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.

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.

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.

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.

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.

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.

The gut microbiota-related metabolite phenylacetylglutamine associates with increased risk of incident coronary artery disease.

OBJECTIVE: The gut microbiota is increasingly being implicated in cardiovascular health. Metabolites produced by bacteria have been suggested to be mediators in the bacterial action on cardiovascular health. We aimed to identify gut microbiota-related plasma metabolites and test whether these metabolites associate with future risk of coronary artery disease (CAD). METHODS: Nontargeted metabolomics was performed using liquid chromatography-mass spectrometry in order to measure 1446 metabolite features in the Malmö Offspring Study (MOS) (N = 776). The gut microbiota was characterized using 16S rRNA sequencing. Gut bacteria-related metabolites were measured in two independent prospective cohorts, the Malmö Diet and Cancer - Cardiovascular Cohort (MDC-CC) (N = 3361) and the Malmö Preventive Project (MPP) (N = 880), in order to investigate the associations between gut bacteria-related metabolites and risk of CAD. RESULTS: In MOS, 33 metabolite features were significantly (P < 4.8e-7) correlated with at least one operational taxonomic unit. Phenylacetylglutamine (PAG) was associated with an increased risk of future CAD, using inverse variance weighted meta-analysis of age and sex-adjusted logistic regression models in MDC-CC and MPP. PAG remained significantly associated with CAD (OR = 1.17, 95% CI = 1.06-1.29, P = 1.9e-3) after adjustments for cardiovascular risk factors. CONCLUSION: The levels of 33 plasma metabolites were correlated with the gut microbiota. Out of these, PAG was associated with an increased risk of future CAD independently of other cardiovascular risk factors. Our results highlight a link between the gut microbiota and CAD risk and should encourage further studies testing if modification of PAG levels inhibits development of CAD.

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.

Plasma Lipidome and Prediction of Type 2 Diabetes in the Population-Based Malmö Diet and Cancer Cohort.

OBJECTIVE: Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle. RESEARCH DESIGN AND METHODS: At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence (lipid-PCDM), and assessed its association with T2DM incidence using Cox regression and lifestyle factors using general linear models. RESULTS: A T2DM-predictive lipid-PCDM derived from the discovery set was independently associated with T2DM incidence in the replication set, with hazard ratio (HR) among subjects in the fifth versus first quintile of lipid-PCDM of 3.7 (95% CI 2.2-6.5). In comparison, the HR of T2DM among obese versus normal weight subjects was 1.8 (95% CI 1.2-2.6). Clinical lipids did not improve T2DM risk prediction, but adding the lipid-PCDM to all conventional T2DM risk factors increased the area under the receiver operating characteristics curve by 3%. The lipid-PCDM was also associated with a dietary risk score for T2DM incidence and lower level of physical activity. CONCLUSIONS: A lifestyle-related lipidomic profile strongly predicts T2DM development beyond current risk factors. Further studies are warranted to test if lifestyle interventions modifying this lipidomic profile can prevent T2DM.

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.

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.

Dimethylguanidino Valerate: A Lifestyle-Related Metabolite Associated With Future Coronary Artery Disease and Cardiovascular Mortality.

