Infants with biliary atresia exhibit an altered amino acid profile in their newborn screening.

INTRODUCTION: Biliary atresia (BA) is a rare progressive neonatal cholangiopathy with unknown pathophysiology and time of onset. Newborn Screening (NBS) in Germany is routinely performed in the first days of life to identify rare congenital diseases utilizing dried blood spot (DBS) card analyses. Infants with biliary atresia (BA) are known to have altered amino acid profiles (AAP) at the time point of diagnosis, but it is unclear whether these alterations are present at the time point of NBS. OBJECTIVES: We aimed to analyze amino acid profiles in NBS-DBS of infants with Biliary Atresia. METHODS: Original NBS-DBS cards of 41 infants who were later on diagnosed with BA were retrospectively obtained. NBS-DBS cards from healthy newborns (n = 40) served as controls. In some BA infants (n = 14) a second DBS card was obtained at time of Kasai surgery. AAP in DBS cards were analyzed by targeted metabolomics. RESULTS: DBS metabolomics in the NBS of at that time point seemingly healthy infants later diagnosed with BA revealed significantly higher levels of Methionine (14.6 ± 8.6 µmol/l), Histidine (23.5 ± 50.3 µmol/l), Threonine (123.9 ± 72.8 µmol/l) and Arginine (14.1 ± 11.8 µmol/l) compared to healthy controls (Met: 8.1 ± 2.6 µmol/l, His: 18.6 ± 10.1 µmol/l, Thr: 98.1 ± 34.3 µmol/l, Arg: 9.3 ± 6.6 µmol/l). Methionine, Arginine and Histidine showed a further increase at time point of Kasai procedure. No correlation between amino acid levels and clinical course was observed. CONCLUSION: Our data demonstrate that BA patients exhibit an altered AAP within 72 h after birth, long before the infants become symptomatic. This supports the theory of a prenatal onset of the disease and, thus, the possibility of developing a sensitive and specific NBS. Methionine might be particularly relevant due to its involvement in glutathione metabolism. Further investigation of AAP in BA may help in understanding the underlying pathophysiology.

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

AIMS/HYPOTHESIS: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes. METHODS: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively. RESULTS: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

Stool and blood metabolomics in the metabolic syndrome: a cross-sectional study.

INTRODUCTION/OBJECTIVES: Changes in the stool metabolome have been poorly studied in the metabolic syndrome (MetS). Moreover, few studies have explored the relationship of stool metabolites with circulating metabolites. Here, we investigated the associations between stool and blood metabolites, the MetS and systemic inflammation. METHODS: We analyzed data from 1,370 participants of the KORA FF4 study (Germany). Metabolites were measured by Metabolon, Inc. (untargeted) in stool, and using the AbsoluteIDQ® p180 kit (targeted) in blood. Multiple linear regression models, adjusted for dietary pattern, age, sex, physical activity, smoking status and alcohol intake, were used to estimate the associations of metabolites with the MetS, its components and high-sensitivity C-reactive protein (hsCRP) levels. Partial correlation and Multi-Omics Factor Analysis (MOFA) were used to investigate the relationship between stool and blood metabolites. RESULTS: The MetS was significantly associated with 170 stool and 82 blood metabolites. The MetS components with the highest number of associations were triglyceride levels (stool) and HDL levels (blood). Additionally, 107 and 27 MetS-associated metabolites (in stool and blood, respectively) showed significant associations with hsCRP levels. We found low partial correlation coefficients between stool and blood metabolites. MOFA did not detect shared variation across the two datasets. CONCLUSIONS: The MetS, particularly dyslipidemia, is associated with multiple stool and blood metabolites that are also associated with systemic inflammation. Further studies are necessary to validate our findings and to characterize metabolic alterations in the MetS. Although our analyses point to weak correlations between stool and blood metabolites, additional studies using integrative approaches are warranted.

Inflammation and prediction of death in type 2 diabetes. Evidence of an intertwined link with tryptophan metabolism.

