Short-term variability of the human serum metabolome depending on nutritional and metabolic health status

Untargeted metabolomics reveals the effects of pre-analytic storage on serum metabolite profiles from healthy cats

Untargeted metabolomics investigations have characterized metabolic disturbances associated with various diseases in domestic cats. However, the pre-analytic stability of serum metabolites in the species is unknown. Our objective was to compare serum metabolomes from healthy cats stored at -20°C for up to 12 months to samples stored at -80°C. Serum samples from 8 adult, healthy cats were stored at -20°C for 6 months, -20°C for 12 months, or -80°C for 12 months. Untargeted liquid chromatography-mass spectrometry was used to generate serum metabolite profiles containing relative abundances of 733 serum metabolites that were compared among storage conditions. Unsupervised analysis with principal component analysis and hierarchical clustering of Euclidian distances revealed separation of samples from individual cats regardless of storage condition. Linear mixed-effects models identified 75 metabolites that differed significantly among storage conditions. Intraclass correlation analysis (ICC) classified most serum metabolites as having excellent (ICC ≥ 0.9; 33%) or moderate (ICC 0.75-0.89; 33%) stability, whereas 13% had poor stability (ICC < 0.5). Biochemicals that varied significantly among storage conditions and classified with poor stability included glutathione metabolites, amino acids, gamma-glutamyl amino acids, and polyunsaturated fatty acids. The benzoate; glycine, serine and threonine; tryptophan; chemical (xenobiotics); acetylated peptide, and primary bile acid sub pathways were enriched among highly stable metabolites, whereas the monohydroxy fatty acid, polyunsaturated fatty, and monoacylglycerol sub-pathways were enriched among unstable metabolites. Our findings suggest that serum metabolome profiles are representative of the cat of origin, regardless of storage condition. However, changes in specific serum metabolites, especially glutathione, gamma-glutamyl amino acid, and fatty acid metabolites were consistent with increased sample oxidation during storage at -20°C compared with -80°C. By investigating the pre-analytic stability of serum metabolites, this investigation provides valuable insights that could aid other investigators in planning and interpreting studies of serum metabolomes in cats.

Metformin and feeding increase levels of the appetite-suppressing metabolite Lac-Phe in humans

Metformin, a widely used first-line treatment for type 2 diabetes (T2D), is known to reduce blood glucose levels and suppress appetite. Here we report a significant elevation of the appetite-suppressing metabolite N-lactoyl phenylalanine (Lac-Phe) in the blood of individuals treated with metformin across seven observational and interventional studies. Furthermore, Lac-Phe levels were found to rise in response to acute metformin administration and post-prandially in patients with T2D or in metabolically healthy volunteers.

Plasma metabolomics supports non-fasted sampling for metabolic profiling across a spectrum of glucose tolerance in the Nile rat model for type 2 diabetes

Type 2 diabetes is a challenge in modern healthcare, and animal models are necessary to identify underlying mechanisms. The Nile rat (Arvicanthis niloticus) develops diet-induced diabetes rapidly on a conventional rodent chow diet without genetic or chemical manipulation. Unlike common laboratory models, the outbred Nile rat model is diurnal and has a wide range of overt diabetes onset and diabetes progression patterns in both sexes, better mimicking the heterogeneous diabetic phenotype in humans. While fasted blood glucose has historically been used to monitor diabetic progression, postprandial blood glucose is more sensitive to the initial stages of diabetes. However, there is a long-held assumption that ad libitum feeding in rodent models leads to increased variance, thus masking diabetes-related metabolic changes in the plasma. Here we compared repeatability within triplicates of non-fasted or fasted plasma samples and assessed metabolic changes relevant to glucose tolerance in fasted and non-fasted plasma of 8-10-week-old male Nile rats. We used liquid chromatography-mass spectrometry lipidomics and polar metabolomics to measure relative metabolite abundances in the plasma samples. We found that, compared to fasted metabolites, non-fasted plasma metabolites are not only more strongly associated with glucose tolerance on the basis of unsupervised clustering and elastic net regression model, but also have a lower replicate variance. Between the two sampling groups, we detected 66 non-fasted metabolites and 32 fasted metabolites that were associated with glucose tolerance using a combined approach with multivariable elastic net and individual metabolite linear models. Further, to test if metabolite replicate variance is affected by age and sex, we measured non-fasted replicate variance in a cohort of mature 30-week-old male and female Nile rats. Our results support using non-fasted plasma metabolomics to study glucose tolerance in Nile rats across the progression of diabetes.

