on ASCVD in T2DM. Such an attempt should inevitably run in parallel with biotechnological solutions that allow large-scale determination of these sets of methodologically diverse parameters.

Cardiovascular risk assessment in inflammatory bowel disease with metabolic dysfunction-associated steatotic liver disease.

BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) has been reported to increase the risk of early atherosclerosis even in young patients. Moreover, metabolic dysfunction-associated steatotic liver disease (MASLD), which has been linked to IBD, is a well-recognized but underdiagnosis entity related to cardiovascular risk. We analyze the impact of MASLD in IBD patients' cardiovascular risk through both advanced lipoprotein profile sorted by nuclear magnetic resonance spectroscopy, and carotid artery intima-media thickness (CIMT). METHODS: Cross-sectional cohort study which involves 941 IBD adult outpatients. Of them, 50 patients with IBD who met criteria for MASLD and 50 with IBD without MASLD, matched by sex and age were included. Alterations in CIMT were evaluated considering abnormal measures above the 75th percentile adjusted for sex and age. Specific advanced lipoprotein profile was also carried out. RESULTS: Most of the patients had an abnormal CIMT (58%). MASLD (OR=5.05, CI 95%=1.71-14.92) and female sex (OR=3.32, CI 95%=1.03-10) were significantly associated with CIMT alterations. Dense LDL particles (with high cholesterol composition in general cohort (OR=3.62, 95% CI=1.07-12.19) and high triglycerides density in young subgroup (OR=6.25, 95% CI=1.04-50) but not total LDL cholesterol were associated with CIMT alterations. CONCLUSIONS: MASLD and female sex are associated with early atherosclerosis in IBD patients. Dense LDL particle in combination with vascular imaging findings should be evaluated as non-invasive tools in the management of cardiovascular risk in IBD patients.

Lipidomics of triglyceride-rich lipoproteins derived from hyperlipidemic patients on inflammation.

BACKGROUND AND AIM: Triglyceride-rich lipoproteins (TRLs) can have an important role in atherosclerosis development due to their size and ability to penetrate the endothelium. While high plasma triglyceride (TG) levels and chronic inflammation are relevant in metabolic diseases, it remains unclear whether TGs are atherogenic or which TRL-TG-derived metabolites are responsible for inflammation. Here, we aimed to study the lipidome modifications of TRL particles enriched in TG in patients with hyperlipidemia and their associations with a proinflammatory status both in vivo and in vitro. METHODS: Using proton nuclear magnetic resonance (1 H-NMR), we analysed the plasma levels of glycoprotein acetyls and the TRL lipidomic profile of 307 patients with dyslipidemia. THP-1-derived macrophages were used as an in vitro model to explore the molecular inflammatory effects mediated by TRL. RESULTS: In vivo, higher TRL-TG levels were associated with higher circulating levels of NMR-measured glycoproteins (Glyc-A, Glyc-B and Glyc-F; p < .001). Lipidomic analysis showed that TRL-TG enrichment led to decreased cholesterol and phospholipid content (p < .01), an increase in omega-9, and a decrease in saturated fatty acids (p < .001). THP-1 macrophages exposed to increasing TRL particle concentrations augmented the secretion of IL-1ß and TNF-α, which varied based on particle composition. Particles with higher cholesterol and phospholipid contents exerted higher cytokine secretion. The activation of MAPK, Akt/NFκB, and caspase-1 was concurrent with this proinflammatory response. CONCLUSIONS: High TRL-TG levels are associated with a higher systemic inflammatory status and increased particle concentrations. In vitro, higher particle numbers increase proinflammatory cytokine secretion, with cholesterol and phospholipid-rich TRL being more proinflammatory.

Remodelling of Skeletal Muscle Myosin Metabolic States in Hibernating Mammals.

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.

Association between exposure to air pollution and blood lipids in the general population of Spain.

BACKGROUND AND AIMS: We aimed to assess the associations of exposure to air pollutants and standard and advanced lipoprotein measures, in a nationwide sample representative of the adult population of Spain. METHODS: We included 4647 adults (>18 years), participants in the national, cross-sectional, population-based di@bet.es study, conducted in 2008-2010. Standard lipid measurements were analysed on an Architect C8000 Analyzer (Abbott Laboratories SA). Lipoprotein analysis was made by an advanced 1 H-NMR lipoprotein test (Liposcale®). Participants were assigned air pollution concentrations for particulate matter <10 µm (PM10 ), <2.5 µm (PM2.5 ) and nitrogen dioxide (NO2 ), corresponding to the health examination year, obtained by modelling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). RESULTS: In multivariate linear regression models, each IQR increase in PM10 , PM2.5 and NO2 was associated with 3.3%, 3.3% and 3% lower levels of HDL-c and 1.3%, 1.4% and 1.1% lower HDL particle (HDL-p) concentrations (p < .001 for all associations). In multivariate logistic regression, there was a significant association between PM10 , PM2.5 and NO2 concentrations and the odds of presenting low HDL-c (<40 mg/dL), low HDL-p (

Traffic Density Exposure, Oxidative Stress Biomarkers and Plasma Metabolomics in a Population-Based Sample: The Hortega Study.