OBJECTIVE: To study whether inflammation is associated with and helps predict mortality risk in patients with type 2 diabetes. To explore the intertwined link between inflammation and tryptophan metabolism on death risk. DESIGN: Two prospective cohorts: the aggregate Gargano Mortality Study (1,731 individuals; 872 all-cause deaths) as discovery sample, the Foggia Mortality Study (490 individuals; 256 deaths) as validation sample. Twenty-seven inflammatory markers were measured. Causal mediation analysis and in vitro studies were carried out to explore the link between inflammatory markers and the kynurenine-to-tryptophan ratio (KTR) in shaping mortality risk. RESULTS: Using multivariable stepwise Cox regression analysis, IL-4, IL-6, IL-8, IL-13, RANTES and IP-10, were independently associated with death. An inflammation score (I-score) comprising these six molecules is strongly associated with death in both the discovery and the validation cohorts HR (95%CI) = 2.13 (1.91-2.37) and 2.20 (1.79-2.72), respectively. The I-score improved discrimination and reclassification measures (all P<0.01) of two mortality prediction models based on clinical variables. The causal mediation analysis showed that 28% of the KTR effect on mortality was mediated by IP-10. Studies in cultured endothelial cells showed that 5-Methoxy-tryptophan, an anti-inflammatory metabolite derived from tryptophan, reduces the expression of IP-10, thus providing a functional basis for the observed causal mediation. CONCLUSIONS: Adding the I-score to clinical prediction models may help identify individuals who are at greater risk of death. Deeply addressing the intertwined relationship between low-grade inflammation and imbalanced tryptophan metabolism in shaping mortality risk may help discover new therapies targeting patients characterized by these abnormalities.

GFR decline predicts total mortality and mediates the effect of tryptophan metabolism on death risk in type 2 diabetes.

CONTEXT: The independent role of glomerular filtration rate (GFR) decline in shaping the risk of mortality in people with type 2 diabetes has only been partially addressed. OBJECTIVE: The objective of the study was twofold: i) to investigate the association between all-cause mortality and eGFR changes over time; ii) to understand whether renal dysfunction mediates the effect of tryptophan metabolism on death risk. DESIGN: Prospective study with an average follow-up of 14.8 years. SETTING: Research Hospital. PATIENTS: The aggregate Gargano Mortality Study included 962 patients with type 2 diabetes who had at least three eGFR recordings and at least 1.5 years of follow-up. INTERVENTIONS: This was an observational study, with no intervention. MAIN OUTCOME MEASURES: Rate of all-cause mortality. RESULTS: Age and sex adjusted annual incident rate of mortality was 2.75 events per 100 person-years. The median annual rate of decline of eGFR was 1.3 ml/min per 1.73 m2 per year (range -3.7; 7.8). The decline of kidney function was strongly and independently associated with the risk of death. Serum kynurenine-to-tryptophan ratio (KTR) was associated with both eGFR decline and all-cause mortality. Causal mediation analysis showed that 24.3% of the association between KTR and mortality was mediated by eGFR decline. CONCLUSIONS: In patients with type 2 diabetes, eGFR decline is independently associated with the risk of all-cause mortality and mediates a significant proportion of the association between tryptophan metabolism and death.

A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes.

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

The HuMet Repository: Watching human metabolism at work.

Metabolism oscillates between catabolic and anabolic states depending on food intake, exercise, or stresses that change a multitude of metabolic pathways simultaneously. We present the HuMet Repository for exploring dynamic metabolic responses to oral glucose/lipid loads, mixed meals, 36-h fasting, exercise, and cold stress in healthy subjects. Metabolomics data from blood, urine, and breath of 15 young, healthy men at up to 56 time points are integrated and embedded within an interactive web application, enabling researchers with and without computational expertise to search, visualize, analyze, and contextualize the dynamic metabolite profiles of 2,656 metabolites acquired on multiple platforms. With examples, we demonstrate the utility of the resource for research into the dynamics of human metabolism, highlighting differences and similarities in systemic metabolic responses across challenges and the complementarity of metabolomics platforms. The repository, providing a reference for healthy metabolite changes to six standardized physiological challenges, is freely accessible through a web portal.

Bile acid profiles and messenger RNA expression of bile acid-related genes in the liver of dairy cows with high versus normal body condition.

