Both Humoral and Cellular Immune Responses to SARS-CoV-2 Are Essential to Prevent Infection: a Prospective Study in a Working Vaccinated Population from Southern France.

COVID-19 vaccines have significantly decreased the number of severe cases of the disease, but the virus circulation remains important, and questions about the need of new vaccination campaigns remain unanswered. The individual's protection against SARS-CoV-2 infection is most commonly measured by the level and the neutralizing capacity of antibodies produced against SARS-CoV-2. T cell response is a major contributor in viral infection, and several studies have shown that cellular T cell response is crucial in fighting off SARS-CoV-2 infection. Actually, no threshold of protective immune response against SARS-CoV2 infection has been identified. To better understand SARS-CoV-2-mediated immunity, we assessed both B cell (measuring anti-Spike IgG titer and neutralization capacity) and T cell (measuring IFNγ release assay after specific SARS-CoV2 stimulation) responses to SARS-CoV-2 vaccination with or without virus encounter in a cohort of 367 working volunteers. Vaccinated individuals who had previously been infected had a stronger and more lasting immunity in comparison to vaccinated individuals naive to infection whose immunity started to decline 3 months after vaccination. IFNγ release ≥ 0.285 IU/mL and anti-Spike IgG antibodies ≥ 244 BAU/mL were associated with a sufficient immune response following vaccination preventing future infections. Individuals with comorbidities had a lower chance of reaching the protective thresholds of T cell and B cell responses as identified in multivariate analysis. A combined B cell and T cell analysis of immune responses to determine protective thresholds after SARS-CoV-2 vaccination will allow us to identify individuals in need of a booster vaccine dose, particularly in comorbid subjects.

A healthy dietary metabolic signature is associated with a lower risk for type 2 diabetes and coronary artery disease.

BACKGROUND: The global burden of cardiovascular disease and type 2 diabetes could be decreased by improving dietary factors, but identification of groups suitable for interventional approaches can be difficult. Reporting of dietary intake is prone to errors, and measuring of metabolites has shown promise in determining habitual dietary intake. Our aim is to create a metabolic signature that is associated with healthy eating and test if it associates with type 2 diabetes and coronary artery disease risk. METHODS: Using plasma metabolite data consisting of 111 metabolites, partial least square (PLS) regression was used to identify a metabolic signature associated with a health conscious food pattern in the Malmö Offspring Study (MOS, n = 1538). The metabolic signature's association with dietary intake was validated in the Malmö Diet and Cancer study (MDC, n = 2521). The associations between the diet-associated metabolic signature and incident type 2 diabetes and coronary artery disease (CAD) were tested using Cox regression in MDC and logistic regression in Malmö Preventive Project (MPP, n = 1083). Modelling was conducted unadjusted (model 1), adjusted for potential confounders (model 2) and additionally for potential mediators (model 3). RESULTS: The metabolic signature was associated with lower risk for type 2 diabetes in both MDC (hazard ratio: 0.58, 95% CI 0.52-0.66, per 1 SD increment of the metabolic signature) and MPP (odds ratio: 0.54, 95% CI 0.44-0.65 per 1 SD increment of the metabolic signature) in model 2. The results were attenuated but remained significant in model 3 in both MDC (hazard ratio 0.73, 95% CI 0.63-0.83) and MPP (odds ratio 0.70, 95% CI 0.55-0.88). The diet-associated metabolic signature was also inversely associated with lower risk of CAD in both MDC and MPP in model 1, but the association was non-significant in model 3. CONCLUSIONS: In this proof-of-concept study, we identified a healthy diet-associated metabolic signature, which was inversely associated with future risk for type 2 diabetes and coronary artery disease in two different cohorts. The association with diabetes was independent of traditional risk factors and might illustrate an effect of health conscious dietary intake on cardiometabolic health.

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort.

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays.

The inverse association between a fish consumption biomarker and gingival inflammation and periodontitis: A population-based study.