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.

Serum branch-chained amino acids are increased in type 2 diabetes and associated with atherosclerotic cardiovascular disease.

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 < 0.05). Likewise, these three BCAAS were associated with diabetes even after adjusting for covariates (p < 0.05). During the follow-up period of 10 years, 29 of the 185 patients with diabetes at baseline (15.68%) developed ASCVD. After adjusting for clinical covariates, baseline levels of valine and alanine were associated with the development of ASCVD (p < 0.05). CONCLUSION: Overall, our results indicated that plasma levels of LMWMs measured by 1H-NMR could be potential biomarkers associated with T2D. Moreover, alanine and valine can help in the early detection of the cardiovascular risk associated with this metabolic disease.

Similarity network fusion to identify phenotypes of small-for-gestational-age fetuses.

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.

Gradual Increase in Inflammation-Linked Glycoproteins and a Proatherogenic Lipoprotein Profile in the Early Stages of Psychosis as Characterized by 1H NMR Blood Analysis.

Minimally invasive prognostic markers of inflammation and dyslipidemia in individuals with a risk of psychosis, also called "at-risk mental state" (ARMS), or in the first episode of psychosis (FEP) are of utmost clinical importance to prevent cardiovascular disorders. We analyzed the plasma concentration of inflammation-linked glycoproteins (Glycs) and lipoprotein subclasses by proton nuclear magnetic resonance (1H NMR) in a single acquisition. Study participants were healthy controls (HCs, N = 67) and patients with ARMS (N = 58), FEP (N = 110), or early psychosis diagnosis with ≥2 episodes (critical period (CP), N = 53). Clinical biomarkers such as high-sensitivity C-reactive protein, interleukin 6, fibrinogen, insulin, and lipoproteins were also measured. Although all participants had normal lipoprotein profiles and no inflammation according to conventional biomarkers, a gradual increase in the Glyc 1H NMR levels was observed from HCs to CP patients; this increase was statistically significant for GlycA (CP vs HC). In parallel, a progressive and significant proatherogenic 1H NMR lipoprotein profile was also identified across stages of psychosis (ARMS and CP vs HC). These findings highlight the potential of using 1H NMR Glyc and lipoprotein profiling to identify blood changes in individuals with ARMS or FEP and pave the way for applications using this technology to monitor metabolic and cardiovascular risks in clinical psychiatry.

NMR-based metabolomic profiling identifies inflammation and muscle-related metabolites as predictors of incident type 2 diabetes mellitus beyond glucose: The Di@bet.es study.

AIMS: The aim of this study was to combine nuclear magnetic resonance-based metabolomics and machine learning to find a glucose-independent molecular signature associated with future type 2 diabetes mellitus development in a subgroup of individuals from the Di@bet.es study. METHODS: The study group included 145 individuals developing type 2 diabetes mellitus during the 8-year follow-up, 145 individuals matched by age, sex and BMI who did not develop diabetes during the follow-up but had equal glucose concentrations to those who did and 145 controls matched by age and sex. A metabolomic analysis of serum was performed to obtain the lipoprotein and glycoprotein profiles and 15 low molecular weight metabolites. Several machine learning-based models were trained. RESULTS: Logistic regression performed the best classification between individuals developing type 2 diabetes during the follow-up and glucose-matched individuals. The area under the curve was 0.628, and its 95% confidence interval was 0.510-0.746. Glycoprotein-related variables, creatinine, creatine, small HDL particles and the Johnson-Neyman intervals of the interaction of Glyc A and Glyc B were statistically significant. CONCLUSIONS: The model highlighted a relevant contribution of inflammation (glycosylation pattern and HDL) and muscle (creatinine and creatine) in the development of type 2 diabetes as independent factors of hyperglycemia.

A case of hypocholesterolemia under study. / Un caso de hipocolesterolemia a estudio.