Bile acids (BA) play a crucial role not only in lipid digestion but also in the regulation of overall energy homeostasis, including glucose and lipid metabolism. The aim of this study was to investigate BA profiles and mRNA expression of BA-related genes in the liver of high versus normal body condition in dairy cows. We hypothesized that body condition and the transition from gestation to lactation affect hepatic BA concentrations as well as the mRNA abundance of BA-related receptors, regulatory enzymes, and transporters. Therefore, we analyzed BA in the liver as well as the mRNA abundance of BA-related synthesizing enzymes, transporters, and receptors in the liver during the transition period in cows with different body conditions around calving. In a previously established animal model, 38 German Holstein cows were divided into groups with high body condition score (HBCS; n = 19) or normal body condition score (NBCS; n = 19) based on BCS and backfat thickness (BFT). Cows were fed diets aimed at achieving the targeted differences in BCS and BFT (NBCS: BCS <3.5, BFT <1.2 cm; HBCS: BCS >3.75, BFT >1.4 cm) until they were dried off at wk 7 before parturition. Both groups were fed identical diets during the dry period and subsequent lactation. Liver biopsies were taken at wk -7, 1, 3, and 12 relative to parturition. For BA measurement, a targeted metabolomics approach with liquid chromatography electrospray ionization MS/MS was used to analyze BA in the liver. The mRNA abundance of targeted genes related to BA synthesizing enzymes, transporters, and receptors in the liver was analyzed using microfluidic quantitative PCR. In total, we could detect 14 BA in the liver: 6 primary and 8 secondary BA, with glycocholic acid (GCA) being the most abundant one. The increase of glycine-conjugated BA after parturition, in parallel to increasing serum glycine concentrations may originate from an enhanced mobilization of muscle protein to meet the high nutritional requirements in early lactating cows. Higher DMI in NBCS cows compared with HBCS cows was associated with higher liver BA concentrations such as GCA, deoxycholic acid, and cholic acid. The mRNA abundance of BA-related enzymes measured herein suggests the dominance of the alternative signaling pathway in the liver of HBCS cows. Overall, BA profiles and BA metabolism in the liver depend on both, the body condition and lactation-induced effects in periparturient dairy cows.

GALNT2 expression is associated with glucose control and serum metabolites in patients with type 2 diabetes.

AIMS: Aim of this study was to investigate in type 2 diabetes whether expression level of GALNT2, a positive modulator of insulin sensitivity, is associated with a metabolic signature. METHODS: Five different metabolite families, including acylcarnitines, aminoacids, biogenic amines, phospholipids and sphingolipids were investigated in fasting serum of 70 patients with type 2 diabetes, by targeted metabolomics. GALNT2 expression levels were measured in peripheral white blood cells by RT-PCR. The association between GALNT2 expression and serum metabolites was assessed using false discovery rate followed by stepwise selection and, finally, multivariate model including several clinical parameters as confounders. The association between GALNT2 expression and the same clinical parameters was also investigated. RESULTS: GALNT2 expression was independently correlated with HbA1c levels (P value = 0.0052), a finding that is the likely consequence of the role of GALNT2 on insulin sensitivity. GALNT2 expression was also independently associated with serum levels of the aminoacid glycine (P value = 0.014) and two biogenic amines phenylethylamine (P value = 0.0065) and taurine (P value = 0.0011). The association of GALNT2 expression with HbA1c was not mediated by these three metabolites. CONCLUSIONS: Our data indicate that in type 2 diabetes the expression of GALNT2 is associated with several serum metabolites. This association needs to be further investigated to understand in depth its role in mediating the effect of GALNT2 on insulin sensitivity, glucose control and other clinical features in people with diabetes.

The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study.

CONTEXT: The role of glucagon-like peptide-1 (GLP-1) in type 2 diabetes (T2D) and obesity is not fully understood. OBJECTIVE: We investigate the association of cardiometabolic, diet, and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. METHODS: We analyzed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1 (n = 2127) individuals at risk of diabetes; cohort 2 (n = 789) individuals with new-onset T2D. RESULTS: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin-resistant phenotype and observe a strong independent relationship with male sex, increased adiposity, and liver fat, particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycemia, higher adiposity, liver fat, male sex, and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit, and vegetables in people with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. CONCLUSION: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake, and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

Bile acid profiles and mRNA abundance of bile acid-related genes in adipose tissue of dairy cows with high versus normal body condition.