AIM: The metabolite 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid (CMPF) is a fatty fish-intake biomarker. We investigated the association between plasma levels of CMPF in relation to gingival inflammation and periodontitis case definition, as well as the extent and severity variables. MATERIALS AND METHODS: The Malmö Offspring Study is a population-based study, and the Malmö Offspring Dental Study (MODS) is its dental arm, including periodontal charting. Plasma CMPF was measured using liquid chromatography-mass spectrometry and studied in relation to periodontal diagnosis and parameters using multivariable linear or logistic regression modelling adjusting for age, sex, education, body mass index, fasting glucose, and smoking. RESULTS: Metabolite data were available for 922 MODS participants. Higher CMPF levels were associated with less gingival inflammation (ß = -2.12, p = .002) and lower odds of severe periodontitis (odds ratio [OR] = 0.74, 95% confidence interval [CI]: 0.56 to 0.98). Higher CMPF levels were also associated with more teeth (ß = 0.19, p = .001), lower number of periodontal pockets (≥4 mm) (ß = -1.07, p = .007), and lower odds of having two or more periodontal pockets of ≥6 mm (OR = 0.80, 95% CI: 0.65 to 0.98) in fully adjusted models. CONCLUSIONS: CMPF, a validated biomarker of fatty fish consumption, is associated with less periodontal inflammation and periodontitis. Residual confounding cannot be ruled out, and future studies are warranted.

Magnitude of rise in proneurotensin is related to amount of triglyceride appearance in blood after standardized oral intake of both saturated and unsaturated fat.

BACKGROUND: In rodents, neurotensin contributes to high fat diet induced obesity by facilitation of intestinal fat absorption. The effect of oral lipid load on plasma proneurotensin and relationship with plasma triglycerides in humans is unknown. AIM: To investigate the acute effects of an oral lipid load on proneurotensin and plasma triglycerides and their interrelationships in healthy individuals. SETTING/ METHODS: Twenty-two healthy subjects were given 150 mL of full milk cream (54 g fat) and 59 mL of pure olive oil (54 g fat) in the fasted state at two different occasions separated by at least 1 week in random order. Venous blood was drawn at fasted before 0 h (h) and at 1 h, 2 h and 4 h after ingestion. Post-ingested values of proneurotensin and plasma triglycerides were compared with fasting levels and post ingestion Area Under the Curve (AUC) of proneurotensin was correlated with that of plasma triglycerides. RESULTS: An immediate rise of plasma proneurotensin and plasma triglycerides were observed after ingestion of cream with maximum increase at 2 h for proneurotensin [mean (95% confidence interval)] of 22 (12-31) pmol/L (P < 0.001) and at 3 h for triglycerides of 0.60 (0.43-0.78) mmol/L (P < 0.001). Similarly, plasma proneurotensin and plasma triglycerides increased after ingestion of olive oil with maximum increase of proneurotensin at 3 h of 62 (46-78) pmol/L (P < 0.001) and plasma triglycerides at 3 h of 0.32 (0.18-0.45) mmol/L (P < 0.001). The post lipid load AUC for proneurotensin correlated significantly with the AUC for plasma triglycerides both after cream (r = 0.49, P = 0.021) and olive oil (r = 0.55, P = 0.008), respectively. CONCLUSION: Proneurotensin increases after an oral lipid load of both cream and olive oil and the rise of post-ingestion plasma triglycerides is significantly related to the rise of post-ingestion proneurotensin.

Optimization of Rituximab Therapy in Adult Patients With PLA2R1-Associated Membranous Nephropathy With Artificial Intelligence.