Effect of providing citrus pulp-integrated diet on fecal microbiota and serum and fecal metabolome shifts in crossbred pigs

The study aimed to assess the impact of dehydrated citrus pulp (DCP) on growth performance, fecal characteristics, fecal bacterial composition (based on 16S rRNA analysis), and fecal and serum metabolomic profiles in crossbred pigs. 80 finishing pigs Duroc × (Landrace × Large White) were fed either a control diet (C) or a diet with 240 g/kg DCP (T) for six weeks. Including DCP in diets tended to decrease feed intake, increased (p < 0.05) the concentrations of acetic and heptanoic acids and decreased (p < 0.05) fecal butyric and branched-chain fatty acid concentrations in feces. Animals fed DCP exhibited a lower abundance of the genera Clostridium and Romboutsia, while Lachnospira significantly increased. Orthogonal partial least squares discriminant analysis plotted a clear separation of fecal and serum metabolites between groups. The main discriminant fecal metabolites were associated with bacterial protein fermentation and were downregulated in T-fed pigs. In serum, DCP supplementation upregulated metabolites related to protein and fatty acids metabolism. In conclusion, the addition of DCP as an environmentally friendly source of nutrients in pig diets, resulted in modifications of fecal bacterial composition, fermentation patterns, and overall pig metabolism, suggesting improvements in protein metabolism and gut health.

Dietary biomarkers-an update on their validity and applicability in epidemiological studies

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

Metabolic Differences in Diabetic Kidney Disease Patients with Normoalbuminuria versus Moderately Increased Albuminuria

Key Points

The pathophysiological mechanisms of diabetic kidney disease (DKD) with normal (nonalbuminuric DKD) versus moderately increased albuminuria (A-DKD) are not well-understood. Fatty acid biosynthesis and oxydation, gluconeogenesis, TCA cycle, and glucose-alanine cycle were more disturbed in patients with A-DKD compared with those with nonalbuminuric DKD with identical eGFR. DKD patients with and without microalbuminuria could represent different clinical phenotypes.

Background

The pathophysiological mechanisms of diabetic kidney disease (DKD) with normal versus moderately increased albuminuria (nonalbuminuric DKD [NA-DKD] and A-DKD) are currently not well-understood and could have implications for diagnosis and treatment.

Methods

Fourteen patients with NA-DKD with urine albumin–creatinine ratio <3 mg/mmol, 26 patients with A-DKD with albumin–creatinine ratio 3–29 mg/mmol, and 60 age- and sex-matched healthy controls were randomly chosen from a population-based cohort study (Nord-Trøndelag Health Study-3, Norway). Seventy-four organic acids, 21 amino acids, 21 biogenic acids, 40 acylcarnitines, 14 sphingomyelins, and 88 phosphatidylcholines were quantified in urine. One hundred forty-six patients with diabetes from the US-based Chronic Renal Insufficiency Cohort study were used to verify main findings.

Results

Patients with NA-DKD and A-DKD had similar age, kidney function, diabetes treatment, and other traditional risk factors. Still, partial least-squares discriminant analysis showed strong metabolite-based separation (R2, 0.82; Q2, 0.52), with patients with NA-DKD having a metabolic profile positioned between the profiles of healthy controls and patients with A-DKD. Seventy-five metabolites contributed significantly to separation between NA-DKD and A-DKD (variable importance in projection scores ≥1.0) with propionylcarnitine (C3), phosphatidylcholine C38:4, medium-chained (C8) fatty acid octenedioic acid, and lactic acid as the top metabolites (variable importance in projection scores, 2.7–2.2). Compared with patients with NA-DKD, those with A-DKD had higher levels of short-chained acylcarnitines, higher long-chained fatty acid levels with more double bounds, higher branched-chain amino acid levels, and lower TCA cycle intermediates. The main findings were similar by random forest analysis and in the Chronic Renal Insufficiency Cohort study. Formal enrichment analysis indicated that fatty acid biosynthesis and oxydation, gluconeogenesis, TCA cycle, and glucose-alanine cycle were more disturbed in patients with A-DKD compared with those with NA-DKD with identical eGFR. We also found indications of a Warburg-like effect in patients with A-DKD (i.e. , metabolism of glucose to lactate despite adequate oxygen).

Conclusion

DKD patients with normoalbuminuria differ substantially in their metabolic disturbances compared with patients with moderately increase albuminuria and could represent different clinical phenotypes.

A randomized trial involving a multifunctional diet reveals systematic lipid remodeling and improvements in cardiometabolic risk factors in middle aged to aged adults

Background

A multifunctional diet (MFD) combining foods and ingredients with proven functional properties, such as fatty fish and fiber-rich foods, among others, was developed and shown to markedly reduce cardiometabolic risk-associated factors.