Besides their lipid-digestive role, bile acids (BA) influence overall energy homeostasis, such as glucose and lipid metabolism. We hypothesized that BA along with their receptors, regulatory enzymes, and transporters are present in subcutaneous adipose tissue (scAT). In addition, we hypothesized that their mRNA abundance varies with the body condition of dairy cows around calving. Therefore, we analyzed BA in serum and scAT as well as the mRNA abundance of BA-related enzymes, transporters, and receptors in scAT during the transition period in cows with different body conditions around calving. In a previously established animal model, 38 German Holstein cows were divided into either a high (HBCS; n = 19) or normal BCS (NBCS; n = 19) group based on their BCS and back-fat thickness (BFT). Cows were fed different diets to achieve the targeted differences in BCS and BFT (NBCS: BCS <3.5, BFT <1.2 cm; HBCS: BCS >3.75, BFT >1.4 cm) until dry-off at 7 wk antepartum. During the dry period and subsequent lactation, both groups were fed the same diets according to their energy demands. Using a targeted metabolomics approach via liquid chromatography-electrospray ionization-MS /MS, BA were analyzed in serum and scAT at wk -7, 1, 3, and 12 relative to parturition. In serum, 15 BA were observed: cholic acid (CA), chenodeoxycholic acid (CDCA), glycocholic acid (GCA), taurocholic acid (TCA), glycochenodeoxycholic acid (GCDCA), taurochenodeoxycholic acid, deoxycholic acid (DCA), lithocholic acid, glycodeoxycholic acid (GDCA), glycolithocholic acid, taurodeoxycholic acid, taurolithocholic acid, ß-muricholic acid, tauromuricholic acid (sum of α and ß), and glycoursodeoxycholic acid, whereas in scAT 7 BA were detected: CA, GCA, TCA, GCDCA, taurochenodeoxycholic acid, GDCA, and taurodeoxycholic acid. In serum and scAT samples, the primary BA CA and its conjugate GCA were predominantly detected. Increasing serum concentrations of CA, CDCA, TCA, GCA, GCDCA, DCA, and ß-muricholic acid with the onset of lactation might be related to the increasing DMI after parturition. Furthermore, serum concentrations of CA, CDCA, GCA, DCA, GCDCA, TCA, lithocholic acid, and GDCA were lower in HBCS cows compared with NBCS cows, concomitant with increased lipolysis in HBCS cows. The correlation between CA in serum and scAT may point to the transport of CA across cell membranes. Overall, the findings of the present study suggest a potential role of BA in lipid metabolism depending on the body condition of periparturient dairy cows.

Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study.

INTRODUCTION: Circulating omentin levels have been positively associated with insulin sensitivity. Although a role for adiponectin in this relationship has been suggested, underlying mechanisms remain elusive. In order to reveal the relationship between omentin and systemic metabolism, this study aimed to investigate associations of serum concentrations of omentin and metabolites. RESEARCH DESIGN AND METHODS: This study is based on 1124 participants aged 61-82 years from the population-based KORA (Cooperative Health Research in the Region of Augsburg) F4 Study, for whom both serum omentin levels and metabolite concentration profiles were available. Associations were assessed with five multivariable regression models, which were stepwise adjusted for multiple potential confounders, including age, sex, body mass index, waist-to-hip ratio, lifestyle markers (physical activity, smoking behavior and alcohol consumption), serum adiponectin levels, high-density lipoprotein cholesterol, use of lipid-lowering or anti-inflammatory medication, history of myocardial infarction and stroke, homeostasis model assessment 2 of insulin resistance, diabetes status, and use of oral glucose-lowering medication and insulin. RESULTS: Omentin levels significantly associated with multiple metabolites including amino acids, acylcarnitines, and lipids (eg, sphingomyelins and phosphatidylcholines (PCs)). Positive associations for several PCs, such as diacyl (PC aa C32:1) and alkyl-alkyl (PC ae C32:2), were significant in models 1-4, whereas those with hydroxytetradecenoylcarnitine (C14:1-OH) were significant in all five models. Omentin concentrations were negatively associated with several metabolite ratios, such as the valine-to-PC ae C32:2 and the serine-to-PC ae C32:2 ratios in most models. CONCLUSIONS: Our results suggest that omentin may influence insulin sensitivity and diabetes risk by changing systemic lipid metabolism, but further mechanistic studies investigating effects of omentin on metabolism of insulin-sensitive tissues are needed.