Introduction: Rituximab is a first-line treatment for membranous nephropathy. Nephrotic syndrome limits rituximab exposure due to urinary drug loss. Rituximab underdosing (serum level <2 µg/ml at month-3) is a risk factor for treatment failure. We developed a machine learning algorithm to predict the risk of underdosing based on patients' characteristics at rituximab infusion. We investigated the relationship between the predicted risk of underdosing and the cumulative dose of rituximab required to achieve remission. Methods: Rituximab concentrations were measured at month-3 in 92 sera from adult patients with primary membranous nephropathy, split into a training (75%) and a testing set (25%). A forward-backward machine-learning procedure determined the best combination of variables to predict rituximab underdosing in the training data set, which was tested in the test set. The performances were evaluated for accuracy, sensitivity, and specificity in 10-fold cross-validation training and test sets. Results: The best variables combination to predict rituximab underdosing included age, gender, body surface area (BSA), anti-phospholipase A2 receptor type 1 (anti-PLA2R1) antibody titer on day-0, serum albumin on day-0 and day-15, and serum creatinine on day-0 and day-15. The accuracy, sensitivity, and specificity were respectively 79.4%, 78.7%, and 81.0% (training data set), and 79.2%, 84.6% and 72.7% (testing data set). In both sets, the algorithm performed significantly better than chance (P < 0.05). Patients with an initial high probability of underdosing experienced a longer time to remission with higher rituximab cumulative doses required to achieved remission. Conclusion: This algorithm could allow for early intensification of rituximab regimen in patients at high estimated risk of underdosing to increase the likelihood of remission.

Impact of temperature dependent sampling procedures in proteomics and peptidomics--a characterization of the liver and pancreas post mortem degradome.

Little is known about the nature of post mortem degradation of proteins and peptides on a global level, the so-called degradome. This is especially true for nonneural tissues. Degradome properties in relation to sampling procedures on different tissues are of great importance for the studies of, for instance, post translational modifications and/or the establishment of clinical biobanks. Here, snap freezing of fresh (<2 min post mortem time) mouse liver and pancreas tissue is compared with rapid heat stabilization with regard to effects on the proteome (using two-dimensional differential in-gel electrophoresis) and peptidome (using label free liquid chromatography). We report several proteins and peptides that exhibit heightened degradation sensitivity, for instance superoxide dismutase in liver, and peptidyl-prolyl cis-trans isomerase and insulin C-peptides in pancreas. Tissue sampling based on snap freezing produces a greater amount of degradation products and lower levels of endogenous peptides than rapid heat stabilization. We also demonstrate that solely snap freezing related degradation can be attenuated by subsequent heat stabilization. We conclude that tissue sampling involving a rapid heat stabilization step is preferable to freezing with regard to proteomic and peptidomic sample quality.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Metabolome-Defined Obesity and the Risk of Future Type 2 Diabetes and Mortality.

OBJECTIVE: Obesity is a key risk factor for type 2 diabetes; however, up to 20% of patients are normal weight. Our aim was to identify metabolite patterns reproducibly predictive of BMI and subsequently to test whether lean individuals who carry an obese metabolome are at hidden high risk of obesity-related diseases, such as type 2 diabetes. RESEARCH DESIGN AND METHODS: Levels of 108 metabolites were measured in plasma samples of 7,663 individuals from two Swedish and one Italian population-based cohort. Ridge regression was used to predict BMI using the metabolites. Individuals with a predicted BMI either >5 kg/m2 higher (overestimated) or lower (underestimated) than their actual BMI were characterized as outliers and further investigated for obesity-related risk factors and future risk of type 2 diabetes and mortality. RESULTS: The metabolome could predict BMI in all cohorts (r2 = 0.48, 0.26, and 0.19). The overestimated group had a BMI similar to individuals correctly predicted as normal weight, had a similar waist circumference, were not more likely to change weight over time, but had a two times higher risk of future type 2 diabetes and an 80% increased risk of all-cause mortality. These associations remained after adjustments for obesity-related risk factors and lifestyle parameters. CONCLUSIONS: We found that lean individuals with an obesity-related metabolome have an increased risk for type 2 diabetes and all-cause mortality compared with lean individuals with a healthy metabolome. Metabolomics may be used to identify hidden high-risk individuals to initiate lifestyle and pharmacological interventions.

Low baseline IFN-γ response could predict hospitalization in COVID-19 patients.