Objective

Here, we aim at examining metabolic physiological changes associated with these improvements.

Methods

Adult overweight individuals without other risk factors were enrolled in an 8-week randomized controlled intervention following a parallel design, with one group (n = 23) following MFD and one group (n = 24) adhering to a control diet (CD) that followed the caloric formula (E%) advised by the Nordic Nutritional Recommendations. Plasma metabolites and lipids were profiled by gas chromatography and ultrahigh performance liquid chromatography/mass spectrometry.

Results

Weight loss was similar between groups. The MFD and CD resulted in altered levels of 137 and 78 metabolites, respectively. Out of these, 83 were uniquely altered by the MFD and only 24 by the CD. The MFD-elicited alterations in lipid levels depended on carbon number and degree of unsaturation.

Conclusion

An MFD elicits weight loss-independent systematic lipid remodeling, promoting increased circulating levels of long and highly unsaturated lipids.

Clinical trial registration

https://clinicaltrials.gov/ct2/show/NCT02148653?term=NCT02148653&draw=2&rank=1, NCT02148653.

Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS

In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.

NMR-Metabolomics Reveals a Metabolic Shift after Surgical Resection of Non-Small Cell Lung Cancer

Background: Lung cancer can be detected by measuring the patient’s plasma metabolomic profile using nuclear magnetic resonance (NMR) spectroscopy. This NMR-based plasma metabolomic profile is patient-specific and represents a snapshot of the patient’s metabolite concentrations. The onset of non-small cell lung cancer (NSCLC) causes a change in the metabolite profile. However, the level of metabolic changes after complete NSCLC removal is currently unknown. Patients and methods: Fasted pre- and postoperative plasma samples of 74 patients diagnosed with resectable stage I-IIIA NSCLC were analyzed using 1H-NMR spectroscopy. NMR spectra (s = 222) representing two preoperative and one postoperative plasma metabolite profile at three months after surgical resection were obtained for all patients. In total, 228 predictors, i.e., 228 variables representing plasma metabolite concentrations, were extracted from each NMR spectrum. Two types of supervised multivariate discriminant analyses were used to train classifiers presenting a strong differentiation between the pre- and postoperative plasma metabolite profiles. The validation of these trained classification models was obtained by using an independent dataset. Results: A trained multivariate discriminant classification model shows a strong differentiation between the pre- and postoperative NSCLC profiles with a specificity of 96% (95% CI [86–100]) and a sensitivity of 92% (95% CI [81–98]). Validation of this model results in an excellent predictive accuracy of 90% (95% CI [77–97]) and an AUC value of 0.97 (95% CI [0.93–1]). The validation of a second trained model using an additional preoperative control sample dataset confirms the separation of the pre- and postoperative profiles with a predictive accuracy of 93% (95% CI [82–99]) and an AUC value of 0.97 (95% CI [0.93–1]). Metabolite analysis reveals significantly increased lactate, cysteine, asparagine and decreased acetate levels in the postoperative plasma metabolite profile. Conclusions: The results of this paper demonstrate that surgical removal of NSCLC generates a detectable metabolic shift in blood plasma. The observed metabolic shift indicates that the NSCLC metabolite profile is determined by the tumor’s presence rather than donor-specific features. Furthermore, the ability to detect the metabolic difference before and after surgical tumor resection strongly supports the prospect that NMR-generated metabolite profiles via blood samples advance towards early detection of NSCLC recurrence.

Metabolomics of early myocardial ischemia

INTRODUCTION

Diagnosing myocardial infarction is difficult during the initial phase. As, acute myocardial ischemia is associated with changes in metabolic pathways, metabolomics may provide ways of identifying early stages of ischemia. We investigated the changes in metabolites after induced ischemia in humans using nuclear magnetic resonance spectroscopy (NMR).

METHODS

We included patients undergoing elective coronary angiography showing normal coronary arteries. These were randomized into 4 groups and underwent coronary artery occlusion for 0, 30, 60 or 90 s. Blood was collected over the next 3 h and analyzed using NMR. We used 2-way ANOVA of time from baseline- and treatment group to find metabolites that changed significantly following the intervention and principal component analysis (PCA) to investigate changes between the 90 s ischemia- and control groups at 15 and 60 min after intervention.

RESULTS

We included 34 patients. The most pronounced changes were observed in the lipid metabolism where 38 of 112 lipoprotein parameters (34%) showed a significant difference between the patients exposed to ischemia and the control group. There was a decrease in total plasma triglycerides over the first hour followed by a normalization. The principal component analysis showed a effects of the treatment after just 15 min. These effects were dominated by changes in high-density lipoprotein. An increase in lactic acid levels was detected surprisingly late, 1-2 h after the ischemia.