Background Identification of lifestyle modifiable metabolic pathways related to cardiometabolic disease risk is essential for improvement of primary prevention in susceptible individuals. It was recently shown that plasma dimethylguanidino valerate (DMGV) levels are associated with incident type 2 diabetes mellitus. Our aims were to investigate whether plasma DMGV is related to risk of future coronary artery disease and with cardiovascular mortality and to replicate the association with type 2 diabetes mellitus and pinpoint candidate lifestyle interventions susceptible to modulate DMGV levels. Methods and Results Plasma DMGV levels were measured using liquid chromatography-mass spectrometry in a total of 5768 participants from the MDC (Malmö Diet and Cancer Study-Cardiovascular Cohort), MPP (Malmö Preventive Project), and MOS (Malmö Offspring Study). Dietary intake assessment was performed in the MOS. Baseline levels of DMGV associated with incident coronary artery disease in both the MDC (hazard ratio=1.29; CI=1.16-1.43; P<0.001) and MPP (odds ratio=1.25; CI=1.08-1.44; P=2.4e-3). In the MDC, DMGV was associated with cardiovascular mortality and incident coronary artery disease, independently of traditional risk factors. Furthermore, the association between DMGV and incident type 2 diabetes mellitus was replicated in both the MDC (hazard ratio=1.83; CI=1.63-2.05; P<0.001) and MPP (odds ratio=1.65; CI=1.38-1.98; P<0.001). Intake of sugar-sweetened beverages was associated with increased levels of DMGV, whereas intake of vegetables and level of physical activity was associated with lower DMGV. Conclusions We discovered novel independent associations between plasma DMGV and incident coronary artery disease and cardiovascular mortality, while replicating the previously reported association with incident type 2 diabetes mellitus. Additionally, strong associations with sugar-sweetened beverages, vegetable intake, and physical activity suggest the potential to modify DMGV levels using lifestyle interventions.

Purine Metabolites and Carnitine Biosynthesis Intermediates Are Biomarkers for Incident Type 2 Diabetes.

CONTEXT: Metabolomics has the potential to generate biomarkers that can facilitate understanding relevant pathways in the pathophysiology of type 2 diabetes (T2DM). METHODS: Nontargeted metabolomics was performed, via liquid chromatography-mass spectrometry, in a discovery case-cohort study from the Malmö Preventive Project (MPP), which consisted of 698 metabolically healthy participants, of whom 202 developed T2DM within a follow-up time of 6.3 years. Metabolites that were significantly associated with T2DM were replicated in the population-based Malmö Diet and Cancer-Cardiovascular Cohort (MDC-CC) (N = 3423), of whom 402 participants developed T2DM within a follow-up time of 18.2 years. RESULTS: Using nontargeted metabolomics, we observed alterations in nine metabolite classes to be related to incident T2DM, including 11 identified metabolites. N2,N2-dimethylguanosine (DMGU) (OR = 1.94; P = 4.9e-10; 95% CI, 1.57 to 2.39) was the metabolite most strongly associated with an increased risk, and beta-carotene (OR = 0.60; P = 1.8e-4; 95% CI, 0.45 to 0.78) was the metabolite most strongly associated with a decreased risk. Identified T2DM-associated metabolites were replicated in MDC-CC. Four metabolites were significantly associated with incident T2DM in both the MPP and the replication cohort MDC-CC, after adjustments for traditional diabetes risk factors. These included associations between three metabolites, DMGU, 7-methylguanine (7MG), and 3-hydroxytrimethyllysine (HTML), and incident T2DM. CONCLUSIONS: We used nontargeted metabolomics in two Swedish prospective cohorts comprising >4000 study participants and identified independent, replicable associations between three metabolites, DMGU, 7MG, and HTML, and future risk of T2DM. These findings warrant additional studies to investigate a potential functional connection between these metabolites and the onset of T2DM.

N1-methylnicotinamide is a signalling molecule produced in skeletal muscle coordinating energy metabolism.

Obesity is a major health problem, and although caloric restriction and exercise are successful strategies to lose adipose tissue in obese individuals, a simultaneous decrease in skeletal muscle mass, negatively effects metabolism and muscle function. To deeper understand molecular events occurring in muscle during weight-loss, we measured the expressional change in human skeletal muscle following a combination of severe caloric restriction and exercise over 4 days in 15 Swedish men. Key metabolic genes were regulated after the intervention, indicating a shift from carbohydrate to fat metabolism. Nicotinamide N-methyltransferase (NNMT) was the most consistently upregulated gene following the energy-deficit exercise. Circulating levels of N1-methylnicotinamide (MNA), the product of NNMT activity, were doubled after the intervention. The fasting-fed state was an important determinant of plasma MNA levels, peaking at ~18 h of fasting and being lowest ~3 h after a meal. In culture, MNA was secreted by isolated human myotubes and stimulated lipolysis directly, with no effect on glucagon or insulin secretion. We propose that MNA is a novel myokine that enhances the utilization of energy stores in response to low muscle energy availability. Future research should focus on applying MNA as a biomarker to identify individuals with metabolic disturbances at an early stage.