The SARS-CoV-2 infection has spread rapidly around the world causing millions of deaths. Several treatments can reduce mortality and hospitalization. However, their efficacy depends on the choice of the molecule and the precise timing of its administration to ensure viral clearance and avoid a deleterious inflammatory response. Here, we investigated IFN-γ, assessed by a functional immunoassay, as a predictive biomarker for the risk of hospitalization at an early stage of infection or within one month prior to infection. Individuals with IFN-γ levels below 15 IU/mL were 6.57-times more likely to be hospitalized than those with higher values (p<0.001). As confirmed by multivariable analysis, low IFN-γ levels, age >65 years, and no vaccination were independently associated with hospitalization. In addition, we found a significant inverse correlation between low IFN-γ response and high level of IL-6 in plasma (Spearman's rho=-0.38, p=0.003). Early analysis of the IFN-γ response in a contact or recently infected subject with SARS-CoV-2 could predict hospitalization and thus help the clinician to choose the appropriate treatment avoiding severe forms of infection and hospitalization.

Air pollution exposure induces a decrease in type II interferon response: A paired cohort study.

BACKGROUND: While air pollution is a major issue due to its harmful effects on human health, few studies focus on its impact on the immune system and vulnerability to viral infections. The lockdown declared following the COVID-19 pandemic represents a unique opportunity to study the large-scale impact of variations in air pollutants in real life. We hypothesized that variations in air pollutants modify Th1 response represented by interferon (IFN) γ production. METHODS: We conducted a single center paired pilot cohort study of 58 participants, and a confirmation cohort of 320 participants in Nice (France), with for each cohort two samplings at six months intervals. We correlated the variations in the production of IFNγ after non-specific stimulation of participants' immune cells with variations in key regulated pollutants: NO2, O3, PM2.5, and PM10 and climate variables. Using linear regression, we studied the effects of variations of each pollutant on the immune response. FINDINGS: In the pilot cohort, IFNγ production significantly decreased by 25.7% post-lockdown compared to during lockdown, while NO2 increased significantly by 46.0%. After the adjustment for climate variations during the study period (sunshine and temperature), we observed a significant effect of NO2 variation on IFNγ production (P=0.03). In the confirmation cohort IFNγ decreased significantly by 47.8% and after adjustment for environmental factors and intrinsic characteristics we observed a significant effect of environmental factors: NO2, PM10, O3, climatic conditions (sunshine exposure, relative humidity) on variation in IFNγ production (P=0.005, P<0.001, P=0.001, P=0.002 and P<0.001 respectively) but not independently from the BMI at inclusion and the workplace P=0.007 and P<0.001 respectively). INTERPRETATION: We show a weakening of the antiviral cellular response in correlation with an increase of pollutants exposition. FUNDING: Agence Nationale de la Recherche, Conseil Départemental des Alpes-Maritimes and Region Sud.

A plasma lipid signature predicts incident coronary artery disease.

BACKGROUND: Dyslipidemia is a hallmark of cardiovascular disease but is characterized by crude measurements of triglycerides, HDL- and LDL cholesterol. Lipidomics enables more detailed measurements of plasma lipids, which may help improve risk stratification and understand the pathophysiology of cardiovascular disease. METHODS: Lipidomics was used to measure 184 lipids in plasma samples from the Malmö Diet and Cancer - Cardiovascular Cohort (N = 3865), taken at baseline examination. During an average follow-up time of 20.3 years, 536 participants developed coronary artery disease (CAD). Least absolute shrinkage and selection operator (LASSO) were applied to Cox proportional hazards models in order to identify plasma lipids that predict CAD. RESULTS: Eight plasma lipids improved prediction of future CAD on top of traditional cardiovascular risk factors. Principal component analysis of CAD-associated lipids revealed one principal component (PC2) that was associated with risk of future CAD (HR per SD increment =1.46, C·I = 1.35-1.48, P < 0.001). The risk increase for being in the highest quartile of PC2 (HR = 2.33, P < 0.001) was higher than being in the top quartile of systolic blood pressure. Addition of PC2 to traditional risk factors achieved an improvement (2%) in the area under the ROC-curve for CAD events occurring within 10 (P = 0.03), 15 (P = 0.003) and 20 (P = 0.001) years of follow-up respectively. CONCLUSIONS: A lipid pattern improve CAD prediction above traditional risk factors, highlighting that conventional lipid-measures insufficiently describe dyslipidemia that is present years before CAD. Identifying this hidden dyslipidemia may help motivate lifestyle and pharmacological interventions early enough to reach a substantial reduction in absolute risk.