Association between pre-diagnostic circulating lipid metabolites and colorectal cancer risk: a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND: Altered lipid metabolism is a hallmark of cancer development. However, the role of specific lipid metabolites in colorectal cancer development is uncertain. METHODS: In a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC), we examined associations between pre-diagnostic circulating concentrations of 97 lipid metabolites (acylcarnitines, glycerophospholipids and sphingolipids) and colorectal cancer risk. Circulating lipids were measured using targeted mass spectrometry in 1591 incident colorectal cancer cases (55% women) and 1591 matched controls. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between concentrations of individual lipid metabolites and metabolite patterns with colorectal cancer risk. FINDINGS: Of the 97 assayed lipids, 24 were inversely associated (nominally p < 0.05) with colorectal cancer risk. Hydroxysphingomyelin (SM (OH)) C22:2 (ORper doubling 0.60, 95% CI 0.47-0.77) and acylakyl-phosphatidylcholine (PC ae) C34:3 (ORper doubling 0.71, 95% CI 0.59-0.87) remained associated after multiple comparisons correction. These associations were unaltered after excluding the first 5 years of follow-up after blood collection and were consistent according to sex, age at diagnosis, BMI, and colorectal subsite. Two lipid patterns, one including 26 phosphatidylcholines and all sphingolipids, and another 30 phosphatidylcholines, were weakly inversely associated with colorectal cancer. INTERPRETATION: Elevated pre-diagnostic circulating levels of SM (OH) C22:2 and PC ae C34:3 and lipid patterns including phosphatidylcholines and sphingolipids were associated with lower colorectal cancer risk. This study may provide insight into potential links between specific lipids and colorectal cancer development. Additional prospective studies are needed to validate the observed associations. FUNDING: World Cancer Research Fund (reference: 2013/1002); European Commission (FP7: BBMRI-LPC; reference: 313010).

Association of sex hormones and sex hormone-binding globulin with liver fat in men and women: an observational and Mendelian randomization study.

Background: Sex hormones and sex hormone-binding globulin (SHBG) may play a role in fatty liver development. We sought to examine the association of various endogenous sex hormones, including testosterone (T), and SHBG with liver fat using complementary observational and Mendelian randomization (MR) analyses. Methods: The observational analysis included a total of 2,239 participants (mean age 60 years; 35% postmenopausal women) from the population-based KORA study (average follow-up time: 6.5 years). We conducted linear regression analysis to investigate the sex-specific associations of sex hormones and SHBG with liver fat, estimated by fatty liver index (FLI). For MR analyses, we selected genetic variants associated with sex hormones and SHBG and extracted their associations with magnetic resonance imaging measured liver fat from the largest up to date European genome-wide associations studies. Results: In the observational analysis, T, dihydrotestosterone (DHT), progesterone and 17α-hydroxyprogesterone (17-OHP) were inversely associated with FLI in men, with beta estimates ranging from -4.23 to -2.30 [p-value <0.001 to 0.003]. Whereas in women, a positive association of free T with FLI (ß = 4.17, 95%CI: 1.35, 6.98) was observed. SHBG was inversely associated with FLI across sexes [men: -3.45 (-5.13, -1.78); women: -9.23 (-12.19, -6.28)]. No causal association was found between genetically determined sex hormones and liver fat, but higher genetically determined SHBG was associated with lower liver fat in women (ß = -0.36, 95% CI: -0.61, -0.12). Conclusion: Our results provide suggestive evidence for a causal association between SHBG and liver fat in women, implicating the protective role of SHBG against liver fat accumulation.

Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes.

INTRODUCTION: Low glomerular filtration rate (GFR) is a leading cause of reduced lifespan in type 2 diabetes. Unravelling biomarkers capable to identify high-risk patients can help tackle this burden. We investigated the association between 188 serum metabolites and kidney function in type 2 diabetes and then whether the associated metabolites improve two established clinical models for predicting GFR decline in these patients. RESEARCH DESIGN AND METHODS: Two cohorts comprising 849 individuals with type 2 diabetes (discovery and validation samples) and a follow-up study of 575 patients with estimated GFR (eGFR) decline were analyzed. RESULTS: Ten metabolites were independently associated with low eGFR in the discovery sample, with nine of them being confirmed also in the validation sample (ORs range 1.3-2.4 per 1SD, p values range 1.9×10-2-2.5×10-9). Of these, five metabolites were also associated with eGFR decline (ie, tiglylcarnitine, decadienylcarnitine, total dimethylarginine, decenoylcarnitine and kynurenine) (ß range -0.11 to -0.19, p values range 4.8×10-2 to 3.0×10-3). Indeed, tiglylcarnitine and kynurenine, which captured all the information of the other three markers, improved discrimination and reclassification (all p<0.01) of two clinical prediction models of GFR decline in people with diabetes. CONCLUSIONS: Further studies are needed to validate our findings in larger cohorts of different clinical, environmental and genetic background.