Primary hypocholesterolemia (or hypobetalipoproteinemia) is a rare disorder of lipoprotein metabolism that may be due to a polygenic predisposition or a monogenic disease. Among these, it is possible to differentiate between symptomatic and asymptomatic forms, in which, in the absence of secondary causes, the initial clinical suspicion is plasma ApoB levels below the 5th percentile of the distribution by age and sex. Here we describe the differential diagnosis of a case of asymptomatic hypocholesterolemia. We studied proband's clinical data, the lipid profile of the proband and her relatives and the clinical data of the family relevant to carry out the differential diagnosis. We performed a genetic study as the diagnostic test. The information obtained from the differential diagnosis suggested a heterozygous hypobetalipoproteinemia due to PCSK9 loss-of-function variants. The diagnostic test revealed, in the proband, the presence of a heterozygous PCSK9 frame-shift variant of a maternal origin. Plasma levels of LDL cholesterol and PCSK9 of the patient and her relatives were compatible with the segregation of the variant revealed. In conclusion, the diagnostic test performed confirmed the suspected diagnosis of the proband as asymptomatic familial hypobetalipoproteinemia due to a loss-of-function variant in the PCSK9 gene.

PCSK9 Inhibitors Have Apolipoprotein C-III-Related Anti-Inflammatory Activity, Assessed by 1H-NMR Glycoprotein Profile in Subjects at High or very High Cardiovascular Risk.

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.

Multifaceted Analysis of Cerebrospinal Fluid and Serum from Progressive Multiple Sclerosis Patients: Potential Role of Vitamin C and Metal Ion Imbalance in the Divergence of Primary Progressive Multiple Sclerosis and Secondary Progressive Multiple Sclerosis.

The progressive forms of multiple sclerosis (MS) primary progressive MS (PPMS) and secondary progressive MS (SPMS) are clinically distinguished by the rate at which symptoms worsen. Little is however known about the pathological mechanisms underlying the differential rate of accumulation of pathological changes. In this study, 1H NMR spectroscopy was used to measure low-molecular-weight metabolites in paired cerebrospinal fluid (CSF) and serum of PPMS, SPMS, and control patients, as well as to determine lipoproteins and glycoproteins in serum samples. Additionally, neurodegenerative and inflammatory markers, neurofilament light (NFL) and chitinase-3-like protein 1 (CHI3L1), and the concentration of seven metal elements, Mg, Mn, Cu, Fe, Pb, Zn, and Ca, were also determined in both CSF and serum. The results indicate that the pathological changes associated with progressive MS are mainly localized in the central nervous system (CNS). More so, PPMS and SPMS patients with comparable disability status are pathologically similar in relation to neurodegeneration, neuroinflammation, and some metabolites that distinguish them from controls. However, the rapid progression of PPMS from the onset may be driven by a combination of neurotoxicity induced by heavy metals coupled with diminished CNS antioxidative capacity associated with differential intrathecal ascorbate retention and imbalance of Mg and Cu.

Metabolomic patterns, redox-related genes and metals, and bone fragility endpoints in the Hortega Study.

BACKGROUND: The potential joint influence of metabolites on bone fragility has been rarely evaluated. We assessed the association of plasma metabolic patterns with bone fragility endpoints (primarily, incident osteoporosis-related bone fractures, and, secondarily, bone mineral density BMD) in the Hortega Study participants. Redox balance plays a key role in bone metabolism. We also assessed differential associations in participant subgroups by redox-related metal exposure levels and candidate genetic variants. MATERIAL AND METHODS: In 467 participants older than 50 years from the Hortega Study, a representative sample from a region in Spain, we estimated metabolic principal components (mPC) for 54 plasma metabolites from NMR-spectrometry. Metals biomarkers were measured in plasma by AAS and in urine by HPLC-ICPMS. Redox-related SNPs (N = 341) were measured by oligo-ligation assay. RESULTS: The prospective association with incident bone fractures was inverse for mPC1 (non-essential and essential amino acids, including branched-chain, and bacterial co-metabolites, including isobutyrate, trimethylamines and phenylpropionate, versus fatty acids and VLDL) and mPC4 (HDL), but positive for mPC2 (essential amino acids, including aromatic, and bacterial co-metabolites, including isopropanol and methanol). Findings from BMD models were consistent. Participants with decreased selenium and increased antimony, arsenic and, suggestively, cadmium exposures showed higher mPC2-associated bone fractures risk. Genetic variants annotated to 19 genes, with the strongest evidence for NCF4, NOX4 and XDH, showed differential metabolic-related bone fractures risk. CONCLUSIONS: Metabolic patterns reflecting amino acids, microbiota co-metabolism and lipid metabolism were associated with bone fragility endpoints. Carriers of redox-related variants may benefit from metabolic interventions to prevent the consequences of bone fragility depending on their antimony, arsenic, selenium, and, possibly, cadmium, exposure levels.

Different profiles of lipoprotein particles associate various degrees of cardiac involvement in adolescents with morbid obesity.

Introduction: Dyslipidemia 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. Methods: Prospective 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. Results: The 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. Conclusions: ALT 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.