Dimethylguanidino valeric acid is a marker of liver fat and predicts diabetes.

Unbiased, "nontargeted" metabolite profiling techniques hold considerable promise for biomarker and pathway discovery, in spite of the lack of successful applications to human disease. By integrating nontargeted metabolomics, genetics, and detailed human phenotyping, we identified dimethylguanidino valeric acid (DMGV) as an independent biomarker of CT-defined nonalcoholic fatty liver disease (NAFLD) in the offspring cohort of the Framingham Heart Study (FHS) participants. We verified the relationship between DMGV and early hepatic pathology. Specifically, plasma DMGV levels were correlated with biopsy-proven nonalcoholic steatohepatitis (NASH) in a hospital cohort of individuals undergoing gastric bypass surgery, and DMGV levels fell in parallel with improvements in post-procedure cardiometabolic parameters. Further, baseline DMGV levels independently predicted future diabetes up to 12 years before disease onset in 3 distinct human cohorts. Finally, we provide all metabolite peak data consisting of known and unidentified peaks, genetics, and key metabolic parameters as a publicly available resource for investigations in cardiometabolic diseases.

Identification of Shared and Unique Serum Lipid Profiles in Diabetes Mellitus and Myocardial Infarction.

BACKGROUND: Diabetes mellitus (DM) and cardiovascular disease are associated with dyslipidemia, but the detailed lipid molecular pattern in both diseases remains unknown. METHODS AND RESULTS: We used shotgun mass spectrometry to determine serum levels of 255 molecular lipids in 316 controls, 171 DM, and 99 myocardial infarction (MI) events from a cohort derived from the Malmö Diet and Cancer study. Orthogonal projections to latent structures analyses were conducted between the lipids and clinical parameters describing DM or MI. Fatty acid desaturases (FADS) and elongation of very long chain fatty acid protein 5 (ELOVL5) activities were estimated by calculating product to precursor ratios of polyunsaturated fatty acids in complex lipids. FADS genotypes encoding these desaturases were then tested for association with lipid levels and ratios. Differences in the levels of lipids belonging to the phosphatidylcholine and triacylglyceride (TAG) classes contributed the most to separating DM from controls. TAGs also played a dominating role in discriminating MI from controls. Levels of C18:2 fatty acids in complex lipids were lower both in DM and MI versus controls (DM, P=0.004; MI, P=6.0E-06) at least due to an acceleration in the metabolic flux from C18:2 to C20:4 (eg, increased estimated ELOVL5: DM, P=0.02; MI, P=0.04, and combined elongase-desaturase activities: DM, P=3.0E-06; MI, P=2.0E-06). Minor allele carriers of FADS genotypes were associated with increased levels of C18:2 (P≤0.007) and lower desaturase activity (P≤0.002). CONCLUSIONS: We demonstrate a possible relationship between decreased levels of C18:2 in complex lipids and DM or MI. We thereby highlight the importance of molecular lipids in the pathogenesis of both diseases.

Green tea powder and Lactobacillus plantarum affect gut microbiota, lipid metabolism and inflammation in high-fat fed C57BL/6J mice.