Residual Viremia Is Linked to a Specific Immune Activation Profile in HIV-1-Infected Adults Under Efficient Antiretroviral Therapy.

Chronic immune activation persists in persons living with HIV-1 even though they are aviremic under antiretroviral therapy, and fuels comorbidities. In previous studies, we have revealed that virologic responders present distinct profiles of immune activation, and that one of these profiles is related to microbial translocation. In the present work, we tested in 140 HIV-1-infected adults under efficient treatment for a mean duration of eight years whether low-level viremia might be another cause of immune activation. We observed that the frequency of viremia between 1 and 20 HIV-1 RNA copies/mL (39.5 ± 24.7% versus 21.1 ± 22.5%, p = 0.033) and transient viremia above 20 HIV-1 RNA copies/mL (15.1 ± 16.9% versus 3.3 ± 7.2%, p = 0.005) over the 2 last years was higher in patients with one profile of immune activation, Profile E, than in the other patients. Profile E, which is different from the profile related to microbial translocation with frequent CD38+ CD8+ T cells, is characterized by a high level of CD4+ T cell (cell surface expression of CD38), monocyte (plasma concentration of soluble CD14), and endothelium (plasma concentration of soluble Endothelial Protein C Receptor) activation, whereas the other profiles presented low CD4:CD8 ratio, elevated proportions of central memory CD8+ T cells or HLA-DR+ CD4+ T cells, respectively. Our data reinforce the hypothesis that various etiological factors shape the form of the immune activation in virologic responders, resulting in specific profiles. Given the type of immune activation of Profile E, a potential causal link between low-level viremia and atherosclerosis should be investigated.

Hormone-sensitive lipase (HSL) is also a retinyl ester hydrolase: evidence from mice lacking HSL.

Here, we investigated the importance of hormone-sensitive lipase (HSL) as a retinyl ester hydrolase (REH). REH activity was measured in vitro using recombinant HSL and retinyl palmitate. The expression of retinoic acid (RA)-regulated genes and retinoid metabolites were measured in high-fat diet fed HSL-null mice using real-time quantitative PCR and triple-stage liquid chromatography/tandem mass spectrometry, respectively. Age- and gender-matched wild-type littermates were used as controls. The REH activity of rat HSL was found to be higher than that against the hitherto best known HSL substrate, i.e., diacylglycerols. REH activity in white adipose tissue (WAT) of HSL-null mice was completely blunted and accompanied by increased levels of retinyl esters and decreased levels of retinol, retinaldehyde and all-trans RA. Accordingly, genes known to be positively regulated by RA were down-regulated in HSL-null mice, including pRb and RIP140, key factors promoting differentiation into the white over the brown adipocyte lineage. Dietary RA supplementation partly restored WAT mass and the expression of RA-regulated genes in WAT of HSL-null mice. These findings demonstrate the importance of HSL as an REH of adipose tissue and suggest that HSL via this action provides RA and other retinoids for signaling events that are crucial for adipocyte differentiation and lineage commitment.

Plasma Metabolites Associate with All-Cause Mortality in Individuals with Type 2 Diabetes.

Alterations in the human metabolome occur years before clinical manifestation of type 2 diabetes (T2DM). By contrast, there is little knowledge of how metabolite alterations in individuals with diabetes relate to risk of diabetes complications and premature mortality. Metabolite profiling was performed using liquid chromatography-mass spectrometry in 743 participants with T2DM from the population-based prospective cohorts The Malmö Diet and Cancer-Cardiovascular Cohort (MDC-CC) and The Malmö Preventive Project (MPP). During follow-up, a total of 175 new-onset cases of cardiovascular disease (CVD) and 298 deaths occurred. Cox regressions were used to relate baseline levels of plasma metabolites to incident CVD and all-cause mortality. A total of 11 metabolites were significantly (false discovery rate (fdr) <0.05) associated with all-cause mortality. Acisoga, acylcarnitine C10:3, dimethylguanidino valerate, homocitrulline, N2,N2-dimethylguanosine, 1-methyladenosine and urobilin were associated with an increased risk, while hippurate, lysine, threonine and tryptophan were associated with a decreased risk. Ten out of 11 metabolites remained significantly associated after adjustments for cardiometabolic risk factors. The associations between metabolite levels and incident CVD were not as strong as for all-cause mortality, although 11 metabolites were nominally significant (p < 0.05). Further examination of the mortality-related metabolites may shed more light on the pathophysiology linking diabetes to premature mortality.