CONCLUSION

We investigated the earliest changes in metabolites of patients undergoing brief myocardial ischemia and found that ischemia led to changes throughout the lipid metabolism as early as 15 min post-intervention.

Single and Joined Behaviour of Circulating Biomarkers and Metabolic Parameters in High-Fit and Low-Fit Healthy Females

Biomarkers are important in the assessment of health and disease, but are poorly studied in still healthy individuals with a (potential) different risk for metabolic disease. This study investigated, first, how single biomarkers and metabolic parameters, functional biomarker and metabolic parameter categories, and total biomarker and metabolic parameter profiles behave in young healthy female adults of different aerobic fitness and, second, how these biomarkers and metabolic parameters are affected by recent exercise in these healthy individuals. A total of 102 biomarkers and metabolic parameters were analysed in serum or plasma samples from 30 young, healthy, female adults divided into a high-fit (V̇O2peak ≥ 47 mL/kg/min, N = 15) and a low-fit (V̇O2peak ≤ 37 mL/kg/min, N = 15) group, at baseline and overnight after a single bout of exercise (60 min, 70% V̇O2peak). Our results show that total biomarker and metabolic parameter profiles were similar between high-fit and low-fit females. Recent exercise significantly affected several single biomarkers and metabolic parameters, mostly related to inflammation and lipid metabolism. Furthermore, functional biomarker and metabolic parameter categories corresponded to biomarker and metabolic parameter clusters generated via hierarchical clustering models. In conclusion, this study provides insight into the single and joined behavior of circulating biomarkers and metabolic parameters in healthy females, and identified functional biomarker and metabolic parameter categories that may be used for the characterisation of human health physiology.

Type 2 diabetes is associated with increased circulating levels of 3-hydroxydecanoate activating GPR84 and neutrophil migration

Obesity and diabetes are associated with inflammation and altered plasma levels of several metabolites, which may be involved in disease progression. Some metabolites can activate G protein-coupled receptors (GPCRs) expressed on immune cells where they can modulate metabolic inflammation. Here, we find that 3-hydroxydecanoate is enriched in the circulation of obese individuals with type 2 diabetes (T2D) compared with nondiabetic controls. Administration of 3-hydroxydecanoate to mice promotes immune cell recruitment to adipose tissue, which was associated with adipose inflammation and increased fasting insulin levels. Furthermore, we demonstrate that 3-hydroxydecanoate stimulates migration of primary human and mouse neutrophils, but not monocytes, through GPR84 and Gα_i signaling in vitro. Our findings indicate that 3-hydroxydecanoate is a T2D-associated metabolite that increases inflammatory responses and may contribute to the chronic inflammation observed in diabetes.

Reproducibility of the Blood and Urine Exposome: A Systematic Literature Review and Meta-Analysis

Endogenous and exogenous metabolite concentrations may be susceptible to variation over time. This variability can lead to misclassification of exposure levels and in turn to biased results. To assess the reproducibility of metabolites, the intraclass correlation coefficient (ICC) is computed. A literature search in three databases from 2000 to May 2021 was conducted to identify studies reporting ICCs for blood and urine metabolites. This review includes 192 studies, of which 31 studies are included in the meta-analyses. The ICCs of 359 single metabolites are reported, and the ICCs of 10 metabolites were meta-analyzed. The reproducibility of the single metabolites ranges from poor to excellent and is highly compound-dependent. The reproducibility of bisphenol A (BPA), mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-2-ethylhexyl phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-benzyl phthalate (MBzP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), methylparaben, and propylparaben is poor to moderate (ICC median: 0.32; range: 0.15-0.49), and for 25-hydroxyvitamin D [25(OH)D], it is excellent (ICC: 0.95; 95% CI, 0.90-0.99). Pharmacokinetics, mainly the half-life of elimination and exposure patterns, can explain reproducibility. This review describes the reproducibility of the blood and urine exposome, provides a vast dataset of ICC estimates, and hence constitutes a valuable resource for future reproducibility and clinical epidemiologic studies.

Variability of human fasted venous plasma metabolomic profiles with tourniquet induced hemostasis

Venous plasma metabolomics is a potent and highly sensitive tool for identifying and measuring metabolites of interest in human health and disease. Accurate and reproducible insights from such metabolomic studies require extreme care in removing preanalytical confounders; one of these is the duration of tourniquet application when drawing the venous blood sample. Using an untargeted plasma metabolomics approach, we evaluated the effect of varying durations of tourniquet application on the variability in plasma metabolite concentrations in five healthy female subjects. Tourniquet application introduced appreciable variation in the metabolite abundances: 73% of the identified metabolites had higher temporal variation compared to interindividual variation [Intra-Class Correlation (ICC) > 0.50]. As such, we recommend tourniquet application for minimal duration and to wait for 5 min with the needle in situ after removing the tourniquet, to reduce hemostasis-induced variability and false flags in interpretation.