The HuMet Repository: Watching human metabolism at work.

The human metabolism constantly responds to stimuli such as food intake, fasting, exercise, and stress, triggering adaptive biochemical processes across multiple metabolic pathways. To understand the role of these processes and disruptions thereof in health and disease, detailed documentation of healthy metabolic responses is needed but still scarce on a time-resolved metabolome-wide level. Here, we present the HuMet Repository, a web-based resource for exploring dynamic metabolic responses to six physiological challenges (exercise, 36 h fasting, oral glucose and lipid loads, mixed meal, cold stress) in healthy subjects. For building this resource, we integrated existing and newly derived metabolomics data measured in blood, urine, and breath samples of 15 young healthy men at up to 56 time points during the six highly standardized challenge tests conducted over four days. The data comprise 1.1 million data points acquired on multiple platforms with temporal profiles of 2,656 metabolites from a broad range of biochemical pathways. By embedding the dataset into an interactive web application, we enable users to easily access, search, filter, analyze, and visualize the time-resolved metabolomic readouts and derived results. Users can put metabolites into their larger context by identifying metabolites with similar trajectories or by visualizing metabolites within holistic metabolic networks to pinpoint pathways of interest. In three showcases, we outline the value of the repository for gaining biological insights and generating hypotheses by analyzing the wash-out of dietary markers, the complementarity of metabolomics platforms in dynamic versus cross-sectional data, and similarities and differences in systemic metabolic responses across challenges. With its comprehensive collection of time-resolved metabolomics data, the HuMet Repository, freely accessible at https://humet.org/, is a reference for normal, healthy responses to metabolic challenges in young males. It will enable researchers with and without computational expertise, to flexibly query the data for their own research into the dynamics of human metabolism.

Maternal hyperglycemia induces alterations in hepatic amino acid, glucose and lipid metabolism of neonatal offspring: Multi-omics insights from a diabetic pig model.

OBJECTIVE: To gain mechanistic insights into adverse effects of maternal hyperglycemia on the liver of neonates, we performed a multi-omics analysis of liver tissue from piglets developed in genetically diabetic (mutant INS gene induced diabetes of youth; MIDY) or wild-type (WT) pigs. METHODS: Proteome, metabolome and lipidome profiles of liver and clinical parameters of serum samples from 3-day-old WT piglets (n = 9) born to MIDY mothers (PHG) were compared with those of WT piglets (n = 10) born to normoglycemic mothers (PNG). Furthermore, protein-protein interaction network analysis was used to reveal highly interacting proteins that participate in the same molecular mechanisms and to relate these mechanisms with human pathology. RESULTS: Hepatocytes of PHG displayed pronounced lipid droplet accumulation, although the abundances of central lipogenic enzymes such as fatty acid-synthase (FASN) were decreased. Additionally, circulating triglyceride (TG) levels were reduced as a trend. Serum levels of non-esterified free fatty acids (NEFA) were elevated in PHG, potentially stimulating hepatic gluconeogenesis. This is supported by elevated hepatic phosphoenolpyruvate carboxykinase (PCK1) and circulating alanine transaminase (ALT) levels. Even though targeted metabolomics showed strongly elevated phosphatidylcholine (PC) levels, the abundances of multiple key enzymes involved in major PC synthesis pathways - most prominently those from the Kennedy pathway - were paradoxically reduced in PHG liver. Conversely, enzymes involved in PC excretion and breakdown such as PC-specific translocase ATP-binding cassette 4 (ABCB4) and phospholipase A2 were increased in abundance. CONCLUSIONS: Our study indicates that maternal hyperglycemia without confounding obesity induces profound molecular changes in the liver of neonatal offspring. In particular, we found evidence for stimulated gluconeogenesis and hepatic lipid accumulation independent of de novo lipogenesis. Reduced levels of PC biosynthesis enzymes and increased levels of proteins involved in PC translocation or breakdown may represent counter-regulatory mechanisms to maternally elevated PC levels. Our comprehensive multi-omics dataset provides a valuable resource for future meta-analysis studies focusing on liver metabolism in newborns from diabetic mothers.

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts.

BACKGROUND: Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways. METHODS: We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed. RESULTS: We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism. CONCLUSION: Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.