Altered Acylcarnitine Metabolism Is Associated With an Increased Risk of Atrial Fibrillation.

Background Atrial fibrillation (AF) is the most common cardiac arrhythmia, but the pathogenesis is not completely understood. The application of metabolomics could help in discovering new metabolic pathways involved in the development of the disease. Methods and Results We measured 112 baseline fasting metabolites of 3770 participants in the Malmö Diet and Cancer Study; these participants were free of prevalent AF. Incident cases of AF were ascertained through previously validated registers. The associations between baseline levels of metabolites and incident AF were investigated using Cox proportional hazard models. During 23.1 years of follow-up, 650 cases of AF were identified (incidence rate: 8.6 per 1000 person-years). In Cox regression models adjusted for AF risk factors, 7 medium- and long-chain acylcarnitines were associated with higher risk of incident AF (hazard ratio [HR] ranging from 1.09; 95% CI, 1.00-1.18 to 1.14, 95% CI, 1.05-1.24 per 1 SD increment of acylcarnitines). Furthermore, caffeine and acisoga were also associated with an increased risk (HR, 1.17; 95% CI, 1.06-1.28 and 1.08; 95% CI, 1.00-1.18, respectively), while beta carotene was associated with a lower risk (HR, 0.90; 95% CI, 0.82-0.99). Conclusions For the first time, we show associations between altered acylcarnitine metabolism and incident AF independent of traditional AF risk factors in a general population. These findings highlight metabolic alterations that precede AF diagnosis by many years and could provide insight into the pathogenesis of AF. Future studies are needed to replicate our finding in an external cohort as well as to test whether the relationship between acylcarnitines and AF is causal.

Ergothioneine is associated with reduced mortality and decreased risk of cardiovascular disease.

OBJECTIVES: We recently identified a health conscious food pattern (HCFP) associated with reduced risk of cardiometabolic disease. However, the molecular events linking the healthy food pattern to reduced risk of cardiometabolic disease are unknown. Our aim was to identify plasma metabolites associated with the HCFP and test if such metabolites predict cardiometabolic disease and mortality. METHODS: Using liquid-chromatography mass-spectrometry, 112 plasma metabolites were measured in 3236 participants without cardiovascular disease (CVD) and diabetes mellitus from the population-based Malmö Diet and Cancer study. Metabolites associated with the HCFP were identified using multivariable adjusted linear regressions followed by Bonferroni correction. The healthy dietary biomarkers were subsequently related to risk of cardiometabolic disease and mortality during long-term follow-up with multivariable adjusted Cox proportional hazards models. RESULTS: During a median follow-up time of 21.4 years, 603 participants developed CVD, 362 developed diabetes mellitus and 843 participants died. Five healthy dietary biomarkers were associated with the HCFP at baseline (p<0.0004) and four predicted at least one of the studied end points (p<0.05). Ergothioneine was the metabolite most strongly connected to the HCFP and was associated with a lower risk of coronary disease (HR per 1 SD increment of ergothioneine, HR=0.85, p=0.01), cardiovascular mortality (HR=0.79, p=0.002) and overall mortality (HR=0.86, p=4e-5). CONCLUSIONS: We identified that higher ergothioneine was an independent marker of lower risk of cardiometabolic disease and mortality, which potentially can be induced by a specific healthy dietary intake.

Personalized Medicine for PLA2R1-Related Membranous Nephropathy: A Multicenter Randomized Control Trial.