BACKGROUND: Type 2 diabetes is associated with obesity, ectopic lipid accumulation and low-grade inflammation. A dysfunctional gut microbiota has been suggested to participate in the pathogenesis of the disease. Green tea is rich in polyphenols and has previously been shown to exert beneficial metabolic effects. Lactobacillus plantarum has the ability to metabolize phenolic acids. The health promoting effect of whole green tea powder as a prebiotic compound has not been thoroughly investigated previously. METHODS: C57BL/6J mice were fed a high-fat diet with or without a supplement of 4% green tea powder (GT), and offered drinking water supplemented with Lactobacillus plantarum DSM 15313 (Lp) or the combination of both (Lp + GT) for 22 weeks. Parameters related to obesity, glucose tolerance, lipid metabolism, hepatic steatosis and inflammation were examined. Small intestinal tissue and caecal content were collected for bacterial analysis. RESULTS: Mice in the Lp + GT group had significantly more Lactobacillus and higher diversity of bacteria in the intestine compared to both mice in the control and the GT group. Green tea strongly reduced the body fat content and hepatic triacylglycerol and cholesterol accumulation. The reduction was negatively correlated to the amount of Akkermansia and/or the total amount of bacteria in the small intestine. Markers of inflammation were reduced in the Lp + GT group compared to control. PLS analysis of correlations between the microbiota and the metabolic variables of the individual mice showed that relatively few components of the microbiota had high impact on the correlation model. CONCLUSIONS: Green tea powder in combination with a single strain of Lactobacillus plantarum was able to promote growth of Lactobacillus in the intestine and to attenuate high fat diet-induced inflammation. In addition, a component of the microbiota, Akkermansia, correlated negatively with several metabolic parameters known to be risk factors for the development of type 2 diabetes.

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.

Efficient strategies for preimplantation genetic diagnosis of spinal muscular atrophy.

OBJECTIVE: To develop and apply efficient multiplex preimplantation genetic diagnosis (PGD) protocols for spinal muscular atrophy (SMA). DESIGN: Two multiplex PGD protocols were developed allowing the detection of the common homozygous deletion of the telomeric spinal muscular atrophy gene (SMN1), together with two microsatellites located on each side of SMN1. SETTING: The molecular genetics laboratory of the university hospital in Montpellier. PATIENT(S): A couple who had already given birth to a child affected with SMA. INTERVENTION(S): In vitro fertilization using intracytoplasmic sperm injection (ICSI) and blastomere biopsy. MAIN OUTCOME MEASURE(S): Improvement of PGD for SMA. RESULT(S): Two different multiplex protocols were set up on 81 (multiplex A) and 64 single cells (multiplex B) from normal controls, affected patients, and individuals with homozygous SMN2 deletion. In one PGD cycle that used one of these protocols, two embryos were transferred, which resulted in the birth of a healthy baby. CONCLUSION(S): Analysis of microsatellite markers in addition to the SMN1 deletion allows the detection of contamination, the study of ploidy of the biopsied blastomeres, and the performance of an indirect genetic diagnosis, thereby increasing the reliability of the results. This PGD assay may be applied to all families with the common deletion of SMN1 and also to couples in whom one of the partners carries a small intragenic mutation in SMN1, identified in about 6% of affected individuals who do not lack both copies of SMN1.

Competitive adsorption of water soluble plasma proteins from egg yolk at the oil/water interface.

Water soluble plasma proteins were fractionated from hen's egg yolk, and the molecular weight and pI of the most abundant protein species were characterized with gel electrophoresis. The proteins were identified by mass spectrometry. The protein fraction was used to produce oil-in-water emulsions, both at various protein concentrations and at various pH values, and the surface load was determined through serum depletion. The competitive adsorption was studied through the determination of nonadsorbing species with gel electrophoresis. The results show that it was possible to form an oil-in-water emulsion for which droplet size and maximum surface load depended on the protein concentration and pH. Serum albumin and YGP40 adsorbed selectively at the oil/water interface throughout the pH range investigated, and for albumin the selectivity increased close to its pI. It is suggested that this selective adsorption is due to long hydrophobic stretches in the polypeptide chain, which are present in the selectively adsorbing species but absent in less adsorbing species.