Metabolomics analysis for diagnosis and biomarker discovery of transthyretin amyloidosis

Untargeted metabolomics is a well-established technique and a powerful tool to find potential plasma biomarkers for early diagnosing hereditary transthyretin amyloidosis. Hereditary transthyretin amyloidosis (ATTRv) is a disabling and fatal disease with different clinical features such as polyneuropathy, cardiomyopathy, different gastrointestinal symptoms and renal failure. Plasma specimens collected from 27 patients with ATTRv (ATTRV30M), 26 asymptomatic TTRV30M carriers and 26 control individuals were subjected to gas chromatography (GC)- and liquid chromatography (LC)-mass spectrometry (MS)-based metabolomics analysis. Partial least squares discriminant and univariate analysis was used to analyse the data. The models constructed by Partial least squares-discriminant analysis (PLS-DA) could clearly discriminate ATTRV30M patients from controls and asymptomatic TTRV30M carriers. In total, 24 plasma metabolites (VIP > 1.0 and p < .05) were significantly altered in ATTRV30M patient group (6 increased and 18 decreased). Eleven of these distinguished the ATTRV30M group from both controls and TTRV30M carriers. Plasma metabolomics analysis revealed marked changes in several pathways in patients with ATTRV30M amyloidosis. Statistical analysis identified a panel of biomarkers that could effectively separate controls/TTRV30M carriers from ATTRV30M patients. These biomarkers can potentially be used to diagnose patients at an early stage of the disease.

Biological and Clinical Factors Contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19

The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. The present large study sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831) that tested positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on plasma from acutely ill patients collected while in the emergency department, at admission, or during hospitalization. Lipidomics analyses were also performed on COVID-19-positive or -negative subjects with the lowest and highest body mass index (n = 60/group). Significant changes in amino acid and fatty acid/acylcarnitine metabolism emerged as highly relevant markers of disease severity, progression, and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half, yielding ~78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for mechanistic follow-up studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses.

Whole-body metabolic fate of branched-chain amino acids

Oxidation of branched-chain amino acids (BCAAs) is tightly regulated in mammals. We review here the distribution and regulation of whole-body BCAA oxidation. Phosphorylation and dephosphorylation of the rate-limiting enzyme, branched-chain α-ketoacid dehydrogenase complex directly regulates BCAA oxidation, and various other indirect mechanisms of regulation also exist. Most tissues throughout the body are capable of BCAA oxidation, and the flux of oxidative BCAA disposal in each tissue is influenced by three key factors: 1. tissue-specific preference for BCAA oxidation relative to other fuels, 2. the overall oxidative activity of mitochondria within a tissue, and 3. total tissue mass. Perturbations in BCAA oxidation have been implicated in many disease contexts, underscoring the importance of BCAA homeostasis in overall health.

Intergenerational Metabolomic Analysis of Mothers with a History of Gestational Diabetes Mellitus and Their Offspring

Shared metabolomic patterns at delivery have been suggested to underlie the mother-to-child transmission of adverse metabolic health. This study aimed to investigate whether mothers with gestational diabetes mellitus (GDM) and their offspring show similar metabolomic patterns several years postpartum. Targeted metabolomics (including 137 metabolites) was performed in plasma samples obtained during an oral glucose tolerance test from 48 mothers with GDM and their offspring at a cross-sectional study visit 8 years after delivery. Partial Pearson's correlations between the area under the curve (AUC) of maternal and offspring metabolites were calculated, yielding so-called Gaussian graphical models. Spearman's correlations were applied to investigate correlations of body mass index (BMI), Matsuda insulin sensitivity index (ISI-M), dietary intake, and physical activity between generations, and correlations of metabolite AUCs with lifestyle variables. This study revealed that BMI, ISI-M, and the AUC of six metabolites (carnitine, taurine, proline, SM(-OH) C14:1, creatinine, and PC ae C34:3) were significantly correlated between mothers and offspring several years postpartum. Intergenerational metabolite correlations were independent of shared BMI, ISI-M, age, sex, and all other metabolites. Furthermore, creatinine was correlated with physical activity in mothers. This study suggests that there is long-term metabolic programming in the offspring of mothers with GDM and informs us about targets that could be addressed by future intervention studies.