Background: Membranous Nephropathy (MN) is a rare autoimmune disease related to PLA2R1 antibodies in 70% of cases. One third of patients enter in spontaneous remission. PLA2R1 epitopes in MN have been characterized in four different domains of PLA2R1 and a mechanism of epitope spreading from the immunodominant CysR domain to CTLD1 and/or CTLD7 and/or CTLD8 domains has been associated with poor prognosis. Epitope spreading could predict spontaneous remission (45% in non-spreader patients vs. 0.05% in spreader patients). The comparison of different regimens of rituximab dosing showed that: (i) early remission rate depends on rituximab dosing, (ii) low dose could be enough for patients with anti-PLA2R1 activity restricted to CysR, (iii) high dose may be required for spreader patients. This study aims to evaluate the efficacy of personalized treatment in PLA2R1-related MN depending on the epitope spreading status, in comparison to the established GEMRITUX protocol. Methods: A multicenter, randomized, controlled, prospective clinical trial will be conducted in 22 French hospitals. Sixty-four consecutive patients with PLA2R1-related MN will be randomly assigned to either the control group following the GEMRITUX protocol (symptomatic treatment for 6 months, if the nephrotic syndrome (NS) persists at month-6, two 375 mg/m2 rituximab infusions at 1 week interval) or the personalized treatment group (patients with no epitope spreading at month-0 will be treated with symptomatic treatment for 6 months, if NS persists at month-6, two 375 mg/m2 rituximab infusions at 1 week interval; patients with epitope spreading at month-0 or month-6 with persistent NS will be treated immediately with two 1 g rituximab infusions at 2 week interval). The primary study outcome is the rate of clinical remission at month-12. The secondary outcomes include complete and partial remissions, immunological remissions, relapses, proteinuria, albuminuria, serum creatinine, eGFR, PLA2R1 antibody titers, severe infections, lymphocyte counts and lymphocyte phenotype, residual rituximab levels at month-3 and neutralizing anti-rituximab antibodies at month-6 and month-12 after rituximab treatment. Discussion: The results of this trial will confirm whether personalized treatment of PLA2R1-driven nephrotic MN is more efficient to induce clinical remission than the established GEMRITUX protocol, and may thus contribute to improved remission rates and reduced relapse rates. Trial registration: NCT03804359 trial number. Registered on 15th January 2019.

Circulating protein biomarkers predict incident hypertensive heart failure independently of N-terminal pro-B-type natriuretic peptide levels.

AIMS: Hypertension is the leading cause for the development of heart failure (HF). Here, we aimed to identify cardiomyocyte stretch-induced circulating biomarkers for predicting hypertension-associated HF. METHODS AND RESULTS: Circulating levels of 149 proteins were measured by proximity extension assay at baseline examination in 4742 individuals from the Malmö Diet and Cancer study. Protein levels were compared with stretch-activated gene expression changes in cultured neonatal rat ventricular myocytes (NRVMs) in response to 1-48 h of mechanical stretch. We also studied the association between protein levels and hypertension and HF incidence using respectively binary logistic and Cox regressions. Levels of 35 proteins were differentially expressed after Bonferroni correction in incident HF vs. control (P < 3.4E-4). Growth differentiation factor-15 (GDF-15), interleukin-6 (IL-6), IL-1 receptor type 1, and urokinase plasminogen activator surface receptor had corresponding mRNA levels up-regulated by stretch in NRVMs at all time points (P < 0.05). These four proteins were individually associated with increased risk of HF after age and sex adjustment [hazard ratio (HR) per standard deviation: 1.19 ≤ HR ≤ 1.49, P ≤ 4.90E-3]. GDF-15 and IL-6 were associated with HF independently of each other (1.22 ≤ HR ≤ 1.33, P ≤ 0.001). In subjects with hypertension, these associations remained significant after further adjustment for N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels (1.23 ≤ HR ≤ 1.45, P ≤ 0.001). A higher fasting value of a GDF-15, IL-6 score aggregate was associated with increased risk of hypertensive HF after adjustment for all traditional risk factors for HF and NT-proBNP (HR = 1.31, P = 2.19E-4). CONCLUSIONS: Cardiomyocyte mRNA levels of GDF-15 and IL-6 are consistently up-regulated by stretch, and their circulating protein levels predict HF in hypertensive subjects independently of NT-proBNP during long-term follow-up. Our results encourage further studies on lower blood pressure goals in hypertensive subjects with high GDF-15 and IL-6, and interventions targeted at stretch-induced cardiomyocyte expressed biomarkers.